1. When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks
- Author
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Stan C. A. M. Gielen, Magteld Zeitler, Ingo Bojak, and Atthaphon Viriyopase
- Subjects
long-range synchronization ,Computer science ,DCN MP - Plasticity and memory ,Lag ,Biophysics ,Neuroscience (miscellaneous) ,Phase (waves) ,Local field potential ,zero-lag synchronization ,01 natural sciences ,Synchronization ,lcsh:RC321-571 ,law.invention ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,0302 clinical medicine ,Relay ,law ,0103 physical sciences ,Premovement neuronal activity ,010306 general physics ,DCN NN - Brain networks and neuronal communication ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries) ,Original Research ,Phase response curve ,Spike-timing-dependent plasticity ,spike-timing dependent plasticity ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP.
- Published
- 2012