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Published Online: 29 June 2017

Defining the Neural Substrate of the Adult Outcome of Childhood ADHD: A Multimodal Neuroimaging Study of Response Inhibition

Abstract

Objective:

Understanding the neural processes tied to the adult outcome of childhood attention deficit hyperactivity disorder (ADHD) could guide novel interventions to improve its clinical course. It has been argued that normalization of prefrontal cortical activity drives remission from ADHD, while anomalies in subcortical processes are “fixed,” present even in remission. Using multimodal neuroimaging of inhibitory processes, the authors tested these hypotheses in adults followed since childhood, contrasting remitted against persistent ADHD.

Method:

Adult participants (persistent ADHD, N=35; remit-ted ADHD, N=47; never affected, N=99) were scanned with functional MRI (fMRI) (N=85), magnetoencephalography (N=33), or both (N=63) during a response inhibition task.

Results:

In fMRI analyses, during inhibition, right caudate anomalies reflected a childhood ADHD history and were present even among those who remitted. By contrast, differences related to adult outcome emerged in cortical (right inferior frontal and inferior parietal/precuneus) and cerebellar regions. The persistent ADHD group showed under-activation, whereas the remitted ADHD group did not differ significantly from the never-affected group. Magnetoencephalography showed that the association between adult symptom severity and prefrontal neuronal activity was confined to the time window covering the act of inhibition (300 ms–350 ms). Group differences in cerebellar and parietal neuronal activity occurred during the time window of performance monitoring processes (500 ms–600 ms).

Conclusions:

By combining fMRI and magnetoencephalography, the location and time window of neuronal activity that underpins the adult outcome of ADHD was pinpointed. Thus, the cortico-cerebellar processes tied to the clinical course of ADHD are separated from the subcortical processes that are not.
While some children “grow out” of attention deficit hyperactivity disorder (ADHD) by adulthood, many do not. Prospective studies have found that 15%−45% of children with ADHD will have the full syndrome into adulthood, and a further 25%−48% continue to have impairing symptoms (15). This variable clinical outcome prompts the following question: How does the adult brain differ in those whose ADHD persists after childhood compared with those who remit? Identifying the “plastic” brain regions that drive remission could provide targets for interventions to improve the clinical course of the disorder.
A prominent neurodevelopmental model posits that ADHD onset is linked to early aberrations in the striato-thalamic circuitry and associated deficits in “bottom-up” cognitive processes that persist into adulthood, regardless of clinical outcome (6). In support of this model, adult anomalies in subcortical, thalamic activation during response preparation (a bottom-up cognitive process) were found to reflect a childhood history of ADHD even in those who remitted (7). The other tenet of this model is that the variable adult outcome of ADHD is tied to developmental trajectories of the prefrontal cortex and associated “top-down” cognitive processes (6). This is in line with behavioral observations indicating that remission from ADHD is associated with normalization in higher-order cognitive functions (2). However, the delineation of the underlying prefrontal cortical circuitry and its links with adult outcome of childhood ADHD are currently not well characterized.
In the present study, we examined adults with a childhood history of ADHD followed prospectively. Using two imaging modalities, we delineated brain activation patterns during a “top-down” task of motor inhibition. We focused on motor inhibition because it has been viewed as a core deficit in ADHD, associated particularly with impulsivity (8, 9). We used the stop-signal task, which—in functional MRI (fMRI) studies—reliably activates both prefrontal cortical (in particular the inferior frontal cortex) and caudate regions, central to neurodevelopmental models of ADHD (1013). However, motor inhibition unfolds rapidly, in hundreds of milliseconds. While fMRI provides excellent spatial resolution, its temporal resolution is on the orders of seconds. Therefore, to provide better temporal resolution, we incorporated magnetoencephalography, an imaging technique that maps the magnetic fields evoked by populations of activated cortical neurons. Thus, magnetoencephalography provides a direct observation of neuronal activity during inhibitory processes, which has temporal resolution in the order of milliseconds.
We tested the hypothesis that the variable adult outcome of childhood ADHD is linked to differences in cortical activity. We primarily focused on associations between adult outcome of childhood ADHD and activity in the inferior frontal cortex during motor inhibition. By contrast, we predicted that a childhood history of ADHD would result in fixed anomalies in striatal processing that are present even among those who remit.

Method

Participants

A total of 181 individuals participated in the study, with 63 completing the fMRI and magnetoencephalography task versions, 85 completing the fMRI version only, and 33 completing the magnetoencephalography version only. Eighty-two participants (46%) had a childhood history of ADHD; the remainder had no history of ADHD (“never affected”). Current adult ADHD symptoms were assessed using the clinician-administered ADHD Rating Scale, Version IV, providing prompts appropriate for late adolescent and young adult groups (14). Seventy-three (89%) of the individuals with ADHD entered National Institutes of Health research studies as children, when they received a diagnosis using the Diagnostic Interview for Children and Adolescents for parents (15). Nine participants entered the study as young adults, and their childhood history of ADHD symptoms was confirmed through parental interviews. In line with DSM-5, the persistent ADHD group was defined by the presence of five or more impairing symptoms of inattention, five or more symptoms of hyperactivity-impulsivity, or both (16). Remission was defined by having four or fewer symptoms in each of the two symptom dimensions. The presence of other psychiatric disorders was established through the Structured Clinical Interview for DSM-IV Axis I Disorders (17). Two experienced clinicians (P.S. and W.S.) conducted the interviews (interrater reliabilities; kappa >0.9). Contrasts were made against 99 individuals never affected by ADHD, drawn from a longitudinal study of typical brain development. General exclusion criteria were a full-scale IQ <80 (estimated from age-appropriate versions of the Wechsler intelligence scales), neurological disorders known to affect brain structure, current substance dependence, or psychotic disorders. Psychostimulant medication was used among 48.6% of adults with persistent ADHD and 12.7% of those with four or fewer symptoms (remitted). To mitigate acute effects, all participants stopped psychostimulant medication the day prior to scanning. The institutional review board of the National Human Genome Research Institute approved the research protocol, and written informed consent was obtained.

