neural engineering & plasticity lab

Neurotechnology based on the network dynamics of learning and memory consolidation.


Network basis of memory consolidation and active forgetting

The motor network consists 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 generalization).  Image on right depicts that sleep patterns (slow-oscillations, delta waves, spindles) may regulate consolidation versus forgetting.

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

We aim to understand how the distributed motor network supports 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

‘Plug-and-play’ complex BCI control

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., PLoS Biology, 2009