Biology subjects

Schnupp, J. W. H.

Publications and source records attributed to Schnupp, J. W. H..

14 recordsLinked to original sources

bioRxiv2024

Evaluating Cochlear Implant Stimulation Strategies Through Wide-field Calcium Imaging of the Auditory Cortex

Cochlear Implants (CI) are an effective neuroprosthesis for humans with profound hearing loss, enabling deaf adults to have phone calls without lipreading and babies to have successful language development. However, CIs have significant limitations in complex hearing situations, motivating the need for further research, including studies in animal models. Here, we demonstrate the usefulness of wide field Ca++ imaging in assessing different CI stimulation strategies. One major challenge in electrophysiology in CI animals lies in excluding the CI electric artifacts from the recording, since they are orders of magnitude larger than the amplitude of action potentials. Also, electrophysiology can rarely sample large areas of neuropil at high spatial resolution. To circumvent these problems, we have set up an imaging system allowing us to monitor neural activity in the auditory cortex (AC) of CI supplied rats using the Ca++ sensitive dye OGB. Here we describe an initial experiment with this setup, in which we recorded cortical responses to 4 different stimulation patterns which were delivered across 3 CI channels to the contralateral ear. We then investigated two parameters that have been shown to affect intelligibility in CI users: pulse rate and relative pulse timing across CI channels. While pulse rate had only a very modest effect on the discriminability of the neural responses, the stimulation mode had a major effect, with simultaneous pulse timing, perhaps surprisingly, allowing much better pattern discrimination than interleaved sampling. The result suggests that allowing collisions of pulses on neighboring channels may not always be detrimental, at least if partial overlaps of pulses, in which anodic and cathodic pulse phases might cancel, are avoided.

neuroscience↗

bioRxiv2023

Rats synchronize predictively to metronomes

Humans easily and naturally synchronize their motor activity to music, a behavior unparalleled by other species. As a consequence of the mystery surrounding its evolutionary and biological origins, there is rapidly growing interest in exploring the capacity of nonhuman species to synchronize motor activity with auditory rhythms. The hallmark observation in human studies is that synchronization is predictive. Given the highly variable behaviors observed in other animals, it is particularly difficult to distinguish a predictive synchronization behavior from one that perhaps resembles it, but relies on simpler strategies. Here, we introduce a novel modeling approach that quantitatively compares candidate strategies for explaining observed behaviors. Eight rats synchronized to metronomes across a range of tempi (0.5-2 Hz), and immediate water reward was delivered whenever they initiated a lick burst within a short time window around beats. We observed a roughly constant baseline lick probability throughout, with a [~]30% modulation of the lick rate around beats. We fitted to the results six candidate models, ranging from an insensitive model assuming that rats lick at random, to predictive models where rats suppress licking between beats for a tempo-dependent duration of time. The predictive model consistently outperformed other models, including a reactive model, demonstrating that rats synchronize predictively to auditory metronomes.

neuroscience↗

bioRxiv2023

Dissociable roles of the auditory midbrain and cortex in processing the statistical features of natural sound textures

It is well established that sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed in auditory subcortical and cortical regions. Here, we compared the neural representation of sound textures in the inferior colliculus (IC), and primary and non-primary auditory cortex (AC) of anesthetized rats with texture morph stimuli which gradually add statistical features of increasingly higher order. We generated texture morphs for a representative subset of 13 sound textures, chosen to span the three principal component dimensions of a corpus of 200 natural texture recordings. For each of the 13 texture types, six different exemplar morphs were synthesized using different random seeds. All exemplars of each texture type have the same long term statistics, but they differ in their acoustic waveforms. Meanwhile, different texture types differ in statistical features as well as waveforms. An analysis of transient and ongoing multi-unit responses to our stimulus set showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent, but only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of "texture-type tuning" in the IC, but this was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses classification performance remained constant, and consistently lower, than for the IC. These results argue against the idea that AC plays an important role in encoding statistical features of natural sound textures.

