Replay in human visual cortex is linked to the formation of successor representations and independent of consciousness

Wittkuhn, Lennart; Krippner, Lena M.

doi:10.1101/2022.02.02.478787

Cited by 10 publications

(11 citation statements)

References 160 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Taken together, these studies suggest that hippocampal subfields may contribute to both associative and episodic learning through complementary circuitry, functions, and interactions. Moreover, recent work connects the statistical learning of successor representation to on-task replay (Wittkuhn, Krippner, and Schuck 2022), providing further credence to the importance of the predictive structure of memory in our understanding of behavioral and neural phenomena surrounding memory, replay, and planning.…”

Section: Predictive Representations and Complementary Learning Systemsmentioning

confidence: 92%

Learning Structures: Predictive Representations, Replay, and Generalization

Momennejad¹

2020

Preprint

View full text Add to dashboard Cite

Memory and planning rely on learning the structure of relationships among experiences. Compact representations of these structures guide flexible behavior in humans and animals. A century after ‘latent learning’ experiments summarized by Tolman, the larger puzzle of cognitive maps remains elusive: how does the brain learn and generalize relational structures? This review focuses on a reinforcement learning (RL) approach to learning compact representations of the structure of states. We review evidence showing that capturing structures as predictive representations updated via replay offers a neurally plausible account of human behavior and the neural representations of predictive cognitive maps. We highlight multi-scale successor representations, prioritized replay, and policy-dependence. These advances call for new directions in studying the entanglement of learning and memory with prediction and planning.

show abstract

Section: Predictive Representations and Complementary Learning Systemsmentioning

confidence: 92%

Learning Structures: Predictive Representations, Replay, and Generalization

Momennejad¹

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The SR introduces two parameters to estimate: The discount factor γ and the learning rate θ . For all our model fitting, we kept the learning rate θ fixed at 0.1 (44,97).…”

Section: Methodsmentioning

confidence: 99%

The successor representation subserves hierarchical abstraction for goal-directed behavior

Wientjes

Holroyd

2023

Preprint

View full text Add to dashboard Cite

Humans have the ability to craft abstract, temporally extended and hierarchically organized plans. For instance, when considering how to make spaghetti for dinner, we typically concern ourselves with useful "subgoals" in the task, such as cutting onions, boiling pasta, and cooking a sauce, rather than particulars such as how many cuts to make to the onion, or exactly which muscles to contract. A core question is how such decomposition of a more abstract task into logical subtasks happens in the first place. Previous research has shown that humans are sensitive to a form of hierarchical statistical learning named "community structure". Community structure is a common feature of abstract tasks characterized by a logical ordering of subtasks. This structure can be captured by a model where humans learn predictions of upcoming events multiple steps into the future, discounting predictions of events further away in time. One such model is the "successor representation", which has been argued to be useful for hierarchical abstraction. As of yet, no study has convincingly shown that this hierarchical abstraction can be put to use for goal-directed behavior. Here, we investigate whether participants utilize learned community structure to craft hierarchically informed action plans for goal-directed behavior. Participants were asked to search for paintings in a virtual museum, where the paintings were grouped together in "wings" representing community structure in the museum. We find that participants' choices accord with the hierarchical structure of the museum and that their response times are best predicted by a successor representation. The degree to which the response times reflect the community structure of the museum correlates with several measures of performance, including the ability to craft temporally abstract action plans. These results suggest that successor representation learning subserves hierarchical abstractions relevant for goal-directed behavior.

show abstract

“…42 , primarily used with MEG 9,14,28,30,44,45 , and recently EEG 25 . The other is a regression method, as per Wittkuhn and Schuck 26 and used in fMRI studies 27 . Note this panel is for illustrative purpose alone.…”

Section: Spatiotemporal Dynamics Of Neural Replay During Mental Simul...mentioning

confidence: 99%

“…Human functional magnetic resonance imaging (fMRI) has been used to localize sequential neural replay to specific brain regions 22,26,27 . Wittkuhn and Schuck 26 , employed fMRI to index the sequence of predictive probabilities within a time repetition (TR), reporting sub-second activations of visual stimuli in the occipital-temporal cortex on-task.…”

Section: Introductionmentioning

confidence: 99%

Replay-triggered Brain-wide Activation in Humans

Huang,

Xiao,

et al. 2023

Preprint

View full text Add to dashboard Cite

The consolidation of discrete experiences into a coherent narrative shapes our cognitive map, providing a structured mental representation of our experiences. Neural replay, by fostering crucial hippocampal-cortical dialogue, is thought to be pivotal in this process. However, the brain-wide engagement coinciding with replay bursts remains largely unexplored. In this study, by employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of replay. We find that during mental simulation, the strength of on-task replay, as detected via EEG, correlates with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Intriguingly, increased replay strength also enhances the functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing cognitive map. Furthermore, during the post-learning resting state, we observed a positive association between increased task-related reactivation, hippocampal activity, and augmented connectivity to the entorhinal cortex. Our findings elucidate the neural mechanism of human replay in both time and space, providing novel insights into dynamics of replay and associated brain-wide activation.

show abstract

Replay in human visual cortex is linked to the formation of successor representations and independent of consciousness

Cited by 10 publications

References 160 publications

Learning Structures: Predictive Representations, Replay, and Generalization

Learning Structures: Predictive Representations, Replay, and Generalization

The successor representation subserves hierarchical abstraction for goal-directed behavior

Replay-triggered Brain-wide Activation in Humans

Contact Info

Product

Resources

About