Color Naming and Categorization Depend on Distinct Functional Brain Networks

被引:7
|
作者
Siuda-Krzywicka, Katarzyna [1 ]
Witzel, Christoph [2 ]
Bartolomeo, Paolo [1 ]
Cohen, Laurent [1 ,3 ]
机构
[1] Sorbonne Univ, Inst Cerveau, Hop Pitie Salpetriere, ICM,Inserm U 1127,CNRS UMR 7225, F-75013 Paris, France
[2] Univ Southampton, Sch Psychol, Southampton SO17 1BJ, Hants, England
[3] Hop La Pitie Salpetriere, Assistance Publ Hop Paris, Federat Neurol, F-75013 Paris, France
关键词
color vision; fMRI; language; resting-state connectivity; Sapir-Whorf hypothesis;
D O I
10.1093/cercor/bhaa278
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Naming a color can be understood as an act of categorization, that is, identifying it as a member of a category of colors that are referred to by the same name. But are naming and categorization equivalent cognitive processes and consequently rely on same neural substrates? Here, we used task and resting-state functional magnetic resonance imaging as well as behavioral measures to identify functional brain networks that modulated naming and categorization of colors. We first identified three bilateral color-sensitive regions in the ventro-occipital cortex. We then showed that, across participants, color naming and categorization response times (RTs) were correlated with different resting state connectivity networks seeded from the color-sensitive regions. Color naming RTs correlated with the connectivity between the left posterior color region, the left middle temporal gyrus, and the left angular gyrus. In contrast, color categorization RTs correlated with the connectivity between the bilateral posterior color regions, and left frontal, right temporal and bilateral parietal areas. The networks supporting naming and categorization had a minimal overlap, indicating that the 2 processes rely on different neural mechanisms.
引用
收藏
页码:1106 / 1115
页数:10
相关论文
共 50 条
  • [31] Structure of Brain Functional Networks
    Kuchaiev, Oleksii
    Wang, Po T.
    Nenadic, Zoran
    Przulj, Natasa
    2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 4166 - +
  • [32] Aging and functional brain networks
    D Tomasi
    N D Volkow
    Molecular Psychiatry, 2012, 17 : 549 - 558
  • [33] Aging and functional brain networks
    Tomasi, D.
    Volkow, N. D.
    MOLECULAR PSYCHIATRY, 2012, 17 (05) : 549 - 558
  • [34] Negative functional brain networks
    Parente, Fabrizio
    Frascarelli, Marianna
    Mirigliani, Alessia
    Di Fabio, Fabio
    Biondi, Massimo
    Colosimo, Alfredo
    BRAIN IMAGING AND BEHAVIOR, 2018, 12 (02) : 467 - 476
  • [35] Imageability effect on the functional brain activity during a naming to definition task
    Garbarini, Francesca
    Calzavarini, Fabrizio
    Diano, Matteo
    Biggio, Monica
    Barbero, Carola
    Radicioni, Daniele P.
    Geminiani, Giuliano
    Sacco, Katiuscia
    Marconi, Diego
    NEUROPSYCHOLOGIA, 2020, 137
  • [36] Distinct Effects of Motor Training on Resting-State Functional Networks of the Brain in Parkinson's Disease
    Droby, Amgad
    Maidan, Inbal
    Jacob, Yael
    Giladi, Nir
    Hausdorff, Jeffrey M.
    Mirelman, Anat
    NEUROREHABILITATION AND NEURAL REPAIR, 2020, 34 (09) : 795 - 803
  • [37] TRANSIENT SPECTRAL PEAK ANALYSIS REVEALS DISTINCT TEMPORAL ACTIVATION PROFILES FOR DIFFERENT FUNCTIONAL BRAIN NETWORKS
    Miller, Robyn L.
    Calhoun, Vince D.
    2020 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI 2020), 2020, : 108 - 111
  • [38] Distinct Functional Contributions of Primary Sensory and Association Areas to Audiovisual Integration in Object Categorization
    Werner, Sebastian
    Noppeney, Uta
    JOURNAL OF NEUROSCIENCE, 2010, 30 (07): : 2662 - 2675
  • [39] COLOR NAMING DEFICIT IN APHASIC AND NON-APHASIC BRAIN-DAMAGED PATIENTS
    POECK, K
    STACHOWIAK, FJ
    JOURNAL OF NEUROLOGY, 1975, 209 (02) : 95 - 102
  • [40] Interpretable, highly accurate brain decoding of subtly distinct brain states from functional MRI using intrinsic functional networks and long short-term memory recurrent neural networks
    Li, Hongming
    Fan, Yong
    NEUROIMAGE, 2019, 202