A Caltech Library Service

Partially Mixed Selectivity and Parietal Cortex


Zhang, Carey Yuzhe (2018) Partially Mixed Selectivity and Parietal Cortex. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/R1RS-RJ59.


Brain-machine interfaces (BMIs) decode intention signals and other variables from the brain in order to control a computer, tablet, or prosthetic limb. In order to improve the technology, a better understanding of the representational mechanisms within the brain is necessary. Here we study how the anterior intraparietal area (AIP) of human posterior parietal cortex is able to represent many variables within a small patch of cortex. We record single unit activity using a 4 x 4 mm microelectrode array implanted in AIP of a human tetraplegic volunteer. Testing movements of different cognitive strategies, body parts, and body sides, we find that the neural population represents information in a high-dimensional way, termed "mixed selectivity", with individual units coding for idiosyncratic combinations of variables. Furthermore, we find that the variables are not randomly mixed but exhibited "partially mixed selectivity" with certain variables more randomly mixed than others. Representations were "functionally segregated", with representations of the hand and shoulder largely orthogonal despite the high degree of anatomical overlap; representations of body side and strategy were organized by body part. We also examine how the representations changed between BMI training and online BMI control. We find that the structure of the movement representations was preserved, with the different representations found during calibration maintained during online control. Finally, we study the sensory mirror system, a system that processes observed sensations similarly to experienced sensations. We once again find partially mixed selectivity and functional segregation by body parts, showing that this method of encoding information exists not just in the action intention domain but also in the sensory domain. Our results propose partially mixed selectivity as a general mechanism for encoding high dimensional in formation in a small neural population, while also advancing the possibility of limited electrode-array BMIs decoding movements of a large extent of the body.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Brain-machine interface, parietal cortex, neurons, mixed selectivity
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Andersen, Richard A.
Thesis Committee:
  • Murray, Richard M. (chair)
  • Burdick, Joel Wakeman
  • Rutishauser, Ueli
  • Andersen, Richard A.
Defense Date:17 May 2018
Non-Caltech Author Email:carey.zhang (AT)
Funding AgencyGrant Number
National Institutes of Health (NIH)5R01EY015545-12
Tianqiao and Chrissy Chen Brain-Machine Interface Center at CaltechUNSPECIFIED
Boswell FoundationUNSPECIFIED
Record Number:CaltechTHESIS:05212018-145923990
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for Ch. 3.
Zhang, Carey Yuzhe0000-0001-9867-4510
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:10918
Deposited By: Carey Zhang
Deposited On:24 May 2018 23:35
Last Modified:08 Nov 2023 00:08

Thesis Files

PDF (Dissertation) - Final Version
See Usage Policy.

[img] Video (MPEG) (Supplemental Video) - Final Version
See Usage Policy.


Repository Staff Only: item control page