neural engineering & plasticity lab

Neurotechnology based on the dynamics of learning and memory consolidation.

Research Goals

  • Understand how activity patterns drive learning and consolidation of complex behaviors across a continuum of awake, rest and sleep periods.
  • Understand how activity drives long-term recovery after injury.
  • Develop methods to modulate activity patterns in order to improve recovery.
  • Translate fundamental discoveries into new therapies for individuals with paralysis.


Network basis of memory consolidation and active forgetting

Brain networks consist of interconnected cortical and subcortical areas. Large scale recordings suggest frameworks for processing such as oscillatory dynamics and cross-area filtering. We aim to delineate the network dynamics of learning, consolidation and active forgetting (which may be important for “credit assignment” and generalizable schemas).  Image on the right depicts that sleep patterns (slow-oscillations, delta waves, spindles) may regulate consolidation versus forgetting. We aim to understand the importance of these potentially competing processes.

Kim et al., Nature, 2023; Lemke et al. eLife, 2019; Kim et al., Cell, 2019; Gulati et al., Nature Neuroscience, 2017

Network basis of recovery from injury

We aim to understand how distributed brain networks support long-term recovery after injury. A particular focus in on how premotor areas can compensate through changes in coupling to the striatum and brainstem.

Ganguly et al., Neuron, 2022; Guo et al., Cell Reports, 2022; Ramanathan, Guo et al., Nature Medicine, 2018;

Real-time modulation of network dynamics to improve function

A key goal is to develop methods for large-scale modulation of network dynamics to improve function. For example, we have found that restoration of oscillatory dynamics is important.

Khanna et al., Cell, 2021; Ganguly et al., Neuron, 2022; Ramanathan, Guo et al., Nature Medicine, 2018

Long-term BCI control of an upper limb prosthetic in individuals with paralysis (‘Plug and Play’)

We aim to translate our growing understanding of memory consolidation and representational stability/plasticity to create long-term stable neuroprosthetic control that resembles our natural ability for skill consolidation.

Natraj et al., Neuron, 2022‚Äč; Silversmith*,Abiri*,Hardy*,Natraj* et al,  Nature Biotechnology, 2021; Ganguly et al., Nature Neuroscience, 2011; Ganguly et al., PLoS Biology, 2009