Bayesian population receptive field modeling in human somatosensory cortex

Puckett, Alexander M.; Bollmann, Saskia; Junday, Keerat; Barth, Markus; Cunnington, Ross

doi:10.1016/j.neuroimage.2019.116465

Cited by 46 publications

(89 citation statements)

References 88 publications

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“…This left open the question whether or not there are enlarged population receptive field (pRF) sizes in the human hand area in older compared to younger humans. Bayesian pRF modeling was employed to model pRFs in individual topographic maps, and to compare pRF sizes between younger and older adults (Puckett et al, 2020). pRF distances were used to individuate the five fingers, and pRF sizes were extracted map- and finger-specific in each individual (Puckett et al, 2020) (see Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Bayesian pRF modeling was employed to model pRFs in individual topographic maps, and to compare pRF sizes between younger and older adults. pRF centre locations were used to individuate the five fingers, and pRF sizes were extracted map- and finger-specific in each individual (Puckett et al, 2020) (see Figure 4A,C ). pRF centre locations revealed an organized finger map with D1-D5 arranged from superior to inferior, as expected (see Figure 4A , see Figure 4-figure supplement 1 for individual data and for a comparison between pRF-based and Fourier-based topographic maps).…”

Section: Resultsmentioning

confidence: 99%

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The organizational principles of de-differentiated topographic maps in somatosensory cortex

Liu

Chrysidou

Doehler

et al. 2020

Preprint

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AbstractTopographic maps are a fundamental feature of cortex architecture in the mammalian brain. One common theory is that the de-differentiation of topographic maps links to impairments in everyday behavior due to less precise functional map readouts. Here, we tested this theory by characterizing de-differentiated topographic maps in primary somatosensory cortex (SI) of younger and older adults by means of ultra-high resolution functional magnetic resonance imaging together with perceptual finger individuation and hand dexterity. Older adults’ SI maps showed similar amplitude, size, and levels of stimulus-related noise than younger adults’ SI maps, but presented with less representational similarity between distant fingers. Larger population receptive field sizes in older adults’ maps did not correlate with behavior, whereas reduced cortical distances related to better hand dexterity. Our data uncover the drawbacks of a simple de-differentiation model of topographic map function, and motivate the introduction of a feature-based model of cortical reorganization.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

The organizational principles of de-differentiated topographic maps in somatosensory cortex

Liu

Chrysidou

Doehler

et al. 2020

Preprint

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“…Apart from characterizing the properties of voxels in response to external stimulation, the pRF modeling approach has also been extended to study resting state connectivity (Gravel et al, 2014). Outside the study of visual areas, pRF modeling approaches have been successfully applied to map the spatial organization of the somatosensory cortex (Puckett et al, 2020) as well as the preference and selectivity (i.e., tuning) to sound frequency in auditory cortical areas (Thomas et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Investigating the Reliability of Population Receptive Field Size Estimates Using fMRI

et al. 2020

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In functional MRI (fMRI), population receptive field (pRF) models allow a quantitative description of the response as a function of the features of the stimuli that are relevant for each voxel. The most popular pRF model used in fMRI assumes a Gaussian shape in the features space (e.g., the visual field) reducing the description of the voxel's pRF to the Gaussian mean (the pRF preferred feature) and standard deviation (the pRF size). The estimation of the pRF mean has been proven to be highly reliable. However, the estimate of the pRF size has been shown not to be consistent within and between subjects. While this issue has been noted experimentally, here we use an optimization theory perspective to describe how the inconsistency in estimating the pRF size is linked to an inherent property of the Gaussian pRF model. When fitting such models, the goodness of fit is less sensitive to variations in the pRF size than to variations in the pRF mean. We also show how the same issue can be considered from a bias-variance perspective. We compare different estimation procedures in terms of the reliability of their estimates using simulated and real fMRI data in the visual (using the Human Connectome Project database) and auditory domain. We show that, the reliability of the estimate of the pRF size can be improved considering a linear combination of those pRF models with similar goodness of fit or a permutation based approach. This increase in reliability of the pRF size estimate does not affect the reliability of the estimate of the pRF mean and the prediction accuracy.

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“…Conventional pRF modeling tries to fit a Gaussian pRF across a rigid functional space, e.g. visual field locations [19] or auditory frequencies [20], which has also been applied to finger space in combination with somatosensory [21] and motor tasks [18]. However, to adequately assess the internal structure of neuronal populations with respect to motor activity, we cannot simply assume that each pRF consists of a rigid ordering or body parts, e.g.…”

Section: Introductionmentioning

confidence: 99%

Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population Response Fields

Schellekens

Bakker

et al. 2020

Preprint

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For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and importance. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.

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Bayesian population receptive field modeling in human somatosensory cortex

Cited by 46 publications

References 88 publications

The organizational principles of de-differentiated topographic maps in somatosensory cortex

The organizational principles of de-differentiated topographic maps in somatosensory cortex

Investigating the Reliability of Population Receptive Field Size Estimates Using fMRI

Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population Response Fields

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