Mentalizing refers to our ability to read the mental states of other agents and engages many neural processes. The brain's mirror system allows us to share the emotions of others. Through perspective taking, we can infer what a person currently believes about the world given their point of view. Finally, the human brain has the unique ability to represent the mental states of the self and the other and the relationship between these mental states, making possible the communication of ideas.

Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict (...) individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs. (shrink)

Although patient data have traditionally implicated the left prefrontal cortex in hypothesis generation, recent lesion data implicate right PFC in hypothesis generation tasks that involve set shifts. To test the involvement of the right prefrontal cortex in a hypothesis generation task involving set shifts, we scanned 13 normal subjects with fMRI as they completed Match Problems and a baseline task. In Match Problems subjects determined the number of possible solutions for each trial. Successful solutions are indicative of set shifts. In (...) the baseline condition subjects evaluated the accuracy of hypothetical solutions to match problems. A comparison of Match Problems versus baseline trials revealed activation in right ventral lateral PFC and left dorsal lateral PFC. A further comparison of successfully versus unsuccessfully completed Match Problems revealed activation in right ventral lateral PFC, left middle frontal gyrus and left frontal pole, thus identifying the former as a critical component of the neural mechanisms of set-shift transformation. By contrast, activation in right dorsal lateral PFC covaried as a function of the number of solutions generated in Match Problems, possibly due to increased working memory demands to maintain multiple solutions ‘on-line’, conflict resolution, or progress monitoring. These results go beyond the patient data by identifying the ventral lateral aspect of right PFC as being a critical component of the neural systems underlying lateral transformations, and demonstrate a dissociation between right VLPFC and DLPFC in hypotheses generation and maintenance. (shrink)

We tested an architect with a lesion to the right prefrontal cortex in a real-world architectural design/planning task that required him to develop a new design for our lab space and compared his performance to an age- and education-matched architect. The patient understood the task and even observed that “this is a very simple problem.” His sophisticated architectural knowledge base was still intact and he used it quite skilfully during the problem structuring phase. However, the patient's problem-solving behaviour differed from (...) the control's behaviour in the following ways: he was unable to make the transition from problem structuring to problem solving; as a result preliminary design did not start until two thirds of the way into the session; the preliminary design phase was minimal and erratic, consisting of three independently generated fragments; there was no progression or lateral development of these fragments; there was no carry-over of abstract information into the preliminary design or later phases, and the patient did not make it to the detailing phase. This suggests that the key to understanding our patient's deficit is to understand the cognitive processes and mechanisms involved in the preliminary design phase. We appeal to a theory of design problem solving that associates cognitive processes involved in preliminary design with “lateral” state transformations and argues that “ill-structured” representational and computational systems are necessary to support these transformations. We conclude that the neural basis of this system is selectively damaged in our patient. (shrink)