Neuronal oscillations have been hypothesized important for information processing. Oscillations come in short bursts, with stochastic timing and frequency. Combined with the variety of lags of long-range connections, these properties cast doubt on the reliability of their proposed functional roles. In vivo oscillations indicate a functional complexity. We will discuss how dynamic complexity allows for a multiplicity of possible phase-locking patterns to become transiently stable. Self-organization allows controlling the system's wide reconfiguration of information flow via local interventions.
We also analyze electrophysiological recordings in hippocampal circuits, investigating spiking activity patterns at the micro-level and oscillatory activity at the regional level. Using information-theoretical approaches, we characterize the primitive information processing operations that each neuron performs and show that different neurons get involved in different computing functions at different times, with roles which are thus not hardwired but dynamically reassigned at the second time scale.
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