22 papers · ranked by Valyu relevance
Iván Mindlin, Carlos Coronel-Oliveros, Marc Llabrés, Jacobo D. Sitt + 5 more
A main characteristic of biological systems is their capacity to dynamically adapt to environmental changes. In the brain, synaptic plasticity enables the strengthening or weakening of connections between neurons, allowing neural circuits to adapt based on experience, learning, and environmental changes. Yet, it is…
Elias Roihuvuo, Lee Sturgis, Ahmed B. Montaser, Marcin Tabaka + 7 more
Purpose Homeostatic plasticity is crucial for maintaining stable neural activity by adjusting strength and intrinsic properties of synapses. This mechanism is vital for normal nervous system function and plays a role in various neurological conditions, including retinal degenerations. Sensitive night vision has been…
Burak Uzay, Kevin J. Zhang, Lisa M. Monteggia, Ege T. Kavalali
Dopamine is a monoamine neurotransmitter that regulates neuronal activity and synaptic transmission. While dopaminergic activity is known to suppress action potential-dependent glutamate release in certain brain regions, the modulatory effect of dopaminergic tone on spontaneous glutamate release is unclear. Here, we…
Michelle C Miller, Christoph Miehl, Brent Doiron
Strongly interconnected neuronal populations, called assemblies, dynamically form through synaptic plasticity mechanisms and are thought to be a substrate for memories in the brain. Many assembly formation models use Hebbian excitatory-to-excitatory plasticity, where coordinated activity strengthens recurrent…
Lindsay J. Stolting, Randall D. Beer
Neural circuits are remarkably robust to perturbations that threaten their function. Activity-dependent homeostatic plasticity (ADHP) is a stabilizing mechanism that supports robustness by tuning neuronal ion conductances to combat chronic over- or under-activity. Its restorative capacity has been demonstrated in the…
Lindsay J. Stolting, Randall D. Beer
Neural circuits are remarkably robust to perturbations that threaten their function. Activity-dependent homeostatic plasticity (ADHP) is a stabilizing mechanism that supports robustness by tuning neuronal ion conductances to combat chronic over- or under-activity. Its restorative capacity has been demonstrated in the…
Elena D. Bagatelas, Ok-ho Shin, Reagan M. Armstrong, Qiangjun Zhou + 1 more
De novo mutations in synaptotagmin-1 (syt1) cause a rare neurodevelopmental disorder, manifesting in global developmental delay, ophthalmic abnormalities, infantile hypotonia, facial dysmorphisms, absent speech, EEG abnormalities, and hyperkinetic movements, ranging from moderate to severe. Here, we evaluate eleven…
Gregor A. Bergmann, Melissa W. Tan, Katie Greenin‐Whitehead, Philippe J. Fischer + 2 more
Neural networks maintain stable activity levels by compensating for perturbations through homeostatic plasticity. However, homeostatic mechanisms operating at different levels may conflict with each other. For example, in inhibitory feedback circuits, if inhibitory neurons receive excess excitation, compensation at a…
Elena D. Bagatelas, Ok-ho Shin, Reagan M. Armstrong, Qiangjun Zhou + 1 more
De novo mutations in synaptotagmin-1 (syt1) cause a rare neurodevelopmental disorder, manifesting in global developmental delay, ophthalmic abnormalities, infantile hypotonia, facial dysmorphisms, absent speech, EEG abnormalities, and hyperkinetic movements, ranging from moderate to severe. Here, we evaluate eleven…
Andreas Massey, Aliaksandr Hubin, Stefano Nichele, Solve Sæbø
Spike-timing-dependent plasticity (STDP) provides a biologically-plausible learning mechanism for spiking neural networks (SNNs); however, Hebbian weight updates in architectures with recurrent connections suffer from pathological weight dynamics: unbounded growth, catastrophic forgetting, and loss of representational…
Stefano Antonucci, Guillaume Caron, Natalie Dikwella, Sruthi Sankari Krishnamurthy + 11 more
