Corticothalamic Synaptic Noise as a Mechanism for Selective Attention in Thalamic Neurons.

A reason why the thalamus is more than a passive gateway for sensory signals is that two-third of the synapses of thalamocortical neurons are directly or indirectly related to the activity of corticothalamic axons. While the responses of thalamocortical neurons evoked by sensory stimuli are well characterized, with ON- and OFF-center receptive field structures, the prevalence of synaptic noise resulting from neocortical feedback in intracellularly recorded thalamocortical neurons in vivo has attracted little attention. However, in vitro and modeling experiments point to its critical role for the integration of sensory signals.

Cortically-controlled population stochastic facilitation as a plausible substrate for guiding sensory transfer across the thalamic gateway.

The thalamus is the primary gateway that relays sensory information to the cerebral cortex. While a single recipient cortical cell receives the convergence of many principal relay cells of the thalamus, each thalamic cell in turn integrates a dense and distributed synaptic feedback from the cortex. During sensory processing, the influence of this functional loop remains largely ignored.

T-type calcium channels consolidate tonic action potential output of thalamic neurons to neocortex.

The thalamic output during different behavioral states is strictly controlled by the firing modes of thalamocortical neurons. During sleep, their hyperpolarized membrane potential allows activation of the T-type calcium channels, promoting rhythmic high-frequency burst firing that reduces sensory information transfer. In contrast, in the waking state thalamic neurons mostly exhibit action potentials at low frequency (i.

Oversampling method to extract excitatory and inhibitory conductances from single-trial membrane potential recordings.

Variations of excitatory and inhibitory conductances determine the membrane potential (V(m)) activity of neurons, as well as their spike responses, and are thus of primary importance. Methods to estimate these conductances require clamping the cell at several different levels of V(m), thus making it impossible to estimate conductances from "single trial" V(m) recordings. We present here a new method that allows extracting estimates of the full time course of excitatory and inhibitory conductances from single-trial V(m) recordings.

Network-state modulation of power-law frequency-scaling in visual cortical neurons.

Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity.