This group discusses methods for generating and analyzing brain connectivity data (the "connectome") and how to simulate development and dynamics on anatomicially realistic neural networks. It can also be used to announce jobs, events, and CFP's.
Complex systems, when poised near a critical point of a phase transition between order and disorder, exhibit scale-free, power law dynamics. Critical systems are highly adaptive and flexibly process and store information, which prompted the conjecture that the cortex might operate at criticality. This view is supported by the recent discovery of neuronal avalanches in superficial layers of cortex. The spatiotemporal, synchronized activity patterns of avalanches form a scale-free organization that spontaneously emerges in vitro as well as in vivo in the anesthetized rat and awake monkeys. Avalanches are established at the time of superficial layer differentiation, require balanced fast excitation and inhibition, and are regulated via an inverted-U profile of NMDA/dopamine-D1 interaction. Neuronal synchronization in the form of avalanches naturally incorporates nested theta/gamma-oscillations as well as sequential activations as proposed for synfire chains. Importantly, a single avalanche is not an isolated network event, but rather its specific occurrence in time, its spatial spread, and overall size is part of an elementary organization of the dynamics that is described by three fundamental power laws. Overall, these results suggest that neuronal avalanches indicate a critical network dynamics at which the cortex gains universal properties found at criticality. These properties constitute a novel framework that allow for a precise quantification of cortex function such as the absolute discrimination of pathological from non-pathological synchronization, and the identification of maximal dynamic range for input-output processing.
Petermann, T., Thiagarajan, T. C., Lebedev, M., Nicolelis, M., Chialvo, D. R. and D. Plenz (2009) Ongoing cortical activity in awake monkeys composed of neuronal avalanches. Proc. Natl. Acad. Sci. U. S. A., (in press).
Gireesh, E.D. and D. Plenz (2009) Neuronal avalanches organize as nested theta and beta/gamma-oscillations during development of cortical layer 2/3. Proc. Natl. Acad. Sci. U. S. A., 105:7576-7581.
Pajevic, S. and D. Plenz (2008) Efficient network reconstruction from dynamics cascades identifies small-world topology of neuronal avalanches. PLoS Comp. Biol. 5: e1000271.
Stewart, C. and D. Plenz (2008) Homeostasis of neuronal avalanches during postnatal cortex development in vitro. J. Neurosci. Meth. 169:405-416.
Plenz, D. and T. Thiagarajan (2007) The organizing principles of neuronal avalanche activity: Cell assemblies in the cortex? TINS, 30:101-110.
Stewart, C. and D. Plenz (2006) Inverted-U profile of dopamine-NMDA mediated avalanche formation and retrieval in superficial layers of prefrontal cortex. J. Neurosci. 26: 8148–8159.
D. Plenz (2005) Comment on "Critical branching captures activity in living neural networks and maximizes the number of metastable states". Phys. Rev. Lett. 95: 219801.
Pfeffer, L., Ide, D., Stewart, C.V., and D. Plenz (2004) A life support systems for stimulation of and recording from rodent neuron networks grown on multi-electrode arrays. Proceedings 17th IEEE Symposium on Computer-Based Medical Systems: CBMS 2004, Eds. R. Long, S. Atani, et al, pp. 473 – 478, ISBN 0-7695-2104-5.
Beggs, J. and D. Plenz (2004) Neuronal avalanches are diverse and precise activity patterns that are stable for many hours in cortical slice cultures. J. Neurosci. 24: 5216 – 5229.
Kerr, J. and D. Plenz (2004) Action potential timing determines dendritic calcium during striatal Up-states. J. Neurosci. 24: 877 – 885.
Beggs, J. M. and D. Plenz (2003) Neuronal avalanches in neocortical circuits. J. Neurosci. 23: 11167 – 11177
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