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ref: -2012 tags: DiCarlo Visual object recognition inferior temporal cortex dorsal ventral stream V1 date: 03-13-2019 22:24 gmt revision:1 [0] [head]

PMID-22325196 How Does the Brain Solve Visual Object Recognition

  • James DiCarlo, Davide Zoccolan, Nicole C Rust.
  • Infero-temporal cortex is organized into behaviorally relevant categories, not necessarily retinotopically, as demonstrated with TMS studies in humans, and lesion studies in other primates.
    • Synaptic transmission takes 1-2ms; dendritic propagation ?, axonal propagation ~1ms (e.g. pyramidal antidromic activation latency 1.2-1.3ms), so each layer can use several synapses for computation.
  • Results from the ventral stream computation can be well described by a firing rate code binned at ~ 50ms. Such a code can reliably describe and predict behavior
    • Though: this does not rule out codes with finer temporal resolution.
    • Though anyway: it may be inferential issue, as behavior operates at this timescale.
  • IT neurons' responses are sparse, but still contain information about position and size.
    • They are not narrowly tuned detectors, not grandmother cells; they are selective and complex but not narrow.
    • Indeed, IT neurons with the highest shape selectivities are the least tolerate to changes in position, scale, contrast, and visual clutter. (Zoccolan et al 2007)
    • Position information avoids the need to re-bind attributes with perceptual categories -- no need for syncrhony binding.
  • Decoded IT population activity of ~100 neurons exceeds artificial vision systems (Pinto et al 2010).
  • As in {1448}, there is a ~ 30x expansion of the number of neurons (axons?) in V1 vs the optic tract; serves to allow controlled sparsity.
  • Dispute in the field over primarily hierarchical & feed-forward vs. highly structured feedback being essential for performance (and learning?) of the system.
    • One could hypothesize that feedback signals help lower levels perform inference with noisy inputs; or feedback from higher layers, which is prevalent and manifest (and must be important; all that membrane is not wasted..)
    • DiCarlo questions if the re-entrant intra-area and inter-area communication is necessary for building object representations.
      • This could be tested with optogenetic approaches; since the publication, it may have been..
      • Feedback-type active perception may be evinced in binocular rivalry, or in visual illusions;
      • Yet 150ms immediate object recognition probably does not require it.
  • Authors propose thinking about neurons/local circuits as having 'job descriptions', an metaphor that couples neuroscience to human organization: who is providing feedback to the workers? Who is providing feeback as to job function? (Hinton 1995).
  • Propose local subspace untangling; when this is tacked and tiled, this is sufficient for object perception.
    • Indeed, modern deep convolutional networks behave this way; yet they still can't match human performance (perhaps not sparse enough, not enough representational capability)
    • Cite Hinton & Salakhutdinov 2006.
  • The AND-OR or conv-pooling architecture was proposed by Hubbel and Weisel back in 1962! In their paper's formulatin, they call it a Normalized non-linear model, NLN.
  1. Nonlinearities tend to flatten object manifolds; even with random weights, NLN models tend to produce easier to decode object identities, based on strength of normalization. See also {714}.
  2. NLNs are tuned / become tuned to the statistics of real images. But they do not get into discrimination / perception thereof..
  3. NLNs learn temporally: inputs that occur temporally adjacent lead to similar responses.
    1. But: scaades? Humans saccade 100 million times per year!
      1. This could be seen as a continuity prior: the world is unlikely to change between saccades, so one can infer the identity and positions of objects on the retina, which say can be used to tune different retinotopic IT neurons..
    2. See Li & DiCarlo -- manipulation of image statistics changing visual responses.
  • Regarding (3) above, perhaps attention is a modifier / learning gate?

