Denis Brunet

Topographic ERP Analyses: A Step-by-Step Tutorial Review

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

Spatiotemporal analysis of multichannel EEG: CARTOOL

This paper describes methods to analyze the brains electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.

Rapid discrimination of visual and multisensory memories revealed by electrical neuroimaging.

Though commonly held that multisensory experiences enrich our memories and that memories influence ongoing sensory processes, their neural mechanisms remain unresolved. Here, electrical neuroimaging shows that auditory-visual multisensory experiences alter subsequent processing of unisensory visual stimuli during the same block of trials at early stages poststimulus onset and within visual object recognition areas. We show this with a stepwise analysis of scalp-recorded event-related potentials (ERPs) that statistically tested (1) ERP morphology and amplitude, (2) global electric field power, (3) topographic stability of and changes in the electric field configuration, and (4) intracranial distributed linear source estimations. Subjects performed a continuous recognition task, discriminating repeated vs. initial image presentations. Corresponding, but task-irrelevant, sounds accompanied half of the initial presentations during a given block of trials. On repeated presentations within a block of trials, only images appeared, yielding two situations-the images prior presentation was only visual or with a sound. Image repetitions that had been accompanied by sounds yielded improved memory performance accuracy (old or new discrimination) and were differentiated as early as approximately 60-136 ms from images that had not been accompanied by sounds through generator changes in areas of the right lateral-occipital complex (LOC). It thus appears that unisensory percepts trigger multisensory representations associated with them. The collective data support the hypothesis that perceptual or memory traces for multisensory auditory-visual events involve a distinct cortical network that is rapidly activated by subsequent repetition of just the unisensory visual component.

Head model and electrical source imaging: A study of 38 epileptic patients

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from scalp EEG. When applied to interictal epileptiform discharges (IEDs), this technique is of great use for identifying the irritative zone in focal epilepsies. Inaccuracies in the modeling of electro-magnetic field propagation in the head (forward model) may strongly influence ESI and lead to mislocalization of IED generators. However, a systematic study on the influence of the selected head model on the localization precision of IED in a large number of patients with known focus localization has not yet been performed. We here present such a performance evaluation of different head models in a dataset of 38 epileptic patients who have undergone high-density scalp EEG, intracranial EEG and, for the majority, subsequent surgery. We compared ESI accuracy resulting from three head models: a Locally Spherical Model with Anatomical Constraints (LSMAC), a Boundary Element Model (BEM) and a Finite Element Model (FEM). All of them were computed from the individual MRI of the patient and ESI was performed on averaged IED. We found that all head models provided very similar source locations. In patients having a positive post-operative outcome, at least 74% of the source maxima were within the resection. The median distance from the source maximum to the nearest intracranial electrode showing IED was 13.2, 15.6 and 15.6 mm for LSMAC, BEM and FEM, respectively. The study demonstrates that in clinical applications, the use of highly sophisticated and difficult to implement head models is not a crucial factor for an accurate ESI.

Antiepileptic drugs modify power of high EEG frequencies and their neural generators

Background:  The clinical and molecular effects of antiepileptic drugs (AEDs) have been extensively investigated. Much less is known about their effects on human electrophysiology.

Parieto-Frontal Circuits During Observation of Hidden and Visible Motor Acts in Children. A High-density EEG Source Imaging Study

Several studies showed that in the human brain specific premotor and parietal areas are activated during the execution and observation of motor acts. The activation of this premotor-parietal network displaying the so-called Mirror Mechanism (MM) was proposed to underpin basic forms of action understanding. However, the functional properties of the MM in children are still largely unknown. In order to address this issue, we recorded high-density EEG from 12 children (6 female, 6 male; average age 10.5, SD ±2.15). Data were collected when children observed video clips showing hands grasping objects in two different experimental conditions: (1) Full Vision, in which the motor act was fully visible; (2) Hidden, in which the interaction between the hand and the object was not visible. Event-related potentials (ERPs) and topographic map analyses were used to investigate the temporal pattern of the ERPs and their brain source of localization, employing a children template of the Montreal Neurological Institute. Results showed that two different parieto-premotor circuits are activated by the observation of object-related hand reaching-to-grasping motor acts in children. The first circuit comprises the ventral premotor and the inferior parietal cortices. The second one comprises the dorsal premotor and superior parietal cortices. The activation of both circuits is differently lateralized and modulated in time, and influenced by the amount of visual information available about the hand grasping-related portion of the observed motor acts.

