Dataset Information

Simulating laminar neuroimaging data for a visual delayed match-to-sample task.

ABSTRACT: Invasive electrophysiological and neuroanatomical studies in nonhuman mammalian experimental preparations have helped elucidate the lamina (layer) dependence of neural computations and interregional connections. Noninvasive functional neuroimaging can, in principle, resolve cortical laminae (layers), and thus provide insight into human neural computations and interregional connections. However human neuroimaging data are noisy and difficult to interpret; biologically realistic simulations can aid experimental interpretation by relating the neuroimaging data to simulated neural activity. We illustrate the potential of laminar neuroimaging by upgrading an existing large-scale, multiregion neural model that simulates a visual delayed match-to-sample (DMS) task. The new laminar-based neural unit incorporates spiny stellate, pyramidal, and inhibitory neural populations which are divided among supragranular, granular, and infragranular laminae (layers). We simulated neural activity which is translated into local field potential-like data used to simulate conventional and laminar fMRI activity. We implemented the laminar connectivity schemes proposed by Felleman and Van Essen (Cerebral Cortex, 1991) for interregional connections. The hemodynamic model that we employ is a modified version of one due to Heinzle et al. (Neuroimage, 2016) that incorporates the effects of draining veins. We show that the laminar version of the model replicates the findings of the existing model. The laminar model shows the finer structure in fMRI activity and functional connectivity. Laminar differences in the magnitude of neural activities are a prominent finding; these are also visible in the simulated fMRI. We illustrate differences between task and control conditions in the fMRI signal, and demonstrate differences in interregional laminar functional connectivity that reflect the underlying connectivity scheme. These results indicate that multi-layer computational models can aid in interpreting layer-specific fMRI, and suggest that increased use of laminar fMRI could provide unique and fundamental insights to human neuroscience.

SUBMITTER: Corbitt PT

PROVIDER: S-EPMC5911248 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Simulating laminar neuroimaging data for a visual delayed match-to-sample task.

Corbitt Paul T PT Ulloa Antonio A Horwitz Barry B

NeuroImage 20180222

Invasive electrophysiological and neuroanatomical studies in nonhuman mammalian experimental preparations have helped elucidate the lamina (layer) dependence of neural computations and interregional connections. Noninvasive functional neuroimaging can, in principle, resolve cortical laminae (layers), and thus provide insight into human neural computations and interregional connections. However human neuroimaging data are noisy and difficult to interpret; biologically realistic simulations can ai ...[more]

PMID: 29476912

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Project description:BackgroundVisual search declines with aging, dementia, and brain injury and is linked to limitations in everyday activities. Recent studies suggest that visual search can be improved with practice using computerized visual search tasks and puzzle video games. For practical use, it is important that visual search ability can be assessed and practiced in a controlled and adaptive way. However, commercial puzzle video games make it hard to control task difficulty, and there are little means to collect performance data.ObjectiveThe aim of this study was to develop and initially validate the search and match task (SMT) that combines an enjoyable tile-matching match-3 puzzle video game with features of the visual search paradigm (taskified game). The SMT was designed as a single-target visual search task that allows control over task difficulty variables and collection of performance data.MethodsThe SMT is played on a grid-based (width × height) puzzle board, filled with different types of colored polygons. A wide range of difficulty levels was generated by combinations of 3 task variables over a range from 4 to 8 including height and width of the puzzle board (set size) and the numbers of tile types (distractor heterogeneity). For each difficulty level, large numbers of playable trials were pregenerated using Python. Each trial consists of 4 consecutive puzzle boards, where the goal of the task is to find a target tile configuration (search) on the puzzle board and swap 2 adjacent tiles to create a line of 3 identical tiles (match). For each puzzle board, there is exactly 1 possible match (single target search). In a user study with 28 young adults (aged 18 to 31 years), 13 older (aged 64 to 79 years) and 11 oldest (aged 86 to 98 years) adults played the long (young and older adults) or short version (oldest adults) of the difficulty levels of the SMT. Participants rated their perception and the usability of the task and completed neuropsychological tests that measure cognitive domains engaged by the puzzle game.ResultsResults from the user study indicate that the target search time is associated with set size, distractor heterogeneity, and age. Results further indicate that search performance is associated with general cognitive ability, selective and divided attention, visual search, and visuospatial and pattern recognition ability.ConclusionsOverall, this study shows that an everyday puzzle game-based task can be experimentally controlled, is enjoyable and user-friendly, and permits data collection to assess visual search and cognitive abilities. Further research is needed to evaluate the potential of the SMT game to assess and practice visual search ability in an enjoyable and adaptive way. A PsychoPy version of the SMT is freely available for researchers.

Dataset Information

Simulating laminar neuroimaging data for a visual delayed match-to-sample task.

Publications

Simulating laminar neuroimaging data for a visual delayed match-to-sample task.

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