As a rule, no new neurons are born in the adult mammalian brain. As an exception, however, adult neurogenesis is readily observed in niches such as the dentate gyrus where neuronal precursors are transformed into granule cells. Dentate granule cells constitute a major population of principal cells in the trisynaptic circuit and are implicated in hippocampal functions such as pattern...
The Brain/MINDS 2.0 Digital Brain Project aims to develop an open, interoperable software platform dedicated to digital brain construction. This platform targets seamless integration of neuroscience simulation tools—including TVB, NEST, BMTK, —via their Python APIs, allowing researchers to build comprehensive and detailed brain models. As brain modeling and simulation research evolves, there...
Comprehensive simulation studies of dynamical regimes of cortical networks with realistic synaptic densities depend on compute systems capable of running such models significantly faster than biological real time. Since CPUs still are the primary target for established simulators, an inherent bottleneck caused by the von Neumann design is frequent memory access with minimal compute....
The human brain computes in a massively parallel fashion, not only at the level of the neurons, but also through complex subcellular signaling networks which support learning and memory. Therefore, it’s desirable to utilize the parallelization capabilities of modern supercomputers to simulate the brain in a massively parallel fashion. The NEural Simulation Tool (NEST) [1] enables massively...
This study translates the model of Chindemi et al. on calcium-dependent neocortical plasticity into a spiking neural network framework. Building on their work, we implemented a computationally efficient model comprising a point neuron and synapse model, using NESTML. Our approach combines the Hill-Tononi (HT) neuron, which features detailed NMDA and AMPA conductance dynamics, with the...
We present the development of a biologically grounded spiking neuronal network model of the prefrontal cortex (PFC), implemented in the NEST simulator using the adaptive exponential integrate-and-fire (AdEx) neuron model. Based on the architecture proposed by Hass et al. (2016), our model replaces the simplified AdEx (simpAdEx) neurons used in their study with the full AdEx model, thereby...
