Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations

High resolution, wide field optical imaging of macaque visual cortex with a curved detector

Objective. Cortical activity can be recorded using a variety of tools, ranging in scale from the single neuron (microscopic) to the whole brain (macroscopic). There is usually a trade-off between scale and resolution; optical imaging techniques, with their high spatio-temporal resolution and wide field of view, are best suited to study brain activity at the mesoscale. Optical imaging of cortical areas is however in practice limited by the curvature of the brain, which causes the image quality to deteriorate significantly away from the center of the image.Approach. To address this issue and harness the full potential of optical cortical imaging techniques, we developed a new wide-field optical imaging system adapted to the macaque brain. Our system is composed of a curved detector, an aspherical lens and a ring composed of light emitting diodes providing uniform illumination at wavelengths relevant for the different optical imaging methods, including intrinsic and fluorescence imaging.Main results. The system was characterized and compared with the standard macroscope used for cortical imaging, and a three-fold increase of the area in focus was measured as well as a four-fold increase in the evenness of the optical qualityin vivo.Significance. This new instrument, which is to the best of our knowledge the first use of a curved detector for cortical imaging, should facilitate the observation of wide mesoscale phenomena such as dynamic propagating waves within and between cortical maps, which are otherwise difficult to observe due to technical limitations of the currently available recording tools.

Neural field model to reconcile structure with function in primary visual cortex

Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.

Catching the voltage gradient-asymmetric boost of cortical spread generates motion signals across visual cortex: a brief review with special thanks to Amiram Grinvald

Wide-field voltage imaging is unique in its capability to capture snapshots of activity-across the full gradient of average changes in membrane potentials from subthreshold to suprathreshold levels-of hundreds of thousands of superficial cortical neurons that are simultaneously active. Here, I highlight two examples where voltage-sensitive dye imaging (VSDI) was exploited to track gradual space-time changes of activity within milliseconds across several millimeters of cortex at submillimeter resolution: the line-motion condition, measured in Amiram Grinvald's Laboratory more than 10 years ago and-coming full circle running VSDI in my laboratory-another motion-inducing condition, in which two neighboring stimuli counterchange luminance simultaneously. In both examples, cortical spread is asymmetrically boosted, creating suprathreshold activity drawn out over primary visual cortex. These rapidly propagating waves may integrate brain signals that encode motion independent of direction-selective circuits.

Improving voltage-sensitive dye imaging: with a little help from computational approaches

Voltage-sensitive dye imaging (VSDI) is a key neurophysiological recording tool because it reaches brain scales that remain inaccessible to other techniques. The development of this technique from in vitro to the behaving nonhuman primate has only been made possible thanks to the long-lasting, visionary work of Amiram Grinvald. This work has opened new scientific perspectives to the great benefit to the neuroscience community. However, this unprecedented technique remains largely under-utilized, and many future possibilities await for VSDI to reveal new functional operations. One reason why this tool has not been used extensively is the inherent complexity of the signal. For instance, the signal reflects mainly the subthreshold neuronal population response and is not linked to spiking activity in a straightforward manner. Second, VSDI gives access to intracortical recurrent dynamics that are intrinsically complex and therefore nontrivial to process. Computational approaches are thus necessary to promote our understanding and optimal use of this powerful technique. Here, we review such approaches, from computational models to dissect the mechanisms and origin of the recorded signal, to advanced signal processing methods to unravel new neuronal interactions at mesoscopic scale. Only a stronger development of interdisciplinary approaches can bridge micro- to macroscales.

Breaking the Excitation-Inhibition Balance Makes the Cortical Network's Space-Time Dynamics Distinguish Simple Visual Scenes

Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes.

Probing the functional impact of sub-retinal prosthesis

Retinal prostheses are promising tools for recovering visual functions in blind patients but, unfortunately, with still poor gains in visual acuity. Improving their resolution is thus a key challenge that warrants understanding its origin through appropriate animal models. Here, we provide a systematic comparison between visual and prosthetic activations of the rat primary visual cortex (V1). We established a precise V1 mapping as a functional benchmark to demonstrate that sub-retinal implants activate V1 at the appropriate position, scalable to a wide range of visual luminance, but with an aspect-ratio and an extent much larger than expected. Such distorted activation profile can be accounted for by the existence of two sources of diffusion, passive diffusion and activation of ganglion cells’ axons en passant. Reverse-engineered electrical pulses based on impedance spectroscopy is the only solution we tested that decreases the extent and aspect-ratio, providing a promising solution for clinical applications.

DOI:http://dx.doi.org/10.7554/eLife.12687.001

One of the most common causes of blindness is a disorder called retinitis pigmentosa. In a healthy eye, the surface at the back of the eye – called the retina – contains cells called photoreceptors that detect light and convert it into electrical signals for the brain to process. In people with retinitis pigmentosa, these photoreceptor cells die off gradually, which leads to loss of vision.

The only treatment available for retinitis pigmentosa is to have an artificial retina implanted into the eye. The artificial retina consists of an array of tiny electrodes, which take over from the damaged photoreceptors and generate electrical signals. The person with the implant perceives these electrical signals as bright flashes called “phosphenes”. However, the phosphenes are too large and imprecise to provide the person with vision that is good enough for tasks such as walking unaided or reading.

To find out why artificial retinas produce such poor resolution, Roux et al. compared how a rat’s brain responds to either natural visual stimuli or activation of implanted an array of micro-electrodes. Both the micro-electrodes and the natural stimuli activated the same areas of the brain. However, the micro-electrodes produced larger and more elongated patterns of activation. This is because the electrical currents generated by the micro-electrodes diffused throughout the retinal tissue and activated other neurons besides those intended. To overcome this problem, Roux et al. tested different ways of stimulating the micro-electrodes in order to identify those that induce the desired patterns of brain activity. This approach – known as reverse engineering – did indeed improve the performance of the micro-electrode array.

The next step is to extend these findings, which were obtained in healthy rats, to non-human primates or animal models of retinitis pigmentosa to better understand the condition in humans. In addition, combining the current approach with other existing techniques should further improve the vision that can be achieved with artificial retinas.

DOI:http://dx.doi.org/10.7554/eLife.12687.002