Local Functional Input to Neurons in Deep Layers of Rat Visual Cortex

Local Functional Input to Neurons in Deep Layers of Rat Visual Cortex
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Total Pages : 135
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ISBN-10 : OCLC:71332513
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Book Synopsis Local Functional Input to Neurons in Deep Layers of Rat Visual Cortex by : Amir Zarrinpar

Download or read book Local Functional Input to Neurons in Deep Layers of Rat Visual Cortex written by Amir Zarrinpar and published by . This book was released on 2006 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unraveling the precise connectivity of underlying neural circuits will lead to a better understanding of how the cortex accomplishes even the most effortless task. It has been a fundamental goal of neurophysiology to identify individual cell types based on morphological and/or intrinsic physiological properties and to discover their respective role in the circuitry within which they are embedded. To understand visual cortical circuitry even better, this dissertation focuses on the deep layers (layers 5 and 6) of the rat visual system. These cells, which comprise more than half of the cortical depth in the rat, are in a unique position in the visual system circuitry. Compared to the superficial layers, the deep layers have a greater diversity of cell morphologies and probably play a more varied role in visual information processing. We studied dendritic morphologies and local excitatory input to individual layer 6 and layer 5 neurons in rat visual cortex by combining intracellular labeling and recording with laser-scanning photostimulation. We found significant differences in the sources of local excitatory input to different cell types. In layer 6 we found six distinct cell subtypes which we characterized based on morphology and sublaminar organization. Most notably, there were differences in local input to neurons that were likely to project only to the lateral geniculate nucleus versus those that were likely also to project to the lateral posterior nucleus. In layer 5 we distinguished three non-overlapping cell subtypes based on both their morphological and intrinsic physiological properties. Although all cell types received significant input from all layers. One subset of cells, presumed to be cortico-cortical projecting neurons, received stronger input from layer 4 and weaker input from layer 5 when compared to the others. We did not find any differences in input patterns between two subtypes that had similar morphology but different firing patterns. Using an analysis of synchronous activity, however, we showed that although the two cell types receive the same laminar input patterns, they receive input from different cell populations within those layers.


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