Summary

Eligibility
for people ages 10-64 (full criteria)
Location
at UCLA
Dates
study started
completion around

Description

Summary

Humans have a remarkable ability to flexibly interact with the environment. A compelling demonstration of this cognitive flexibility is human's ability to respond correctly to novel contextual situations on the first attempt, without prior rehearsal. The investigators refer to this ability as 'ad hoc self-programming': 'ad hoc' because these new behavioral repertoires are cobbled together on the fly, based on immediate demand, and then discarded when no longer necessary; 'self-programming' because the brain has to configure itself appropriately based on task demands and some combination of prior experience and/or instruction. The overall goal of our research effort is to understand the neurophysiological and computational basis for ad hoc self-programmed behavior. The previous U01 project (NS 108923) focused on how these programs of action are initially created. The results thus far have revealed tantalizing notions of how the brain represents these programs and navigates through the programs. In this proposal, therefore, the investigators focus on the question of how these mental programs are executed. Based on the preliminary findings and critical conceptual work, the investigators propose that the medial temporal lobe (MTL) and ventral prefrontal cortex (vPFC) creates representations of the critical elements of these mental programs, including concepts such as 'rules' and 'locations', to allow for effective navigation through the algorithm. These data suggest the existence of an 'algorithmic state space' represented in medial temporal and prefrontal regions. This proposal aims to understand the neurophysiological underpinnings of this algorithmic state space in humans. By studying humans, the investigators will profit from our species' powerful capacity for generalization to understand how such state spaces are constructed. The investigators therefore leverage the unique opportunities available in human neuroscience research to record from single cells and population-level signals, as well as to use intracranial stimulation for causal testing, to address this challenging problem. In Aim 1 the investigators study the basic representations of algorithmic state space using a novel behavioral task that requires the immediate formation of unique plans of action. Aim 2 directly compares representations of algorithmic state space to that of physical space by juxtaposing balanced versions of spatial and algorithmic tasks in a virtual reality (VR) environment. Finally, in Aim 3, the investigators test hypotheses regarding interactions between vPFC and MTL using intracranial stimulation.

Official Title

Mapping Algorithmic State Space in the Human Brain

Keywords

Epilepsy, Single-neuron, Local-field potentials, NEUROPACE RNS SYSTEM, EMU, Epilepsy Monitoring Unit, Neuropace RNS Device

Eligibility

You can join if…

Open to people ages 10-64

  • Eligible subjects include both male and female patients, between 10 years of age and 64 years of age, who undergo placement of intracranial electrodes for clinical characterization of epilepsy.

You CAN'T join if...

  • Grounds for exclusion would include inability to understand and follow instructions, or inability to concentrate sufficiently to achieve a high proportion of correct responses.

Locations

  • University of California, Los Angeles accepting new patients
    Los Angeles California 90095 United States
  • University of Utah in progress, not accepting new patients
    Salt Lake City Utah 84112 United States
  • Baylor College of Medicine accepting new patients
    Houston Texas 77030 United States

Details

Status
accepting new patients
Start Date
Completion Date
(estimated)
Sponsor
Baylor College of Medicine
ID
NCT05283811
Study Type
Interventional
Participants
Expecting 205 study participants
Last Updated