#FLUID INTELLIGENCE CONSISTS OF PROFESSIONAL#

The Wechsler Adult Intelligence Scale (WAIS) 16 has also been used to estimate fluid intelligence by averaging performance on a diverse range of subtests. Less commonly, verbal tests of fluid intelligence such as Part 1 of the Alice Heim 4 (AH4-1) 15 are adopted. Each problem presents an incomplete matrix of geometric figures with a multiple choice of options for the missing figure. 11, 12 Raven’s Advanced Progressive Matrices 13 (APM), a test widely adopted in clinical practice and research, 14 contains multiple choice visual analogy problems of increasing difficulty. Such tests are known to have strong fluid intelligence correlations in large-scale factor analyses. 10įluid intelligence is traditionally measured with tests of novel problem-solving with non-verbal material that minimize dependence on prior knowledge. 9 Despite the importance of fluid intelligence in defining human behaviour, it remains contentious whether this is a single or a cluster of cognitive abilities and the nature of its relationship with the brain. 6 It is thought to be a key mental capacity involved in ‘active thinking’, 7 fluid intelligence declines dramatically in various types of dementia 8 and reflects the degree of executive impairment in older patients with frontal involvement.

#FLUID INTELLIGENCE CONSISTS OF PROFESSIONAL#

memory), 2 and predicts educational and professional success, 3 social mobility, 4 health 5 and longevity. 1 Fluid intelligence ranks amongst the most important features of cognition, correlates with many cognitive abilities (e.g. Further they suggest that Raven’s Advanced Progressive Matrices is a useful clinical index of fluid intelligence and a sensitive marker of right frontal lobe dysfunction.įrontal lobes, executive functions, fluency, focal lesion, lesion-symptom mapping Introductionįluid intelligence refers to the ability to solve challenging novel problems when prior learning or accumulated experience are of limited use. Our findings indicate that a set of predominantly right frontal regions, rather than a more widely distributed network, is critical to the high-level functions involved in fluid intelligence. Combining novel graph-based lesion-deficit mapping with detailed investigation of cognitive performance in a large sample of patients provides crucial information about the neural basis of intelligence. Our study represents the first large-scale investigation of the distributed neural substrates of fluid intelligence in the focally injured brain. Similar results were obtained with standard lesion-deficit analyses. Crucially, this localization was confirmed on explicitly disentangling functional from pathology-driven effects within a layered stochastic block model, prominently highlighting a right frontal network involving middle and inferior frontal gyrus, pre- and post-central gyri, with a weak contribution from right superior parietal lobule. Both conventional network-based statistics and non-parametric Bayesian stochastic block modelling heavily implicated the right frontal lobe. Neither the presence nor the extent of multiple demand network involvement affected performance. Patients with non-frontal lesions were indistinguishable from controls and showed no modulation by laterality. Impaired performance was confined to patients with frontal lesions, more marked on the right than left. Non-parametric Bayesian stochastic block models were used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. We assessed 165 healthy controls and 227 frontal or non-frontal patients with unilateral brain lesions on the best-established test of fluid intelligence, Raven’s Advanced Progressive Matrices, employing an array of lesion-deficit inferential models responsive to the potentially distributed nature of fluid intelligence.

The task demands large samples of patients, comprehensive investigation of performance, fine-grained anatomical mapping, and robust lesion-deficit inference, yet to be brought to bear on it.

Influential proposals drawing primarily on functional imaging data have implicated ‘multiple demand’ frontoparietal and more widely distributed cortical networks, but extant lesion-deficit studies with greater causal power are almost all small, methodologically constrained, and inconclusive. Yet the nature of its relationship with the brain remains a contentious topic.

Fluid intelligence is arguably the defining feature of human cognition.

Fluid intelligence consists of