Cross-area dynamics during learning

Learning a new skill appears to require a distributed circuit including cognitive and motor networks. We aim to understand this process from the first exploratory attempt to the emergence of a consolidated skill. Figure on the left is from Kim et al., Nature 2023 showing changes from fast learning (stage 1, ~ 1 week) to slow learning (~ >1 week); there were changes in coupling in prefrontal cortex (PFC) and motor cortex (M1) in sleep that demarcarted changes in task-related M1 population dynamics. This transition was also closely linked to stabilization of performance accuracy.

Kim et al., Nature, 2023; Lemke et al, Nature Neuroscience, 2019; Lemke et al. eLife, 2019; Veuthey et al., Nat Comm, 2020

Network basis of memory consolidation and active forgetting during sleep

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. We aim to understand the importance of these competing processes.

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. Our perspective (Ganguly et al., Neuron, 2022) provides a more detailed perspective on this.

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 (Developing ‘Plug and Play’ Systems)

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. Video below from Natraj et al, BioRxiv, 2023 (in revision).

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

PI: Karunesh Ganguly MD PHD