Understanding Prefrontal and Medial Temporal Neuronal Responses to Algorithmic Cognitive Variables in Epilepsy Patients

NCT ID: NCT05283811

Last Updated: 2025-07-20

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 205 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-06-01
• Study Completion Date: 2026-03-31

Brief 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.

Conditions

Epilepsy

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: FACTORIAL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

Epilepsy Monitoring Unit

Patient's behavioral and neural activity via computer tasks and questionnaires are monitored in the Epilepsy Monitoring Unit

Group Type: OTHER

EMU

Intervention Type: BEHAVIORAL

Patients are admitted to the Epilepsy Monitoring Unit for observation of seizure activity prior to further treatment

Neuropace RNS Device

Patients are implanted with RNS device to treat their seizure activity

Group Type: OTHER

NEUROPACE RNS SYSTEM

Intervention Type: DEVICE

This device is indicated as a therapy in reducing the frequency of seizures in individuals

Interventions

NEUROPACE RNS SYSTEM

This device is indicated as a therapy in reducing the frequency of seizures in individuals

Intervention Type: DEVICE

EMU

Patients are admitted to the Epilepsy Monitoring Unit for observation of seizure activity prior to further treatment

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• 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.

Exclusion Criteria

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

• Minimum Eligible Age: 10 Years
• Maximum Eligible Age: 64 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Baylor College of Medicine

OTHER

Sponsor Role: lead

Responsible Party

Sameer Sheth

Associate Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

University of California, Los Angeles

Los Angeles, California, United States

Site Status: RECRUITING

Baylor College of Medicine

Houston, Texas, United States

Site Status: RECRUITING

University of Utah

Salt Lake City, Utah, United States

Site Status: ACTIVE_NOT_RECRUITING

Countries

United States

Central Contacts

Sameer Sheth, MD, PhD

Role: CONTACT

sasheth@bcm.edu

713-798-5060

Facility Contacts

Nanthia Suthana

Role: primary

Victoria Pirtle

Role: primary

victoria.pirtle@bcm.edu

713-798-1717

Sameer A Sheth, MD, PhD

Role: backup

sameer.sheth@bcm.edu

713-798-5060

Other Identifiers

H18112

Identifier Type: -

Identifier Source: org_study_id