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

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.

2004 ◽  
Vol 91 (6) ◽  
pp. 2551-2567 ◽  
Author(s):  
Simranjit Kaur ◽  
Ronit Lazar ◽  
Raju Metherate

To examine the basis of frequency receptive fields in auditory cortex (ACx), we have recorded intracellular (whole cell) and extracellular (local field potential, LFP) responses to tones in anesthetized rats. Frequency receptive fields derived from excitatory postsynaptic potentials (EPSPs) and LFPs from the same location resembled each other in terms of characteristic frequency (CF) and breadth of tuning, suggesting that LFPs reflect local synaptic (including subthreshold) activity. Subthreshold EPSP and LFP receptive fields were remarkably broad, often spanning five octaves (the maximum tested) at moderate intensities (40–50 dB above threshold). To identify receptive-field features that are generated intracortically, we microinjected the GABAA receptor agonist muscimol (0.2–5.1 mM, 1–5 μl) into ACx. Muscimol dramatically reduced LFP amplitude and reduced receptive-field bandwidth, implicating intracortical contributions to these features but had lesser effects on CF response threshold or onset latency, suggesting minimal loss of thalamocortical input. Reversal of muscimol's inhibition preferentially at the recording site by diffusion from the recording pipette of the GABAA receptor antagonist picrotoxin (0.01–100 μM) disinhibited responses to CF stimuli more than responses to spectrally distant, non-CF stimuli. We propose that thalamocortical and intracortical pathways preferentially contribute to responses evoked by CF and non-CF stimuli, respectively, and that intracortical projections linking frequency representations determine the breadth of receptive fields in primary ACx. Broad, subthreshold receptive fields may distinguish ACx from subcortical auditory relay nuclei, promote integrated responses to spectrotemporally complex stimuli, and provide a substrate for plasticity of cortical receptive fields and maps.


2010 ◽  
Vol 104 (2) ◽  
pp. 784-798 ◽  
Author(s):  
Noopur Amin ◽  
Patrick Gill ◽  
Frédéric E. Theunissen

We estimated the spectrotemporal receptive fields of neurons in the songbird auditory thalamus, nucleus ovoidalis, and compared the neural representation of complex sounds in the auditory thalamus to those found in the upstream auditory midbrain nucleus, mesencephalicus lateralis dorsalis (MLd), and the downstream auditory pallial region, field L. Our data refute the idea that the primary sensory thalamus acts as a simple, relay nucleus: we find that the auditory thalamic receptive fields obtained in response to song are more complex than the ones found in the midbrain. Moreover, we find that linear tuning diversity and complexity in ovoidalis (Ov) are closer to those found in field L than in MLd. We also find prevalent tuning to intermediate spectral and temporal modulations, a feature that is unique to Ov. Thus even a feed-forward model of the sensory processing chain, where neural responses in the sensory thalamus reveals intermediate response properties between those in the sensory periphery and those in the primary sensory cortex, is inadequate in describing the tuning found in Ov. Based on these results, we believe that the auditory thalamic circuitry plays an important role in generating novel complex representations for specific features found in natural sounds.


1999 ◽  
Vol 82 (5) ◽  
pp. 2327-2345 ◽  
Author(s):  
Jagmeet S. Kanwal ◽  
Douglas C. Fitzpatrick ◽  
Nobuo Suga

Mustached bats, Pteronotus parnellii parnellii,emit echolocation pulses that consist of four harmonics with a fundamental consisting of a constant frequency (CF1-4) component followed by a short, frequency-modulated (FM1-4) component. During flight, the pulse fundamental frequency is systematically lowered by an amount proportional to the velocity of the bat relative to the background so that the Doppler-shifted echo CF2 is maintained within a narrowband centered at ∼61 kHz. In the primary auditory cortex, there is an expanded representation of 60.6- to 63.0-kHz frequencies in the “Doppler-shifted CF processing” (DSCF) area where neurons show sharp, level-tolerant frequency tuning. More than 80% of DSCF neurons are facilitated by specific frequency combinations of ∼25 kHz (BFlow) and ∼61 kHz (BFhigh). To examine the role of these neurons for fine frequency discrimination during echolocation, we measured the basic response parameters for facilitation to synthesized echolocation signals varied in frequency, intensity, and in their temporal structure. Excitatory response areas were determined by presenting single CF tones, facilitative curves were obtained by presenting paired CF tones. All neurons showing facilitation exhibit at least two facilitative response areas, one of broad spectral tuning to frequencies centered at BFlowcorresponding to a frequency in the lower half of the echolocation pulse FM1 sweep and another of sharp tuning to frequencies centered at BFhigh corresponding to the CF2 in the echo. Facilitative response areas for BFhigh are broadened by ∼0.38 kHz at both the best amplitude and 50 dB above threshold response and show lower thresholds compared with the single-tone excitatory BFhigh response areas. An increase in the sensitivity of DSCF neurons would lead to target detection from farther away and/or for smaller targets than previously estimated on the basis of single-tone responses to BFhigh. About 15% of DSCF neurons show oblique excitatory and facilitatory response areas at BFhigh so that the center frequency of the frequency-response function at any amplitude decreases with increasing stimulus amplitudes. DSCF neurons also have inhibitory response areas that either skirt or overlap both the excitatory and facilitatory response areas for BFhigh and sometimes for BFlow. Inhibition by a broad range of frequencies contributes to the observed sharpness of frequency tuning in these neurons. Recordings from orthogonal penetrations show that the best frequencies for facilitation as well as excitation do not change within a cortical column. There does not appear to be any systematic representation of facilitation ratios across the cortical surface of the DSCF area.


2006 ◽  
Vol 96 (2) ◽  
pp. 746-764 ◽  
Author(s):  
Jos J. Eggermont

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.


2015 ◽  
Vol 113 (2) ◽  
pp. 475-486
Author(s):  
Melanie A. Kok ◽  
Daniel Stolzberg ◽  
Trecia A. Brown ◽  
Stephen G. Lomber

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.


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

2009 ◽  
Vol 102 (6) ◽  
pp. 3329-3339 ◽  
Author(s):  
Nima Mesgarani ◽  
Stephen V. David ◽  
Jonathan B. Fritz ◽  
Shihab A. Shamma

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.


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