Session Browser 2022

All session times are shown in Pacific Standard Time (PST).

S1. Predictive decoding of the auditory mind

Shihab Shamma

Topic areas: neural coding

Fri, 11/11 9:00AM - 10:00AM | Keynote Lecture

Abstract

Perception and action engage extensive sensory and motor interactions with predictive signals playing the major role in skill learning and cognition. I shall briefly describe ECoG recordings of such responses during speech vocalizations and discuss the role of the auditory-motor mappings in learning how to speak. These results are then generalized to sensory perception and imagination of music and speech with EEG and MEG recordings, leading to a brief account of how to decode imagined music and speech from these non-invasive signals.

S2. Integration of parallel ascending pathways in the primary and higher-order auditory cortices

Hiroyuki Kato

Topic areas: neural coding hierarchical organization correlates of behavior/perception

Fri, 11/11 2:35PM - 3:00PM | Young Investigator Spotlight

Abstract

Information flow in the sensory cortex is classically considered as feedforward-hierarchical computation, where higher-order cortices receive inputs from the primary cortex to extract more complex sensory features. However, recent human studies challenged such simple serial transformation by demonstrating robust speech perception in patients with primary auditory cortex lesions. To understand the interplay between the primary and higher-order cortices during sensory feature extraction, my laboratory focuses on the mouse primary (A1) and secondary (A2) auditory cortices as a model system. Using in vivo two-photon calcium imaging and unit recording in awake animals, we recently identified A2 as a locus for extracting temporally-coherent harmonic sounds. Interestingly, acute optogenetic inactivation of A1 did not disturb animals’ performance for the A2-dependent harmonics discrimination task. Moreover, we found short-latency (less than 10 ms) auditory input onto layer 6 (L6) of A2, which was as fast as the primary lemniscal input to A1 L4. We performed a series of anatomical and electrophysiological experiments and found that A2 L6 receives short-latency inputs from neurons along the non-lemniscal pathway, bypassing A1. These results align with the findings in humans and together indicate parallel and distributed, rather than simply feedforward, processing of auditory information across cortical areas. Nevertheless, it is important to note that A1 and A2 neurons have mutual excitatory influences on each other, as demonstrated by our area-targeted perturbation experiments. In this talk, I will further discuss our ongoing experiments investigating how A1 and A2 circuits integrate parallel ascending pathways to achieve unified sensory representations.

T1. Extratelencephalic neurons encode learned stimulus categories and behavioral choice

Nathan A. Schneider, Tomas Suarez Omedas, Rebecca F. Krall and Ross S. Williamson

Topic areas: correlates of behavior/perception neural coding

Descending Categorization Auditory Cortex Behavior

Fri, 11/11 12:15PM - 1:00PM | Podium Presentations 1

Abstract

Auditory-guided behavior is ubiquitous in everyday life, whenever auditory information is used to guide our decisions and actions. Nestled amongst several populations, extratelencephalic (ET) neurons reside in the deep layers of auditory cortex (ACtx) and provide a primary means of routing auditory information to diverse, sub-cortical targets associated with decision-making, action, and reward. To investigate the role of ET neurons in auditory-guided behavior, we developed a head-fixed choice task, where mice categorized the rate of sinusoidal amplitude-modulated (sAM) noise bursts as either high or low to receive a water reward. We first established ACtx necessity using bilateral optogenetic inhibition (with GtACR2), then used two-photon calcium imaging alongside selective GCaMP8s expression to monitor the activity of ET (N=3 mice, n=~180 neurons/day/animal) and layer (L)2/3 intratelencephalic (IT) (N=3 mice, n=~450 neurons/day/animal) populations. Clustering analyses of ET and L2/3 IT populations revealed heterogenous response motifs that correlated with various stimulus and task variables. One such motif, primarily present in ET neurons, corresponded to “categorical” firing patterns (i.e., neurons that responded best to low or high sAM rates). This categorical selectivity was not present early in training, and longitudinal recording revealed that ET neurons shifted their response profiles dynamically across learning to reflect these discrete perceptual categories. Our stimulus set included a sAM rate at the category boundary, rewarded probabilistically, allowing us to investigate stimulus-independent choice. Using statistical approaches to visualize high-dimensional neural activity we found that ET population activity, in response to this boundary stimulus, reflected behavioral choice, regardless of reward outcome. Further quantification using neural decoding analyses confirmed that behavioral choice could be robustly predicted from ET activity. Both choice and categorical selectivity were notably lessened in the L2/3 IT population, hinting at a unique ET role. Critically, ET categorical selectivity was only evident during active behavioral engagement and disappeared during passive presentation of identical stimuli. This suggests that learned categorical selectivity is shaped via top-down inputs that act as a flexible, task-dependent filter, a hypothesis that we are actively pursuing. These results suggest that the ACtx ET projection system selectively propagates behaviorally-relevant signals brain-wide and is critical for auditory-guided behavior.

T2. A dynamic model of neural oscillation can synchronize with natural speech

Iran Roman, Eshed Rabinovitch, Elana Golumbic and Edward Large

Topic areas: speech and language correlates of behavior/perception hierarchical organization

speech envelope tracking neural oscillation dynamical systems model

Fri, 11/11 12:15PM - 1:00PM | Podium Presentations 1

Abstract

Speech is a pseudo-periodic signal with an envelope frequency that dynamically fluctuates around 5Hz. One influential hypothesis proposed in recent years is that intrinsic neural oscillations entrain to the speech rhythm to track and predict speech timing. However, given that natural speech is not strictly periodic, but contains irregular pauses and continuous changes in speech-rate, the question of whether this type of stimulus can be efectively tracked or predicted by neural oscillations has been highly debated. Here we present a simple and parsimonious computational model of neural oscillation that is able to dynamically and continuously synchronize with the speech envelope. Our work is an adaptation of a previously proposed model that captures rhythmic complexities in music (Roman, Roman and Large 2020), extended to deal with stimuli that are not strictly periodic. The model has a natural frequency of oscillation, which it dynamically adapts to match stimulus frequency using Hebbian learning. Additionally, an elastic force pulls the system back towards its natural frequency in the absence of a stimulus. Using automatic diferentiation in tensorflow and gradient descent to optimize parameters, the model was trained to maximize the correlation between its activity and the speech onsets in a corpus of spoken utterances. The model was validated on an independent set of stimuli not included in the training data. First, using phase coupling only, performance reached a mean predictive power of r = 0.33 (0.24 less than r less than 0.42). Next, when frequency was also allowed to adapt dynamically, the model achieved a mean predictive power of r = 0.40 (0.29 less than r less than 0.50). For comparison we ran an ablation study in which the oscillator model was decoupled from the stimulus (i.e., neither phase coupling nor frequency adaptation). In the ablation study we observed chance-level predictive power of r = -0.001. These results demonstrate the theoretical plausibility that neural oscillations synchronize to continuous speech, exploiting the principles of neural resonance and Hebbian learning. This model paves the way for future research to empirically test the mechanistic hypothesis that speech processing is mediated by entrainment of neural oscillations.

T3. Predictive Coding in Songbird Auditory Cortical Neurons

Srihita Rudraraju, Brad Theilman, Michael Turvey and Timothy Gentner

Topic areas: correlates of behavior/perception neural coding

perception and cognition predictive coding error birdsong

Fri, 11/11 12:15PM - 1:00PM | Podium Presentations 1

Abstract

Predictive coding (PC), a theoretical framework in which the brain compares a generative model to incoming sensory signals, has been employed to explain perceptual and cognitive phenomena. There is little understanding, however, of how PC might be implemented mechanistically in auditory neurons. Here, we examined neural responses in caudomedial nidopallium (NCM) and caudal mesopallium (CM), analogs of higher order auditory cortex, in anesthetized European starlings listening to conspecific songs. We trained a feedforward temporal prediction model (TPM) to predict short segments (10.5 ms) of future birdsongs based on past 170 ms spectrographic samples to define a “latent” predictive feature space. To examine PC, we modeled each neuron’s composite receptive field (CRF) fit to either: 1) all spectrotemporal features (fft-CRF) or 2) only the predictive spectrotemporal features (tpm-CRF) or 3) prediction error spectrotemporal features computed by the mean squared error (mse-CRF). In NCM (n = 541 neurons), the tpm-CRFs yield excellent predictions of empirical spiking response to novel song and slightly higher than the fft-CRF (70.41% & 67.92% variance; p < 5.5x10-8, paired t-test), but mse-CRFs yield significantly poorer predictions (11.15%; p=0.0, paired t-test). Unlike NCM, however, the mse-CRF predicted a significant proportion of the CM response variance (53.61%; p < 1.7x10-190, t-test CM vs NCM). We showed that NCM spiking responses are best modeled by predictive features of song, while CM responses capture both predictive and error features. This provides strong support for the notion of a feature-based predictive auditory code implemented in single neurons in songbirds.

T4. Cross-Modal Representation of Individual Identity in Primate Hippocampus

Timothy Tyree, Mike Metke and Cory Miller

Topic areas: memory and cognition hierarchical organization multisensory processes neural coding

Hippocampus Primate Recognition Decoders

Fri, 11/11 3:00PM - 3:45PM | Podium Presentations 2

Abstract

The ability to recognize the identity of other individuals is integral to social living, as it is necessary for the myriad cognitive processes routinely employed by individuals navigating the complex dynamics of societies, such as memory, decision-making and communication amongst others. While evidence of neural representations for individual identity for a single, sensory modality (e.g. face, voice, odor, etc.) are evident in several species, compelling evidence for cross-modal representations of individual identity have been limited. Here we tested whether cross-modal representations of identity are also evident in the hippocampus of a nonhuman primate: common marmoset. We recorded the activity of ~2400 single neurons while presenting N=4 subjects with faces and voices of a large battery of familiar conspecifics as both unimodal and cross-modal stimuli. During cross-modal stimulus presentations, the face and voice were either from the same individual (Match) or different individuals (Mismatch). Our population-level decoder could almost perfectly distinguish between Match and Mismatch trials, even though subjects were presented with ~10 different individuals in each recording session. This decoder was so robust that ~50 randomly selected neurons from the entire population achieved ~80% reliability suggesting that cross-modal representations of identity in primate hippocampus are highly distributed. These compelling findings shed new insight into the nature of identity representations in primate hippocampus by demonstrating that cross-modal representations of identity are not only evident but are a facet of social recognition that supports a robust, distributed coding mechanism.

