Local cortical circuit model inferred from power-law distributed neuronal avalanches
- 401 Downloads
How cortical neurons process information crucially depends on how their local circuits are organized. Spontaneous synchronous neuronal activity propagating through neocortical slices displays highly diverse, yet repeatable, activity patterns called “neuronal avalanches”. They obey power-law distributions of the event sizes and lifetimes, presumably reflecting the structure of local circuits developed in slice cultures. However, the explicit network structure underlying the power-law statistics remains unclear. Here, we present a neuronal network model of pyramidal and inhibitory neurons that enables stable propagation of avalanche-like spiking activity. We demonstrate a neuronal wiring rule that governs the formation of mutually overlapping cell assemblies during the development of this network. The resultant network comprises a mixture of feedforward chains and recurrent circuits, in which neuronal avalanches are stable if the former structure is predominant. Interestingly, the recurrent synaptic connections formed by this wiring rule limit the number of cell assemblies embeddable in a neuron pool of given size. We investigate how the resultant power laws depend on the details of the cell-assembly formation as well as on the inhibitory feedback. Our model suggests that local cortical circuits may have a more complex topological design than has previously been thought.
KeywordsNeuronal wiring Synchronization Cell assembly Synfire chain Cortical network development
The authors express their sincere thanks to T. Hensch and N. Yamamoto for fruitful discussions about the development of the cortical circuits. The present work was partially supported by Grants in Aid for Scientific Research of Priority Areas and Grant-in-Aid for Young Scientists (B) from the Japanese Ministry of Education, Culture, Sports, Science and Technology.
- Abbott LF, Rohrkemper R (2006) A simple growth model constructs critical avalanche networks. Prog. Brain Res. in press.Google Scholar
- Abeles M (1991) Corticonics: Neural Circuits of the Cerebral Cortex. Cambridge University Press, Cambridge.Google Scholar
- Amari S (1988) Associative memory and its statistical neurodynamical analysis. In: Neural and synergetic computers. Haken H (ed.) Springer-Verlag, Berlin, pp. 85–99.Google Scholar
- Braitenberg V, Schuz A (1998) Cortex: Statics and Geometry of Neuronal Connectivity. Springer-Verlag, Berlin.Google Scholar
- Harris TE (1989) The Theory of Branching Processes. Dover, New York.Google Scholar
- Levina A, Herrmann JM, Geisel T (2006) Dynamical Synapses give rise to a power-law distribution of neuronal avalanches. Adv. in Neural Information Processing Systems.Google Scholar
- Peinado A (2000) Traveling slow waves of neural activity: a novel form of network activity in developing neocortex. J. Neurosci. 20: RC54:1–6.Google Scholar
- Rolls ET, Treves A (1998) Neural Networks and Brain Function. Oxford University Press, New York.Google Scholar
- Stewart CV, Gerfen CR, Plenz D (2004) Dopamine facilitates “neuronal avalanches” and “synfire chains” in layer 2/3 of rat somatosensory cortex slices. Abs. Soc. Neurosci.Google Scholar
- Teramae J, Fukai T (2005) Neuronal avalanches as a probe for cortical circuit structure. Abs. Soc. Neurosci.Google Scholar