Recent experimental evidence indicates that in the neocortex, the manner in which each synapse releases neurotransmitter in response to trains of presynaptic action potentials is potentially unique. These unique transmission characteristics arise because of a large heterogeneity in various synaptic properties that determine frequency dependence of transmission such as those governing the rates of synaptic depression and facilitation. A theoretical analysis was therefore undertaken to explore the phenomenologies of changes in the values of these synaptic parameters. The results illustrate how the change in any one of several synaptic parameters produces a distinctive effect on synaptic transmission and how these distinctive effects can point to the most likely biophysical mechanisms. These results could therefore be useful in studies of synaptic plasticity in order to obtain a full characterization of the phenomenologies of synaptic modifications and to isolate potential biophysical mechanisms. Based on this theoretical analysis and experimental data, it is proposed that there exists multiple mechanisms, phenomena and algorithms for synaptic plasticity at single synapses. Finally, it is shown that the impact of changing the values of synaptic parameters depends on the values of the other parameters. This may indicate that the various mechanisms, phenomena and algorithms are interlinked in a 'synaptic plasticity code'.
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http://dx.doi.org/10.1016/s0028-3908(98)00049-5 | DOI Listing |
Exp Brain Res
January 2025
Department of Rehabilitation Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510080, China.
Vestibular dysfunction has been reported as a potential cause in adolescent idiopathic scoliosis (AIS). However, it remained unclear how stochastic galvanic vestibular stimulation (GVS) affected kinetic performance of patients with AIS. This study aimed to investigate the effect of stochastic GVS on ground reaction forces (GRF) measures during obstacle negotiation among patients with AIS.
View Article and Find Full Text PDFBackground: Neuroblastoma is a heterogeneous disease with adrenergic (ADRN)- and therapy resistant mesenchymal (MES)-like cells driven by distinct transcription factor networks. Here, we investigate the expression of immunotherapeutic targets in each neuroblastoma subtype and propose pan-neuroblastoma and cell state specific targetable cell-surface proteins.
Methods: We characterized cell lines, patient-derived xenografts, and patient samples as ADRN-dominant or MES-dominant to define subtype-specific and pan-neuroblastoma gene sets.
Sci Rep
January 2025
Chair of Applied Mechanics, Technical University of Munich, Garching, 85748, Germany.
Ankle push-off is important for efficient, human-like walking, and many prosthetic devices mimic push-off using motors or elastic elements. The knee is extended throughout the stance phase and begins to buckle just before push-off, with timing being crucial. However, the exact mechanisms behind this buckling are still unclear.
View Article and Find Full Text PDFEcol Lett
January 2025
Department of Geography, Faculty of Science, Environment and Economy, University of Exeter, Exeter, UK.
Understanding the effects of multiple stressors has become a major focus in ecology and evolution. While many studies have investigated the combined effects of stressors, revealing massive variability, a mechanistic understanding that reconciles the diversity of multiple stressor outcomes is lacking. Here, we show how performance curves can fill this gap by revealing mechanisms that shape multiple stressor outcomes.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions.
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