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Articles 1 - 3 of 3
Full-Text Articles in Computational Neuroscience
Deep Jansen-Rit Parameter Inference For Model-Driven Analysis Of Brain Activity, Deepa Tilwani, Christian O'Reilly
Deep Jansen-Rit Parameter Inference For Model-Driven Analysis Of Brain Activity, Deepa Tilwani, Christian O'Reilly
Faculty Publications
Accurately modeling effective connectivity (EC) is critical for understanding how the brain processes and integrates sensory information. Yet, it remains a formidable challenge due to complex neural dynamics and noisy measurements such as those obtained from the electroencephalogram (EEG). Model-driven EC infers local (within a brain region) and global (between brain regions) EC parameters by fitting a generative model of neural activity onto experimental data. This approach offers a promising route for various applications, including investigating neurodevel- opmental disorders. However, current approaches fail to scale to whole-brain analyses and are highly noise-sensitive. In this work, we employ three deep-learning architectures—a …
The Classification Of Basket Neural Cells In The Mammalian Neocortex, Sreya Pudi
The Classification Of Basket Neural Cells In The Mammalian Neocortex, Sreya Pudi
Senior Theses
Basket neuronal cells of the mammalian neocortex have been classically categorized into two or more groups. Originally, it was thought that the large and small types are the naturally occurring groups that emerge from reasons that relate to neurobiological function and anatomical position. Later, a study based on anatomical and physiological features of these neurons introduced a third type, the net basket cell which is intermediate in size as compared to the large and small types. In this study, multivariate analysis was used to test the hypothesis that the large and small types are morphologically distinct groups. The results of …
Predicting Phase Resetting Due To Multiple Stimuli, Kelsey M. Vollmer, Davy C. Vanderweyen, Derek R. Tuck, Sorinel A. Oprisan
Predicting Phase Resetting Due To Multiple Stimuli, Kelsey M. Vollmer, Davy C. Vanderweyen, Derek R. Tuck, Sorinel A. Oprisan
Journal of the South Carolina Academy of Science
We generalized the phase resetting curve (PRC) to a more realistic case of neural oscillators receiving two or more inputs per cycle. The PRC tabulates the transient change in the firing period of a neuron due to an external perturbation, such as a presynaptic stimulus. We used a conductance-based model neuron to estimate experimentally the two-stimulus PRC and compared the results against our mathematical prediction based on the assumption of instantaneous recurrent stimulation. Within the limits of the recurrent stimulation assumptions, we found that the newly introduced prediction for the two-stimulus PRC matched experimental measurements. Our new results open the …