Toward open sharing of task-based fMRI data: the OpenfMRI project

Increased intraindividual variability (IIV) is a hallmark of disorders of attention. Recent work has linked these disorders to abnormalities in a "default mode" network, comprising brain regions routinely deactivated during goal-directed cognitive tasks. Findings from a study of the neural basis of attentional lapses suggest that a competitive relationship between the "task-negative" default mode network and regions of a "task-positive" attentional network is a potential locus of dysfunction in individuals with increased IIV. Resting state studies have shown that this competitive relationship is intrinsically represented in the brain, in the form of a negative correlation or antiphase relationship between spontaneous activity occurring in the two networks. We quantified the negative correlation between these two networks in 26 subjects, during active (Eriksen flanker task) and resting state scans. We hypothesized that the strength of the negative correlation is an index of the degree of regulation of activity in the default mode and task-positive networks and would be positively related to consistent behavioral performance. We found that the strength of the correlation between the two networks varies across individuals. These individual differences appear to be behaviorally relevant, as interindividual variation in the strength of the correlation was significantly related to individual differences in response time variability: the stronger the negative correlation (i.e., the closer to 180 degrees antiphase), the less variable the behavioral performance. This relationship was moderately consistent across resting and task conditions, suggesting that the measure indexes moderately stable individual differences in the integrity of functional brain networks. We discuss the implications of these findings for our understanding of the behavioral significance of spontaneous brain activity, in both healthy and clinical populations.

People typically exhibit greater sensitivity to losses than to equivalent gains when making decisions. We investigated neural correlates of loss aversion while individuals decided whether to accept or reject gambles that offered a 50/50 chance of gaining or losing money. A broad set of areas (including midbrain dopaminergic regions and their targets) showed increasing activity as potential gains increased. Potential losses were represented by decreasing activity in several of these same gain-sensitive areas. Finally, individual differences in behavioral loss aversion were predicted by a measure of neural loss aversion in several regions, including the ventral striatum and prefrontal cortex.

Brain networks with energy-efficient hubs might support the high cognitive performance of humans and a better understanding of their organization is likely of relevance for studying not only brain development and plasticity but also neuropsychiatric disorders. However, the distribution of hubs in the human brain is largely unknown due to the high computational demands of comprehensive analytical methods. Here we propose a 10(3) times faster method to map the distribution of the local functional connectivity density (lFCD) in the human brain. The robustness of this method was tested in 979 subjects from a large repository of MRI time series collected in resting conditions. Consistently across research sites, a region located in the posterior cingulate/ventral precuneus (BA 23/31) was the area with the highest lFCD, which suggest that this is the most prominent functional hub in the brain. In addition, regions located in the inferior parietal cortex (BA 18) and cuneus (BA 18) had high lFCD. The variability of this pattern across subjects was <36% and within subjects was 12%. The power scaling of the lFCD was consistent across research centers, suggesting that that brain networks have a "scale-free" organization.