Biology subjects

Kenneth A Norman

Publications and source records attributed to Kenneth A Norman.

6 recordsLinked to original sources

bioRxiv2016

Decoding the contents of working memory tracks strategy and performance in prospective remembering

Theories of prospective memory (PM) posit that it can be subserved either by working memory (WM) or episodic memory (EM). Testing and refining these multiprocess theories of PM requires a way of tracking participants reliance on WM versus EM. Here we use multi-voxel pattern analysis (MVPA) to derive a trial-by-trial measure of WM use in prospective memory. We manipulated strategy demands by varying the degree of proactive interference (which impairs EM) and the memory load required to perform the secondary task (which impairs WM). For the condition in which participants were pushed to rely more on WM, our MVPA measures showed 1) greater WM use and 2) a trial-by-trial correlation between WM use and PM behavior. Finally, we also showed that MVPA measures of WM use are not redundant with other behavioral measures: in the condition in which participants were pushed more to rely on WM, using neural and behavioral measures together led to better prediction of PM accuracy than either measure on its own.

Neuroscience↗

bioRxiv2016

Complementary learning systems within the hippocampus: A neural network modeling approach to reconciling episodic memory with statistical learning

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway -- the pathway connecting entorhinal cortex directly to region CA1 -- was able to support statistical learning, while the trisynaptic pathway -- connecting entorhinal cortex to CA1 through dentate gyrus and CA3 -- learned only individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.

Neuroscience↗

bioRxiv2016

Neural Pattern Change During Encoding of a Narrative Predicts Retrospective Duration Estimates

What mechanisms support our ability to estimate durations on the order of minutes? Behavioral studies in humans have shown that changes in contextual features lead to overestimation of past durations. Based on evidence that the medial temporal lobes and prefrontal cortex represent contextual features, we related the degree of fMRI pattern change in these regions with peoples subsequent duration estimates. After listening to a radio story in the scanner, participants were asked how much time had elapsed between pairs of clips from the story. Our ROI analysis found that the neural pattern distance between two clips at encoding was correlated with duration estimates in the right entorhinal cortex and right pars orbitalis. Moreover, a whole-brain searchlight analysis revealed a cluster spanning the right anterior temporal lobe. Our findings provide convergent support for the hypothesis that retrospective time judgments are driven by \"drift\" in contextual representations supported by these regions.

Neuroscience↗

bioRxiv2016

The Computational Nature of Memory Modification

Retrieving a memory can modify its influence on subsequent behavior. Whether this phenomenon arises from modification of the contents of the memory trace or its accessibility is a matter of considerable debate. We develop a computational theory that incorporates both mechanisms. Modification of the contents of the memory trace occurs through classical associative learning, but which memory trace is accessed (and thus made eligible for modification) depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature, including dependence on the strength and age of memories, the interval between memory retrieval and extinction, and prediction errors following retrieval.

Animal Behavior and Cognition↗

bioRxiv2016

Shared experience, shared memory: a common structure for brain activity during naturalistic recall

Our daily lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? In this study, participants viewed a fifty-minute audio-visual movie, then verbally described the events while undergoing functional MRI. These descriptions were completely unguided and highly detailed, lasting for up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated (movie-vs.-recall correlation) in default network, medial temporal, and high-level visual areas; moreover, individual event patterns were highly discriminable and similar between people during recollection (recall-vs.-recall similarity), suggesting the existence of spatially organized memory representations. In posterior medial cortex, medial prefrontal cortex, and angular gyrus, activity patterns during recall were more similar between people than to patterns elicited by the movie, indicating systematic reshaping of percept into memory across individuals. These results reveal striking similarity in how neural activity underlying real-life memories is organized and transformed in the brains of different people as they speak spontaneously about past events.

Neuroscience↗

bioRxiv2015

Putting value in context: A role for context memory in decisions for reward.

How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free Reinforcement Learning (RL); however, samples can vary from trial to trial, causing decisions to vary. Here, we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of RL. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event. This effect is mediated by fMRI measures of context retrieval on each trial, suggesting a mechanism whereby cues trigger retrieval of context, which then triggers retrieval of other decisions from that context. This result establishes a new avenue by which experience can guide choice, and as such has broad implications for the study of decisions.

Neuroscience↗