scholarly journals Recurrent network dynamics shape direction selectivity in primary auditory cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Destinee A. Aponte ◽  
Gregory Handy ◽  
Amber M. Kline ◽  
Hiroaki Tsukano ◽  
Brent Doiron ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Vocal Communication ◽  
Network Dynamics ◽  
Charge Asymmetry ◽  
Primary Auditory Cortex ◽  
Theoretical Models ◽  
Recurrent Network ◽  
Direction Selectivity ◽  
Complex Sounds ◽  
Recurrent Network Dynamics

AbstractDetecting the direction of frequency modulation (FM) is essential for vocal communication in both animals and humans. Direction-selective firing of neurons in the primary auditory cortex (A1) has been classically attributed to temporal offsets between feedforward excitatory and inhibitory inputs. However, it remains unclear how cortical recurrent circuitry contributes to this computation. Here, we used two-photon calcium imaging and whole-cell recordings in awake mice to demonstrate that direction selectivity is not caused by temporal offsets between synaptic currents, but by an asymmetry in total synaptic charge between preferred and non-preferred directions. Inactivation of cortical somatostatin-expressing interneurons (SOM cells) reduced direction selectivity, revealing its cortical contribution. Our theoretical models showed that charge asymmetry arises due to broad spatial topography of SOM cell-mediated inhibition which regulates signal amplification in strongly recurrent circuitry. Together, our findings reveal a major contribution of recurrent network dynamics in shaping cortical tuning to behaviorally relevant complex sounds.

scholarly journals FM-selective Networks in Human Auditory Cortex Revealed Using fMRI and Multivariate Pattern Classification

2012 ◽  
Vol 24 (9) ◽  
pp. 1896-1907 ◽  
Author(s):  
I-Hui Hsieh ◽  
Paul Fillmore ◽  
Feng Rong ◽  
Gregory Hickok ◽  
Kourosh Saberi
Keyword(s):  
Auditory Cortex ◽  
Pattern Analysis ◽  
Primary Auditory Cortex ◽  
Brain Regions ◽  
Direction Selectivity ◽  
Multivariate Pattern Analysis ◽  
Acoustic Feature ◽  
Complex Sounds ◽  
Human Auditory Cortex ◽  
Multivariate Pattern

Frequency modulation (FM) is an acoustic feature of nearly all complex sounds. Directional FM sweeps are especially pervasive in speech, music, animal vocalizations, and other natural sounds. Although the existence of FM-selective cells in the auditory cortex of animals has been documented, evidence in humans remains equivocal. Here we used multivariate pattern analysis to identify cortical selectivity for direction of a multitone FM sweep. This method distinguishes one pattern of neural activity from another within the same ROI, even when overall level of activity is similar, allowing for direct identification of FM-specialized networks. Standard contrast analysis showed that despite robust activity in auditory cortex, no clusters of activity were associated with up versus down sweeps. Multivariate pattern analysis classification, however, identified two brain regions as selective for FM direction, the right primary auditory cortex on the supratemporal plane and the left anterior region of the superior temporal gyrus. These findings are the first to directly demonstrate existence of FM direction selectivity in the human auditory cortex.

Sound frequency representation in primary auditory cortex is level tolerant for moderately loud, complex sounds

2011 ◽  
Vol 106 (2) ◽  
pp. 1016-1027 ◽  
Author(s):  
Martin Pienkowski ◽  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Field Potential ◽  
Primary Auditory Cortex ◽  
Sound Level ◽  
Sound Frequency ◽  
Frequency Resolution ◽  
Neural Population ◽  
Complex Sounds ◽  
Individual Unit ◽  
Nonlinear Processing

