NDLI: Laminar dependence of neuronal correlations in visual cortex

Content Provider	PubMed Central
Author	Smith, Matthew A. Jia, Xiaoxuan Amin, Zandvakili Kohn, Adam
Copyright Year	2013
Abstract	Neuronal responses are correlated on a range of timescales. Correlations can affect population coding and may play an important role in cortical function. Correlations are known to depend on stimulus drive, behavioral context, and experience, but the mechanisms that determine their properties are poorly understood. Here we make use of the laminar organization of cortex, with its variations in sources of input, local circuit architecture, and neuronal properties, to test whether networks engaged in similar functions but with distinct properties generate different patterns of correlation. We find that slow timescale correlations are prominent in the superficial and deep layers of primary visual cortex (V1) of macaque monkeys, but near zero in the middle layers. Brief timescale correlation (synchrony), on the other hand, was slightly stronger in the middle layers of V1, although evident at most cortical depths. Laminar variations were also apparent in the power of the local field potential, with a complementary pattern for low frequency (<10 Hz) and gamma (30–50 Hz) power. Recordings in area V2 revealed a laminar dependence similar to V1 for synchrony, but slow timescale correlations were not different between the input layers and nearby locations. Our results reveal that cortical circuits in different laminae can generate remarkably different patterns of correlations, despite being tightly interconnected.
Related Links	http://dx.doi.org/10.1152/jn.00846.2012
Ending Page	947
Page Count	8
Starting Page	940
File Format	PDF
ISSN	00223077
e-ISSN	15221598
Journal	Journal of Neurophysiology
Issue Number	4
Volume Number	109
Language	English
Publisher	American Physiological Society
Publisher Date	2013-02-15
Access Restriction	Open
Rights Holder	American Physiological Society
Subject Keyword	Physiology Neuroscience(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Neuroscience Physiology

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