23 papers · ranked by Valyu relevance
Xiaoxuan Xiao, Ueli Rutishauser, Taufik A. Valiante, Jiannis Taxidis
Working memory (WM), the active retention of information over short periods, is a fundamental cognitive function, yet its underlying neural mechanisms remain unclear. In rodents, cue-selective “time cells” fire at specific timepoints after a WM memory cue, collectively forming sequences that encode cue-memory and…
Huanqiu Zhang, Israel Nelken, Tatyana Sharpee
Deciphering the neural code requires identifying its fundamental symbols or code-words. Neural activity is usually interpreted either as a rate code – based on average spike counts – or as a temporal code, which distinguishes patterns with identical counts. Yet, the symbols of the code remain undefined. Here we show…
Nigel Crook, Alexander D. Rast, Eleni Elia, Mario Antoine Aoun
Introduction In this work, we introduce a novel approach to one of the historically fundamental questions in neural networks: how to encode information? More particularly, we look at temporal coding in spiking networks, where the timing of a spike as opposed to the frequency, determines the information content. In…
Aakash Sarkar, Marc W. Howard
Human cognition integrates information across nested timescales. While the cortex exhibits hierarchical Temporal Receptive Windows (TRWs), local circuits often display heterogeneous time constants. To reconcile this, we trained biologically constrained deep networks, based on scale-invariant hippocampal time cells, on…
Toktam Samiei, Hafiz Fareed Ahmed, Edward Zagha, Erfan Nozari
Despite over a century of research into the neural code, the fundamental principles by which the brain encodes sensory information remain debated. In this study we provide converging evidence for the presence of a dynamic, fast-switching integration of rate and temporal coding in the thalamus, primary visual cortex…
Stefano Panzeri, Nicola Marie Engel, Marco Celotto
The publication of Mainen and Sejnowski’s 1995 seminal paper strongly renewed interest in how spike timing contributes to the neural code. In the 3 decades since then, considerable experimental and theoretical research has investigated the timescales at which spike timing contributes to the neural code. Here we review…
Honghua Chen, Jing Wang, Jiaxin Gao, Hang Zhang + 1 more
Encoding time intervals in complex sound faces dual challenges: it must be precise and cover a broad dynamic range. In speech, for example, a ten millisecond lengthening of a syllable can signal stress or phrasal boundaries, yet the syllable duration distribution is long tailed beyond 500 ms and has variable statistics…
Toktam Samiei, Hafiz Fareed Ahmed, Edward Zagha, Erfan Nozari
Despite over a century of research into the neural code, the fundamental principles by which the brain encodes sensory information remain debated. In this study we provide converging evidence for the presence of a dynamic, fast-switching integration of rate and temporal coding in the thalamus, primary visual cortex…
Johanni Brea, Alireza Modirshanechi, Georgios Iatropoulos, Wulfram Gerstner + 1 more
Humans and animals can remember how long ago specific events happened. Little is known about the neural mechanisms that enable remembering the “when” of memories stored for long durations in the episodic memory system - in contrast to interval-timing on the order of seconds and minutes. Based on a systematic…
Haowen Hou, Zhen Huang, Zheming Liang, Qingyi Si + 7 more
Video is temporally redundant: adjacent frames usually share most objects, background, and layout. Yet existing video multimodal large language models (video MLLMs) usually encode each sampled frame as an independent RGB image, causing visual tokens to repeat content already present in earlier frames. This suggests a…
Bingde Hu, Enhao Pan, Wanjing Zhou, Yang Gao + 2 more
Spatiotemporal vector retrieval has emerged as a critical paradigm in modern information retrieval, enabling efficient access to massive, heterogeneous data that evolve over both time and space. However, existing spatiotemporal retrieval methods are often extensions of conventional vector search systems that rely on…
Hyeyoung Shin
Perception is a process of inference, whereby incoming sensory evidence is interpreted based on prior expectations about the sensory world. Thus, the neural code of perception should be evaluated based on how optimally it computes perceptual inference. However, the neural code of perception has conventionally been…
Authors not listed
Accurate prediction of chemical reaction yields remains essential for accelerating synthesis optimization, yet current machine learning models face critical limitations in capturing temporal dynamics, providing calibrated uncertainty estimates, and explicitly modeling reactant-to-product transformations. Here we…
Federico Szmidt, Camilo J. Mininni
Place and time cells are widely thought to provide complementary representations of spatial location and elapsed time in the hippocampus. Recent experiments reported CA1 neurons whose place and time fields shift systematically with running speed, suggesting that representations of space and time are integrated and…
Tuan-Luc Huynh, Weiqing Wang, Trung Le, Thuy-Trang Vu + 3 more
Retrievers are a key bottleneck in Temporal Retrieval-Augmented Generation (RAG) systems: failing to retrieve temporally relevant context can degrade downstream generation, regardless of LLM reasoning. We propose Temporal-aware Matryoshka Representation Learning (TMRL), an efficient method that equips retrievers with…
Hongjiang Chen, Pengfei Jiao, Ming Du, Xuan Guo + 3 more
The growing interest in Temporal Graph Neural Networks (TGNNs) stems from their ability to model complex dynamics and deliver superior performance. However, TGNNs encounter fundamental challenges in capturing long-term dependencies and identifying periodic patterns. To address these limitations, we propose TGFormer, a…
Peter Zsoldos
While video compression algorithms effectively reduce bitrate, aggressive quantization often compromises temporal coherence, introducing artifacts such as flicker, motion inconsistency, and unstable textures. Although spatial quality degradation is well-documented, the relationship between compression intensity and…
Xihua Sheng, Chang Wen Chen
Neural video coding has advanced rapidly, achieving competitive compression performance while also enabling real-time coding speed. Yet, existing codecs exhibit severe rigidity when deployed in dynamic environments, failing to adapt to different video content, user requirements, and quality preferences. First, to meet…
Roberto Pellerito, Daniel Gehrig, Shintaro Shiba, Davide Scaramuzza
Event cameras capture dynamic scenes with exceptional temporal fidelity by representing them as a continuous stream of microsecond resolution \textit{events}. Each individual event, however, only carries minimal semantic value, merely signaling a localized brightness change. To derive meaningful signals, downstream…
Authors not listed
We report a new workflow to model time-resolved transient absorption spectra, based on propagating nonadiabatic dynamics with ab initio multiple spawning. By explicitly including a laser field in the molecular Hamiltonian, we are able to model both the effect of a pump pulse in depopulating the ground state and a…
Authors not listed
Localized detection of hydrogen permeation in steel membranes is crucial for practical applications but remains challenging. We present a reflective microscopy (RM) approach combined with machine learning (ML)-driven image analysis to address this issue. Hydrogen permeation in press-hardened steel alters the…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…