IntrAnat Electrodes: A Free Database and Visualization Software for Intracranial Electroencephalographic Data Processed for Case and Group Studies.

In some cases of pharmaco-resistant and focal epilepsies, intracranial recordings performed epidurally (electrocorticography, ECoG) and/or in depth (stereoelectroencephalography, SEEG) can be required to locate the seizure onset zone and the eloquent cortex before surgical resection. In SEEG, each electrode contact records brain's electrical activity in a spherical volume of 3 mm diameter approximately. The spatial coverage is around 1% of the brain and differs between patients because the implantation of electrodes is tailored for each case. Group studies thus need a large number of patients to reach a large spatial sampling, which can be achieved more easily using a multicentric approach such as implemented in our F-TRACT project (f-tract.eu). To facilitate group studies, we developed a software-IntrAnat Electrodes-that allows to perform virtual electrode implantation in patients' neuroanatomy and to overlay results of epileptic and functional mapping, as well as resection masks from the surgery. IntrAnat Electrodes is based on a patient database providing multiple search criteria to highlight various group features. For each patient, the anatomical processing is based on a series of software publicly available. Imaging modalities (Positron Emission Tomography (PET), anatomical MRI pre-implantation, post-implantation and post-resection, functional MRI, diffusion MRI, Computed Tomography (CT) with electrodes) are coregistered. The 3D T1 pre-implantation MRI gray/white matter is segmented and spatially normalized to obtain a series of cortical parcels using different neuroanatomical atlases. On post-implantation images, the user can position 3D models of electrodes defined by their geometry. Each electrode contact is then labeled according to its position in the anatomical atlases, to the class of tissue (gray or white matter, cerebro-spinal fluid) and to its presence inside or outside the resection mask. Users can add more functionally informed labels on contact, such as clinical responses after electrical stimulation, cortico-cortical evoked potentials, gamma band activity during cognitive tasks or epileptogenicity. IntrAnat Electrodes software thus provides a means to visualize multimodal data. The contact labels allow to search for patients in the database according to multiple criteria representing almost all available data, which is to our knowledge unique in current SEEG software. IntrAnat Electrodes will be available in the forthcoming release of BrainVisa software and tutorials can be found on the F-TRACT webpage.

Response inhibition rapidly increases single-neuron responses in the subthalamic nucleus of patients with Parkinson's disease.

The subthalamic nucleus (STN) plays a critical role during action inhibition, perhaps by acting like a fast brake on the motor system when inappropriate responses have to be rapidly suppressed. However, the mechanisms involving the STN during motor inhibition are still unclear, particularly because of a relative lack of single-cell responses reported in this structure in humans. In this study, we used extracellular microelectrode recordings during deep brain stimulation surgery in patients with Parkinson's disease (PD) to study STN neurophysiological correlates of inhibitory control during a stop signal task. We found two neuronal subpopulations responding either during motor execution (GO units) or during motor inhibition (STOP units). GO units fired selectively before patients' motor responses whereas STOP units fired selectively when patients successfully withheld their move at a latency preceding the duration of the inhibition process. These results provide electrophysiological evidence for the hypothesized role of the STN in current models of response inhibition.

Anatomy-preserving nonlinear registration of deep brain ROIs using confidence-based block-matching.

Brain atlases are commonly used in a number of applications such as MRI segmentation and surgery targetting. Our goal is to register a basal ganglia atlas to a subject using MR image registration. Existing registration methods are for the most part either too constrained (linear registration) or can deform deep brain ROIs into implausible anatomical shapes. We developed a block-matching registration method suitable for atlas registration, using a new confidence-based regularization of the vector field. The method was used to register a set of 17 manually segmented MRI onto one subject. Results show that basal ganglia structures were better registered than when using an affine registration method.