Behavioral Task

The stop-signal task was a rapid, mixed-trial, event-related paradigm used in previous studies (18, 19). On all trials, a fixation cross appeared centrally against a black background for 500 ms, followed by a white “X” or “O” go signal for 1,000 ms. Participants were instructed to press the right button on a button box for an “X” and the left button for an “O.” During the unexpected, infrequent stop trials (25% of trials, randomly dispersed), after the “X” or “O” appeared the background changed from black to red (stop signal), and participants were instructed to inhibit their motor response. The first stop signal appeared 250 ms after the go signal. In subsequent stop trials, the time interval between the go and stop signals (i.e., inhibit delay) adapted to individual performance. It became 50 ms longer after a successful trial, making it harder to inhibit, and 50 ms shorter after an unsuccessful trial, making it easier to inhibit. This algorithm ensured that the task was equally challenging for all individuals, resulting in approximately 50% successful and 50% failed stop trials. Trials were separated by 750 ms, with 86 trials in each run. Participants completed four runs (344 trials) in the fMRI and eight runs (688 trials) in the magnetoencephalography experiment.

fMRI Acquisition

Gradient echo planar images were acquired on a 3-T GE Signa scanner (General Electric, Milwaukee, Wisc.): 26 contiguous, 4 mm axial slices obtained with single-shot gradient echo T2*-weighting, aligned to the anterior-posterior commissure. Images were aligned to a T1-weighted anatomical scan (see the data supplement accompanying the online version of this article).

Magnetoencephalography Acquisition

Magnetoencephalography data were acquired using a 275-gradiometer whole-helmet magnetoencephalography system (CTF Systems, Coquitlam, British Columbia, Canada) at 600 Hz. The locations of three fiducial points (nasial and left/right auricular) were determined for localization of magnetoencephalography signal sources.

Data Analysis

Behavioral data.

Performance was measured by 1) go trial accuracy and reaction time, 2) stop trial accuracy, 3) “inhibit delay” or the time interval between the onset of the go and stop signals, and 4) the stop-signal reaction time calculated as the mean go reaction time minus the mean inhibit delay in participants who inhibited successfully on 50% of the stop trials (8, 19). If a participant’s stop trial accuracy deviated from 50%, an interpolation algorithm was used to compute stop-signal reaction time: the mean inhibit delay was subtracted from the go reaction time at the Xth percentile of the go reaction times, where X is the participant’s percent accuracy on stop trials.

fMRI data.

fMRI data were analyzed using Analysis of Functional Neuroimages (https://afni.nimh.nih.gov/). Preprocessing included slice timing correction, motion correction, spatial normalization to Talairach space, and smoothing (kernel full width at half maximum=8 mm) (see the online data supplement).
In the event-related fMRI analysis, brain activation was considered for three contrasts. First, successful inhibition compared with successful go trials: this contrast holds constant (successful) performance but differs on task demand and motor response. Second, failed inhibition compared with successful go: these two conditions have the same motor response but differ on task demand and performance. Third, failed compared with successful inhibition: this contrast holds the task demands constant, but the conditions differ on motor response and performance. These contrasts parse out neural activation pertaining to task demands, performance success, and motor response and identify circuitry mediating successful and failed inhibition. Incorrect go trials were very infrequent and not included in the analyses.
We focused on two regions of interest implicated in motor inhibition by meta-analyses of fMRI and human lesion studies, namely the inferior frontal cortex and the caudate (10, 11, 20). These were defined using the Talairach-Tournoux Atlas, applied to each participant’s normalized brain.
Differences between the persistent, remitted, and never-affected adults were calculated for each of the three contrasts using factorial analyses of variance (ANOVAs). Given the four regions of interest, significance was set at p<0.05/4=0.01; significant group differences were examined in pairwise, post hoc analyses using Fisher’s least significant difference. Direct comparisons between adults with and without a childhood history of ADHD were made by categorizing individuals according to the presence or absence of a childhood diagnosis for ADHD using t tests. We additionally explored associa-tions with the number of adult inattentive and hyperactive-impulsive symptoms using correlation analysis.
Finally, we conducted exploratory whole-brain analyses. Results were corrected for multiple testing using the most current version of 3dClustSim (https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dClustSim.html), which corrects for issues with parametric approaches for preventing type 1 errors (21). Significance was declared at a voxel-wise p value <0.05 and a cluster-corrected alpha level <0.05 (k=1, minimum cluster size=512 voxels).
We repeated all analyses comparing those with childhood ADHD (i.e., combining persistent and remitted participants into one group) against the group of never-affected adults.