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ref: Bures-1968 tags: inferior colliculus stimulation classical conditioning plasticity hebb Bures date: 01-03-2012 07:08 gmt revision:5 [4] [3] [2] [1] [0] [head]

bibtex:Bures-1968 Plastic changes of unit activity based on reinforcing properties of extracellular stimulation of single neurons

  • images/972_1.pdf
  • Trained neurons to respond to auditory stimuli throughout the brain (though mostly the IC) to a auditory tone.
    • Hebb's rule, verified.
  • Yoshii & Ogura (22): Reticular units, originally not responding to sciatic nerve US, started to respond to the CS after a few tens of trials, however the conditioned reactions disappeared with continued training.
    • This must be regarded as response to arousal at the initial stages of classical aversive (sciatic nerve pain?) conditioning.
  • Used capilary electrodes 1um in diameter, filled with KCl or sodium glutamate
  • Stimulation current 10-50nA DC, 0.3-1 sec.
  • Were able to record and stimulate at the same time using these glass microelectrodes.
  • The majority of units (cortex, reticular formation, thalamus) showed no response, though some did. These responses tended to fade with overtraining.
  • Quote: "The rather low incidence of positive results int he above experiment might be due to the fact that many examined neurons lack even an indirect acoustic input and cannot, therefore, be activated by acoustic stimuli."
  • Neurons in the IC show the strongest plastic change.
  • Their study is more specific than Loucks (15), Olds and Milner (17) Delgaso (6) Doty(7) which used less specific ICMS.
  • That said, there is no behavior .. so we don't know if the stimuli is being reacted to or attended to (might explain the low # of responses in areas).
  • They also think that the response can be credited to nonspecific phenomena like dominant focus, reflex sensitization, or heterosynaptic facilitation.
    • That said, the IC did show strong responses.

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ref: Lim-2009.09 tags: auditory midbrain implant deaf cochlea stimulation inferior colliculus date: 01-03-2012 06:55 gmt revision:2 [1] [0] [head]

PMID-19762428[0] Auditory midbrain implant: a review.

  • Inferior to a cochlear implant -- subjects, at the best, could understand speech only with lip-reading cues.
  • But! It's safe, and offers some degree of perception.
  • Also see: PMID-21157353[1]
    • Neurofibramatosis type 2 can also lead to cochlear deafness.
    • Implanted in the dorsal and ventral cochlear nuclei in the lateral recess of the IVth ventricle of the brain stem.
    • EABRs (evoked auditory brain stem responses); even though these were associated with electrodes in the right place, they could not be used for device fitting (?)

____References____

[0] Lim HH, Lenarz M, Lenarz T, Auditory midbrain implant: a review.Trends Amplif 13:3, 149-80 (2009 Sep)
[1] O'Driscoll M, El-Deredy W, Ramsden RT, Brain stem responses evoked by stimulation of the mature cochlear nucleus with an auditory brain stem implant.Ear Hear 32:3, 286-99 (2011 May-Jun)

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ref: Bengtsson-2006.01 tags: inferior olive anatomy date: 01-03-2012 02:49 gmt revision:2 [1] [0] [head]

http://www.neuroanatomy.wisc.edu/virtualbrain/BrainStem/06Olive.html

  • source of long-latency climbing fibers
  • projects to contralateral cerebellum.
  • destruction of IO = destruction of contralateral cerebellum.
  • conversely, removal of one cerebellar hemesphere -> atropy of contralateral IO.
  • the climbing fibers of the IO run through the inferior cerebellar peduncle.
  • according to {115}, the motor cortex projects to the inferior olive. from wikipedia: many collaterals from the reticular formation and from the pyramides enter the inferior olivary nucleus.
  • PMID-16527758 the afferents from the DCN to the IO are involved in feedback control of learning & feedback control of complex/simple spike activity in purkinje cells.
  • PMID-5967023 Afferent connexions to single units in the inferior olive of the cat
    • the immediate response to stimulation of the limb nerves was always excitation of the olivary units, sometimes which was followed by a slent period of inhibition.
    • single units in the olive could be excited by moving single hairs on the foot or be stroking the surface of the limbs.
    • stimulation of the ipsilateral caudate nucleus caused firing in IO units with a latency of 1.0 20ms
  • PMID-5340538 http://hardm.ath.cx:88/pdf/AfferentsInferiorOlive1967.pdf
    • there seem to be two classes of olive units: those that respond with low latency to motor cortex stimulation and spinal pathways (these have a high degree of topographic specificity), and those which respond with higher latency to stimulation of the caudate (with lower topographic specificity).
    • climbing fibers fire more of a wave than an isolated AP.
  • red nucleus and VA/VL thalamus are innervated from the deep cerebellar nuclei, which is inhibited by purkinje cells.