Neuronal Population Encoding of Sensory Information in the Rat Barrel Cortex: Local Field Potential Recording and Characterization by an Innovative High-Resolution Brain-Chip Interface

Neuronal networks are at the base of information processing in the brain. They are series of interconnected neurons whose activation defines a recognizable linear pathway. The main goal of studying neural ensembles is to characterize the relationship between the stimulus and the individual or general neuronal responses and the relation amongst the electrical activities of neurons within the network, also understanding how topology and connectivity relates to their function. Many techniques have been developed to study these complex systems: single-cell approaches aim to investigate single neurons and their connections with a limited number of other nerve cells; on the opposite side, low-resolution large-scale approaches, such as functional MRI (Magnetic Resonance Imaging) or electroencephalography (EEG), record signal changes in the brain that are generated by large populations of cells. More recently, multisite recording techniques have been developed to overcome the limitations of previous approaches, allowing to record simultaneously from huge neuronal ensembles with high spatial resolution and in different brain regions, i.e. by using implantable semiconductor chips. Local Field Potentials (LFPs), the part of electrophysiological signals that has frequencies below 500 Hz, capture key integrative synaptic processes that cannot be measured by analyzing the spiking activity of few neurons alone. Several studies have used LFPs to investigate cortical network mechanisms involved in sensory processing, motor planning and higher cognitive processes, like memory and perception. LFPs are also promising signals for steering neuroprosthetic devices and for monitoring neural activity even in human beings, since they are more easily and stably recorded in chronic settings than neuronal spikes. In this work, LFP profiles recorded in the rat barrel cortex through high-resolution CMOS-based needle chips are presented and compared to those obtained by means of conventional Ag/AgCl electrodes inserted into glass micropipettes, which are widely used tools in electrophysiology. The rat barrel cortex is a well-known example of topographic mapping where each of the whiskers on the snout of the animal is mapped onto a specific cortical area, called a barrel. The barrel cortex contains the somatosensory representation of the whiskers and forms an early stage of cortical processing for tactile information, along with the trigeminal ganglion and the thalamus. It is an area of great importance for understanding how the cerebral cortex works, since the cortical columns that form the basic building blocks of the neocortex can be actually seen within the barrel. Moreover, the barrel cortex has served as a test-bed system for several new methodologies, partly because of its unique and instantly identifiable form, and partly because the species that have barrels, i.e. rodents, are the most commonly used laboratory mammal. The barrel cortex, the whiskers that activate it and the intervening neural pathways have been increasingly the subject of focus by a growing number of research groups for quite some time. Nowadays, studies (such this one) are directed not only at understanding the barrel cortex itself but also at investigating issues in related fields using the barrel cortex as a base model. In this study, LFP responses were evoked in the target barrel by repeatedly deflecting the corresponding whisker in a controlled fashion, by means of a specifically designed closed-loop piezoelectric bending system triggered by a custom LabView acquisition software. Evoked LFPs generated in the barrel cortex by many consecutive whiskers' stimulations show large variability in shapes and timings. Moreover, anesthetics can deeply affect the profile of evoked responses. This work presents preliminary results on the variability and the effect of commonly used anesthetics on these signals, by comparing the distributions of evoked responses recorded from rats anesthetized with tiletamine-xylazine, which mainly blocks the excitatory NMDA receptors, and urethane, which conversely affects both the excitatory and inhibitory system, in a complex and balanced way yet preserving the synaptic plasticity. Representative signal shape characteristics (e.g., latencies and amplitude of events) extracted from evoked responses acquired from different cortical layers are analyzed and discussed. Statistical distributions of these parameters are estimated for all the different depths, in order to assess the variability of LFPs generated by individual mechanical stimulations of single whiskers along the entire cortical column. Preliminary results showed a great variability in cortical responses, which varied both in latency and amplitude across layers. We found significant difference in the latency of the first principal peak of the responses: under tiletamine-xylazine anesthetic, the responses or events of the evoked LFPs occurred later than the ones recorded while urethane was administered. Furthermore, the distributions of this parameter in all cortical layers were narrower in case of urethane. This behavior should be attributed to the different effects of these two anesthetics on specific synaptic receptors and thus on the encoding and processing of the sensory input information along the cortical pathway. The role of the ongoing basal activity on the modulation of the evoked response was also investigated. To this aim, spontaneous activity was recorded in different cortical layers of the rat barrel cortex under the two types of anesthesia and analyzed in the statistical context of neuronal avalanches. A neuronal avalanche is a cascade of bursts of activity in neural networks, whose size distribution can be approximated by a power law. The event size distribution of neuronal avalanches in cortical networks has been reported to follow a power law of the type P(s)= s^-a, with exponent a close to 1.5, which represent a reflection of long-range spatial correlations in spontaneous neuronal activity. Since negative LFP peaks (nLFPs) originates from the sum of synchronized Action Potentials (AP) from neurons within the vicinity of the recording electrode, we wondered if it were possible to model single nLFPs recorded in the basal activity traces by means of only one electrode as the result of local neuronal avalanches, and thus we analyzed the size (i.e. the amplitude in uV) distribution of these peaks so as to identify a suitable power-law distribution that could describe also these single-electrode records. Finally, the results of the first ever measurements of evoked LFPs within an entire column of the barrel cortex obtained by means of the latest generation of CMOS-based implantable needles, having 256 recording sites arranged into two different array topologies (i.e. 16 x 16 or 4 x 64, pitches in the x- and y-direction of 15 um and 33 um respectively), are presented and discussed. A propagation dynamics of the LFP can be already recognized in these first cortical profiles. In the next future, the use of these semiconductor devices will help, among other things, to understand how degenerating syndromes like Parkinson or Alzheimer evolve, by coupling detected behaviors and symptoms of the disease to neuronal features. Implantable chips could then be used as 'electroceuticals', a newly coined term that describes one of the most promising branch of bioelectronic medicine: they could help in reverting the course of neurodegenerative diseases, by constituting the basis of neural prostheses that physically supports or even functionally trains impaired neuronal ensembles. High-resolution extraction and identification of neural signals will also help to develop complex brain-machine interfaces, which can allow intelligent prostheses to be finely controlled by their wearers and to provide sophisticated feedbacks to those who have lost part of their body or brain functions