T5. Visual cues bias single-trial responses in the macaque inferior colliculus to favor a visually-paired sound

Meredith Schmehl, Surya Tokdar and Jennifer Groh

Topic areas: correlates of behavior/perception multisensory processes neural coding subcortical processing

auditory sound localization audiovisual audiovisual integration multisensory multisensory integration inferior colliculus macaque primate

Fri, 11/11 3:00PM - 3:45PM | Podium Presentations 2

Abstract

Visual cues can influence brain regions that are sensitive to auditory space (Schmehl & Groh, Annual Review of Vision Science 2021). However, how such visual signals in auditory structures contribute in the perceptual realm is poorly understood. One possibility is that visual inputs help the brain distinguish among different sounds, allowing better localization of behaviorally relevant sounds in noisy environments (i.e., the cocktail party phenomenon). Our lab previously reported that when two sounds are present, auditory neurons may switch between encoding each sound across time (Caruso et al., Nature Communications 2018). We sought to study how pairing a visual cue with one of two sounds might change these time-varying responses (e.g., Atilgan et al., Neuron 2018). We trained one rhesus macaque to localize one or two sounds in the presence or absence of accompanying lights. While the monkey performed this task, we recorded extracellularly from single neurons in the inferior colliculus (IC), a critical auditory region that receives visual input and has visual and eye movement-related responses. We found that pairing a light with a sound can change a neuron's response to that sound, even if the neuron is unresponsive to light. Further, when two sounds are present and one sound is paired with a light, neurons are more likely to spend individual trials responding to the visually-paired sound. Together, these results suggest that the IC alters its sound representation in the presence of visual cues, providing insight into how the brain combines visual and auditory information into perceptual objects.

T6. Representation of auditory space in the shell of the inferior colliculus

Meike M. Rogalla, Gunnar L. Quass, Deepak Dileepkumar, Alex Ford, Gunseli Wallace, Harry Yardley and Pierre F. Apostolides

Topic areas: auditory disorders correlates of behavior/perception neural coding subcortical processing

spatial plasticity monaural hearing loss auditory midbrain

Fri, 11/11 3:00PM - 3:45PM | Podium Presentations 2

Abstract

Spatial hearing enables humans and animals to localize sounds in their vicinity, which contributes to survival. Unlike vision or touch, the peripheral auditory system lacks a spatial map at the sensory receptor level. Sound source location is therefore derived centrally from mainly binaural cues, as well as from monaural cues. In the case of unilateral hearing loss, binaural cues are no longer available, which limits spatial hearing. However, monaurally occluded humans and animals can regain sound localization following perceptual training. It is assumed that the observable re-learning of sound localization relies on the context-dependent re-calibration of auditory space representation by monaural cues. Thus, central experience-dependent auditory plasticity mechanisms must exist to re-calibrate sound localization circuits. The “shell” nuclei of the inferior colliculus (shell IC) are hypothesized to act as plasticity loci for sound localization cues. However, the neural population coding of spatial information in the mammalian shell IC remains poorly understood. We developed an acoustic delivery system to present sound stimuli from distinct spatial positions within the horizontal frontal field by moving a speaker around the animals’ head while performing cellular resolution 2-photon Ca2+-imaging in the shell IC of awake, head-fixed mice. We found that neurons in the murine shell IC are spatially tuned, and that the population coding follows a surprisingly different pattern as previously shown for other auditory regions: In contrast to the central IC, where spatial tuning shows a contralateral dominance, we found both contra- and ipsi-lateral selective neurons, such that a single hemisphere contained a representation of the entire horizontal field. Although previous data suggested a monotonic code for spatial representations in the mammalian auditory system, many shell IC neurons were tuned to discrete contra- and ipsi-lateral positions. Tuning required binaural integration and seemed impervious to representational drift: tuning broadened or shifted towards the contralateral hemifield after inserting an ear plug into the left ear. To our knowledge, these results are the first insight into spatial population codes of the mammalian shell IC. Future studies will test if active engagement in a localization task is required for plasticity of spatial tuning during monaural hearing loss.

1. Relating linguistic speech features with EEG using a deep neural network

Corentin Puffay, Jonas Vanthornhout, Marlies Gillis, Bernd Accou, Hugo Van Hamme and Tom Francart

Topic areas: speech and language correlates of behavior/perception neural coding novel technologies

EEG decoding deep learning speech auditory system linguistics

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

The extent to which the brain tracks a speech stimulus can be measured for natural continuous speech by modeling the relationship between stimulus features and the corresponding EEG. Recently neural tracking of linguistic features has been shown using subject-specific linear models. As linguistics are processed in high-cortical areas, we expect their response to having a nonlinear component that a linear model cannot model. Therefore, we present a deep learning model to obtain a nonlinear subject independent model relating EEG to linguistic features as well as their added value over acoustic and lexical features. Sixty normal-hearing subjects listened attentively to 10 stories of 14 minutes each while their EEG was recorded. We here define neural tracking as the ability of the model to associate EEG with speech, and we use the classification accuracy on a match-mismatch task to measure it. We compare the baseline model (including acoustical and lexical representations) with a model including different phoneme- and word-level linguistic representations in addition to the baseline. Using subject-specific fine-tuning on a subject-independent pre-trained model, we found significant linguistic tracking on top of acoustic and lexical tracking for some features. We showed that some of the linguistic features carry additional information beyond acoustics and lexical features. The benefit of our deep learning model is that it may need less subject-specific training data than a linear model and that it can model non-linear relations between stimulus features and EEG. We will further use this model to objectively measure speech understanding.

2. Impact of auditory system impairments on eye-movement-related eardrum oscillations (EMREOs)

Cynthia King, Stephanie Lovich, David Kaylie, Christopher Shera and Jennifer Groh

Topic areas: multisensory processes subcortical processing

audiovisual integration eye movements middle ear muscles outer hair cells

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Eye movements are critical to linking vision and spatial hearing – every eye movement shifts the relative relationship between visual (eye-centered) and auditory (head-centered) frames of reference, which requires constant updating of incoming sensory information in order to integrate the two sensory inputs. Previous neurophysiological studies have revealed eye movement-related modulation of the auditory pathway. We recently discovered a unique type of low frequency otoacoustic emission that accompanies eye movements. These eye movement-related eardrum oscillations (EMREOs) occur in the absence of external sound and carry precise information about saccade magnitude, direction, and timing (Gruters et al 2018, Murphy et al 2020). However, it is not well understood how these eye movement-related effects in the auditory periphery contribute mechanistically to hearing. Two auditory motor systems may be involved in generating EMREOs: the middle ear muscles and the cochlear outer hair cells. To gain insight into which systems are involved and how they contribute, we are presently investigating the EMREOs in human subjects with dysfunction involving these systems compared to a normal hearing population. The impact of hearing loss on the EMREO is examined by comparing responses from individuals with different hearing pathologies to normal hearing population data. We find EMREOs are abnormal in subjects with hearing impairment, most commonly being abnormally small in individuals who have impaired outer hair cell or stapedius function. Future work is needed to assess if patients with these types of hearing loss have specific impairments in the perceptual process of integrating visual and auditory spatial information.

3. Neural dynamics of listened and imagined musical sound sequences

David R. Quiroga Martinez, Leonardo Bonetti, Robert Knight and Peter Vuust

Topic areas: memory and cognition correlates of behavior/perception thalamocortical circuitry/function

Imagery music MEG decoding oscillations

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Imagine a song you know by heart. With low effort you could play it vividly in your mind. However, little is known about how the brain represents and holds in mind such musical “thoughts”. Here, we leverage time-generalized decoding from MEG brain source activations to show that listened and imagined melodies are represented in auditory cortex, thalamus, middle cingulate cortex and precuneus. Accuracy patterns reveal that during listening and imagining sounds are represented as a melodic group, while during listening they are also represented individually. Opposite brain activation patterns distinguish between melodies during listening compared to imagining. Furthermore, encoding, imagining and retrieving melodies enhances delta and theta power in frontopolar regions, and suppresses alpha and beta power in sensorimotor and auditory regions. Our work sheds light on the neural dynamics of listened and imagined musical sound sequences.

4. Evidence for a vocal error signal in marmoset auditory cortex

Steven Eiades and Joji Tsunada

Topic areas: correlates of behavior/perception neuroethology/communication

Auditory cortex vocalization sensory-motor marmoset non-human primate

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

During both human speech and non-human primate vocalization, there is a well described suppression of activity in the auditory cortex. Despite this suppression, the auditory cortex remains sensitive to perturbations in sensory feedback, and this sensitivity has been shown to be important in feedback-dependent vocal control. Although the mechanisms of suppression and vocal feedback encoding are unclear, this process has been suggested to represent an error signal encoding the difference between sensory-motor prediction and feedback inputs. However, direct evidence for the existence of such an error signal is lacking. In this study, we investigated the responses of auditory cortical neurons in marmoset monkeys during vocal production, testing frequency-shifted feedback of varying magnitude and direction. Consistent with an error signal hypothesis, we found that population-level neural activity increased with the magnitude of feedback shifts, but were symmetric between positive and negative frequency changes. This feedback sensitivity was strongest in vocally-suppressed units and for units whose frequency tuning overlapped that of vocal acoustics. Individual units tested with multiple feedback shifts often showed preferences for either positive or negative feedback shifts, with only a minority showing sensitivity to feedback shifts in both directions. Frequency tuning distributions were different for units showing preference for one feedback direction over the other. These results suggest that vocal feedback sensitivity in the auditory cortex is consistent with a vocal error signal, seen at both the individual unit and population level.

5. A network model of complex scene analysis in auditory cortex with multiple inhibitory neuron types

Jian Carlo Nocon, Howard Gritton, Xue Han and Kamal Sen

Topic areas: neural coding

Auditory cortex Computational modeling Complex scene analysis Neural coding Cortical inhibition Parvalbumin

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Cortical representations underlying complex scene analysis emerge from circuits with a tremendous diversity of cell types. However, cell type-specific contributions to this are not well-understood. Specifically, how are competing dynamic stimuli from different spatial locations represented by cortical circuits and cell types? Recently, we investigated complex scene analysis in mouse ACx using a cocktail party-like paradigm, where we presented target sounds in the presence of maskers from different spatial configurations and quantified neural discrimination performance. We found that cortical neurons were spatial configuration-sensitive, with high discrimination performance at specific combinations of target and masker locations (“hotspots”). Further, optogenetically suppressing parvalbumin (PV) neurons in ACx degraded discrimination via changes in rapid temporal modulations in rate and spike timing over several timescales. These results suggest PV neurons contribute to complex scene analysis by enhancing cortical temporal coding and reducing network noise. Here, we propose a network model of ACx to explain these observations. The model consists of different spatial channels, with excitatory and multiple inhibitory neuron types based on experimental data. Our results suggest PV neurons mediate “within-channel” inhibition in the cortical network, while a distinct population of inhibitory neurons mediate “cross-channel” surround inhibition. Because complex scene analysis is modulated by behavioral state, we then extend the model to simulate top-down modulation via other inhibitory populations. Finally, we hypothesize a mapping of the distinct inhibitory neuron populations in the model to those in cortex (PV, SOM, and VIP) to generate experimentally testable predictions for cell type-specific responses in passive versus task-engaged conditions.

