20 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…
Danil Tyulmankov
- Summarize the key models of synaptic plasticity and types of signals that can be used to update synaptic weights. - Provide an outline for organizing several major classes of learning and memory paradigms. - Link learning outcomes at a behavioral level to synaptic plasticity mechanisms that can implement them.
Marc van Oostrum, Thomas Blok, Stefano L. Giandomenico, Susanne tom Dieck + 4 more
Brain function relies on communication via neuronal synapses. Neurons build and diversify synaptic contacts using different protein combinations that define the specificity, function and plasticity potential of synapses. More than a thousand proteins have been globally identified in both pre- and postsynaptic…
Friedemann Zenke, Axel Laborieux
continual learning Authors: ['Friedemann Zenke' 'Axel Laborieux'] Humans and animals learn throughout life. Such continual learning is crucial for intelligence. In this chapter, we examine the pivotal role plasticity mechanisms with complex internal synaptic dynamics could play in enabling this ability in neural…
Ido Aizenbud, Daniela Yoeli, David Beniaguev, Christiaan PJ de Kock + 2 more
Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct…
Gabriel Moreno Cunha, Gillberto Corso, Matheus Phellipe Brasil de Sousa, Gustavo Zampier dos Santos Lima
'Matheus Phellipe Brasil de Sousa' 'Gustavo Zampier dos Santos Lima'] 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 the brain and…
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…
Stefano Fusi
Memory is a complex phenomenon that involves several distinct mechanisms. These mechanisms operate at different spatial and temporal levels. This chapter focuses on the theoretical framework and the mathematical models that have been developed to understand how these mechanisms are orchestrated to store, preserve and…
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…
Anamika Agrawal, Michael A. Buice
The simple linear threshold units used in many artificial neural networks have a limited computational capacity. Famously, a single unit cannot handle non-linearly separable problems like XOR. In contrast, real neurons exhibit complex morphologies as well as active dendritic integration, suggesting that their…
Alessio Quaresima, Hartmut Fitz, Renato Duarte, Dick van den Broek + 2 more
Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection, and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and…
Ido Aizenbud, David Beniaguev, Noam Pnueli, Idan Segev + 1 more
Cortical pyramidal neurons possess elaborate dendritic trees with diverse nonlinear membrane conductances and thousands of plastic synapses, suggesting substantial computational capabilities at the single-cell level. Yet, what can a neuron compute remains an open question, largely due to the lack of a systematic…
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…
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…
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…
Afsaneh Taheri Kal-Koshvandi
We present the first light-free, genetically minimal platform for spatiotemporally resolved proximity labeling across five neuronal compartments—synaptic, nuclear, endosomal, mitochondrial, and activity-dependent microdomains. A covalent "catalyst–luciferase sandwich" architecture site-specifically conjugates five…
Yuanmo Wang, Ajay Pradhan, Pankaj Gupta, Jörg Hanrieder + 2 more
Acetylcholine (ACh) is a critical neurotransmitter influencing various neurophysiological functions. Despite its significance, there is a lack of quantitative methods with adequate spatiotemporal resolution for recording single exocytotic efflux of ACh. In this study, we present an ultrafast amperometric ACh biosensor…
Sofie S. Kristensen, Kaan Kesgin, Henrik Jörntell
Complexity is important for flexibility of natural behavior and for the remarkably efficient learning of the brain. Here we assessed the signal complexity among neuron populations in somatosensory cortex (S1). To maximize our chances of capturing population level signal complexity, we used highly repeatable resolvable…
R. Jungmann, Thaís Feliciano, Leandro A. A. Aguiar, Carina Soares‐Cunha + 6 more
'Carina Soares‐Cunha' 'Bárbara Coimbra' 'Ana João Rodrigues' 'Mauro Copelli' 'Fernanda S. Matias' 'Nivaldo A. P. de Vasconcelos' 'Pedro V. Carelli'] The local field potential (LFP) is as a measure of the combined activity of neurons within a region of brain tissue. While biophysical modeling schemes for LFP in cortical…
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…