Spatiotemporal reorganization of corticostriatal networks encodes motor skill learning.

Motor skill learning requires the activity of the dorsal striatum, with a differential global implication of the dorsomedial and dorsolateral territories. We investigate here whether and how specific striatal neurons encode the acquisition and consolidation of a motor skill. Using ex vivo two-photon calcium imaging after rotarod training, we report that highly active (HA) striatal populations arise from distinct spatiotemporal reorganization in the dorsomedial (DMS) and dorsolateral (DLS) striatum networks and are correlated with learning performance. The DMS overall activity decreases in early training, with few and sparsely distributed HA cells, while the DLS shows a progressive and long-lasting formation of HA cell clusters. These reorganizations result from reinforcement of synaptic connections to the DMS and anatomical rearrangements to the DLS. Targeted silencing of DMS or DLS HA cells with the cFos-TRAP strategy strongly impairs individual performance. Our data reveal that discrete domains of striatal populations encode acquisition and long-lasting retention of a motor skill.

Brain tissue classification from stereoelectroencephalographic recordings.

BACKGROUND: Stereoelectroencephalographic (SEEG) recordings can be performed before final resective surgery in some drug-resistant patients with focal epilepsies. For good SEEG signal interpretation, it is important to correctly identify the brain tissue in which each contact is inserted. Tissue classification is usually done with the coregistration of CT scan (with implanted SEEG electrodes) with preoperative MRI. NEW METHOD: Brain tissue classification is done here directly from SEEG signals obtained at rest by a linear discriminant analysis (LDA) classifier using measured SEEG signals. The classification operates on features extracted from Bode plots obtained via non-parametric frequency domain transfer functions of adjacent contacts pairs. Classification results have been compared with classification from T1 MRI following the labelling procedure described in Deman et al. (2018), together with minor corrections by visual inspection by specialists. RESULTS: With the data processed from 19 epileptic patients representing 1284 contact pairs, an accuracy of 72 ± 3% was obtained for homogeneous tissue separation. To our knowledge only one previous study conducted brain tissue classification using the power spectra of SEEG signals, and the distance between contacts on a shaft. The features proposed in our article performed better with the LDA classifier. However, the Bayesian classifier proposed in Greene et al. (2020) is more robust and could be used in a future study to enhance the classification performance. CONCLUSIONS AND SIGNIFICANCE: Our findings suggest that careful analysis of the transfer function between adjacent contacts measuring resting activity via frequency domain identification, could allow improved interpretation of SEEG data and or their co-registration with subject's anatomy.

Functional connectivity is preserved but reorganized across several anesthetic regimes.

Under anesthesia, systemic variables and CBF are modified. How does this alter the connectivity measures obtained with rs-fMRI? To tackle this question, we explored the effect of four different anesthetics on Long Evans and Wistar rats with multimodal recordings of rs-fMRI, systemic variables and CBF. After multimodal signal processing, we show that the blood-oxygen-level-dependent (BOLD) variations and functional connectivity (FC) evaluated at low frequencies (0.031-0.25 â€‹Hz) do not depend on systemic variables and are preserved across a large interval of baseline CBF values. Based on these findings, we found that most brain areas remain functionally active under any anesthetics, i.e. connected to at least one other brain area, as shown by the connectivity graphs. In addition, we quantified the influence of nodes by a measure of functional connectivity strength to show the specific areas targeted by anesthetics and compare correlation values of edges at different levels. These measures enable us to highlight the specific network alterations induced by anesthetics. Altogether, this suggests that changes in connectivity could be evaluated under anesthesia, routinely used in the control of neurological injury.

Classification of epileptic motor manifestations and detection of tonic-clonic seizures with acceleration norm entropy.

In this paper, three triaxis accelerometers positioned on the wrists and the head of epileptic patients submitted to long-term video electroencephalographic monitoring as part of presurgical investigation are evaluated to characterize the different classes of motor manifestations observed during seizures. Quadratic discriminant classifiers are trained on features extracted from 1 or 4 s windows. It is shown that a simple rule applied to the acceleration norm entropy HnA produces the best performances compared to other classifiers trained on other feature sets. The simple rule is as follows with values given in bits: (0 HnA 1.34), no movement; (1.34 HnA 3.87), tonic manifestations; (3.87 HnA), tonic-clonic manifestations. For this classifier, features are extracted from 1 s windows and the misclassification rate is 11% evaluated on 5,607 s of epileptic motor manifestations obtained from 58 seizures in 30 patients. A quantile normalization can improve the results with features based on absolute power spectral density but performances are not as good as the ones obtained with HnA. Based on the classifier using only HnA, a simple tonic-clonic seizure detector is proposed and produces a 80% sensitivity with a 95% specificity.

