Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. However, what remains unknown is which visual prop...

How do people preserve mental continuity when tasks are interrupted? One established pathway runs through the hippocampus, which stores snapshots of our mental context for later reinstatement. We prop...

A new recycling machine in a parking lot at Johns Hopkins Bayview Medical Center takes airy chunks of foam and churns them into dense plastic cubes that can be made into park benches, picture frames, ...

People are increasingly choosing to limit or reject the use of AI tools, according to a new report published today by the Digital Futures Institute at King’s College London and Responsible AI UK.

This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...

We are seeking a Research Assistant who will work jointly in the Isik and Bedny labs on projects involving neuroimaging (fMRI, EEG), behavioral testing, and computational approaches. The position is p...

Hippocampal neurons track positions of self, others, and gaze direction. However, it is unclear how their respective neural codes differ enough to avoid confusion while allowing for abstraction. We re...

Course materials for PSYC 51.17: Language Models from Scratch - Dartmouth College

When we investigate busy visual scenes, how do we estimate the number of objects that we see? Most work on number perception answers this question by focusing on properties of the to-be-estimated set...

Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differenc...

When people recall a movie, their eye movements and brain activity resemble those observed during the viewing. These behavioral and neural reactivations are linked through a common process, likely ref...

Humans can implicitly learn about multistep sequential relationships between events in the environment from their statistical co-occurrence. Theore...

The Learning & Behavior Change Lab at Rice University, directed by Dr. Sinclair

Music is a potent cue for recalling personal experiences, yet the neural basis of music-evoked memory remains elusive. We address this question by using the full-length film Eternal Sunshine of the Spotless Mind to examine how repeated musical themes reactivate previously encoded events in cortex and shape next-day recall. Participants in an fMRI study viewed either the original film (with repeated musical themes) or a no-music version. By comparing neural activity patterns between these groups, we found that music-evoked reactivation of neural patterns linked to earlier scenes in the default mode network was associated with improved subsequent recall. This relationship was specific to the music condition and persisted when we controlled for a proxy measure of initial encoding strength (spatial intersubject correlation), suggesting that music-evoked reactivation may play a role in making event memories stick that is distinct from what happens at initial encoding. ### Competing Interest Statement The authors have declared no competing interest. National Institutes of Health, https://ror.org/01cwqze88, F99 NS118740, R01 MH112357

Fewer papers are reporting findings on the border of statistical significance, a potential marker of dodgy research practices

The capacity to prevent unwanted thoughts is important for cognitive function and mental health. Anderson et al. describe insights into the neural mechanisms of the inhibitory control of thought that ...

Madar et al. report that behavioral timescale synaptic plasticity (BTSP), not spike-timing-dependent plasticity, explains heterogeneous place fields shifting in the hippocampus. The probability of BTS...

A general reinforcement-learning algorithm, called Dreamer, outperforms specialized expert algorithms across diverse tasks by learning a model of the environment and improving its behaviour by imagining future scenarios.

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Koster et al introduce a deep reinforcement learning (RL) mechanism designed to manage common-pool resources successfully encourages sustainable cooperation among human participants by dynamically adj...

Prediction of future inputs is a key computational task for the brain. Here, the authors proposed a predictive learning rule in neurons that leads to anticipation and recall of inputs, and that reprod...