6. Encoding of non-auditory inputs by coordinated neuronal ensembles in mouse auditory cortex

James Bigelow, Ryan Morill, Timothy Olsen, Jefferson DeKloe, Christoph Schreiner and Andrea Hasenstaub

Topic areas: memory and cognition correlates of behavior/perception multisensory processes neural coding

auditory cortex population coding crossmodal attention arousal

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Mounting evidence suggests synchronous activity among multiple neurons may be an essential aspect of cortical information processing and transmission. Previous work in auditory cortex (AC) has shown that coordinated neuronal ensemble (cNE) events contain more information about sound features than individual member neuron spikes on a per spike basis. Moreover, preferred sound features encoded by single neurons often depend on whether they were spiking with a given cNE. In addition to sound encoding, it is well known that AC neurons are influenced by diverse non-auditory inputs reflecting motor activity, arousal, crossmodal sensory events, and attention. Nevertheless, it remains unknown whether these extramodal inputs are processed through population-level encoding in the same way as acoustic signals from the ascending auditory pathway. In the present study, we addressed this question by examining single neurons and cNEs in AC of mice performing an audiovisual attention switching task. As in previous studies, many single units and cNEs responded to sounds and were often modulated by non-auditory variables including movement velocity, pupil size, and modality specific attention. Importantly, we found that cNE representation of non-auditory inputs contained more information about events and states than member neuron spikes, similar to patterns previously described for sounds. Furthermore, modulation of single neuron activity by non-auditory inputs often depended on whether its activity coincided with a cNE. Our findings suggest auditory and extra-modal inputs may be subject to similar processing by cNEs in AC, and support prior work suggesting cNE activity as an information processing motif in cortex.

7. EEG-detected brain networks associated with listening to continuous speech in normal-hearing and hearing-impaired people

Ramtin Mehraram, Marlies Gillis, Maaike Vandermosten and Tom Francart

Topic areas: auditory disorders speech and language correlates of behavior/perception

EEG hearing loss temporal response function connectomics network natural speech

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Introduction The impact of hearing loss on brain functionality is a matter of interest in audiology research. However, there is still a lack of knowledge on hearing-impairment-related alterations in the neural networks when listening to natural speech. We investigated the relationship between acoustical features of speech (spectrogram, acoustic onset) and the spatial distribution of the neural activity in hearing-impaired (HI) and normal-hearing participants (NH). Methods Our sample comprised 14 HI and 14 NH age-matched participants. High density EEG (64ch) was recorded while the participants listened to a 12-minute long story. Temporal response functions (TRFs) for speech spectrogram and acoustical onsets were obtained through linear forward modelling. EEG-network connectivity was measured and subnetworks associated with TRFs’ peak latencies were obtained through correlation tests using Network Based Statistics. Results For the NH group positive correlations emerged between the connectivity strength of an α-band (7.5-14.5 Hz) right-temporo-frontal network component and the latency of N1 peak of the spectrogram-TRF, and between a right-occipito-parietal θ-band (4.5-7 Hz) network component and the latency of the P2 peak of the spectrogram. For the HI group, an inter-hemispheric-frontal and right-parietal θ-band network component negatively correlated with the P1 peak of the acoustical onset-TRF. Conclusion Our results show that neural response features in HI and NH groups relate to different brain subnetworks. Whilst physiological association between functional connectivity and spectrogram-TRF peaks is lost in HI, an abnormal correlation with the earliest part of acoustical-TRF emerges, suggesting that hearing impairment results in alteration of the earliest auditory mechanisms.

8. The functional geometry of human auditory cortical resting state networks

Matthew Banks, Bryan Krause, Hiroto Kawasaki, Mitchell Steinschneider and Kirill Nourski

Topic areas: memory and cognition speech and language correlates of behavior/perception hierarchical organization

Functional connectivity Network topology Limbic cortex Intracranial electrophysiology

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Introduction: Critical organizational features of human auditory cortex (AC) remain unclear, including the definition of information processing streams and the relationship of canonical AC to the rest of the brain. We investigated these questions using diffusion map embedding (DME) applied to intracranial electroencephalographic (iEEG) data from neurosurgical patients. DME maps data into a space where proximity represents similar connectivity to the rest of the network. Methods: Resting state data were obtained from 6487 recording sites in 46 patients (20 female). Regions of interest (ROI) were located in AC, temporo-parietal auditory-related, prefrontal, sensorimotor and limbic/paralimbic cortex. Functional connectivity was averaged within ROI then across subjects, thresholded and normalized, then analyzed using DME. Results: ROIs exhibited a hierarchical organization, symmetric between hemispheres and robust to the choice of iEEG frequency band and connectivity metric. Tight clusters of canonical auditory and prefrontal ROIs were maximally segregated in embedding space. Planum polare (PP) and the lower bank of the superior temporal sulcus (STSL) were located at a distance from the auditory cluster. Clusters consistent with ventral and dorsal auditory processing streams were paralleled by a cluster suggestive of a third stream linking auditory and limbic structures. Portions of anterior temporal cortex were characterized as global hubs. Conclusions: The separation of PP and STSL from AC suggests a higher order function for these ROIs. The limbic stream may carry memory- and emotion-related auditory information. This approach will facilitate identifying network changes during active speech and language processing and elucidating mechanisms underlying disorders of auditory processing.

9. Single neuron encoding of speech across cortical layers of the human superior temporal gyrus

Laura Gwilliams, Matthew Leonard, Kristin Sellers, Jason Chung, Barundeb Dutta and Edward Chang

Topic areas: speech and language correlates of behavior/perception neural coding

speech language single neuron activity neuropixels human auditory cortex superior temporal gyrus

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Decades of lesion and brain imaging studies have identified the superior temporal gyrus (STG) as a critical brain area for speech perception. Here, we used high-resolution multi-laminar Neuropixels arrays to record from hundreds of neurons in the human STG while participants listened to natural speech. We found that neurons exhibit tuning to complex spectro-temporal acoustic cues, which correspond to phonetic and prosodic speech features. However, single neuron activity across the cortical layers demonstrated a highly heterogeneous set of tuning profiles across the depth of the cortex, revealing a novel dimension of speech encoding in STG. Finally, single neuron speech-evoked responses across cortical layers were compared with field potentials recorded at the cortical surface. We found that high-frequency field potential activity reflects the contributions of neurons across all depths, encompassing the diversity of tuning response profiles across cortical layers. Together, these results demonstrate an important axis of speech encoding in STG, namely single neuron tuning across the cortical laminae. L.G. and M.K.L. contributed equally.

10. Evidence for invariant processing of phonemes from EEG responses to naturalistic speech.

Ole Bialas, Edmund Lalor, Emily Teoh and Andrew Anderson

Topic areas: speech and language correlates of behavior/perception

temporal response function naturalistic sounds speech perception

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

The past decade has seen an increase in efforts to understand the processing of speech and language using naturalistic stimuli. One popular approach has been to use forward encoding models to predict neural responses to speech based on different representations of that speech. For example, it has been shown that adding a categorical representation of phonemes to an acoustic (spectrogram) representation of a speech stimulus increases the predicted EEG response’s accuracy. This has been taken as evidence for a cortical representation of sublexical linguistic units that is categorical and robust with respect to spectrotemporal variation. However, subsequent studies argued that this gain could be explained more parsimoniously based on acoustic features alone. Here, we address this issue by investigating whether the spectral variance across utterances of the same phoneme determines how strongly that phoneme contributes to predicting EEG responses to speech. Simply put, if a phoneme was to be pronounced exactly the same all of the time, adding a categorical phoneme label to a spectrogram of the speech would be redundant and should not increase the predictive accuracy. Conversely, the accuracy gained by incorporating a phoneme label should be greater the more variantly that phoneme is pronounced. We predicted the brain responses of subjects who listened to segments of an audiobook based on a spectrogram as well as a phoneme representation of the acoustic input with temporal response functions. We investigate whether the loss in predictive accuracy after deleting a phoneme is correlated with its variability and whether this relationship is reflected in the weights assigned by the model. Our preliminary results suggest that the variance between utterances of a phoneme does affect its predictive power, supporting the idea that EEG indexes a robust cortical representation of language tokens.

11. Ecological Investigation of Attention to Speech, processing of irrelevant speech and the Own-Name Advantage in a Virtual Café

Danna Pinto, Adi Brown and Elana Zion Golumbic

Topic areas: speech and language

Speech Processing Attention Cocktail Party Own-Name

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Detecting that someone has said your name is one of the most famous examples for incidental processing of supposedly task-irrelevant speech. However, empirical investigation of this so-called “cocktail party effect” has yielded conflicting results. Here we present a novel empirical approach for revisiting this effect under highly ecological condition, using speech-stimuli and tasks relevant for real-life and immersing participants in a multisensory virtual environment of a café. Participants listened to narratives of conversational speech from a character sitting across from them, and were told to ignore a stream of announcements spoken by a barista character in the back of the café. Unbeknownst to them, the barista-stream sometimes contained their own name or semantic violations. We used combined measurements of brain activity (EEG), eye-gaze patterns, physiological responses (GSR) and behavior, to gain a well-rounded description of the response-profile to the task-irrelevant barista-stream. Both the own-name and semantic-violation probes elicited unique neural and physiological responses relative to control stimuli, indicating that the system was able to process these words and detect their unique status, despite being task-irrelevant. Interestingly, these responses were covert in nature and were not accompanied by systematic gaze-shifts towards the barista character. This patterns demonstrate that under these highly ecological conditions, listeners incidentally pick up information from task-irrelevant speech and are not severely limited by a lack of sufficient processing resources. This invites a more nuanced discourse about how the brain deals with simultaneous stimuli in real-life environments and emphasizes the dynamic and non-binary nature of attention.

