Shape-independent object category responses revealed by MEG and fMRI decoding

Kaiser, Daniel; Azzalini, Damiano; Peelen, Marius V.

doi:10.1152/jn.01074.2015

Cited by 84 publications

(73 citation statements)

References 23 publications

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“…It should be noted that previous studies provided some evidence for a contribution of semantic object properties to the MEG signal even at relatively early latencies (<250 ms) (Clarke et al, 2015;Coggan et al, 2016;Kaiser et al, 2016b). These studies differed from the current study in several important ways.…”

Section: Discussioncontrasting

confidence: 90%

“…It is likely that the semantic factors in these studies (e.g., the property "has legs"; Clarke et al, 2015) would still express in perceptual similarity differences in tasks like the oddball visual search task used here. Second, two of these studies included human faces (Coggan et al, 2016) or bodies (Kaiser et al, 2016b). The human visual system is particularly sensitive to such stimuli (Stein et al, 2012), showing highly selective and localized face-and bodyselective responses in fMRI (Kanwisher, 2010).…”

Section: Discussionmentioning

confidence: 99%

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MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

Proklova

Kaiser

Peelen³

2017

Preprint

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High-level visual cortex shows a distinction between animate and inanimate objects, as revealed by fMRI. Recent studies have shown that object animacy can similarly be decoded from MEG sensor patterns. What object properties drive this decoding? Here, we disentangled the influence of perceptual and categorical properties by presenting perceptually matched objects that were easily recognizable as being animate or inanimate (e.g., snake and rope). In a series of behavioral experiments, three aspects of perceptual dissimilarity of these objects were quantified: overall dissimilarity, outline dissimilarity, and texture dissimilarity. Neural dissimilarity of MEG sensor patterns, collected in male and female human participants, was modeled using regression analysis, in which perceptual dissimilarity (taken from the behavioral experiments) and categorical dissimilarity served as predictors of neural dissimilarity. We found that perceptual dissimilarity was strongly reflected in MEG sensor patterns from 80 ms after stimulus onset, with separable contributions of outline and texture dissimilarity. Surprisingly, MEG patterns did not distinguish between animate and inanimate objects after controlling for perceptual dissimilarity. Nearly identical results were found in a second MEG experiment that required object recognition. These results indicate that MEG sensor patterns do not capture object animacy independently of perceptual differences between animate and inanimate objects. This is in contrast to results observed in fMRI using the same stimuli, task, and analysis approach, with fMRI showing a highly reliable categorical distinction in ventral temporal cortex even when controlling for perceptual dissimilarity. The discrepancy between MEG and fMRI precludes the straightforward integration of these imaging modalities. Significance statementRecent studies have shown that multivariate analysis of MEG sensor patterns allows for a detailed characterization of the time course of visual object processing, demonstrating that the neural representational space starts to become organized by object category (e.g., separating animate and inanimate objects) from around 150 ms after stimulus onset. It is unclear, however, whether this organization truly reflects a categorical distinction or whether it reflects uncontrolled differences in perceptual similarity (e.g., most animals have four legs). Here we find that MEG sensor patterns no longer distinguish between animate and inanimate objects when controlling for perceptual differences between objects (e.g., when comparing snake and rope). These results indicate that MEG sensor patterns are primarily sensitive to visual object properties.

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Section: Discussioncontrasting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

Proklova

Kaiser

Peelen³

2017

Preprint

Self Cite

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“…By orthogonalizing category membership and visual features of visual stimuli, previous studies reported a residual categorical effect in VOTC, highlighting how some of the variance in the neural data of VOTC might be explained by high-level categorical properties of the stimuli even when the contribution of the basic lowlevel features has been controlled for (Bracci & Beeck, 2016;Kaiser, Azzalini, & Peelen, 2016;Proklova, Kaiser, & Peelen, 2016). Category-selectivity has also been observed in VOTC during semantic tasks when word stimuli were used, suggesting an involvement of the occipito-temporal cortex in the retrieval of category-specific conceptual information.…”

Section: Discussionmentioning

confidence: 97%

Categorical representation from sound and sight in the ventral occipito-temporal cortex of sighted and blind

Mattioni

Rezk

Battal

et al. 2019

Preprint

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and Olivier Collignon (olivier.collignon@uclouvain.be). AbstractThe Ventral Occipito-Temporal Cortex (VOTC) shows reliable category selective response to visual information. Do the development, topography and information content of this categorical organization depend on visual input or even visual experience? To further address this question, we used fMRI to characterize the brain responses to eight categories (4 living, 4 non-living) presented acoustically in sighted and early blind individuals, and visually in a separate sighted group. Using a combination of decoding and representational similarity analyses, we observed that VOTC reliably encodes sounds categories in the sighted and blind groups, using a representational structure strikingly similar to the one found in vision. Moreover, we found that the representational connectivity between VOTC and large-scale brain networks was substantially similar across modalities and groups. Blind people however showed higher decoding accuracies and higher inter-subject consistency for the representation of sounds in VOTC, and the correlation between the representational structure of visual and auditory categories was almost double in the blind when compared to the sighted group. Crucially, we also demonstrate that VOTC represents the categorical membership of sounds rather that their acoustic features in both groups. Our results suggest that early visual deprivation triggers an extension of the intrinsic categorical organization of VOTC that is at least partially independent from vision.

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“…To test 170generalisation between the conditions, we trained classifiers on all time points in the data from the 5Hz 171 sequences and tested them on all time points in the data from the 20Hz sequences. We repeated this 172 for the inverse (training on 20Hz and testing on 5Hz), and averaged the resulting time-generalisation 173 matrices(Kaiser, Azzalini, & Peelen, 2016). 174 175 All steps in the decoding analysis were implemented in CoSMoMVPA(Oosterhof et al, 2016).…”

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confidence: 99%

The representational dynamics of visual objects in rapid serial visual processing streams

Grootswagers

Robinson

Carlson

2018

Preprint

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12In our daily lives, we are bombarded with a stream of rapidly changing visual input. Humans have the 13 remarkable capacity to detect and identify objects in fast-changing scenes. Yet, when studying brain 14 representations, stimuli are generally presented in isolation. Here, we studied the dynamics of human 15 vision using a combination of fast stimulus presentation rates, electroencephalography and multivariate 16 decoding analyses. Using a presentation rate of 5 images per second, we obtained the representational 17 structure of a large number of stimuli, and showed the emerging abstract categorical organisation of 18 this structure. Furthermore, we could separate the temporal dynamics of perceptual processing from 19 higher-level target selection effects. In a second experiment, we used the same paradigm at 20Hz to 20 show that shorter image presentation limits the categorical abstraction of object representations. Our 21 results show that applying multivariate pattern analysis to every image in rapid serial visual processing 22 streams has unprecedented potential for studying the temporal dynamics of the structure of 23 representations in the human visual system. 24

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Shape-independent object category responses revealed by MEG and fMRI decoding

Abstract: Kaiser D, Azzalini DC, Peelen MV. Shape-independent object category responses revealed by MEG and fMRI decoding.

Cited by 84 publications

References 23 publications

MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

Categorical representation from sound and sight in the ventral occipito-temporal cortex of sighted and blind

The representational dynamics of visual objects in rapid serial visual processing streams

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