Morphometry and localization of the temporal transverse Heschl's gyrus in magnetic resonance imaging: a guide for cortical stimulation of chronic tinnitus.

PURPOSE: Subjective tinnitus is considered a phantom auditory phenomenon. Recent studies show that electrical or magnetic stimulation of the cortex can alleviate some tinnitus. The usual target of the stimulation is the primary auditory cortex (PAC) on Heschl's gyrus (HG). The objective of this study was to specify the anatomy of HG by magnetic resonance imaging (MRI). METHODS: Cerebral MRI of 60 patients with chronic tinnitus, carried out before neuronavigated repetitive transcranial magnetic stimulation targeting the auditory cortex, were included. 3D-T1 MRI was reformatted in Talairach-Tournoux's stereotactic space, then the following steps were performed: morphometry of HG, localization of the probabilistic center of the PAC (pcPAC) chosen at the junction between the medial third and the lateral two-thirds of HG, relative to external and cortical landmarks, and identification of its coordinates relative to the bicommissural line (AC-PC). RESULTS: In relation to external landmarks, the pcPAC was identified around 5 cm above the root of the helix of the ear in the direction of a point on the vertex located 4 cm behind the coronal suture, for both sides. In Talairach-Tournoux's stereotactic space with the anterior commissure as the origin, the pcPAC coordinates were x = 43, y = -20, z = 6.8 on the right side, and x = -42.5, y = -21.5, and z = 6.5 on the left. Probabilistic maps of the presence of HG pointed to a relative contraction of data in space, despite inter- and intraindividual differences. CONCLUSION: The choice of our stimulation target was established in the middle of the theoretical position of the PAC. MRI allows a reliable identification of the target structure.

Definition of a stereotactic 3-dimensional magnetic resonance imaging template of the human insula.

BACKGROUND: This study proposes a 3-dimensional (3-D) template of the insula in the bicommissural reference system with posterior commissure (PC) as the center of coordinates. OBJECTIVE: Using the bicommissural anterior commissure (AC)-PC reference system, this study aimed to define a template and design a method for the 3-D reconstruction of the human insula that may be used at an individual level during stereotactic surgery. METHODS: Magnetic resonance imaging (MRI)-based morphometric analysis was performed on 100 cerebral cortices with normal insulae based on a 3-step procedure: Step 1: AC-PC reference system-based reconstruction of the insula from the 1-mm thick 3-D T1-weighted MRI slices. Step 2: Digitalization and superposition of the data obtained in the 3 spatial planes. Step 3: Representation of pixels as colors on a scale corresponding to the probability of localization of each insular anatomic component. RESULTS: The morphometric analysis of the insula confirmed our previously reported findings of a more complex shape delimited by 4 peri-insular sulci. A very significant correlation between the coordinates of the main insular structures and the length of AC-PC was demonstrated. This close correlation allowed us to develop a method that allows the 3-D reconstruction of the insula from MRI slices and only requires the localization of AC and PC. This process defines an area deemed to contain insula with 100% probability. CONCLUSION: This 3-D reconstruction of the insula should be useful to improve its localization and other cortical areas and allow the differentiation of insular cortex from opercular cortex.

Classification of epileptic motor manifestations using inertial and magnetic sensors.

In order to characterize objectively the succession of movements observed during motor seizures, inertial and magnetic sensors were placed on epileptic patients. Video recordings synchronized with motion recordings were analyzed visually during seizures and divided, for each limb, into events corresponding to different classes of motor manifestations. For each classified event, features were extracted and a subset selection was automated using artificial neural networks. The best artificial neural network was simulated on whole recordings to generate a stereotypic evolution of motor manifestations that we called motorograms. It is shown that motorograms can point out seizure movements and emphasize epileptic patterns.

MRI-based definition of a stereotactic two-dimensional template of the human insula.

