✎ literature:modelinghc []

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Introduction to computational modeling reading list (biased towards hippocampus):

[[https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Intro#The_Computational_Approach|Chapter]] from “Computational Explorations in Cognitive Neurocience” (O’Reilly and Munakata, 2000, 2013), kind of a manifesto for the “why” of computational modeling 

[[http://128.197.153.21/hasselmo/HasselmoMcClelland.pdf|A brief overview]] of classic computational models of memory: Hasselmo & McClelland (1999)

[[ttp://link.springer.com/article/10.1007/s00422-005-0567-x|Overview of theories and models]] of the function of the hippocampal theta rhythm: Lengyel et al. (2005)

Two specific examples of using computational modeling to demonstrate how an interesting consequence follows from known assumptions (1) or how an interesting phenomenon in the data can be explained from the interaction of known parts (2):

1) Softky & Koch, Journal of Neuroscience 1993. They show that if a model neuron receives many independent Poisson-distributed spike trains (i.e. spike trains in which you can’t predict when the next spike will occur based on what came before) as inputs, the output spiking of this neuron will be highly regular. Yet, cortical neurons often have spike trains with Poisson-like statistics, so how can neurons that receive lots of Poisson inputs generate Poisson outputs? The strong implication is that the inputs are not independent, i.e. there is synchrony in the inputs cortical neurons receive.

2) van der Meer et al. J Neurophysiol 2007. They show that anticipation in head direction cells (the property of firing some short time ahead of their preferred firing direction, i.e. “I’m going to be facing north soon”) can be explained by the known properties of certain vestibular neurons (spike rate adaptation and rebound from inhibition) operating on realistic movement profiles. Demonstrates that you don’t need fancy explanations like motor efference copy or planning to obtain anticipation effects.

Some influential/interesting hippocampus modeling papers:

3) McClelland & McNaughton, Psych Review, 1995

4) Abbott & Blum, Neural Computation 1996

5) Samsonovich & McNaughton, J Neurosci 1997

6) Hopfield, PNAS 2010 (maybe not as influential, but relevant to replay/preplay, and relatively accessible)
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