Categorical perception (CP) describes our tendency to perceive the visual world in a categorical manner, suggesting that high-level cognition may affect perception. While most studies are conducted in static visual scenes, Sun and colleagues found CP effects of color in multiple object tracking (MOT). This study used functional magnetic resonance imaging to investigate the neural mechanism behind the categorical effects of color in MOT. Categorical effects were associated with activities in a broad range of brain regions, including both the ventral (V4, middle temporal gyrus) and dorsal pathways (MT + /V5, inferior parietal lobule) of feature processing, as well as frontal regions (middle frontal gyrus, medial superior frontal gyrus). We proposed that these regions are hierarchically organized and responsible for distinct functions. The color-selective V4 encodes color categories, making cross-category colors more discriminable than within-category colors. Meanwhile, the language and/or semantic regions encode the verbal information of the colors. Both visual and nonvisual codes of color categories then modulate the activities of motion-sensitive MT + areas and frontal areas responsible for attentional processes.
BellgowanP. S.SaadZ. S.BandettiniP. A. (2003). Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width. Proceedings of the National Academy of Sciences, 100, 1415–1419. https://doi.org/10.1073/pnas.0337747100
2.
BermanR. A.ColbyC. L. (2002). Auditory and visual attention modulate motion processing in area MT + . Cognitive Brain Research, 14, 64–74. https://doi.org/10.1016/S0926-6410(02)00061-7
3.
BirdC. M.BerensS. C.HornerA. J.FranklinA. (2014). Categorical encoding of color in the brain. Proceedings of the National Academy of Sciences of the United States of America, 111, 4590–4595. https://doi.org/10.1073/pnas.1315275111
4.
BornsteinM. H.KordaN. O. (1984). Discrimination and matching within and between hues measured by reaction times: Some implications for categorical perception and levels of information processing. Psychological Research, 46, 207–222. https://doi.org/10.1007/BF00308884
5.
BraddickO. J.O’BrienJ. M.Wattam-BellJ.AtkinsonJ.HartleyT.TurnerR. (2001). Brain areas sensitive to coherent visual motion. Perception, 30, 61–72. https://doi.org/10.1068/p3048
6.
BrainardD. H.PelliD. G.RobsonT. (2002). Display characterization. Signal Processing, 80, 2067–2070.
7.
BrettM.AntonJ. L.ValabregueR.PolineJ. B. (2002, June). Region of interest analysis using an SPM toolbox. 8th International Conference on Functional Mapping of the Human Brain, Vol. 16, 497. https://doi.org/10.1016/S1053-8119(02)90013-3
BrownA. M.IsseA.LindseyD. T. (2016). The color lexicon of the Somali language. Journal of Vision, 16, 14. https://doi.org/10.1167/16.5.14
10.
ChakrabortyA.TranT. T.SilvaA. E.GiaschiD.ThompsonB. (2021). Continuous theta burst TMS of area MT + impairs attentive motion tracking. European Journal of Neuroscience, 54, 7289–7300. https://doi.org/10.1111/ejn.15480
11.
CulhamJ. C.BrandtS. A.CavanaghP.KanwisherN. G.DaleA. M.TootellR. B. (1998). Cortical fMRI activation produced by attentive tracking of moving targets. Journal of Neurophysiology, 80, 2657–2670.
12.
Culham, J. C., Cavanagh, P., & Kanwisher, N. G. (2001). Attention response functions: Characterizing brain areas using fMRI activation during parametric variations of attentional load. Neuron, 32, 737-745. https://doi.org/10.1016/S0896-6273(01)00499-8
13.
EndressA. D.KorjoukovI.BonattiL. L. (2017). Category-based grouping in working memory and multiple object tracking. Visual Cognition, 25, 1–20. https://doi.org/10.1080/13506285.2017.1349229
14.
ErlikhmanG.KeaneB. P.MettlerE.HorowitzT. S.KellmanP. J. (2013). Automatic feature-based grouping during multiple object tracking. Journal of Experimental Psychology: Human Perception & Performance, 39, 1625–1637. https://doi.org/10.1037/a0031750
15.
FristonK. J.AshburnerJ. T.KiebelS. J.NicholsT. E. (eds.). (2011). Statistical parametric mapping: the analysis of functional brain images. Elsevier.
16.
GibsonE.FutrellR.Jara-EttingerJ.MahowaldK.BergenL.RatnasingamS., et al. (2017). Color naming across languages reflects color use. Proceedings of the National Academy of Sciences of the United States of America, 114, 10785–10790.
17.
