Atypical Activations of Fronto-Cerebellar Regions During Forethought in Parents of Children With ADHD

Abstract

Objective: Although several studies suggest heritability of ADHD, only a few investigations of possible associations between people at risk and neural abnormalities in ADHD exist. In this study, we tested whether parents of children with ADHD would show atypical patterns of cerebral activations during forethought, a feature of working memory. Method: Using Functional Magnetic Resonance Imaging (fMRI), we compared 12 parents of children with ADHD and 9 parents of control children during a forethought task. Results: Parents of children with ADHD exhibited significantly increased neural activations in the posterior lobes of the cerebellum and in the left inferior frontal gyrus, relative to parents of control children. Conclusion: These findings are consistent with previous reports in children and suggest the fronto-cerebellar circuit’s abnormalities during forethought in parents of children with ADHD. Future studies of people at risk of ADHD are needed to fully understand the extent of the fronto-cerebellar heritability.

Keywords

ADD/ADHD parental functioning fMRI executive function cerebellum

ADHD is a frequent neurodevelopmental condition that persists into adulthood in more than half of the cases (Barkley, Fischer, Smallish, & Fletcher, 2002). Genetic factors have been implicated in ADHD suggesting a high heritability of the disorder (Faraone et al., 2005). Studies have demonstrated increased rates of ADHD (Biederman, Faraone, Spencer, & Wilens, 1993; Faraone, 2004; Sprich, Biederman, Crawford, Mundy, & Faraone, 2000) as well as increased comorbidities with other mental health problems and neuropsychological deficits (Durston, Mulder, Casey, Ziermans, & van Engeland, 2006; Kuntsi et al., 2010; Mulder et al., 2008; Poissant & Rapin, 2012; Slaats-Willemse, Swaab-Barneveld, de Sonneville, & Buitelaar, 2007) among siblings and parents of children with ADHD. Neuropsychological literature has reported deficits in executive functions (inhibition, working memory, self-regulation, temporal processing) and altered attentional network in children with ADHD (see Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005, for a review). Cerebral imagery data show alterations in the architecture and function of the prefrontal cortex (PFC) related to cognitive/executive impairments. ADHD has been associated with hypofunction of fronto-striatal and cingulo-fronto-parietal network circuits normally supporting executive functions (Cortese et al., 2012; Cubillo, Halari, Smith, Taylor, & Rubia, 2012; Dickstein, Bannon, Castellanos, & Milham, 2006).

Apart from examining fronto-striatal functioning, a growing literature on ADHD has revealed some cerebellar abnormalities. The cerebellum is involved in motor coordination as well as cognitive control by transporting information to frontal regions via connections in the thalamus. Cerebellar dysfunction has been observed in children with ADHD; however, the results have not been consistent, showing either hyper- or hypo-activation of this structure across studies. For example, during tasks involving temporal processing such as temporal foresight, children with ADHD have demonstrated reduced activation compared with control subjects in dorsal and ventrolateral PFCs, supplementary motor area (SMA), anterior cingulate cortex (ACC), and cerebellum (Durston et al., 2006; Rubia et al., 2009; Smith, Taylor, Brammer, Halari, & Rubia, 2008). In contrast, Dickstein and colleagues (2006) found increased activation of the right posterior cerebellum in the ADHD-affected population during response inhibition and working memory. A recent study by Poissant, Mendrek, and Senhadji (2012) confirms an increased activation of the cerebellar vermis and a hypoactivation of the PFC during a forethought task in children with ADHD. Forethought is described as the ability to conjecture possible future scenarios related to present events (Fuster, 1997; Goldman-Rakic, 1995). According to Barkley’s (2006) hierarchic model, forethought is dependent on working memory; it is associated with anticipation and self-regulation, and is under the control of inhibition functioning. Forethought is hence included in executive functioning that has been shown to be defective in ADHD (Willcutt et al., 2005). This suggests that children with ADHD are less able to determine, plan, and time future actions and events (Barkley, 2006). Poissant et al. (2012) proposed the existence of a compensatory network consisting of an overactive cerebellum (in replacement of a hypo-functioning PFC) in children with ADHD to facilitate speculation of possible future scenarios of events.

