Zoom link: https://iu.zoom.us/j/97589644080
Leonid Rubchinsky,
Joel Zirkle**The impact of noise on the temporal patterning of neural synchronization**
**Joel Zirkle 1, Leonid Rubchinsky1,2**
1 Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN 46032, USA
2 Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN 46032, USA
E-mail: lrubchin@iupui.edu
Neural synchrony in the brain is often present in an intermittent fashion, i.e. there are intervals of synchronized activity interspersed with intervals of desynchronized activity. A series of experimental studies showed that the temporal patterning of neural synchronization may be very specific exhibiting predominantly short (although potentially numerous) desynchronized episodes [1] and may be correlated with behavior (even if the average synchrony strength is not changed) [2,3,4]. Prior computational neuroscience research showed that a network with many short desynchronized intervals may be functionally different than a network with few long desynchronized intervals [5]. In this study, we investigated the effect of noise on the temporal patterns of synchronization. We employed a simple network of two conductance- based neurons that were mutually connected via excitatory synapses. The resulting dynamics of the network was studied using the same time-series analysis methods used in prior experimental and computational studies. It has been well known that synchrony strength degrades with noise. We found that noise also affects the temporal patterning of synchrony. Increase in the noise level promotes dynamics with predominantly short desynchronizations. Thus, noise may be one of the mechanisms contributing to the short desynchronization dynamics observed in multiple experimental studies.
Acknowledgement
This work was supported by NSF grant DMS 1813819.
References
1\. Ahn S, Rubchinsky LL. Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms. Chaos. 2013, 23, 013138.
2\. Ahn S, Rubchinsky LL, Lapish CC. Dynamical reorganization of synchronous
activity patterns in prefrontal cortex - hippocampus networks during behavioral
sensitization. Cerebral Cortex 2014, 24, 2553-2561.
3\. Ahn S, Zauber SE, Worth RM, Witt T, Rubchinsky LL. Neural synchronization: average strength vs. temporal patterning. Clinical Neurophysiology 2018, 129, 842-844.
4\. Malaia E, Ahn S, Rubchinsky LL. Dysregulation of temporal dynamics of
synchronous neural activity in adolescents on autism spectrum. Autism Research 2020, 13, 24-
31.
5\. Ahn S, Rubchinsky LL. Potential mechanisms and functions of intermittent neural synchronization. Frontiers in Computational Neuroscience 2017, 11, 44.
