Memory of a sequence of distinct events requires encoding the temporal order as well as the intervals that separates these events. In this study, using order-place association task where the animal learns to associate the location of the food pellet to the order of entry into the event arena, we probe the nature of temporal order memory in mice. In our task, individual trials become distinct events, as the animal is trained to form a unique association between entry order and a correct location. The inter-trial intervals (> 30 min) are chosen deliberately to minimize the inputs from working memory. We develop this paradigm initially using four order-place associates and later extend it to five paired associates. Our results show that animals not only acquire these explicit (entry order to place) associations but also higher order associations that can only be inferred implicitly (temporal relation between the events) from the temporal order of these events. As an indicator of such higher order learning during the probe trial, the mice exhibit predominantly prospective errors that decline proportionally with temporal distance. On the other hand, prior to acquiring the sequence, the retrospective errors are dominant. In addition, we also tested the nature of such acquisitions when temporal order CS is presented along with flavored pellet as a compound stimulus comprising of order and flavor both simultaneously being paired with location. Results from these experiments indicate that the animal learns both order-place and flavor-place associations. Comparing with pure order-place training, we find that the additional flavor stimulus in a compound training paradigm did not interfere with the ability of the animals to acquire the order-place associations. When tested remotely, pure order-place associations could be retrieved only after a reminder training. Further higher order associations representing the temporal relationship between the events is markedly absent in the remote time.
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http://dx.doi.org/10.1007/s00221-021-06282-7 | DOI Listing |
Comput Methods Programs Biomed
December 2024
Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Electronic address:
Background And Objective: Cancer's complex and multifaceted nature makes it challenging to identify unique molecular and pathophysiological signatures, thereby hindering the development of effective therapies. This paper presents a novel fractal-fractional cancer model to study the complex interplay among stem cells, effectors cells, and tumor cells in the presence and absence of chemotherapy. The cancer model with effective treatment through chemotherapy drugs is considered and discussed in detail.
View Article and Find Full Text PDFSci Rep
December 2024
College of Sports, Beihua University, Jilin, 132000, China.
In order to eliminate the impact of camera viewpoint factors and human skeleton differences on the action similarity evaluation and to address the issue of human action similarity evaluation under different viewpoints, a method based on deep metric learning is proposed in this article. The method trains an automatic encoder-decoder deep neural network model by means of a homemade synthetic dataset, which maps the 2D human skeletal key point sequence samples extracted from motion videos into three potential low-dimensional dense spaces. Action feature vectors independent of camera viewpoint and human skeleton structure are extracted in the low-dimensional dense spaces, and motion similarity metrics are performed based on these features, thereby effectively eliminating the effects of camera viewpoint and human skeleton size differences on motion similarity evaluation.
View Article and Find Full Text PDFNeural Netw
December 2024
Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom.
First spike timings are crucial for decision-making in spiking neural networks (SNNs). A recently introduced first-spike (FS) coding method demonstrates comparable accuracy to firing-rate (FR) coding in processing complex temporal information through supervised learning. However, its performance still falls behind advanced approaches.
View Article and Find Full Text PDFGeriatrics (Basel)
December 2024
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Background: Hand dexterity is affected by normal aging and neuroinflammatory processes in the brain. Understanding the relationship between hand dexterity and brain structure in neurotypical older adults may be informative about prodromal pathological processes, thus providing an opportunity for earlier diagnosis and intervention to improve functional outcomes.
Methods: this study investigates the associations between hand dexterity and brain measures in neurotypical older adults (≥65 years) using the Nine-Hole Peg Test (9HPT) and magnetic resonance imaging (MRI).
Neurosci Res
December 2024
Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands.
This study investigates the cognitive and neural mechanisms involved in the linearization of events during language production, focusing on the processing of temporal conjunctions "before" and "after." While natural language typically presents events in chronological order, non-chronological sequences, as required by "before" sentences, impose additional cognitive demands. Using an adapted network task, we recorded event-related potentials (ERPs) in 24 healthy German speaking participants to examine the brain activity associated with these demands.
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