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<b>11 am Friday January 26<sup>th</sup></b></div>
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<b>Jeanne Timmins Amphitheatre</b></div>
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<b>Speaker:</b></div>
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Danielle Bassett. University of Pennsylvania. <a href="https://complexsystemsupenn.com" id="OWAa6e594a8-0c9a-4f04-01c1-471f6b98d84c" class="OWAAutoLink" title="https://complexsystemsupenn.com" data-auth="NotApplicable" data-loopstyle="linkonly">
Website</a>. <a href="https://scholar.google.com/citations?user=siYpAPsAAAAJ&hl=en&oi=ao" id="OWAd5b9e732-9330-d549-7c1f-ae6b38fbd1e2" class="OWAAutoLink" title="https://scholar.google.com/citations?user=siYpAPsAAAAJ&hl=en&oi=ao" data-auth="NotApplicable" data-loopstyle="linkonly">
GoogleScholar</a>.</div>
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<div style="direction: ltr;"><span style="letter-spacing: normal; font-size: 15px; color: rgb(36, 36, 36); background-color: rgb(255, 255, 255); font-weight: 400;">The cost of brain state transitions</span></div>
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<b>Abstract:</b></div>
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<div style="direction: ltr;"><span style="letter-spacing: normal; font-size: 15px; color: rgb(36, 36, 36); background-color: rgb(255, 255, 255); font-weight: 400;">Neural tissue is a heterogeneous material characterized by fibrous and non-fibrous sectors. In
the large-scale human brain, the fibrous tissue is composed of bundles of neuronal axons along which electrical signals can propagate. These so-called white matter tracts collectively form a fiber network, or structural connectome, that both supports and constrains
complex activity dynamics. How does this constraint affect the cost of activity flow? In this talk, I will describe work that seeks to address this question using the formal mathematical approach of network control theory. Drawing on decades of work in systems
engineering, network control theory provides a framework for calculating energy costs associated with network systems reaching, maintaining, and transitioning among brain states. Using this approach, I’ll address open modeling questions and validate key assumptions,
demonstrate that theory-predicted energy costs align with biological measurements of glucose metabolism, show how the energetics of transitions depend upon brain states’ information content, and illustrate how these ideas help us to better understand processes
elicited by mindfulness training. Taken together, the studies that I will describe characterize the role of the structural connectome in constraining the flow of activity, thereby determining a formal cost of brain state transitions that is biologically grounded
and psychologically explanatory.</span></div>
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<div style="font-family: Tahoma; font-size: 13px;"><span style="font-family: wf_segoe-ui_normal, "Segoe UI", "Segoe WP", Tahoma, Arial, sans-serif, serif, EmojiFont; font-size: 10pt; color: rgb(0, 0, 0);">Bratislav Misic, PhD</span></div>
<div style="font-family: Tahoma; font-size: 13px;"><span style="font-family: wf_segoe-ui_normal, "Segoe UI", "Segoe WP", Tahoma, Arial, sans-serif, serif, EmojiFont; font-size: 10pt; color: rgb(0, 0, 0);">Montreal Neurological Institute</span></div>
<div style="font-family: Tahoma; font-size: 13px;"><span style="font-family: wf_segoe-ui_normal, "Segoe UI", "Segoe WP", Tahoma, Arial, sans-serif, serif, EmojiFont; font-size: 10pt; color: rgb(0, 0, 0);"><a href="https://netneurolab.github.io/" id="OWA45e6ddd1-0225-80c1-13fa-08dcbc31a965" class="x_OWAAutoLink" title="https://netneurolab.github.io/" data-auth="NotApplicable" data-loopstyle="linkonly">https://netneurolab.github.io/</a></span></div>
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