Dataset Information

The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map.

ABSTRACT: Learning arises through the activity of large ensembles of cells, yet most of the data neuroscientists accumulate is at the level of individual neurons; we need models that can bridge this gap. We have taken spatial learning as our starting point, computationally modeling the activity of place cells using methods derived from algebraic topology, especially persistent homology. We previously showed that ensembles of hundreds of place cells could accurately encode topological information about different environments ("learn" the space) within certain values of place cell firing rate, place field size, and cell population; we called this parameter space the learning region. Here we advance the model both technically and conceptually. To make the model more physiological, we explored the effects of theta precession on spatial learning in our virtual ensembles. Theta precession, which is believed to influence learning and memory, did in fact enhance learning in our model, increasing both speed and the size of the learning region. Interestingly, theta precession also increased the number of spurious loops during simplicial complex formation. We next explored how downstream readout neurons might define co-firing by grouping together cells within different windows of time and thereby capturing different degrees of temporal overlap between spike trains. Our model's optimum coactivity window correlates well with experimental data, ranging from ?150-200 msec. We further studied the relationship between learning time, window width, and theta precession. Our results validate our topological model for spatial learning and open new avenues for connecting data at the level of individual neurons to behavioral outcomes at the neuronal ensemble level. Finally, we analyzed the dynamics of simplicial complex formation and loop transience to propose that the simplicial complex provides a useful working description of the spatial learning process.

SUBMITTER: Arai M

PROVIDER: S-EPMC4063672 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map.

Arai Mamiko M Brandt Vicky V Dabaghian Yuri Y

PLoS computational biology 20140619 6

Learning arises through the activity of large ensembles of cells, yet most of the data neuroscientists accumulate is at the level of individual neurons; we need models that can bridge this gap. We have taken spatial learning as our starting point, computationally modeling the activity of place cells using methods derived from algebraic topology, especially persistent homology. We previously showed that ensembles of hundreds of place cells could accurately encode topological information about dif ...[more]

PMID: 24945927

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Project description:Humans can rapidly and seemingly implicitly learn to predict typical locations of relevant items when those items are encountered in familiar spatial contexts. Two important questions remain, however, concerning this type of learning: (1) which neural structures and mechanisms are involved in acquiring and exploiting such contextual knowledge? (2) Is this type of learning truly implicit and unconscious? We now answer both these questions after closely examining behavior and recording neural activity using MEG while observers (male and female) were acquiring and exploiting statistical regularities. Computational modeling of behavioral data suggested that, after repeated exposures to a spatial context, participants' behavior was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that hippocampus and prefrontal cortex (PFC) were involved in the task and furthermore revealed a striking dissociation: only the initial learning phase was associated with hippocampal theta band activity, while the subsequent exploitation phase showed a shift in theta band activity to the PFC. Intriguingly, the behavioral benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. Together, these findings demonstrate that (1a) hippocampus and PFC play complementary roles in the implicit, unconscious learning and exploitation of spatial statistical regularities; (1b) these mechanisms are implemented in the theta frequency band; and (2) contextual knowledge can indeed be acquired unconsciously, and awareness of such knowledge can even interfere with the exploitation thereof.SIGNIFICANCE STATEMENT Human visual perception is determined not just by the light that strikes our eyes, but also strongly by our prior knowledge and expectations. Such expectations, particularly about where to expect certain objects given scene context, might be learned implicitly and unconsciously, although this is hotly debated. Furthermore, it is unknown which brain mechanisms underpin this type of learning. We now show that, indeed, spatial prior expectations can be learned without awareness; in fact, strikingly, awareness seems to hinder the exploitation of the relevant knowledge. Furthermore, we demonstrate that one brain mechanism (hippocampal theta-band activity) is responsible for learning in these settings, whereas another mechanism (prefrontal theta-band activity) is involved in exploiting the learned associations.

Dataset Information

The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map.

Publications

The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map.

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