Ido Kanter (Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Israel)

Abstract:
Consistency and predictability of brain functionalities depend on reproducible activity of a single neuron. We examined the neuronal response latency, the time-gap between stimulation and evoked spike, of a neuron embedded within a large-scale network of cortical cells in vitro, but functionally separated from the network by synaptic blockers. We identified a reproducible non-chaotic neuronal phase where deviations between concave response latency profiles of a single neuron do not increase with the number of stimulations. A chaotic neuronal phase emerges at a transition to convex latency profiles which diverge exponentially, indicating irreproducible response timings. These results put a bound on the neuronal temporal resolution which can be enhanced below a millisecond using neuronal chains. In addition, we experimentally show that the neuron functions as a precise time-integrator, where the accumulated changes in neuronal response latencies, under complex and random stimulation patterns, are solely a function of a global quantity, the average time-lag between stimulations. In contrast, momentary leaps in the neuronal response latency follow trends of consecutive stimulations, indicating ultra-fast neuronal plasticity. On a circuit level, this plasticity implements error-correction mechanisms and fast detectors for misplaced stimulations.