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Decoding individual natural scene representations during perception and imagery.

Johnson MR, Johnson MK - Front Hum Neurosci (2014)

Bottom Line: We found that item-specific information was represented in multiple scene-selective areas: the occipital place area (OPA), parahippocampal place area (PPA), retrosplenial cortex (RSC), and a scene-selective portion of the precuneus/intraparietal sulcus region (PCu/IPS).These results support findings from previous decoding analyses for other types of visual information and/or brain areas during imagery or working memory, and extend them to the case of visual scenes (and scene-selective cortex).This suggests that although decodable scene-relevant activity occurs in FFA during perception, FFA activity may not be a necessary (or even relevant) component of one's mental representation of visual scenes.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Yale University New Haven, CT, USA.

ABSTRACT
We used a multi-voxel classification analysis of functional magnetic resonance imaging (fMRI) data to determine to what extent item-specific information about complex natural scenes is represented in several category-selective areas of human extrastriate visual cortex during visual perception and visual mental imagery. Participants in the scanner either viewed or were instructed to visualize previously memorized natural scene exemplars, and the neuroimaging data were subsequently subjected to a multi-voxel pattern analysis (MVPA) using a support vector machine (SVM) classifier. We found that item-specific information was represented in multiple scene-selective areas: the occipital place area (OPA), parahippocampal place area (PPA), retrosplenial cortex (RSC), and a scene-selective portion of the precuneus/intraparietal sulcus region (PCu/IPS). Furthermore, item-specific information from perceived scenes was re-instantiated during mental imagery of the same scenes. These results support findings from previous decoding analyses for other types of visual information and/or brain areas during imagery or working memory, and extend them to the case of visual scenes (and scene-selective cortex). Taken together, such findings support models suggesting that reflective mental processes are subserved by the re-instantiation of perceptual information in high-level visual cortex. We also examined activity in the fusiform face area (FFA) and found that it, too, contained significant item-specific scene information during perception, but not during mental imagery. This suggests that although decodable scene-relevant activity occurs in FFA during perception, FFA activity may not be a necessary (or even relevant) component of one's mental representation of visual scenes.

No MeSH data available.


Related in: MedlinePlus

Classification accuracy for distinguishing between the overall processes of perception and mental imagery by ROI. In all cases, accuracies were significantly above chance (AUC = 0.5), but there were significant differences in accuracy by region. OPA differentiated between perception and imagery the best, followed by PPA, PCu/IPS, and RSC. Pairwise comparisons between OPA and PPA, and between PCu/IPS and RSC, were significant, though PPA and PCu/IPS did not significantly differ. Analyses used 80 voxels per hemisphere per region, for a total of 160 voxels per region. *p < 0.05, ***p < 0.001. Error bars represent s.e.m. See text and Table 1 for full statistics.
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Figure 5: Classification accuracy for distinguishing between the overall processes of perception and mental imagery by ROI. In all cases, accuracies were significantly above chance (AUC = 0.5), but there were significant differences in accuracy by region. OPA differentiated between perception and imagery the best, followed by PPA, PCu/IPS, and RSC. Pairwise comparisons between OPA and PPA, and between PCu/IPS and RSC, were significant, though PPA and PCu/IPS did not significantly differ. Analyses used 80 voxels per hemisphere per region, for a total of 160 voxels per region. *p < 0.05, ***p < 0.001. Error bars represent s.e.m. See text and Table 1 for full statistics.

Mentions: We also asked to what extent the classifier was able to distinguish perception trials from imagery trials on the whole, regardless of the specific items being seen or visualized. As noted above, for this analysis, we coded each trial as either a Perception or Imagery trial and used a single cross-validation classifier. Results are shown in Figure 5. As expected, performance for classifying perception vs. imagery was high, and significantly above chance in all ROIs and both experiments (all AUC > 0.72, all p < 10−5). However, perception vs. imagery classification differed by area in both Experiment 1 [F(3, 45) = 13.79, p = 1.64 × 10−6] and Experiment 2 [F(3, 33) = 15.95, p = 1.40 × 10−6; both One-Way repeated-measures ANOVAs], supporting previous hypotheses that different areas along the visual processing pipeline for scenes may not all distinguish equally between perceptual and reflective processing (Johnson et al., 2007; Johnson and Johnson, 2009). OPA distinguished the most between perception and imagery, significantly more so than PPA [AUCs: 0.881 vs. 0.839, t(27) = 2.77, p = 0.010]; PPA did not significantly differ from PCu/IPS [AUCs: 0.839 vs. 0.808, t(27) = 1.55, p = 0.13]; but PCu/IPS distinguished between perception and imagery significantly more than RSC [AUCs: 0.808 vs. 0.730, t(27) = 3.71, p = 0.00095; values were collapsed across experiment for these comparisons, as the label modality (visual or auditory) should not be expected to affect perception vs. imagery classification].


