14 papers · ranked by Valyu relevance
María Jesús Ramírez-Expósito, Cristina Cueto-Ureña, José Manuel Martínez-Martos, Paschalis Theotokis
Neuronal synapses are the functional units of communication in the central nervous system. This review describes the molecular mechanisms regulating synaptic transmission, plasticity, and circuit refinement. At the presynaptic active zone, scaffolding proteins including bassoon, piccolo, RIMs, and munc13 organize…
Margot Wagner, Thomas M. Bartol, Terrence J. Sejnowski, Gert Cauwenberghs
Progress in computational neuroscience toward understanding brain function is challenged both by the complexity of molecular-scale electrochemical interactions at the level of individual neurons and synapses and the dimensionality of network dynamics across the brain covering a vast range of spatial and temporal…
Terry Elliott
Models of associative memory with discrete state synapses learn new memories by forgetting old ones. In the simplest models, memories are forgotten exponentially quickly. Sparse population coding ameliorates this problem, as do complex models of synaptic plasticity that posit internal synaptic states, giving rise to…
Gabriel Moreno Cunha, Gilberto Corso, Matheus Phellipe Brasil de Sousa, Gustavo Zampier dos Santos Lima + 1 more
'Matheus Phellipe Brasil de Sousa' 'Gustavo Zampier dos Santos Lima' 'Michele Giugliano'] The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of…
Yuru Song, Marcus K. Benna
Cortical neurons often establish multiple synaptic contacts with the same postsynaptic neuron. To avoid functional redundancy of these parallel synapses, it is crucial that each synapse exhibits distinct computational properties. Here we model the current to the soma contributed by each synapse as a sigmoidal…
Michael W Reimann, Sirio Bolaños-Puchet, Jean-Denis Courcol, Daniela Egas Santander + 41 more
The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, interregional connectivity. We present a data-driven computational model of the anatomy of non-barrel primary somatosensory cortex of juvenile rat, integrating whole-brain scale data while providing…
Sapir Shapira, Ido Aizenbud, Daniela Yoeli, Yoni Leibner + 4 more
'Huibert D. Mansvelder' 'Christiaan P. J. de Kock' 'Michael London' 'Idan Segev'] The human brain’s remarkable computational power enables parallel processing of vast information, integrating sensory inputs, memories, and emotions for rapid learning, adaptability, and creativity - far surpassing present-day artificial…
Moritz Stingl, Andreas Draguhn, Martin Both
Dendritic signal integration beyond the “antenna” model Authors: ['Moritz Stingl' 'Andreas Draguhn' 'Martin Both'] Neurons in central nervous systems receive multiple synaptic inputs and transform them into a largely standardized output to their target cells-the action potential. A simplified model posits that synaptic…
Zubaer Ibna Mannan, Sami Azam, Ram Kaji Budhathoki, MD Nur Alam + 1 more
Title: Graphical abstract A neuromemristive synapse is developed that can emulate both homo- and heterosynaptic plasticity, showcasing the homeostatic and modular input-dependent roles of heterosynaptic plasticity, along with homosynaptic long-term and short-term potentiation and depression, and functioning effectively…
Luis El Srouji, Mahmoud Abdelghany, Hari Rakul Ambethkar, Yun-Jhu Lee + 2 more
'Yun-Jhu Lee' 'Mehmet Berkay On' 'S. J. Ben Yoo'] With the increasing number of applications reliant on large neural network models, the pursuit of more suitable computing architectures is becoming increasingly relevant. Progress toward co-integrated silicon photonic and CMOS circuits provides new opportunities for…
Zahra Khodadadi, Daniel Trpevski, Robert Lindroos, Jeanette Hellgren Kotaleski + 2 more
This study investigates the computational potential of single striatal projection neurons (SPNs), emphasizing dendritic nonlinearities and their crucial role in solving complex integration problems. Utilizing a biophysically detailed multicompartmental model of an SPN, we introduce a calcium-based, local synaptic…
W. Tecumseh Fitch
Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems. Both the information processing and information storage abilities of actual biological neurons vastly exceed the simple weighted sum of…
Roman Makarov, Michalis Pagkalos, Panayiota Poirazi
The brain is a highly efficient system evolved to achieve high performance with limited resources. We propose that dendrites make information processing and storage in the brain more efficient through the segregation of inputs and their conditional integration via nonlinear events, the compartmentalization of activity…
Daniela Egas Santander, Christoph Pokorny, András Ecker, Jānis Lazovskis + 5 more
'Jānis Lazovskis' 'Matteo Santoro' 'Jason P. Smith' 'Kathryn Hess' 'Ran Levi' 'Michael W. Reimann'] Title: Summary We hypothesized that the heterogeneous architecture of biological neural networks provides a substrate to regulate the well-known tradeoff between robustness and efficiency, thereby allowing different…