Neuroimaging findings in adults with ADHD have been even more inconsistent and less frequent, due in part to the underestimation of ADHD diagnosis in the adult population (Kessler et al., 2006). On one hand, adults with ADHD have shown decreased activations in fronto-striatal, fronto-parietal, and cerebellar networks during interference inhibition, sustained attention (Burgess et al., 2010; Schneider et al., 2010), and working memory (Ehlis, Bahne, Jacob, Herrmann, & Fallgatter, 2008; Valera, Faraone, Biederman, Poldrack, & Seidman, 2005; Wolf et al., 2009). Other studies, however, observed increased activation in the same neural circuits during inhibition and working memory (Epstein et al., 2007; for reviews, see Cubillo & Rubia, 2010, and Schneider, Retz, Coogan, Thome, & Rosler, 2006). Despite these inconsistencies, studies in adults with ADHD suggest that brain abnormalities observed in ADHD children may persist into adulthood (Cubillo et al., 2012). For example, Schneider and colleagues (2006) indicate similarities between functional abnormalities in children and adults in the posterior lobes of the cerebellum.

The vast majority of familial studies pertain to siblings of children with ADHD (Durston et al., 2006; Kuntsi et al., 2010; Mulder et al., 2008; Slaats-Willemse et al., 2007). Less frequent studies of parents of children with ADHD indicate a heritable component in the etiology of the pathology (Casey et al., 2007; Epstein et al., 2007; Hale et al., 2010; McLoughlin et al., 2011). A diffusion tensor imaging (DTI) study conducted by Casey et al. (2007) on parents–children dyads during an inhibition task showed that the right prefrontal fiber circuit was correlated to a greater extent with Inferior Frontal Gyrus (IFG) activation within ADHD dyads than within control dyads. The authors interpreted these results as evidence of an inheritance of the fronto-striatal dysfunction in ADHD.

Numerous task-based functional imaging studies have revealed altered cerebral activity in ADHD in the context of various aspects of inhibition, working memory, attention allocation, and motor function. Recent research goes beyond the fronto-striatal circuitry investigation, and there is an emerging interest in cerebellar functions in ADHD (Cortese et al., 2012; Durston et al., 2007; Mulder et al., 2008).

Aims and Hypotheses

Working memory and inhibition deficits in ADHD have been observed in relation to a decreased ability to predict future events (Barkley, 2006; Poissant et al., 2012). Yet, research on forethought in ADHD has been rare and is still unclear whether it can be seen as a transmissible trait of ADHD. Although studies in children with ADHD are more numerous and consistent, the emerging evidence from cerebral functional imaging studies in adult ADHD suggests that brain abnormalities observed in children with ADHD may persist into adult ADHD (Cubillo et al., 2012). To our knowledge, only a few studies have used the same behavioral and functional imaging paradigms across pediatric and adult samples (Casey et al., 2007; Epstein et al., 2007). Even though the cognitive and neurological profiles of ADHD are better known in children, we believe that parents at risk of ADHD will present the same kind of neurologic deficits as children with ADHD given the same cognitive task. Consequently, we aimed to extend to parents previous cerebral findings in children on a forethought task initially developed by Poissant et al. (2012). We compared parents of children with ADHD with parents of control children during forethought. We predicted group differences in fronto-striatal and fronto-cerebellar circuits between parents of ADHD children and parents of control children. According to the findings observed in children with ADHD, we predicted that parents of ADHD children would show decreased activation of the PFC and increased activation of the cerebellum relative to control parents.

Method

Sample

Parents were recruited via a children database (Poissant et al., 2012) as well as through the Montreal association for parents of children with ADHD and a Montreal psycho-pediatric clinic specialized in learning and attention. Nine biological parents of control children (Control Parents) and 12 biological parents of children with ADHD (ADHD parents) were recruited. Control parents were parents of children without any Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association [APA], 1994) diagnosis (APA, 2000), and ADHD parents were parents of children with a diagnosis of ADHD. The criterion to form the ADHD-Parents group was thus initially based on the presence of a diagnosis in their children while not necessarily in parents. By using this more lenient criterion, we intended to include a population of adults, possibly underdiagnosed, that is not usually considered in familial studies. Among ADHD parents, four had been formally diagnosed with ADD or ADHD in the past whereas the others showed borderline clinical profiles (average t scores above 65 on two attention/inattention scales; see below and Table 1). These scores demonstrate that, on average, parents of children with ADHD experience mainly inattention symptoms.

Table 1.

Descriptive Statistics of Parent’s Characteristics.