GoebelR.Khorram-SefatD.MuckliL.HackerH.SingerW. (1998). The constructive nature of vision: Direct evidence from functional magnetic resonance imaging studies of apparent motion and motion imagery. European Journal of Neuroscience, 10, 1563–1573. https://doi.org/10.1046/j.1460-9568.1998.00181.x
18.
GrinbandJ.WagerT. D.LindquistM.FerreraV. P.HirschJ. (2008). Detection of time-varying signals in event-related fMRI designs. Neuroimage, 43, 509–520. https://doi.org/10.1016/j.neuroimage.2008.07.065
19.
HensonR. N.PriceC. J.RuggM. D.TurnerR.FristonK. J. (2002). Detecting latency differences in event-related BOLD responses: Application to words versus nonwords and initial versus repeated face presentations. NeuroImage, 15, 83–97. https://doi.org/10.1006/nimg.2001.0940
20.
Howe, P. D., & Holcombe, A. O. (2012). Motion information is sometimes used as an aid to the visual tracking of objects. Journal of vision, 12, 10–10. https://doi.org/10.1167/12.13.10
21.
HoweP. D.HorowitzT. S.MoroczI. A.WolfeJ.LivingstoneM. S. (2009). Using fmri to distinguish components of the multiple object tracking task. Journal of Vision, 9, 1–11. https://doi.org/10.1167/9.4.1
KourtziZ.BülthoffH. H.ErbM.GroddW. (2002). Object-selective responses in the human motion area MT/MST. Nature Neuroscience, 5, 17–18. https://doi.org/10.1038/nn780
26.
KriegeskorteN.MurM.BandettiniP. A. (2008). Representational similarity analysis-connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience, 2, 4.
27.
LiuZ.LuW.SegerC. A. (2019). Perceptual and categorical processing and representation in color categorization. Brain and Cognition, 136, 103617. https://doi.org/10.1016/j.bandc.2019.103617
NummenmaaL.OksamaL.GlereanE.HyönäJ. (2017). Cortical circuit for binding object identity and location during multiple-object tracking. Cerebral Cortex, 27, 162–172. https://doi.org/10.1093/cercor/bhw380
31.
Nagahama, Y., Okada, T., Katsumi, Y., Hayashi, T., Yamauchi, H., Sawamoto, N., & Shibasaki, H. (1999). Transient neural activity in the medial superior frontal gyrus and precuneus time locked with attention shift between object features. Neuroimage, 10, 193–199. https://doi.org/10.1006/nimg.1999.0451
32.
OosterhofN. N.ConnollyA. C.HaxbyJ. V. (2016). CoSMoMVPA: Multi-modal multivariate pattern analysis of neuroimaging data in Matlab/GNU Octave. Frontiers in Neuroinformatics, 10, 27. https://doi.org/10.3389/fninf.2016.00027
33.
PersichettiA. S.Thompson-schillS. L.ButtO. H.BrainardD. H.AguirreG. K. (2015). Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex. Journal of Vision, 15, 18. https://doi.org/10.1167/15.6.18
34.
PurmannS.PollmannS. (2015). Adaptation to recent conflict in the classical color-word Stroop-task mainly involves facilitation of processing of task-relevant information. Frontiers in Human Neuroscience, 9, 88. https://doi.org/10.3389/fnhum.2015.00088
35.
ReesG.FristonK.KochC. (2000). A direct quantitative relationship between the functional properties of human and macaque V5. Nature Neuroscience, 3, 716–723. https://doi.org/10.1038/76673
RidderinkhofK. R.UllspergerM.CroneE. A.NieuwenhuisS. (2004). The role of the medial frontal cortex in cognitive control. Science, 306, 443–447. https://doi.org/10.1126/science.1100301
38.
RushworthM. F.WaltonM. E.KennerleyS. W.BannermanD. M. (2004). Action sets and decisions in the medial frontal cortex. Trends in Cognitive Sciences, 8, 410–417. https://doi.org/10.1016/j.tics.2004.07.009
39.
SachsO.WeisS.ZellaguiN.HuberW.ZvyagintsevM.MathiakK.KircherT. (2008). Automatic processing of semantic relations in fMRI: Neural activation during semantic priming of taxonomic and thematic categories. Brain Research, 1218, 194–205. https://doi.org/10.1016/j.brainres.2008.03.045
40.
SiokW. T.KayP.WangW. S.ChanA. H.ChenL.LukeK. K.TanL. H. (2009). Language regions of brain are operative in color perception. Proceedings of the National Academy of Sciences, 106, 8140–8145. https://doi.org/10.1073/pnas.0903627106
41.