OBJECTIVE: This study aimed to create a stereotactic two-dimensional description of the human insula based on accurate radiological morphometric studies. METHODS: Seventy-five normal cerebral MRIs were selected and drawings of the insula then obtained from serial sagittal slices. These drawings were digitalized before superimposing the anterior (AC) and posterior (PC) commissures as references. This allowed us to quantify interindividual anatomical variations in a large cohort of subjects. RESULTS: The morphometric analysis of the insula revealed a more complex shape than previously described. This structure is delimited by four peri-insular sulci (anterior, superior, posterior and inferior) instead of the three sulci classically mentioned. Males have a statistically larger surface area than females, according to a correlated index. Precise measurements of the different insular components allowed us to quantify their potential interindividual anatomical variations and to define their average shapes and stereotactic locations. CONCLUSION: These data create a two-dimensional template of the human insula, with regard to the classical AC-PC stereotactic reference system. They furthermore allow us to quantify the probability that a given element of this structure is located at a predefined position. This should be useful in functional neuroimaging studies and in insular surgery for diagnostic and therapeutic goals.

Collection and exploratory analysis of attitude sensor data in an epilepsy monitoring unit.

The aim of this paper is to present the collection of attitude sensor data from an epilepsy monitoring unit and the results of standard exploration using principal component analysis. The collection of data from attitude sensors positioned on three limbs of epileptic patients at their bedside is described. The analysis of the data focuses, on one hand, on motor features extraction from attitude sensor data and on the other hand, on visual segmentation of seizures into events corresponding to motor manifestations classes by an expert. Principal component analysis is then realized over these features and groups of data are localized according to the expert classification. This exploration indicates a possible discrimination between these motor manifestation classes.

On-line segmentation algorithm for continuously monitored data in intensive care units.

An on-line segmentation algorithm is presented in this paper. It is developed to preprocess data describing the patient's state, sampled at high frequencies in intensive care units, with a further purpose of alarm filtering. The algorithm splits the signal monitored into line segments--continuous or discontinuous--of various lengths and determines on-line when a new segment must be calculated. The delay of detection of a new line segment depends on the importance of the change: the more important the change, the quicker the detection. The linear segments are a correct approximation of the structure of the signal. They emphasise steady-states, level changes and trends occurring on the data. The information returned by the algorithm, which is the time at which the segment begins, its ordinate and its slope, is sufficient to completely reconstruct the filtered signal. This makes the algorithm an interesting tool to provide a processed time history record of the monitored variable. It can also be used to extract on-line information on the signal, such as its trend, in the short or long term.

Evaluation of a device scoring classes of hemorrhagic shock.

In order to evaluate the feasibility of a device scoring classes of hemorrhagic shock, a multivariate analysis of physiological data collected on swine enduring continuous blood loss was conducted. Raw data sampled at up to 500 Hz were first preprocessed and used for features extraction over period of 1 mm. An expert scored all these physiological features, into one of the four classes of hemorrhagic shock: none, compensated, uncompensated and irreversible. A supervised learning of various classifiers was then evaluated over these data. The percentage of misclassification obtained when using a realistic way of estimating error (a leave one -animal- out validation) is about 20% when mean arterial pressure is used, and about 40% when only non invasive features are used. The results are about the same whatever the classifiers used. This evaluation is discussed and a visualization is proposed in order to assess the temporal supervision given by the classifiers.

Do we need a systematic activation of alarm soundings for blood pressure monitoring for the safety of ICU patients?

PURPOSE: Evaluation of a protocol of activation-deactivation of alarm soundings on noninvasive mean arterial pressure (MAP) monitoring. MATERIALS AND METHODS: 103 patients were analyzed. Alarm soundings on noninvasive MAP were either activated (group A) or inactivated (group NA) according to a protocol based on patient's hemodynamic status. RESULTS: In the first part of the study (11 periods of 24 hours), we informed the nursing staff before data collection. In the second part of the study (11 periods of 24 hours), we did not inform the nursing staff before data collection. Results of the two parts were assembled and the final analysis consisted of 3,304 hours of monitoring with 12,839 noninvasive MAP measurements, 6,354 in group A and 6,485 in group NA. In group A, 75 of 944 (8%) of abnormal measurements were detected or managed with a delay > 15 minutes and among them 16 required a therapeutic adjustment. In group NA, 140 of 265 (53%) of abnormal measurements were detected or managed with a delay > 15 minutes and among them, only one required a therapeutic adjustment. The number of alarm soundings avoided in group NA was 286. CONCLUSION: In this study, a systematic activation of alarm soundings for non-invasive blood pressure monitoring seemed unnecessary for the safety of ICU patients.