TY - JOUR
T1 - Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes
AU - Kumar, Manoj
AU - Federmeier, Kara D.
AU - Fei-Fei, Li
AU - Beck, Diane M.
N1 - Funding Information:
The authors would like to thank the following people: Dr. Christopher Baldassano for his help with performing the permutation test; Mahmoud Elhrakhawy, Echo Ye, Keyur Kurani and Seema Dave for help with preparing the stimuli. Funding for this work was provided by the following: National Science Foundation IGERT Fellowship (0903622) (MK), James S. McDonnell Foundation Scholar award (KDF), National Institutes of Health Grant 1 R01 EY019429 (LFF and DMB) and ONR MURI (LFF and DMB).
Publisher Copyright:
© 2017 Elsevier Inc.
PY - 2017/7/15
Y1 - 2017/7/15
N2 - A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. “sandy beach”) describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and frontal cortices. This similarity of neural activity patterns across the two input types, for categories that co-activate local brain regions, provides strong evidence of a common semantic code for pictures and words in the brain.
AB - A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. “sandy beach”) describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and frontal cortices. This similarity of neural activity patterns across the two input types, for categories that co-activate local brain regions, provides strong evidence of a common semantic code for pictures and words in the brain.
KW - MVPA
KW - Natural scenes
KW - Pictures
KW - Semantics
KW - Words
KW - fMRI
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UR - http://www.scopus.com/inward/citedby.url?scp=85019008386&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2017.03.037
DO - 10.1016/j.neuroimage.2017.03.037
M3 - Article
C2 - 28343000
AN - SCOPUS:85019008386
SN - 1053-8119
VL - 155
SP - 422
EP - 436
JO - NeuroImage
JF - NeuroImage
ER -