physiology↗

bioRxiv2023

Hierarchical Deviant Processing in Auditory Cortex of Awake Mice

Detecting patterns, and noticing unexpected pattern changes, in the environment is a vital aspect of sensory processing. Adaptation and prediction error responses are two components of neural processing related to these tasks, and previous studies in the auditory system in rodents show that these two components are partially dissociable in terms of the topography and latency of neural responses to sensory deviants. However, many previous studies have focused on repetitions of single stimuli, such as pure tones, which have limited ecological validity. In this study, we tested whether the auditory cortical activity shows adaptation to repetition of more complex sound patterns (bisyllabic pairs). Specifically, we compared neural responses to violations of sequences based on single stimulus probability only, against responses to more complex violations based on stimulus order. We employed an auditory oddball paradigm and monitored the auditory cortex (ACtx) activity of awake mice (N=8) using wide-field calcium imaging. We found that cortical responses were sensitive both to single stimulus probabilities and to more global stimulus patterns, as mismatch signals were elicited following both substitution deviants and transposition deviants. Notably, A2 area elicited larger mismatch signaling to those deviants than primary ACtx (A1), which suggests a hierarchical gradient of prediction error signaling in the auditory cortex. Such a hierarchical gradient was observed for late but not early peaks of calcium transients to deviants, suggesting that the late part of the deviant response may reflect prediction error signaling in response to more complex sensory pattern violations.

neuroscience↗

bioRxiv2022

"What" and "When" Predictions Modulate Auditory Processing in a Contextually Specific Manner

Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli (i.e., "what" it is) and their timing (i.e., "when" it will occur), both of which are known to interactively modulate sensory processing. In real-world stimulus streams, regularities also occur contextually - e.g. predictions of individual notes vs. melodic contour in music. However, it is unknown whether the brain integrates predictions in a contextually congruent manner (e.g., if slower "when" predictions selectively interact with complex "what" predictions), and whether integrating predictions of simple vs. complex features rely on dissociable neural correlates. To address these questions, our study employed "what" and "when" violations at different levels - single tones (elements) vs. tone pairs (chunks) - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N=20) performing a repetition detection task. Our results reveal that "what" and "when" predictions interactively modulated stimulus-evoked response amplitude in a contextually congruent manner, but that these modulations were shared between contexts in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" prediction selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network. Taken together, these results suggest that the brain integrates different predictions with a high degree of contextual specificity, but in a shared and distributed cortical network. Significance statementPredictions of stimulus features, present in different statistically-regular contexts in the environment, are crucial to forming adaptive behavior. However, it is unknown if the brain integrates predictions selectively according to such contextual differences. By recording human electroencephalography during experimental manipulations of time-based and content-based predictions, we found that those predictions interactively modulated neural activity in a contextually congruent manner, such that local (vs. global) time-based predictions modulated content-based predictions of sequence elements (vs. chunks). These modulations were shared between contextual levels in terms of the spatiotemporal distribution of neural activity. This suggests that the brain integrates different predictions with a high degree of contextual specificity, but in a shared and distributed cortical network.

neuroscience↗

bioRxiv2022

Omission responses in field potentials but not spikes in rat auditory cortex

Non-invasive recordings of gross neural activity in humans often show responses to omitted stimuli in steady trains of identical stimuli. This has been taken as evidence for the neural coding of prediction or prediction error. However, evidence for such omission responses from invasive recordings of cellular-scale responses in animal models is scarce. Here, we sought to characterise omission responses using extracellular recordings in the auditory cortex of anaesthetised rats. We profiled omission responses across local field potentials (LFP), analogue multiunit activity (AMUA), and single/multi-unit spiking activity, using stimuli that were fixed-rate trains of acoustic noise bursts where 5% of bursts were randomly omitted. Significant omission responses were observed in LFP and AMUA signals, but not in spiking activity. These omission responses had a lower amplitude and longer latency than burst-evoked sensory responses, and omission response amplitude increased as a function of the number of preceding bursts. Contrary to theories of neural entrainment, rhythmic stimulus presentation did not increase low-frequency phase-locking of neural activity specific to the stimulus presentation rate. Together, our findings show that omission responses are observed in LFP and AMUA signals, with laminar specificity, but are not observed in spiking activity, and do not show evidence for low-frequency phase locking. This has implications for models of cortical processing that require many neurons to encode prediction error in their spike output, and may have some consistency with representation of error in dendrites electrotonically distant from the soma.

neuroscience↗

bioRxiv2021

The precedence effect in spatial hearing emerges only late in the auditory pathway

BackgroundTo localize sound sources accurately in a reverberant environment, human binaural hearing strongly favors analyzing the initial wave front of sounds. Behavioral studies of this "precedence effect" have so far largely been confined to human subjects, limiting the scope of complementary physiological approaches. Similarly, physiological studies have mostly looked at neural responses in the inferior colliculus, or used modeling of cochlear mechanics in an attempt to identify likely underlying mechanisms. Studies capable of providing a direct comparison of neural coding and behavioral measures of sound localization under the precedence effect are lacking. ResultsWe adapted a "temporal weighting function" paradigm for use in laboratory rats. The animals learned to lateralize click trains in which each click in the train had a different interaural time difference. Computing the "perceptual weight" of each click in the train revealed a strong onset bias, very similar to that reported for humans. Follow-on electrocorticographic recording experiments revealed that onset weighting of ITDs is a robust feature of the cortical population response, but interestingly it often fails to manifest at individual cortical recording sites. ConclusionWhile previous studies suggested that the precedence effect may be caused by cochlear mechanics or inhibitory circuitry in the brainstem and midbrain, our results indicate that the precedence effect is not fully developed at the level of individual recording sites in auditory cortex, but robust and consistent precedence effects are observable at the level of cortical population responses. This indicates that the precedence effect is significantly "higher order" than has hitherto been assumed.

neuroscience↗

bioRxiv2021

Interaural Time Difference Tuning in the Rat Inferior Colliculus is Predictive of Behavioral Sensitivity

Recent studies have shown that rats are a useful model for binaural cochlear implant (CI) research, with behavioral sensitivity to interaural time differences (ITDs) of CI stimuli which are better than those of human patients. Here, we characterize ITD tuning in the rat inferior colliculus (IC) and explore whether quality of tuning can predict behavioral performance. We recorded IC responses to stimuli of varying pulse rates and envelope types and quantified both mutual information (MI) and neural d' as measures of ITD sensitivity. Neural d' values paralleled behavioral ones, declining with increasing click rates or when envelopes changed from rectangular to Hanning windows. While MI values increased with experience, neural d' did not. However, neural d' values correlated much better with behavioral performance than MI. Thus, neural d' appears to be a particularly well suited to predicting how stimulus parameters will impact behavioral performance.

neuroscience↗

bioRxiv2020

Memory Transfer of Random Time Patterns Across Modalities

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, temporal patterns implicitly learned within one modality can also be recognised in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers (N=24, 12 females, 12 males) using electroencephalography (EEG), while participants were exposed to brief sequences of randomly-timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment, enabling implicit learning. Replicating previous behavioural findings, we showed that participants benefit from temporal information learned in audition, and that they can apply this information to stimuli presented in vision. Such memory transfer was not observed from vision to audition. However, using an analysis of EEG response learning curves, we showed that learning temporal structures both within and across modalities modulates single-trial EEG response amplitudes in both conditions (audition to vision and vision to audition). Interestingly, the neural correlates of temporal learning within modalities relied on modality-specific brain regions, while learning transfer affected activity in frontal regions, suggesting distinct mechanisms. The cross-modal effect could be linked to frontal beta-band activity. The neural effects of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. Thus, both modality-specific mechanisms for learning of temporal information, and general mechanisms which mediate learning transfer across modalities, have distinct physiological signatures that are observable in the EEG.

neuroscience↗

bioRxiv2020

Neural correlates of auditory pattern learning in the auditory cortex

Learning of new auditory stimuli requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models.

neuroscience↗

bioRxiv2020

Exploring the distribution of statistical feature parameters for natural sound textures