Magnetoencephalography data.

Using MNE-Python (22) and Analysis of Functional Neuroimages, eye blinks and other subject-related artifacts in the raw signal were removed, and data were visually inspected to rule out other anomalies. Because we were interested in the neural processes underlying inhibition, only inhibit trials were analyzed further. Each trial was parsed into individual epochs such that time point 0 marked the onset of the stop signal. Data were averaged across trials within condition (successful inhibition, unsuccessful inhibition) and then source-localized using DICS (23) for the frequency bands: delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), low gamma (30–55 Hz), and high gamma (65–100 Hz). Further details are presented in the online data supplement. ANOVAs compared neural responses between the outcome groups, and correlation analyses tested for associations with ADHD symptoms. We applied a false discovery rate (q=0.05) to correct for multiple comparisons over each brain image (24). Robustness analysis tested whether results held when we considered possible effects of psychostimulant medication.

Results

Do Cortical Rather Than Subcortical Anomalies Reflect the Adult Outcome of Childhood ADHD?

The three outcome groups did not differ behaviorally in the fMRI task version (Table 1) but did in the magnetoencephalography version, which had twice as many trials (N=688 trials). In the magnetoencephalography version, the persistent ADHD group was less accurate on go trials and had a longer stop signal response time compared with the never-affected group (Table 2).
TABLE 1. Behavioral Performance and Characteristics of Adults With Persistent ADHD, Adults With Remitted ADHD, and Never-Affected Individuals on the Functional MRI (fMRI) Version of the Stop-Signal Taska
CharacteristicNever Affected (N=84)Remitted (N=40)Persistent (N=24)Analysis
 MeanSDMeanSDMeanSDTest Statisticp
Percent accuracy go trials89.4310.1789.4910.9891.788.360.530.59
Percent accuracy stop trials50.378.6553.3712.1150.947.371.360.26
Mean go response time (ms)714.84107.98708.62102.11663.31120.991.660.19
Stop signal response time (ms)a271.8795.53241.1065.32243.0064.242.340.1
Inhibit delay (ms)450.64114.73489.43121.43433.56144.981.970.14
Age (years)24.464.0924.333.8523.343.950.740.48
 N%N%N%Test Statisticp
Sex (male)4857.12562.51145.81.710.42
 MeanSDMeanSDMeanSDTest Statisticp
Inattentive symptomsNA 2.031.315.921.74–10.15<0.001
Hyperactive-impulsive symptomsNA 1.431.454.082.76–4.36<0.001
 N%N%N%Test Statisticp
Psychostimulant useNA 4101562.519.81<0.001
Presence of comorbidityNA 225512500.150.7
a
Calculated as the mean go reaction time at the Xth percentile minus the mean inhibit delay. X is the participant’s percent accuracy on stop trials.
TABLE 2. Behavioral Performance and Characteristics of Adults With Persistent ADHD, Adults With Remitted ADHD, and Never-Affected Individuals on the Magnetoencephalography Version of the Stop-Signal Taska
CharacteristicNever Affected (N=46)Remitted (N=26)Persistent (N=25)Analysis
 MeanSDMeanSDMeanSDTest StatisticpComparison
Percent accuracy go trials86.6510.5079.8111.9880.678.564.540.01Never affected > remitted, persistent
Percent accuracy stop trials47.397.1246.8112.1449.026.440.460.63 
Mean go response time (ms)735.4192.80749.1794.31765.7447.781.060.35 
Stop signal response time (ms)a296.9679.57305.6498.67353.2390.273.460.04Persistent > never affected
Inhibit delay (ms)437.42127.40442.74178.39414.93111.540.30.74 
Age (years)23.312.9624.793.8623.734.181.460.24 
 N%N%N%Test Statisticp 
Sex (male)2247.81661.51352.01.260.53 
 MeanSDMeanSDMeanSDTest Statisticp 
Inattentive symptomsNA 1.881.396.401.68–10.45<0.001 
Hyperactive-impulsive symptomsNA 1.151.354.042.91–4.52<0.001 
 N%N%N%Test Statisticp 
Psychostimulant useNA 311.513529.690.002 
Presence of comorbidityNA 1557.712480.480.49 
a
Calculated as the mean go reaction time at the Xth percentile minus the mean inhibit delay. X is the participant’s percent accuracy on stop trials.
We tested the hypothesis that activation in the cortical (inferior frontal cortex) but not subcortical region of interest (caudate) was tied to the degree of persistence of childhood ADHD into adulthood. First, categorical contrasts were drawn between the persistent ADHD, remitted ADHD, and never-affected groups. In the fMRI data, group differences emerged in inferior frontal cortex activation during failed inhibition when contrasted against either successful inhibition (left: F=4.37, df=2, 145, p=0.01; right [fell short of statistical significance]: F=3.67, df=2, 145, p=0.03) or go trials (left: F=5.07, df=2, 145, p=0.007). The group effects were due to reduced inferior frontal cortex activity during failed inhibition in the persistent group compared with both the remitted group (right: p=0.01; left: p=0.004) and the never-affected group (left: p=0.009) (Figure 1). The remitted and never-affected groups did not differ significantly (p>0.05). As predicted, no outcome group differences emerged for the subcortical regions of interest and the left and right caudate.
FIGURE 1. Mean Activation Differences for Failed Compared With Successful Inhibition Contrast Between the Persistent ADHD, Remitted ADHD, and Never-Affected Groupsa
a The graphs show activation differences in the A) left inferior frontal cortex, with a similar pattern emerging in the B) right inferior frontal cortex.
We followed up this finding with symptom-level analyses. Higher levels of adult hyperactivity-impulsivity were associated with decreased activation in the bilateral inferior frontal cortex during failed inhibition contrasted against either successful inhibition (right: r=–0.27, p=0.03; left: r=–0.28, p=0.03) or go trials (left: r=–0.33, p=0.009) (see Figure S1 in the online data supplement). There were no significant associations with symptoms of inattention.
In the whole-brain fMRI analysis, no clusters showed significant differences between the three groups. However, we identified a bilateral cerebellar cluster (799 voxels) where increased adult hyperactive-impulsive symptoms were associated with decreased activation during successful inhibition (contrasted against go trials) (Figure 2). An inferior parietal cluster (492 voxels) showed a nearly significant association (cluster-corrected α<0.06) with adult hyperactive-impulsive symptoms.
FIGURE 2. Regions in the Functional MRI Task Where Activation Was Associated With Severity of Adult Hyperactive-Impulsive Symptoms in the Successful Inhibition vs. Go Contrast (Clinical Group, N=64)a
a The cerebellar cluster shown (799 voxels) reveals peak activation in the right cerebellum (Montreal Neurological Institute coordinates x=−26.2, y=78, z=−28.5). Increased hyperactive-impulsive symptoms in adulthood were associated with decreased activation during successful inhibition.
In summary, as hypothesized, anomalous activity in the inferior frontal cortex, but not the caudate, was associated with the adult outcome of childhood ADHD during failed inhibition. Links also emerged between the degree of adult persistence of childhood hyperactive-impulsive symptoms and activation during inhibitory processes in both the right inferior frontal cortex and cerebellum.

