Verbal and visual cognition: Individual differences in the lab, in the brain, and in the classroom

References

• Alloway, T. P. (2009). Working memory, but not IQ, predicts subsequent learning in children with learning difficulties. European Journal of Psychological Assessment, 25(2), 92–98. doi:10.1027/1015-5759.25.2.92
   Web of Science ®Google Scholar
• Alloway, T. P., Gathercole, S. E., & Pickering, S. J. (2006). Verbal and visuospatial short-term and working memory in children: Are they separable? Child Development, 77(6), 1698–1716. doi:10.1111/j.1467-8624.2006.00968.x
   PubMed Web of Science ®Google Scholar
• Archibald, L. M. D., & Alloway, T. P. (2008). Comparing language profiles: Children with specific language impairment and developmental coordination disorder. International Journal of Language & Communication Disorders, 43(2), 165–180. doi:10.1080/13682820701422809
   PubMed Web of Science ®Google Scholar
• Archibald, L. M. D., & Gathercole, S. E. (2006). Short‐term and working memory in specific language impairment. International Journal of Language & Communication Disorders, 41(6), 675–693. doi:10.1080/13682820500442602
   PubMed Web of Science ®Google Scholar
• Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4(10), 829–839.
   PubMed Web of Science ®Google Scholar
• Baddeley, A. (2012). Working memory: Theories, models, and controversies. Annual Review of Psychology, 63(1), 1–29. doi:10.1146/annurev-psych-120710-100422
   PubMed Web of Science ®Google Scholar
• Baldo, J., Dronkers, N., Wilkins, D., Ludy, C., Raskin, P., & Kim, J. (2005). Is problem solving dependent on language? Brain and Language, 92(3), 240–250. doi:10.1016/j.bandl.2004.06.103
   PubMed Web of Science ®Google Scholar
• Buzzell, G. A., Roberts, D. M., Baldwin, C. L., & McDonald, C. G. (2013). An electrophysiological correlate of conflict processing in an auditory spatial Stroop task: The effect of individual differences in navigational style. International Journal of Psychophysiology, 90(2), 265–271. doi:10.1016/j.ijpsycho.2013.08.008
   PubMed Web of Science ®Google Scholar
• Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor-Analytic Studies (1St Edition). Cambridge University Press.
   Google Scholar
• Chiou, R., & Lambon Ralph, M. A. (2016). The anterior temporal cortex is a primary semantic source of top-down influences on object recognition. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 79, 75–86. doi:10.1016/j.cortex.2016.03.007
   PubMed Web of Science ®Google Scholar
• Colom, R., Jung, R. E., & Haier, R. J. (2006). Distributed brain sites for the g-factor of intelligence. NeuroImage, 31(3), 1359–1365. doi:10.1016/j.neuroimage.2006.01.006
   PubMed Web of Science ®Google Scholar
• Coutanche, M. N., & Thompson-Schill, S. L. (2015). Creating concepts from converging features in human cortex. Cerebral Cortex, 25(9), 2584–2593. doi:10.1093/cercor/bhu057
   PubMed Web of Science ®Google Scholar
• Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience, 11(3), 201–211. doi:10.1038/nrn2793
   PubMed Web of Science ®Google Scholar
• Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13–21. doi:10.1016/j.intell.2006.02.001
   Web of Science ®Google Scholar
• Dronkers, N. F., Wilkins, D. P., Van Valin, R. D. Jr,, Redfern, B. B., & Jaeger, J. J. (2004). Lesion analysis of the brain areas involved in language comprehension. Cognition, 92(1–2), 145–177.
