Literature DB >> 16267238

Dynamically modulated spike correlation in monkey inferior temporal cortex depending on the feature configuration within a whole object.

Toshiyuki Hirabayashi1, Yasushi Miyashita.   

Abstract

The mechanism underlying the processing of spatially separated multiple local features to form a unique whole object is an important issue in visual object recognition. We tested whether, in behaving monkeys, the spike correlation between pairs of inferior temporal (IT) neurons dynamically changes depending on the spatial configuration of the local features within a whole object. We prepared more than 60,000 face-like objects (FOs) and their corresponding non-face-like objects (NFOs) that consisted of random arrangements of the same set of local features as those in FOs. The spike correlation between a pair of neurons was quantified by the peak height of the shift predictor-subtracted cross-correlogram. For both neurons of the pair, the local features in a whole object were determined so that they elicited as high a response as possible to enable a reliable cross-correlation analysis. We found that the FOs thus constructed elicited neuronal activities that were more strongly correlated than the corresponding NFOs. Firing rates of the same neurons did not show such a consistent bias depending on the feature configuration. Furthermore, receiver operating characteristic analysis revealed that this FO dominance of spike correlation was robust enough to discriminate between different feature configurations at the population level. Spike correlation of the cell pairs exhibited significant FO dominance within 300 ms after stimulus onset. The present results suggest that feature configuration within a unique whole object can be reflected in the rapid modulation of spike correlation among a population of neurons in the IT cortex.

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Year:  2005        PMID: 16267238      PMCID: PMC6725794          DOI: 10.1523/JNEUROSCI.3036-05.2005

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  22 in total

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9.  The Magnitude, But Not the Sign, of MT Single-Trial Spike-Time Correlations Predicts Motion Detection Performance.

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10.  Neural synchrony in cortical networks: history, concept and current status.

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