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Geometric Analysis of the Axo-Dendritic Interface in Neocortical Pyramidal Neurons

Mel, Bartlett W. and Bansal, Arjun K. (2004) Geometric Analysis of the Axo-Dendritic Interface in Neocortical Pyramidal Neurons. In: 11th Joint Symposium on Neural Computation, May 15 2004, University of Southern California. (Unpublished)

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Since the time of Hebb, the physical substrate for learning and memory in the brain has been most often discussed in relation to activity-dependent synaptic "weight" changes mediated by LTP or LTD. However, two recent theoretical studies suggest that long term information storage in neural tissue could also depend (heavily) on structural plasticity at the interface between axons and dendrites (Poirazi & Mel, 2001; Stepanyants et al. 2002). According to both theories, the capacity for structure-based information storage depends on the interaccessibility of afferent axons and their dendritic targets within the neuropil. For example, how many different axons are likely to be accessible to any given postsynaptic dendrite with only minor structural modification? How much overlap exists in the set of axons accessible to two different dendritic branches? Using axonal and dendritic arborizations of a reconstructed pyramidal neuron from cat visual cortex as a reference point (courtesy J. Hirsch), we quantified the tradeoffs among several morphological variables that parameterize the axo-dendritic interface in neocortex, including spine length, spine density, dendritic branch length, branches per neuron, etc. We then used an extended version of the formula derived in Poirazi & Mel (2001) to understand how each of these variables separately and together contribute to the tissue's capacity to learn.

Item Type:Conference or Workshop Item (Poster)
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Deposited On:07 Jun 2004
Last Modified:03 Oct 2019 22:49

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