openMINDS is a metadata framework for neuroscience graph databases, such as the EBRAINS Knowledge Graph. The framework is composed of (i) a set of interlinked metadata models formalizing different aspects of neuroscience data descriptions, (ii) libraries of controlled metadata descriptions for selected schema types (e.g, brain atlas schemas), (iii) mappings of schema types and properties to...
MOTIVATION
The firing patterns of stellate cells in layer II of medial entorhinal cortex are involved in memory, cognition and perception [1]. These patterns are largely modulated by the underlying subcellular calcium dynamics within the axon initial segment (AIS) [2]. Recent experimental data have suggested a putative coupling between dopamine D2 receptors (D2R) and T-type Ca2+ channels as...
This paper introduces methods and a novel toolbox that efficiently integrates any high-dimensional Neural Mass Models (NMMs) specified by two essential components. The first is the set of nonlinear Random Differential Equations of the dynamics of each neural mass. The second is the highly sparse three-dimensional Connectome Tensor (CT) that encodes the strength of the connections and the...
In goal-driven modeling, constructing a model of the brain as a neural network begins at the macroscopic scale; i.e., brain regions and the pathways linking them build the foundation for connecting layers in neuro-inspired network architectures. The precise weights linking units in connected layers, however, emerge from optimization on an ecologically valid task constituting the goal. It is...
Aims: Visual system of mammals is comprised of two parallel pathways: the “what” and the “where” pathways which are specialized for object categorization and movement, respectively. An Artificial Neural Network (ANN) model of mammalian visual systems should also have the same specialized parallel pathways. Previously (Bakhtiari et al., NeurIPS, 2021), we showed that the “what” and “where”...
The analysis of high-resolution microscopic scans of histological brain sections enables the identification of cytoarchitectonic areas, which are defined by the spatial organization of neuronal cells. Cutting the brain into histological sections is necessary to enable image acquisition at sufficient resolution. However, this cutting process leads to a loss of information about the 3D structure...
