Neural correlates of individual differences in personality and intelligence : Studies using an isochronous timing task and voxel based morphometry

It is easy to imagine that humans have always noticed the differences between themselves and others and perhaps even speculated about the origins of these differences. The study of individual differences as a formal field encompasses variations in intelligence and personality as well as other dimensions. Studies of the neural basis of individual differences are by their nature correlational. Two approaches that have proven fruitful in the investigation of intelligence and personality are the examination of relations between traits and performance on timed elementary cognitive tasks as well as between traits and structural features of the brain. This literature has shown that high intelligence is related to faster and less variable performance in reaction time tasks and other tasks requiring temporal processing, as well as larger volumes of neural tissue in widespread cortical areas. The personality trait Neuroticism has, similar to low intelligence, been related to more variable performance in reaction time tasks. Finally, personality differences have been related to neural structural differences as well, in regions involved in social and emotional processing. The overall aim of this thesis was to further investigate the neural underpinnings of intelligence and personality, in particular the relations of these variables to the accuracy of timing and neuroanatomy. A main question investigated in Study I was whether a relation between intelligence and temporal variability is also seen in a simple, automatic timing task. We studied performance variability on a simple finger tapping task, isochronous serial interval production (ISIP). As predicted, we found a negative correlation between intelligence and ISIP variability. Furthermore, this relation was strongest for Local interval-to-interval variability using tapping intervals in the range 500-1000 ms, and there was no difference in the strength of the correlation between more and less variable trials. These findings support a bottom-up model of the relation between timing variability and intelligence, where temporal variability of neural activity plays a functional role for cognition. In Study II we investigated whether ISIP variability and intelligence also share neuroanatomical correlates. Regional white and gray matter volumes were quantified using voxel based morphometry (VBM) from structural MR images. A main finding was that both low ISIP variability and high intelligence are related to larger white matter volume in overlapping prefrontal brain regions. This provides further support for a functional relation between temporal variability and cognitive ability, and suggests that these variables may have common neural substrates in the frontal lobe. In Study III we investigated the relation between ISIP variability and Neuroticism. A main question was whether Neuroticism is related to a different component of temporal variability than intelligence, since these traits are essentially uncorrelated. A positive relation between Neuroticism and ISIP variability was found and, unlike the correlation with intelligence, this relation was strongest for non-Local variability, i.e. Drift. This suggests that while intelligence and Neuroticism are both related to variability, the underlying mechanisms of these relations may differ. In the final study (Study IV) we examined relations between personality and neuroanatomy, using VBM. We found that Extraversion is negatively related to regional brain volume in cortical gray matter regions known to be involved in the behavioral inhibition and socialemotional processing, as well as to global white matter volume. LIST OF PUBLICATIONS INCLUDED IN THIS THESIS I. Madison G, Forsman L, Blom O, Karabanov A, Ullen F. Correlations between intelligence and components of serial timing variability. Intelligence (2009) 37:68–75. II. Ullen F, Forsman L, Blom O, Karabanov A, Madison G. Intelligence and variability in a simple timing task share neural substrates in the prefrontal white matter. The Journal of Neuroscience (2008) 28(16): 4238-4232. III. Forsman L, Madison G, Ullen F. Neuroticism is correlated with drift in serial time interval production. Personality and Individual Differences (article in review). IV. Forsman L, Blom O, Karabanov A, Madison G, Ullen F. Differences in regional brain volume related to the Extraversion-Introversion dimension – a voxel based morphometry study. NeuroImage (article in review). LIST OF PUBLICATIONS NOT INCLUDED IN THIS THESIS V. Bengtsson SL, Nagy Z, Skare S, Forsman L, Forssberg H, Ullen F. Extensive piano practicing has regionally specific effects on white matter development. Nature Neuroscience 2005, 8(9):1148-50. VI. Vollmer B, Holmstrom L, Forsman L, Krumlinde-Sundholm L, ValeroCuevas FJ, Forssberg H, Ullen F. Evidence of validity in the StrengthDexterity Test, a new assessment of dexterity in children and adolescents. (submitted for publication) VII. Karabanov A, Blom O, Forsman L, Ullen F. The dorsal auditory pathway is involved in performance of both visual and auditory regions. NeuroImage (2009) 44:480-88. TABLE OF CONTENTS 1 Background and Introduction 1 1.1 Background 1 1.1.1 The inspiration for this thesis – timing and musicians 1 1.2 Introduction Individual Differences 2 1.2. 1 Definition 2 1.2. 2 Why use an individual differences perspective? 3 1.2. 3 The neural basis of individual differences 3 1.3 Intelligence 4 1.3.1 Psychometric intelligence or “g” 4 1.3.2 Measuring g 6 1.3.3 Mental speed – elementary cognitive tasks & g 6 1.3. 4 Temporal tasks and g 8 1.3. 5 Neuroanatomy and g 11 1.3. 6 Neural correlates of intelligence – hypotheses 12 1.4 Personality 13 1.4.1 The biological (genetic) basis of personality 13 1.4.2 Dominant theories in the field of personality 13 1.4. 3 Neuroticism 15 1.4. 4 Extraversion 16 2 Aims of the studies 18 3 Methods 19 3.1 Participants 19 3.2 Materials – behavioral testing 19 3.2. 1 Intelligence Test Ravens 19 3.2. 2 Personality Test Cattell 16PF 19 3.2. 3 Isochronous Serial Interval Production (ISIP) 20 3.3 Materials Brain volume measurements 22 3.3.1 Voxel based morphometry 22 3.3.2 Image acquisition and preprocessing 22 3.3.3 Statistical analysis 23 4 Results and Discussion 25 4.1 Neural underpinnings of intelligence 25 4.1.1 Evidence for the involvement of bottom-up processes 25 4.1.2 Neural anatomical correlates of the ISIP & intelligence 27 4.1.3 Possible neural mechanisms of ISIP x intelligence relationship . 29 4.2 Neural Underpinnings of Personality 31 4.2. 1 Correlations between Neuroticism and ISIP 31 4.2. 2 Neural anatomical correlates of Extraversion 34 5 Future Directions 39 5.1 Further investigation of the ISIP Task 39 5.2 Further Neuroimaging explorations 39 6 Acknowledgements 40 7 References 42 LIST OF ABBREVIATIONS BAS Behavioral approach system BIS Behavioral inhibition system CV Coefficient of variance dBA A-weighted decibels E Extraversion ECT Elementary cognitive task FA Factor analysis FFM Five factor model GM Gray matter ID Individual differences IOI Inter-onset interval ISIP Isochronous serial interval production IT Inspection time MA Moving average MIDI Musical instrument digital interface MR(I) Magnetic resonance (imaging) ms millisecond N Neuroticism PCA Principle components analysis P-FIT Parieto-frontal integration theory Raven’s SPM Raven’s Standard Progressive Matrices RT Reaction time s second SPM Statistical parametric mapping VBM Voxel based morphometry WM White matter WPR Worst performance rule