Article

fMRI of intrasubject variability in ADHD: anomalous premotor activity with prefrontal compensation.

Kennedy Krieger Institute.
Journal of the American Academy of Child and Adolescent Psychiatry (Impact Factor: 6.35). 09/2008; 47(10):1141-50. DOI: 10.1097/CHI.0b013e3181825b1f
Source: PubMed

ABSTRACT Children with attention-deficit/hyperactivity disorder (ADHD) consistently display increased intrasubject variability (ISV) in response time across varying tasks, signifying inefficiency of response preparation compared to typically developing (TD) children. Children with ADHD also demonstrate impaired response inhibition; inhibitory deficits correlate with ISV, suggesting that similar brain circuits may underlie both processes. To better understand the neural mechanisms underlying increased ISV and inhibitory deficits in children with ADHD, functional magnetic resonance imaging was used to examine the neural correlates of ISV during Go/No-go task performance.
Event-related functional magnetic resonance imaging was used to study 25 children with ADHD and 25 TD children ages 8 to 13 years performing a simplified Go/No-go task. Brain-behavior correlations were examined between functional magnetic resonance imaging activation and ISV within and between groups.
For TD children, increased rostral supplementary motor area (pre-supplementary motor area) activation during No-go events was associated with less ISV, whereas the reverse was true for children with ADHD for whom increased pre-supplementary motor area activation was associated with more ISV. In contrast, children with ADHD with less ISV showed greater prefrontal activation, whereas TD children with more prefrontal activation demonstrated more ISV.
These findings add to evidence that dysfunction of premotor systems may contribute to increased variability and impaired response inhibition in children with ADHD and that compensatory strategies eliciting increased cognitive control may improve function. However, recruitment of prefrontal resources as a compensatory mechanism for motor task performance may preclude the use of those prefrontal resources for higher order, more novel executive functions with which children with ADHD often struggle.

0 Followers
 · 
82 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The primary defining characteristic of a diagnosis of an eating disorder (ED) is the "disturbance of eating or eating-related behavior that results in the altered consumption or absorption of food" (DSM V; American Psychiatric Association, 2013). There is a spectrum, ranging from those who severely restrict eating and become emaciated on one end to those who binge and overconsume, usually accompanied by some form of compensatory behaviors, on the other. How can we understand reasons for such extremes of food consummatory behaviors? Recent work on obesity and substance use disorders has identified behaviors and neural pathways that play a powerful role in human consummatory behaviors. That is, corticostriatal limbic and dorsal cognitive neural circuitry can make drugs and food rewarding, but also engage self-control mechanisms that may inhibit their use. Importantly, there is considerable evidence that alterations of these systems also occur in ED. This paper explores the hypothesis that an altered balance of reward and inhibition contributes to altered extremes of response to salient stimuli, such as food. We will review recent studies that show altered sensitivity to reward and punishment in ED, with evidence of altered activity in corticostriatal and insula processes with respect to monetary gains or losses, and tastes of palatable foods. We will also discuss evidence for a spectrum of extremes of inhibition and dysregulation behaviors in ED supported by studies suggesting that this is related to top-down self-control mechanisms. The lack of a mechanistic understanding of ED has thwarted efforts for evidence-based approaches to develop interventions. Understanding how ED behavior is encoded in neural circuits would provide a foundation for developing more specific and effective treatment approaches.
    Frontiers in Behavioral Neuroscience 12/2014; 8:410. DOI:10.3389/fnbeh.2014.00410 · 4.16 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: ADHD is characterized by increased intra-individual variability in response times during the performance of cognitive tasks. However, little is known about developmental changes in intra-individual variability, and how these changes relate to cognitive performance. Twenty subjects with ADHD aged 7-24 years and 20 age-matched, typically developing controls participated in an fMRI-scan while they performed a go-no-go task. We fit an ex-Gaussian distribution on the response distribution to objectively separate extremely slow responses, related to lapses of attention, from variability on fast responses. We assessed developmental changes in these intra-individual variability measures, and investigated their relation to no-go performance. Results show that the ex-Gaussian measures were better predictors of no-go performance than traditional measures of reaction time. Furthermore, we found between-group differences in the change in ex-Gaussian parameters with age, and their relation to task performance: subjects with ADHD showed age-related decreases in their variability on fast responses (sigma), but not in lapses of attention (tau), whereas control subjects showed a decrease in both measures of variability. For control subjects, but not subjects with ADHD, this age-related reduction in variability was predictive of task performance. This group difference was reflected in neural activation: for typically developing subjects, the age-related decrease in intra-individual variability on fast responses (sigma) predicted activity in the dorsal anterior cingulate gyrus (dACG), whereas for subjects with ADHD, activity in this region was related to improved no-go performance with age, but not to intra-individual variability. These data show that using more sophisticated measures of intra-individual variability allows the capturing of the dynamics of task performance and associated neural changes not permitted by more traditional measures.
    01/2015; 7:132-41. DOI:10.1016/j.nicl.2014.11.014
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bilinguals' ability to control which language they speak and to switch between languages may rely on neurocognitive mechanisms shared with non-linguistic task switching. However, recent studies also reveal some limitations on the extent control mechanisms are shared across domains, introducing the possibility that some control mechanisms are unique to language. We investigated this hypothesis by directly comparing the neural correlates of task switching and language switching. Nineteen Spanish–English bilingual university students underwent a functional magnetic resonance imaging (fMRI) study employing a hybrid (event-related and blocked) design involving both color-shape switching and language switching paradigms. We compared the two switching tasks using within-subject voxel-wise t-tests for each of three trial types (single trials in single blocks, and stay and switch trials in mixed blocks). Comparing trial types to baseline in each task revealed widespread activation for single, stay, and switch trials in both color-shape and language switching. Direct comparisons of each task for each trial type revealed few differences between tasks on single and switch trials, but large task differences during stay trials, with more widespread activation for the non-linguistic than for the language task. Our results confirm previous suggestions of shared mechanisms of switching across domains, but also reveal bilinguals have greater efficiency for sustaining the inhibition of the non-target language than the non-target task when two responses are available. This efficiency of language control might arise from bilinguals' need to control interference from the non-target language specifically when not switching languages, when speaking in single- or mixed-language contexts.
    Neuropsychologia 11/2014; 66. DOI:10.1016/j.neuropsychologia.2014.10.037 · 3.45 Impact Factor