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Biology subjects

Wernecke, H. O.

Publications and source records attributed to Wernecke, H. O..

2 recordsLinked to original sources

A note on the responsiveness of neurons

The time constant of biological neurons is typically around 5-20ms. This raises the question of how a system made of slow devices can generate and respond to faster signals. A potential solution is a population of uncorrelated neurons that, as a whole, can respond arbitrarily fast despite individual slow neurons. The response speed of a neuron or a population of neurons is often defined as how quickly neurons increase or decrease their firing rate given a change in the input, similar to a reaction time. Less emphasis is placed on the recovery time - the duration to transition and settle in a stationary state again in response to the change in the input. Here, we investigate the reaction time and the recovery time of leaky integrate-and-fire neurons given a change in, either the mean input drive, or input fluctuation level. In general, neurons react faster and fire quicker the larger the change in the input. Moreover, the closer the membrane potential is to the threshold, the faster the reaction. We observe that neurons react faster to increased input fluctuations than to stronger mean drive. Complementarily, the recovery time is systematically longer the larger the input change. Also, the closer the neurons' potentials are to the threshold, the longer it takes the neuron to recover. Most interestingly, the baseline firing of the neuron strongly determines whether recovery is faster when the change happens in the mean drive or the fluctuation level. This observation suggests that communication via the mean drive and the fluctuation level could target different aspects of the overall response - quick reaction time and the recovery speed - based on the initial baseline activity.

neuroscience↗

Controlling spatio-temporal sequences of neural activity by local synaptic changes

The neural basis of behavior is believed to consist of sequential patterns of neural activity in the relevant brain regions. Behavioral flexibility also requires neural circuit mechanisms that support dynamic control of sequential activity. However, mechanisms to control and reconfigure sequential activity have received little attention. Here, we show that recurrently connected networks with heterogeneous connectivity and a smooth spatial in-degree landscape (which may arise due to asymmetric neuron morphologies) provide a robust mechanism to evoke and control sequential activity. By modulating the synaptic strength of only a few neurons in local neighborhoods, we uncovered high-impact locations which can start, stop, extend, gate, and redirect sequences. Interestingly, high-impact locations coincide with mid in-degree regions. We demonstrate that these motifs can flexibly reconfigure sequential activity, and hence, provide a framework for fast and flexible computations on behavioral time scales, while the individual parts of the pathways remain rigid and reliable.

neuroscience↗