Brain entropy and human intelligence: A resting-state fMRI study

Abstract

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

A Study of Brain Neuronal and Functional Complexities Estimated Using Multiscale Entropy in Healthy Young Adults

“…These regions are known to be influential on fluid intelligence [33,39,41]. In addition, fluid intelligence is related to activity in the bilateral superior, inferior, and middle frontal gyri, as well as the anterior cingulate and paracingulate cortex [41]. The selected features corroborate with these past studies.…”

“…The group mean correlation of nMSE with fluid intelligence was negative at fine scales and positive at coarse scales. Recent studies have shown the FC and SampEn have a similar correlation trend [34,36,42,43], and FC had a positive correlation with fluid intelligence [10,39,41,44]. In addition, studies have shown that fluid intelligence depends on synchrony in the brain's intrinsic network [45].…”

“…The brain regions in the RECN and LECN, such as frontal gyrus, angular gyrus, and parietal gyrus were selected as significant features in the leave-one-subject-out SVR models. These regions are known to be influential on fluid intelligence [33,39,41]. In addition, fluid intelligence is related to activity in the bilateral superior, inferior, and middle frontal gyri, as well as the anterior cingulate and paracingulate cortex [41].…”

“…On each box, the central mark shows the median, bottom and top edges show the 25th and 75th percentiles, respectively, and the whiskers extend to the most extreme data points that are not considered as outliers, which are defined as 1.5 times the interquartile range away from the top or bottom of the box. Nodes belonging to the RSNs are shown in parentheses-auditory (1-3), basal ganglia(4-7), dorsal default mode network(8)(9)(10)(11)(12)(13)(14)(15)(16)(17), primary visual(18)(19), language (20-26), left executive control network(27)(28)(29)(30)(31)(32), sensorimotor(33)(34)(35)(36)(37)(38), posterior salience(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50), precuneus(51)(52)(53)(54), higher visual (55-56), right executive control network (57-62), anterior salience (63-69), ventral default mode network (70-79), visuospatial (80-90).…”

Two Kinds of Information Processing in Cognition

“…Cognitive processing is sometimes defined over the information-theoretic properties of the neural vehicles. Saxe et al (2018) describe how brain entropy during resting state, as measured by fMRI, correlates with general intelligence. Chang et al (2018) describe how drinking coffee increases the brain's entropy during resting state.…”