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NCT Number: NCT06551090

Prediction of Anxiety and Memory State

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.

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Key information

Age range

18 year–55 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Columbia University Irving Medical Center

New York, 10032, United States

Location status: Recruiting

Location contact

Brett E Youngerman, MD

CONTACT

[email protected]

646-317-2887

Brett E Youngerman, MD

PRINCIPAL_INVESTIGATOR

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

CAMERA (Context-Aware Multimodal Ecological Research and Assessment)

Other

The CAMERA platform is a multimodal, hardware-software framework for measuring brain-behavior interactions in an unstructured environment and predict ecological states. CAMERA will use multimodal, passive sensor data to predict anxiety-memory state in patients undergoing inpatient monitoring with intracranial electrodes for clinical epilepsy. CAMERA consists of: Wristband sensors of autonomic physiologic signals, emphasizing heart rate metrics and electrodermal activity; Smartphone usage, emphasizing natural language processing of text input for linguistic features; Subject-tracking audiovisual array, emphasizing subject vocal activity; Intracranial neural recordings, emphasizing hippocampal theta power and high-frequency activity (~70-200 Hz).

Primary outcomes

  1. Mean absolute error between predicted and actual ecological momentary assessment (EMA) scores

    Time frame: 1-30 days

    Use a multimodal machine learning model (EMANet ) to predict ≥1 EMA anxiety-memory state outcome (target) in held-out data at the population level. Mean absolute error will be the mean difference in absolute value of predicted EMA and actual EMA scores. A higher mean error represents a less accurate prediction. Prediction must use ≥2 different passive modalities, showing significantly better prediction accuracy than either of the modalities alone.

  2. Percent of subjects demonstrating improvement in the EMANet prediction over time.

    Time frame: 1-30 days

    Use EMANet to predict ≥1 ecological momentary assessment (EMA) anxiety-memory state outcome (target) demonstrating improvement over time as measured with a linear regression applied to the mean absolute error between predicted and actual EMA values measured over days. Prediction must use ≥2 different passive modalities, showing significantly better prediction accuracy than either of the modalities alone.

Secondary outcomes

  1. Mean absolute error between predicted and actual absolute error on a daily basis

    Time frame: 1-30 days

    Use a multimodal machine learning model of prediction uncertainty (UncertaintyNet) to predict the mean absolute prediction error of ecological momentary assessment (EMA) predictions in held-out data, at single-subject level on each day. Mean absolute error will measure the difference between the predicted error (based on all available data) and the actual error.

Other outcomes

  1. Jitter of neural data (milliseconds)

    Time frame: 1-30 days

    Precise synchronization of neural data with jitter <30 milliseconds.

  2. Latency of audiovisual data (seconds)

    Time frame: 1-30 days

    Precise synchronization of audiovisual data with latency <10 seconds.

  3. Latency of wrist sensor data (minutes)

    Time frame: 1-30 days

    Precise synchronization of wrist sensor data with latency <2 minutes.

  4. Latency of smartphone data (minutes)

    Time frame: 1-30 days

    Precise synchronization of smartphone data with latency <20 minutes.

  5. Jitter of ecological momentary assessment (EMA) delivery. (milliseconds)

    Time frame: 1-30 days

    Successful delivery of EMA assessments with precise synchronization of ecological momentary assessment delivery with jitter <50 milliseconds.

  6. Percentage improvement in normalized response rate to ecological momentary assessment (EMA) delivery.

    Time frame: 1-30 days

    Successful delivery of EMA assessments with ≥10% statistically significant (p<0.05) improvement in normalized response rate over time (across subjects) with implementation of context-aware EMA delivery using ResponseNet.

  7. Number of subjects demonstrating feasibility of translation to the ambulatory setting.

    Time frame: 14 days

    Collection of (synchronized) non-neural physiological, smartphone and EMA (survey and task) data from 10 outpatients in the ambulatory setting consecutively for 2 weeks with <10% passive data loss.

Study contacts

Contact information is provided by the study sponsor or research team.

Angela Velazquez

CONTACT

[email protected]

646-515-1909

Brett E Youngerman, MD

CONTACT

[email protected]

516-946-2145

Sponsors and collaborators

Lead sponsor

Columbia University

Other

Collaborators

  • National Institute of Mental Health (NIMH)
  • Rutgers University
  • University of Minnesota

Registry information

Official study title

Developing the Context-Aware Multimodal Ecological Research and Assessment (CAMERA) Platform for Continuous Measurement and Prediction of Anxiety and Memory State

Acronym: CAMERA

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
Aug 13, 2024
Registry last updated
Jan 28, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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