Sounds like "running water" and "buzzing bees" are classes of sounds which are a collective result of many similar acoustic events and are known as "sound textures". Recent psychoacoustic study using sound textures by [1] reported that natural sounding textures can be synthesized from white noise by imposing statistical features such as marginals and correlations computed from the outputs of cochlear models responding to the textures. The outputs being the envelopes of bandpass filter responses, the cochlear envelope. This suggests that the perceptual qualities of many natural sounds derive directly from such statistical features, and raises the question of how these statistical features are distributed in the acoustic environment. To address this question, we collected a corpus of 200 sound textures from public online sources and analyzed the distributions of the textures marginal statistics (mean, variance, skew, and kurtosis), cross-frequency correlations and modulation power statistics. A principal component analysis of these parameters revealed a great deal of redundancy in the texture parameters. For example, just two marginal principal components, which can be thought of as measuring the sparseness or burstiness of a texture, capture as much as 66% of the variance of the 128 dimensional marginal parameter space, while the first two principal components of cochlear correlations capture as much as 90% of the variance in over 1000 correlation parameters. Knowledge of the statistical distributions documented here may help guide the choice of acoustic stimuli with high ecological validity in future research.

neuroscience↗

bioRxiv2019

Selective attention to sound features mediates cross-modal activation of visual cortices

Contemporary schemas of brain organization now include multisensory processes both in low-level cortices as well as at early stages of stimulus processing. Evidence has also accumulated showing that unisensory stimulus processing can result in cross-modal effects. For example, task-irrelevant and lateralized sounds can activate visual cortices; a phenomenon referred to as the auditory-evoked contralateral occipital positivity (ACOP). Some claim this is an example of automatic attentional capture in visual cortices. Other results, however, indicate that context may play a determinant role. Here, we investigated whether selective attention to spatial features of sounds is a determining factor in eliciting the ACOP. We recorded high-density auditory evoked potentials (AEPs) while participants selectively attended and discriminated sounds according to four possible stimulus attributes: location, pitch, speaker identity or syllable. Sound acoustics were held constant, and their location was always equiprobable (50% left, 50% right). The only manipulation was to which sound dimension participants attended. We analysed the AEP data from healthy participants within an electrical neuroimaging framework. The presence of sound-elicited activations of visual cortices depended on the to-be-discriminated, goal-based dimension. The ACOP was elicited only when participants were required to discriminate sound location, but not when they attended to any of the non-spatial features. These results provide a further indication that the ACOP is not automatic. Moreover, our findings showcase the interplay between task-relevance and spatial (un)predictability in determining the presence of the cross-modal activation of visual cortices.

neuroscience↗

bioRxiv2018

Beat-Relevant Signals in Auditory Cortical Responses to Musical Excerpts

Musical beat perception is widely regarded as a high-level ability involving widespread coordination across brain areas, but how low-level auditory processing must necessarily shape these dynamics, and therefore perception, remains unexplored. Previous cross-species work suggested that beat perception in simple rhythmic noise bursts is shaped by neural transients in the ascending sensory pathway. Here, we found that low-level processes even substantially explain the emergence of beat in real music. Firing rates in the rat auditory cortex in response to twenty musical excerpts were on average higher on the beat than off the beat tapped by human listeners. This \"neural emphasis\" distinguished the perceived beat from alternative interpretations, was predictive of the degree of consensus across listeners, and was accounted for by a spectrotemporal receptive field model. These findings indicate that low-level auditory processing may have a stronger influence on the location and clarity of the beat in music than previously thought.

neuroscience↗

bioRxiv2017

Sensory cortex is optimised for prediction of future input

Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimised to represent features in the recent past of sensory input that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few video or audio frames in clips of natural scenes. The networks developed receptive fields that closely matched those of real cortical neurons, including the oriented spatial tuning of primary visual cortex, the frequency selectivity of primary auditory cortex and, most notably, in their temporal tuning properties. Furthermore, the better a network predicted future inputs the more closely its receptive fields tended to resemble those in the brain. This suggests that sensory processing is optimised to extract those features with the most capacity to predict future input.\n\nImpact statementPrediction of future input explains diverse neural tuning properties in sensory cortex.

neuroscience↗