Spontaneous cortical activity is transiently poised close to criticality.

Brain activity displays a large repertoire of dynamics across the sleep-wake cycle and even during anesthesia. It was suggested that criticality could serve as a unifying principle underlying the diversity of dynamics. This view has been supported by the observation of spontaneous bursts of cortical activity with scale-invariant sizes and durations, known as neuronal avalanches, in recordings of mesoscopic cortical signals. However, the existence of neuronal avalanches in spiking activity has been equivocal with studies reporting both its presence and absence. Here, we show that signs of criticality in spiking activity can change between synchronized and desynchronized cortical states. We analyzed the spontaneous activity in the primary visual cortex of the anesthetized cat and the awake monkey, and found that neuronal avalanches and thermodynamic indicators of criticality strongly depend on collective synchrony among neurons, LFP fluctuations, and behavioral state. We found that synchronized states are associated to criticality, large dynamical repertoire and prolonged epochs of eye closure, while desynchronized states are associated to sub-criticality, reduced dynamical repertoire, and eyes open conditions. Our results show that criticality in cortical dynamics is not stationary, but fluctuates during anesthesia and between different vigilance states.

Hidden complexity of synaptic receptive fields in cat V1.

In the primary visual cortex (V1), Simple and Complex receptive fields (RFs) are usually characterized on the basis of the linearity of the cell spiking response to stimuli of opposite contrast. Whether or not this classification reflects a functional dichotomy in the synaptic inputs to Simple and Complex cells is still an open issue. Here we combined intracellular membrane potential recordings in cat V1 with 2D dense noise stimulation to decompose the Simple-like and Complex-like components of the subthreshold RF into a parallel set of functionally distinct subunits. Results show that both Simple and Complex RFs exhibit a remarkable diversity of excitatory and inhibitory Complex-like contributions, which differ in orientation and spatial frequency selectivity from the linear RF, even in layer 4 and layer 6 Simple cells. We further show that the diversity of Complex-like contributions recovered at the subthreshold level is expressed in the cell spiking output. These results demonstrate that the Simple or Complex nature of V1 RFs does not rely on the diversity of Complex-like components received by the cell from its synaptic afferents but on the imbalance between the weights of the Simple-like and Complex-like synaptic contributions.

Horizontal connectivity in V1: Prediction of coherence in contour and motion integration.

This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150-250°/s when it matches the propagation speed of horizontal connectivity (0.15-0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal "prediction" wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.

Involvement of nicotinic and muscarinic receptors in the endogenous cholinergic modulation of the balance between excitation and inhibition in the young rat visual cortex.

This study aims to clarify how endogenous release of cortical acetylcholine (ACh) modulates the balance between excitation and inhibition evoked in visual cortex. We show that electrical stimulation in layer 1 produced a significant release of ACh measured intracortically by chemoluminescence and evoked a composite synaptic response recorded intracellularly in layer 5 pyramidal neurons of rat visual cortex. The pharmacological specificity of the ACh neuromodulation was determined from the continuous whole-cell voltage clamp measurement of stimulation-locked changes of the input conductance during the application of cholinergic agonists and antagonists. Blockade of glutamatergic and gamma-aminobutyric acid (GABAergic) receptors suppressed the evoked response, indicating that stimulation-induced release of ACh does not directly activate a cholinergic synaptic conductance in recorded neurons. Comparison of cytisine and mecamylamine effects on nicotinic receptors showed that excitation is enhanced by endogenous evoked release of ACh through the presynaptic activation of alpha(*)beta4 receptors located on glutamatergic fibers. DHbetaE, the selective alpha4beta2 nicotinic receptor antagonist, induced a depression of inhibition. Endogenous ACh could also enhance inhibition by acting directly on GABAergic interneurons, presynaptic to the recorded cell. We conclude that endogenous-released ACh amplifies the dominance of the inhibitory drive and thus decreases the excitability and sensory responsiveness of layer 5 pyramidal neurons.

[Multiscale functional imaging: reconstructing network dynamics from the synaptic echoes recorded in a single visual cortex neuron]. / Imagerie fonctionnelle multi-echelle: reconstruction de la dynamique corticale a partir des echos synaptiques enregistrés dans un seul neurone.