Siuda-KrzywickaK.BorosM.BartolomeoP.WitzelC. (2019). The biological bases of colour categorisation: From goldfish to the human brain. Cortex, 118, 82–106. https://doi.org/10.1016/j.cortex.2019.04.010
42.
StrongS. L.SilsonE. H.GouwsA. D.MorlandA. B.McKeefryD. J. (2017). A direct demonstration of functional differences between subdivisions of human V5/MT + . Cerebral Cortex, 27, 1–10. https://doi.org/10.1093/cercor/bhw362
43.
Suegami, T., Aminihajibashi, S., & Laeng, B. (2014). Another look at category effects on colour perception and their left hemispheric lateralisation: No evidence from a colour identification task. Cognitive processing, 15, 217–226. https://doi.org/10.1007/s10339-013-0595-8
SunM.HuL.FanL.ZhangX. (2020). Tracking within-category colors is easier: Color categories modulate location processing in a dynamic visual task. Memory & Cognition, 48, 32–41. https://doi.org/10.3758/s13421-019-00959-9
46.
SunM.HuL.XinX.ZhangX. (2021). Neural hierarchy of color categorization: From prototype encoding to boundary encoding. Frontiers in Neuroscience, 5, 679626.
47.
SunM.ZhangX. (2022). Language modulates categorical effects of moving color objects. Perception51, 210–217. Advance online publication. https://doi.org/10.1177/03010066221078992
48.
SunM.ZhangX.FanL.HuL. (2018). Hue distinctiveness overrides category in determining performance in multiple object tracking. Attention Perception & Psychophysics, 80, 374–386. https://doi.org/10.3758/s13414-017-1466-7
49.
TanL. H.ChanA. H.KayP.KhongP. L.YipL. K.LukeK. K. (2008). Language affects patterns of brain activation associated with perceptual decision. Proceedings of the National Academy of Sciences of the United States of America, 105, 4004–4009. https://doi.org/10.1073/pnas.0800055105
50.
ThompsonS. K.EngelS. A.OlmanC. A. (2014). Larger neural responses produce BOLD signals that begin earlier in time. Frontiers in Neuroscience, 8, 159.
51.
Wang, C., Hu, L., Hu, S., Xu, Y., & Zhang, X. (2018). Functional specialization for feature-based and symmetry-based groupings in multiple object tracking. cortex, 108, 265–275. https://doi.org/10.1016/j.cortex.2018.09.005
52.
WardN. S.SwayneO. B.NewtonJ. M. (2008). Age-dependent changes in the neural correlates of force modulation: An fMRI study. Neurobiology of Aging, 29, 1434–1446. https://doi.org/10.1016/j.neurobiolaging.2007.04.017
WaughC. E.LemusM. G.GotlibI. H. (2014). The role of the medial frontal cortex in the maintenance of emotional states. Social Cognitive and Affective Neuroscience, 9, 2001–2009. https://doi.org/10.1093/scan/nsu011
55.
WeiL.ZhangX.LyuC.HuS.LiZ. (2017). Brain activation of semantic category-based grouping in multiple identity tracking task. PLoS One, 12, e0177709. https://doi.org/10.1371/journal.pone.0177709
56.
WinawerJ.WitthoftN.FrankM. C.WuL.WadeA. R.BoroditskyL. (2007). Russian Blues reveal effects of language on color discrimination. Proceedings of the National Academy of Sciences, 104, 7780–7785. https://doi.org/10.1073/pnas.0701644104
Witzel, C., & Gegenfurtner, K. R. (2011). Is there a lateralized category effect for color. Journal of Vision, 11, 16–16.https://doi.org/10.1167/11.12.16
59.
Witzel, C., & Gegenfurtner, K. R. (2015). Categorical facilitation with equally discriminable colors. Journal of Vision, 15, 22. https://doi.org/10.1167/15.8.22
60.
Witzel, C., & Gegenfurtner, K. R. (2016). Categorical perception for red and brown. Journal of Experimental Psychology: Human Perception and Performance, 42, 540.https://doi.org/10.1037/xhp0000154
61.
YangJ.KanazawaS.YamaguchiM. K.KurikiI. (2016). Cortical response to categorical color perception in infants investigated by near-infrared spectroscopy. Proceedings of the National Academy of Sciences of the United States of America, 113, 2370–2375. https://doi.org/10.1073/pnas.1512044113
62.
Yantis, S. (1992). Multielement visual tracking: Attention and perceptual organization. Cognitive psychology, 24, 295–340. https://doi.org/10.1016/0010-0285(92)90010-Y
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
