Emergence of Connectivity Motifs in Networks of Model Neurons with Short- and Long-Term Plastic Synapses
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The cortex must maintain balanced levels of neural activity to correctly integrate inputs and to provide contextually meaningful outputs. Neuronal excitation is counterbalanced by various forms of inhibition such as spike frequency adaptation, short- and l ...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections ...
Neurons are arranged in networks in which they communicate between each other by the means of synapses. Synaptic transmission can undergo activity-dependent and short-lived changes in strength, known as short-term synaptic plasticity. Short-term plasticity ...
While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical findings concerning the rules of spike timi ...
Frontiers Research Foundation2013
Neuronal firing, synaptic transmission, and its plasticity form the building blocks for processing and storage of information in the brain. It is unknown whether adult human synapses are more efficient in transferring information between neurons than roden ...
Public Library Science2014
Can we understand the interspike interval (ISI) statistics of spontaneous neural activity? What is the relation between input and output statistics of a neuron? --> Important for understanding population activity. Most theoretical studies assume that neuro ...
2014
Random networks of integrate-and-fire neurons with strong current-based synapse scan, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze ...
Frontiers Research Foundation2014
Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of t ...
Frontiers Research Foundation2014
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To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing att ...
Frontiers Research Foundation2014
How do animals learn to repeat behaviors that lead to the obtention of food or other “rewarding” objects? As a biologically plausible paradigm for learning in spiking neural networks, spike-timing dependent plasticity (STDP) has been shown to perform well ...
