Ly, Cheng

Wendling, Kyle P

English

VCU Scholars Compass

Virginia Commonwealth UniversityVCU Scholars CompassBiology and Medicine Through MathematicsConference 2017May 18th, 6:00 PM - 6:30 PMNoisy Neural Oscillators with Intrinsic andNetwork HeterogeneityKyle P. WendlingVirginia Commonwealth University, wendlingk@vcu.eduCheng LyVirginia Commonwealth University, cly@vcu.eduFollow this and additional works at: http://scholarscompass.vcu.edu/bammPart of the Dynamic Systems Commons, and the Neuroscience and Neurobiology CommonsThis Event is brought to you for free and open access by the Dept. of Mathematics and Applied Mathematics at VCU Scholars Compass. It has beenaccepted for inclusion in Biology and Medicine Through Mathematics Conference by an authorized administrator of VCU Scholars Compass. Formore information, please contact libcompass@vcu.edu.http://scholarscompass.vcu.edu/bamm/2017/thursday/29Noisy Neural Oscillators with Intrinsic and Network Heterogeneity  Kyle Wendling1, Cheng Ly11 Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA E-mail: wendlingk@vcu.edu  Noisy phase oscillators have been invaluable for characterizing dynamics in many areas of the physical and life sciences.  In neuroscience in particular, they have been fruitful for developing new mathematics and in addressing neuroscience questions because these models incorporate an experimentally measurable entity.  Heterogeneity of neural attributes is recognized as a crucial feature in neural processing.  With this feature in mind, we study the population firing rate statistics in a heterogeneous coupled network of phase models.  We consider two sources of heterogeneity, intrinsic and network, both of which have been widely reported in experiments.  We find that the relationship between intrinsic and network heterogeneity can lead to relatively large differences in the firing rate distribution.  We present analytic theory to capture the shape of the firing rate distribution, and use it to uncover how intrinsic and network heterogeneity interact to yield these different firing rate distributions.  

Noisy Neural Oscillators with Intrinsic and Network Heterogeneity

https://scholarscompass.vcu.edu/cgi/viewcontent.cgi?article=1161&amp;context=bamm

Noisy Neural Oscillators with Intrinsic and Network Heterogeneity

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