Do Subcortical Rather Than Cortical Anomalies Reflect Childhood ADHD?

Next, we categorized individuals according to the presence or absence of a childhood diagnosis for ADHD, predicting differential activation in the subcortical but not cortical regions of interest. The group with a history of childhood ADHD showed reduced right caudate activity when successfully inhibiting (t=2.28, df=1, 146, p=0.02) and increased activity in the right caudate when failing to inhibit (t=–2.18, df=1, 146, p=0.03). As hypothesized, no differences were found for the cortical region of interest (inferior frontal cortex) (all p values >0.1). Furthermore, we did not detect any differences that reflected a childhood history of ADHD in whole-brain analyses.

The Patterns of Neuronal Activation Tied to the Adult Outcome of Childhood ADHD

Given our fMRI findings, we used magnetoencephalography to characterize further the cortical inhibitory processes that reflect adult outcome groups, with additional focus on associations with the degree of adult persistence of childhood hyperactivity-impulsivity. We examined the neural processes relating to successful and failed inhibitory events separately, using exploratory whole-brain analysis.
We found significant differences between the three groups during successful inhibition. These differences occurred in two frequency bands at 500 ms–600 ms after the stop signal in cerebellar and precuneal/parietal regions; these regions overlapped with those identified in the fMRI analysis. Specifically, in the delta frequency band the three groups differed in evoked responses 550 ms–600 ms after the stop signal (minimum: F=6.05, df=2, 93, p<0.05, false discovery rate-corrected) in two clusters. The first cluster (697 voxels) encompassed the cerebellum (Figure 3); the second cluster (69 voxels) was centered on the left precuneus (see Figure S2 in the online data supplement). Pairwise group analyses showed that neural activity was highest in never-affected individuals and lowest in the persistent ADHD group, with the remitted group showing intermediate levels of activation.
FIGURE 3. Cerebellar Regions From Magnetoencephalography Whole-Brain Analysis Showing Differential Neural Response in Relation to Adult Outcome During Successful Inhibitiona
a The images in the panels show A) cerebellar cluster in the delta band where group differences emerged at 550 ms–600 ms following the stop signal (699 voxels centered on the left cerebellum; Montreal Neurological Institute [MNI] coordinates: x=16.9, y=47.1, z=−28.5); and B) cerebellar cluster in the theta band where group differences emerged at 500 ms–550 ms following the stop signal (1,102 voxels centered on the right cerebellum; MNI coordinates: x=−9.3, y=53.6, z=−31.5).
In the theta band, the three outcome groups also showed differences in neural activity at 500 ms–550 ms after the stop signal (minimum: F=5.25, df=2, 93, p<0.05, false discovery rate-corrected) in a bilateral cerebellar cluster (1,002 voxels) that overlapped with the cerebellar cluster found in the delta band (see Figure 3). As in the delta band, the lowest amplitude was observed in the persistent ADHD group, and the highest in the never-affected group, with the remitted group showing intermediate levels of activation. Further clusters showing differences between outcome groups were noted in the right inferior parietal cluster (341 voxels) and right cuneus/posterior cingulate cluster (172 voxels) (see Figure S3 in the online data supplement).
In analyses of adult symptoms of hyperactivity-impulsivity, we detected associations with neural responses in the right inferior prefrontal cortex during successful inhibition; this region overlapped with the cortical region of interest in the fMRI analysis. This theta band cluster (42 voxels; minimum: t=4.06, p<0.05, false discovery rate-corrected) was confined to the time window during which successful inhibition typically occurs (i.e., 300 ms–350 ms after the stop signal). During this “inhibitory” time window, individuals with persistent ADHD exhibited decreased theta activity within the right inferior frontal cortex, compared with those who had remitted (Figure 4). In summary, the degree of persistence into adulthood of hyperactive-impulsive symptoms was associated with neuronal activity during the time window of the act of inhibition.
FIGURE 4. Neuronal Activity and Time Course of Average Magnetic Field Response During Successful Inhibitiona
a The top panel shows regions from whole-brain magnetoencephalography analyses where neuronal activity during successful inhibition was associated with the severity of hyperactive-impulsive symptoms persisting from childhood. This signal was detected in the theta band and centered on the right inferior prefrontal cortex (42 voxels; peak Montreal Neurological Institute coordinates: x=−38.0, y=−38.4, z=2.3). The lower graph shows the time course of the average magnetic field response in the right inferior frontal cortical region during successful inhibition. The green line indicates adults with remittent attention deficit hyperactivity disorder (ADHD), and the orange line indicates adults with persistent ADHD. The time window of the significant group difference is highlighted in the shaded box and occurred at 300 ms–350 ms following the stop signal.

