28 papers · ranked by Valyu relevance
Giulia Cencetti, Federico Battiston, Bruno Lepri, Márton Karsai
Human social interactions in local settings can be experimentally detected by recording the physical proximity and orientation of people. Such interactions, approximating face-to-face communications, can be effectively represented as time varying social networks with links being unceasingly created and destroyed over…
Yohan J. John, Kayle S. Sawyer, Karthik Srinivasan, Eli J. Müller + 2 more
'Brandon R. Munn' 'James M. Shine'] Title: Abstract Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static…
Fernanda Dantas Bueno, Vanessa C. Morita, Raphael Y. de Camargo, Marcelo B. Reyes + 2 more
'Marcelo B. Reyes' 'Marcelo S. Caetano' 'André M. Cravo'] The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view…
Pednekar, Amrapali, Álvaro Garrido-Pérez, Yara Khaluf + 1 more
This study explores the interference in temporal processing within a dual-task paradigm from an artificial intelligence (AI) perspective. In this context, the dualtask setup is implemented as a simplified version of the Overcooked environment with two variations, single task (T) and dual task (T+N). Both variations…
Tony Lindeberg
This article presents an overview of a theory for performing temporal smoothing of temporal signals in such a way that: (i) temporally smoothed signals at coarser temporal scales are guaranteed to constitute simplifications of corresponding temporally smoothed signals at any finer temporal scale (including the original…
Jonathan Fromentin, Damien Eveillard, Olivier Roux
Background Modeling a dynamical biological system is often a difficult task since the a priori unknown parameters of such models are not always directly given by the experiments. Despite the lack of experimental quantitative knowledge, one can see a dynamical biological system as (i) the combined evolution tendencies…
Tomoya Maruyama, Jing Gong, Masahiro Takinoue
Bio-soft matter droplets formed via liquid-liquid phase separation (LLPS) of biopolymers have been found in living cells. Synthetic LLPS droplets have recently been employed in nanobiotechnology for artificial cell construction, molecular robotics, molecular computing, diagnosis, and therapeutics. Controlling the…
Seth W. Egger, Nhat M. Le, Mehrdad Jazayeri
Humans can rapidly and flexibly coordinate their movements with external stimuli. Theoretical considerations suggest that this flexibility can be understood in terms of how sensory responses reconfigure the neural circuits that control movements. However, because external stimuli can occur at unexpected times, it is…
Erin R. Bigus, Hyun-Woo Lee, John C. Bowler, Jiani Shi + 1 more
Episodic memory requires encoding the temporal structure of experience and relies on brain circuits in the medial temporal lobe, including the medial entorhinal cortex (MEC). Recent studies have identified MEC ’time cells’, which fire at specific moments during interval timing tasks, collectively tiling the entire…
Zafeirios Fountas, Alexey Zakharov
Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of the brain's cognitive underpinnings – that it is a Bayesian inference…
Rui Cao, Ian M. Bright, Marc W. Howard
In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings…
Louise C. Barne, João R. Sato, Raphael Y. de Camargo, Peter M. E. Claessens + 2 more
Humans’ and non-human animals’ ability to process time on the scale of milliseconds and seconds is essential for adaptive behaviour. A central question of how brains keep track of time is how specific temporal information across different sensory modalities is. In the present study, we show that encoding of temporal…
Timothy Muller, Anna C Nobre
Although the study of time has been central to physics and philosophy for millennia, questions of how time is represented in the brain and how this representation is related to time perception have only recently started to be addressed. Emerging evidence subtly yet profoundly challenges our intuitive notions of time…
Authors not listed
Drawing parallels between Deep Artificial Neural Networks (DNNs) and biological systems can aid in understanding complex biological mechanisms that are difficult to disentangle. Temporal processing, an extensively researched topic, is one such example that lacks a coherent understanding of its underlying mechanisms. In…
Midhula Chandran, Anna Thorwart
Ability to recall the timing of events is a crucial aspect of associative learning. Yet, traditional theories of associative learning have often overlooked the role of time in learning association and shaping the behavioral outcome. They address temporal learning as an independent and parallel process. Temporal Coding…
M. A. Elfouly, T. S. Amer
Movement disorders, like Parkinson’s disease, happen because of unusual patterns in the connections between the cortex and basal ganglia, often caused by timing issues in feedback pathways. This study uses a two-delay nonlinear dynamic model, based on the delayed the van der Pol oscillator, to examine how delays in the…
Tony Lindeberg
This article presents an overview of a theory for performing temporal smoothing on temporal signals in such a way that: (i) temporally smoothed signals at coarser temporal scales are guaranteed to constitute simplifications of corresponding temporally smoothed signals at any finer temporal scale (including the original…
Authors not listed
Atomistic simulations provide essential mechanistic insights into chemical processes, yet many important phenomena in chemistry and materials science occur on timescales that are inaccessible to molecular dynamics. Existing computational approaches force a choice between atomic resolution on relatively short timescales…
Michail Maniadakis, Panos Trahanias
The representation of the environment assumes the encoding of four basic dimensions in the brain, that is the 3D space and time. The vital role of time for cognition is a topic that recently attracted increasing research interest. Surprisingly, the scientific community investigating mind-time interactions has mainly…
Jane Kondev, Marc Kirschner, Hernan G. Garcia, Gabriel L. Salmon + 1 more
Many biological processes can be thought of as the result of an underlying dynamics in which the system repeatedly undergoes distinct and abortive trajectories with the dynamical process only ending when some specific process, purpose, structure or function is achieved. A classic example is the way in which…
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…
Gabriele Cimolino, François Rivest
Animals can quickly learn the timing of events with fixed intervals and their rate of acquisition does not depend on the length of the interval. In contrast, recurrent neural networks that use gradient based learning have difficulty predicting the timing of events that depend on stimulus that occurred long ago. We…
Matthew Bailey, Mark Wilson
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the applicability of a persistence diagram showing the existence of topological features (here rings in a 2D network) generated over time instead of space as a tool to analyse trajectories of biological networks. We show how the…
Tosif Ahamed, Antonio C. Costa, Greg J. Stephens
Animal behavior is often quantified through subjective, incomplete variables that may mask essential dynamics. Here, we develop a behavioral state space in which the full instantaneous state is smoothly unfolded as a combination of short-time posture dynamics. Our technique is tailored to multivariate observations and…
Marina Gorostiola González, Remco L. van den Broek, Thomas G.M. Braun, Magdalini Chatzopoulou + 4 more
Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive…
Authors not listed
Kinetic modeling is essential for predicting changes in food quality during processing and storage. This study evaluates the application of physics-informed neural networks (PINN) for food kinetic modeling, integrating kinetic insights into neural network frameworks. Based on three case studies, namely seed drying…
Simon Bennie, Kara Ranaghan, Helen Deeks, Heather Goldsmith + 3 more
The reemergence of virtual reality (VR) in the last few years has led to affordable commodity hardware that can offer new ways to teach, communicate and engage with difficult concepts, especially those which involve complicated 3D motion and spatial manipulation. In a higher education context, these immersive…
Fergal Byrne
Reverse engineering the brain is proving difficult, perhaps impossible. While many believe that this is just a matter of time and effort, a different approach might help. Here, we describe a very simple idea which explains the power of the brain as well as its structure, exploiting complex dynamics rather than…