Neural circuit mechanisms for neural computation

Currently, some of the projects of the lab include:

  • The role of interneurons in neural code generation, synchronization and propagation (See bioRxiv, link)
  • The role of distinct subtypes of interneurons in memory encoding and its application to Alzheimer’s disease therapeutics (see bioRxiv, link)

Neuroscience-inspired computational models of the brain for AI and neuromorphic robot applications

The neural circuits of the brain are extremely complex and dynamic thus it is difficult to capture the full details using the current experimental tools. To complement this, using the experimentally-derived data, we build physiologically and anatomically realistic computational models of synapses, neurons and neural circuits.  Using these models, we can extrapolate our experimental data as well as come up with new predictions on neural computational rules that can again be experimentally tested. In addition, the computational models of the neural circuits and the new neural computational rules can provide new insights to developing “neuroscience-inspired AI algorithms” and neuromorphic systems.

Current projects of the lab include:

  • Development of “neuroscience-inspired” feedforward neural networks models for AI applications
  • Development of neuromorphic robot for spatial navigation