   PubMed Web of Science ®Google Scholar
• Engle, R. W., Kane, M. J., & Tuholski, S. W. (1999). Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. In dividual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence. In A. Miyake, & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 102–134). New York, NY, US: Cambridge University Press. doi:10.1017/CBO9781139174909.007
   Google Scholar
• Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128(3), 309–331. doi:10.1037/0096-3445.128.3.309
   PubMed Web of Science ®Google Scholar
• Fedorenko, E., Behr, M. K., & Kanwisher, N. (2011). Functional specificity for high-level linguistic processing in the human brain. Proceedings of the National Academy of Sciences of the United States of America, 108(39), 16428–16433. doi:10.1073/pnas.1112937108
   PubMed Web of Science ®Google Scholar
• Fedorenko, E., & Thompson-Schill, S. L. (2014). Reworking the language network. Trends in Cognitive Sciences, 18(3), 120–126. doi:10.1016/j.tics.2013.12.006
   PubMed Web of Science ®Google Scholar
• Fiebach, C. J., Rissman, J., & D’Esposito, M. (2006). Modulation of inferotemporal cortex activation during verbal working memory maintenance. Neuron, 51(2), 251–261. doi:10.1016/j.neuron.2006.06.007
   PubMed Web of Science ®Google Scholar
• Friedman, N. P., & Miyake, A. (2000). Differential roles for visuospatial and verbal working memory in situation model construction. Journal of Experimental Psychology: General, 129(1), 61–83. doi:10.1037/0096-3445.129.1.61
   PubMed Web of Science ®Google Scholar
• Fürst, A. J., & Hitch, G. J. (2000). Separate roles for executive and phonological components of working memory in mental arithmetic. Memory & Cognition, 28(5), 774–782. doi:10.3758/BF03198412
   PubMed Web of Science ®Google Scholar
• Gathercole, S. E., & Alloway, T. P. (2008). Working memory and learning: A practical guide for teachers. Los Angeles, CA: Sage.
   Google Scholar
• Gathercole, S. E., Tiffany, C., Briscoe, J., Thorn, A. S. C., Team, A., et al. (2005). Developmental consequences of phonological loop deficits during early childhood: A longitudinal study. Journal Children Psychologist Psychiatry, 46(6), 598–611.
   PubMed Web of Science ®Google Scholar
• Gathercole, S. E., Lamont, E., & Alloway, T. P. (2006). Working memory in the classroom. In Working memory and education (pp. 219–240). Elsevier. doi:10.1016/B978-012554465-8/50010-7.
   Google Scholar
• Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6(3), 316–322. doi:10.1038/nn1014
   PubMed Web of Science ®Google Scholar
• Hodges, J. R., Patterson, K., Oxbury, S., & Funnell, E. (1992). Semantic dementia. Progressive Fluent Aphasia with Temporal Lobe Atrophy. Brain: A Journal of Neurology, 115(Pt 6), 1783–1806.
   Google Scholar
• Hsu, N. S., Kraemer, D. J. M., Oliver, R. T., Schlichting, M. L., & Thompson-Schill, S. L. (2011). Color, context, and cognitive style: Variations in color knowledge retrieval as a function of task and subject variables. Journal of Cognitive Neuroscience, 23(9), 2544–2557. doi:10.1162/jocn.2011.21619
   PubMed Web of Science ®Google Scholar
• Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioral and Brain Sciences, 30(2), 135. doi:10.1017/S0140525X07001185
   PubMed Web of Science ®Google Scholar
• Kirchhoff, B. A., & Buckner, R. L. (2006). Functional-anatomic correlates of individual differences in memory. Neuron, 51(2), 263–274. doi:10.1016/j.neuron.2006.06.006
   PubMed Web of Science ®Google Scholar
• Klein, I., Paradis, A.-L., Poline, J.-B., Kosslyn, S. M., & Le Bihan, D. (2000). Transient activity in the human calcarine cortex during visual-mental imagery: An event-related fMRI study. Journal of Cognitive Neuroscience, 12(supplement 2), 15–23. doi:10.1162/089892900564037
   PubMedGoogle Scholar
• Kozhevnikov, M., Kosslyn, S., & Shephard, J. (2005). Spatial versus object visualizers: A new characterization of visual cognitive style. Memory & Cognition, 33(4), 710–726.
