Back to results

City University of New York - City College

Characterization of the Intrinsic Neural Timescale Indices as a Reliable Fingerprint of Brain Dynamics

Abstract

dc:description.abstract

<p>Intrinsic neural timescales (INTs) characterize the persistence of neural activity over time and offer insight into the brain’s temporal hierarchy. This thesis evaluates and compares six autocorrelation-based INT metrics—AR(1) Coefficient (Autoregressive Coefficient at 1), First Zero Lag, Lag at ACF = 1/e, Sum of Positive ACFs, ACF at Half Lag, Exponential Decay Constant (τ)— using resting-state fMRI data from 400 cortical regions across a large, lifespan sample (ages 6– 85) from the NKI-Rockland dataset. A discriminability analysis revealed that the AR(1) coefficient provided the highest test-retest reliability and individual specificity across repeated scans, establishing it as the most reliable INT estimator. Using the AR(1) metric, we investigated how intrinsic timescales vary systematically with age, sex, across the cortical hierarchy. A linear mixedeffects model revealed nonlinear (inverted-U) age trends, sex interactions, and widespread motion sensitivity, particularly in sensory and salience networks. These findings support the existence of a developmentally structured gradient of cortical temporal dynamics and underscore the need for careful metric selection and motion correction in INT research. By combining comparative metric evaluation with a lifespan analysis, this study lays the groundwork for establishing normative baselines essential for future clinical investigations into neurodevelopmental disorders.</p>

Degree

thesis:*
Name thesis:degree_name
Master of Science (M.S.)
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Biomedical Engineering
Year dc:date.available
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Honarpisheh, Helya
Contributors dc:contributor
  • Ting Xu
  • Lucas Parra
  • Jacek Dmochowski

Subjects

dc:subject × 8

Identifiers

dc:identifier.*
Repository record dc:identifier
https://academicworks.cuny.edu/cc_etds_theses/1266
OAI identifier oai:identifier
oai:academicworks.cuny.edu:cc_etds_theses-2335

Chain of custody

source
Harvested from
City University of New York - City College
Base URL
academicworks.cuny.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Honarpisheh, Helya. Characterization of the Intrinsic Neural Timescale Indices as a Reliable Fingerprint of Brain Dynamics. Thesis thesis, 2025. https://academicworks.cuny.edu/cc_etds_theses/1266