Neuronal response impedance mechanism implementing cooperative networks with low firing rates and μs precision

Abstract

Realizations of low firing rates in neural networks usually require globally balanced distributions among excitatory and inhibitory links, while feasibility of temporal coding is limited by neuronal millisecond precision. We show that cooperation, governing global network features, emerges through nodal properties, as opposed to link distributions. Using in vitro and in vivo experiments we demonstrate microsecond precision of neuronal response timings under low stimulation frequencies, whereas moderate frequencies result in a chaotic neuronal phase characterized by degraded precision. Above a critical stimulation frequency, which varies among neurons, response failures were found to emerge stochastically such that the neuron functions as a low pass filter, saturating the average inter-spike-interval. This intrinsic neuronal response impedance mechanism leads to cooperation on a network level, such that firing rates are suppressed toward the lowest neuronal critical frequency simultaneously with neuronal microsecond precision. Our findings open up opportunities of controlling global features of network dynamics through few nodes with extreme properties.

Oscillations in networks of networks stem from adaptive nodes with memory

“…S1 and S2), and that p sp (m•d)=m•d•fc for all m<(fc•d) -1 and 1 for m>(fc•d) -1 , Eq. (7) can be written as a finite sum: (8) In case any of the probabilities stochastically deviates from [0,1], it truncates to the boundaries.…”

“…We test our analytical framework on a model where nodes have activity-dependent response probability. Although this model is based on experimental results on neural networks [8][9][10][11] , their dynamics resemble many other physical systems 12 .…”

Fast reversible learning based on neurons functioning as anisotropic multiplex hubs

“…2a. The first 500 stimulations demonstrate a typical behavior of a stimulated neuron -the nodal plasticity [10]. The NRL initially increases by several milliseconds, without response failures (light-gray background in figs.…”

“…Besides the synaptic plasticity, the plasticity of the neurons [10] was recently found as a source for controlling the network's firing homeostasis and for spontaneous cortical oscillations [11]. The major expressions of the nodal plasticity are the changes in the nodal response timings, the neuronal response latency (NRL), and nodal response probability, resulting in a saturated low-firing frequency, independent of the stimulation frequency.…”

“…The major expressions of the nodal plasticity are the changes in the nodal response timings, the neuronal response latency (NRL), and nodal response probability, resulting in a saturated low-firing frequency, independent of the stimulation frequency. When a neuron is repeatedly stimulated above its characteristic critical frequency (typically ranging between 1 and 30 Hz) its response latency is gradually stretched by several milliseconds until the emergence of a new phase, the intermittent phase, characterized by stochastic response failures which maintain its critical firing frequency [10] (fig. 1b).…”