12. Cortical PV neurons regulate the perceptual volume knob: bi-directional changes in loudness perception via reduced or enhanced PV-mediated inhibition in the auditory cortex

Matthew McGill, Caroline Kremer, Kameron Clayton, Kamryn Stecyk, Yurika Watanabe, Desislava Skerleva, Eve Smith, Chelsea Rutagengwa, Sharon Kujawa and Daniel Polley

Topic areas: auditory disorders correlates of behavior/perception

Hyperacusis Inhibition Hearing Loss Behavior Optogenetics

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Noise exposure that damages cochlear sensory cells and afferent nerve endings is associated with reduced feedforward inhibition from parvalbumin+ (PV) cortical GABAergic neurons, resulting in hyperactive, hyperresponsive, and hypercorrelated spiking in ACtx pyramidal neurons. To better establish how disinhibited neural circuit pathology studied in laboratory animals relates to loudness hypersensitivity and other clinical phenotypes observed in humans with sensorineural hearing loss, we developed a two-alternative forced-choice classification task for head-fixed mice to probe changes in the perception of loudness after controlled cochlear injuries. At baseline (N=17) or in sham-exposed control mice (N=6), behavioral classification of soft versus loud varied smoothly across a 40-80 dB SPL range. After noise exposures that caused either a “pure” cochlear neural damage (N=6), or mixed sensorineural pathology (N=5), mice rapidly developed loudness hypersensitivity that manifested as a 9 dB shift in their loudness transition threshold. As expected, bilateral silencing of auditory cortex via optogenetic activation of PV neurons did not affect tone detection probability but had an interesting effect on loudness perception, in that PV activation strongly biased mice to report high-intensity sounds as soft (N=6). Taken together, these data suggest that cortical PV neurons function as a perceptual volume knob; sounds are perceived as louder than normal following acoustic exposures that reduce PV-mediated cortical inhibition but softer than normal when PV neurons are artificially activated via optogenetics. Clinically, these data enrich the growing literature that identifies PV pathology as critical point of dysfunction in auditory perceptual disorders.

13. Physical properties of eye movement-related eardrum oscillations (EMREOs) in rhesus monkeys

Stephanie Lovich, David Kaylie, Cynthia King, Christopher Shera and Jennifer Groh

Topic areas: correlates of behavior/perception multisensory processes subcortical processing

multisensory eye movement hair cells middle ear muscles sub-cortical

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

The auditory, visual, and oculomotor systems work together to aid spatial perception. We have recently reported an oscillation of the eardrum that is time-locked to the onset of an eye movement in the absence of sounds or visual stimuli. These eye movement-related eardrum oscillations (EMREOs) suggest that interactions between auditory, visual, and oculomotor systems may begin as early as the ear itself. Much is still unknown about this phenomenon. Open questions include: 1) Which motor systems of the inner and middle ear contribute to this eardrum oscillation? Potential candidates include the stapedius muscle, tensor tympani muscle, and/or outer hair cells. 2) What neural circuits drive this oscillation? 3) What are the cognitive or perceptual effects of this oscillation, especially with respect to sound localization? To study the anatomical and neural circuits, we use the rhesus monkey as a model to perform controlled invasive surgical and pharmacological manipulations. The rhesus monkey can perform saccadic eye movements on similar time scales to human participants, and we are able to record ear canal changes in the same manner as with human participants. Monkeys have a highly-reproducible oscillation in both ears, comparable to humans, including alternating phase of the oscillation between the ears and separable horizontal and vertical components related to the horizontal and vertical components of the eye movement. Finally, monkeys allow for a single, specific surgical or pharmacological intervention after baseline data collection, data collection almost immediately after the procedure, and data collection on the order of thousands of trials.

14. Objectively evaluating hearing and language capabilities in patients with disorders of consciousness

Rien Sonck, Jonas Vanthornhout, Estelle Bonin, Aurore Thibaut, Steven Laureys and Tom Francart

Topic areas: speech and language

Consciousness Language Neural tracking

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Objectives. Following a severe brain injury, some patients fall into a coma and may subsequently experience disorders of consciousness (DOC). The patient’s hearing disability is a confounding factor that can interfere with the assessment of their consciousness and lead to misdiagnosis. To reduce misdiagnosis, we propose to assess the hearing- and language abilities of patients with DOC using electroencephalography (EEG) to investigate their auditory steady-state responses (ASSR) and neural speech envelope tracking. Methods. Sixteen adults participated in the first experiment. While their EEG was recorded, they listened passively to three ASSR stimuli, with amplitude modulation frequencies of 3.1 Hz, 40.1 Hz, and 102.1 Hz; each frequency provides information about different brain regions along the auditory pathway. These stimuli are presented both sequentially (i.e., single ASSR) and simultaneously (i.e., multiplexed ASSR). In a second experiment, which is still ongoing (n=2), patients with DOC first listen to a multiplexed ASSR stimulus. Then, we tracked their neural speech envelope after listening to a story in their native language, in a foreign language, and in noise. Results. We have shown that the signal-to-noise ratio of evoked multiplexed ASSR responses does not significantly differ from evoked single ASSR responses. Furthermore, our preliminary results indicate that neural speech envelope tracking is possible in patients with DOC. Conclusion. Multiplexed ASSR is a valid replacement for single ASSR, which can shorten EEG measurements, crucial for patients with DOC as they quickly get exhausted. Moreover, neural speech envelope tracking might be a promising tool to analyze DOC patients’ speech processing abilities.

15. Laminar Specificity of the Auditory Awareness Negativity Under Multitone Masking: A Biophysical Modeling Study

Carolina Fernandez Pujol, Andrew Dykstra and Elizabeth G Blundon

Topic areas: correlates of behavior/perception thalamocortical circuitry/function

consciousness auditory modeling

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Electroencephalography and magnetoencephalography are excellent mediums for capturing human neural activity on a millisecond time scale, yet little is known about their underlying laminar and biophysical basis. Here, we used a reduced but realistic cortical circuit model - Human Neocortical Neurosolver (HNN) - to shed light on the laminar specificity of brain responses associated with auditory conscious perception under multitone masking. HNN provides a canonical model of a neocortical column circuit, including both excitatory pyramidal and inhibitory basket neurons in layers II/III and layer V. We found that the difference in event-related responses between perceived and unperceived target tones could be accounted for by additional input to supragranular layers arriving from either the non-lemniscal thalamus or cortico-cortical feedback connections. Layer-specific spiking activity of the circuit revealed that the additional negative-going peak that was present for detected but not undetected target tones was accompanied by increased firing of layer-V pyramidal neurons. These results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of analysis of perception-related brain activity.

16. Decoding auditory attention in multitalker speech using glimpsed and masked acoustic events

Vinay Raghavan, James O'Sullivan and Nima Mesgarani

Topic areas: speech and language neural coding novel technologies

auditory attention decoding glimpsing model event-related potential

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Individuals suffering from hearing loss struggle to attend to speech in complex acoustic environments. While hearing aids suppress background noise, a talker can only be amplified when it is known who the listener aims to attend to. Neuroscientific advances have allowed us to determine the focus of a listener’s attention from their neural recordings, including non-invasive electroencephalography (EEG) and intracranial EEG (iEEG), a process known as auditory attention decoding (AAD). Recent research suggests that attention differentially influences glimpsed and masked speech event encoding in auditory cortex. However, these differences have yet to be leveraged for stimulus reconstruction (SR), and they suggest that event-related potentials (ERPs) to glimpsed and masked speech features also contain robust signatures of attention. Therefore, we sought to characterize attention decoding accuracy using SR- and ERP-based methods that leverage differences in the neural representations of glimpsed and masked speech. Here, we obtained iEEG responses in auditory cortex while subjects attended to one talker in a two-talker mixture. We also analyzed two publicly-available EEG datasets with the same task. We used linear decoding models to reconstruct the glimpsed, masked, and combined envelope and to classify ERPs to glimpsed, masked, and combined acoustic edge events. We found AAD through the classification of glimpsed and masked ERPs was most accurate at shorter time durations when utilizing iEEG recordings. Fewer differences in performance were observed in low-frequency EEG. These results suggest glimpsed and masked ERP-based AAD is preferable when using intracranial recordings due to increased performance at low latencies.

17. How many sounds can we hear?

Chloe Weiser, Bailey King, Maya Provencal, Jennifer Groh and Cynthia King

Topic areas: correlates of behavior/perception multisensory processes

sound localization auditory perception simultaneous auditory signals

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

The visual system can detect many different simultaneous stimuli. This is achieved in part due to small neuronal receptive fields in primary visual cortex as well as neuronal multiplexing of simultaneously presented stimuli (Li et al, 2016; Caruso et al, 2018). However, the mammalian auditory system appears to lack a map of auditory space, possibly limiting processing of multiple simultaneous sounds. Previous work reported that humans can accurately detect 2-4 simultaneous sounds, depending on stimulus type (Yost and Zhong 2017; Yost et al 2019). Participants in these earlier studies reported the number of detectable sound locations but a 2-interval-forced-choice task comparing different numbers of sound locations might be more sensitive. Here, subjects were asked which of two sets of spatially differentiated auditory stimuli involved more distinct locations. Each trial contained two presentations of 6 fixed-frequency noise bands, randomly spread across 1-6 of 8 speakers evenly spaced around the horizontal frontal field. For each stimulus pair, the first stimulus (the benchmark) always played from 3 randomly assigned speakers. For the second stimulus the number of speakers was randomized between 1-6. Subjects indicated whether the first or second stimulus used more speakers. Subjects completed two 600-trial sessions (200ms and 1000ms stimulus duration). Results align with previous work showing humans can detect roughly 2-4 sound locations at a time. Longer stimulus duration did not improve task performance. Thus, to the extent that multiple sound locations are multiplexed in the auditory system, additional detection time does not increase the number of sounds encoded.

18. Brain and behavioral development of distractibility during childhood: an EEG study

Aurélie Bidet-Caulet, Philippe Albouy and Roxane Hoyer

Topic areas: memory and cognition correlates of behavior/perception

auditory attention distraction EEG human development

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Distractibility is the propensity to behaviorally react to irrelevant information. It relies on a balance between voluntary and involuntary attention. Voluntary attention enables performing an ongoing task efficiently over time by selecting relevant information and inhibiting irrelevant stimuli; whereas involuntary attention is captured by an unexpected salient stimulus, leading to distraction. Voluntary and involuntary attention rely on partially overlapping dorsal and ventral brain networks, which undergo significant development during childhood. The developmental trajectory of distractibility has been behaviorally characterized using a recently developed paradigm, the Competitive Attention Test (CAT). In young children, increased distractibility was found to mostly result from reduced sustained attention and enhanced distraction, and from decreased motor control and increased impulsivity in teenagers. However, it is not clear how these behavioral developmental changes are implemented in the brain. To address this question, we recorded electrophysiological (EEG) signal and behavioral responses from 3 age groups (6-7,11-13 and 18-25-years-old) performing the CAT. To assess voluntary attention orienting, the CAT includes informative and uninformative visual cues before an auditory target to detect. To measure distraction, the CAT comprises trials with a task-irrelevant complex sound preceding the target sound. Moreover, the rates of different types of false alarms, late and missed responses provide behavioral measures of sustained attention, impulsivity, and motor control. EEG brain responses to relevant and irrelevant sounds were investigated. The CNV before the target was found modulated by the cue information in adults only. In response to the target, a cue effect was found on the N1 in teenagers and on the P3b in children. These effects of voluntary orienting at different moments of the task according to age suggest a shift from a reactive to a proactive strategy from 6-years-old to adulthood. In response to the irrelevant sounds, a larger and longer RON was found in children and teenagers compared to adults, suggesting difficulties in reorienting back to the task before adulthood. These brain changes during childhood are associated with a behavioral increase in sustained attention, and a decrease in distraction and impulsivity. These findings give important insights into how the developing brain shapes child behavior.

