Fluid intelligence - Cam-CAN
1
We show that fluid intelligence shows a strong non-linear decline over lifetime. Furthermore, GM density in the MDS positively predicts fluid intelligence scores, and GM density in the MDS declined less quickly with age compared to TGM, suggesting differential developmental trajectories. These findings suggest that the MDS can provide a unique insight into the possible preservation of fluid intelligence over lifetime. Fluid intelligence over lifetime A confirmatory factor model to estimate scores on the latent variable fluid reasoning fit the data very well, χ²(2, N=247)= 1.334, p=.51, CFI=1, RMSEA=0.0, SRMR=0.01). A regression of fluid intelligence on age showed a strong non-linear decline of estimated fluid intelligence scores with age (linear BIC= 434.30 versus quadratic BIC= 431.5). C1 C2 C3 C4 1 .83 .91 .87 ε1 ε2 ε3 ε4 Fluid intelligence The Multiple Demand System Grey matter, fluid intelligence and ageing -1.0 -0.5 0.0 0.5 1.0 -1.0 -0.5 0.0 0.5 1.0 Variables factor map (PCA) Dim 1 (48.29%) Dim 2 (11.51%) ROI1 ROI2 ROI3 ROI4 ROI5 ROI6 ROI7 ROI8 Fluid intelligence shows a strong non-linear decline over lifetime that is partially counteracted by grey matter density in a core brain network called the Multiple Demand System. ε1 ε2 ε3 ε4 C1 C2 C3 Fluid intelligence C4 1 .85 .97 .89 TGM MDS Age -0.73*** -0.06(n.s.) 0.148*** Grey Matter Density in the Multiple Demand System explains changes in Fluid Intelligence over lifetime Rogier A. Kievit 1 , Jason R Taylor 1 , John Duncan 1 , Cam-CAN 2 & Rik Henson 1 1 MRC CBU, Cambridge, UK Background References Data acquisition and participants Conclusion One-sentence summary 2 Biotechnology and Biological Sciences Research Council, UK. Fluid intelligence is the ability to think logically and solve novel problems in the absence of task-specific knowledge. It is consistently positively related to grey matter (GM) density (Deary, Penke & Johnson, 2010) and shows a decline over lifetime (Cattell, 1971). The Multiple Demand System (MDS) is a core set of brain regions involved in diverse cognitive demands, with clear functional (Duncan, 2010) and structural (Woolgar et al., 2010) associations with fluid intelligence. We examine the relationship between the MDS, total grey matter (TGM) and fluid intelligence in a representative ageing sample. Participants (N=250; 18-88, mean=56.9, sd=17.8, 122 female) were recruited as part the Cambridge Centre for Ageing and Neuroscience project (Cam-CAN). We assessed fluid intelligence using the Cattell Culture Fair test, a standardized set of matrix reasoning items. Structural brain scans were acquired using a 3T Siemens TIM Trio MRI system at the MRC-CBSU. A MIMIC model of MDS, TGM and age best fit the data (χ² (11, N=247)= 20.196, p=.043, CFI=0.983, RMSEA=0.059, SRMR=0.033). This model fit showed a significant positive loading of MDS but not TGM on fluid intelligence, and a significant negative loading of age on fluid intelligence. Grey matter in the MDS decreased less quickly with age than TGM (Steiger’s Z-test, -0.45>-.015, t=-3.71, p<0.001) sug- gesting that the MDS is relatively preserved during ageing. Cattell, R.B. (1971). Abilities: Their structure, growth, and action. Houghton-Mifflin, Boston. Deary, I. J., Penke, L. & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience , 11, 201-211. Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in cognitive sciences, 14(4), 172 179. Kievit, R. A., van Rooijen, H., Wicherts, J. M., Waldorp, L. J., Kan, K. J., Scholte, H. S., & Borsboom, D. (2012). Intelligence and the brain: A model-based approach. Cognitive Neuroscience, 3, 89-97. Woolgar, A., Parr, A., Cusack, R., Thompson, R., Nimmo-Smith, I., Torralva, T., ... & Duncan, J. (2010). Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex. Proceedings of the National Academy of Sciences, 107, 14899-14902. Grey matter density in 8 bilaterally symmetrical regions of interest (ROIS) that form the core of the MDS was estimated. A Principal Component Analysis across these 8 ROIs yielded one significant principal component. Component scores were used for further analyses. Core MDS ROIS 1. Lateral occipital complex 2. Insular cortex 3. Frontal pole 4. Precentral gyrus 5. Intraparietal sulcus 6. Middle frontal gyrus 7. Paracingulate gyrus 8. Superior Frontal gyrus 20 30 40 50 60 70 80 -2 0 1 2 3 4 Age Brainmeasure TGM= -.45*** MD= -.15* -1 Cattell Culture Fair test Possible responses Example item
Transcript of Fluid intelligence - Cam-CAN
We show that fluid intelligence shows a strong non-linear decline over lifetime. Furthermore, GM density in the MDS positively predicts fluid intelligence scores, and GM density in the MDS declined less quickly with age compared to TGM, suggesting differential developmental trajectories. These findings suggest that the MDS can provide a unique insight into the possible preservation of fluid intelligence over lifetime.
