In several studies, it has been suggested that task-switching performance is linked to processing speed. Here we argue that the relation between processing speed and high-level cognitive ability found in previous studies may be due to confounded measurements of processing speed and task-switching ability. In the present study, we required participants to complete an inspection time (IT) task to probe their processing speed. We employed conventional task-switching paradigms but applied a linear integrated speed-accuracy score (LISAS) which combines latency and accuracy scores to express task-switching ability. The results of regression analyses show that IT predicted average performance in task-switching paradigms. However, IT did not relate to any specific effects common in the task-switching task, which contradicts previous results. Our results suggest independent mechanisms of processing speed and tasks that require a high level of cognitive flexibility and control.
Akbari ChermahiniS.HommelB. (2012). More creative through positive mood? Not everyone. Frontiers in Human Neuroscience, 6, 319. https://doi.org/10.3389/fnhum.2012.00319
2.
AllportA.StylesE. A.HsiehS. (1994). Shifting intentional set: Exploring the dynamic control of tasks. In UmiltaC.MoscovitchM. (Eds), Attention and performance XV (pp. 421–452). Erlbaum.
BariA.RobbinsT. W. (2013). Inhibition and impulsivity: Behavioral and neural basis of response control. Progress in Neurobiology, 108, 44–79. https://doi.org/10.1016/j.pneurobio.2013.06.005
5.
BrownS.LehmannC.PobokaD. (2006). A critical test of the failure-to-engage theory of task switching. Psychonomic Bulletin & Review, 13(1), 152–159. https://doi.org/10.3758/bf03193827
6.
BurgessP. W. (1997). Theory and methodology in executive function research. In RabbittP. (Ed), Methodology of frontal and executive function (pp. 81–116). Psychology Press.
7.
BurnsN.NettelbeckT. (2003). Inspection time in the structure of cognitive abilities. Intelligence, 31(3), 237-255. DOI:10.1016/s0160-2896(02)00120-4
8.
BurnsN. R.NettelbeckT. (2005). Inspection time and speed of processing: Sex differences on perceptual speed but not IT. Personality and Individual Differences, 39(2), 439–446. https://doi.org/10.1016/j.paid.2005.01.022
9.
CaemmererJ. M.KeithT. Z.ReynoldsM. R. (2020). Beyond individual intelligence tests: Application of Cattell-Horn-Carroll theory. Intelligence, 79(1), 101433. https://doi.org/10.1016/j.intell.2020.101433
10.
CarrollJ. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. : Cambridge University Press.
DasekingM.PetermannF.WaldmannH.-C. (2017). Sex differences in cognitive abilities: Analyses for the German WAIS-IV. Personality and Individual Differences, 114, 145–150. https://doi.org/10.1016/j.paid.2017.04.003
14.
De JongR. (2000). An intention-activation account of residual switch costs. In MonsellS.DriverJ. (Eds), Attention and performance XVIII: Control of cognitive processes (pp. 357–376). MIT Press.
15.
DeákG. O.WiseheartM. (2015). Cognitive flexibility in young children: General or task-specific capacity?Journal of Experimental Child Psychology, 138, 31–53. https://doi.org/10.1016/j.jecp.2015.04.003
16.
DearyI. J.StoughC. (1996). Intelligence and inspection time: Achievements, prospects, and problems. American Psychologist, 51(6), 599–608. https://doi.org/10.1037/0003-066x.51.6.599
DreisbachG.GoschkeT. (2004). How positive affect modulates cognitive control: reduced perseveration at the cost of increased distractibility. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2), 343–353. https://doi.org/10.1037/0278-7393.30.2.343
19.
DuanX.ShiJ.ZhouD. (2009). Developmental changes in processing speed: Influence of accelerated education for gifted children. Gifted Child Quarterly, 54(2), 85–91. https://doi.org/10.1177/0016986209355971
EismaY. B.WinterJ. D. (2020). How do people perform an inspection time task? An examination of visual illusions, Task Experience, and Blinking. Journal of Cognition, 3(1), 34. https://doi.org/10.5334/joc.123
22.
Faroqi-ShahY.GehmanM. (2021). The role of processing speed and cognitive control on word retrieval in aging and aphasia. Journal Of Speech, Language, and Hearing Research, 64(3), 949–964. https://doi.org/10.1044/2020_jslhr-20-00326
23.
FaulF.ErdfelderE.LangA. G.BuchnerA. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146
24.
GajewskiP. D.FerdinandN. K.KrayJ.FalkensteinM. (2018). Understanding sources of adult age differences in task switching: Evidence from behavioral and ERP studies. Neuroscience & Biobehavioral Reviews, 92(1), 255–275. https://doi.org/10.1016/j.neubiorev.2018.05.029
GarbinG.SanjuanA.FornC.BustamanteJ. C.Rodriguez-PujadasA.BellochV.HernandezM.CostaA.AvilaC. (2010). Bridging language and attention: Brain basis of the impact of bilingualism on cognitive control. Neuroimage, 53(4), 1272–1278. https://doi.org/10.1016/j.neuroimage.2010.05.078
27.
