Our research aims to characterize multi-scale normal and abnormal brain dynamics, with the ultimate goal to improve our understanding of the neural mechanisms underlying behavior as well as to identify robust neural signatures of neurological disorders/diseases. To achieve these goals we develop novel computational (signal processing and statistical) methods and mathematical models for the analysis of high-dimensional electrophysiological and imaging data. Our research activities lie at the intersection of neuroscience, electrical engineering, applied mathematics and statistics.
- Robust characterization of brain networks and their dynamics in the typically developing human brain during the first few years of life using large longitudinal electrophysiological (EEG) datasets
- Identification of novel neurophysiological signatures of seizure dynamics and more broadly the epileptic brain
- Multi-scale characterization of the impact of repeated sleep restriction and recovery on brain dynamics and associated cognitive performance.
This work is supported by the National Science Foundation, the National Institutes of Health and Harvard Catalyst.
Stamoulis, C., Betensky, RA (2015), Optimization of Signal Decomposition Matched Filtering for improved detection of copy-number variations in genomic data, IEEE Trans Comput Biol Bioinform (in press; PMID not yet available, DOI: 10.1109/TCBB.2015.2448077)
Stamoulis, C., Vanderwert, RE, Zeanah, CH, Fox, NA, Nelson, CA (2015), Early psychosocial deprivation adversely impacts developmental trajectories of brain rhythms and their interactions, J Cogn Neurosci, 27(12): 2512–2528, PMID: 26351990
Bick, J., Zhu, T., Stamoulis, C., Fox, N., Zeanah, C., Nelson, C.A (2015) A Randomized Clinical Trial of Foster Care as an Intervention for Early Institutionalization: Long Term Improvements in White Matter Microstructure, JAMA Pediatr, 169(3):211-9 PMID: 25622303
Stamoulis, C., Vogel-Farley, V. Degregorio, G., Jeste, S.S., Nelson, C.A (2014), Resting and Task-Modulated High-Frequency Brain Rhythms Measured by Scalp Encephalograms in Infants with TuberousvSclerosis Complex, J Autism Develop Disord, 45(2):336-53, (Epub ahead of press 2014), PMID: 23838730
Stamoulis, C., Chang, B.S (2013), Modeling Non-Invasive Neurostimulation in Epilepsy as Stochastic Interference in Brain Networks, IEEE Trans Neural Syst Rehabil Eng, 21(3):354-63, (Epub ahead of print, June 2012) PMID: 22692940
Orbach, D.B., Stamoulis, C., Strauss, K.J., Manchester, J., Smith, E.R., Scott, M.R., Lin, N., Neurointerventions in children: radiation exposure and its import, American Journal of Neuroradiology, Apr;35(4):650-6, 2014 (Epub ahead of print, October 2013), PMID: 24157736
Stamoulis, C., Schomer, D.L., Chang, B.S (2013), Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination, Epilepsy Res. 105(3):299-315, PMID: 23608198
Stamoulis, C., Gruber, L.J., Schomer, D.L., Chang, B.S (2012), High-frequency neuronal network modulations encoded in scalp EEG precede the onset of focal seizures, Epilepsy Behav, 23(4):471-80, PMID: 22410338
Stamoulis, C., Betensky, R.A (2011) A novel signal processing approach for the detection of copy-number variations in the human genome, Bionformatics, 27(17):2338-2345, PMID: 21752800
Stamoulis, C., Oberman, L.M., Praeg, E., Pascual-Leone, A (2011), Single pulse TMS-induced modulations of resting brain neurodynamics encoded in EEG phase , Brain Topography, 24(2):105-113, PMID: 21203817
Stamoulis, C., Richardson, A.G (2009), Application of Matched-Filtering to Identify Behavioral Modulation of Brain Oscillations, J. of Comput. Neurosci., 29:(1-2):63-72, PMID:19424783
Stamoulis, C., Richardson, A.G (2010) Encoding of Brain State Changes in Local Field Potentials Modulated by Motor Behaviors, J. of Comput. Neurosci., 29(3):475-83, PMID:20130974