Biology subjects

St-Laurent, M.

Publications and source records attributed to St-Laurent, M..

5 recordsLinked to original sources

bioRxiv2026

Brain states recur across diverse narrative contexts during longitudinal viewing

What does the brain do during the continuous, varied experience of watching a story unfold? One account holds that the brain traverses a finite repertoire of recurring states, but whether that repertoire is a stable property of the individual or is reshaped by each new experience has not been tested across diverse naturalistic content within the same person. We characterized the dynamic brain-state repertoire in six individuals who watched the television series Friends across its six seasons during fMRI (up to [~]146 episodes, [~]54 hours per person). For each individual we fit a sticky hierarchical Dirichlet process hidden Markov model across all episodes, discovering brain states (recurring whole-brain activity patterns with characteristic coupling) without pre-specifying their number. Each individuals brain visited roughly forty-five states arrayed along a continuous recurrence gradient, from states active in nearly every episode to episode-specific ones, with no sharp division between them. The repertoire was heterogeneous in why its states recurred: a minority locked to scan-run structure, the majority remaining eligible for content. Transitions were organized by the functional-connectivity similarity between states (per-individual Spearman {rho} = 0.33-0.55) and, in most individuals, respected resting-state network boundaries. Episode content was associated with which states the brain occupied moment to moment. The recurrence ordering discovered in Friends transferred to state occupancy during other social-narrative films (five of six individuals) and attenuated as stimuli departed from that class, weakening for visual-only reading and audio-only listening. Across diverse narrative experience, the dynamic repertoire is a property of the individual: content varies which states are visited and when, not which states exist.

neuroscience↗

bioRxiv2025

Training neural networks from scratch in a videogame leads to brittle brain encoding

Recent brain-encoding studies using videogame tasks suggest that the training objective of an artificial neural network plays a central role in how well the networks representations align with brain activity. This study investigates the alignment of artificial neural network activations with brain activity elicited by a video game task using models trained from scratch in controlled settings. We specifically compared three model training objectives: reinforcement learning, imitation learning, and a vision task, while accounting for other potential factors which may impact performance such as training data and model architecture. We tested models on brain encoding, i.e. their ability to predict functional magnetic resonance imaging (fMRI) signals acquired while human subjects played different levels of the video game Super Mario Bros. When tested on new playthroughs from the game levels seen at training, the reinforcement learning objective had a small but significant advantage in brain encoding, followed by the imitation learning and vision models. We hypothesized that brain-aligned representations would emerge only in task-competent models, and that the specific brain regions well encoded by a model would depend on the nature of the task it was trained on. While brain encoding did improve during model training, even an untrained model with matching architecture approached the performance of the best models. Contrary to our hypotheses, no model layers or specific training objectives aligned preferentially with specific brain areas. Large performance gaps also persisted in fully trained models across game levels, both those seen during training and entirely novel ones. Overall, even though reinforcement learning presented a small advantage to train brain encoding models for videogame data, all tested brain encoding models exhibited brittle performance with limited generalization both within- and out-of-distribution. Overall, our results suggest that training small artificial models from scratch is not sufficiently reliable, and that incorporating pretrained models such as foundation vision-action models may ultimately be necessary to support robust inferences about brain representations.

neuroscience↗

bioRxiv2021

Neural Correlates of Reactivation and Vividness Reveal Separable Contributions to Objective and Subjective Measures of Episodic Memory

Episodic recollections vary in fidelity, sharpness, and strength--qualities that can be examined using both introspective judgements of mental states and objective measures of brain activity. Subjective and objective measures are both valid ways of "reading out" the content of someones internal mnemonic states, each with different strengths and weaknesses. St-Laurent and colleagues (2015) investigated the neural correlates of memory vividness ratings and neural reactivation during memory recall and found considerable overlap, suggesting common neural basis underlying these different markers of successful recollection. Here we extended this work with a much more extensive examination in which we used meta-analytic methods to pool four neuroimaging datasets in order to compare and contrast the neural substrates of neural reactivation and vividness judgements. While reactivation and vividness judgements correlated positively with one another and were associated with common univariate activity in the dorsal attention network and anterior hippocampus, some differences were also observed. Vividness judgments were tied to stronger activation in the striatum and dorsal attention network, together with suppression of default mode network nodes, and we also observed a trend for reactivation to be more closely associated with early visual cortex activity. A mediation analysis found support for the hypothesis that neural reactivation is necessary for vivid recollection, with activity in the anterior hippocampus associated with greater reactivation. Our results suggest that neural reactivation and vividness judgements reflect common recollective processing but differ in the extent to which they engage effortful, attentional processing. Additionally, the similarity between reactivation and vividness appears to arise, partly, through hippocampal processing during recollection.

neuroscience↗

bioRxiv2018

Changes in patterns of neural activity underlie a time-dependent transformation of memory in rats and humans

The dynamic process of memory consolidation involves a reorganization of brain regions that support a memory trace over time, but exactly how the network reorganizes as the memory changes remains unclear. We present novel converging evidence from studies of animals (rats) and humans for the time-dependent reorganization and transformation of different types of memory as measured both by behavior and brain activation. We find that context-specific memories in rats, and naturalistic episodic memories in humans, lose precision over time and activity in the hippocampus decreases. If, however, the retrieved memories retain contextual or perceptual detail, the hippocampus is engaged similarly at recent and remote timepoints. As the interval between the timepoint increases, the medial prefrontal cortex is engaged increasingly during memory retrieval, regardless of the context or the amount of retrieved detail. Moreover, these hippocampal-frontal shifts are accompanied by corresponding changes in a network of cortical structures mediating perceptually-detailed as well as less precise, schematic memories. These findings provide cross-species evidence for the crucial interplay between hippocampus and neocortex that reflects changes in memory representation over time and underlies systems consolidation.

neuroscience↗

bioRxiv2017

Eye-Movement Reinstatement and Neural Reactivation: Testing the Hebbian Theory of Mental Imagery

Half a century ago, Donald Hebb posited that mental imagery is a constructive process that emulates perception. Specifically, Hebb claimed that visual imagery results from the reactivation of neural activity associated with viewing images. He also argued that neural reactivation and imagery benefit from the re-enactment of eye movement patterns that first occurred at viewing (fixation reinstatement). To investigate these claims, we applied multivariate pattern analyses to functional MRI (fMRI) and eye-tracking data collected while healthy human participants repeatedly viewed and visualized complex images. We observed that the specificity of neural reactivation correlated positively with vivid imagery and with memory for stimulus image details. Moreover, neural reactivation correlated positively with fixation reinstatement, meaning that image-specific eye movements accompanied image-specific patterns of brain activity during visualization. These findings support the conception of mental imagery as a simulation of perception, and provide evidence of the supportive role of eye-movement in neural reactivation.

neuroscience↗