Michael W. Cole
| Michael W. Cole | |
|---|---|
| Born | 1980 (age 45–46) San Francisco Bay Area, California, U.S. |
| 🏳️ Nationality | American |
| 🎓 Alma mater | University of California, Berkeley |
| 💼 Occupation | |
| Known for | Functional connectivity, Network neuroscience |
| 🏅 Awards | Cognitive Neuroscience Society’s Young Investigator Award (2019) |
Michael W. Cole (born 1980) is an American neuroscientist and Associate Professor of Neuroscience at the Center for Molecular and Behavioral Neuroscience at Rutgers University–Newark.[1]. Cole is known for his discovery of flexible hubs in the human brain, which are brain regions that facilitate adaptive cognition when learning new tasks[2][3]. He is known more generally for his work in cognitive neuroscience, particularly in the areas of network neuroscience and clinical neuroscience[4]. Cole directs the Cole Neurocognition Lab at Rutgers University, where his research focuses on understanding the neural mechanisms underlying cognitive control and executive functions.[5]
Early life and education
Michael W. Cole was born in 1980 in the San Francisco Bay Area, California. He earned his Bachelor’s degree in Cognitive Science from the University of California, Berkeley in 2003[6]. Cole then pursued graduate studies at the University of Pittsburgh, where he received his Ph.D. in Neuroscience in 2009. His doctoral research explored the neural basis of cognitive control using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG).
Following his Ph.D., Cole completed a postdoctoral fellowship at Washington University in St. Louis from 2009 to 2013, where he further developed his expertise in neuroimaging and network neuroscience.
Career
In 2014, Cole moved to Rutgers University–Newark to join the Center for Molecular and Behavioral Neuroscience as an Assistant Professor. He was promoted to Associate Professor in 2019.
At Rutgers University, Cole established the Cole Neurocognition Lab, which employs a combination of neuroimaging techniques, computational modeling, and machine learning to investigate the organization and function of large-scale brain networks involved in cognition.
Research
Cole’s research centers on understanding how functional connectivity within the brain supports cognitive processes such as attention, working memory, and cognitive control. He has contributed to the field of network neuroscience by developing methods to map and analyze functional brain networks[7]. His work often involves the use of fMRI, MEG, electroencephalography (EEG), and computational modeling to study brain activity and connectivity.
One of Cole’s notable contributions is the development of the activity flow modeling approach to understanding brain function, which emphasizes the importance of widespread brain networks in supporting cognitive abilities[8]. His research aims to uncover how these networks adapt to support flexible behavior and how disruptions in network connectivity may underlie neuropsychiatric disorders[9]
Awards and honors
- 2022: Web of Science Highly Cited Researcher in the field of Neuroscience and Behavior[10]
- 2019: Cognitive Neuroscience Society’s Young Investigator Award[11]
- 2010: NeuroImage Editor’s Choice Award, for Cole et al. 2010, “Identifying the brain’s most globally connected regions”[12]
- 2012: NIH Pathway to Independence Award (K99/R00)
- 2005: National Science Foundation Graduate Research Fellowship
Selected publications
- Cole, M. W., & Schneider, W. (2007). “The cognitive control network: Integrated cortical regions with dissociable functions.” NeuroImage, 37(1), 343–360.
- Cole, M. W., Reynolds, J. R., Power, J. D., Repovš, G., Anticevic, A., & Braver, T. S. (2013). “Multi-task connectivity reveals flexible hubs for adaptive task control.” Nature Neuroscience, 16(9), 1348–1355.
- Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014). “Intrinsic and task-evoked network architectures of the human brain.” Neuron, 83(1), 238–251.
- Cole, M. W., Ito, T., Bassett, D. S., & Schultz, D. H. (2016). “Activity flow over resting-state networks shapes cognitive task activations.” Nature Neuroscience, 19(12), 1718–1726.
References
- ↑ "CMBN Faculty". Retrieved November 1, 2024.
- ↑ Zanto, Theodore P.; Gazzaley, Adam (2013). "Fronto-parietal network: flexible hub of cognitive control". Trends in Cognitive Sciences. 17 (12): 602–603. doi:10.1016/j.tics.2013.10.001. PMC 3873155. PMID 24129332.
- ↑ Cole, M. W.; Reynolds, J. R.; Power, J. D.; Repovš, G.; Anticevic, A.; Braver, T. S. (2013). "Multi-task connectivity reveals flexible hubs for adaptive task control". Nature Neuroscience. 16 (9): 1348–1355. doi:10.1038/nn.3470. PMC 3758404. PMID 23892552.
- ↑ "Neuroscientist Michael Cole Uses Machine Learning and Predictive Modeling to Help Patients With Cognitive Deficits". Retrieved November 1, 2024.
- ↑ "Cole Neurocognition Lab". Retrieved November 1, 2024.
- ↑ "Michael W. Cole Curriculum Vitae" (PDF). Retrieved November 1, 2024.
- ↑ Cole, M. W.; Schneider, W. (2007). "The cognitive control network: Integrated cortical regions with dissociable functions". NeuroImage. 37 (1): 343–360. doi:10.1016/j.neuroimage.2007.03.071. PMID 17553704.
- ↑ Cole, M. W.; Ito, T.; Bassett, D. S.; Schultz, D. H. (2016). "Activity flow over resting-state networks shapes cognitive task activations". Nature Neuroscience. 19 (12): 1718–1726. doi:10.1038/nn.4406. PMC 5127712. PMID 27723746.
- ↑ Cole, M. W.; Reynolds, J. R.; Power, J. D.; Repovš, G.; Anticevic, A.; Braver, T. S. (2013). "Multi-task connectivity reveals flexible hubs for adaptive task control". Nature Neuroscience. 16 (9): 1348–1355. doi:10.1038/nn.3470. PMID 23892552.
- ↑ "Highly Cited Researchers Clarivate". 11 July 2024. Retrieved November 1, 2024.
- ↑ "Cognitive Neuroscience Society; Going with the Flow: Mapping Information in the Human Brain". 22 January 2019. Retrieved November 1, 2024.
- ↑ Cole, M. W.; Pathak, S.; Schneider, W. (2010). "Identifying the brain's most globally connected regions". NeuroImage. 49 (4): 3132–3148. doi:10.1016/j.neuroimage.2009.11.001. PMID 19909818.
External links
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