Discussion

By combining fMRI and magnetoencephalography, we have pinpointed the location and time window of neuronal activity that is tied to the adult outcome of childhood ADHD. This detailed spatiotemporal mapping of the neural substrate tied to remission could guide more targeted interventions for improving the clinical course of ADHD. We separated the cortico-cerebellar processes that underpin adult outcome from the striatal processes that do not. Specifically, we found inhibition-related anomalies in the inferior frontal cortex to be associated with the adult outcome of childhood ADHD, particularly the persistence of hyperactive-impulsive, rather than inattentive, symptoms. Leveraging the exquisite temporal resolution of magnetoencephalography, we pinpointed these prefrontal anomalies to the time window covering the act of inhibition. Additional activations in cerebellar and precuneal/inferior parietal regions also reflected adult outcome. Here, magnetoencephalography indicated that neuronal activation differences occurred relatively late after the onset of the stop sign, compatible with disruption of cerebellar performance monitoring processes. Not all neural differences were tied to adult outcome. Subcortical, right caudate anomalies reflected a childhood history of ADHD and were present even in those who had remitted as adults.

The Neurobiology of the Variable Adult Outcome of Childhood ADHD

What do these findings tell us about the processes underpinning adult remission compared with the persistence of childhood ADHD? Our results support a model in which prefrontally mediated cognitive processes are tied to the adult outcome of ADHD (6, 10). In general, the remitted ADHD group did not differ from the never-affected group, compatible with the concept that remission is underpinned by a normalization of inferior frontal cortex activity. Although not suggested by the original model (6), it is noteworthy that cerebellar and parietal regions also showed partial normalization with remission from ADHD. Also noteworthy is that adult severity of hyperactive-impulsive symptoms rather than inattentive symptoms accounted for these findings. This is in line with an influential model of ADHD, which links inhibitory deficits with hyperactive-impulsive symptoms. While there is empirical support from neuropsychological studies for this model (2528), there are also some conflicting reports (2931). Prior neuroimaging studies have primarily examined ADHD-related inhibitory deficits using diagnostic categories and did not include separate analyses of hyperactive-impulsive and inattentive symptom dimen-sions. Mapping the neural substrate of inhibition onto symptom dimensions, as we attempted in the present study, is an area of active interest. Additionally, more recent models have linked inattention, particularly deficient sustained attention and increased distractibility, with intrusions of the default mode network (prominent during introspective processing) into neural activity tied to task performance (3234). A future goal is to examine whether such dysregulated interactions between brain networks account for the persistence of inattention into adulthood.
As expected, only caudate anomalies were related to childhood symptoms of ADHD irrespective of later outcome. This is consonant with a recent, independent finding of atypical subcortical—specifically thalamic—activity among adults with a childhood diagnosis of ADHD, regardless of adult status (7). This supports the concept that fixed subcortical abnormalities drive the onset of ADHD and remain relatively unchanged throughout development and recovery (6). We further demonstrate that these subcortical anomalies are not only present during bottom-up cognitive processes but also in higher-order processes of cognitive control.

