Neural correlates (ERP/fMRI) of voluntary selection in adult ADHD patients
Deficits in executive functions, e.g. voluntary selection, are considered central to the attention-deficit/hyperactivity disorder (ADHD). The aim of this simultaneous EEG/fMRI study was to examine associated neural correlates in ADHD patients. Patients with ADHD and healthy subjects performed an adapted go/nogo task including a voluntary selection condition allowing participants to freely decide, whether to press the response button. Electrophysiologically, response inhibition and voluntary selection led to fronto-central responses. The fMRI data revealed increased medial/lateral frontal and parietal activity during the voluntary selection task. Frontal brain responses were reduced in ADHD patients compared to controls during free responses, whereas parietal brain functions seemed to be unaffected. These results may indicate that selection processes are related to dysfunctions, predominantly in frontal brain regions in ADHD patients.
Available from: Carrie E Bearden
- "These findings suggest that RI-related deficits in activity within these regions may be useful endophenotypes that extend beyond the affected individuals of the family. While there are also reports of greater fronto-striatal activation (Dillo et al., 2010; Karch et al., 2010), or no differences in activation (Carmona et al., 2012; Congdon et al., 2014), during RI in ADHD patients as compared with controls, a review of this heterogeneous literature suggests that differences in the cognitive paradigm employed (e.g., Stop-signal task vs. Go/No-Go task), medication status, symptom severity, and small sample size may account for these discrepant findings. "
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22q11DS offers a compelling model to understand the neural substrates of attentional dysfunction.
First study directly comparing neural function in 22q11DS vs. ADHD patients
22q11DS and ADHD patients show a shared deficit in RI-related activation.
ADHD patients showed greater activity in the middle frontal gyrus than 22q11DS during RI.
Neural activity is inversely correlated with self-reported Cognitive Impulsivity in 22q11DS.
- "We included studies that fulfilled the following criteria: (a) employed fMRI and a motor inhibition task (stop-signal or go/no-go), (b) compared ADHD patients with healthy control subjects, (c) analyzed the data to assess motor response inhibition, and (d) reported the coordinates of activation areas normalized into a stereotaxic standardized space (such as Talairach space or Montreal Neurological Institute [MNI] space). We excluded studies on the following grounds: (a) the data analysis was not focused on motor response inhibition but rather on posterrors (Spinelli, Vasa, et al., 2011), inhibitory errors (Spinelli, Joel, et al., 2011), or selection conditions (Karch et al., 2010); (b) included overlapping samples (Suskauer, Simmonds, Caffo, et al., 2008a); or (c) used region-of-interest approaches (Liddle et al., 2011). Based on these criteria, 23 studies (listed in Table 1) were eligible for analysis, including 15 studies that used a go/no-go task (Booth et al., 2005; Dibbets, Evers, Hurks, Marchetta , & Jolles, 2009; Dillo et al., 2010; Durston, Mulder, Casey, Ziermans, & van Engeland, 2006; Durston et al., 2003; Epstein et al., 2007; Kooistra et al., 2010; Ma et al., 2012; Mulligan et al., 2011; Schulz et al., 2004; Schulz, Newcorn, Fan, Tang, & Halperin , 2005; Siniatchkin et al., 2012; Smith, Taylor, Brammer, Toone, & Rubia, 2006; Suskauer, Simmonds, Fotedar, et al., 2008b: and 1 study that used; Tamm, Menon, Ringel, & Reiss, 2004), seven studies that used a stop-signal task (Cubillo et al., 2010; Hart et al., 2014; Passarotti, Sweeney, & Pavuluri, 2010; Rubia et al., 2010; Rubia, Halari, Mohammad, Taylor, & Brammer , 2011; Rubia et al., 1999; Rubia, Smith, Brammer, Toone, & Taylor, 2005), and one study that used both (Sebastian et al., 2012). "
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ABSTRACT: Attention-deficit hyperactivity disorder (ADHD) has been recognized as a disorder of executive function, and a number of functional MRI (fMRI) studies have been conducted to investigate the altered brain activation patterns between ADHD patients and healthy controls. However, the findings across different studies have been inconsistent, and the different neural mechanisms between adults and children with ADHD remain unclear. The aim of this study was to perform a meta-analysis of fMRI studies to further investigate and compare the abnormalities in adults and children with ADHD during motor response inhibition.
Activation likelihood estimation (ALE) was used to investigate brain activation differences between ADHD patients and controls, and a subtraction meta-analysis was performed to compare adult and child patients.
Twenty-three studies met the inclusion criteria. Meta-analysis using ALE detected significantly decreased activation during response inhibition in ADHD in the supplementary motor area, insula, caudate, and precentral gyrus, as well as increased activation in the postcentral gyrus, inferior frontal gyrus, and precuneus. The activation decreases in the right caudate were greater in child ADHD patients than adult ADHD patients.
This meta-analysis identified dysfunction in several areas of the motor inhibition network that may play a role in the abnormal neural mechanisms of response inhibition in ADHD. The comparison of child and adult subgroups raises the possibility that the persistence of functional abnormalities of the caudate may be an important factor in whether ADHD persists. (PsycINFO Database Record
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Available from: Alexandra Sebastian
- "This approach is also designated " integration-byprediction " regarding that single-trial EEG/fMRI analyses usually employ EEG-derived regressors as predictors of the fMRI BOLD responses (for more detail see Debener et al., 2006; Eichele et al., 2009; Bland et al., 2011). In the process of isolating taskrelated single-trial EEG activity, different routines have been used: single-trial EEG features are extracted from single independent components (ICs) reflecting best the EEG component of interest (Debener et al., 2005; Feige et al., 2005; Mobascher et al., 2009), from artifact-cleaned EEG data using several electrodes (Eichele et al., 2005; Novitskiy et al., 2011) or single electrodes (Bénar et al., 2007; Mulert et al., 2008; Warbrick et al., 2009; Karch et al., 2010; Scheibe et al., 2010; Juckel et al., 2012; Baumeister et al., 2014). However, in the majority of studies components of interest were identified by visual inspection, which depends on subjective evaluation and can be biased by inter-and intra-individual variations of the evaluator. "
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ABSTRACT: Due to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen ERP component is specific for the targeted neurophysiological process on the group and single subject level. Here we introduce a newly developed data-driven analysis procedure that automatically selects task-specific electrophysiological independent components (ICs). We used single-trial simultaneous EEG/fMRI analysis of a visual Go/Nogo task to assess inhibition-related EEG components, their trial-to-trial amplitude variability, and the relationship between this variability and the fMRI. Single-trial EEG/fMRI analysis within a subgroup of 22 participants revealed positive correlations of fMRI BOLD signal with EEG-derived regressors in fronto-striatal regions which were more pronounced in an early compared to a late phase of task execution. In sum, selecting Nogo-related ICs in an automated, single subject procedure reveals fMRI-BOLD responses correlated to different phases of task execution. Furthermore, to illustrate utility and generalizability of the method beyond detecting the presence or absence of reliable inhibitory components in the EEG, we show that the IC selection can be extended to other events in the same dataset, e.g., the visual responses.
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