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Neural population tuning links visual cortical anatomy to human visual perception.

Song C, Schwarzkopf DS, Kanai R, Rees G - Neuron (2015)

Bottom Line: We found that visual cortical thickness correlated negatively with the sharpness of neural population tuning and the accuracy of perceptual discrimination at different visual field positions.In contrast, visual cortical surface area correlated positively with neural population tuning sharpness and perceptual discrimination accuracy.Our findings reveal a central role for neural population tuning in linking visual cortical anatomy to visual perception and suggest that a perceptually advantageous visual cortex is a thinned one with an enlarged surface area.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK; Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: chen.song.09@ucl.ac.uk.

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Relationship between Neural Population Tuning Width and V2 Anatomy along Visual Field EccentricityThe cortical surface map from a representative participant illustrated the width of neural population tuning at individual V2 cortical surface locations (vertices) for corresponding visual field positions (A). Based on the cortical surface maps from all 20 participants, we plotted the position tuning width at individual V2 locations against visual field eccentricities these locations responded to and V2 anatomy at these locations. The 3D plots were binned into data grids where individual data points represented the position tuning width averaged over V2 locations that responded to similar eccentricities and were from the same participant or had similar thickness (A). The data grids allowed us to disentangle the influences that visual field eccentricity (B) and V2 anatomy (C and D) exerted on the position tuning width of V2 neural populations. Specifically, along the axis of V2 surface area, each plot of the position tuning width, visual field eccentricity represented the data from a single participant and illustrated the increase in the position tuning width with visual field eccentricity (B). Along the axis of visual field eccentricity, each plot of the position tuning width, V2 anatomy represented the data from a single eccentricity range and illustrated the dependence of the position tuning width on V2 surface area (C) or V2 thickness (D). Data points are color coded according to the position tuning width (A), the participant (B), or the visual field eccentricity (C and D). Equations (B) reflect linear fit to the plot of the position tuning width, visual field eccentricity. Statistical values (C and D) reflected permutation-based Spearman’s rank correlation with FWE correction for multiple comparisons. Error bars represent 1 SEM.
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fig7: Relationship between Neural Population Tuning Width and V2 Anatomy along Visual Field EccentricityThe cortical surface map from a representative participant illustrated the width of neural population tuning at individual V2 cortical surface locations (vertices) for corresponding visual field positions (A). Based on the cortical surface maps from all 20 participants, we plotted the position tuning width at individual V2 locations against visual field eccentricities these locations responded to and V2 anatomy at these locations. The 3D plots were binned into data grids where individual data points represented the position tuning width averaged over V2 locations that responded to similar eccentricities and were from the same participant or had similar thickness (A). The data grids allowed us to disentangle the influences that visual field eccentricity (B) and V2 anatomy (C and D) exerted on the position tuning width of V2 neural populations. Specifically, along the axis of V2 surface area, each plot of the position tuning width, visual field eccentricity represented the data from a single participant and illustrated the increase in the position tuning width with visual field eccentricity (B). Along the axis of visual field eccentricity, each plot of the position tuning width, V2 anatomy represented the data from a single eccentricity range and illustrated the dependence of the position tuning width on V2 surface area (C) or V2 thickness (D). Data points are color coded according to the position tuning width (A), the participant (B), or the visual field eccentricity (C and D). Equations (B) reflect linear fit to the plot of the position tuning width, visual field eccentricity. Statistical values (C and D) reflected permutation-based Spearman’s rank correlation with FWE correction for multiple comparisons. Error bars represent 1 SEM.

Mentions: Together, these analyses suggested that our observations at 4.7 degree eccentricity, where thickness and surface area of V1 exerted opposite influences on the position tuning width of V1 neural populations with behavioral consequences on the position discrimination threshold of human participants, were generalizable across the visual field. To investigate whether such generalization was also observable in V2, we plotted the position tuning width (Figure 7) and position discrimination threshold (Figure 8) at individual V2 locations (vertices) against visual field eccentricities these locations responded to and V2 anatomy at these locations. Similar to our observations in V1, surface area of V2 correlated negatively with the position tuning width of V2 neural populations (Figure 7C) and the position discrimination threshold of our participants (Figure 8C), and specifically, with their value near the fovea (tuning width, r = −0.729, p < 0.001, n = 20 and discrimination threshold, r = −0.596, p < 0.01, n = 20), as well as their slope of increase along visual field eccentricity (tuning width, r = −0.705, p < 0.001, n = 20 and discrimination threshold, r = −0.642, p < 0.01, n = 20). In contrast, thickness of V2 exhibited positive correlations with the position tuning width (Figure 7D) and position discrimination threshold (Figure 8D), within individual ranges of visual field eccentricity.


Neural population tuning links visual cortical anatomy to human visual perception.

