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Articles, Behavioral/Cognitive

Perceptual Gloss Parameters Are Encoded by Population Responses in the Monkey Inferior Temporal Cortex

Akiko Nishio, Takeaki Shimokawa, Naokazu Goda and Hidehiko Komatsu
Journal of Neuroscience 13 August 2014, 34 (33) 11143-11151; DOI: https://doi.org/10.1523/JNEUROSCI.1451-14.2014
Akiko Nishio
1Division of Sensory and Cognitive Information, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan,
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Takeaki Shimokawa
2ATR Neural Information Analysis Laboratories, Kyoto, 619-0288, Japan, and
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Naokazu Goda
1Division of Sensory and Cognitive Information, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan,
3Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki, 444-8585, Japan
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Hidehiko Komatsu
1Division of Sensory and Cognitive Information, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan,
3Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki, 444-8585, Japan
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  • Figure 1.
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    Figure 1.

    Gloss parameters and stimuli with various combinations of c and d. A, Schematic illustration of three reflection parameters: diffuse reflectance (ρd), specular reflectance (ρs), and spread of specular reflection (α). When ρd increases, the lightness of the object increases. When ρs increases, the highlights become stronger. When α increases, the highlights become blurred. B, Example of a stimulus set with a combination of four c values, four d values, and a fixed ρd value (gray). Both c and d are perceptual gloss parameters. c corresponds to the contrast gloss parameter and is represented by a nonlinear combination of ρs and ρd. d corresponds to the distinctness-of-image gloss parameter and is represented by 1 − α. Along both axes, perceived gloss increases when the value becomes larger.

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    Figure 2.

    Responses of an example neuron in perceptual gloss space (c/d space). A, Responses of an example neuron (Cell 1) to the 16 stimuli also illustrated in Figure 1B. Responses are depicted as raster plots and spike density functions (σ = 10 ms). A horizontal bar under the spike density function indicates the stimulus presentation period. B, Bubble plot showing the response magnitude of Cell 1 to each stimulus as the diameter of a circle. Responses to stimuli with high ρd (white), middle ρd (gray), and low ρd (black) are shown in the left, middle, and right panels, respectively. This neuron strongly responded to stimuli with large d value regardless of the c or ρd values.

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    Figure 3.

    Responses of example neurons with different selectivities. Rows show responses of Cell 2 (top), Cell 3 (middle), and Cell 4 (bottom); columns indicate, from left to right, responses to stimuli with high ρd (white), middle ρd (gray) and low ρd (black). Responses of Cell 2 changed along the d-axis, and this neuron preferred stimuli with large d value. Responses of Cell 3 changed along the c-axis, and this neuron preferred stimuli with large c values. Responses of Cell 4 changed in a direction intermediate between the c- and d-axes. Responses of all these neurons depended on the ρd value.

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    Figure 4.

    Multiple regression analysis of responses of individual neurons. A, Three-dimensional plots showing the results of multiple regression analyses for two example neurons depicted in Figure 3 (Cells 3 and 4). The actual neural responses to a stimulus set (black circles) and responses estimated based on the multiple regression analysis (asterisks on the gray plane) are shown in the three-dimensional space defined by axes representing c, d, and neural response. Results obtained with the optimal ρd are shown. The correlation coefficients between the actual and estimated responses are shown in the insets. B, Distribution of correlation coefficients between the actual and estimated responses. The horizontal axis indicates the correlation coefficient; the vertical axis indicates number of cells. Filled and open bars indicate significant and non-significant fits by the multiple regression analysis (F test, p < 0.05). C, Tuning direction in c/d space of each neuron significantly fit in the multiple regression analysis. Tuning direction was defined as the direction of the maximum slope of the c/d regression plane in the multiple regression analysis after the relative weighting between the c- and d-axes was adjusted (see Materials and Methods): if the responses increased (decreased) along the c axis, tuning direction becomes 0° (180)°, and if the responses increased (decreased) along the d axis, tuning directions becomes 90° (270°). Arrows corresponding to Cells 1–4 in Figures 2 and 3 are indicated.

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    Figure 5.

