Visual feature binding can occur through local recurrent mechanisms without req…

{
  "n": null,
  "doi": "10.1371/journal.pcbi.1005888",
  "claim": "Visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mo…",
  "cite_key": "Muir2017",
  "evidence": "Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons res...",
  "effect_size": "Parameter\n\nDescription\n\nNominal value\n\nτ\n\ni\n\nLumped neuron time constant for neuron\n\n10 ms\n\ng\n\nj\n\nNominal current injected by synapses from neuron\n\nExc.: 0.01 pA HzInh.:10×0.01 pA Hz\n\nα\n\nj\n\nNominal I–F output gain of neuron\n\n0.066 Hz pA\n\nn\n\n,\n\nNumber of synapses made from neuronto neuron\n\nβ\n\nj\n\nThreshold of neuron\n\nZero\n\n⋅()\n\nNoise current injected into neuron.",
  "text_access": "fulltext",
  "study_system": "mouse; V1, visual cortex; in vivo, computational model; PLoS computational biology",
  "argument_role": "supporting",
  "replication_status": "single_study",
  "claim_source_sentence": "Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.",
  "source_provenance_status": "ok",
  "replication_evidence_dois": [],
  "claim_rewritten_from_source": true,
  "effect_size_source_sentence": "Parameter\n\nDescription\n\nNominal value\n\nτ\n\ni\n\nLumped neuron time constant for neuron\n\n10 ms\n\ng\n\nj\n\nNominal current injected by synapses from neuron\n\nExc.: 0.01 pA HzInh.:10×0.01 pA Hz\n\nα\n\nj\n\nNominal I–F output gain of neuron\n\n0.066 Hz pA\n\nn\n\n,\n\nNumber of synapses made from neuronto neuron\n\nβ\n\nj\n\nThreshold of neuron\n\nZero\n\n⋅()\n\nNoise current injected into neuron."
}

Parameter

Description

Nominal value

τ

i

Lumped neuron time constant for neuron

10 ms

g

j

Nominal current injected by synapses from neuron

Exc.: 0.01 pA HzInh.:10×0.01 pA Hz

α

j

Nominal I–F output gain of neuron

0.066 Hz pA

n

,

Number of synapses made from neuronto neuron

β

j

Threshold of neuron

Zero

⋅()

Noise current injected into neuron.

[
  "paper:paper-8d890b2475da"
]

[
  {
    "ref": "paper:paper-8d890b2475da"
  }
]

{
  "mode": "public_source_pointer_with_short_context",
  "notes": [
    "Local review repositories are read-only inputs.",
    "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
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  "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
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Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons res...