20 papers · ranked by Valyu relevance
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…
Sara Zomorodi, Beate Knauer, Yacine Brahimi, Antonio Reboreda + 2 more
The ability to encode and maintain temporal relationships is crucial for learning, predicting, and forming episodic memories. While hippocampal time cells and entorhinal temporal context cells are well-established in vivo, it remains unclear whether single neurons can sustain representations of elapsed time over…
Huaxu He
Handling static images that lack inherent temporal dynamics remains a fundamental challenge for spiking neural networks (SNNs). In directly trained SNNs, static inputs are typically repeated across time steps, causing the temporal dimension to collapse into a rate like representation and preventing meaningful temporal…
Joy Bose
The Thousand Brains Theory (TBT) and its open-source Monty framework model object recognition through sensorimotor inference -- identifying objects by actively moving a sensor across their surface and building evidence contact by contact. The current implementation encodes each contact as a dense floating-point vector.…
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…
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…
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…
Phung, Huu-Tai, Gao, Zong-Lin + 12 more
This work, termed MH-LVC, presents a multi-hypothesis temporal prediction scheme that employs long- and shortterm reference frames in a conditional residual video coding framework. Recent temporal context mining approaches to conditional video coding offer superior coding performance. However, the need to store and…
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…
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…
Jingyi Wang, Joanne E. Stasiak, Neil M. Dundon, Elizabeth J. Rizor + 4 more
Growing evidence suggests that emotion shapes temporal aspects of memory—such as remembering when an event occurred—yet the neural bases of these effects remain unclear. Prior work indicates that temporal-context representations in memory are supported by the function of medial temporal lobe (MTL) and prefrontal…
Julian Ng-Kee-Kwong, Mufeng Tang, Thomas Akam, Rafal Bogacz
The ability to extract and exploit temporal structure across diverse tasks is central to human cognition. Neuroscientists have typically relied on recurrent neural networks (RNNs) trained with backpropagation through time (BPTT) when modelling neural and behavioural processes such as decision-making and motor control.…
Melissa Lober, Younes Bouhadjar, Markus Diesmann, Tom Tetzlaff
Processing sequential inputs is a fundamental brain function, underlying tasks such as sensory perception, language, and motor control. A challenge in sequence processing is to represent not only the order of events, but also their precise timing. While existing computational models can learn sequential structure, many…
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…
Janet M. Baker, Peter Cariani
Waves are fundamental. In our view, waves in the brain may constitute and drive organized neural activity patterns on individual neural and population levels. Their interactions follow basic physical principles. Taking a comprehensive, temporal and spatiotemporal perspective, we endeavor to explain multiple brain…
Esteban Félez Martínez, Filippo Costa, Debora Ledergerber, Lukas Imbach + 2 more
Composing individual memory traces into unified representations is fundamental to encoding of structured relationships and flexible cognition. A central debate in neuroscience concerns the neural mechanisms of these compositions: are these compositions encoded through mixed selectivity, where the same neurons…
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…
Authors not listed
We present a chemical framework in which adaptive organization is achieved by tuning a gated quantum resonator (adaptive genomic resonator) {driven quantum oscillator} across a driven, dissipative reaction manifold (fitness landscape) {Hamiltonian potential surface}. In this view, catalytic elements set gain and phase…