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Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

Publication ,  Journal Article
Zhang, X; Ju, H; Penney, TB; VanDongen, AMJ
Published in: eNeuro
2017

Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher's discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits.

Duke Scholars

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Published In

eNeuro

DOI

EISSN

2373-2822

Publication Date

2017

Volume

4

Issue

3

Location

United States

Related Subject Headings

  • Unsupervised Machine Learning
  • Recognition, Psychology
  • Receptors, N-Methyl-D-Aspartate
  • Neurons
  • Neuronal Plasticity
  • Neural Pathways
  • Neural Networks, Computer
  • Learning
  • Humans
  • Facial Recognition
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhang, X., Ju, H., Penney, T. B., & VanDongen, A. M. J. (2017). Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity. ENeuro, 4(3). https://doi.org/10.1523/ENEURO.0361-16.2017
Zhang, Xiaoyu, Han Ju, Trevor B. Penney, and Antonius M. J. VanDongen. “Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.ENeuro 4, no. 3 (2017). https://doi.org/10.1523/ENEURO.0361-16.2017.
Zhang, Xiaoyu, et al. “Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.ENeuro, vol. 4, no. 3, 2017. Pubmed, doi:10.1523/ENEURO.0361-16.2017.

Published In

eNeuro

DOI

EISSN

2373-2822

Publication Date

2017

Volume

4

Issue

3

Location

United States

Related Subject Headings

  • Unsupervised Machine Learning
  • Recognition, Psychology
  • Receptors, N-Methyl-D-Aspartate
  • Neurons
  • Neuronal Plasticity
  • Neural Pathways
  • Neural Networks, Computer
  • Learning
  • Humans
  • Facial Recognition