The distribution of neuronal characteristic frequencies over the area of primary auditory cortex (AI) roughly reflects the tonotopic organization of the cochlea. However, because the area of AI activated by any given sound frequency increases erratically with sound level, it has generally been proposed that frequency is represented in AI not with a rate-place code but with some more complex, distributed code. Here, on the basis of both spike and local field potential (LFP) recordings in the anesthetized cat, we show that the tonotopic representation in AI is much more level tolerant when mapped with spectrotemporally dense tone pip ensembles rather than with individually presented tone pips. That is, we show that the tuning properties of individual unit and LFP responses are less variable with sound level under dense compared with sparse stimulation, and that the spatial frequency resolution achieved by the AI neural population at moderate stimulus levels (65 dB SPL) is better with densely than with sparsely presented sounds. This implies that nonlinear processing in the central auditory system can compensate (in part) for the level-dependent coding of sound frequency in the cochlea, and suggests that there may be a functional role for the cortical tonotopic map in the representation of complex sounds.

scholarly journals Influence of Context and Behavior on Stimulus Reconstruction From Neural Activity in Primary Auditory Cortex

2009 ◽  
Vol 102 (6) ◽  
pp. 3329-3339 ◽  
Author(s):  
Nima Mesgarani ◽  
Stephen V. David ◽  
Jonathan B. Fritz ◽  
Shihab A. Shamma
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Neural Population ◽  
Stimulus Context ◽  
Sensory Stimuli ◽  
Complex Sounds ◽  
Population Responses ◽  
Stimulus Reconstruction

Population responses of cortical neurons encode considerable details about sensory stimuli, and the encoded information is likely to change with stimulus context and behavioral conditions. The details of encoding are difficult to discern across large sets of single neuron data because of the complexity of naturally occurring stimulus features and cortical receptive fields. To overcome this problem, we used the method of stimulus reconstruction to study how complex sounds are encoded in primary auditory cortex (AI). This method uses a linear spectro-temporal model to map neural population responses to an estimate of the stimulus spectrogram, thereby enabling a direct comparison between the original stimulus and its reconstruction. By assessing the fidelity of such reconstructions from responses to modulated noise stimuli, we estimated the range over which AI neurons can faithfully encode spectro-temporal features. For stimuli containing statistical regularities (typical of those found in complex natural sounds), we found that knowledge of these regularities substantially improves reconstruction accuracy over reconstructions that do not take advantage of this prior knowledge. Finally, contrasting stimulus reconstructions under different behavioral states showed a novel view of the rapid changes in spectro-temporal response properties induced by attentional and motivational state.

Layer-specific excitatory circuits differentially control recurrent network dynamics in the neocortex

2013 ◽  
Vol 16 (2) ◽  
pp. 227-234 ◽  
Author(s):  
Riccardo Beltramo ◽  
Giulia D'Urso ◽  
Marco Dal Maschio ◽  
Pasqualina Farisello ◽  
Serena Bovetti ◽  
...  
Keyword(s):  
Network Dynamics ◽  
Recurrent Network ◽  
Recurrent Network Dynamics

Neural Population Coding of Natural Sounds in Non-flying Mammals

2017 ◽  
Author(s):  
Israel Nelken
Keyword(s):  
Auditory Cortex ◽  
Auditory System ◽  
Cortical Neurons ◽  
Dominant Role ◽  
Primary Auditory Cortex ◽  
Population Coding ◽  
Neural Population ◽  
Good Effect ◽  
Natural Sounds ◽  
Complex Sounds

Understanding the principles by which sensory systems represent natural stimuli is one of the holy grails of neuroscience. In the auditory system, the study of the coding of natural sounds has a particular prominence. Indeed, the relationships between neural responses to simple stimuli (usually pure tone bursts)—often used to characterize auditory neurons—and complex sounds (in particular natural sounds) may be complex. Many different classes of natural sounds have been used to study the auditory system. Sound families that researchers have used to good effect in this endeavor include human speech, species-specific vocalizations, an “acoustic biotope” selected in one way or another, and sets of artificial sounds that mimic important features of natural sounds. Peripheral and brainstem representations of natural sounds are relatively well understood. The properties of the peripheral auditory system play a dominant role, and further processing occurs mostly within the frequency channels determined by these properties. At the level of the inferior colliculus, the highest brainstem station, representational complexity increases substantially due to the convergence of multiple processing streams. Undoubtedly, the most explored part of the auditory system, in term of responses to natural sounds, is the primary auditory cortex. In spite of over 50 years of research, there is still no commonly accepted view of the nature of the population code for natural sounds in the auditory cortex. Neurons in the auditory cortex are believed by some to be primarily linear spectro-temporal filters, by others to respond to conjunctions of important sound features, or even to encode perceptual concepts such as “auditory objects.” Whatever the exact mechanism is, many studies consistently report a substantial increase in the variability of the response patterns of cortical neurons to natural sounds. The generation of such variation may be the main contribution of auditory cortex to the coding of natural sounds.

