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Most single neurons threshold models in the literature account for spike-frequency adaptation by means of a single exponential spike-triggered current. However, it is well known that, in real neurons adaptation occurs on multiple timescales, ranging from tens of milliseconds to seconds. Here, we use a Leaky Integrate-and-Fire model with escape noise extended with two adaptive mechanisms: each time a spike is fired, both an adaptive current and a change in the threshold are triggered. Importantly, the functional shape of these two processes are not imposed a priori but are directly extracted from the data. We find that pyramidal neurons of the cortex have a moving threshold that last for 200 ms and a spike triggered adapting current that lasts for at least 20 seconds. Fast-Spiking and non-Fast-Spiking interneurons have less adapting current and no moving threshold. Our model is able to predict up to 70% of the observed spikes with an accuracy of 2 ms and accurately predicts the firing-rate modulations on large timescales. These adaptation processes also influence the synaptic plasticity rules that maximize information transfer. |
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