Neural Representation of Sound Patterns in the Auditory Cortex of Monkeys

2002 ◽  
Author(s):  
Michael Brosch ◽  
Henning Scheich
Keyword(s):  
Auditory Cortex ◽  
Neural Representation ◽  
Sound Patterns

scholarly journals Disparity in interaural time difference improves the accuracy of neural representations of individual concurrent narrowband sounds in rat inferior colliculus and auditory cortex

2020 ◽  
Vol 123 (2) ◽  
pp. 695-706
Author(s):  
Lu Luo ◽  
Na Xu ◽  
Qian Wang ◽  
Liang Li
Keyword(s):  
Auditory Cortex ◽  
Inferior Colliculus ◽  
Interaural Time Difference ◽  
Critical Role ◽  
Low Frequency ◽  
Time Difference ◽  
Neural Representation ◽  
Frequency Bands ◽  
Neural Segregation ◽  
Peripheral Auditory System

The central mechanisms underlying binaural unmasking for spectrally overlapping concurrent sounds, which are unresolved in the peripheral auditory system, remain largely unknown. In this study, frequency-following responses (FFRs) to two binaurally presented independent narrowband noises (NBNs) with overlapping spectra were recorded simultaneously in the inferior colliculus (IC) and auditory cortex (AC) in anesthetized rats. The results showed that for both IC FFRs and AC FFRs, introducing an interaural time difference (ITD) disparity between the two concurrent NBNs enhanced the representation fidelity, reflected by the increased coherence between the responses evoked by double-NBN stimulation and the responses evoked by single NBNs. The ITD disparity effect varied across frequency bands, being more marked for higher frequency bands in the IC and lower frequency bands in the AC. Moreover, the coherence between IC responses and AC responses was also enhanced by the ITD disparity, and the enhancement was most prominent for low-frequency bands and the IC and the AC on the same side. These results suggest a critical role of the ITD cue in the neural segregation of spectrotemporally overlapping sounds. NEW & NOTEWORTHY When two spectrally overlapped narrowband noises are presented at the same time with the same sound-pressure level, they mask each other. Introducing a disparity in interaural time difference between these two narrowband noises improves the accuracy of the neural representation of individual sounds in both the inferior colliculus and the auditory cortex. The lower frequency signal transformation from the inferior colliculus to the auditory cortex on the same side is also enhanced, showing the effect of binaural unmasking.

scholarly journals Cortical Representations of Speech in a Multi-talker Auditory Scene

2017 ◽  
Author(s):  
Krishna C. Puvvada ◽  
Jonathan Z. Simon
Keyword(s):  
Auditory Cortex ◽  
Human Subjects ◽  
Higher Order ◽  
Neural Representation ◽  
Cortical Areas ◽  
Auditory Scene ◽  
Global Representation ◽  
Stimulus Reconstruction ◽  
Background Object ◽  
Cortical Representations

AbstractThe ability to parse a complex auditory scene into perceptual objects is facilitated by a hierarchical auditory system. Successive stages in the hierarchy transform an auditory scene of multiple overlapping sources, from peripheral tonotopically-based representations in the auditory nerve, into perceptually distinct auditory-objects based representation in auditory cortex. Here, using magnetoencephalography (MEG) recordings from human subjects, both men and women, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in distinct hierarchical stages of auditory cortex. Using systems-theoretic methods of stimulus reconstruction, we show that the primary-like areas in auditory cortex contain dominantly spectro-temporal based representations of the entire auditory scene. Here, both attended and ignored speech streams are represented with almost equal fidelity, and a global representation of the full auditory scene with all its streams is a better candidate neural representation than that of individual streams being represented separately. In contrast, we also show that higher order auditory cortical areas represent the attended stream separately, and with significantly higher fidelity, than unattended streams. Furthermore, the unattended background streams are more faithfully represented as a single unsegregated background object rather than as separated objects. Taken together, these findings demonstrate the progression of the representations and processing of a complex acoustic scene up through the hierarchy of human auditory cortex.Significance StatementUsing magnetoencephalography (MEG) recordings from human listeners in a simulated cocktail party environment, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in separate hierarchical stages of auditory cortex. We show that the primary-like areas in auditory cortex use a dominantly spectro-temporal based representation of the entire auditory scene, with both attended and ignored speech streams represented with almost equal fidelity. In contrast, we show that higher order auditory cortical areas represent an attended speech stream separately from, and with significantly higher fidelity than, unattended speech streams. Furthermore, the unattended background streams are represented as a single undivided background object rather than as distinct background objects.

