Time and the brain: neurorelativity. The chronoarchitecture of the brain from the neuronal rather than the observer's perspective
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Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentia ...
A rank-adaptive integrator for the approximate solution of high-order tensor differential equations by tree tensor networks is proposed and analyzed. In a recursion from the leaves to the root, the integrator updates bases and then evolves connection tenso ...
In this thesis, we present a data-driven iterative pipeline to generate, simulate and validate point-neuron models of the whole mouse brain. The ultimate goal is to replicate close loop experiments with a virtual body in a virtual world. This pipeline was ...
Neurons primarily communicate through release of neurotransmitter from presynaptic specialisations along their axonal arborisations. In order to understand the functional role of a specific neuron, it is therefore of great interest to know the structure of ...
An important function of the brain is to analyze sensory information, and to modulate animal behaviour according to previous experience. During processes of emotional learning, sensory percepts with a reinforcing quality, also called unconditioned stimuli ...
Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise ...
Despite a long history of research in motor control, the exact mechanism of how the brain communicates with the the invertebrate ventral nerve cord (VNC) and the vertebrate spinal cord on a single neuron basis remains largely elusive.Drosophila melanogaste ...
Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these ...
Fitting network models to neural activity is an important tool in neuroscience. A popular approach is to model a brain area with a probabilistic recurrent spiking network whose parameters maximize the likelihood of the recorded activity. Although this is w ...
Computational modeling and simulation have become essential tools in the quest to better understand the brain's makeup and to decipher the causal interrelations of its components. The breadth of biochemical and biophysical processes and structures in the b ...