Properties of Correlated Neural Activity Clusters in Cat Auditory Cortex Resemble Those of Neural Assemblies

2006 ◽  
Vol 96 (2) ◽  
pp. 746-764 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Spike Activity ◽  
Correlation Matrix ◽  
Cross Correlation ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Simultaneous Recording ◽  
Electrode Arrays ◽  
Tone Stimulus ◽  
Neural Assemblies

Spiking activity was recorded from cat auditory cortex using multi-electrode arrays. Cross-correlograms were calculated for spikes recorded on separate microelectrodes. The pair-wise cross-correlation matrix was constructed for the peak values of the correlograms. Hierarchical clustering was performed on the cross-correlation matrix for six stimulus conditions. These were silence, three multi-tone stimulus ensembles with different spectral densities, low-pass amplitude-modulated noise, and Poisson-distributed click trains that each lasted 15 min. The resulting neuron clusters reflect patches in cortex of up to several mm2 in size that expand and contract in response to different stimuli. Cluster positions and size were very similar for spontaneous activity and multi-tone stimulus-evoked activity but differed between those conditions and the noise and click stimuli. Cluster size was significantly larger in posterior auditory field (PAF) compared with primary auditory cortex (AI), whereas the fraction of common spikes (within a 10-ms window) across all electrode activity participating in a cluster was significantly higher in AI compared with PAF. Clusters crossed area boundaries in <5% of the cases were simultaneous recording were made in AI and PAF. Clusters are therefore similar to but not synonymous with the traditional view of neural assemblies. Common-spike spectrotemporal receptive fields (STRFs) were obtained for common-spike activity and all-spike activity within a cluster. Common-spike STRFs had higher signal-to-noise ratio than all-spike STRFs and showed generally spectral and temporal sharpening. The coincident and noncoincident output of the clusters could potentially act in parallel and may serve different modes of stimulus coding.

scholarly journals Cross-Correlation and Joint Spectro-Temporal Receptive Field Properties in Auditory Cortex

2005 ◽  
Vol 93 (1) ◽  
pp. 378-392 ◽  
Author(s):  
Masahiko Tomita ◽  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Neural Activity ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Network Activity ◽  
Electrode Arrays ◽  
The Cross ◽  
The Right

Recordings were made from the right primary auditory cortex in 17 adult cats using two eight-electrode arrays. We recorded the neural activity under spontaneous firing conditions and during random, multi-frequency stimulation, at 65 dB SPL, from the same units. Multiple single-unit (MSU) recordings (281) were stationary through 900 s of silence and during 900 s of stimulation. The cross-correlograms of 545 MSU pairs with peak lag times within 10 ms from zero lag time were analyzed. Stimulation reduced the correlation in background activity, and as a result, the signal-to-noise ratio of correlated activity in response to the stimulus was enhanced. Reconstructed spectro-temporal receptive fields (STRFs) for coincident spikes showed larger STRF overlaps, suggesting that coincident neural activity serves to sharpen the resolution in the spectro-temporal domain. The cross-correlation for spikes contributing to the STRF depended much stronger on the STRF overlap than the cross-correlation during either silence or for spikes that did not contribute to the STRF (OUT-STRF). Compared with that for firings during silence, the cross-correlation for the OUT-STRF spikes was much reduced despite the unchanged firing rate. This suggests that stimulation breaks up the large neural assembly that exists during long periods of silence into a stimulus related one and maybe several others. As a result, the OUT-STRF spikes of the unit pairs, now likely distributed across several assemblies, are less correlated than during long periods of silence. Thus the ongoing network activity is significantly different from that during stimulation and changes afterng arousal during stimulation.

scholarly journals Comparison of LFP-Based and Spike-Based Spectro-Temporal Receptive Fields and Cross-Correlation in Cat Primary Auditory Cortex

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e20046 ◽  
Author(s):  
Jos J. Eggermont ◽  
Raymundo Munguia ◽  
Martin Pienkowski ◽  
Greg Shaw
Keyword(s):  
Auditory Cortex ◽  
Cross Correlation ◽  
Receptive Fields ◽  
Primary Auditory Cortex

Component analysis reveals sharp tuning of the local field potential in the guinea pig auditory cortex

2013 ◽  
Vol 109 (1) ◽  
pp. 261-272 ◽  
Author(s):  
Alain de Cheveigné ◽  
Jean-Marc Edeline ◽  
Quentin Gaucher ◽  
Boris Gourévitch
Keyword(s):  
Auditory Cortex ◽  
Local Field ◽  
Receptive Fields ◽  
Field Potential ◽  
Component Analysis ◽  
Electrode Arrays ◽  
Linear Combinations ◽  
Spectrotemporal Receptive Fields ◽  
Analysis Technique ◽  
Channel Electrode

Local field potentials (LFPs) recorded in the auditory cortex of mammals are known to reveal weakly selective and often multimodal spectrotemporal receptive fields in contrast to spiking activity. This may in part reflect the wider “listening sphere” of LFPs relative to spikes due to the greater current spread at low than high frequencies. We recorded LFPs and spikes from auditory cortex of guinea pigs using 16-channel electrode arrays. LFPs were processed by a component analysis technique that produces optimally tuned linear combinations of electrode signals. Linear combinations of LFPs were found to have sharply tuned responses, closer to spike-related tuning. The existence of a sharply tuned component implies that a cortical neuron (or group of neurons) capable of forming a linear combination of its inputs has access to that information. Linear combinations of signals from electrode arrays reveal information latent in the subspace spanned by multichannel LFP recordings and are justified by the fact that the observations themselves are linear combinations of neural sources.

