第33回日本神経科学大会

会期:2010.9.2-4(発表日9月3日)
会場: 神戸コンベンションセンター

Shiozaki, H., Motonaga,T., Tamura, H., Fujita, I. (2010)Pairwise interactions account for correlated activity of neurons in the inferior temporal cortex of macaque monkeys
塩崎博史、本永拓、田村弘、藤田一郎「サル下側頭葉皮質の神経細胞群が示す相関発火は2細胞間の相互作用で説明できる」

妙録O2-8-3-4
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Characterization of the activity of populations of neurons provides clues for the computation performed by neural circuits. Recent studies have shown spatial patterns that describe the activity of tens of retinal ganglion cells and neurons in the primary visual cortex can be explained by a model that incorporates firing rates of individual cells and pairwise interactions but ignores higher-order interactions. However, it remains unclear whether pairwise interactions account for the concerted activity of neurons in higher-order visual areas where dendritic morphology and local anatomical connections differ from those in the early visual processing stages. To address this issue, we simultaneously recorded the spike activity of a population of neurons in the inferior temporal cortex (ITC), a higher-order visual area, of two monkeys under analgesia. We obtained data from four populations consisting of 23, 25, 32, and 37 neurons over 15 to 60 minutes. The probability of the number of neurons that were active in the same 5-ms time bin systematically deviated from the prediction of a model that assumes statistical independence between the activity of different neurons. This deviation was largely explained by a model that takes into account pairwise interactions in addition to the firing rates of individual neurons. The pairwise model captured 94% of the deviations seen in the statistical independence model. To further test the pairwise model, we randomly selected subpopulations consisting of 10 neurons and examined the probability of the individual activity patterns of these subpopulations in a 5-ms time bin. The pairwise model predicted 88% of the deviations seen in the statistical independence model. From these results, we suggest that pairwise interactions account for correlated activity of neurons in the ITC. Functional networks in different visual areas may share common features despite their heterogeneity in the anatomical structures.