19. Functional dissection of disinhibition versus sensitization in the emergence of cortical hyperexcitability after hearing loss

Bshara Awwad, Yurika Watanbe, Olivia Stevenson, Liam Casey, Kameron Clayton and Daniel Polley

Topic areas: auditory disorders neural coding

Hearing loss disinhibition hyperexcitability neural plasticity

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

After sensorineural hearing loss, auditory cortex (ACtx) neurons become hyperresponsive to sound – excess central gain –, a core feature of tinnitus and hyperacusis. Ex vivo experiments suggest that auditory hyperresponsivity could arise through two mechanisms: either disinhibition via reduced feedforward inhibition or sensitization via enhanced glutamatergic inputs. Here, we developed a novel optogenetic approach to put these ideas to the test in the intact ACtx. We used a triple virus strategy to express ChR2 in parvalbumin+ (PV) GABAergic neurons and a somatically restricted, red-shifted opsin in contralateral neurons that project to the ACtx via the corpus callosum, allowing independent optical control over select populations of inhibitory (PV) and excitatory (callosal) neurons. High-density translaminar recordings were made from the high-frequency region of A1 in awake, head-fixed mice up to three days following acoustic trauma or an innocuous sham exposure. Sound intensity growth functions from regular spiking putative pyramidal neurons were markedly increased after acoustic trauma (n = 484 units in 6 mice), particularly in layer 5, compared to sham exposure (n=402 units in 5 mice). Dual optogenetic activation revealed that excess auditory gain was accompanied by a striking disinhibition, as measured from reduced PV-mediated suppression of spiking, without any evidence of sensitization to direct activation of excitatory callosal neurons. Hyperresponsivity from deep layer projection neurons via disinhibition could induce strong coupling with limbic brain regions and negative auditory affects after acoustic trauma, a possibility that we are exploring in ongoing experiments via dual recordings from the ACtx and basolateral amygdala.

20. Task-dependent modulation of subcortical areas during auditory perceptual learning

Rose Ying, Daniel Stolzberg and Melissa Caras

Topic areas: correlates of behavior/perception subcortical processing

inferior colliculus medial geniculate nucleus perceptual learning task-dependent plasticity

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Training can improve the detection of near-threshold stimuli, a process called perceptual learning. Previous research has shown perceptual learning strengthens task-dependent modulations of auditory cortical activity. However, it is unclear whether these changes emerge in the ascending auditory pathway and are inherited by the auditory cortex, or arise in the cortex de novo. To address this, we implanted Mongolian gerbils with chronic microelectrode arrays in either the central nucleus of the inferior colliculus (CIC) or the ventral medial geniculate nucleus (vMGN). We recorded single- and multi-unit activity as animals trained and improved on an aversive go/no-go amplitude modulation (AM) detection task, and during passive exposure to the same AM sounds. AM-evoked firing rates and vector strengths were calculated and transformed into the signal detection metric d’. Neural thresholds were obtained for each training day by fitting d’ values across AM depths and determining the depth at which d’ = 1. As expected, CIC neurons encoded AM using a temporal strategy. Neural thresholds were similar during task and passive conditions, suggesting an absence of task-dependent modulation in the CIC. However, both task and passive neural thresholds improved, suggesting that the CIC does display learning-related plasticity independent of task engagement. vMGN neurons used both temporal and rate strategies to encode AM. As in the CIC, neural thresholds recorded during task performance improved, suggesting that learning-based plasticity is also present in the vMGN. However, unlike in the CIC, rate-based neural thresholds in the vMGN were better during task performance compared to passive exposure, suggesting that the vMGN is subject to task-dependent modulation. Notably, the magnitude of task dependent modulation increased over the course of training, similar to what has been reported in the auditory cortex . These findings suggest that training may improve neural sensitivity at or below the level of the auditory midbrain, and simultaneously strengthen non-sensory modulations of auditory thalamus. Our results contribute to a deeper understanding of the circuits supporting perceptual learning, and may ultimately inform strategies for improving sound perception in the hearing-impaired.

21. Effects of language understanding on hemispheric lateralization in brain activity

John Kyle Cooper, Marlies Gillis, Lotte Van den Eynde, Jonas Vanthornhout and Tom Francart

Topic areas: speech and language correlates of behavior/perception neural coding

EEG Language Lateralization

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Motivation Previous research has shown that the left hemisphere of the brain plays an important role in language understanding. We investigate the effects of language understanding on hemispheric lateralization in brain activity using electroencephalography (EEG) and temporal response functions (TRFs) in two experimental paradigms that use different languages. Using these languages we observe how activity in the brain changes depending on if the listener understands the language. Methods In a first study, 26 native Dutch-speaking subjects listened to a Dutch story and a Frisian story while their EEG was recorded. In a second study, 4 subjects listened to stories in Dutch, French, and Italian while their EEG was recorded. Results In the TRFs, increased left-hemisphere lateralization was found at 150 ms when listeners were presented with their native language. When listeners were presented with their second language there was decreased left-hemisphere lateralization at 150 ms. Decreased left-hemisphere lateralization was also observed when listeners were presented with languages they do not understand. Conclusion Using EEG measurements we analyzed the effects of language understanding on hemispheric lateralization in TRFs. The hemispheric lateralization observed when subjects listen to their second language is inconsistent with lateralization observed when listening to their native language. Therefore, hemispheric lateralization could be used to assess native language understanding for individuals with hearing impairment and/or neurological disorders (e.g. aphasia). Acknowledgments Financial support for this project is provided by a Ph.D. grant from the Research Foundation Flanders (FWO).

22. The influence of sound statistics on auditory decisions in ferrets

Katharina S Bochtler, Fred Dick, Lori L Holt, Andrew J King and Kerry M M Walker

Topic areas: memory and cognition

auditory attention sound statistics duration discrimination ferrets attentional gain

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

The ability to direct our attention towards a single sound source such as a friend’s voice in a crowded room is necessary in our acoustical world. This process is thought to rely, in part, on directing attention to different sound dimensions, such as frequency. Previous investigations have shown task-dependent changes in the frequency tuning of auditory cortical neurons when ferrets actively detect or discriminate a particular frequency of sound (e.g. Fritz et al. 2010). However, questions remain about how attentional gain can arise based on sound statistics. Specifically, to what extent can this modulation occur even if frequency is not a necessary component of the task demands? Mondor & Bregman (1994) demonstrated that human listeners’ reaction times on a tone duration task were slower when the presented tone frequency was unexpected (i.e. low probability). Here, we test the hypothesis that the statistical likelihood of sound frequencies alone can also affect animals’ behavioural decisions on orthogonal dimensions of sounds. We trained ferrets on a 2-alternative forced choice tone duration discrimination task in which we manipulated the statistical likelihood of tone frequencies. Our results show that, similar to humans, ferrets’ reaction times on this duration judgement task increased for low-probability frequencies, while their accuracy remained stable across other frequencies. These results suggest that attentional filters are employed during listening, even for an acoustical dimension (frequency) that is orthogonal to the task demands (duration). Our future experiments will use this task in combination with microelectrode recordings to investigate the neurophysiological basis of statistical-based attentional filtering in the auditory cortex.

23. Dynamic and structured action bias masks learned task contingencies early in learning

Ziyi Zhu, Celine Drieu and Kishore Kuchibhotla

Topic areas: correlates of behavior/perception

Reinforcement learning Two-alternative forced choice Auditory discrimination Computational modelling

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Learning is not only the acquisition of knowledge, but also the ability to express that knowledge when needed. We tested the acquisition of task knowledge using non-reinforced probe trials while mice were trained to perform a balanced, wheel-based auditory two-alternative forced choice (2AFC) task. During probe trials, animals exhibited surprisingly higher accuracy and lower directional bias early in learning, as compared to reinforced trials, suggesting that they have already acquired unbiased knowledge of stimulus-action contingency, but expressed this knowledge much slower under reinforcement. Why do animals exhibit this gap in accuracy and directional bias between acquisition and expression, despite already acquiring the stimulus-action associations? Animals may (1) exhibit motor biases that they slowly learn to suppress, (2) continue to explore different choice alternatives, or (3) base decisions on recent trial history, including choice and reward, rather than current stimuli. To test between these and other potential drivers, we first used a generalized linear model to separate different contributors to animals’ choice during learning, including stimulus identity, trial history effects, and a continuous but slowly evolving directional preference (not influenced by stimulus or history factors), which we term action bias. Action bias, but not trial history, was the most important contributor to choice besides stimulus identity, and partially bridged the gap between acquisition and expression. We then asked if the structure of this action bias is static, reflecting a motor bias, or dynamic, reflecting changing behavioral strategies. Individual animals showed distinct states with left or right bias in blocks of tens to hundreds of trials and transitioned between both directions and un-biased states throughout learning, suggesting a dynamic bias structure. As learning progressed, animals exhibited less extreme bias, but continued to transition in and out of low biased states even at expert level performance. Taken together, behavioral expression may reflect an action bias driven exploratory process that is uncoupled from acquisition, evolves during learning, and persists to a lower degree at expert level to potentially maintain flexibility.

24. Modeling and predicting human perceptual sensitivity of speech recognition in natural environmental noise

Xiu Zhai, Alex Clonan, Ian Stevenson and Monty Escabi

Topic areas: speech and language correlates of behavior/perception

speech in noise natural sounds modulation frequency speech recognition auditory midbrain model

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Being able to recognize sounds in competing noise is a critical task of the normal functioning auditory system. Here we performed human psychoacoustic studies to assess how spectrum and modulation content of natural background sounds masks the recognition of speech digits. Native English speakers with normal hearing (0-20 dB threshold, 0.25-8 kHz) listened to digits in various original and perturbed maskers at 72 dB SPL and -9 dB SNR. Phase randomized (PR) and spectrum equalized (SE) background variants were used to dissociate spectrum vs. modulation masking effects. Response accuracy shows differences across sounds and conditions indicating that masking can be attributed to the modulation content and its high-order structure. For instance, the PR speech babble exhibits an increase in the accuracy, indicating that the modulation content is a major masking component. For construction noise, by comparison, the modulations tend to improve the accuracy. Thus, individual backgrounds can produce varied outcomes and the unique modulation content of each background can affect digit identification beneficially or detrimentally. We next developed an auditory midbrain model to determine whether masker interference in a physiologically inspired modulation space could predict the perceptual trends. Sounds were decomposed through a cochlear filterbank and a subsequent set of spectro-temporal receptive fields that model modulation sensitivity and map the waveform into temporal and spectral modulation. These outputs were then sent to a logistic regression model to estimate perceptual transfer functions and ultimately predict response accuracy. Cross-validated predictions demonstrate that the model accounts for ~90% of the perceptual response variance. The model also outperformed predictions obtained using a cochlear model, which accounted only for ~60% of the variance. The perceptually derived transfer functions subsequently allow us to identify salient cues that impact recognition in noise. For instance, slow background modulations (less than 8 Hz) tended to reduce accuracy whereas spectral modulations in speech in the voicing harmonicity range tended to improve accuracy. The finding demonstrate that the modulation content of environmental sounds can have adversarial masking outcomes on speech recognition and that an auditory midbrain inspired representation can predict and identify high-order cues that contribute to listening in noise.

