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Subcortical connectivity correlates selectively with attention's effects on spatial choice bias.

ABSTRACT: Neural mechanisms of attention are extensively studied in the neocortex; comparatively little is known about how subcortical regions contribute to attention. The superior colliculus (SC) is an evolutionarily conserved, subcortical (midbrain) structure that has been implicated in controlling visuospatial attention. Yet how the SC contributes mechanistically to attention remains unknown. We investigated the role of the SC in attention, combining model-based psychophysics, diffusion imaging, and tractography in human participants. Specifically, we asked whether the SC contributes to enhancing sensitivity (d') to attended information, or whether it contributes to biasing choices (criteria) in favor of attended information. We tested human participants on a multialternative change detection task, with endogenous spatial cueing, and quantified sensitivity and bias with a recently developed multidimensional signal detection model (m-ADC model). At baseline, sensitivity and bias exhibited complementary patterns of asymmetries across the visual hemifields: While sensitivity was consistently higher for detecting changes in the left hemifield, bias was higher for reporting changes in the right hemifield. Remarkably, white matter connectivity of the SC with the neocortex mirrored this pattern of asymmetries. Specifically, the asymmetry in SC-cortex connectivity correlated with the asymmetry in choice bias, but not in sensitivity. In addition, SC-cortex connectivity strength could predict cueing-induced modulation of bias, but not of sensitivity, across individuals. In summary, the SC may be a key node in an evolutionarily conserved network for controlling choice bias during visuospatial attention.

SUBMITTER: Sreenivasan V

PROVIDER: S-EPMC6765279 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Subcortical connectivity correlates selectively with attention's effects on spatial choice bias.

Sreenivasan Varsha V Sridharan Devarajan D

Proceedings of the National Academy of Sciences of the United States of America 20190906 39

Neural mechanisms of attention are extensively studied in the neocortex; comparatively little is known about how subcortical regions contribute to attention. The superior colliculus (SC) is an evolutionarily conserved, subcortical (midbrain) structure that has been implicated in controlling visuospatial attention. Yet how the SC contributes mechanistically to attention remains unknown. We investigated the role of the SC in attention, combining model-based psychophysics, diffusion imaging, and tr ...[more]

PMID: 31492811

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Project description:BackgroundThe spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.MethodsThe recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets.ResultsThe estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets.ConclusionsDetailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions.

Dataset Information

Subcortical connectivity correlates selectively with attention's effects on spatial choice bias.

Publications

Subcortical connectivity correlates selectively with attention's effects on spatial choice bias.

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