    Regression analysis of gloss parameters using the population activities of gloss-selective neurons. A, Relationship between the actual and estimated values of each physical parameter. The horizontal axis indicates actual values; the vertical axis indicates values estimated through regression from population responses. The black line shows the linear regression. The correlation coefficients between the actual and estimated values are shown in the insets. The top, middle, and bottom panels are for the parameters ρs, d = 1 − α and ρd, respectively. B, Relationship between the actual and estimated values of perceptual parameters of gloss. Conventions are the same as in A. The top, middle, and bottom panels are for the parameters c, d′, and Embedded Image, respectively. C, Three-dimensional plot showing the results of a regression analysis of three physical parameters of gloss (ρd, ρs, and d = 1 − α). Actual parameter values (blue) and values estimated through regression (red) are plotted in the three-dimensional space defined by axes representing the physical parameters. D, Three-dimensional plot showing the results of a regression analysis of three perceptual parameters of gloss (Embedded Image, c, and d′). Conventions are the same as in C. To aid visualization, color contours were traced by connecting the points corresponding to the minimum and maximum values of c and d in each stimulus set.

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    Figure 6.

    Contribution of individual neurons to the representation of perceptual parameters of gloss. A, The degree to which neurons tuned to different directions in the c/d plane contributed to the parameter c. The length of arrows representing the tuning direction in the c/d plane (Fig. 4C) were scaled in proportion to the magnitude of a weight coefficient, W, in Equation 6 when the parameter c was regressed with the responses of the population of gloss-selective neurons. B, C, The degree to which neurons tuned to different directions in the c/d plane contributed to the representation of the parameters d′ and Embedded Image, respectively. Conventions are the same as in A. Red, green, and blue arrows represent neurons exhibiting a large W (top five) for the regression of c, d′, and Embedded Image, respectively. The asterisk indicates that blue arrows representing two neurons are nearly completely overlapping. Purple represents a neuron that showed a large W for the regression of both c and Embedded Image (n = 1). Black represents neurons that did not exhibit large W (of the top five) for any parameters.

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    Table 1.

    Values of the stimulus parameters (ρd, c, d) used for analysis

    Diffuse reflectance (ρd)(c, d)
    White ρd = 0.795(0.03, 1.00)(0.06, 1.00)(0.08, 1.00)(0.10, 1.00)
    (0.04, 0.93)(0.06, 0.93)(0.09, 0.93)(0.11, 0.93)
    (0.04, 0.87)(0.06, 0.87)(0.09, 0.87)(0.11, 0.87)
    (0.04, 0.80)(0.06, 0.80)(0.09, 0.80)(0.11, 0.80)
    Gray ρd = 0.416(0.06, 1.0)(0.10, 1.0)(0.13, 1.0)(0.16, 1.0)
    (0.05, 0.93)(0.10, 0.93)(0.14, 0.93)(0.17, 0.93)
    (0.05, 0.87)(0.10, 0.87)(0.14, 0.87)(0.17, 0.87)
    (0.05, 0.80)(0.10, 0.80)(0.14, 0.80)(0.18, 0.80)
    Black ρd = 0.004(0.10, 1.0)(0.23, 1.0)(0.32, 1.0)(0.40, 1.0)
    (0.11, 0.93)(0.23, 0.93)(0.34, 0.93)(0.42, 0.93)
    (0.12, 0.87)(0.24, 0.87)(0.34, 0.87)(0.43, 0.87)
    (0.12, 0.80)(0.24, 0.80)(0.34, 0.80)(0.43, 0.80)
    • The parameters of 48 stimuli are separated into three sets according to their diffuse reflectance (ρd). In each set, the parameters of 16 stimuli are arranged in a 4 × 4 matrix corresponding to the arrangement of stimuli in Figures 1 and 2.

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The Journal of Neuroscience: 34 (33)
Journal of Neuroscience
Vol. 34, Issue 33
13 Aug 2014
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Perceptual Gloss Parameters Are Encoded by Population Responses in the Monkey Inferior Temporal Cortex
Akiko Nishio, Takeaki Shimokawa, Naokazu Goda, Hidehiko Komatsu
Journal of Neuroscience 13 August 2014, 34 (33) 11143-11151; DOI: 10.1523/JNEUROSCI.1451-14.2014

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Perceptual Gloss Parameters Are Encoded by Population Responses in the Monkey Inferior Temporal Cortex
Akiko Nishio, Takeaki Shimokawa, Naokazu Goda, Hidehiko Komatsu
Journal of Neuroscience 13 August 2014, 34 (33) 11143-11151; DOI: 10.1523/JNEUROSCI.1451-14.2014
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Keywords

  • gloss
  • IT cortex
  • lightness
  • monkey
  • perception
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