Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
We investigate the memory effects in cyclically deformed amorphous solids through computer simulations. Applying oscillatory shear deformations in all orthogonal directions during encoding creates fault-tolerant memories that are agnostic to the reading direction. Our extensive system size analysis shows that memory encoding is faster in small systems and becomes exceedingly challenging as systems approach the thermodynamic limit. To capitalize on the quickness of memory encoding in small system sizes, it is important to demonstrate that memory can be encoded in nanoscale objects, where open surfaces play a crucial role. We achieve this by going from 3D bulk to pseudo-1D nanorods. Using tension-compression cycles on these nanorods, we show that memory encoding and reading are also possible in the presence of free surfaces.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1103/PhysRevLett.134.018202 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Cortical versus hippocampal network dysfunction in a human brain assembloid model of epilepsy and intellectual disability.
Cell Rep
September 2025
Department of Neurology, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA 90095, USA; Department of Neurobiology, University of California, Los Angeles, Los Angeles, CA 90095, USA; Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, Un
Neurodevelopmental disorders often impair multiple cognitive domains. For instance, a genetic epilepsy syndrome might cause seizures due to cortical hyperexcitability and present with memory impairments arising from hippocampal dysfunction. This study examines how a single disorder differentially affects distinct brain regions using induced pluripotent stem cell (iPSC)-derived cortical- and hippocampal-ganglionic eminence assembloids to model developmental and epileptic encephalopathy 13, a condition arising from gain-of-function mutations in the SCN8A gene encoding the sodium channel Nav1.
View Article and Find Full Text PDFTumor microenvironment differences between diagnostic and relapsed classic Hodgkin lymphoma revealed by scRNA-seq.
Blood Adv
September 2025
BC Cancer, Vancouver, British Columbia, Canada.
Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed-Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B-cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL.
View Article and Find Full Text PDFPreparatory attentional templates in prefrontal and sensory cortex encode target-associated information.
Elife
September 2025
Center for Mind and Brain, University of California, Davis, Davis, United States.
Visual search relies on the ability to use information about the target in working memory to guide attention and make target-match decisions. The 'attentional' or 'target' template is thought to be encoded within an inferior frontal junction (IFJ)-visual attentional network. While this template typically contains veridical target features, behavioral studies have shown that target-associated information, such as statistically co-occurring object pairs, can also guide attention.
View Article and Find Full Text PDFEEG-ERnet: Emotion Recognition based on Rhythmic EEG Convolutional Neural Network Model.
J Integr Neurosci
August 2025
School of Computer Science, Guangdong Polytechnic Normal University, 510665 Guangzhou, Guangdong, China.
Background: Emotion recognition from electroencephalography (EEG) can play a pivotal role in the advancement of brain-computer interfaces (BCIs). Recent developments in deep learning, particularly convolutional neural networks (CNNs) and hybrid models, have significantly enhanced interest in this field. However, standard convolutional layers often conflate characteristics across various brain rhythms, complicating the identification of distinctive features vital for emotion recognition.
View Article and Find Full Text PDFFrom encoding to remembering: pragmatic inferences reveal distinct routes of word learning in autistic children.
Front Hum Neurosci
August 2025
Department of Psychology, Northeastern University, Boston, MA, United States.
Mentalizing skills-the capacity to attribute mental states-play critical roles in word learning during typical language development. In autism, mentalizing difficulties may constrain word-learning pathways, limiting language-acquisition opportunities. We ask how autistic children encode and retrieve novel words and what drives individual differences.
View Article and Find Full Text PDF