24 papers · ranked by Valyu relevance
Eduardo Camina, Francisco Güell
This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot…
Ji-Woo Seok, Chaejoon Cheong
Background The hippocampus reportedly plays a crucial role in memory. However, examining individual human hippocampal-subfield function remains challenging because of their small sizes and convoluted structures. Here, we identified hippocampal subregions involved in memory types (implicit and explicit memory) and…
Marcel R. Schreiner, Wilfried Kunde
In four experiments, we investigated the contribution of explicit and implicit memory processes to the learning of action-effect relations, focusing on early learning with few repetitions of action-effect episodes. We further provide a new and now validated methodological approach to directly distinguish between…
Friederike Contier, Melissa Höger, Milena Rabovsky
The P600 ERP component is elicited by a wide range of anomalies and ambiguities during sentence comprehension and remains important for neurocognitive models of language processing. It has been proposed that the P600 is a more domain-general component, signaling phasic norepinephrine release from the locus coeruleus in…
KA Zhivago, Sneha Shashidhara, Ranjini Garani, Simran Purokayastha + 3 more
A decline in declarative or explicit memory has been extensively characterized in cognitive ageing and is a hallmark of cognitive impairments. However, whether and how implicit perceptual memory varies with ageing or cognitive impairment is unclear. Here, we compared implicit perceptual memory and explicit memory…
Jason R. Finley
What is human memory? Evidence from cognitive psychology and neuroscience supports the view that human memory is composed of multiple subsystems. The influential “modal model” of the late 1960s proposed a sensory register, short-term store, and long-term store. Refinements and expansions to this taxonomy followed…
Katja Kleespies, Philipp C. Paulus, Hao Zhu, Florian Pargent + 6 more
Sleep supports stabilization of explicit, declarative memory and benefits implicit statistical learning. In addition, sleep may change the quality of memory representations. Explicit and implicit learning systems, usually linked to hippocampus and striatum, can compete during learning, but whether they continue to…
Katja Kleespies, Philipp C. Paulus, Hao Zhu, Florian Pargent + 6 more
Sleep supports stabilization of explicit, declarative memory and benefits implicit, procedural memory. In addition, sleep may change the quality of memory representations. Explicit and implicit learning systems, usually linked to the hippocampus and striatum, can compete during learning, but whether they continue to…
Emma V. Ward, Christopher J. Berry, David R. Shanks, Petter L. Moller + 1 more
'Petter L. Moller' 'Enida Czsiser'] Explicit memory declines with age, but age effects on implicit memory are debated. This issue is important because if implicit memory is age invariant, it may support effective interventions in individuals experiencing memory decline. In this study, we overcame several methodological…
Yuyang Hu, Shichun Liu, Yanwei Yue, Guibin Zhang + 50 more
Yuyang Hu† , Shichun Liu† , Yanwei Yue† , Guibin Zhang† ò , Boyang Liu, Fangyi Zhu, Jiahang Lin, Honglin Guo, Shihan Dou, Zhiheng Xi, Senjie Jin, Jiejun Tan, Yanbin Yin, Jiongnan Liu, Zeyu Zhang, Zhongxiang Sun, Yutao Zhu, Hao Sun, Boci Peng, Zhenrong Cheng, Xuanbo Fan, Jiaxin Guo, Xinlei Yu, Zhenhong Zhou, Zewen Hu…
Thomas Geyer, Pardis Rostami, Lisa Sogerer, Bernhard Schlagbauer + 1 more
'Hermann J. Müller'] Visual search is facilitated when observers encounter targets in repeated display arrangements. This ‘contextual-cueing’ (CC) effect is attributed to incidental learning of spatial distractor-target relations. Prior work has typically used only one recognition measure (administered after the search…
Weinan Sun, Madhu Advani, Nelson Spruston, Andrew Saxe + 1 more
Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize a safe route to a water source and generalize to features that allow them to find new water sources, without expecting new paths to exactly resemble previous ones. Memory…
Emily Cordeiro, Daniela Herrera Chaves, Nima Talei, Iván Castro + 6 more
Statistical learning (SL) has been proposed to depend on the hippocampus, but traditional neuropsychological theories of long-term memory posit that the hippocampus is only necessary for explicit memory processes, not implicit memory processes. To reconcile these two accounts, we exposed 27 temporal lobe epilepsy (TLE)…
Wei Zhou, Xuanhe Zhou, Shaokun Han, Hongming Xu + 4 more
Memory for large language model (LLM) agents has rapidly evolved from simple retrieval-augmented mechanisms into a data management system that supports persistent information storage, retrieval, update, consolidation, and dynamic lifecycle governance throughout agent execution. Despite this evolution, existing…
L. Bonetti, E. Risgaard Olsen, F. Carlomagno, E. Serra + 8 more
Memory is a crucial cognitive process involving several subsystems: sensory memory (SM), short-term memory (STM), working memory (WM), and long-term memory (LTM). While each has been extensively studied, the interaction between WM and LTM, particularly in relation to predicting temporal sequences, remains largely…
Authors not listed
Computational toxicology plays a pivotal role in modern drug discovery and environmental risk assessment; however, the reliability of predictive models on unseen chemical scaffolds remains a critical bottleneck. Deep learning architectures, despite their prevalence, are susceptible to ’silent failures’—yielding…
Zidi Xiong, Yuping Lin, Wenya Xie, Pengfei He + 3 more
'Himabindu Lakkaraju' 'Zhen Xiang'] Memory is a critical component in large language model (LLM)-based agents, enabling them to store and retrieve past executions to improve task performance over time. In this paper, we conduct an empirical study on how memory management choices impact the LLM agents' behavior…
Sangjun Park, JinYeong Bak
Making neural networks remember over the long term has been a longstanding issue. Although several external memory techniques have been introduced, most focus on retaining recent information in the short term. Regardless of its importance, information tends to be fatefully forgotten over time. We present Memoria, a…
Jeff Guo, Philippe Schwaller
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy desired objectives under minimal oracle evaluations (computational prediction or wet-lab experiment). This problem becomes more apparent when using oracles that can provide increased…
Authors not listed
This paper develops a comprehensive theoretical framework for designing quantum memory systems with enhanced resilience to thermal decoherence through engineered lattice geometries and protective structures. We formulate a unified mathematical description connecting material properties, geometric configurations, and…
Jeff Guo, Philippe Schwaller
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy desired objectives under minimal oracle evaluations (computational prediction or wet-lab experiment). This problem becomes more apparent when using oracles that can provide increased…
Wilma Bainbridge
When we experience an event, it feels like our previous experiences, our interpretations of that event (e.g., aesthetics, emotions), and our current state will determine how we will remember it. However, recent work has revealed a strong sway of the visual world itself in influencing what we remember and forget.…
Authors not listed
Large Language Models (LLMs) based on transformer architectures excel at internet-scale tasks. However, real-world scientific scenarios—such as synthetic chemistry laboratories and autonomous experimental setups—typically involve incremental data generation in batches as new chemical reactions are conducted, unlike…
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…