Song C, Schwarzkopf DS, Kanai R, Rees G - Neuron (2015)

Relationship between Neural Population Tuning Width and V2 Anatomy along Visual Field EccentricityThe cortical surface map from a representative participant illustrated the width of neural population tuning at individual V2 cortical surface locations (vertices) for corresponding visual field positions (A). Based on the cortical surface maps from all 20 participants, we plotted the position tuning width at individual V2 locations against visual field eccentricities these locations responded to and V2 anatomy at these locations. The 3D plots were binned into data grids where individual data points represented the position tuning width averaged over V2 locations that responded to similar eccentricities and were from the same participant or had similar thickness (A). The data grids allowed us to disentangle the influences that visual field eccentricity (B) and V2 anatomy (C and D) exerted on the position tuning width of V2 neural populations. Specifically, along the axis of V2 surface area, each plot of the position tuning width, visual field eccentricity represented the data from a single participant and illustrated the increase in the position tuning width with visual field eccentricity (B). Along the axis of visual field eccentricity, each plot of the position tuning width, V2 anatomy represented the data from a single eccentricity range and illustrated the dependence of the position tuning width on V2 surface area (C) or V2 thickness (D). Data points are color coded according to the position tuning width (A), the participant (B), or the visual field eccentricity (C and D). Equations (B) reflect linear fit to the plot of the position tuning width, visual field eccentricity. Statistical values (C and D) reflected permutation-based Spearman’s rank correlation with FWE correction for multiple comparisons. Error bars represent 1 SEM.
© Copyright Policy - CC BY
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4321887&req=5

fig7: Relationship between Neural Population Tuning Width and V2 Anatomy along Visual Field EccentricityThe cortical surface map from a representative participant illustrated the width of neural population tuning at individual V2 cortical surface locations (vertices) for corresponding visual field positions (A). Based on the cortical surface maps from all 20 participants, we plotted the position tuning width at individual V2 locations against visual field eccentricities these locations responded to and V2 anatomy at these locations. The 3D plots were binned into data grids where individual data points represented the position tuning width averaged over V2 locations that responded to similar eccentricities and were from the same participant or had similar thickness (A). The data grids allowed us to disentangle the influences that visual field eccentricity (B) and V2 anatomy (C and D) exerted on the position tuning width of V2 neural populations. Specifically, along the axis of V2 surface area, each plot of the position tuning width, visual field eccentricity represented the data from a single participant and illustrated the increase in the position tuning width with visual field eccentricity (B). Along the axis of visual field eccentricity, each plot of the position tuning width, V2 anatomy represented the data from a single eccentricity range and illustrated the dependence of the position tuning width on V2 surface area (C) or V2 thickness (D). Data points are color coded according to the position tuning width (A), the participant (B), or the visual field eccentricity (C and D). Equations (B) reflect linear fit to the plot of the position tuning width, visual field eccentricity. Statistical values (C and D) reflected permutation-based Spearman’s rank correlation with FWE correction for multiple comparisons. Error bars represent 1 SEM.
Mentions: Together, these analyses suggested that our observations at 4.7 degree eccentricity, where thickness and surface area of V1 exerted opposite influences on the position tuning width of V1 neural populations with behavioral consequences on the position discrimination threshold of human participants, were generalizable across the visual field. To investigate whether such generalization was also observable in V2, we plotted the position tuning width (Figure 7) and position discrimination threshold (Figure 8) at individual V2 locations (vertices) against visual field eccentricities these locations responded to and V2 anatomy at these locations. Similar to our observations in V1, surface area of V2 correlated negatively with the position tuning width of V2 neural populations (Figure 7C) and the position discrimination threshold of our participants (Figure 8C), and specifically, with their value near the fovea (tuning width, r = −0.729, p < 0.001, n = 20 and discrimination threshold, r = −0.596, p < 0.01, n = 20), as well as their slope of increase along visual field eccentricity (tuning width, r = −0.705, p < 0.001, n = 20 and discrimination threshold, r = −0.642, p < 0.01, n = 20). In contrast, thickness of V2 exhibited positive correlations with the position tuning width (Figure 7D) and position discrimination threshold (Figure 8D), within individual ranges of visual field eccentricity.

Bottom Line: We found that visual cortical thickness correlated negatively with the sharpness of neural population tuning and the accuracy of perceptual discrimination at different visual field positions.In contrast, visual cortical surface area correlated positively with neural population tuning sharpness and perceptual discrimination accuracy.Our findings reveal a central role for neural population tuning in linking visual cortical anatomy to visual perception and suggest that a perceptually advantageous visual cortex is a thinned one with an enlarged surface area.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK; Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: chen.song.09@ucl.ac.uk.

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Related in: MedlinePlus