Theoretical Methods for Characterizing the Brain and Sensory-Motor Processing
LOADING
-
Neuro-Seconsory Connectome Dynamics in C. Elegans
-
Compromised Decision Making from Neurodegenerative Diseases
-
Encoding and Decoding Dynamics in Olfaction
-
Connectomic Dynamics in Olfactory Processing
-
Navigation, Behavior and Signal Processing in Odor Tracking
-
-
Patterns and Clustering in Brain Activity in ECOG
-
Spatio-Temporal Patterns in ECOG Recordings
Neuro-Sensory Dynamics and Connectomics
We develop biophysical models of neuro-sensory integration in, for instance, the model organism Caenorhabditis elegans. Building on recent experimental findings of the neuron conductances and their resolved connectome, we have posited the first full dynamic model of the neural voltage excitations that allows for a characterization of input stimuli to behavioral responses. Thus a clear connection between receptory cell inputs to downstream motor-responses is found, showing that robust, low-dimensional bifurcation structures dominate neural pathwaths of activity. The underlying bifurcation structures discovered, i.e. an induced Hopf bifurcation, are critical in explaining behavioral responses such as swimming and crawling.
Encoding and Decoding in Networks of Neurons
Neural codes in high-dimensional sensory systems produce low-dimensional embeddings of firing rate activity for known input stimulus. These stereotyped patterns of activity are the fundamental codes transmitting information in large networks of neurons. How such high-dimensional networks produce such robust patterns of activity, and how such patterns can be learned for new stimulus, are key questions being addressed in, for instance, olfactory processing in insects. We study not only the encoding space for odor classification, but also how new odors can be learned in such networks.
Selected Recent Publications
- J. Riffell, E. Shlizerman, E. Sanders, Abrel, Medina, Hinterwirth and J. N. Kutz, Flower discrimination by pollinators in a dynamic chemical environment, Science 344 (2014) 1515-1518.
- P. Maia, M. Hemphill, B. Zhender, C. Zhang, K. Parker and J. N. Kutz, Diagnostic tools for evaluating the impact of Focal Axonal Swellings arising in neurodegenerative diseases and/or traumatic brain injury, Journal of Neuroscience Methods 253 (2015) 233-242.
- J. Kunert, E. Shlizerman and J. N. Kutz, Low-dimensional functionality of complex network dynamics: Neuro-sensory integration in the Caenorhabditis elegans connectome, Physical Review E 89 (2014) 052805.
- P. Maia and J. N. Kutz Compromised axonal functionality after neurodegeneration, concussion and/or traumatic brain injury, Journal of Computational Neuroscience 27 (2014) 317-332.
- E. Shlizerman, J. Riffell and J. N. Kutz Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe, Frontiers in Neuroscience 18 (2014) article 70, 1-15.