GrahamS.JiangJ.ManningV.NejadA. B.ZhishengK.SallehS. R.GolayX.BerneY. I.McKennaP. J. (2010). IQ-Related fMRI differences during cognitive set shifting. Cerebral Cortex, 20(3), 641–649. https://doi.org/10.1093/cercor/bhp130
28.
GrudnikJ. L.KranzlerJ. H. (2001). Meta-analysis of the relationship between intelligence and inspection time. Intelligence, 29(6), 523–535. https://doi.org/10.1016/s0160-2896(01)00078-2
HolmS. (1979). A simple sequentially rejective multiple test procedure. Scandinavian journal of statistics, 65–70.
31.
IhleA.OrisM.FagotD.ChicherioC.van der LindenB. W. A.SauterJ.KliegelM. (2018). Associations of educational attainment and cognitive level of job with old age verbal ability and processing speed: The mediating role of chronic diseases. Applied Neuropsychology: Adult, 25(4), 356–362. https://doi.org/10.1080/23279095.2017.1306525
JohnsonW.BouchardT. J. (2007). Sex differences in mental abilities: g masks the dimensions on which they lie. Intelligence, 35(1), 23–39. https://doi.org/10.1016/j.intell.2006.03.012
34.
KieselA.SteinhauserM.WendtM.FalkensteinM.JostK.PhilippA. M.KochI. (2010). Control and interference in task switching—a review. Psychological Bulletin, 136(5), 849–874. https://doi.org/10.1037/a0019842
35.
KimH.CheyJ.LeeS. (2017). Effects of multicomponent training of cognitive control on cognitive function and brain activation in older adults. Neuroscience Research, 124, 8–15. https://doi.org/10.1016/j.neures.2017.05.004
36.
KochI.PoljacE.MüllerH.KieselA. (2018). Cognitive structure, flexibility, and plasticity in human multitasking—an integrative review of dual-task and task-switching research. Psychological Bulletin, 144(6), 557–583. https://doi.org/10.1037/bul0000144
LiX.HuangL.LiB.WangH.HanC. (2020). Time for a true display of skill: Top players in league of legends have better executive control. Acta Psychologica, 204, 103007. https://doi.org/10.1016/j.actpsy.2020.103007
43.
LiX.LiB.LiuX.LagesM.StoetG. (2019). Task-switching costs disappear if non-Chinese participants respond to Chinese characters. Journal of Experimental Psychology: Learning, Memory, And Cognition, 45(11), 2051–2071. https://doi.org/10.1037/xlm0000692
44.
LindsenJ.De JongR. (2010). Distinguishing between the partial-mapping preparation hypothesis and the failure-to-engage hypothesis of residual switch costs. Journal of Experimental Psychology: Human Perception and Performance, 36(5), 1207–1226. DOI:10.1037/a0020362
45.
López ZuniniR. A.MorrisonC.KousaieS.TalerV. (2019). Task switching and bilingualism in young and older adults: A behavioral and electrophysiological investigation. Neuropsychologia, 133, 107186. https://doi.org/10.1016/j.neuropsychologia.2019.107186
46.
LucianoM.PosthumaD.WrightM. J.de GeusE. J.SmithG. A.GeffenG. M.BoomsmaD. I.MartinN. G. (2005). Perceptual speed does not cause intelligence, and intelligence does not cause perceptual speed. Biological Psychology, 70(1), 1–8. https://doi.org/10.1016/j.biopsycho.2004.11.011
47.
LucianoM.SmithG. A.WrightM. J.GeffenG. M.GeffenL. B.MartinN. G. (2001). On the heritability of inspection time and its covariance with IQ: a twin study. Intelligence, 29(6), 443–457. https://doi.org/10.1016/s0160-2896(01)00071-x
48.
MacPhersonS. E.CoxS. R.DickieD. A.KaramaS.StarrJ. M.EvansA. C.BastinM. E.WardlawJ. M.DearyI. J. (2017). Processing speed and the relationship between trail making Test-B performance, cortical thinning and white matter microstructure in older adults. Cortex, 95, 92-103. https://doi.org/10.1016/j.cortex.2017.07.021
49.
MiyakeA.FriedmanN. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21(1), 8–14. https://doi.org/10.1177/0963721411429458
50.
MiyakeA.FriedmanN. P.EmersonM. J.WitzkiA. H.HowerterA.WagerT. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100. https://doi.org/10.1006/cogp.1999.0734
51.
MorettiL.SemenzaC.VallesiA. (2018). General slowing and education mediate task switching performance across the life-span. Frontiers in Psychology, 9, 630. https://doi.org/10.3389/fpsyg.2018.00630
52.
NwezeT.NwaniW. (2020). Contributions of working memory and inhibition to cognitive flexibility in Nigerian adolescents. Developmental Neuropsychology, 45(3), 118–128. https://doi.org/10.1080/87565641.2020.1765169
53.
