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Inhibition, population coupling, behavior, and Rett syndrome
Published in Nature Communications. We use 3D motion capture to measure body movement and 32 channel chronic electrode implants to record single unit activity in primary motor cortex. We also impose pharmacological changes to inhibition. We found that neurons that are strongly coupled to ongoing cortical activity are weakly coupled to body movements, and vice versa. This relationship may be disrupted in Rett syndrome. Funded by National Institutes of Health, Foundational Questions Institute and Arkansas Bioscience Institute.
Mechanisms of retronasal olfaction
We perform recordings of many single neurons in olfactory bulb and piriform cortex as odorants are inhaled (orthonasal) and exhaled (retronasal). We aim to determine new coding principles that distinguish retro and orthonasal olfaction. We also perform micro CT imaging of rat nasal cavities and computer modeling of fluid flow and neural network models. This is a collaboration with Cheng Ly (VCU) and Andrea Barreiro (SMU). Supported by National Science Foundation and Arkansas Bioscience Institute.
Scale-change symmetry of the rules governing neural systems
Published in iScienceWe have developed an approach based on renormalization group theory from physics to study a basic symmetry of the laws that govern network dynamics of neurons. We use computational models and analyze experimental data (from Knopfel Lab). We find that the governing rules of neural systems become symmetric to changes in scale (like a fractal) near dynamical phase transitions. This could explain why diverse experimental systems display similar critical dynamics. Funded by National Science Foundation. Made possible by Arkansas High Performance Computing Center.
Clawson, W. P., Wright, N. C., Wessel, R. & Shew, W. L. Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection. PLOS Comput. Biol. 13, e1005574 (2017).
Roisen, D. A., & Shew, W. L. (2020). Fractal brain dynamics: from Mandelbrot to marmosets. The Journal of Physiology.
Virkar, Y. S., Restrepo, J. G., Shew, W. L., & Ott, E. (2020). Dynamic regulation of resource transport induces criticality in interdependent networks of excitable units. Physical Review. E, 101(2–1), 022303.
Nur T, Gautam SH, Stenken JA, Shew WL (2019) Probing spatial inhomogeneity of cholinergic changes in cortical state in rat. Sci Rep 9:9387.
Ly, C., Shew, W. L. & Barreiro, A. K. Efficient calculation of heterogeneous non-equilibrium statistics in coupled firing-rate models. J. Math. Neurosc. 7, (2019).
Agrawal, V. et al. Robust entropy requires strong and balanced excitatory and inhibitory synapses. Chaos An Interdiscip. J. Nonlinear Sci. 28, 103115 (2018).
Hoseini, M. S. et al. Induced cortical oscillations in turtle cortex are coherent at the mesoscale of population activity, but not at the microscale of the membrane potential of neurons. J. Neurophysiol. 118, (2017).
Hoseini, M. S. et al. The turtle visual system mediates a complex spatiotemporal transformation of visual stimuli into cortical activity. J. Comp. Physiol. A (2017).
Fakhraei, L., Gautam, S. H. & Shew, W. L. State-dependent intrinsic predictability of cortical network dynamics. PLoS One 12, e0173658 (2017).
Virkar, Y. S., Shew, W. L., Restrepo, J. G. & Ott, E. Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain. Phys. Rev. E 94, 042310 (2016).
Fagerholm, E. D. et al. Cascades and Cognitive State: Focused Attention Incurs Subcritical Dynamics. J. Neurosci. 35, 4626–4634 (2015).
Yang, H., Shew, W. L., Roy, R. & Plenz, D. in Criticality in Neural Systems (eds. Plenz, D. & Niebur, E.) 335–346 (Wiley, 2014).
Larremore, D. B., Shew, W. L. & Restrepo, J. G. Critical Dynamics in Complex Networks. Criticality in Neural Systems (2014).
Yang, H., Shew, W. L., Roy, R. & Plenz, D. Peak Variability and Optimal Performance in Cortical Networks at Criticality. Criticality in Neural Systems (2014).
Grady, S. K., Hoang, T. T., Gautam, S. H. & Shew, W. L. Millisecond, Micron Precision Multi-Whisker Detector. PLoS One 8, e73357 (2013).
Yang, H., Shew, W. L., Roy, R. & Plenz, D. Maximal Variability of Phase Synchrony in Cortical Networks with Neuronal Avalanches. J. Neurosci. 32, 1061–1072 (2012).
Plenz, D. et al. Multi-electrode array recordings of neuronal avalanches in organotypic cultures. J. Vis. Exp. (2011). doi:10.3791/2949
Larremore, D. B., Shew, W. L., Ott, E. & Restrepo, J. G. Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus. Chaos 21, 025117 (2011).
Shew, W. L., Bellay, T. & Plenz, D. Simultaneous multi-electrode array recording and two-photon calcium imaging of neural activity. J. Neurosci. Methods 192, 75–82 (2010).
Lyotard, N., Shew, W. L., Bocquet, L. & Pinton, J.-F. Polymer and surface roughness effects on the drag crisis for falling spheres. Eur. Phys. J. B 60, 469–476 (2008).
Gasteuil, Y. et al. Lagrangian Temperature, Velocity, and Local Heat Flux Measurement in Rayleigh-Bénard Convection. Phys. Rev. Lett. 99, 1–4 (2007).
Shew, W. L., Gasteuil, Y., Gibert, M., Metz, P. & Pinton, J.-F. Instrumented tracer for Lagrangian measurements in Rayleigh-Bénard convection. Rev. Sci. Instrum. 78, 065105 (2007).
Shew, W. & Pinton, J.-F. Dynamical Model of Bubble Path Instability. Phys. Rev. Lett. 97, 6–9 (2006).
Shew, W. L., Poncet, S. & Pinton, J.-F. Force measurements on rising bubbles. J. Fluid Mech. 569, 51 (2006).
Shew, W. L. & Pinton, J.-F. Viscoelastic effects on the dynamics of a rising bubble. J. Stat. Mech. Theory Exp. 2006, P01009–P01009 (2006).
Shew, W. & Lathrop, D. Liquid sodium model of geophysical core convection. Phys. Earth Planet. Inter. 153, 136–149 (2005).
Sisan, D., Shew, W. L. & Lathrop, D. P. Lorentz force effects in magneto-turbulence. Phys. Earth Planet. Inter. 135, 137–159 (2003).
Shew, W. L., Coy, H. A. & Lindner, J. F. Taming chaos with disorder in a pendulum array. Am. J. Phys. 67, 703 (1999).