Mapping the Patterns of Neuronal Activation Sensitive to the Adult Outcome of Childhood ADHD

Using magnetoencephalography, we showed that the link between adult hyperactive-impulsive symptoms and right inferior prefrontal neuronal activation was confined to 300 ms–350 ms following the stop signal. This time window overlaps with the time it takes an individual to successfully stop an already initiated response (3537). This confirms prior event-related potential studies in healthy individuals showing that right inferior frontal cortical activation during successful inhibition occurs during this time window (38). Here, we further demonstrate that this epoch of prefrontal inhibitory processing is sensitive to the adult outcome of childhood ADHD.
Activation differences associated with adult ADHD symptoms extended to the cerebellum, in both fMRI and magnetoencephalography. This finding is congruent with the role of the cerebellum in response inhibition. Prior positron emission tomography studies found cerebellar activation during the inhibition of prepotent responses in Stroop tasks, while deficits in the Stroop task are seen in patients with cerebellar lesions (39, 40). Similarly, slower go-signal reaction times in the go/no-go task have been linked to the extent of cerebellar lesions (41). Such human lesion studies implicate the cerebellum in response inhibition and align with previous reports of subtle cerebellar anatomic anomalies in adults with persistent ADHD (42). Using magnetoencephalography, we additionally find that ADHD symptoms were associated with cerebellar activity in a time window 500 ms–600 ms after the stop signal. This time window points to anomalies in the processing of feedback around successful inhibition, which is reliant on prefrontal-cerebellar interactions (43, 44). It suggests that adults with persistent symptoms show impairment in such processing, whereas those who have remitted may have more typical performance monitoring.
Electrophysiological differences that tracked with adult outcome lay in the theta and delta bands. Interestingly, event-related potential studies also show augmented power in both theta and delta frequencies during inhibition (45). Specifically, frontal theta activation has been observed during response inhibition (46, 47), while delta oscillations are observed during the evaluation of motor inhibition (46). Indeed, frontal-midline theta is associated with a wide range of cognitive processes, including working memory, spatial navigation, and episodic memory, thus indicating a general role in action monitoring (46). Our findings support the emerging picture that both theta and delta bands are sensitive both to increased cognitive demands during response inhibition and to the severity of adult symptoms of ADHD (48).

Limitations

This study has several limitations. First, magnetoencephalography is best suited to detect cortical activation and could not specify the characteristics of the caudate anomalies we found using fMRI. Second, nine participants were not followed from childhood but recruited in adulthood. Consequently, we had to establish the presence of a childhood history of ADHD retrospectively. Nevertheless, whenever possible, we also collected collateral information about childhood history and the results held when we reanalyzed the sample excluding the individuals who entered the study as adults (see the online data supplement). Third, follow-up assessments in adulthood were not blind. Consequently, there may have been a bias toward underestimating ADHD symptoms in adults who entered as typically developing children and toward overestimating adult ADHD symptoms in those who entered the study as children with the diagnosis. This is of relevance given the recent interest in the possibility of adult-onset ADHD (4951). Finally, regional neural activation is partly task-dependent (52), and it is interesting to consider whether the same general finding of cortical anomalies in those with persistent symptoms, but typical activity in remitters, would emerge using different cognitive probes. One pertinent study found greater integration of thalamo-cortical activity in remitters compared with individuals whose symptoms persisted during a task of response preparation, while childhood history was characterized by a general hypoactivation (7). This adult imaging study embedded within a longitudinal study starting in childhood provides hypotheses about mechanisms of recovery. Ideally, these should be tested and refined through the future collection of longitudinal imaging data.

Clinical Implications

We show that the “plasticity” underpinning remission from ADHD lies in inferior prefrontal/cerebellar rather than striatal regions. This implies that cognitive or pharmacological interventions targeting prefrontal or cerebellar functions (such as executive or temporal information processes) may prove more successful than interventions that “train” more automatic processes, supported by the striatum. In devising novel interventions, it is noteworthy that both fMRI and magnetoencephalography have been successfully used as real-time neurofeedback devices, allowing participants to modulate task-related brain activation and oscillatory rhythms associated with awareness and attention (53, 54). For example, it is possible to provide real-time magnetoencephalography feedback on the right inferior frontal gyrus during critical time windows for response inhibition (55, 56). Thus, the tools we use to map the cognitive deficits underlying persistent symptoms of ADHD could feasibly also be used for their remediation. Finally, the findings are consonant with studies that tie recovery from ADHD to a convergence toward typical brain structure and function (5).

Supplementary Material

File (appi.ajp.2017.16111313.ds001.pdf)

