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[0] Shidara M, Aigner TG, Richmond BJ, Neuronal signals in the monkey ventral striatum related to progress through a predictable series of trials.J Neurosci 18:7, 2613-25 (1998 Apr 1)

[0] Lavin A, Nogueira L, Lapish CC, Wightman RM, Phillips PE, Seamans JK, Mesocortical dopamine neurons operate in distinct temporal domains using multimodal signaling.J Neurosci 25:20, 5013-23 (2005 May 18)[1] Pirot S, Godbout R, Mantz J, Tassin JP, Glowinski J, Thierry AM, Inhibitory effects of ventral tegmental area stimulation on the activity of prefrontal cortical neurons: evidence for the involvement of both dopaminergic and GABAergic components.Neuroscience 49:4, 857-65 (1992 Aug)

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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: RodriguezOroz-2011.01 tags: DBS dopamine impulse control spain pamplona ventral beta date: 02-22-2012 17:02 gmt revision:9 [8] [7] [6] [5] [4] [3] [head]

PMID-21059746[0] Involvement of the subthalamic nucleus in impulse control disorders associated with Parkinson’s disease

  • recorded LFP in the STN of 28 patients.
    • of these 10 had impulse control disorders, 9 had dyskinesias, and 9 had no complications.
  • compared ON and OFF medication.
  • no difference between groups in off states.
  • large differences in ON states.
    • Impulse control problems: theta-alpha activity(4-10 Hz) 6 Hz mean.
      • Larger coherence with frontal regions 4-7.5 Hz.
    • Dyskinesias: higher frequency theta-alpha 8 Hz mean.
      • Higher coherence with motor areas, 7.5 - 10Hz.
    • No problems: no noticeable LFP oscillations (?).
  • PD patients often have side-effects of Punding and hobbyism.
    • Does meth treat PD? Selegiline does. Fascinating history there regarding combining MAOI + amphetamine --> effective PD drug.
    • Why does both meth and levodopa induce impulsivity?
    • Some of the other effects of L-DOPA treatment: hypersexuality, manic behavior or shopping.
    • Lesion of the subthalamic nucleus by infarction or tumor is associated with behavioral alterations including agitation, manic states and logorrhoea, with or without hemiballismus.
  • In some patients with ICD (impulse control disorders) induced by subthalamic nucleus deep brain stimulation, the abnormal behavior was provoked by stimulation with a ventral contact and suppressed by switching it off. (dorsal region is more motor).
    • In three patients with ICD, stimulation through the ventral contact induced a euphoric state -- PPN?
  • STN recordings from rats and monkeys modify their frequency in response to reward related tasks (Aron and Poldrack 2006); in humans the STN is active during an inhibition task (LI et al 2008).
  • LFP recordings from the treatment electrode were very low! 16uV.
  • Typical results show large differences between ON and OFF: ON show more activity > 60 Hz, OFF more < 60 Hz (Brown et al 2001; Brown 2003 Gatev et al 2006).
  • LFP recordings in PD patients from the STN showed that emotional stimulus led to a decrease in alpha power in the ventral contacts (Brucke et al 2007), whereas active movement led to a decrease in the beta power recorded in the dorsal subthalamic nucleus (Alegre et al 2005).
  • Original work on STN mediating impulsivity: Delong 1983 PMID-6422317 The neurophysiologic basis of abnormal movements in basal ganglia disorders.
    • Single cell studies in the basal ganglia of behaving animals have revealed specific relations of neuronal activity to movements of individual body parts and a relation to specific parameters of movement, particularly direction, amplitude, and velocity. (no fulltext available).

____References____

[0] Rodriguez-Oroz MC, López-Azcárate J, Garcia-Garcia D, Alegre M, Toledo J, Valencia M, Guridi J, Artieda J, Obeso JA, Involvement of the subthalamic nucleus in impulse control disorders associated with Parkinson's disease.Brain 134:Pt 1, 36-49 (2011 Jan)

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ref: Shidara-1998.04 tags: ventral striatum nucleus accumbens monkey reward progress cue date: 03-27-2007 14:39 gmt revision:0 [head]

PMID-9502820[] Neuronal signals in the monkey ventral striatum related to progress through a predictable series of trials

  • neurons seem to cue/indicate/keep track of the state that a monkey is in during a sequence of reward-motivated behavior, e.g. there are neurons here which respond to the first trial, another group to anything other than 1st, others to first trial of schedules longer than one.
    • the recording site.

____References____

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ref: Lavin-2005.05 tags: dopamine PFC VTA prefrontal_cortex ventral_tegmentum 2005 date: 02-05-2007 20:37 gmt revision:1 [0] [head]

PMID-15901782[0]Mesocortical Dopamine Neurons Operate in Distinct Temporal Domains Using Multimodal Signaling

  • good paper, decent review of relevant infos in the introduction.
  • they suggest that the mesocortical system transmits fast signals about reward/salience via corelease of glutamate, whereas dopamine provides a more long-term modulator of cortical processing dynamics.
  • the ventral tegmental area provides dopamine to the prefrontal cortex.
  • DA levels in the PFC can increase ~10x above baseline for 10's of minutes.
    • these responses occur to both to unexpectedly rewarding stimuli as well as to aversive stimuli.
  • brief VTA stimulation invokes a short, transient (~200ms) inhibition of PFC in vivo, and this inhibition is typically blocked by DA antagonists. from: PMID-1436485[1]
    • transient inhibition begins ~20ms after VTA stimulation, which is barely enough time for activation of ionotropic receptors, let alone metabotropic DA receptors.
  • MFB stimulation evoked increased DA levels and an elevation in firing of nearby striatal neurons that outlasted the period of stimulation by > 300s.
  • strangely, the excitatory glutamergic response in the PFC to VTA stimulation is blocked by lesion of the MFB.
  • in suppport of co-release, TH-positive neurons in rats and primates are co-reactive for glutamate.
    • DA neurons can form glutamate synapses in vitro.
  • check it out:
    • midbrain DA neurons respond by firing a ~200ms burst of spikes to primary rewards, conditioned, or secondary rewards, rewards that are not predicted, and novel or unexpected stimuli.
    • DA neurons are activated by rewarding events that are better than predicted, remain unaffected by events that are as good as predicted, and are depressed by events that are worse than predicted (yet they do not cite any refs for this... there are a bunch of refs in the prev sentence. ) see:
    • stress can also increase PFC DA

____References____