Dendrites are crucial for integrating incoming synaptic information. Individual dendritic branches are thought to constitute a signal processing unit, yet how neighboring synapses shape the boundaries of functional dendritic units is not well understood. Here, we address the cellular basis underlying the organization of the strengths of neighboring Schaffer collateral-CA1 synapses by optical quantal analysis and spine size measurements. Inducing potentiation at clusters of spines produces NMDA-receptor-dependent heterosynaptic plasticity. The direction of postsynaptic strength change shows distance dependency to the stimulated synapses where proximal synapses predominantly depress, whereas distal synapses potentiate; potentiation and depression are regulated by CaMKII and calcineurin, respectively. In contrast, heterosynaptic presynaptic plasticity is confined to weakening of presynaptic strength of nearby synapses, which requires CaMKII and the retrograde messenger nitric oxide. Our findings highlight the parallel engagement of multiple signaling pathways, each with characteristic spatial dynamics in shaping the local pattern of synaptic strengths.
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http://dx.doi.org/10.1016/j.celrep.2021.108693 | DOI Listing |
PLoS Comput Biol
January 2025
Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. It is not always clear, however, how these theoretically-derived rules relate to biological mechanisms of plasticity in the brain, or how these different rules might be mechanistically implemented in different contexts and brain regions. This study shows that the calcium control hypothesis, which relates synaptic plasticity in the brain to the calcium concentration ([Ca2+]) in dendritic spines, can produce a diverse array of learning rules.
View Article and Find Full Text PDFCancer Res
January 2025
Yale University, New Haven, CT, United States.
Biomolecular condensation has emerged as a general principle in organizing biological processes, including immune response. Xu and colleagues recently reported that the cytoplasmic tail of the CD3ɛ subunit of TCR complex, when fused to CAR, can promote CAR condensation by liquid-liquid phase separation. Through sequence engineering, the authors identified modified CD3ɛ sequences that enhance the maturation of the immunological synapse and co-receptor signaling, leading to an improvement of cytotoxicity in vitro and anti-tumor effects in mouse xenograft models.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Sun Yat-Sen University, School of Material Science and Engineering, Nr.135 Xingang Xi Road, 510275, Guangzhou, CHINA.
Degradable features are highly desirable to advance next-generation organic mixed ionic-electronic conductors (OMIECs) for transient bioinspired artificial intelligence devices.It is highly challenging that OMIECs exhibit excellent mixed ionic-electronic behavior and show degradability simultaneously.Specially,in OMIECs,doping is often a tradeoff between structural disorder and charge carrier mobilities.
View Article and Find Full Text PDFNeurooncol Adv
January 2025
Imaging AI Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
Background: Publicly available data are essential for the progress of medical image analysis, in particular for crafting machine learning models. Glioma is the most common group of primary brain tumors, and magnetic resonance imaging (MRI) is a widely used modality in their diagnosis and treatment. However, the availability and quality of public datasets for glioma MRI are not well known.
View Article and Find Full Text PDFResearch (Wash D C)
January 2025
Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL 61801, USA.
Soft electronics, known for their bendable, stretchable, and flexible properties, are revolutionizing fields such as biomedical sensing, consumer electronics, and robotics. A primary challenge in this domain is achieving low power consumption, often hampered by the limitations of the conventional von Neumann architecture. In response, the development of soft artificial synapses (SASs) has gained substantial attention.
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