Current Research Areas
Analysis of large-scale brain activity
We develop techniques for analyzing and visualizing the rich spatiotemporal structure and network organization of brain activity. In one avenue, we are studying time-varying changes in fMRI signal characteristics across scales of seconds to minutes, and using multimodal imaging and behavioral measures to examine patterns that may give rise to ongoing physiological and cognitive processes. These "dynamic" imaging features may reveal new information about state-dependent brain activity and provide more sensitive disease biomarkers.
Selected publications:
C Chang, GH Glover. Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage. 2010 Mar; 50(1):81-98.
RG Bayrak*, N Hoang*, CB Hansen, C Chang, M Berger. PRAGMA: Interactively Constructing Functional Brain Parcellations. IEEE Transactions on Visualization and Computer Graphics, 2020.
RM Hutchison*, T Womelsdorf, EA Allen, PA Bandettini, VD Calhoun, M Corbetta, S Della Penna, JH Duyn, GH Glover, J Gonzalez-Castillo, DA Handwerker, S Keilholz, V Kiviniemi, DA Leopold, F de Pasquale, O Sporns, M Walter, C Chang*. Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage 2013 80:360-78
JP Hamilton, DJ Furman, C Chang, ME Thomason, E Dennis, IH Gotlib. Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination. Biol Psychiatry 2011 70:327-33
State-dependent brain activity
Vigilance states are closely intertwined with behavior, cognition, and numerous disorders. By integrating fMRI with simultaneous EEG, behavioral, and physiological recordings, we are studying brain-wide signatures of vigilance and autonomic activity, and developing computational methods for detecting changes in vigilance levels from fMRI data alone. This research also aims to increase the sensitivity of fMRI studies more broadly by modeling state-related variability in fMRI datasets.
Selected publications:
SE Goodale, N Ahmed, C Zhao, JA de Zwart, PS Özbay, D Picchioni, JH Duyn, DJ Englot, VL Morgan, C Chang. fMRI-based detection of alertness predicts behavioral response variability. eLife, 10:e62376.
CG Martin, BJ He, C Chang. State-related neural influences on fMRI connectivity estimation. Neuroimage, 244:118590.
C Chang, DA Leopold, ML Scholvinck, H Mandelkow, D Picchioni, X Liu, FQ Ye, J N Turchi, JH Duyn. Tracking brain arousal fluctuations with fMRI. PNAS 2016
J Turchi*, C Chang*, FQ Ye, BE Russ, DK Yu, CR Cortes, IE Monosov, JH Duyn, DA Leopold. The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations. Neuron 2018
C Chang*, CD Metzger*, GH Glover, JH Duyn, HJ Heinze, M Walter. Association between heart rate variability and fluctuations in resting-state functional connectivity. Neuroimage 2013 68:93-104
C Chang, Z Liu, MC Chen, X Liu, JH Duyn. EEG correlates of time-varying BOLD functional connectivity. Neuroimage 2013 72:227-36
Mechanisms and origins of fMRI signals/networks
fMRI signals have complex neural and physiological underpinnings. In one avenue, we work on characterizing the effects of systemic physiological processes on fMRI signals and their long-range correlation patterns, translating this knowledge into tools for improving the sensitivity and interpretation of fMRI studies. Secondly, to probe the mechanisms supporting large-scale network organization, we integrate fMRI with complementary biological measures and targeted manipulations of neural circuits.
Selected publications:
RG Bayrak, CB Hansen, JA Salas, N Ahmed, I Lyu, Y Huo, C Chang. From Brain to Body: Learning Low-Frequency Respiration and Cardiac Signals from fMRI Dynamics. MICCAI 2021.
JA Salas, RG Bayrak, Y Huo, C Chang. Reconstruction of respiratory variation signals from fMRI data. Neuroimage 225:117459 (2020).
C Chang, JP Cunningham, GH Glover. Influence of heart rate on the BOLD signal: the cardiac response function. Neuroimage 2009 44:857-69
C Chang, ME Thomason, GH Glover. Mapping and correction of vascular hemodynamic latency in the BOLD signal. Neuroimage 2008 43:90-102
AC Chen, DJ Oathes, C Chang, T Bradley, ZW Zhou, LM Williams, GH Glover, K Deisseroth, A Etkin. Causal interactions between fronto-parietal central executive and default-mode networks in humans. PNAS 2013
Richiardi J*, Altmann A*, Milazzo AC, Chang C, Chakravarty MM, [et al.], Greicius MD; IMAGEN consortium. Correlated gene expression supports synchronous activity in brain networks. Science 2015
