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[0] Bar-Gad I, Morris G, Bergman H, Information processing, dimensionality reduction and reinforcement learning in the basal ganglia.Prog Neurobiol 71:6, 439-73 (2003 Dec)

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ref: -2005 tags: dimensionality reduction contrastive gradient descent date: 09-13-2020 02:49 gmt revision:2 [1] [0] [head]

Dimensionality reduction by learning and invariant mapping

  • Raia Hadsell, Sumit Chopra, Yann LeCun
  • Central idea: learn and invariant mapping of the input by minimizing mapped distance (e.g. the distance between outputs) when the samples are categorized as the same (same numbers in MNIST eg), and maximizing mapped distance when the samples are categorized as distant.
    • Two loss functions for same vs different.
  • This is an attraction-repulsion spring analogy.
  • Use gradient descent to change the weights to satisfy these two competing losses.
  • Resulting constitutional neural nets can extract camera pose information from the NORB dataset.
  • Surprising how simple analogies like this, when iterated across a great many samples, pull out intuitively correct invariances.

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ref: BarGad-2003.12 tags: information dimensionality reduction reinforcement learning basal_ganglia RDDR SNR globus pallidus date: 01-16-2012 19:18 gmt revision:3 [2] [1] [0] [head]

PMID-15013228[] Information processing, dimensionality reduction, and reinforcement learning in the basal ganglia (2003)

  • long paper! looks like they used latex.
  • they focus on a 'new model' for the basal ganglia: reinforcement driven dimensionality reduction (RDDR)
  • in order to make sense of the system - according to them - any model must ingore huge ammounts of information about the studied areas.
  • ventral striatum = nucelus accumbens!
  • striatum is broken into two, rough, parts: ventral and dorsal
    • dorsal striatum: the caudate and putamen are a part of the
    • ventral striatum: the nucelus accumbens, medial and ventral portions of the caudate and putamen, and striatal cells of the olifactory tubercle (!) and anterior perforated substance.
  • ~90 of neurons in the striatum are medium spiny neurons
    • dendrites fill 0.5mm^3
    • cells have up and down states.
      • the states are controlled by intrinsic connections
      • project to GPe GPi & SNr (primarily), using GABA.
  • 1-2% of neurons in the striatum are tonically active neurons (TANs)
    • use acetylcholine (among others)
    • fewer spines
    • more sensitive to input
    • TANs encode information relevant to reinforcement or incentive behavior