   PubMed Web of Science ®Google Scholar
• Kraemer, D. J. M., Hamilton, R. H., Messing, S. B., DeSantis, J. H., & Thompson-Schill, S. L. (2014). Cognitive style, cortical stimulation, and the conversion hypothesis. Frontiers in Human Neuroscience, 8, 1–9. doi:10.3389/fnhum.2014.00015
   PubMed Web of Science ®Google Scholar
• Kraemer, D. J. M., Rosenberg, L. M., & Thompson-Schill, S. L. (2009). The neural correlates of visual and verbal cognitive styles. Journal of Neuroscience, 29(12), 3792–3798. doi:10.1523/JNEUROSCI.4635-08.2009
   PubMed Web of Science ®Google Scholar
• Kraemer, D. J. M., Schinazi, V. R., Cawkwell, P. B., Epstein, R. A., & Thompson-Schill, S. L. (2016). Verbalizing, visualizing, and navigating: The effect of strategies on encoding a large-scale virtual environment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(4), 611.
   PubMed Web of Science ®Google Scholar
• Lee, K. H., Choi, Y. Y., Gray, J. R., Cho, S. H., Chae, J.-H., Lee, S., & Kim, K. (2006). Neural correlates of superior intelligence: Stronger recruitment of posterior parietal cortex. NeuroImage, 29(2), 578–586. doi:10.1016/j.neuroimage.2005.07.036
   PubMed Web of Science ®Google Scholar
• Li, S., Gong, D., Jia, S., Zhang, W., & Ma, Y. (2011). Object and spatial visualizers have different object-processing patterns: Behavioral and ERP evidence. NeuroReport, 22(17), 860–864. doi:10.1097/WNR.0b013e32834b6d3b
   PubMed Web of Science ®Google Scholar
• Martinussen, R., Hayden, J., Hogg-Johnson, S., & Tannock, R. (2005). A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 44(4), 377–384.
   PubMed Web of Science ®Google Scholar
• Martinussen, R., & Tannock, R. (2006). Working memory impairments in children with attention-deficit hyperactivity disorder with and without comorbid language learning disorders. Journal of Clinical and Experimental Neuropsychology, 28(7), 1073–1094.
   PubMed Web of Science ®Google Scholar
• Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? Learning and Individual Differences, 16(4), 321–335. doi:10.1016/j.lindif.2006.10.001
   Web of Science ®Google Scholar
• McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–260. doi:10.1006/jecp.1999.2516
   PubMed Web of Science ®Google Scholar
• Miller, M. B., Donovan, C.-L., Bennett, C. M., Aminoff, E. M., & Mayer, R. E. (2012). Individual differences in cognitive style and strategy predict similarities in the patterns of brain activity between individuals. NeuroImage, 59(1), 83–93. doi:10.1016/j.neuroimage.2011.05.060
   PubMed Web of Science ®Google Scholar
• Miller, M. B., Donovan, C.-L., Van Horn, J. D., German, E., Sokol-Hessner, P., & Wolford, G. L. (2009). Unique and persistent individual patterns of brain activity across different memory retrieval tasks. NeuroImage, 48(3), 625–635. doi:10.1016/j.neuroimage.2009.06.033
   PubMed Web of Science ®Google Scholar
• Miyake, A., Friedman, N. P., Rettinger, D. A., Shah, P., & Hegarty, M. (2001). How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis. Journal of Experimental Psychology: General, 130(4), 621–640. doi:10.1037/0096-3445.130.4.621
   PubMed Web of Science ®Google Scholar
• Motes, M. A., Malach, R., & Kozhevnikov, M. (2008). Object-processing neural efficiency differentiates object from spatial visualizers. NeuroReport, 19(17), 1727–1731. doi:10.1097/WNR.0b013e328317f3e2
   PubMed Web of Science ®Google Scholar
• Oliveri, S., Incorpora, C., Genevini, M., Santagostino, L., Tettamanti, L., Antonietti, A., & Risoli, A. (2012). Clinical investigation of cognitive styles in patients with acquired brain damage. Neuropsychological Rehabilitation, 22(3), 362–373. doi:10.1080/09602011.2011.647416
   PubMed Web of Science ®Google Scholar
• Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., … Ballard, C. G. (2010). Putting brain training to the test. Nature, 465(7299), 775–778. doi:10.1038/nature09042
   PubMed Web of Science ®Google Scholar
• Palmiero, M., Nori, R., & Piccardi, L. (2016). Visualizer cognitive style enhances visual creativity. Neuroscience Letters, 615, 98–101. doi:10.1016/j.neulet.2016.01.032
   PubMed Web of Science ®Google Scholar
• Park, G., Lubinski, D., & Benbow, C. P. (2007). Contrasting intellectual patterns predict creativity in the arts and sciences: tracking intellectually precocious youth over 25 years. Psychological Science, 18(11), 948–952. doi:https://doi.org/10.1111/j.1467-9280.2007.02007.x
   PubMed Web of Science ®Google Scholar
• Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105–119.
