12 papers · ranked by Valyu relevance
Jeffrey D. Walker, Paul Aparicio, Shreya Saxena, Nicholas G. Hatsopoulos + 1 more
The ability to record neural populations during natural behavior now allows us to ask whether canonical motor-cortical dynamics, defined largely in constrained reaches to static targets, also organize self-paced, feedback-rich actions that require continuous correction. We recorded sensorimotor cortex in marmosets…
Justin D Shin, Michael Satchell, Paul Miller, Shantanu P Jadhav + 2 more
REM (rapid eye movement) and non-REM (NREM) sleep stages contribute to systems memory consolidation in hippocampal-cortical circuits. However, the physiological mechanisms underlying REM memory processes remain relatively unclear compared to NREM memory reactivation. Here we report, in rodents, the existence of…
Yiming Xue, Xiaojian Liu, Weimin Zhu, Shengfan Wang + 2 more
While protein-RNA interactions are fundamental to post-transcriptional processes, achieving a holistic understanding of their regulatory logic remains challenging. Current computational models often treat binding affinity, interface mapping, and RNA design as isolated tasks, thereby failing to provide a unified…
Hao Ding, Nannan Wu, Tianyi Qiu
DNA foundation models such as Evo2 7B adopt hybrid Hyena/attention architectures (Striped-Hyena2) whose single-stream autoregressive decoding is bounded by weight bandwidth at ∼45 tok/s. Speculative decoding on such hybrids faces a systems problem that prior SSM work solves only partially: after a draft is verified…
Hiroyuki Kusano, Takayuki Shiomi
Digital pathology has rapidly expanded over the past decade, driven by advances in whole-slide imaging and increasing demand for remote and data-integrated diagnostic workflows. However, many implementations remain limited to partial digitization, without fundamentally transforming laboratory and diagnostic processes.…
Zichao Jin, Jiaoru Wang, Wenjiang Huang, Jingcheng Zhang + 2 more
Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework.…
Xuebin Feng, Emma R. Master
Sequence similarity networks (SSNs) are graphical representations of sequence relationship frequently used for exploring protein sequence space. Conventional SSN workflows typically use BLAST to calculate sequence similarities and rely on external visualization tools to generate the final networks. Consequently, raw…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Hayato Idei, Keisuke Suzuki, Yuichi Yamashita
Mindfulness has established psychological benefits, such as stress reduction and emotional regulation; however, the underlying computational mechanisms, particularly in relation to mind-wandering, remain unclear. This study aimed to present a hierarchical recurrent neural network-based agent model grounded in the free…
Jackie Rao, Muntadher Jihad, Giulia Biffi, Paul D.W. Kirk
Identifying cell types from single-cell RNA sequencing (scRNA-seq) data typically requires several separate and often uninterpretable steps: dimensionality reduction, batch-correction, clustering, marker-gene identification and the discovery of finer-grained structure. Here we introduce scFLAME (single-cell Factor…
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
Emily Cordeiro, Daniela Herrera Chaves, Nima Talei, Iván Castro + 6 more
Statistical learning (SL) has been proposed to depend on the hippocampus, but traditional neuropsychological theories of long-term memory posit that the hippocampus is only necessary for explicit memory processes, not implicit memory processes. To reconcile these two accounts, we exposed 27 temporal lobe epilepsy (TLE)…