98%
921
2 minutes
20
The breadth and complexity of natural behaviors inspires awe. Understanding how our perceptions, actions, and internal thoughts arise from evolved circuits in the brain has motivated neuroscientists for generations. Researchers have traditionally approached this question by focusing on stereotyped behaviors, either natural or trained, in a limited number of model species. This approach has allowed for the isolation and systematic study of specific brain operations, which has greatly advanced our understanding of the circuits involved. At the same time, the emphasis on experimental reductionism has left most aspects of the natural behaviors that have shaped the evolution of the brain largely unexplored. However, emerging technologies and analytical tools make it possible to comprehensively link natural behaviors to neural activity across a broad range of ethological contexts and timescales, heralding new modes of neuroscience focused on natural behaviors. Here we describe a three-part roadmap that aims to leverage the wealth of behaviors in their naturally occurring distributions, linking their variance with that of underlying neural processes to understand how the brain is able to successfully navigate the everyday challenges of animals' social and ecological landscapes. To achieve this aim, experimenters must harness one challenge faced by all neurobiological systems, namely variability, in order to gain new insights into the language of the brain.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082559 | PMC |
http://dx.doi.org/10.1016/j.cub.2022.03.031 | DOI Listing |
Comput Biol Med
September 2025
Department of Electrical and Computer Engineering and the Institute of Biomedical Engineering, University of New Brunswick, Fredericton, E3B 5A3, NB, Canada.
Pattern recognition-based myoelectric control is traditionally trained with static or ramp contractions, but this fails to capture the dynamic nature of real-world movements. This study investigated the benefits of training classifiers with continuous dynamic data, encompassing transitions between various movement classes. We employed both conventional (LDA) and deep learning (LSTM) classifiers, comparing their performance when trained with ramp data, continuous dynamic data, and an LSTM pre-trained with a self-supervised learning technique (VICReg).
View Article and Find Full Text PDFChem Biodivers
September 2025
School of Traditional Chinese Materia Medica, Key Laboratory of Ethnomedicine Material Basis & Pharmacological Mechanisms, Shenyang, Shenyang Pharmaceutical University, Shenyang, China.
In intracellular signaling, mammalian target of rapamycin (mTOR) as an important mammalian target for breast cancer therapy, plays a key role in receiving upstream signals from growth factor receptors such as epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2). Using 30 compounds from Meehania fargesii var. Radicans, structure-based virtual screening and molecular docking were performed to develop novel and safe breast cancer targeting inhibitors from natural products.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh 15213, Pennsylvania.
We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
State Key Laboratory of Membrane Biology, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing 100084, China.
Although clinical research has revealed microglia-related inflammatory and immune responses in bipolar disorder (BD) patient brains, it remains unclear how microglia contribute to the pathogenesis of BD. Here, we demonstrated that Serinc2 is associated with susceptibility to BD and showed a reduced expression in BDII patient plasma, which correlated with the disease severity. Using induced pluripotent stem cell (iPSC) models of sporadic and familial BDII patients, we found that Serinc2 expression showed deficits in iPSC-derived microglia-like cells, resulting in decreased synaptic pruning.
View Article and Find Full Text PDFPLoS One
September 2025
School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Background: When analyzing cells in culture, assessing cell morphology (shape), confluency (density), and growth patterns are necessary for understanding cell health. These parameters are generally obtained by a skilled biologist inspecting light microscope images, but this can become very laborious for high-throughput applications. One way to speed up this process is by automating cell segmentation.
View Article and Find Full Text PDF