23 papers · ranked by Valyu relevance
Guohua Yuan, Zhe Zhao, Xiaoxiang Dong, Xu-Wen Wang + 11 more
In the developing neocortex, a diverse array of neurons with defined types and abundances are systematically generated by a limited population of radial glial progenitors (RGPs) as they undergo successive fate changes. The molecular regulation behind this intricate temporal patterning remains elusive. We undertook…
Jimena Garcia-Guillen, Mahla Ahmadi, Theophilus Frimpong, Iris Seaman + 6 more
How spatial patterns arise during embryonic development is classically explained by the French Flag model, in which cells acquire positional identities by interpreting morphogen concentration thresholds. However, in many developmental systems, spatial patterns instead emerge progressively through temporal programs of…
Konstantina Filippopoulou, Elisavet Iliopoulou, Claire Julliot de La Morandière, Christy Lee + 4 more
The nervous system consists of a wide variety of neuronal cell types arranged into complex circuits that support a broad range of behaviors. Patterning of neural stem cells in time through the sequential expression of series of temporal transcription factors is a key contributor to the generation of neuronal diversity.…
Van Ho-Long, Nguyen Ho, Anh-Vu Dinh-Duc, Ha Manh Tran + 4 more
The explosive growth of IoT-enabled sensors is producing enormous amounts of time series data across many domains, offering valuable opportunities to extract insights through temporal pattern mining. Among these patterns, an important class exhibits periodic occurrences, referred to as seasonal temporal patterns…
Yijun Ma, Zehong Wang, Weixiang Sun, Yanfang Ye
Temporal graph learning is pivotal for deciphering dynamic systems, where the core challenge lies in explicitly modeling the underlying evolving patterns that govern network transformation. However, prevailing methods are predominantly task-centric and rely on restrictive assumptions such as short-term dependency…
Qiaorong S. Yu, Zhaoze Wang, Vijay Balasubramanian
Hippocampal place and time cells encode spatial and temporal aspects of experience. Both have the same neural substrate, but have been modeled as having different functions and mechanistic origins, place cells as continuous attractors, and time cells as leaky integrators. Here, we show that both types emerge from two…
Peter Cariani, Janet M. Baker
This paper focuses on possible time-domain neurocomputational mechanisms for short-term anticipatory processes. Here we present a simple, signal processing functional model of how short-term rhythmic pattern expectancies could be computed on the fly using recurrent neural timing nets (RTNs). The model is inspired by…
Wu Yonggang
| 1. Introduction4 | | |----------------------------------------------------------------------|--| | 2. Module 1: Visual processing system (VPS) module4 | | | 2.1 Complementary plasticity hypothesis (CPH)5 | | | 2.2 Training and tuning6 | | | 2.3 Specificity and invariance7 | | | 2.4 Invariance through excitatory…
Janelle D. Healy, Satvinder S. Dhaliwal, Christina M. Pollard, Amelia J. Harray + 4 more
Background/Objective: Temporal eating patterns and ultra-processed food (UPF) consumption have independently been associated with obesity and non-communicable diseases. Little is known about the temporal patterns of UPF consumption, as data is challenging to collect. Temporal data can be extracted from mobile food…
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…
Jayakrishnan Madathil, Kitty Meeks, Marc Roth
We study the structural expressivity and the parameterised complexity of counting homomorphisms from small temporal patterns to large temporal graphs. Here, a temporal pattern $P$ consists of a graph together with a partial order on its edges, and a homomorphism from $P$ to a temporal graph must not only preserve…
Angus F. Chapman, Rachel N. Denison, Christopher Pack
How does the visual system process dynamic inputs? Perception and neural activity are shaped by the spatial and temporal context of sensory input, which has been modeled by divisive normalization over space or time. However, theoretical work has largely treated normalization separately within these dimensions and has…
Priya Chakraborty, Subrata Dey, Ranu Kundu, Malay Banerjee + 1 more
Exploring the emergence of spatio-temporal patterns due to nonlinearities in gene expression is a relatively new development. In this work, we explore the effect of resource constraint on gene regulatory motif from both equilibrium and spatio-temporal standpoint, taking into consideration the degradation class of…
Vincenzo Rizzuto, Oren Kadosh, Roberto Montanari, Yoram Bonneh
Introduction Perception operates as rhythmically structured sampling in which temporal predictions determine when incoming signals are weighted. Fixational eye movements carry opposing consequences, enhancing acuity yet inducing brief peri-saccadic suppression, suggesting that their timing is paced by expected, salient…
Lilan Peng, Yandi Liu, Qingren Yao, Chongshou Li + 1 more
Spatio-Temporal forecasting is crucial in diverse fields, such as transportation, climate, and energy. Urban spatio-temporal data exhibits temporal mirage: similar short-window inputs have divergent future trends, and vice versa. Existing spatio-temporal graph neural networks (STGNNs) cannot effectively identify such…
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…
Ma, Xiangkai, Zhang, Han + 4 more
Large Multimodal Models (LMMs) have achieved remarkable progress in aligning and generating content across text and image modalities. However, the potential of using non-visual, continuous sequential, as a conditioning signal for high-fidelity image generation remains largely unexplored. Furthermore, existing methods…
Xingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu + 3 more
Large Language Models (LLMs) have achieved impressive reasoning abilities, but struggle with temporal understanding, especially when questions involve multiple entities, compound operators, and evolving event sequences. Temporal Knowledge Graphs (TKGs), which capture vast amounts of temporal facts in a structured…
Sebastian Klavinskis-Whiting, Andrew J. King, Nicol S. Harper, Tim Christian Kietzmann
A major goal of neuroscience is to identify general principles that can explain the diverse structures and functions of the brain. The principle of temporal prediction provides one approach, arguing that the sensory brain is optimized to represent stimulus features that efficiently predict the immediate future input.…
Nathan Thomas Han, Michael B. Steinborn, Liyu Cao
The complication clock, originally introduced by Wilhelm Wundt, remains a pivotal method in experimental psychology for probing the subjective timing of events. By localising the position of a moving pointer, one can objectively measure when someone perceives an event to have occurred. The method therefore maps…
Authors not listed
The capacity to pattern biomolecules within microfluidic devices expands the scope of microfluidic technologies. In such patterned systems, surface-bound components remained localized, while the microfluidic network supplies reagents and removes waste products. This approach has enabled continuous protein expression…
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…
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…