scholarly journals Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex

eNeuro ◽  
2016 ◽  
Vol 3 (3) ◽  
pp. ENEURO.0071-16.2016 ◽  
Author(s):  
Yonatan I. Fishman ◽  
Christophe Micheyl ◽  
Mitchell Steinschneider
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Neural Representation

scholarly journals A complex feature-based representation of vocalizations emerges in the superficial layers of primary auditory cortex

2021 ◽  
Author(s):  
Pilar Montes-Lourido ◽  
Manaswini Kar ◽  
Stephen V David ◽  
Srivatsun Sadagopan
Keyword(s):  
Auditory Cortex ◽  
Auditory Processing ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Neural Representation ◽  
Specific Information ◽  
Intermediate Step ◽  
Stimulus Information ◽  
Feature Selectivity ◽  
Feature Based

Early in auditory processing, neural responses faithfully reflect acoustic input. At higher stages of auditory processing, however, neurons become selective for particular call types, eventually leading to specialized regions of cortex that preferentially process calls at the highest auditory processing stages. We previously proposed that an intermediate step in how non-selective responses are transformed into call-selective responses is the detection of informative call features. But how neural selectivity for informative call features emerges from non-selective inputs, whether feature selectivity gradually emerges over the processing hierarchy, and how stimulus information is represented in non-selective and feature-selective populations remain open questions. In this study, using unanesthetized guinea pigs, a highly vocal and social rodent, as an animal model, we characterized the neural representation of calls in three auditory processing stages: the thalamus (vMGB), and thalamorecipient (L4) and superficial layers (L2/3) of primary auditory cortex (A1). We found that neurons in vMGB and A1 L4 did not exhibit call-selective responses and responded throughout the call durations. However, A1 L2/3 neurons showed high call-selectivity with about a third of neurons responding to only one or two call types. These A1 L2/3 neurons only responded to restricted portions of calls suggesting that they were highly selective for call features. Receptive fields of these A1 L2/3 neurons showed complex spectrotemporal structures that could underlie their high call feature selectivity. Information theoretic analysis revealed that in A1 L4 stimulus information was distributed over the population and was spread out over the call durations. In contrast, in A1 L2/3, individual neurons showed brief bursts of high stimulus-specific information, and conveyed high levels of information per spike. These data demonstrate that a transformation in the neural representation of calls occurs between A1 L4 and A1 L2/3, leading to the emergence of a feature-based representation of calls in A1 L2/3. Our data thus suggest that observed cortical specializations for call processing emerge in A1, and set the stage for further mechanistic studies.

scholarly journals Representation of Dynamic Interaural Phase Difference in Auditory Cortex of Awake Rhesus Macaques

2009 ◽  
Vol 101 (4) ◽  
pp. 1781-1799 ◽  
Author(s):  
Brian H. Scott ◽  
Brian J. Malone ◽  
Malcolm N. Semple
Keyword(s):  
Auditory Cortex ◽  
Phase Difference ◽  
Rhesus Macaques ◽  
Discharge Rate ◽  
Auditory Pathway ◽  
Neural Representation ◽  
Characteristic Analysis ◽  
Binaural Cues ◽  
Interaural Phase ◽  
Interaural Phase Difference

Neurons in auditory cortex of awake primates are selective for the spatial location of a sound source, yet the neural representation of the binaural cues that underlie this tuning remains undefined. We examined this representation in 283 single neurons across the low-frequency auditory core in alert macaques, trained to discriminate binaural cues for sound azimuth. In response to binaural beat stimuli, which mimic acoustic motion by modulating the relative phase of a tone at the two ears, these neurons robustly modulate their discharge rate in response to this directional cue. In accordance with prior studies, the preferred interaural phase difference (IPD) of these neurons typically corresponds to azimuthal locations contralateral to the recorded hemisphere. Whereas binaural beats evoke only transient discharges in anesthetized cortex, neurons in awake cortex respond throughout the IPD cycle. In this regard, responses are consistent with observations at earlier stations of the auditory pathway. Discharge rate is a band-pass function of the frequency of IPD modulation in most neurons (73%), but both discharge rate and temporal synchrony are independent of the direction of phase modulation. When subjected to a receiver operator characteristic analysis, the responses of individual neurons are insufficient to account for the perceptual acuity of these macaques in an IPD discrimination task, suggesting the need for neural pooling at the cortical level.

