Claudia Cecchetto

CMOS-compatible purely capacitive interfaces for high-density in-vivo recording from neural tissue

CMOS-based neural tissue in-vivo recording chips with a purely capacitive interface are presented with 256 sites resp. 256 recording channels. A 3D post-CMOS ALD-based process allows to provide a highly efficient sensor dielectric and to realize a protective insulation layer for the non-active part of the fabricated devices. A simple interconnect-efficient sensor array topology is used. Electrical characterizations and in-vivo measurements with biological content reveal proper operation of the presented approach.

An Automated Method for Characterization of Evoked Single-Trial Local Field Potentials Recorded from Rat Barrel Cortex Under Mechanical Whisker Stimulation

Rodents explore their surroundings through whisking by localizing objects and detecting textures very precisely. During such tactile exploration, whisker deflection is first mechanically transduced by receptors and then information encoded throughout the somatosensory pathway ending in the somatosensory ‘barrel’ cortex. In the barrel cortex, tactile information from a single whisker is segregated and processed in a cortical column corresponding to the deflected whisker. Local Field Potentials (LFPs) generated by whisker deflection in the barrel cortex present typical signatures in terms of shape and amplitude that are related to the activation of the local neuronal populations. Therefore, rigorous analysis of such responses may reveal important features about the function of underlying neuronal microcircuits. In this context, software methods for characterizing single-trial LFPs are needed that are also suitable for online extraction of LFP features and for brain–machine interfacing applications. In this work, we present an automated and efficient method to analyze evoked LFP responses in the rat barrel cortex through automatic removal of stimulation artifacts, detection of single events and characterization of their relevant parameters. Evoked single-trial LFPs recorded under two different anesthetics are examined to demonstrate the feasibility, accuracy and applicability of the method.

Anesthesia effect on single local field potentials variability in rat barrel cortex: Preliminary results.

The rat barrel cortex is a widely used model of information processing in the somatosensory area, thanks to its precise and easily recognizable organization. However, evoked Local Field Potentials (LFPs) generated in the barrel cortex by repetitive deflections of rat whiskers show large variability in shapes and timings. Moreover, anesthetics can deeply affect the profile of evoked responses. This paper presents preliminary report on the variability and the effect of commonly used anesthetics on these signals. We studied representative signal shape characteristics (e.g., latency and amplitude of events) extracted from evoked responses acquired by means of standard Ag/AgCl electrodes from different cortical layers. As an early result, 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 the peak latencies 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 processing of neural information and the encoding of sensory input along the cortical pathway.

A software-based platform for multichannel electrophysiological data acquisition

Recent improvements in microelectrodes technology have enabled neuroscientists to record electrophysiological signals from hundreds of neurons and simultaneously from a large number of channels. However, several environmental factors may introduce noise and artefacts and affect proper interpretation of recordings. Thus, the development of appropriate signal acquisition and processing platforms dealing with large data sets and in real-time represents a current fundamental challenge. In the present work, we present an easily-expandable Lab VIEW based software for handling data in real-time during a multichannel neurophysiological signal acquisition. The software was designed to exploit modern MultiCore CPUs for large scale data processing and, by freely setting key acquisition parameters, to work with virtually any kind of biological signal. The software allows for data storage in MATLAB format to facilitate off-line signal processing. Examples of local field potential signal acquisitions from the mouse hippocampus are reported to illustrate software features.

Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation

BackgroundLocal field potentials (LFPs) evoked by sensory stimulation are particularly useful in electrophysiological research. For instance, spike timing and current transmembrane current flow estimated from LFPs recorded in the barrel cortex in rats and mice are exploited to investigate how the brain represents sensory stimuli. Recent improvements in microelectrodes technology enable neuroscientists to acquire a great amount of LFPs during the same experimental session, calling for algorithms for their quantitative automatic analysis. Several computer tools were proposed for LFP analysis, but many of them incorporate algorithms that are not open to inspection or modification/personalization. We present a MATLAB software to automatically detect some important LFP features (latency, amplitude, time-derivative value in the inflection-point) for a quantitative analysis. The software features can be customized by the user according to his/her personal research needs. The incorporated algorithm is based on Phillips-Tikhonov regularization to deal with noise amplification due to ill-conditioning. In particular, its accuracy in the estimation of the features of interest is assessed in a Monte Carlo simulation mimicking the acquisition of LFPs in different SNR (signal-to-noise-ratio) conditions. Then, the algorithm is tested by analyzing a real set of 2500 LFPs recorded in rat after whisker stimulation at different depths in the primary somatosensory (S1) cortex, i.e., the region involved in the cortical representation of touch in mammals.ResultsAutomatic identification of LFP features by the presented software is easy and fast. As far as accuracy is concerned, error indices from simulated data suggest that the algorithm provides reliable estimates . Indeed, results obtained from LFPs recorded in rat after whisker stimulation are in line with the known sequential activation of the microcircuits of the S1 cortex.ConclusionA MATLAB software implementing an algorithm to automatically detect the main LFPs features was presented. Simulated and real case studies showed that the employed algorithm is accurate and robust against measurement noise. The available code can be used as it is, but the reported description of the algorithms allows users to easily modify the code to cope with specific requirements.

Reference Values for a Panel of Cytokinergic and Regulatory Lymphocyte Subpopulations

Lymphocyte subpopulations producing cytokines and exerting regulatory functions represent key immune elements. Given their reciprocal interdependency lymphocyte subpopulations are usually assayed as diagnostic panels, rather than single biomarkers for specialist clinical use. This retrospective analysis on lymphocyte subpopulations, analyzed over the last few years in an outpatient laboratory in Northeast Italy, contributes to the establishment of reference values for several regulatory lymphocytes currently lacking such reference ranges for the general population. Mean values and ranges in a sample of Caucasian patients (mean age 42±8,5 years), were provided for Th1, Th2, Th17, Th-reg, Tc-reg, Tc-CD57+ and B1 lymphocytes. The results are consistent with what is found in literature for the single subtypes and are: Th1 157.8±60.3/µl (7.3%±2.9); Th2 118.2±52.2/µl (5.4%±2.5); Th17 221.6±90.2/µl (10.5%±4.4); Th-reg 15.1±10.2/µl (0.7%±0.4); Tc-reg 5.8±4.7/µl (0.3%±0.2); Tc-CD57+ 103.7±114.1/µl (4.6%±4.7); B1 33.7±22.8/µl (1.5%±0.9); (Values are mean±SD). The results show that despite their variability, mean values are rather consistent in all age or sex groups and can be used as laboratory internal reference for this regulatory panel. Adding regulatory cells to lymphocyte subpopulations panels allows a more complete view of the state of the subjects immune network balance, thus improving the personalization and the “actionability” of diagnostic data in a systems medicine perspective.

Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex

Local field potentials (LFPs) recorded in the barrel cortex in rats and mice are important to investigate somatosensory systems, the final aim being to start to understand mechanisms of brain representation of sensory stimuli in humans. Parameters extracted from LFP of particular interest include spike timing and transmembrane current flow. Recent improvements in microelectrodes technology have enabled neuroscientists to acquire a great amount of LFP signals during the same experimental session, calling for the development of algorithms for their quantitative automatic analysis. In the present work, an algorithm based on Phillips-Tikhonov regularization is presented to automatically detect the main features (in terms of amplitude and latency) of LFP waveforms recorded after whisker stimulation in rat. The accuracy of the algorithm is first assessed in a Monte Carlo simulation mimicking the acquisition of LFP in three different conditions of SNR. Then, the algorithm is tested by analyzing a set of 100 LFP recorded in the primary somatosensory (S1) cortex, i.e., the region involved in the cortical representation of touch in mammals.