In vivo intracellular electrophysiology offers the unique possibility of listening to the "synaptic rumor " of the cortical network, captured by a recording electrode in a single V1 cell. It allows one to reconstruct the distribution of input sources in space and time, i.e. the effective network dynamics. We have used a reverse engineering method to demonstrate the propagation of visually evoked activity through lateral (and feedback) connectivity in the primary cortex of higher mammals. This approach, based on synaptic echography, is compared here with a real-time brain imaging technique based on voltage-sensitive dye imaging. The former method gives access to the microscopic convergence processes of single neurons, whereas the latter describes the macroscopic divergence process on the neuronal map. A combination of the two techniques can be used to elucidate the cortical origin of low-level (non attentive) binding processes participating in the emergence of Gestalt percepts.

Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning.

This intracellular study investigates synaptic mechanisms of orientation and direction selectivity in cat area 17. Visually evoked inhibition was analyzed in 88 cells by detecting spike suppression, hyperpolarization, and reduction of trial-to-trial variability of membrane potential. In 25 of these cells, inhibition visibility was enhanced by depolarization and spike inactivation and by direct measurement of synaptic conductances. We conclude that excitatory and inhibitory inputs share the tuning preference of spiking output in 60% of cases, whereas inhibition is tuned to a different orientation in 40% of cases. For this latter type of cells, conductance measurements showed that excitation shared either the preference of the spiking output or that of the inhibition. This diversity of input combinations may reflect inhomogeneities in functional intracortical connectivity regulated by correlation-based activity-dependent processes.

Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons.

We review here the development of Hodgkin-Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are "fast spiking", "regular spiking", "intrinsically bursting" and "low-threshold spike" cells. For each class, we fit "minimal" HH type models to experimental data. The models contain the minimal set of voltage-dependent currents to account for the data. To obtain models as generic as possible, we used data from different preparations in vivo and in vitro, such as rat somatosensory cortex and thalamus, guinea-pig visual and frontal cortex, ferret visual cortex, cat visual cortex and cat association cortex. For two cell classes, we used automatic fitting procedures applied to several cells, which revealed substantial cell-to-cell variability within each class. The selection of such cellular models constitutes a necessary step towards building network simulations of the thalamocortical system with realistic cellular dynamical properties.

Spatially Structured Sparse Morphological Component Separation for voltage-sensitive dye optical imaging.

BACKGROUND: Voltage-sensitive dye optical imaging is a promising technique for studying in vivo neural assemblies dynamics where functional clustering can be visualized in the imaging plane. Its practical potential is however limited by many artifacts. NEW METHOD: We present a novel method, that we call "SMCS" (Spatially Structured Sparse Morphological Component Separation), to separate the relevant biological signal from noise and artifacts. It extends Generalized Linear Models (GLM) by using a set of convex non-smooth regularization priors adapted to the morphology of the sources and artifacts to capture. RESULTS: We make use of first order proximal splitting algorithms to solve the corresponding large scale optimization problem. We also propose an automatic parameters selection procedure based on statistical risk estimation methods. COMPARISON WITH EXISTING METHODS: We compare this method with blank subtraction and GLM methods on both synthetic and real data. It shows encouraging perspectives for the observation of complex cortical dynamics. CONCLUSIONS: This work shows how recent advances in source separation can be integrated into a biophysical model of VSDOI. Going beyond GLM methods is important to capture transient cortical events such as propagating waves.

Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1.

Neurons in the primary visual cortex are known for responding vigorously but with high variability to classical stimuli such as drifting bars or gratings. By contrast, natural scenes are encoded more efficiently by sparse and temporal precise spiking responses. We used a conductance-based model of the visual system in higher mammals to investigate how two specific features of the thalamo-cortical pathway, namely push-pull receptive field organization and fast synaptic depression, can contribute to this contextual reshaping of V1 responses. By comparing cortical dynamics evoked respectively by natural vs. artificial stimuli in a comprehensive parametric space analysis, we demonstrate that the reliability and sparseness of the spiking responses during natural vision is not a mere consequence of the increased bandwidth in the sensory input spectrum. Rather, it results from the combined impacts of fast synaptic depression and push-pull inhibition, the later acting for natural scenes as a form of "effective" feed-forward inhibition as demonstrated in other sensory systems. Thus, the combination of feedforward-like inhibition with fast thalamo-cortical synaptic depression by simple cells receiving a direct structured input from thalamus composes a generic computational mechanism for generating a sparse and reliable encoding of natural sensory events.

Shunting inhibition, a silent step in visual cortical computation.