scholarly journals Neural Coding of Periodicity in Marmoset Auditory Cortex

2010 ◽  
Vol 103 (4) ◽  
pp. 1809-1822 ◽  
Author(s):  
Daniel Bendor ◽  
Xiaoqin Wang
Keyword(s):  
Auditory Cortex ◽  
Acoustic Signal ◽  
Repetition Rate ◽  
Neural Coding ◽  
Neural Representation ◽  
Acoustic Feature ◽  
Musical Scale ◽  
Pitch Processing ◽  
Temporal Regularity ◽  
Acoustic Stimuli

Pitch, our perception of how high or low a sound is on a musical scale, crucially depends on a sound's periodicity. If an acoustic signal is temporally jittered so that it becomes aperiodic, the pitch will no longer be perceivable even though other acoustical features that normally covary with pitch are unchanged. Previous electrophysiological studies investigating pitch have typically used only periodic acoustic stimuli, and as such these studies cannot distinguish between a neural representation of pitch and an acoustical feature that only correlates with pitch. In this report, we examine in the auditory cortex of awake marmoset monkeys ( Callithrix jacchus) the neural coding of a periodicity's repetition rate, an acoustic feature that covaries with pitch. We first examine if individual neurons show similar repetition rate tuning for different periodic acoustic signals. We next measure how sensitive these neural representations are to the temporal regularity of the acoustic signal. We find that neurons throughout auditory cortex covary their firing rate with the repetition rate of an acoustic signal. However, similar repetition rate tuning across acoustic stimuli and sensitivity to temporal regularity were generally only observed in a small group of neurons found near the anterolateral border of primary auditory cortex, the location of a previously identified putative pitch processing center. These results suggest that although the encoding of repetition rate is a general component of auditory cortical processing, the neural correlate of periodicity is confined to a special class of pitch-selective neurons within the putative pitch processing center of auditory cortex.

Spectro-Temporal Response Field Characterization With Dynamic Ripples in Ferret Primary Auditory Cortex

2001 ◽  
Vol 85 (3) ◽  
pp. 1220-1234 ◽  
Author(s):  
Didier A. Depireux ◽  
Jonathan Z. Simon ◽  
David J. Klein ◽  
Shihab A. Shamma
Keyword(s):  
Transfer Function ◽  
Auditory Cortex ◽  
Cross Sections ◽  
Primary Auditory Cortex ◽  
Neural Representation ◽  
Temporal Response ◽  
Spectral Functions ◽  
Linear Dynamics ◽  
Complex Response ◽  
Response Field

To understand the neural representation of broadband, dynamic sounds in primary auditory cortex (AI), we characterize responses using the spectro-temporal response field (STRF). The STRF describes, predicts, and fully characterizes the linear dynamics of neurons in response to sounds with rich spectro-temporal envelopes. It is computed from the responses to elementary “ripples,” a family of sounds with drifting sinusoidal spectral envelopes. The collection of responses to all elementary ripples is the spectro-temporal transfer function. The complex spectro-temporal envelope of any broadband, dynamic sound can expressed as the linear sum of individual ripples. Previous experiments using ripples with downward drifting spectra suggested that the transfer function is separable, i.e., it is reducible into a product of purely temporal and purely spectral functions. Here we measure the responses to upward and downward drifting ripples, assuming reparability within each direction, to determine if the total bidirectional transfer function is fully separable. In general, the combined transfer function for two directions is not symmetric, and hence units in AI are not, in general, fully separable. Consequently, many AI units have complex response properties such as sensitivity to direction of motion, though most inseparable units are not strongly directionally selective. We show that for most neurons, the lack of full separability stems from differences between the upward and downward spectral cross-sections but not from the temporal cross-sections; this places strong constraints on the neural inputs of these AI units.

scholarly journals Encoding frequency contrast in primate auditory cortex

2014 ◽  
Vol 111 (11) ◽  
pp. 2244-2263 ◽  
Author(s):  
Brian J. Malone ◽  
Brian H. Scott ◽  
Malcolm N. Semple
Keyword(s):  
Auditory Cortex ◽  
Frequency Modulation ◽  
Carrier Frequency ◽  
Temporal Dynamics ◽  
Frequency Tuning ◽  
Modulation Depth ◽  
Average Rate ◽  
Spike Timing ◽  
Neural Representation ◽  
Response Dynamics

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This “dynamic hyperacuity” suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing.

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