Cortical sensory processing across motivational states during goal-directed behavior.

Behavioral states can influence performance of goal-directed sensorimotor tasks. Yet, it is unclear how altered neuronal sensory representations in these states relate to task performance and learning. We trained water-restricted mice in a two-whisker discrimination task to study cortical circuits underlying perceptual decision-making under different levels of thirst.

Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices.

Subdivisions of mouse whisker somatosensory thalamus project to cortex in a region-specific and layer-specific manner. However, a clear anatomical dissection of these pathways and their functional properties during whisker sensation is lacking. Here, we use anterograde trans-synaptic viral vectors to identify three specific thalamic subpopulations based on their connectivity with brainstem.

Distinct Contributions of Whisker Sensory Cortex and Tongue-Jaw Motor Cortex in a Goal-Directed Sensorimotor Transformation.

The neural circuits underlying goal-directed sensorimotor transformations in the mammalian brain are incompletely understood. Here, we compared the role of primary tongue-jaw motor cortex (tjM1) and primary whisker sensory cortex (wS1) in head-restrained mice trained to lick a reward spout in response to whisker deflection. Two-photon microscopy combined with microprisms allowed imaging of neuronal network activity across cortical layers in transgenic mice expressing a genetically encoded calcium indicator.

Locally coordinated synaptic plasticity of visual cortex neurons in vivo.

Plasticity of cortical responses in vivo involves activity-dependent changes at synapses, but the manner in which different forms of synaptic plasticity act together to create functional changes in neurons remains unknown. We found that spike timing-induced receptive field plasticity of visual cortex neurons in mice is anchored by increases in the synaptic strength of identified spines. This is accompanied by a decrease in the strength of adjacent spines on a slower time scale.

Response-dependent dynamics of cell-specific inhibition in cortical networks in vivo.

In the visual cortex, inhibitory neurons alter the computations performed by target cells via combination of two fundamental operations, division and subtraction. The origins of these operations have been variously ascribed to differences in neuron classes, synapse location or receptor conductances. Here, by utilizing specific visual stimuli and single optogenetic probe pulses, we show that the function of parvalbumin-expressing and somatostatin-expressing neurons in mice in vivo is governed by the overlap of response timing between these neurons and their targets.

[What the whiskers tell the tactile brain].

The rodent whisker system became one of the main system models for the study of the functional properties of sensory neurons. This is due on one hand to the detailed knowledge that we have on the afferent pathways linking the mechanoreceptors in the follicles to the primary somatosensory cortex and on the other hand to the possibility of controlling the sensory input at a micrometer and millisecond scale. The observation of the natural use of the whiskers by rodents indicates that exploration of objects and textures imply multiple contacts with tens of whiskers simultaneously.

Correlated input reveals coexisting coding schemes in a sensory cortex.

As in other sensory modalities, one function of the somatosensory system is to detect coherence and contrast in the environment. To investigate the neural bases of these computations, we applied different spatiotemporal patterns of stimuli to rat whiskers while recording multiple neurons in the barrel cortex. Model-based analysis of the responses revealed different coding schemes according to the level of input correlation.

Stable learning in stochastic network states.

The mammalian cerebral cortex is characterized in vivo by irregular spontaneous activity, but how this ongoing dynamics affects signal processing and learning remains unknown. The associative plasticity rules demonstrated in vitro, mostly in silent networks, are based on the detection of correlations between presynaptic and postsynaptic activity and hence are sensitive to spontaneous activity and spurious correlations. Therefore, they cannot operate in realistic network states.

Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons.

The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states.

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.

A master equation formalism for macroscopic modeling of asynchronous irregular activity states.

Many efforts have been devoted to modeling asynchronous irregular (AI) activity states, which resemble the complex activity states seen in the cerebral cortex of awake animals. Most of models have considered balanced networks of excitatory and inhibitory spiking neurons in which AI states are sustained through recurrent sparse connectivity, with or without external input. In this letter we propose a mesoscopic description of such AI states.

Activated cortical states: experiments, analyses and models.

In awake animals, the cerebral cortex displays an "activated" state, with distinct characteristics compared to other states like slow-wave sleep or anesthesia. These characteristics include a sustained depolarized membrane potential (V(m)) and irregular firing activity. In the present paper, we evaluate our understanding of cortical activated states from a computational neuroscience point of view.

Simulation of networks of spiking neurons: a review of tools and strategies.

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes.

Equilibrium correlations in charged fluids coupled to the radiation field.

We provide an exact microscopic statistical treatment of particle and field correlations in a system of quantum charges in equilibrium with a classical radiation field. Using the Feynman-Kac-Itô representation of the Gibbs weight, the system of particles is mapped onto a collection of random charged wires. The field degrees of freedom can be integrated out, providing an effective pairwise magnetic potential.