Homeostatic feedback loops are essential to stabilize the activity of neurons and neuronal networks. It has been hypothesized that, in the context of Amyotrophic Lateral Sclerosis (ALS), an excessive gain in feedback loops might hyper- or hypo-excite motoneurons (MNs) and contribute to the pathogenesis. Here, we…
Joshua Harrison, Ellie Greene, Aaron Yang, Jumana Akoad + 4 more
Sympathetic neuronal (SN) activity critically regulates the development and function of peripheral organs and tissues. The demonstration of activity-dependent modulation of SN output suggests that compensatory forms of plasticity could contribute to maintaining the stability of sympathetic circuits. Such plasticity…
Byung Gyu Chae
We formulate the Fast-Weights Homeostatic Reentry Network (FHRN) as a continuous-time neural-ODE system, revealing its role as a norm-regulated reentrant dynamical process. Starting from the discrete reentry rule x t = x (ex) t + γ W r g(∥yt−1∥) yt−1, we derive the coupled system y˙ = −y + f(Wry; x, A) + gh(y) showing…
Yunduo Zhou, Bo Dong, Chang Li, Yuanchen Wang + 3 more
Homeostatic mechanisms play a crucial role in maintaining optimal functionality within the neural circuits of the brain. By regulating physiological and biochemical processes, these mechanisms ensure the stability of an organism's internal environment, enabling it to better adapt to external changes. Among these…
Naomi Auer, Lars Chen, Jakob Stubenrauch, Benjamin Lindner + 2 more
The brain can efficiently learn and form memories based on limited exposure to stimuli, often even in single trials. Two key factors are believed to support this ability: large synaptic plasticity to strongly encode new memories; and sparse coding, leading to low overlap between memory representations and to small…
Ece Öner, Cenk Denktaş
Due to the complexities of simulating bioenergetics, most Spiking Neural Network (SNN) models treat neurones as energetically unconstrained, omitting the metabolic costs of neural activity. We introduce a computational framework that employs thermodynamic variables to directly integrate metabolic regulation into…
Chae, B. G.
This study introduces the Fast-Weights Homeostatic Reentry Layer (FH-RL), a neural mechanism that integrates fast-weight associative memory, homeostatic regularization, and learned reentrant feedback to approximate self-referential computation in neural networks. Unlike standard transformer architectures that operate…
Suzanne van der Veldt, Gido M. van de Ven, Sanne Moorman, Guillaume Etter
Deep artificial neural networks famously struggle to learn from non-stationary streams of data. Without dedicated mitigation strategies, continual learning is associated with continuous forgetting of previous tasks and a progressive loss of plasticity. Current approaches to continual learning have either focused on…
Nelson D. Horseman
There have been wide-ranging discussions and arguments about exactly what homeostasis is and how it works, and here I list a few papers that I found informative and useful guides to the rest of the literature (Bechtel & Bich, ; ; Billman, ; Dallman, ; Davies, ; Houk, ; McEwen & Wingfield, ; Modell et al., ; Ramsay &…
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The Golgi apparatus (GA) orchestrates protein modification, trafficking, and secretion through highly dynamic remodeling, yet its proteomic complexity remains difficult to resolve in living systems. Here, we report CAT-Golgi, a genetically independent and light-controlled photocatalytic proximity labeling strategy for…
Authors not listed
Molecular mechanisms governing initiation steps of the assembly of thousands of endogenous multi-protein complexes (EMCs) remain incompletely understood. Here, multiple lines of observations are reported reflecting the biological functions-aligned initiation sequence of hybrid assembly pathways (HAPs) of EMCs. HAPs…
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Understanding how plants respond to dynamic and spatially variable stimuli is a key goal in plant sciences. Traditional imaging methods often involve a trade-off between environmental control and spatial resolution, limiting their ability to capture real-time responses in high resolution. Microfluidic technology…