When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

The timescale of structural remodeling that accompanies functional neuroplasticity is largely unknown. Although structural remodeling of human brain tissue is known to occur following long-term (weeks) acquisition of a new skill, little is known as to what happens structurally when the brain needs to adopt new sequences of procedural rules or memorize a cascade of events within minutes or hours. Using diffusion tensor imaging (DTI), an MRI-based framework, we examined subjects before and after a spatial learning and memory task. Microstructural changes (as reflected by DTI measures) of limbic system structures (hippocampus and parahippocampus) were significant after only 2 hr of training. This observation was also found in a supporting rat study. We conclude that cellular rearrangement of neural tissue can be detected by DTI, and that this modality may allow neuroplasticity to be localized over short timescales.

Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains ("female brain" or "male brain"). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only "male" or only "female" features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the "maleness-femaleness" continuum are rare. Rather, most brains are comprised of unique "mosaics" of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain.gender differences | sex differences | brain structure | brain connectivity | behavior T he question of whether males and females form two distinct categories has attracted thinkers from ancient times to this day. Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved (for a historical overview, see refs. 1 and 2). Documented sex/gender* differences in the brain are often taken as support of a sexually dimorphic view of human brains ("female brain" vs. "male brain"), and consequently, of a sexually dimorphic view of human behavior, cognition, personality, attitudes, and other gender characteristics (3). Joel (4, 5) has recently argued that the existence of sex/gender differences in the brain is not sufficient to conclude that human brains belong to two distinct categories. Rather, such a distinction requires the fulfillment of two conditions: one, the form of the elements that show sex/gender differences should be dimorphic, that is, with little overlap between the forms of the elements in males and females. Two, there should be a high degree of internal consistency in the form of the different elements of a single brain (e.g., all elements have the "male" form).Previous criticisms of the dichotomous view of human brain have focused on the fact that most sex/gender differences are nondimorphic popul...

Magnetic resonance imaging (MRI) has greatly extended the exploration of neuroplasticity in behaving animals and humans. Imaging studies recently uncovered structural changes that occur in gray and white matter, mainly after long-term training. A recent diffusion tensor imaging (DTI) study showed that training in a car racing game for 2 h induces changes in the hippocampus and parahippocampal gyri. However, the effect of short-term training on the white matter microstructure is unknown. Here we investigated the influence of short learning tasks on structural plasticity in the white matter, and specifically in the fornix, in humans and rats. Human subjects performed a 2 h spatial learning task, and rats underwent training for 1 d in a Morris water maze. Between tasks, subjects were scanned with DTI, a diffusion MRI framework sensitive to tissue microstructure. Using tract-based spatial statistics, we found changes in diffusivity indices in both humans and rats. In both species, changes in diffusion in the fornix were correlated with diffusion changes in the hippocampus, as well as with behavioral measures of improvement in the learning tasks. These results, which provide the first indication of short-term white matter plasticity in the human brain, suggest that the adult brain white matter preserves dynamic characteristics and can be modified by short-term learning experiences. The extent of change in white matter was correlated with their extent in gray matter, suggesting that all components of the neural network are capable of rapid remodeling in response to cognitive experiences.

The understanding of the relationship between structure and function has always characterized biology in general and neurobiology in particular. One such fundamental relationship is that between axon diameter and the axon's conduction velocity (ACV). Measurement of these neuronal properties, however, requires invasive procedures that preclude direct elucidation of this relationship in vivo. Here we demonstrate that diffusion-based MRI is sensitive to the fine microstructural elements of brain wiring and can be used to quantify axon diameter in vivo. Moreover, we demonstrate the in vivo correlation between the diameter of an axon and its conduction velocity in the human brain. Using AxCaliber, a novel magnetic resonance imaging technique that enables us to estimate in vivo axon diameter distribution (ADD) and by measuring the interhemispheric transfer time (IHTT) by electroencephalography, we found significant linear correlation, across a cohort of subjects, between brain microstructure morphology (ADD) and its physiology (ACV) in the tactile and visual sensory domains. The ability to make a quantitative assessment of a fundamental physiological property in the human brain from in vivo measurements of ADD may shed new light on neurological processes occurring in neuroplasticity as well as in neurological disorders and neurodegenerative diseases.

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Current noninvasive methods to detect structural plasticity in humans are mainly used to study long-term changes. Diffusion magnetic resonance imaging (MRI) was recently proposed as a novel approach to reveal gray matter changes following spatial navigation learning and object-location memory tasks. In the present work, we used diffusion MRI to investigate the short-term neuroplasticity that accompanies motor sequence learning. Following a 45-min training session in which participants learned to accurately play a short sequence on a piano keyboard, changes in diffusion properties were revealed mainly in motor system regions such as the premotor cortex and cerebellum. In a second learning session taking place immediately afterward, feedback was given on the timing of key pressing instead of accuracy, while participants continued to learn. This second session induced a different plasticity pattern, demonstrating the dynamic nature of learning-induced plasticity, formerly thought to require months of training in order to be detectable. These results provide us with an important reminder that the brain is an extremely dynamic structure. Furthermore, diffusion MRI offers a novel measure to follow tissue plasticity particularly over short timescales, allowing new insights into the dynamics of structural brain plasticity.