Frequency-Modulation Encoding in the Primary Auditory Cortex of the Awake Owl Monkey

2007 ◽  
Vol 98 (4) ◽  
pp. 2182-2195 ◽  
Author(s):  
Craig A. Atencio ◽  
David T. Blake ◽  
Fabrizio Strata ◽  
Steven W. Cheung ◽  
Michael M. Merzenich ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
World Monkey ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Direction Selectivity ◽  
Neural Responses ◽  
Population Distributions ◽  
Spectrotemporal Receptive Fields ◽  
Owl Monkey ◽  
Highly Correlated

Many communication sounds, such as New World monkey twitter calls, contain frequency-modulated (FM) sweeps. To determine how this prominent vocalization element is represented in the auditory cortex we examined neural responses to logarithmic FM sweep stimuli in the primary auditory cortex (AI) of two awake owl monkeys. Using an implanted array of microelectrodes we quantitatively characterized neuronal responses to FM sweeps and to random tone-pip stimuli. Tone-pip responses were used to construct spectrotemporal receptive fields (STRFs). Classification of FM sweep responses revealed few neurons with high direction and speed selectivity. Most neurons responded to sweeps in both directions and over a broad range of sweep speeds. Characteristic frequency estimates from FM responses were highly correlated with estimates from STRFs, although spectral receptive field bandwidth was consistently underestimated by FM stimuli. Predictions of FM direction selectivity and best speed from STRFs were significantly correlated with observed FM responses, although some systematic discrepancies existed. Last, the population distributions of FM responses in the awake owl monkey were similar to, although of longer temporal duration than, those in the anesthetized squirrel monkeys.

Topography and synaptic shaping of direction selectivity in primary auditory cortex

Nature ◽  
2003 ◽  
Vol 424 (6945) ◽  
pp. 201-205 ◽  
Author(s):  
Li I. Zhang ◽  
Andrew Y. Y. Tan ◽  
Christoph E. Schreiner ◽  
Michael M. Merzenich
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Direction Selectivity

scholarly journals Synaptic Mechanisms for Bandwidth Tuning in Awake Mouse Primary Auditory Cortex

2018 ◽  
Vol 29 (7) ◽  
pp. 2998-3009 ◽  
Author(s):  
Haifu Li ◽  
Feixue Liang ◽  
Wen Zhong ◽  
Linqing Yan ◽  
Lucas Mesik ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Cell Voltage ◽  
Inhibitory Neurons ◽  
Complex Sounds ◽  
Excitatory Neurons ◽  
Layer 4 ◽  
Bandwidth Tuning ◽  
Spatial Size

Abstract Spatial size tuning in the visual cortex has been considered as an important neuronal functional property for sensory perception. However, an analogous mechanism in the auditory system has remained controversial. In the present study, cell-attached recordings in the primary auditory cortex (A1) of awake mice revealed that excitatory neurons can be categorized into three types according to their bandwidth tuning profiles in response to band-passed noise (BPN) stimuli: nonmonotonic (NM), flat, and monotonic, with the latter two considered as non-tuned for bandwidth. The prevalence of bandwidth-tuned (i.e., NM) neurons increases significantly from layer 4 to layer 2/3. With sequential cell-attached and whole-cell voltage-clamp recordings from the same neurons, we found that the bandwidth preference of excitatory neurons is largely determined by the excitatory synaptic input they receive, and that the bandwidth selectivity is further enhanced by flatly tuned inhibition observed in all cells. The latter can be attributed at least partially to the flat tuning of parvalbumin inhibitory neurons. The tuning of auditory cortical neurons for bandwidth of BPN may contribute to the processing of complex sounds.

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