27 papers · ranked by Valyu relevance
Kashu Yamazaki, Viet-Khoa Vo-Ho, Darshan Bulsara, Ngan Le + 1 more
The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs. With the recent increasing need for the autonomy of machines in the real world, e.g.…
Padraig Gleeson, Sharon Crook, Robert C. Cannon, Michael L. Hines + 10 more
Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven…
Wei Ou, Shitao Xiao, Chengyu Zhu, Wenbao Han + 1 more
With the development of technology, Moore's law will come to an end, and scientists are trying to find a new way out in brain-like computing. But we still know very little about how the brain works. At the present stage of research, brain-like models are all structured to mimic the brain in order to achieve some of the…
Calvin Yeung, Zhixin Lu, Kris Ganjam, Stefan Mihalas
Biological neural networks contain diverse cell types with heterogeneous electrophysiological properties. Artificial neural networks (ANNs) model computational aspects of biology but use homogeneous neurons, limiting realism. A key obstacle to building bio-inspired ANNs is the absence of a database of neuron models…
Mollie Ward, Oliver Rhodes
Neuromorphic systems aim to provide accelerated low-power simulation of Spiking Neural Networks (SNNs), typically featuring simple and efficient neuron models such as the Leaky Integrate-and-Fire (LIF) model. Biologically plausible neuron models developed by neuroscientists are largely ignored in neuromorphic computing…
Martina Nicoletti, Letizia Chiodo, Alessandro Loppini, Qiang Liu + 4 more
'Viola Folli' 'Giancarlo Ruocco' 'Simonetta Filippi' 'Gennady S. Cymbalyuk'] The nematode Caenorhabditis elegans is a widely used model organism for neuroscience. Although its nervous system has been fully reconstructed, the physiological bases of single-neuron functioning are still poorly explored. Recently, many…
Ankur Sinha, Padraig Gleeson, Bóris Marin, Salvador Dura-Bernal + 7 more
Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these…
Junwen Luo
Neural ptosthetic devices offer the ability to develop novel treatments for previously incurable diseases and ailments, such as deafness, blindness and tetraplepia. There is the potential to extend this concept to incorporate cognitive prosthetics, whereby damaged individual neuron cells or larger brain regiops are…
Oguzhan Derebasi, Murat Işık, Oguzhan Demirag, Dilek Göksel Duru + 1 more
'Anup Das'] Guillain-Barre syndrome is a rare neurological condition in which the human immune system attacks the peripheral nervous system. A peripheral nervous system appears as a diffusively connected system of mathematical models of neuron models, and the system's period becomes shorter than the periods of each…
Viktor Janos Olah, Nigel P Pedersen, Matthew JM Rowan
Understanding the activity of the mammalian brain requires an integrative knowledge of circuits at distinct scales, ranging from ion channel time constants to synaptic connection probabilities. To understand how multiple parameters contribute synergistically to circuit behavior as a whole, neuronal computational models…
Pramod Kumbhar, Michael L. Hines, Jeremy Fouriaux, Aleksandr Ovcharenko + 3 more
'Aleksandr Ovcharenko' 'James King' 'Fabien Delalondre' 'Felix Schürmann'] Abstract The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer…
Alon Korngreen
Modeling voltage-gated ion channel function is essential for understanding neuronal excitability. However, finding the right balance between model complexity and practicality is a significant challenge. In this study, I explored how sensitive Markov models of ion channels were to different parameters, beginning with a…
Justas Birgiolas, Vergil Haynes, Padraig Gleeson, Richard C. Gerkin + 2 more
As researchers develop computational models of neural systems with increasing sophistication and scale, it is often the case that fully de novo model development is impractical and inefficient. Thus arises a critical need to quickly find, evaluate, re-use, and build upon models and model components developed by other…
Nicolas Le Novère
Computational neurobiology was born over half a century ago, and has since been consistently at the forefront of modelling in biology. The recent progress of computing power and distributed computing allows the building of models spanning several scales, from the synapse to the brain. Initially focused on electrical…
Ramin Hasani, Victoria Beneder, Magdalena Fuchs, David Lung + 1 more