25. Precise movement-based predictions in the mouse auditory cortex

Nicholas Audette, Wenxi Zhou, Alessandro La Chioma and David Schneider

Topic areas: memory and cognition correlates of behavior/perception neural coding neuroethology/communication

Predictive Processing Auditory Cortex Sensory-motor Learning Expectation Forelimb Behavior

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Many of the sensations experienced by an organism are caused by their own actions, and accurately anticipating both the sensory features and timing of self-generated stimuli is crucial to a variety of behaviors. In the auditory cortex, neural responses to self-generated sounds exhibit frequency-specific suppression, suggesting that movement-based predictions may be implemented early in sensory processing. Yet it remains unknown whether this modulation results from a behaviorally specific and temporally precise prediction, nor is it known whether corresponding expectation signals are present locally in the auditory cortex. To address these questions, we trained mice to expect the precise acoustic outcome of a forelimb movement using a closed-loop sound-generating lever. Dense neuronal recordings in the auditory cortex revealed suppression of responses to self-generated sounds that was specific to the expected acoustic features, specific to a precise position within the movement, and specific to the movement that was coupled to sound during training. Prediction-based suppression was concentrated in L2/3 and L5, where deviations from expectation also recruited a population of prediction-error neurons that was otherwise unresponsive. Recording in the absence of sound revealed abundant movement signals in deep layers that were biased toward neurons tuned to the expected sound, as well as expectation signals that were present across cortical depths and peaked at the time of expected auditory feedback. Together, these findings reveal that predictive processing in the mouse auditory cortex is consistent with a learned internal model linking a specific action to its acoustic outcome with a temporal resolution of 10s of milliseconds, while identifying distinct populations of neurons that anticipate expected stimuli and differentially process expected versus unexpected outcomes.

26. Utilizing vagus nerve stimulation to reverse maladaptive plasticity in the inferior colliculus in a rat autism model

Yuko Tamaoki, Varun Pasapula, Tanya Danaphongse, Samantha Kroon, Olayinka Olajubutu, Michael Borland and Crystal Engineer

Topic areas: speech and language subcortical processing

Autism Neurodevelopmental Disorder Vagus Nerve Stimulation Inferior Colliculus Electrophysiology

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Receptive language deficits are often observed in individuals with autism spectrum disorders (ASD). Auditory cortex neurons in children with ASD respond slower and weaker compared to typically developing children. When children are prenatally exposed to valproic acid (VPA), an anticonvulsant medication, it increases the risk for ASD. Symptoms associated with ASD are often observed, including altered sensory processing and deficits in language development. Impairments in sensory processing are also seen in rodents prenatally exposed to valproic acid. These rodents display deficits in speech sound discrimination ability. These behavioral characteristics are accompanied by changes in cortical activity patterns. In the primary auditory cortex (A1), the normal tonotopic map observed in typically hearing animals is reorganized and degraded in VPA-exposed rats. In VPA-exposed animals, neurons in the midbrain regions, such as the superior olivary complex and inferior colliculus, have disrupted morphology. Developing a method to improve these neural deficits throughout the auditory pathway is needed. We have developed a new approach to drive plasticity that enhances recovery after neurological damage. This strategy utilizes vagus nerve stimulation paired with a sound presentation. The aims of this study are to 1) document differences in the multi-unit inferior colliculus response to sounds in VPA exposed rats in comparison to saline exposed control rats, and 2) investigate the ability of VNS paired with sounds to reverse the maladaptive plasticity in the inferior colliculus in VPA exposed rats. In these experiments, we test the hypothesis that VNS paired with speech sound and tone presentation will reverse maladaptive plasticity and restore neural responses to sounds in VPA-exposed rats. Our results suggest that VPA rats displayed weaker responses to speech sounds in the IC and VNS-sound pairing is an effective method to enhance auditory processing. VPA rats responded weaker to speech sounds compared to the control rats in the IC. VNS-sound pairing strengthened the IC response to both the paired sound and sounds that were acoustically similar. Insights derived from this study may influence the development of new behavioral and sensory techniques to treat communication impairments that result in part from a degraded neural representation of sounds.

27. Intra-cortical mechanisms for integration of auditory and olfactory information

Nathan Vogler, Violet Tu, Alister Virkler, Ruoyi Chen, Tyler Ling, Jay Gottfried and Maria Geffen

Topic areas: correlates of behavior/perception multisensory processes

Auditory Auditory Cortex Olfactory Multisensory

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

In complex environments, the brain must integrate information from multiple sensory modalities, including the auditory and olfactory systems. However, little is known about how the brain integrates auditory and olfactory stimuli. Here, we investigated the mechanisms underlying auditory-olfactory integration using anatomy, electrophysiology, and behavior. We first used viral tracing strategies to investigate the circuits underlying auditory-olfactory integration. Our results demonstrate direct inputs to the auditory cortex (ACx) from the piriform cortex (PCx), mainly from the posterior PCx, suggesting an anatomical substrate for olfactory integration in ACx. We next developed an experimental system for delivering combinations of auditory and olfactory stimuli during in vivo electrophysiology, and tested the effect of odor stimuli on auditory cortical responses to sound in awake mice. Odor stimuli modulate the responses of ACx neurons in a stimulus- and sound level-dependent manner, suggesting a neural substrate for olfactory integration in ACx. Finally, we trained mice on a sound detection Go/No-Go task to assess how odor stimuli affect auditory perception and behavior. Odors facilitate auditory perception by lowering sound detection thresholds. Together, our findings reveal novel circuits and mechanisms for auditory-olfactory integration involving the ACx.

28. Modeling non-linear dynamics of auditory cortical adaptation to changing background noise with deep neural networks

Gavin Mischler, Menoua Keshishian, Stephan Bickel, Ashesh Mehta and Nima Mesgarani

Topic areas: speech and language

neural adaptation deep neural networks modeling noise-robust gain control

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

The human auditory system displays a robust capacity to adapt to sudden changes in background noise, allowing for continuous speech comprehension despite changes in background environments. However, despite comprehensive studies characterizing this ability, the computations that enable the brain to achieve this are not well understood. The first step towards understanding a complex system is to propose a suitable model, but the classical and easily interpreted model for the auditory system, the spectro-temporal receptive field (STRF), cannot match the nonlinear dynamics of noise adaptation. To overcome this, we utilize a deep neural network (DNN) to model neural adaptation to noise, illustrating its effectiveness at reproducing the complex dynamics at the levels of both individual electrodes and the cortical population. By closely inspecting the model’s STRF-like computations over time, we find that the model alters both the gain and shape of its receptive field when adapting to a sudden noise change, enabling multiple noise filtering methods to be used. Further, we find that models of electrodes in nonprimary auditory cortex exhibit different filtering changes compared to primary auditory cortex, suggesting differences in noise filtering mechanisms along the cortical hierarchy. These findings demonstrate the capability of deep neural networks to model complex neural adaptation and offer new hypotheses about the computations that the auditory cortex performs to enable noise-robust speech perception in real-world, dynamic environments.

29. Experience-dependent gating of primary auditory cortex by frontal top-down inputs

Hiroaki Tsukano and Hiroyuki Kato

Topic areas: memory and cognition correlates of behavior/perception hierarchical organization

Auditory Cortex Orbitofrontal Cortex Habituation

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Sensory stimuli lose their perceptual salience after repetitive exposure (“habituation”). We previously reported that daily passive sound exposure attenuates neural responses in the mouse primary auditory cortex (A1), and local inhibition by somatostatin-expressing neurons (SOM neurons) mediates this plasticity. In the current study, we further explored the source of top-down inputs that control SOM neurons to trigger habituation. We first conducted retrograde tracing and found that A1 receives projections from the frontal cortical areas, including the orbitofrontal cortex (OFC). Interestingly, optogenetic activation of the OFC axon terminals suppressed A1 neuronal activity, suggesting a top-down inhibitory control of sensory representations. To investigate the plasticity of OFC top-down inputs during habituation, we performed two-photon calcium imaging of OFC axon terminals in A1 during daily passive exposure to tones. We found that tone-evoked activity of OFC axons was enhanced over days, suggesting their contribution to the attenuation of A1 sound responses. Finally, we examined the causal role of OFC in habituation by its pharmacological inactivation during chronic calcium imaging of A1 neural activity. Strikingly, acute muscimol infusion into OFC reversed the pre-established A1 habituation, indicating the requirement of the OFC in sensory habituation. Together, these results suggest the predictive gating of sensory activity by a global circuit mechanism recruiting the frontal top-down inputs.

30. From instinct to insight: Neural correlates of associative sound learning to improve an innate social behavior

Kai Lu and Robert Liu

Topic areas: memory and cognition neuroethology/communication

Auditory cortex learning innate

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

In nature, animals learn to modify their innate behaviors to better adapt to the environment, transitioning their actions from pre-existing stereotypes to novel, more adaptive ones. Here we explored the neural basis for such transitions by investigating how freely moving female mice learn to override the way they innately search for pups by relying on a new sound that predicts where pups will be found. Naïve virgins were trained in a T-maze to enter one of the two arms cued by an amplitude-modulated band-pass noise and rewarded with pups, which were then retrieved back to the nest at the main stem. All mice (N=9) initially used an innate spatial memory-based strategy of searching the arm where a pup was presented in the prior trial. Within 8 days, all animals learned (70% correct) to use the sound to locate pups. We recorded single-unit/multi-unit spiking in auditory cortices (AC, N~1200) and medial prefrontal cortices (mPFC, N~600) during learning. Our results showed: (1) AC responses before choosing were significantly different between correct and wrong trials (55% units), suggesting top-down modulation; (2) nest sound sensitivity increased over training (p less than 0.001) as performance using the sound improved. Meanwhile, mPFC neurons exhibited higher population activities when animals made wrong choices (p less than 0.001), suggesting they help evaluate choice outcomes. Future work will model how these sensory and prefrontal changes during learning work together to promote switching from the innate strategy to the more efficient auditory strategy. Grant: R01DC008343

31. Transformation of acoustic information to sensory decision variables in parietal cortex

Justin Yao, Klavdia Zemlianova, David Hocker, Cristina Savin, Christine Constantinople, Sueyeon Chung and Dan Sanes

Topic areas: correlates of behavior/perception neural coding

parietal cortex auditory perception decision-making neural response manifold geometric analysis

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

The process by which sensory evidence contributes to perceptual choices requires an understanding of its transformation into decision variables. Here, we address this issue by evaluating the neural representation of acoustic information in auditory cortex-recipient parietal cortex while gerbils either performed an auditory discrimination task or while they passively listened to identical acoustic stimuli. Gerbils were required to discriminate between two amplitude modulation (AM) rates, 4- versus 10-Hz, as a function of AM duration (100-2000 msec). Task performance improved with increasing AM duration, and reached an optimum at approximately 800 msec. Decoded activity of simultaneously recorded parietal neurons reflected psychometric sensitivity during task performance. Decoded activity during passive listening was poorer than during task performance, but scaled with increasing AM duration. This suggests that the parietal cortex could accumulate this sensory evidence for the purpose of forming a decision variable. To test whether decision variables emerge within parietal cortex activity, we applied principal component and geometric analyses to the neural responses. Both principal component and geometric analyses revealed the emergence of decision-relevant, linearly separable manifolds on a behaviorally-relevant timescale, but only during task engagement. Finally, using a clustering analysis, we found 3 subpopulations of neurons that may reflect the encoding of separate segments of task performance: stimulus integration and motor preparation or execution. Taken together, our findings demonstrate how the parietal cortex integrates and transforms encoded auditory information to guide sound-driven perceptual decisions.

