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Felt, Imagined, and Seen Touch Share a Substrate in Human Posterior Parietal Cortex


Chivukula, Srinivas (2022) Felt, Imagined, and Seen Touch Share a Substrate in Human Posterior Parietal Cortex. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/0tgv-t705.


One of the most remarkable aspects of human cognition is its flexibility. We can think new thoughts, infer meaning, plan actions, predict, extrapolate, and so much more. How do our brains enable this versatility? A growing ability to simultaneously record from large populations of single neurons in human cortex has begun to provide insight. Recent studies have identified that shared populations of neurons in posterior parietal cortex (PPC) of a human subject (involved in a brain-machine interface (BMI) clinical trial) encode many aspects of motor cognition: attempted and imagined actions, observed actions and the semantic processing of action verbs. Individual units are complex, but population representations manifest rich associations across neurons, supporting diverse behavioral contexts. Here, in novel work, we establish that the same PPC substrate also encodes aspects of sensory cognition, and unpack the functional organization of information that enables this versatility. We record populations of neurons in PPC of the same human subject, a tetraplegic trial participant implanted with a 4x4 mm microelectrode array. In a series of novel results, we first establish that neurons in this PPC substrate encode actual (or felt) touch to oneself, at short latency, with bilateral receptive fields, organized by body-part. We show that imagined touch to oneself and observed touch to others engage the same substrate. To understand coding mechanisms further, we manipulated the touch location (cheek, shoulder), and the touch type (pinch, press, rub, tap). As in the motor domain, individual neurons exhibit highly variable responses. At the population-level, however, we find that the diverse touch conditions are explained by a small number of subspaces (meaningful groupings of neurons) that encode basic-level, elemental information such as touch location, and touch type. This suggests a compositional basis in PPC, such that various touch conditions are encoded through diverse combinations of common primitive elements. Moreover, these subspaces are generalizable, able to explain novel (held out) data. These principles of compositionality and generalizability suggest a basis by which PPC may support cognitive behaviors such as comprehension, in situations that extend beyond our experiences. In support of this interpretation, we show finally that this PPC substrate encodes seen touch universally – not only to insensate arm regions on the tetraplegic human subject, and to other human individuals, but also to a wide sampling of inanimate objects. As predicted, neural information combines and generalizes across conditions such that touch to objects with more similar features, is more similarly encoded. Taken together, our work is a novel, neuron-level characterization of how high-level cortex in humans may support diverse sensory, motor, and cognitive behaviors. We speculate that populations of neurons in PPC encode rich internal models of the world that can be flexibly repurposed for diverse (and novel) behavioral contexts.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Neuron; population; brain-computer interface; internal model; parietal cortex
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Biology
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Andersen, Richard A.
Thesis Committee:
  • Burdick, Joel Wakeman (chair)
  • Aflalo, Tyson
  • Pouratian, Nader
  • Prober, David A.
  • Andersen, Richard A.
Defense Date:10 May 2022
Funding AgencyGrant Number
National Institutes of Health (NIH)5R01EY015545-12
Tianqiao and Chrissy Chen Brain-Machine Interface Center at CaltechUNSPECIFIED
National Institutes of Health (NIH)NS079198
Record Number:CaltechTHESIS:05022022-175609842
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for Chapter 3
Chivukula, Srinivas0000-0002-3570-162X
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14569
Deposited By: Srinivas Chivukula
Deposited On:23 May 2022 19:30
Last Modified:08 Nov 2023 00:08

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