'Radu Grosu'] We introduce SIM-CE, an advanced, userfriendly modeling and simulation environment in Simulink for performing multi-scale behavioral analysis of the nervous system of Caenorhabditis elegans (C. elegans). SIM-CE contains an implementation of the mathematical models of C. elegans's neurons and synapses, in…
Justas Birgiolas, Vergil Haynes, Padraig Gleeson, Richard C. Gerkin + 3 more
'Suzanne W. Dietrich' 'Sharon Crook' 'Thomas Serre'] As researchers develop computational models of neural systems with increasing sophistication and scale, it is often the case that fully de novo model development is impractical and inefficient. Thus arises a critical need to quickly find, evaluate, re-use, and build…
Gaute T. Einevoll, Alain Destexhe, Markus Diesmann, Sonja Grün + 6 more
'Viktor Jirsa' 'Marc de Kamps' 'Michele Migliore' 'Torbjørn V. Ness' 'Hans Ekkehard Pleßer' 'Felix Schürmann'] 1Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway 2Department of Physics, University of Oslo, 0316 Oslo, Norway 3Paris-Saclay Institute of Neuroscience (NeuroPSI)…
Renan O. Shimoura, Rodrigo F. O. Pena, Vinícius Lima, Nilton L. Kamiji + 2 more
'Nilton L. Kamiji' 'Mauricio Girardi‐Schappo' 'Antônio C. Roque'] - 1 Departamento de F´ısica, FFCLRP, Universidade de S˜ao Paulo, Ribeir˜ao Preto, SP, 14040- 901, Brazil - 2 Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey, NJ, USA - 3 Institut…
Dimitri Plotnikov, Bernhard Rumpe⋆, Inga Blundell, Tammo Ippen + 2 more
'Jochen Martin Eppler' 'Abgail Morrison'] Biological nervous systems exhibit astonishing complexity. Neuroscientists aim to capture this complexity by modeling and simulation of biological processes. Often very complex models are necessary to depict the processes, which makes it difficult to create these models.…
Nikolay Bazenkov, Varvara Dyakonova, О. П. Кузнецов, Dmitri Sakharov + 2 more
'Dmitry Vorontsov' 'L. Yu. Zhilyakova'] We propose a novel discrete model of central pattern generators (CPG), neuronal ensembles generating rhythmic activity. The model emphasizes the role of nonsynaptic interactions and the diversity of electrical properties in nervous systems. Neurons in the model release different…
Manjusha Nair, Jinesh Manchan Kannimoola, Bharat Jayaraman, Bipin Nair + 2 more
'Bipin Nair' 'Shyam Diwakar' 'Nicolas Rougier'] Background Several new programming languages and technologies have emerged in the past few decades in order to ease the task of modelling complex systems. Modelling the dynamics of complex systems requires various levels of abstractions and reductive measures in…
Sanjar Adilov
Generative neural networks have shown promising results in de novo drug design. Recent studies suggest that one of the efficient ways to produce novel molecules matching target properties is to model SMILES sequences using deep learning in a way similar to language modeling in natural language processing. In this…
Rongpei Gou, Jingyi Yang, Menghan Guo, Yingjun Chen + 1 more
Central nervous system (CNS) drugs have had a significant impact on human health, e.g., treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models, particularly those for designing drugs from scratch, have shown great potential for accelerating drug…
Authors not listed
Acetylcholine (ACh) is a key neurotransmitter involved in cognitive function, motor control, and synaptic modulation, yet its electrochemical inactivity and the rapid kinetics of exocytosis have hindered real-time quantal detection. Previous micrometer-scale enzymatic ACh biosensors enabled sub-millisecond…
Authors not listed
The GluK1 receptor, an ionotropic glutamate receptor, operates as a ligand-gated ion channel. Opioids stand as the most potent pain-relieving medications currently prescribed in the medical field. Inhibiting this receptor is anticipated to result in a reduction of dopamine release in the Nucleus Accumbens, effectively…
Authors not listed
Current methods for determining the neurotoxic potential of (agro)chemicals are not comprehensive enough, as is suggested by the increased incidence of Parkinson’s disease (PD) amongst people exposed to certain pesticides. Mechanism-based in silico screening can address this shortcoming by predicting molecular…
Authors not listed
Carbon fiber has become the standard electrode material to study neuronal communication. For techniques such as single-cell amperometry at synapses and intracellular recordings of neurotransmitters in secretory vesicles, nanometric electrodes are required. The smaller electrode dimension also offers the added benefit…