   PubMedGoogle Scholar
• Ranganath, C., Cohen, M. X., Dam, C., & D’Esposito, M. (2004). Inferior temporal, prefrontal, and hippocampal contributions to visual working memory maintenance and associative memory retrieval. Journal of Neuroscience, 24(16), 3917–3925. doi:10.1523/JNEUROSCI.5053-03.2004
   PubMed Web of Science ®Google Scholar
• Raven, J., Raven, J. C., & Court, J. H. (2000). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Section 3: The standard progressive matrices. San Antonio, TX: Harcourt Assessment.
   Google Scholar
• Rogers, T. T., Graham, K. S., & Patterson, K. (2015). Semantic impairment disrupts perception, memory, and naming of secondary but not primary colours. Neuropsychologia, 70, 296–308. doi:10.1016/j.neuropsychologia.2015.01.010
   PubMed Web of Science ®Google Scholar
• Rogers, T. T., Patterson, K., & Graham, K. (2007). Colour knowledge in semantic dementia: It is not all black and white. Neuropsychologia, 45(14), 3285–3298. doi:10.1016/j.neuropsychologia.2007.06.020
   PubMed Web of Science ®Google Scholar
• Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. Journal of Educational Psychology, 107(1), 64–78. doi:10.1037/a0037478
   Web of Science ®Google Scholar
• Rohde, T. E., & Thompson, L. A. (2007). Predicting academic achievement with cognitive ability. Intelligence, 35(1), 83–92.
   Web of Science ®Google Scholar
• Rourke, B. P., & Finlayson, M. A. (1978). Neuropsychological significance of variations in patterns of academic performance: Verbal and visual-spatial abilities. Journal of Abnormal Child Psychology, 6(1), 121–133.
   PubMed Web of Science ®Google Scholar
• Ryan, R. S., & Schooler, J. W. (1998). Whom do words hurt? Individual differences in susceptibility to verbal overshadowing. Applied Cognitive Psychology, 12(7), S105–S125.
   Google Scholar
• Sahyoun, C. P., Belliveau, J. W., & Mody, M. (2010). White matter integrity and pictorial reasoning in high-functioning children with autism. Brain and Cognition, 73(3), 180–188. doi:10.1016/j.bandc.2010.05.002
   PubMed Web of Science ®Google Scholar
• Sahyoun, C. P., Belliveau, J. W., Soulières, I., Schwartz, S., & Mody, M. (2010). Neuroimaging of the functional and structural networks underlying visuospatial vs. linguistic reasoning in high-functioning autism. Neuropsychologia, 48(1), 86–95. doi:10.1016/j.neuropsychologia.2009.08.013
   PubMed Web of Science ®Google Scholar
• Sahyoun, C. P., Soulières, I., Belliveau, J. W., Mottron, L., & Mody, M. (2009). Cognitive differences in pictorial reasoning between high-functioning autism and asperger’s syndrome. Journal of Autism and Developmental Disorders, 39(7), 1014–1023. doi:10.1007/s10803-009-0712-9
   PubMed Web of Science ®Google Scholar
• Salthouse, T. A. (2004). Localizing age-related individual differences in a hierarchical structure. Intelligence, 32, 6. doi:10.1016/j.intell.2004.07.003
   Web of Science ®Google Scholar
• Seufert, T., Schütze, M., & Brünken, R. (2009). Memory characteristics and modality in multimedia learning: An aptitude–treatment–interaction study. Learning and Instruction, 19(1), 28–42. doi:10.1016/j.learninstruc.2008.01.002
   Web of Science ®Google Scholar
• Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology-General, 125(1), 4–26.
