Presentation is loading. Please wait.

Presentation is loading. Please wait.

Jeremy R. Gray, Christopher F. Chabris and Todd S. Braver Elaine Chan Neural mechanisms of general fluid intelligence.

Similar presentations


Presentation on theme: "Jeremy R. Gray, Christopher F. Chabris and Todd S. Braver Elaine Chan Neural mechanisms of general fluid intelligence."— Presentation transcript:

1 Jeremy R. Gray, Christopher F. Chabris and Todd S. Braver Elaine Chan Neural mechanisms of general fluid intelligence

2 Background Information The general intelligence factor (g) is a construct used to quantify what is common to the scores of all intelligence tests 1904: Charles Spearman

3 Background Information Fluid intelligence (F) – Raymond Cattell the ability to find meaning in confusion and solve new problems, to draw inferences and understand the relationships of various concepts, independent of acquired knowledge General fluid intelligence (gF) a major dimension of individual differences

4 Introduction Evidence from cognitive (behavioural) and anatomical studies suggests that gF should covary with both task performance and neural activity in specific brain systems when specific cognitive demands are present with the neural activity mediating the relation between gF and performance

5 Cognitively: gF thought to be related to metacognition (knowing about and reflecting upon one’s own ongoing mental processes) and to working memory Eg/the ability to overcome interference that would otherwise disrupt performance by compromising task goals or information held active in working memory Anatomically: the neural substrate of gF is thought to include portions of the prefrontal cortex (PFC) No previous studies have correlated gF with neural function across individuals

6 Direct investigation of this would help create a mechanistic model of human intelligence, which might in turn suggest ways to enhance gF through behavioural or neurobehavioural interventions.

7 Hypothesis Individual differences in gF will be most evident on lure trials, both in terms of task performance and neural activity in areas that are critical for cognitive control.

8 Methods Assessed gF in subjects using a standard measure (Raven’s Advanced Progressive Matrices) administered outside of the MR scanner Then, used fMRI to measure event-related brain activity as participants performed a challenging computerized three-back task Individual differences in gF most pronounced in behavioural measures when attentional control is required Target, lure, and non-lure trials

9 Three-back task

10 Subjects Originally 60 participants (29 male, 31 female) 12 excluded due to technical problems, excessive head movement, or too few trials 48 participants used for results Healthy, right-handed, native English speakers Aged 18-37 years No history of neurological disorder, current psychoactive medication, or other factors that would affect the fMRI results

11 Results – Behavioural data Lure trials were far more difficult than non-lure trials Higher gF correlated positively with accuracy on both lure trials and non-lure trials

12 Results – Neuroimaging data On lure trials, gF correlated positively with the magnitude of event-related activity in the a priori search space (lateral PFC, dorsal anterior cingulate, and lateral cerebellum), as well as across the whole brain (within parietal and temporal cortex)

13 Discussion lateral PFC, suspected to support reasoning and novel problem solving ability, does show meaningful neural activity which mediates the relation between ability (gF) and performance on a demanding working-memory task provides the first direct support for a major hypothesis about the neurobiological basis of gF gF-related differences in brain activity emerged almost exclusively on working memory trials with high interference, as predicted from behavioural evidence showing the importance of attentional control in protecting goals, or other information held actively in mind, from such interference

14 Confounds Some of the identified regions of neural signalling may not contribute causally to task performance, or may be supporting a different cognitive function than working memory Eg/ inhibition of incorrect responses cued by familiarity

15 My Opinion Strengths: Experiment type gave a high degree of experimental control over individual differences in motivation and other potential confounds Weaknesses: The results section describing the neuroimaging data was unclear Would have benefited from more diagrams and images of the brain areas in question

16 Future Studies? Sex differences? Further explore relationships among functional, structural, genetic and cognitive correlates of gF within the same sample

17 Thank you! References: Gray JR, Chabris CF, Braver TS. (2003) Neural mechanisms of general fluid intelligence. Nat Neurosci. 6(3):316-22. Any Questions?


Download ppt "Jeremy R. Gray, Christopher F. Chabris and Todd S. Braver Elaine Chan Neural mechanisms of general fluid intelligence."

Similar presentations


Ads by Google