References

1.
Biederman J, Petty CR, Evans M, et al: How persistent is ADHD? A controlled 10-year follow-up study of boys with ADHD. Psychiatry Res 2010; 177:299–304
2.
Halperin JM, Trampush JW, Miller CJ, et al: Neuropsychological outcome in adolescents/young adults with childhood ADHD: profiles of persisters, remitters and controls. J Child Psychol Psychiatry 2008; 49:958–966
3.
Klein RG, Mannuzza S, Olazagasti MA, et al: Clinical and functional outcome of childhood attention-deficit/hyperactivity disorder 33 years later. Arch Gen Psychiatry 2012; 69:1295–1303
4.
Molina BS, Hinshaw SP, Swanson JM, et al: The MTA at 8 years: prospective follow-up of children treated for combined-type ADHD in a multisite study. J Am Acad Child Adolesc Psychiatry 2009; 48:484–500
5.
Shaw P, Malek M, Watson B, et al: Trajectories of cerebral cortical development in childhood and adolescence and adult attention-deficit/hyperactivity disorder. Biol Psychiatry 2013; 74:599–606
6.
Halperin JM, Schulz KP: Revisiting the role of the prefrontal cortex in the pathophysiology of attention-deficit/hyperactivity disorder. Psychol Bull 2006; 132:560–581
7.
Clerkin SM, Schulz KP, Berwid OG, et al: Thalamo-cortical activation and connectivity during response preparation in adults with persistent and remitted ADHD. Am J Psychiatry 2013; 170:1011–1019
8.
Logan GD, Schachar RJ, Tannock R: Impulsivity and inhibitory control. Psychol Sci 1997; 8:60–64
9.
Rubia K: The dynamic approach to neurodevelopmental psychiatric disorders: use of fMRI combined with neuropsychology to elucidate the dynamics of psychiatric disorders, exemplified in ADHD and schizophrenia. Behav Brain Res 2002; 130:47–56
10.
Aron AR, Poldrack RA: The cognitive neuroscience of response inhibition: relevance for genetic research in attention-deficit/hyperactivity disorder. Biol Psychiatry 2005; 57:1285–1292
11.
Aron AR, Robbins TW, Poldrack RA: Inhibition and the right inferior frontal cortex. Trends Cogn Sci 2004; 8:170–177
12.
Band GP, van Boxtel GJ: Inhibitory motor control in stop paradigms: review and reinterpretation of neural mechanisms. Acta Psychol (Amst) 1999; 101:179–211
13.
Rubia K, Russell T, Overmeyer S, et al: Mapping motor inhibition: conjunctive brain activations across different versions of go/no-go and stop tasks. NeuroImage 2001; 13:250–261
14.
DuPaul GJ, Power JD, Anastopouls AA, et al: ADHD Rating Scale-IV: Checklists, Norms and Clinical Interpretation. New York, Guilford Press, 1998
15.
Reich W: Diagnostic Interview for Children and Adolescents (DICA). J Am Acad Child Adolesc Psychiatry 2000; 39:59–66
16.
American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC, American Psychiatric Publishing, 2013
17.
First MB, Spitzer RL, Gibbon M, et al: User’s Guide for the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I): Clinician Version. Washington, DC, American Psychiatric Publishing, 1997
18.
Deveney CM, Connolly ME, Jenkins SE, et al: Striatal dysfunction during failed motor inhibition in children at risk for bipolar disorder. Prog Neuropsychopharmacol Biol Psychiatry 2012; 38:127–133
19.
Leibenluft E, Rich BA, Vinton DT, et al: Neural circuitry engaged during unsuccessful motor inhibition in pediatric bipolar disorder. Am J Psychiatry 2007; 164:52–60
20.
Hart H, Radua J, Nakao T, et al: Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects. JAMA Psychiatry 2013; 70:185–198
21.
Eklund A, Nichols TE, Knutsson H: Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci USA 2016; 113:7900–7905
22.
Gramfort A, Gramfort A, Luessi M, et al: MEG and EEG data analysis with MNE-Python. Front Neurosci 2013; 7:267
23.
Laaksonen H, Kujala J, Salmelin R: A method for spatiotemporal mapping of event-related modulation of cortical rhythmic activity. Neuroimage 2008; 42:207–217
24.
Benjamini Y, Hochberg Y: Multiple hypotheses testing with weights. Scand J Stat 1997; 24:407–418
25.
Houghton S, Douglas G, West J, et al: Differential patterns of executive function in children with attention-deficit hyperactivity disorder according to gender and subtype. J Child Neurol 1999; 14:801–805
26.
Lockwood KA, Marcotte AC, Stern C: Differentiation of attention-deficit/hyperactivity disorder subtypes: application of a neuropsychological model of attention. J Clin Exp Neuropsychol 2001; 23:317–330
27.
Nigg JT, Blaskey LG, Huang-Pollock CL, et al: Neuropsychological executive functions and DSM-IV ADHD subtypes. J Am Acad Child Adolesc Psychiatry 2002; 41:59–66
28.
Solanto MV, Gilbert SN, Raj A, et al: Neurocognitive functioning in AD/HD, predominantly inattentive and combined subtypes. J Abnorm Child Psychol 2007; 35:729–744
29.
Chhabildas N, Pennington BF, Willcutt EG: A comparison of the neuropsychological profiles of the DSM-IV subtypes of ADHD. J Abnorm Child Psychol 2001; 29:529–540
30.
Pasini A, Paloscia C, Alessandrelli R, et al: Attention and executive functions profile in drug naive ADHD subtypes. Brain Dev 2007; 29:400–408
31.
Thorell LB: Do delay aversion and executive function deficits make distinct contributions to the functional impact of ADHD symptoms? A study of early academic skill deficits. J Child Psychol Psychiatry 2007; 48:1061–1070
32.
Sonuga-Barke EJS, Castellanos FX: Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neurosci Biobehav Rev 2007; 31:977–986
33.
Fassbender C, Zhang H, Buzy WM, et al: A lack of default network suppression is linked to increased distractibility in ADHD. Brain Res 2009; 1273:114–128
34.
Rosenberg MD, Finn ES, Scheinost D, et al: A neuromarker of sustained attention from whole-brain functional connectivity. Nat Neurosci 2015
35.
Boehler CN, Münte TF, Krebs RM, et al: Sensory MEG responses predict successful and failed inhibition in a stop-signal task. Cereb Cortex 2009; 19:134–145
36.
Curtis CE, Cole MW, Rao VY, et al: Canceling planned action: an fMRI study of countermanding saccades. Cereb Cortex 2005; 15:1281–1289
37.
Logan GD, Cowan WB: On the ability to inhibit thought and action: A theory of an act of control. Psychol Rev 1984; 91:295
38.
Schmajuk M, Liotti M, Busse L, et al: Electrophysiological activity underlying inhibitory control processes in normal adults. Neuropsychologia 2006; 44:384–395
39.
Neau JP, Arroyo-Anllo E, Bonnaud V, et al: Neuropsychological disturbances in cerebellar infarcts. Acta Neurol Scand 2000; 102:363–370
40.
Taylor SF, Kornblum S, Lauber EJ, et al: Isolation of specific interference processing in the Stroop task: PET activation studies. Neuroimage 1997; 6:81–92
41.
Brunamonti E, Chiricozzi FR, Clausi S, et al: Cerebellar damage impairs executive control and monitoring of movement generation. PLoS One 2014; 9:e85997
42.
Mackie S, Shaw P, Lenroot R, et al: Cerebellar development and clinical outcome in attention deficit hyperactivity disorder. Am J Psychiatry 2007; 164:647–655
43.
Picazio S, Ponzo V, Koch G: Cerebellar control on prefrontal-motor connectivity during movement inhibition. Cerebellum 2016; 15:680–687
44.
Rustemeier M, Koch B, Schwarz M, et al: Processing of positive and negative feedback in patients with cerebellar lesions. Cerebellum 2016; 15:425–438
45.
De Jong R, Coles MG, Logan GD, et al: In search of the point of no return: the control of response processes. J Exp Psychol Hum Percept Perform 1990; 16:164–182
46.
Huster RJ, Enriquez-Geppert S, Lavallee CF, et al: Electroencephalography of response inhibition tasks: functional networks and cognitive contributions. Int J Psychophysiol 2013; 87:217–233
47.
Isabella S, Ferrari P, Jobst C, et al: Complementary roles of cortical oscillations in automatic and controlled processing during rapid serial tasks. Neuroimage 2015; 118:268–281
48.
Harper J, Malone SM, Bernat EM: Theta and delta band activity explain N2 and P3 ERP component activity in a go/no-go task. Clin Neurophysiol 2014; 125:124–132
49.
Agnew-Blais JC, Polanczyk GV, Danese A, et al: Evaluation of the persistence, remission, and emergence of attention-deficit/hyperactivity disorder in young adulthood. JAMA Psychiatry 2016; 73:713–720
50.
Caye A, Rocha TB, Anselmi L, et al: Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood: Evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry 2016; 73:705–712
51.
Moffitt TE, Houts R, Asherson P, et al: Is adult ADHD a childhood-onset neurodevelopmental disorder? Evidence from a four-decade longitudinal cohort study. Am J Psychiatry 2015; 172:967–977
52.
Smith AB, Taylor E, Brammer M, et al: Task-specific hypoactivation in prefrontal and temporoparietal brain regions during motor inhibition and task switching in medication-naive children and adolescents with attention deficit hyperactivity disorder. Am J Psychiatry 2006; 163:1044–1051
53.
Okazaki YO, Horschig JM, Luther L, et al: Real-time MEG neurofeedback training of posterior alpha activity modulates subsequent visual detection performance. Neuroimage 2015; 107:323–332
54.
Sacchet MD, Mellinger J, Sitaram R, et al: Volitional control of neuromagnetic coherence. Front Neurosci 2012; 6:189
55.
Sudre G, Parkkonen L, Bock E, et al: rtMEG: a real-time software interface for magnetoencephalography. Comput Intell Neurosci 2011; 2011:327953
56.
Florin E, Bock E, Baillet S: Targeted reinforcement of neural oscillatory activity with real-time neuroimaging feedback. Neuroimage 2014; 88:54–60

Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 867 - 876
PubMed: 28659040

History

Received: 28 November 2016
Revision received: 30 January 2017
Revision received: 8 March 2017
Accepted: 20 March 2017
Published online: 29 June 2017
Published in print: September 01, 2017

Keywords

  1. Cognitive Neuroscience
  2. Attention Deficit Hyperactivity Disorder
  3. Adult Development

Authors

Details

Eszter Szekely, Ph.D.
From the Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Md.; and the Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health, Bethesda, Md.
Gustavo P. Sudre, Ph.D.
From the Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Md.; and the Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health, Bethesda, Md.
Wendy Sharp, M.S.W.
From the Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Md.; and the Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health, Bethesda, Md.
Ellen Leibenluft, M.D.
From the Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Md.; and the Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health, Bethesda, Md.
Philip Shaw, B.M., B.Ch., Ph.D. [email protected]
From the Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Md.; and the Section on Bipolar Spectrum Disorders, Emotion and Development Branch, National Institute of Mental Health, Bethesda, Md.

Notes

Address correspondence to Dr. Shaw ([email protected]).

Author Contributions

Drs. Szekely and Sudre contributed equally to this study.

Competing Interests

The authors report no financial relationships with commercial interests.

Funding Information

National Human Genome Research Institute10.13039/100000051: Z01 HG200378
Supported by the Intramural Programs of the National Human Genome Research Institute and the National Institute of Mental Health. This work utilized the computational resources of the National Institutes of Health HPC Biowulf cluster (http://hpc.nih.gov).

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