Delayed Inhibition in Cortical Receptive Fields and the Discrimination of Complex Stimuli

2005 ◽  
Vol 94 (4) ◽  
pp. 2970-2975 ◽  
Author(s):  
Rajiv Narayan ◽  
Ayla Ergün ◽  
Kamal Sen
Keyword(s):  
Auditory Cortex ◽  
Temporal Structure ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Natural Sounds ◽  
Functional Roles ◽  
Complex Stimuli ◽  
Animal Vocalizations ◽  
Field L ◽  
Cortical Receptive Fields

Although auditory cortex is thought to play an important role in processing complex natural sounds such as speech and animal vocalizations, the specific functional roles of cortical receptive fields (RFs) remain unclear. Here, we study the relationship between a behaviorally important function: the discrimination of natural sounds and the structure of cortical RFs. We examine this problem in the model system of songbirds, using a computational approach. First, we constructed model neurons based on the spectral temporal RF (STRF), a widely used description of auditory cortical RFs. We focused on delayed inhibitory STRFs, a class of STRFs experimentally observed in primary auditory cortex (ACx) and its analog in songbirds (field L), which consist of an excitatory subregion and a delayed inhibitory subregion cotuned to a characteristic frequency. We quantified the discrimination of birdsongs by model neurons, examining both the dynamics and temporal resolution of discrimination, using a recently proposed spike distance metric (SDM). We found that single model neurons with delayed inhibitory STRFs can discriminate accurately between songs. Discrimination improves dramatically when the temporal structure of the neural response at fine timescales is considered. When we compared discrimination by model neurons with and without the inhibitory subregion, we found that the presence of the inhibitory subregion can improve discrimination. Finally, we modeled a cortical microcircuit with delayed synaptic inhibition, a candidate mechanism underlying delayed inhibitory STRFs, and showed that blocking inhibition in this model circuit degrades discrimination.

scholarly journals Dissociable influences of primary auditory cortex and the posterior auditory field on neuronal responses in the dorsal zone of auditory cortex

2015 ◽  
Vol 113 (2) ◽  
pp. 475-486
Author(s):  
Melanie A. Kok ◽  
Daniel Stolzberg ◽  
Trecia A. Brown ◽  
Stephen G. Lomber
Keyword(s):  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Population Level ◽  
Noise Burst ◽  
Hierarchical Organization ◽  
Neuronal Responses ◽  
Tone Frequency ◽  
Hierarchical Processing ◽  
Auditory Field

Current models of hierarchical processing in auditory cortex have been based principally on anatomical connectivity while functional interactions between individual regions have remained largely unexplored. Previous cortical deactivation studies in the cat have addressed functional reciprocal connectivity between primary auditory cortex (A1) and other hierarchically lower level fields. The present study sought to assess the functional contribution of inputs along multiple stages of the current hierarchical model to a higher order area, the dorsal zone (DZ) of auditory cortex, in the anaesthetized cat. Cryoloops were placed over A1 and posterior auditory field (PAF). Multiunit neuronal responses to noise burst and tonal stimuli were recorded in DZ during cortical deactivation of each field individually and in concert. Deactivation of A1 suppressed peak neuronal responses in DZ regardless of stimulus and resulted in increased minimum thresholds and reduced absolute bandwidths for tone frequency receptive fields in DZ. PAF deactivation had less robust effects on DZ firing rates and receptive fields compared with A1 deactivation, and combined A1/PAF cooling was largely driven by the effects of A1 deactivation at the population level. These results provide physiological support for the current anatomically based model of both serial and parallel processing schemes in auditory cortical hierarchical organization.

scholarly journals The Structure of Spatial Receptive Fields of Neurons in Primary Auditory Cortex of the Cat

1996 ◽  
Vol 16 (14) ◽  
pp. 4420-4437 ◽  
Author(s):  
John F. Brugge ◽  
Richard A. Reale ◽  
Joseph E. Hind
Keyword(s):  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex

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.

scholarly journals Auditory-Cortex Short-Term Plasticity Induced by Selective Attention

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Iiro P. Jääskeläinen ◽  
Jyrki Ahveninen
Keyword(s):  
Selective Attention ◽  
Auditory Cortex ◽  
Receptive Fields ◽  
Discrimination Performance ◽  
Primary Auditory Cortex ◽  
Attentional Focus ◽  
Subcortical Structures ◽  
Short Term ◽  
Functional Changes ◽  
Short Term Plasticity

The ability to concentrate on relevant sounds in the acoustic environment is crucial for everyday function and communication. Converging lines of evidence suggests that transient functional changes in auditory-cortex neurons, “short-term plasticity”, might explain this fundamental function. Under conditions of strongly focused attention, enhanced processing of attended sounds can take place at very early latencies (~50 ms from sound onset) in primary auditory cortex and possibly even at earlier latencies in subcortical structures. More robust selective-attention short-term plasticity is manifested as modulation of responses peaking at ~100 ms from sound onset in functionally specialized nonprimary auditory-cortical areas by way of stimulus-specific reshaping of neuronal receptive fields that supports filtering of selectively attended sound features from task-irrelevant ones. Such effects have been shown to take effect in ~seconds following shifting of attentional focus. There are findings suggesting that the reshaping of neuronal receptive fields is even stronger at longer auditory-cortex response latencies (~300 ms from sound onset). These longer-latency short-term plasticity effects seem to build up more gradually, within tens of seconds after shifting the focus of attention. Importantly, some of the auditory-cortical short-term plasticity effects observed during selective attention predict enhancements in behaviorally measured sound discrimination performance.

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