32. Heard or understood? Evaluating neural tracking of higher-level language features to assess speech understanding

Marlies Gillis, Jonas Vanthornhout and Tom Francart

Topic areas: speech and language

Neural tracking Speech processing Linguistic tracking Speech understanding

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Over the last years, more attention has been devoted to understanding and characterizing the neural responses associated with speech understanding. The differentiation can be made between hearing the stimulus and understanding the presented speech, whereby the listener can connect to the meaning of the storyline. To investigate the neural response to speech, one can investigate neural tracking, i.e., the phenomenon whereby the brain time-locks to specific aspects of the speech. Although envelope tracking is thought to capture certain aspects of speech understanding, this is not always true (Verschueren et al., 2022). A possible solution can be found by focussing on identifying higher-level language features, derived from the speech’s content, which can capture the neural correlates of speech understanding (e.g., Brodbeck et al., 2018; Broderick et al., 2018; Weissbart et al., 2020). This study evaluated whether neural tracking of these higher-level language features, i.e., linguistic tracking, gains more insight into whether the listener understood the presented speech. We investigated the EEG responses of 19 normal-hearing young participants (6 men) who listened to a Dutch story, a Frisian story whereby Frisian was not familiar to the participants, and a word list whereby individual words were understood but the context did not make sense. We hypothesized that the Dutch story would show linguistic tracking as the storyline can be understood, while this would not be the case for the Frisian story and the word list. Preliminary results indicate the Dutch story showed more linguistic neural tracking than the Frisian story, which shows higher linguistic tracking than the word list. The results obtained by analyzing linguistic tracking converged with the subjectively rated speech understanding, i.e., the answer to the question ‘how much of the content of the speech did you comprehend?’. The Dutch story was fully intelligible, followed by the Frisian story, rated around 50%, while the speech understanding for the word list was rated around 10%. Our preliminary results indicate that linguistic tracking can capture the effect of speech understanding. These results open doors toward understanding language disorders and improving their diagnosis and treatment.

33. ECoG-based Auditory Attention Decoding with Moving Talkers and Background Noise

Vishal Choudhari, Cong Han, Stephan Bickel, Ashesh Mehta and Nima Mesgarani

Topic areas: speech and language correlates of behavior/perception novel technologies

Auditory Attention Decoding Spatial Attention Cognitively-Controlled Hearing Aids Speech Separation Deep Learning

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Hearing-impaired listeners experience difficulty in attending to a specific talker in the presence of interfering talkers. Cognitively-controlled hearing aids aim to address this problem by decoding the attended talker from neural signals using auditory attention decoding (AAD) algorithms, separating the speech mixture into individual streams and selectively enhancing the attended speech stream. Prior work investigating AAD algorithms often use simple acoustic scenes for their experiments: the attended and unattended talkers are usually of different sex and stationary in space with no relative motion. Background noise is often ignored. Such scenes do not mimic real-life settings. More importantly, the talkers could also be engaged in conversations, which calls for attention switches during turn-taking. For AAD algorithms to be operable in real-world settings, it is imperative that they generalize to challenging and unpredictable changes in the acoustic scene. We designed an AAD task that replicates real-life acoustic scenes. The task involved two concurrent talkers (either same/different sex) that are spatially separated and continuously moving in the presence of background noise. These talkers independently engaged in two distinct conversations. Different talkers took turns in these conversations. Electrocorticography (ECoG) data from two epilepsy patients was collected. The participants were instructed to attend to the conversation that was cued at the start of each trial. A deep learning-based binaural speech separation algorithm was used to causally separate the speech streams of the talkers in the acoustic scene while also preserving their location information. Spatiotemporal filters were trained to reconstruct the spectrograms and trajectories of the attended and unattended talkers from the neural recordings. These reconstructions were then compared with the spectrograms and trajectories yielded by the binaural speech separation algorithm to determine the attended and unattended talkers. The binaural speech separation algorithm helped in enhancing the attended talker both subjectively and objectively. Trajectories and spectrograms of the attended talker were reconstructed from neural data with accuracies significantly above chance levels. Attended talker could be correctly decoded with an accuracy of 82% using a window size of 4 seconds. These results suggest that our speech separation and AAD algorithms can generalize well to challenging real-life settings.

34. Markov Decision Processes as a tool for quantifying behavioral and neural task representations

Alexander Kazakov, Maciek M. Jankowski, Ana Polterovich, Johannes Niediek and Israel Nelken

Topic areas: cross-species comparisons neural coding

Decision making Reinforcement learning Artificial neural network

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

When an animal is trained on a complex task, different task parts may be learned at different rates. Since reward is provided usually only at the trial’s end, it cannot be used to infer within-trial learning trends. Behavioral features such as speed or trial duration capture trends in the animal’s decision-making, but do not necessarily indicate that the animal is improving on the task. We propose to study learning of sub-parts of the task by a fine-level analysis of animal behavior via a Markov Decision Process (MDP) model. We applied this approach to rats performing a sound localization task. We observed that (1) Rat behavior approached the optimal policy gradually throughout training; (2) most of the policy refinement occurred at a specific, short (less than 1s) segment of the trial; (3) the first trials of each day showed sub-optimal performance that improved during the session. Lastly, we modeled the rat using artificial agents guided by a deep neural network (DNN). We observed similar features of learning in the artificial agents as in the real rats. We then investigated how the task is encoded by the agent’s DNN. Preliminary results indicate that the strongest connections between neurons were crucial for the precise network activity: The action accuracy of the network dropped by 50% when the strongest 5% of the weights are erased. However, removing 40% of the smallest weights also reduced accuracy by 20%. Further study of the information processing may be used to generate working hypotheses for learning in biological brains.

35. The evolutionary continuity and divergence of auditory dorsal and ventral pathways in primates

Yang Zhang, Sherry Xinyi Shen, Adnan Bibic and Xiaoqin Wang

Topic areas: speech and language cross-species comparisons

Language network Dual auditory pathways Evolution

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Auditory dorsal and ventral pathways in the human brain play important roles in supporting language processing. However, the evolutionary course of the dual auditory pathways remains largely unclear. By parcellating the auditory cortex of marmosets, macaques, and humans using the same individual-based analysis method and tracking the fiber pathways originating from the auditory cortex based on multi-shell diffusion-weighted magnetic resonance imaging (dMRI), homologous auditory dorsal and ventral fiber pathways were identified. Ventral pathways were found to be well conserved in the three primate species analyzed but extended to more anterior regions in humans. In contrast, dorsal pathways showed evolutionary divergence in two aspects: first, dorsal pathways in humans have stronger connections to higher-level auditory regions which extended beyond the corresponding regions in non-human primates; second, left lateralization of dorsal pathways was only found in humans. Moreover, dorsal pathways in marmosets are more similar to those in humans than in macaques. These results demonstrate the evolutionary continuity and divergence of dual auditory pathways in the primate brains, suggesting that the putative neural networks supporting human language processing emerged before the lineage of the New World primates diverged from the Old World primates and continued to parallelly evolve thereafter.

36. Modulate of auditory discrimination performance of autism spectrum disorder mice triggered by optogenetic activation of medial prefrontal cortex to primary auditory cortex circuit

Yoon Kyoung Kim, Jihoon Kim, Jeongyoon Lee and Han Kyoung Choe

Topic areas: memory and cognition correlates of behavior/perception

Auditory cortex Anterior cingulate cortex Autism spectrum disorder

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Autism spectrum disorder (ASD) is a developmental disability characterized by social deficit and repetitive behavior. In addition, intellectual disability, common comorbidity to ASD core symptoms, aggravates the caregivers’ burden by hampering cognitive therapies. To devise a neuromodulation procedure that can rescue learning deficits in the ASD, we first addressed the learning deficits in the ASD mouse model using a go/no-go based pure tone-discrimination task. Cntnap2 knockout mice, a mouse model of ASD, exhibited significant retardation in learning with a similar plateau learning curve to wildtype controls. The prefrontal cortex is known to be important in attention and decision making during the discrimination task while the sensory cortex also shows distinct activity during sensory discrimination learning. Fiber photometry analysis of top-down attention control mediated by the anterior cingulate cortex (ACC) to the primary auditory cortex (Au1) revealed that population calcium transient in the ASD model is abnormally regulated during tone discrimination. In wildtype, the manipulation of ACC to Au1 neurons by optogenetic stimulation bidirectionally enhances or decreases discrimination performance in wildtype mice. This observation inspired us to optogenetically stimulate the ACC-Au1 circuit of ASD during the learning. The optogenetic activation of ACC-Au1 projecting neurons indeed enhances learning efficiency to a level similar to non-stimulated wildtype. In summary, we report that the manipulation of ACC-Au1 neurons bidirectionally modulates discrimination performance. Also found regulation of ACC-Au1 neurons decreases the learning deficit of ASD and possibly suggests its therapeutic potential for intellectual disabilities of ASD.

