Clinical trial NCT06551090: Prediction of Anxiety and Memory State
Official title: Developing the Context-Aware Multimodal Ecological Research and Assessment (CAMERA) Platform for Continuous Measurement and Prediction of Anxiety and Memory State
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Anxiety
Memory
Epilepsy
Lead sponsor: Columbia University
Sponsor class: OTHER
Collaborators: name: National Institute of Mental Health (NIMH)
name: Rutgers University
name: University of Minnesota
First posted: 2024-08-13
Enrollment: 40
Sex: ALL
Minimum age (years): 18
Maximum age (years): 55
Standard ages: ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Subjects admitted to the Epilepsy Monitoring Unit with either Stereoelectroencephalography (SEEG) and/or scalp Electroencephalography (EEG)

Brief summary: The purpose of this study is to look at how signals in the brain, body, and behavior relate to anxiety and memory function. This project seeks to develop the CAMERA (Context-Aware Multimodal Ecological Research and Assessment) platform, a state-of-the-art open multimodal hardware/software system for measuring human brain-behavior relationships.

The R61 portion of the project is designed to develop the CAMERA platform, which will use multimodal, passive sensor data to predict anxiety-memory state in patients undergoing inpatient monitoring with intracranial electrodes for clinical epilepsy, as well as to build CAMERA's passive data framework and active data framework.

Detailed description: CAMERA will record neural, physiological, behavioral, and environmental signals, as well as measurements from ecological momentary assessments (EMAs), to develop a continuous high-resolution prediction of a person's level of anxiety and cognitive performance. CAMERA will provide a significant advance over current methods for human behavioral measurement because it leverages the complementary features of multimodal data sources and combines them with interpretable machine learning to predict human behavior. A further distinctive aspect of CAMERA is that it incorporates context-aware, adaptive EMA, where the timing of assessments depends on the subject's physiology and behavior to improve response rates and model learning. In this study, CAMERA focuses on predicting anxiety state and concurrent memory performance, but the platform is flexible for use in various domains.

Currently, it is challenging to study complex, longitudinal relationships between the brain, body, and environment in humans. Most existent tools do not allow the investigator to measure transient internal states or cognitive functions comprehensively or continuously. Instead the investigators typically rely on sparsely collected and constrained self-reports or experimental constructs, including EMA.

Eligibility criteria: Inclusion Criteria:

* Patients must have known or suspected Temporal Lobe Epilepsy.
* Native or proficient in speaking English or Spanish.
* Stereoelectroencephalography (sEEG) cases: The implant plan must include hippocampal head, body, and tail electrodes either unilaterally or bilaterally.
* 7th grade reading level (minimum level considered literate for adults)

Exclusion Criteria:

* Hearing impaired (i.e., not corrected with a hearing aid)
* Unable to read the newspaper at arm's length with corrective lenses.
* Objective intellectual impairment (estimated IQ \< 70)
* Any history of Electroconvulsive Therapy or psychosis (except postictal psychosis for patients)
* Psychotic disorder (lifetime)
* Current Anxiety disorder, Major Depressive Disorder, or Bipolar Disorder
* Neurodegenerative diseases, presence of widespread brain lesions, language problems (other than naming difficulty)
* Medical conditions that could potentially affect cognitive performance (e.g., human immunodeficiency virus (HIV) infection, cancer with metastatic potential).
* Acute renal failure or end-stage renal disease

Primary outcomes:
measure: Mean absolute error between predicted and actual ecological momentary assessment (EMA) scores
timeFrame: 1-30 days
measure: Percent of subjects demonstrating improvement in the EMANet prediction over time.
timeFrame: 1-30 days
Secondary outcomes:
measure: Mean absolute error between predicted and actual absolute error on a daily basis
timeFrame: 1-30 days
Other outcomes:
measure: Jitter of neural data (milliseconds)
timeFrame: 1-30 days
measure: Latency of audiovisual data (seconds)
timeFrame: 1-30 days
measure: Latency of wrist sensor data (minutes)
timeFrame: 1-30 days
measure: Latency of smartphone data (minutes)
timeFrame: 1-30 days
measure: Jitter of ecological momentary assessment (EMA) delivery. (milliseconds)
timeFrame: 1-30 days
measure: Percentage improvement in normalized response rate to ecological momentary assessment (EMA) delivery.
timeFrame: 1-30 days
measure: Number of subjects demonstrating feasibility of translation to the ambulatory setting.
timeFrame: 14 days
Locations:
city: New York
country: United States
facility: Columbia University
state: New York
Study officials:
affiliation: Columbia University
name: Joshua Jacobs, PhD
role: PRINCIPAL_INVESTIGATOR
References: