Local Signal Time-Series during Rest Used for Areal Boundary Mapping in Individual Human Brains

It is widely thought that resting state functional connectivity likely reflects functional interaction among brain areas and that different functional areas interact with different sets of brain areas. A method for mapping areal boundaries has been formulated based on the large-scale spatial characteristics of regional interaction revealed by resting state functional connectivity. In the present study, we present a novel analysis for areal boundary mapping that requires only the signal timecourses within a region of interest, without reference to the information from outside the region. The areal boundaries were generated by the novel analysis and were compared with those generated by the previously-established standard analysis. The boundaries were robust and reproducible across the two analyses, in two regions of interest tested. These results suggest that the information for areal boundaries is readily available inside the region of interest

Optimizing Experimental Design for Comparing Models of Brain Function

This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work

Adolescents, Adults and Rewards: Comparing Motivational Neurocircuitry Recruitment Using fMRI

Background: Adolescent risk-taking, including behaviors resulting in injury or death, has been attributed in part to maturational differences in mesolimbic incentive-motivational neurocircuitry, including ostensible oversensitivity of the nucleus accumbens (NAcc) to rewards. Methodology/Principal Findings: To test whether adolescents showed increased NAcc activation by cues for rewards, or by delivery of rewards, we scanned 24 adolescents (age 12–17) and 24 adults age (22–42) with functional magnetic resonance imaging while they performed a monetary incentive delay (MID) task. The MID task was configured to temporally disentangle potential reward or potential loss anticipation-related brain signal from reward or loss notification-related signal. Subjects saw cues signaling opportunities to win or avoid losing $0,$.50, or $5 for responding quickly to a subsequent target. Subjects then viewed feedback of their trial success after a variable interval from cue presentation of between 6 to17 s. Adolescents showed reduced NAcc recruitment by reward-predictive cues compared to adult controls in a linear contrast with non-incentive cues, and in a volume-of-interest analysis of signal change in the NAcc. In contrast, adolescents showed little difference in striatal and frontocortical responsiveness to reward deliveries compared to adults. Conclusions/Significance: In light of divergent developmental difference findings between neuroimaging incentive paradigms (as well as at different stages within the same task), these data suggest that maturational differences i

Effects of Aversive Stimuli on Prospective Memory. An Event-Related fMRI Study

Prospective memory (PM) describes the ability to execute a previously planned action at the appropriate point in time. Although behavioral studies clearly showed that prospective memory performance is affected by the emotional significance attributed to the intended action, no study so far investigated the brain mechanisms subserving the modulatory effect of emotional salience on PM performance. The general aim of the present study was to explore brain regions involved in prospective memory processes when PM cues are associated with emotional stimuli. In particular, based on the hypothesised critical role of the prefrontal cortex in prospective memory in the presence of emotionally salient stimuli, we expected a stronger involvement of aPFC when the retrieval and execution of the intended action is cued by an aversive stimulus. To this aim BOLD responses of PM trials cued by aversive facial expressions were compared to PM trials cued by neutral facial expressions. Whole brain analysis showed that PM task cued by aversive stimuli is differentially associated with activity in the right lateral prefrontal area (BA 10) and in the left caudate nucleus. Moreover a temporal shift between the response of the caudate nucleus that preceded that of aPFC was observed. These findings suggest that the caudate nucleus might provide an early analysis of the affective properties of the stimuli, whereas the anterior lateral prefrontal cortex (BA10) would be involved in a slower and more deliberative analysis to guide goal-directed behaviour

BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis

Reaction time (RT) is one of the most widely used measures of performance in experimental psychology, yet relatively few fMRI studies have included trial-by-trial differences in RT as a predictor variable in their analyses. Using a multi-study approach, we investigated whether there are brain regions that show a general relationship between trial-by-trial RT variability and activation across a range of cognitive tasks.The relation between trial-by-trial differences in RT and brain activation was modeled in five different fMRI datasets spanning a range of experimental tasks and stimulus modalities. Three main findings were identified. First, in a widely distributed set of gray and white matter regions, activation was delayed on trials with long RTs relative to short RTs, suggesting delayed initiation of underlying physiological processes. Second, in lateral and medial frontal regions, activation showed a "time-on-task" effect, increasing linearly as a function of RT. Finally, RT variability reliably modulated the BOLD signal not only in gray matter but also in diffuse regions of white matter.The results highlight the importance of modeling trial-by-trial RT in fMRI analyses and raise the possibility that RT variability may provide a powerful probe for investigating the previously elusive white matter BOLD signal

Transient neural activity in human parietal cortex during spatial attention shifts.

Observers viewing a complex visual scene selectively attend to relevant locations or objects and ignore irrelevant ones. Selective attention to an object enhances its neural representation in extrastriate cortex, compared with those of unattended objects, via top-down attentional control signals. The posterior parietal cortex is centrally involved in this control of spatial attention. We examined brain activity during attention shifts using rapid, event-related fMRI of human observers as they covertly shifted attention between two peripheral spatial locations. Activation in extrastriate cortex increased after a shift of attention to the contralateral visual field and remained high during sustained contralateral attention. The time course of activity was substantially different in posterior parietal cortex, where transient increases in activation accompanied shifts of attention in either direction. This result suggests that activation of the parietal cortex is associated with a discrete signal to shift spatial attention, and is not the source of a signal to continuously maintain the current attentive state