37. Auditory cortex in awake, freely-moving rats tracks time in trial

Ana Polterovich, Maciej M Jankowski, Johannes Niediek, Alex Kazakov and Israel Nelken

Topic areas: correlates of behavior/perception

Auditory cortex Behavior Electrophysiology Timing Rodents

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Auditory cortex plays an important role in the computations underlying sound localization. Here we study the neural activity in the auditory cortex of freely-moving rats that perform a self-initiated sound localization and identification task. To this end we constructed the Rat Interactive Foraging Facility (RIFF). It consists of a large circular arena with 6 interaction areas (IAs) that have a water port, a food port and two loudspeakers. Rat behavior is monitored online using video tracking and nose-poke identification. Neural responses are recorded using a logger on the head of the animal. In the task studied here, auditory cues consisted of 6 different modified human words, each associated with one IA. When a rat reached the center of the arena, one of the sounds was presented once every 2 seconds from its associated IA, and the rat had to reach the correct IA within 20 seconds in order to collect a reward. Control tasks included pure localization and pure discrimination tasks for the trained rats. The rats learned all tasks rapidly with minimal guidance. They performed best when both the localization and discrimination cues were available, but were able to collect rewards also when either of the cues was missing. Sound-driven neuronal responses were largely as previously described in anesthetized animals, although responses to the same sound presented in active and passive conditions could differ. In addition to the sound-driven responses, we observed large, reproducible slow modulations in firing rates that typically lasted a few seconds (much longer than sound driven responses) and that were locked to self initiated behavioral events before and after sound presentation. These firing rate modulations were often larger than the responses to sounds. The slow modulations were partially correlated with non-auditory, behaviorally-related variables such as speed of motion and head turn direction, but were best explained in many neurons as a slowly-varying function of the time within trial. We conclude that most spiking activity in the auditory cortex during sound-guided behavior tracks the time course of the task rather than the sounds.

38. Learning and exploration by rats in a complex environment

Mousa Karayanni, Yonatan Loewenstein and Israel Nelken

Topic areas: correlates of behavior/perception multisensory processes

Learning Exploration Complex behavior

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

We wanted to study the way freely moving rats explore a complex yet controllable environment. To that purpose we implemented a complex decision task in the Rat Interactive Foraging Facility (RIFF). The RIFF is a large experimental environment that has 6 interaction areas (IAs), in which the rat can poke and receive food and water rewards. To obtain a reward, the rats are required to perform a sequence of pokes in the various IAs in a particular randomly-chosen unmarked order. The task can be described as a multi-state Markov Decision Process (MDP): The states are ordered from the initial state to the final state and are marked with distinct auditory and visual cues. The MDP had one more states than the length of the sequence. In the final state, poking in any of the IAs equally rewarded the rat. All other states are each associated with a one “correct” IA such that poking in it advances the animal to the next state. Poking in any other IA resets the animal to the initial state. The identities of the correct IAs were kept fixed until the animal reached a satisfactory level of performance, and then changed (with no indication). Remarkably, in a 3-state MDP, rats managed to successfully learn up to 5 different sequences within a session of less than 2 hours. Moreover, they learned the correct IA associated with the initial state before learning the correct IA associated with the second state, suggesting that the rats solve the task by learning in each state separately. However, fewer state visits were required to learn the correct IA of the second state than the first. In each state, the probability to find the correct IA location decreased when conditioned on the number of errors, as expected from a random search-pattern with repetitions, but the decrease was faster than expected suggesting an unstructured exploration strategy with a tendency to repeat unsuccessful attempts. In conclusion, rats were able to learn a complex task in the RIFF, behavior was consistent with hierarchical learning and random exploration with some biases in port selection.

39. Serotoninergic Regulation of VIP interneurons and Auditory Learning

Carolyn Sweeney, Maryse Thomas, Kasey Smith, Anna Stewart, Lucas Vattino, Cathryn MacGregor and Anne Takesian

Topic areas: correlates of behavior/perception

VIP Serotonin Interneuron Auditory Cortex

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Auditory perceptual learning induces plasticity in the primary auditory cortex (A1), which can improve hearing perception, but the neural mechanisms that promote these changes are unclear. Neuromodulators such as serotonin (5-HT), acetylcholine, and dopamine can trigger plasticity in the adult cortex. However, little is known about the actions of these neuromodulators within A1 circuits and their function in auditory learning. Here, we focused on 5-HT signaling in mouse A1, its cortical targets, and its effects on auditory perceptual learning. Cortical layer 1 (L1) is a major site for neuromodulatory projections, including the serotonergic raphe nuclei. Our work and others demonstrated that VIP (vasoactive intestinal peptide)-expressing interneurons in L1 robustly express the ionotropic 5-HT receptor, 5HT3A-R. Additionally, they receive bottom-up thalamic input from auditory thalamus. This circuitry suggests that both sensory inputs and 5-HT may engage L1-circuits during learning. To understand how VIP interneurons are activated in vivo by sensory and behavioral stimuli, we expressed the calcium indicator GCaMP6f selectivity in VIP interneurons and used in vivo 2-photon calcium imaging in awake mice to assess the response of these interneurons to a variety of sound stimuli as well as appetitive and aversive reinforcers that are known to activate serotonergic neurons. Our results reveal heterogeneous responses within the VIP population; many neurons were selectively activated by specific, complex sounds or behavioral cues. To understand the function of 5-HT release and VIP activation during auditory perceptual learning, we developed an appetitive Go/No-go auditory frequency discrimination task. Mice showed robust improvements in their perceptual thresholds over the course of three weeks of training. Ongoing fiber photometry studies are monitoring VIP interneuron activity and 5-HT release across perceptual learning using calcium sensor recordings in VIP neurons and signals reported by the fluorescent 5-HT sensor GRAB5HT. Preliminary results show a prominent increase in 5-HT release during rewarded trials as the mice undergo associative learning. After associative learning, an analysis of single trial fluorescent 5-HT transients can discriminate ‘Hit’ versus other trial types in single trials. These ongoing works will help define the dynamics and function of 5-HT release and VIP interneuron activity during perceptual learning.

40. Nonlinear Neural Envelope Tracking: A Mutual Information Approach

Pieter De Clercq, Jonas Vanthornhout, Maaike Vandermosten and Tom Francart

Topic areas: speech and language

auditory processing neural envelope tracking mutual information EEG

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

The human brain tracks the temporal envelope of speech, containing essential cues for speech understanding. Linear models (decoders/temporal response functions) are the most popular tool to study neural envelope tracking, as they provide temporal and spatial information on speech processing. However, information on how speech is processed can be lost since nonlinear relations are precluded. Alternatively, a mutual information (MI) analysis can detect nonlinear relations while retaining temporal and spatial information. In the present study, we directly compare linear models with the MI analysis and investigate whether MI captures nonlinear relations between the brain and the envelope. We analyzed EEG data of 64 participants listening to a story. First, we compared the MI analysis and linear models. Second, we tested whether the MI analysis captures nonlinear components in the data, by first removing all linear components using least-squares regression. Next, the MI analysis was applied to the residual data. Envelope tracking using the MI analysis correlated strongly with outcomes obtained from linear models (r=0.93). Furthermore, temporal and spatial patterns of speech processing were highly similar using both methods. At the single-subject level, we detected significant nonlinear relationships between the EEG and the envelope using the MI analysis. The MI analysis robustly detects nonlinear envelope tracking, beyond limits of linear models. Therefore, we conclude that the MI analysis is a statistically more powerful tool for studying neural envelope tracking. In addition, it retains temporal and spatial characteristics of speech processing, an advantage lost when using more complex (nonlinear) deep neural networks.

41. Encoding of acquired sound-sequence salience by auditory cortical offset responses

Joonyeup Lee and Gideon Rothschild

Topic areas: memory and cognition correlates of behavior/perception neural coding

Auditory Cortex Sound Sequences Offset Responses Neural Coding Learning Two-photon imaging

Fri, 11/11 10:15AM - 12:15PM | Posters 1

Abstract

Behaviorally relevant sounds are often composed of distinct acoustic units organized into specific temporal sequences. The meaning of such sound sequences can therefore be fully recognized only when they have terminated. However, the neural mechanisms underlying the perception of sound sequences remain unclear. Here, we use two-photon calcium imaging in the auditory cortex of behaving mice to test the hypothesis that neural responses to termination of sound sequences (“Off-responses”) encode their acoustic history and behavioral salience. We find that auditory cortical Off-responses encode preceding sound sequences and that learning to associate a sound sequence with a reward induces enhancement of Off-responses relative to responses during the sound sequence (“On-responses”). Furthermore, learning enhances network-level discriminability of sound sequences by Off-responses. Last, learning-induced plasticity of Off-responses but not On-responses lasts to the next day. These findings identify auditory cortical Off-responses as a key neural signature of acquired sound-sequence salience.

42. Sensitivity to Interaural Time Differences in Prosthetic Hearing: What Can Rats Teach Us?

Jan Wh Schnupp, Alexa N Buck, Sarah Buchholz, Theresa A Preyer, Henrike Budig, Felix Kleinschroth and Nicole Roßkothen-Kuhl

Topic areas: novel technologies

cochlear implants deafness binaural hearing interaural time differences

Fri, 11/11 4:00PM - 6:00PM | Posters 2

Abstract

Early deaf human patients whose hearing is restored with bilateral cochlear implants (biCIs) are usually insensitive to interaural time differences (ITDs), an important binaural cue for binaural hearing. This insensitivity has usually been attributed to a lack of auditory input during a presumed sensitive period for the development of normal binaural hearing. However, our group was recently able to show that neonatally deafened (ND) rats who are fitted with biCIs in early adulthood and are given precisely synchronized binaural stimulation from the outset are able to lateralize ITDs with exquisite sensitivity, reaching thresholds of ~50 μs (Rosskothen-Kuhl et al., 2021, eLife doi: 10.7554/eLife.59300). Here we present results from several key follow-on psychoacoustic experiments with our ND biCI rats, which have yielded a number of new and important insights. First, by varying the pulse rate of the binaural stimuli delivered, we were able to show that ITD sensitivity remains surprisingly good for pulse rates of up to 900 pps, but drops sharply at 1800 pps. Electric ITD sensitivity thus declines only at pulse rates higher than the upper limit for acoustic ITDs, and good ITD sensitivity with CIs is achievable at pulse rates used in clinical practice. Second, by independently varying envelope and pulse timing ITDs, we were able to show that ITD discrimination is dominated by the timing of the pulses, and envelope ITDs are essentially useless as a cue under CI stimulation. Third, by independently varying ITDs and ILDs, we were able to show that time-intensity trading ratios for electric hearing are as small as 20 μs/dB. Result 1 indicates that delivering good ITDs via CIs need not be incompatible with the high pulse rates needed for good speech encoding, but results 2 and 3 indicate that the essentially random pulse timing ITDs delivered by current, desynchronized clinical processors are a very significant problem. Pulse timing ITDs would normally be interpreted as powerful lateralization cues, which can confound even very large interaural level difference cues unless the animal becomes desensitized to ITDs.

43. The Impact of Acoustic Environment on Noise Invariance in the Zebra Finch Auditory Cortex

Samantha Moseley, Christof Ferhman, Jonah Weissman and Chad D Meliza

Topic areas: neural coding