3,934 research outputs found
Local Gating of Information Processing through the Thalamus
AbstractInhibitory sculpting of afferent signals in the thalamus is exerted by two types of neurons using γ-amino butyric acid (GABA) as neurotransmitter. Of them, local-circuit neurons exert their functions via two outputs: axons and presynaptic dendrites. In this issue of Neuron, Govindaiah and Cox reveal that synaptic activation of metabotropic glutamate receptors selectively increases the output of presynaptic dendrites of local interneurons in rat visual thalamus, without affecting the axonal output
Instability of synchronized motion in nonlocally coupled neural oscillators
We study nonlocally coupled Hodgkin-Huxley equations with excitatory and
inhibitory synaptic coupling. We investigate the linear stability of the
synchronized solution, and find numerically various nonuniform oscillatory
states such as chimera states, wavy states, clustering states, and
spatiotemporal chaos as a result of the instability.Comment: 8 pages, 9 figure
Corticothalamic projections control synchronization in locally coupled bistable thalamic oscillators
Thalamic circuits are able to generate state-dependent oscillations of
different frequencies and degrees of synchronization. However, only little is
known how synchronous oscillations, like spindle oscillations in the thalamus,
are organized in the intact brain. Experimental findings suggest that the
simultaneous occurrence of spindle oscillations over widespread territories of
the thalamus is due to the corticothalamic projections, as the synchrony is
lost in the decorticated thalamus. Here we study the influence of
corticothalamic projections on the synchrony in a thalamic network, and uncover
the underlying control mechanism, leading to a control method which is
applicable in wide range of stochastic driven excitable units.Comment: 4 pages with 4 figures (Color online on p.3-4) include
Self-Sustaining Oscillations in Complex Networks of Excitable Elements
Random networks of symmetrically coupled, excitable elements can
self-organize into coherently oscillating states if the networks contain loops
(indeed loops are abundant in random networks) and if the initial conditions
are sufficiently random. In the oscillating state, signals propagate in a
single direction and one or a few network loops are selected as driving loops
in which the excitation circulates periodically. We analyze the mechanism,
describe the oscillating states, identify the pacemaker loops and explain key
features of their distribution. This mechanism may play a role in epileptic
seizures.Comment: 5 pages, 4 figures included, submitted to Phys. Rev. Let
Subthreshold dynamics of the neural membrane potential driven by stochastic synaptic input
In the cerebral cortex, neurons are subject to a continuous bombardment of synaptic inputs originating from the network's background activity. This leads to ongoing, mostly subthreshold membrane dynamics that depends on the statistics of the background activity and of the synapses made on a neuron. Subthreshold membrane polarization is, in turn, a potent modulator of neural responses. The present paper analyzes the subthreshold dynamics of the neural membrane potential driven by synaptic inputs of stationary statistics. Synaptic inputs are considered in linear interaction. The analysis identifies regimes of input statistics which give rise to stationary, fluctuating, oscillatory, and unstable dynamics. In particular, I show that (i) mere noise inputs can drive the membrane potential into sustained, quasiperiodic oscillations (noise-driven oscillations), in the absence of a stimulus-derived, intraneural, or network pacemaker; (ii) adding hyperpolarizing to depolarizing synaptic input can increase neural activity (hyperpolarization-induced activity), in the absence of hyperpolarization-activated currents
Signal integration enhances the dynamic range in neuronal systems
The dynamic range measures the capacity of a system to discriminate the
intensity of an external stimulus. Such an ability is fundamental for living
beings to survive: to leverage resources and to avoid danger. Consequently, the
larger is the dynamic range, the greater is the probability of survival. We
investigate how the integration of different input signals affects the dynamic
range, and in general the collective behavior of a network of excitable units.
By means of numerical simulations and a mean-field approach, we explore the
nonequilibrium phase transition in the presence of integration. We show that
the firing rate in random and scale-free networks undergoes a discontinuous
phase transition depending on both the integration time and the density of
integrator units. Moreover, in the presence of external stimuli, we find that a
system of excitable integrator units operating in a bistable regime largely
enhances its dynamic range.Comment: 5 pages, 4 figure
Effects of degree distribution in mutual synchronization of neural networks
We study the effects of the degree distribution in mutual synchronization of
two-layer neural networks. We carry out three coupling strategies: large-large
coupling, random coupling, and small-small coupling. By computer simulations
and analytical methods, we find that couplings between nodes with large degree
play an important role in the synchronization. For large-large coupling, less
couplings are needed for inducing synchronization for both random and
scale-free networks. For random coupling, cutting couplings between nodes with
large degree is very efficient for preventing neural systems from
synchronization, especially when subnetworks are scale-free.Comment: 5 pages, 4 figure
Thalamic reticular nucleus induces fast and local modulation of arousal state
During low arousal states such as drowsiness and sleep, cortical neurons exhibit rhythmic slow wave activity associated with periods of neuronal silence. Slow waves are locally regulated, and local slow wave dynamics are important for memory, cognition, and behaviour. While several brainstem structures for controlling global sleep states have now been well characterized, a mechanism underlying fast and local modulation of cortical slow waves has not been identified. Here, using optogenetics and whole cortex electrophysiology, we show that local tonic activation of thalamic reticular nucleus (TRN) rapidly induces slow wave activity in a spatially restricted region of cortex. These slow waves resemble those seen in sleep, as cortical units undergo periods of silence phase-locked to the slow wave. Furthermore, animals exhibit behavioural changes consistent with a decrease in arousal state during TRN stimulation. We conclude that TRN can induce rapid modulation of local cortical state.National Institutes of Health (U.S.) (TR01 GM104948)Canadian Institutes of Health Research (Fellowship)Harvard University. Society of Fellows (Fellowship
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