PriorA.MacWhinneyB. (2010). A bilingual advantage in task switching. Bilingualism: Language and Cognition, 13(2), 253–262. https://doi.org/10.1017/s1366728909990526
54.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
55.
RavenJ.RavenJ. C.CourtJ. H. (1998). Manual for Raven's progressive matrices and vocabulary scales. The advanced progressive matrices. Section 4. Oxford Psychologists Press. The Psychological Corporation.
56.
RimkusC. M.AvolioI. M. B.MiottoE. C.PereiraS. A.MendesM. F.CallegaroD.LeiteC. D. C. (2018). The protective effects of high-education levels on cognition in different stages of multiple sclerosis. Multiple Sclerosis and Related Disorders, 22, 41–48. https://doi.org/10.1016/j.msard.2018.03.001
57.
RogersR. D.MonsellS. (1995). Costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General, 124(2), 207–231. https://doi.org/10.1037/0096-3445.124.2.207
58.
RoivainenE. (2011). Gender differences in processing speed: A review of recent research. Learning and Individual Differences, 21(2), 145-149. https://doi.org/10.1016/j.lindif.2010.11.021
SalthouseT. A.FristoeN.McGuthryK. E.HambrickD. Z. (1998). Relation of task switching to speed, age, and fluid intelligence. Psychology and Aging, 13(3), 445–461. https://doi.org/10.1037/0882-7974.13.3.445
62.
Sánchez-cubilloI.PeriáñezJ. A.Adrover-RoigD.Rodríguez-sánchezJ. M.RÍOS-LAGOM.TirapuJ.BarcelóF. (2009). Construct validity of the trail making test: role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. Journal of the International Neuropsychological Society, 15(3), 438–450. https://doi.org/10.1017/s1355617709090626
63.
StoetG. (2010). PsyToolkit: A software package for programming psychological experiments using Linux. Behavior Research Methods, 42(4), 1096–1104. https://doi.org/10.3758/brm.42.4.1096
StoetG.SnyderL. H. (2007). Extensive practice does not eliminate human switch costs. Cognitive, Affective, & Behavioral Neuroscience, 7(3), 192–197. https://doi.org/10.3758/cabn.7.3.192
67.
Tello-RamosM. C.BranchC. L.KozlovskyD. Y.PiteraA. M.PravosudovV. V. (2019). Spatial memory and cognitive flexibility trade-offs: to be or not to be flexible, that is the question. Animal Behaviour, 147(1), 129–136. https://doi.org/10.1016/j.anbehav.2018.02.019
68.
TourvaA.SpanoudisG.DemetriouA. (2016). Cognitive correlates of developing intelligence: The contribution of working memory, processing speed and attention. Intelligence, 54, 136–146. https://doi.org/10.1016/j.intell.2015.12.001
69.
UmemotoA.HolroydC. B. (2016). Chapter 8: Exploring individual differences in task switching: Persistence and other personality traits related to anterior cingulate cortex function. In StuderB.KnechtS. (Eds) Progress in brain research, (229, pp. 189–212). https://doi.org/10.1016/bs.pbr.2016.06.003
70.
VandierendonckA. (2017). A comparison of methods to combine speed and accuracy measures of performance: A rejoinder on the binning procedure. Behavior Research Methods, 49(2), 653–673. https://doi.org/10.3758/s13428-016-0721-5
71.
VandierendonckA. (2018). Further tests of the utility of integrated speed-accuracy measures in task switching. Journal of Cognition, 1(1), 8. https://doi.org/10.5334/joc.6
72.
WangT.LiC.RenX.SchweizerK. (2021). How executive processes explain the overlap between working memory capacity and fluid intelligence: A test of process overlap theory. Journal of Intelligence, 9(2), 21. https://doi.org/10.3390/jintelligence9020021
73.
WangY.ChenJ.YueZ. (2017). Positive emotion facilitates cognitive flexibility: An fMRI Study. Frontiers in Psychology, 8(1), 1832. https://doi.org/10.3389/fpsyg.2017.01832
74.
WasylyshynCVerhaeghenPSliwinskiMJ (2011). Aging and task switching: A meta-analysis. Psychology and Aging, 26(1), 15-20. https://doi.org/10.1037/a0020912
75.
WasylyshynC. V. (2007). Individual differences in task switching, executive functioning, and cognition (doctoral dissertation). Syracuse University.
76.
WeissE. M.KemmlerG.DeisenhammerE. A.FleischhackerW. W.DelazerM. (2003). Sex differences in cognitive functions. Personality and Individual Differences, 35(4), 863–875. https://doi.org/10.1016/s0191-8869(02)00288-x
77.
XuY.NyeongY.YuS.YuY.LiB.HanC.LiX. (2021). Task switching in old participants: A potential interplay between strategy and cognitive ability. Acta Psychologica, 214(2), 103253. https://doi.org/10.1016/j.actpsy.2021.103253
78.
YeeDMKrugMKAllenAZBraverTS (2015). Humans integrate monetary and liquid incentives to motivate cognitive task performance. Frontiers in Psychology, 6, 2037. https://doi.org/10.3389/fpsyg.2015.02037