   PubMed Web of Science ®Google Scholar
• Shin, G., & Kim, C. (2015). Neural correlates of cognitive style and flexible cognitive control. NeuroImage, 113, 78–85. doi:10.1016/j.neuroimage.2015.03.046
   PubMed Web of Science ®Google Scholar
• Shipstead, Z., Redick, T. S., & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138(4), 628–654. doi:10.1037/a0027473
   PubMed Web of Science ®Google Scholar
• Soulières, I., Dawson, M., Samson, F., Barbeau, E. B., Sahyoun, C. P., Strangman, G. E., … Mottron, L. (2009). Enhanced visual processing contributes to matrix reasoning in autism. Human Brain Mapping, 30(12), 4082–4107. doi:10.1002/hbm.20831
   PubMed Web of Science ®Google Scholar
• Swanson, H. L., & Howell, M. (2001). Working memory, short-term memory, and speech rate as predictors of children’s reading performance at different ages. Journal of Educational Psychology, 93(4), 720–734. doi:10.1037/0022-0663.93.4.720
   Web of Science ®Google Scholar
• Sweller, J., Merrienboer, J. J. G. V., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296.
   Web of Science ®Google Scholar
• Thompson-Schill, S. L. (2003). Neuroimaging studies of semantic memory: Inferring “how” from “where. Neuropsychologia, 41(3), 280–292. doi:10.1016/S0028-3932(02)00161-6
   PubMed Web of Science ®Google Scholar
• Turley-Ames, K., & Whitfield, M. M. (2003). Strategy training and working memory task performance. Journal of Memory and Language, 49(4), 446–468. doi:10.1016/S0749-596X(03)00095-0
   Web of Science ®Google Scholar
• Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28(2), 127–154. doi:10.1016/0749-596X(89)90040-5
   Web of Science ®Google Scholar
• Wai, J., Lubinski, D., & Benbow, C. P. (2005). Creativity and occupational accomplishments among intellectually precocious youths: An age 13 to age 33 longitudinal study. Journal of Educational Psychology, 97(3), 484–492. doi:10.1037/0022-0663.97.3.484
   Web of Science ®Google Scholar
• Wai, J., Lubinski, D., & Benbow, C. P. (2009). Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance. Journal of Educational Psychology, 101(4), 817.
   Web of Science ®Google Scholar
• Wai, J., Lubinski, D., Benbow, C. P., & Steiger, J. H. (2010). Accomplishment in science, technology, engineering, and mathematics (STEM) and its relation to STEM educational dose: A 25-year longitudinal study. Journal of Educational Psychology, 102(4), 860.
   Web of Science ®Google Scholar
• Wechsler, D. (2008). Wechsler Adult Intelligence Scale–Fourth Edition (WAIS–IV). San Antonio, TX: NCS Pearson, 22, 498.
   Google Scholar
• Zarnhofer, S., Braunstein, V., Ebner, F., Koschutnig, K., Neuper, C., Ninaus, M., … Ischebeck, A. (2013). Individual differences in solving arithmetic word problems. Behavioral and Brain Functions, 9(1), 28.
   PubMedGoogle Scholar
• Zarnhofer, S., Braunstein, V., Ebner, F., Koschutnig, K., Neuper, C., Reishofer, G., & Ischebeck, A. (2012). The influence of verbalization on the pattern of cortical activation during mental arithmetic. Behavioral and Brain Functions, 8(1), 13.
   PubMedGoogle Scholar