Decoding individual natural scene representations during perception and imagery.

Johnson MR, Johnson MK - Front Hum Neurosci (2014)

Classification accuracy for distinguishing between the overall processes of perception and mental imagery by ROI. In all cases, accuracies were significantly above chance (AUC = 0.5), but there were significant differences in accuracy by region. OPA differentiated between perception and imagery the best, followed by PPA, PCu/IPS, and RSC. Pairwise comparisons between OPA and PPA, and between PCu/IPS and RSC, were significant, though PPA and PCu/IPS did not significantly differ. Analyses used 80 voxels per hemisphere per region, for a total of 160 voxels per region. *p < 0.05, ***p < 0.001. Error bars represent s.e.m. See text and Table 1 for full statistics.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3921604&req=5

Figure 5: Classification accuracy for distinguishing between the overall processes of perception and mental imagery by ROI. In all cases, accuracies were significantly above chance (AUC = 0.5), but there were significant differences in accuracy by region. OPA differentiated between perception and imagery the best, followed by PPA, PCu/IPS, and RSC. Pairwise comparisons between OPA and PPA, and between PCu/IPS and RSC, were significant, though PPA and PCu/IPS did not significantly differ. Analyses used 80 voxels per hemisphere per region, for a total of 160 voxels per region. *p < 0.05, ***p < 0.001. Error bars represent s.e.m. See text and Table 1 for full statistics.
Mentions: We also asked to what extent the classifier was able to distinguish perception trials from imagery trials on the whole, regardless of the specific items being seen or visualized. As noted above, for this analysis, we coded each trial as either a Perception or Imagery trial and used a single cross-validation classifier. Results are shown in Figure 5. As expected, performance for classifying perception vs. imagery was high, and significantly above chance in all ROIs and both experiments (all AUC > 0.72, all p < 10−5). However, perception vs. imagery classification differed by area in both Experiment 1 [F(3, 45) = 13.79, p = 1.64 × 10−6] and Experiment 2 [F(3, 33) = 15.95, p = 1.40 × 10−6; both One-Way repeated-measures ANOVAs], supporting previous hypotheses that different areas along the visual processing pipeline for scenes may not all distinguish equally between perceptual and reflective processing (Johnson et al., 2007; Johnson and Johnson, 2009). OPA distinguished the most between perception and imagery, significantly more so than PPA [AUCs: 0.881 vs. 0.839, t(27) = 2.77, p = 0.010]; PPA did not significantly differ from PCu/IPS [AUCs: 0.839 vs. 0.808, t(27) = 1.55, p = 0.13]; but PCu/IPS distinguished between perception and imagery significantly more than RSC [AUCs: 0.808 vs. 0.730, t(27) = 3.71, p = 0.00095; values were collapsed across experiment for these comparisons, as the label modality (visual or auditory) should not be expected to affect perception vs. imagery classification].

Bottom Line: We found that item-specific information was represented in multiple scene-selective areas: the occipital place area (OPA), parahippocampal place area (PPA), retrosplenial cortex (RSC), and a scene-selective portion of the precuneus/intraparietal sulcus region (PCu/IPS).These results support findings from previous decoding analyses for other types of visual information and/or brain areas during imagery or working memory, and extend them to the case of visual scenes (and scene-selective cortex).This suggests that although decodable scene-relevant activity occurs in FFA during perception, FFA activity may not be a necessary (or even relevant) component of one's mental representation of visual scenes.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Yale University New Haven, CT, USA.

ABSTRACT
We used a multi-voxel classification analysis of functional magnetic resonance imaging (fMRI) data to determine to what extent item-specific information about complex natural scenes is represented in several category-selective areas of human extrastriate visual cortex during visual perception and visual mental imagery. Participants in the scanner either viewed or were instructed to visualize previously memorized natural scene exemplars, and the neuroimaging data were subsequently subjected to a multi-voxel pattern analysis (MVPA) using a support vector machine (SVM) classifier. We found that item-specific information was represented in multiple scene-selective areas: the occipital place area (OPA), parahippocampal place area (PPA), retrosplenial cortex (RSC), and a scene-selective portion of the precuneus/intraparietal sulcus region (PCu/IPS). Furthermore, item-specific information from perceived scenes was re-instantiated during mental imagery of the same scenes. These results support findings from previous decoding analyses for other types of visual information and/or brain areas during imagery or working memory, and extend them to the case of visual scenes (and scene-selective cortex). Taken together, such findings support models suggesting that reflective mental processes are subserved by the re-instantiation of perceptual information in high-level visual cortex. We also examined activity in the fusiform face area (FFA) and found that it, too, contained significant item-specific scene information during perception, but not during mental imagery. This suggests that although decodable scene-relevant activity occurs in FFA during perception, FFA activity may not be a necessary (or even relevant) component of one's mental representation of visual scenes.

No MeSH data available.


Related in: MedlinePlus