The ability to tell time, anticipate future events, and produce spatiotemporal motor behaviors, are among the most fundamental computations the brain performs. Precisely because of the importance of timing to brain function, we have proposed that timing is decentralized. I will present experimental and computational studies that reveal that on the scale of seconds the brain often uses its inherent neural dynamics in the form of population clocks—including neural sequences—to encode time. Interestingly both timing and working memory (WM) share the requirement of transiently storing information for future use: prospective information in the case of timing and retrospective information in the case of WM. And some of the same neural signatures that have been implicated in timing have also been implicated in working memory. I will also present computational and psychophysical results supporting the hypothesis that in some cases the encoding time and WM may be multiplexed in neural sequences.

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Abstract: One of the longstanding goals of brain imaging is the development of "brain growth charts" to provide reference norms for measurements from brain magnetic resonance imaging (MRI) analogous to pediatric growth charts for height and weight. Brain charts could enable brain morphological measures from an individual MRI scan, such as cortical thickness or regional gray matter volume, to be placed on a continuous dimension of brain deviation from typical developmental trajectories. Analogously, one of the longstanding goals of psychiatric genetics is the development of genetic risk scores to identify youth with common or rare genetic variants at risk for neurodevelopmental psychiatric conditions such as autism or schizophrenia. The ambitious goal of widely adopted normative models with practical clinical impact has not yet been achieved -- either in brain imaging or in genomics – partly due to difficulty in amassing multi-site data, quality control, and statistical modeling challenges. This seminar will discuss our recent work, along with international consortia, focused on the development of genomic and neuroimaging normative models, including  brain charts generated from over 100,000 MRI scans across the human life cycle. The resulting models provide standardized and interpretable measure of deviation that are sensitive to differences in neuropsychiatric conditions and to interindividual variation in behavioral and cognitive outcomes in at-risk youth.

Bio: Aaron Alexander-Bloch, MPhil, MD, PhD is an Assistant Professor at the Children's Hospital of Philadelphia and the University of Pennsylvania, where he serves as the Director of the Brain-Gene-Development Lab.  He studied philosophy at Harvard College, then computational biology and neuroscience at the University of Cambridge and the National Institute of Mental Health. He completed his medical training at UCLA followed by psychiatry residency at Yale. He is the recipient of multiple awards and federally funded grants for his research. At the Brain-Gene-Development Lab, Dr. Alexander-Bloch leads a multi-disciplinary team of computational scientists focused on the integration of brain imaging, genomics and clinical data to probe neurodevelopment and its disruption in mental illness.

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