Dissociated networks of neurons typically exhibit bursting behavior, whose features are strongly influenced by the age of the culture, by chemical/electrical stimulation or by environmental conditions. To help the experimenter in identifying the changes possibly induced by specific protocols, we developed a self-adapting method for detecting both bursts and network bursts from electrophysiological activity recorded by means of micro-electrode arrays. The algorithm is based on the computation of the logarithmic inter-spike interval histogram and automatically detects the best threshold to distinguish between inter- and intra-burst inter-spike intervals for each recording channel of the array. An analogous procedure is followed for the detection of network bursts, looking for sequences of closely spaced single-channel bursts. We tested our algorithm on recordings of spontaneous as well as chemically stimulated activity, comparing its performance to other methods available in the literature.
Large scale transitions between active (up) and silent (down) states during quiet wakefulness or NREM sleep regulate fundamental cortical functions and are known to involve both excitatory and inhibitory cells. However, if and how inhibition regulates these activity transitions is unclear. Using fluorescence-targeted electrophysiological recording and cell-specific optogenetic manipulation in both anesthetized and non-anesthetized mice, we found that two major classes of interneurons, the parvalbumin and the somatostatin positive cells, tightly control both up-to-down and down-to-up state transitions. Inhibitory regulation of state transition was observed under both natural and optogenetically-evoked conditions. Moreover, perturbative optogenetic experiments revealed that the inhibitory control of state transition was interneuron-type specific. Finally, local manipulation of small ensembles of interneurons affected cortical populations millimetres away from the modulated region. Together, these results demonstrate that inhibition potently gates transitions between cortical activity states, and reveal the cellular mechanisms by which local inhibitory microcircuits regulate state transitions at the mesoscale.DOI:
http://dx.doi.org/10.7554/eLife.26177.001
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