20 papers · ranked by Valyu relevance
Vos, Gideon, van Eijk, Liza + 4 more
- We propose a magnitude-based synaptic pruning method as a regularization approach - The method emulates biological synaptic pruning by dynamically and progressively eliminating low-importance neural connections - Experiments across RNN, LSTM, and PatchTST models show statistically significant error reductions - Our…
Yakang Xing, Yi Mo, Qihui Chen, Xiao Li
Synaptic pruning is a crucial process in synaptic refinement, eliminating unstable synaptic connections in neural circuits. This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms. The pruning process involves multiple molecular signals and a series of…
Ukyo T. Tazawa, Takuya Isomura
Identifying appropriate structures for generative or world models is essential for both biological organisms and machines. This work shows that synaptic pruning facilitates efficient statistical structure learning. We extend previously established canonical neural networks to derive a synaptic pruning scheme that is…
Yo Shinoda, Tsunehiro Tanaka, Keiko Tominaga-Yoshino, Akihiko Ogura + 1 more
'Fabien Tell'] Synaptic pruning is a physiological event that eliminates excessive or inappropriate synapses to form proper synaptic connections during development of neurons. Appropriate synaptic pruning is required for normal neural development. However, the mechanism of synaptic pruning is not fully understood.…
Côme Camus, Léa Leval, Viviana Villicana-Munoz, Sarka Jelinkova + 5 more
Title: Summary Long-term depression (LTD) is an activity-dependent decrease in synaptic strength. This state initiates either a re-potentiation or a loss, aka pruning, of the synapse within hours to days following its induction. However, the precise relationship between LTD and synaptic pruning remains elusive. Using…
Hongying Liu, Min Jiang, Zhiying Chen, Chuan Li + 3 more
'Xiaorong Zhang' 'Moxin Wu'] Stroke is a serious disease that can lead to local neurological dysfunction and cause great harm to the patient’s health due to blood cerebral circulation disorder. Synaptic pruning is critical for the normal development of the human brain, which makes the synaptic circuit completer and…
Huihong Li, Zhiran Xie, Yuxuan Tian, Yaxi Yang + 12 more
Alzheimer’s disease (AD) and epilepsy (EP) share a complex bidirectional relationship, yet the molecular mechanisms underlying their comorbidity remain insufficiently explored. To identify potential consensus transcriptional programs across animal models and human patients with AD and EP, we conducted comprehensive…
Chen Yu, Xiao-Peng Zhang, Wei Wang
Autism spectrum disorder (ASD) has been increasingly associated with abnormalities in synaptic pruning. Although significant progress has been made in elucidating the genetic and immunological underpinnings of ASD, its core pathological mechanisms remain poorly understood. In this study, we developed a network model…
Eli K. Moore, Rishidev Chaudhuri
Many networks in the brain are sparsely connected, and the brain eliminates synapses during development and learning. How could the brain decide which synapses to prune? In a recurrent network, determining the importance of a synapse between two neurons is a difficult computational problem, depending on the role that…
Sanjith Senthil, Rishidev Chaudhuri
The pruning of network connections is key to brain function but, despite its importance, there exist few biologically-plausible pruning rules with demonstrated good performance. In this work we evaluate noise-prune, a recently introduced unsupervised local pruning rule for recurrent networks that uses noisy…
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici, Korbinian Schreiber + 3 more
'Korbinian Schreiber' 'David Kappel' 'Johannes Schemmel' 'Karlheinz Meier'] In computational neuroscience, as well as in machine learning, neuromorphic devices promise an accelerated and scalable alternative to neural network simulations. Their neural connectivity and synaptic capacity depends on their specific design…
Ana P. Millán, Joaquı́n J. Torres, Samuel Johnson, Joaquín Marro
The interplay between structure and function is crucial in determining some emerging properties of many natural systems. Here we use an adaptive neural network model inspired in observations of synaptic pruning that couples activity and topological dynamics and reproduces experimental temporal profiles of synaptic…
Carolin Scholl, Michael E. Rule, Matthias H. Hennig
During development, biological neural networks produce more synapses and neurons than needed. Many of these synapses and neurons are later removed in a process known as neural pruning. Why networks should initially be over-populated, and processes that determine which synapses and neurons are ultimately pruned, remains…
Ngo Cheung
Background Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive behaviors, with incomplete response to current treatments suggesting limitations in prevailing neurotransmitter-focused models. Epidemiological data indicate lifetime DSM-IV OCD in approximately 2.3% and 12-month OCD in…
Bing Han, Feifei Zhao, Yi Zeng, Guobin Shen
—Developmental plasticity plays a prominent role in shaping the brain's structure during ongoing learning in response to dynamically changing environments. However, the existing network compression methods for deep artificial neural networks (ANNs) and spiking neural networks (SNNs) draw little inspiration from brain's…
Rodrigo S. Kazu, Kleber Neves, Bruno Mota
connectivity Authors: ['Rodrigo S. Kazu' 'Kleber Neves' 'Bruno Mota'] From the proliferative mechanisms generating neurons from progenitor cells to neuron migration and synaptic connection formation, several vicissitudes culminate in the mature brain. Both component loss and gain remain ubiquitous during brain…
Wenzhe Guo, Mohammed E. Fouda, Hasan Erdem Yantir, Ahmed M. Eltawil + 1 more
'Khaled Nabil Salama'] To tackle real-world challenges, deep and complex neural networks are generally used with a massive number of parameters, which require large memory size, extensive computational operations, and high energy consumption in neuromorphic hardware systems. In this work, we propose an unsupervised…
Authors not listed
Researching the EEEV virus is challenging due to the virus's high lethality and significant risk. This study employed bioinformatics methods for domain search to investigate the pathogenesis and infection process of the EEEV virus P protein. The results demonstrated that the EEEV virus P protein contains domains that…
Authors not listed
TIMP2 (Tissue Inhibitor of Metalloproteinase-2) plays a crucial role in hippocampal neuroplasticity and cognitive function through MMP-independent signaling. Despite its therapeutic promise, TIMP2 has long been considered 'undruggable' due to its cryptic surface topology and lack of canonical active sites. We present a…
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…