Brain computation, in the early visual system, is often considered as a hierarchical process in which features extracted in a given sensory relay are not present in previous stages of integration. In particular, orientation preference and its fine tuning selectivity are functional properties shared by most cortical cells and they are not observed at the preceding geniculate stage. A classical problem is identifying the mechanisms and circuitry underlying these computations. Several organizational principles have been proposed, giving different weights to the feedforward thalamocortical drive or to intracortical recurrent architectures. Within this context, an important issue is whether intracortical inhibition is fundamental for the genesis of stimulus selectivity, or rather normalizes spike response tuning with respect to other features such as stimulus strength or contrast, without influencing the selectivity bias and preference expressed in the excitatory input alone. We review here experimental observations concerning the presence or absence of inhibitory input evoked by non-preferred orientation/directions. Intracellular current clamp and voltage clamp recordings are analyzed in the light of new methods allowing us (1) to increase the visibility of inhibitory input, and (2) to continuously measure the visually evoked dynamics of input conductances. We conclude that there exists a diversity of synaptic input combinations generating the same profile of spike-based orientation selectivity, and that this diversity most likely reflects anatomical non-homogeneities in input sampling provided by the local context of the columnar and lateral intracortical network in which the considered cortical cell is embedded.

Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons.

Synaptic noise is thought to be a limiting factor for computational efficiency in the brain. In visual cortex (V1), ongoing activity is present in vivo, and spiking responses to simple stimuli are highly unreliable across trials. Stimulus statistics used to plot receptive fields, however, are quite different from those experienced during natural visuomotor exploration. We recorded V1 neurons intracellularly in the anaesthetized and paralyzed cat and compared their spiking and synaptic responses to full field natural images animated by simulated eye-movements to those evoked by simpler (grating) or higher dimensionality statistics (dense noise). In most cells, natural scene animation was the only condition where high temporal precision (in the 10-20 ms range) was maintained during sparse and reliable activity. At the subthreshold level, irregular but highly reproducible membrane potential dynamics were observed, even during long (several 100 ms) "spike-less" periods. We showed that both the spatial structure of natural scenes and the temporal dynamics of eye-movements increase the signal-to-noise ratio by a non-linear amplification of the signal combined with a reduction of the subthreshold contextual noise. These data support the view that the sparsening and the time precision of the neural code in V1 may depend primarily on three factors: (1) broadband input spectrum: the bandwidth must be rich enough for recruiting optimally the diversity of spatial and time constants during recurrent processing; (2) tight temporal interplay of excitation and inhibition: conductance measurements demonstrate that natural scene statistics narrow selectively the duration of the spiking opportunity window during which the balance between excitation and inhibition changes transiently and reversibly; (3) signal energy in the lower frequency band: a minimal level of power is needed below 10 Hz to reach consistently the spiking threshold, a situation rarely reached with visual dense noise.

Adaptation of the simple or complex nature of V1 receptive fields to visual statistics.

Receptive fields in primary visual cortex (V1) are categorized as simple or complex, depending on their spatial selectivity to stimulus contrast polarity. We studied the dependence of this classification on visual context by comparing, in the same cell, the synaptic responses to three classical receptive field mapping protocols: sparse noise, ternary dense noise and flashed Gabor noise. Intracellular recordings revealed that the relative weights of simple-like and complex-like receptive field components were scaled so as to make the same receptive field more simple-like with dense noise stimulation and more complex-like with sparse or Gabor noise stimulations. However, once these context-dependent receptive fields were convolved with the corresponding stimulus, the balance between simple-like and complex-like contributions to the synaptic responses appeared to be invariant across input statistics. This normalization of the linear/nonlinear input ratio suggests a previously unknown form of homeostatic control of V1 functional properties, optimizing the network nonlinearities to the statistical structure of the visual input.

High-resolution intracellular recordings using a real-time computational model of the electrode.

Intracellular recordings of neuronal membrane potential are a central tool in neurophysiology. In many situations, especially in vivo, the traditional limitation of such recordings is the high electrode resistance and capacitance, which may cause significant measurement errors during current injection. We introduce a computer-aided technique, Active Electrode Compensation (AEC), based on a digital model of the electrode interfaced in real time with the electrophysiological setup. The characteristics of this model are first estimated using white noise current injection. The electrode and membrane contribution are digitally separated, and the recording is then made by online subtraction of the electrode contribution. Tests performed in vitro and in vivo demonstrate that AEC enables high-frequency recordings in demanding conditions, such as injection of conductance noise in dynamic-clamp mode, not feasible with a single high-resistance electrode until now. AEC should be particularly useful to characterize fast neuronal phenomena intracellularly in vivo.