shamo: A tool for electromagnetic modelling, simulation and sensitivity analysis of the head

Accurate electromagnetic modelling of the head of a subject is of main interest in the fields of source reconstruction and brain stimulation. Those processes rely heavily on the quality of the model and, even though the geometry of the tissues can be extracted from magnetic resonance images (MRI) or computed tomography (CT), their physical properties such as the electrical conductivity are hard to measure with non intrusive techniques. In this paper, we propose a tool to assess the uncertainty in the model parameters as well as compute a parametric electroencephalography (EEG) forward solution and current distribution for transcranial direct current stimulation (tDCS).Comment: 8 pages, 5 figure

A study of atom localization in an optical lattice by analysis of the scattered light

We present an experimental study of a four beam optical lattice using the light scattered by the atoms in the lattice. We use both intensity correlations and observations of the transient behavior of the scattering when the lattice is suddenly switched on. We compare results for 3 different configurations of the optical lattice. We create situations in which the Lamb-Dicke effect is negligible and show that, in contrast to what has been stated in some of the literature, the damping rate of the 'coherent' atomic oscillations can be much smaller than the inelastic photon scattering rate.Comment: An old pape

Methods for studying cultural attraction

Cultural attraction theory (CAT) describes a general evolutionary process, cultural attraction, by which the spread and stability of cultural items (beliefs, practices, artifacts, etc.) result not just from differential reproduction, but also from transformations that systematically favor the reconstruction of cultural items of specific types. In this way, CAT aims to provide a general framework for the study of cultural evolution. In a thoughtful critical analysis, Buskell questions the ability of CAT to provide methodological guidance for research in cultural evolution. Can CAT be used to develop the sort of mid‐range theories and models that often drive empirical work? Here we argue that CAT can indeed be used in this way, and we outline the methodological practices that students of cultural attraction have used and are currently developing

Computer Aided Diagnosis System Based on Random Forests for the Prognosis of Alzheimer’s Disease

peer reviewedIn this abstract, we propose an original CAD system consisting in the combination of brain parcelling, ensemble of trees methods, and selection of (groups of) features using the importance scores embedded in tree-based methods. Indeed, on top of their ease of use and accuracy without ad hoc parameter tuning, tree ensemble methods such as random forests (RF) (Breiman, 2001) or extremely randomized trees (ET) (Geurts et al., 2006) provide interpretable results in the form of feature importance scores. We also compare the performance and interpretability of our proposed method to standard RF and ET approaches, without feature selection, and to multiple kernel learning (MKL). The latter was shown to be an efficient method notably capable of dealing with anatomically defined regions of the brain by the use of multiple kernels

Shamo v1.0 - Stochastic electromagnetic head modelling made easy

We introduce a Python 3 package: “shamo”. It can perform mesh generation, electromagnetic simulations and sensitivity analysis

Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets

Valuing One's Self: Medial Prefrontal Involvement in Epistemic and Emotive Investments in Self-views.

peer reviewedRecent neuroimaging research has revealed that the medial prefrontal cortex (MPFC) is consistently engaged when people form mental representations of themselves. However, the precise function of this region in self-representation is not yet fully understood. Here, we investigate whether the MPFC contributes to epistemic and emotive investments in self-views, which are essential components of the self-concept that stabilize self-views and shape how one feels about oneself. Using functional magnetic resonance imaging, we show that the level of activity in the MPFC when people think about their personal traits (by judging trait adjectives for self-descriptiveness) depends on their investments in the particular self-view under consideration, as assessed by postscan rating scales. Furthermore, different forms of investments are associated with partly distinct medial prefrontal areas: a region of the dorsal MPFC is uniquely related to the degree of certainty with which a particular self-view is held (one's epistemic investment), whereas a region of the ventral MPFC responds specifically to the importance attached to this self-view (one's emotive investment). These findings provide new insight into the role of the MPFC in self-representation and suggest that the ventral MPFC confers degrees of value upon the particular conception of the self that people construct at a given moment