Computer vision and agricultural robotics for disease control: the Potato Operation

The Potato Operation is a project belonging to the domain of agricultural robotics. It aims to automate pulp sampling of potatoes in order to detect viral diseases. The results of the analysis of these samples are used for the certification of potatoes marked out as seed. The difficulty of this problem lies in the high variability of natural objects, such as their shape, colour or texture. This paper presents two computer vision approaches that have been implemented and tested, as well as the robotic apparatus required for the complete installation. The first computer vision approach, the so-called 3-D image analysis, is based on a combination of classical image analysis methods with active vision. The second approach, the so-called thermography, combines analysis of thermal images of potatoes with active vision. Other methods are also briefly described, which could lead to possible improvements of the results; they rely on alternative lighting schemes, such as fluorometry or the use of multiple sources. Finally, results of the different methods are presented and the long-term goals of the project are discussed.

Whole-scalp EEG mapping of somatosensory evoked potentials in macaque monkeys

High-density scalp EEG recordings are widely used to study whole-brain neuronal networks in humans non-invasively. Here, we validate EEG mapping of somatosensory evoked potentials (SSEPs) in macaque monkeys (Macaca fascicularis) for the long-term investigation of large-scale neuronal networks and their reorganisation after lesions requiring a craniotomy. SSEPs were acquired from 33 scalp electrodes in five adult anaesthetized animals after electrical median or tibial nerve stimulation. SSEP scalp potential maps were identified by cluster analysis and identified in individual recordings. A distributed, linear inverse solution was used to estimate the intracortical sources of the scalp potentials. SSEPs were characterised by a sequence of components with unique scalp topographies. Source analysis confirmed that median nerve SSEP component maps were in accordance with the somatotopic organisation of the sensorimotor cortex. Most importantly, SSEP recordings were stable both intra- and interindividually. We aim to apply this method to the study of recovery and reorganisation of large-scale neuronal networks following a focal cortical lesion requiring a craniotomy. As a prerequisite, the present study demonstrated that a 300-mm2 unilateral craniotomy over the sensorimotor cortex necessary to induce a cortical lesion, followed by bone flap repositioning, suture and gap plugging with calcium phosphate cement, did not induce major distortions of the SSEPs. In conclusion, SSEPs can be successfully and reproducibly recorded from high-density EEG caps in macaque monkeys before and after a craniotomy, opening new possibilities for the long-term follow-up of the cortical reorganisation of large-scale networks in macaque monkeys after a cortical lesion.

Multisource and color lighting for detection of small protuberance

In typical machine vision problems such as quality control or object location, it is often the case that elements of interest are small protuberances over a surface. We present an innovative and robust approach aiming at detecting such protuberances. Its basic ideas are to detect the shadows produced by the protuberances and to use several light sources simultaneously to enhance detection. Each light source produces a different set of shadows; combining the shadows produced by all light sources helps to locate the protuberance, because these shadows are the only significantly varying patterns between views. Rather than using several white light sources in sequence, it is possible to use simultaneous color sources with appropriate filters to separate the image into independent channels. The approach has been validated on a concrete problem with highly variable protuberances and nonplanar surfaces. The results confirm the robustness of this approach, which could be used for other problems as well.

Potato operation: computer vision for agricultural robotics

Each year at harvest time millions of seed potatoes are checked for the presence of viruses by means of an Elisa test. The Potato Operation aims at automatizing the potato manipulation and pulp sampling procedure, starting from bunches of harvested potatoes and ending with the deposit of potato pulp into Elisa containers. Automatizing these manipulations addresses several issues, linking robotic and computer vision. The paper reports on the current status of this project. It first summarizes the robotic aspects, which consist of locating a potato in a bunch, grasping it, positioning it into the camera field of view, pumping the pulp sample and depositing it into a container. The computer vision aspects are then detailed. They concern locating particular potatoes in a bunch and finding the position of the best germ where the drill has to sample the pulp. The emphasis is put on the germ location problem. A general overview of the approach is given, which combines the processing of both frontal and silhouette views of the potato, together with movements of the robot arm (active vision). Frontal and silhouette analysis algorithms are then presented. Results are shown that confirm the feasibility of the approach.