Fluid intelligence over lifetime
A confirmatory factor model to estimate scores on the latent variable fluid reasoning fit the data very well, χ²(2, N=247)= 1.334, p=.51, CFI=1, RMSEA=0.0, SRMR=0.01).
A regression of fluid intelligence on age showed a strong non-linear decline of estimated fluid intelligence scores with age (linear BIC= 434.30 versus quadratic BIC= 431.5).
C1 C2 C3 C4
1 .83 .91 .87
ε1 ε2 ε3 ε4
Fluid intelligence
The Multiple Demand System
Grey matter, fluid intelligence and ageing
−1.0 −0.5 0.0 0.5 1.0
−1.0
−0.5
0.0
0.5
1.0
Variables factor map (PCA)
Dim 1 (48.29%)
Dim
2 (1
1.51
%)
ROI1ROI2
ROI3
ROI4
ROI5
ROI6
ROI7
ROI8
Fluid intelligence shows a strong non-linear decline over lifetime that is partially counteracted by grey matter density in a core brain network called the Multiple Demand System.
ε1 ε2 ε3 ε4
C1 C2 C3
Fluid intelligence
C4
1 .85 .97 .89
TGM MDS Age-0.73***-0.06(n.s.) 0.148***
Grey Matter Density in the Multiple Demand System explains changes in Fluid Intelligence over lifetime
Rogier A. Kievit1, Jason R Taylor1, John Duncan1, Cam-CAN2 & Rik Henson1
1MRC CBU, Cambridge, UK
Background
References
Data acquisition and participants
Conclusion
One-sentence summary
2Biotechnology and Biological Sciences Research Council, UK.
Fluid intelligence is the ability to think logically and solve novel problems in the absence of task-specific knowledge. It is consistently positively related to grey matter (GM) density (Deary, Penke & Johnson, 2010) and shows a decline over lifetime (Cattell, 1971).
The Multiple Demand System (MDS) is a core set of brain regions involved in diverse cognitive demands, with clear functional (Duncan, 2010) and structural (Woolgar et al., 2010) associations with fluid intelligence. We examine the relationship between the MDS, total grey matter (TGM) and fluid intelligence in a representative ageing sample.
Participants (N=250; 18-88, mean=56.9, sd=17.8, 122 female) were recruited as part the Cambridge Centre for Ageing and Neuroscience project (Cam-CAN). We assessed fluid intelligence using the Cattell Culture Fair test, a standardized set of matrix reasoning items. Structural brain scans were acquired using a 3T Siemens TIM Trio MRI system at the MRC-CBSU.
A MIMIC model of MDS, TGM and age best fit the data (χ² (11, N=247)= 20.196, p=.043, CFI=0.983, RMSEA=0.059, SRMR=0.033). This model fit showed a significant positive loading of MDS but not TGM on fluid intelligence, and a significant negative loading of age on fluid intelligence.
Grey matter in the MDS decreased less quickly with age than TGM (Steiger’s Z-test, -0.45>-.015, t=-3.71, p<0.001) sug-gesting that the MDS is relatively preserved during ageing.
Cattell, R.B. (1971). Abilities: Their structure, growth, and action. Houghton-Mifflin, Boston. Deary, I. J., Penke, L. & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience , 11, 201-211.Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in cognitive sciences, 14(4), 172 179. Kievit, R. A., van Rooijen, H., Wicherts, J. M., Waldorp, L. J., Kan, K. J., Scholte, H. S., & Borsboom, D. (2012). Intelligence and the brain: A model-based approach. Cognitive Neuroscience, 3, 89-97.Woolgar, A., Parr, A., Cusack, R., Thompson, R., Nimmo-Smith, I., Torralva, T., ... & Duncan, J. (2010). Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex. Proceedings of the National Academy of Sciences, 107, 14899-14902.
Grey matter density in 8 bilaterally symmetrical regions of interest (ROIS) that form the core of the MDS was estimated. A Principal Component Analysis across these 8 ROIs yielded one significant principal component. Component scores were used for further analyses.
Core MDS ROIS
1. Lateral occipital complex2. Insular cortex 3. Frontal pole 4. Precentral gyrus 5. Intraparietal sulcus 6. Middle frontal gyrus7. Paracingulate gyrus 8. Superior Frontal gyrus
20 30 40 50 60 70 80
−2
01
23
4
Age
Bra
inm
easu
re
TGM= −.45***MD= −.15*
−1
Cattell Culture Fair test
Possible responsesExample item
