Biophysics of Computation I

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Claim: many cortical neurons are not single “point” integrators but contain voltage privacy in long dendritic branches that act as independent nonlinear subunits. Evidence: glutamate uncaging, patch recordings, voltage‑sensitive dyes and calcium imaging in slices and awake animals show NMDA spikes that sum nonlinearly within a branch but attenuate toward the soma. Scale: pyramidal cells carry 10,000–20,000 contacts (Purkinje ~100,000–200,000). Model implication: a within‑neuron two‑layer model (branch subunits → soma) better matches data than a simple point neuron.

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1. 0:00Intro
2. 4:02What's the input-output rule?
3. 11:40The Question: How complicated a model do we need
4. 14:12Historicaly, the point neuron has been the dominant model
5. 15:57The Purkinje Cell
6. 17:19The Cerebellum
7. 20:46The Linear Computational Algorithm of Cerebellar
8. 22:20A progression of models
9. 24:36Problem 1: Long thin dendrites separated by larger-diameter structures provide numerous wel-isolated voltage subunits
10. 34:02Digression: How NMDA Spikes work
11. 42:00Dendritic spikes...in awake animals
12. 43:24Even interneurons generate NMDA spikes!
13. 46:57Direct evidence that dendritic spikes really are well compartmentalized
14. 50:36Experimental test of the 2-layer hypothesis