	Age (year: month)	VIQ	PIQ	FSIQ	CAARS_Inatt^a	CAARS_Hyper^a	ASR_Att^a
ADHD parents (n = 12)
M	42:4	101.8	111.4	107.3	65.67	54.3	65.8
SD	6:1	10.28	9.13	10.11	20.2	11	13.18
Range	29-54	86-120	96-126	94-126	33-90	32-68	51-94
Control parents (n = 9)
M	46:1	107.2	116.7	113.2	52.5	50.5	56
SD	6:8	9.96	8.11	9.2	10.2	5.8	8.4
Range	40-59	92-120	101-128	96-126	41-70	41-57	50-72
Levene’s F		0.007	0.215	0.217	4.66*	2.02	0.871
T(19)	1.34	1.2	1.37	1.37	−1.84^†	−0.789	−1.654

Note. VIQ = verbal IQ; PIQ = performance IQ; FSIQ = full-scale IQ, all measured with Kaufman Brief Intelligence Test; CAARS_Inatt = T score for Inattention subscale; CAARS_Hyper = T score for the Hyperactivity/Impulsivity subscale; ASR_Att = T score for the Attention subscale; CAARS = Conners’ Adult ADHD Rating Scales–Self-Report; ASR = Adult Self-report.

Three control parents did not fill the CAARS and ASR; control = 6, ADHD = 12, and t(17).

†

p < .1. *p < .05; all ps are two-tailed.

All participants were right-handed and native speakers of French. The control group (CTRL) was composed of five women and four men (M age = 46.1 years old; SD = 6.8). The ADHD group was composed of seven women and five men (M age = 42.4 years old; SD = 6.1). There was no significant age difference between the two groups, t(19) = 1.34, p = .19. The exclusion criteria for both groups included (a) history of neurological disorder, traumatic brain injury with loss of consciousness for more than 5 min, and (b) drug/alcohol abuse or addiction. Current diagnosis or a history of psychiatric disorder (self or close family) warranted exclusion for the control group. Other DSM-IV Axis I diagnoses apart from ADD or ADHD warranted exclusion for the ADHD group. Verbal, performance, and full-scale IQ (VIQ, PIQ, FSIQ) were evaluated with the Kaufman Brief Intelligence Test (K-Bit; Kaufman & Kaufman, 1990). The mean FSIQ score were as follows: Control = 113.2 (SD = 9.2); ADHD = 107.3 (SD = 10.11); t(19) = 1.37, p = .19 (Table 1). The presence of ADHD symptoms and comorbidities was assessed with the Conners’ Adult ADHD Rating Scales–Self-Report (CAARS; Conners, Erhardt, & Sparrow, 1999) and the Adult Self-report (ASR 18-59; Achenbach & Rescorla, 2003). The CAARS (Conners et al., 1999) comprises eight scales including those based on the DSM-IV (APA, 2000) and an ADHD general index (inattention and hyperactivity/impulsivity). The ASR 18-59 (Achenbach & Rescorla, 2003) assesses comorbidities and/or other primary deficits: depression, anxiety, somatization, withdrawal, ADHD, and antisocial behavior based on the DSM-IV. Both questionnaires take gender into account. Table 1 reports the mean t scores and range of scores of each group for the CAARS Inattention and Hyperactivity/Impulsivity subscales as well as for the ASR Attention subscale. No other psychological disorder such as anxiety or depression was found in any participant, as revealed by both questionnaires. All subjects gave written informed consent and met Functional Magnetic Resonance Imaging (fMRI) compatibility criteria. The study was ethically approved by both Université du Québec Montreal and Institut Universitaire de Gériatrie de Montreal (IUGM). Participants received CAN$50 as compensation.

Experimental Procedure

A forethought task involving 56 illustrated stories was used. Half of the stories represent congruent (CO) and the other half represent incongruent (INCO) sequences of actions. For example, in the CO situation, the participant sees a man with a basket walking toward an apple tree farm (Slide 1) followed by the picture of the same man with an apple in his hand (Slide 2). In the INCO situation, the participant sees the same first slide followed by a slide illustrating the same man but walking with a carrot in his hand. Being plausible in itself (gathering carrots), Slide 2 in INCO situation is not what one would expect from Slide 1. Participants had to answer if “yes” (CO) or “no” (INCO) the sequences of actions make sense according to their expectation. All stories (28 CO:28 INCO) were presented in blocks of seven stories (4 CO blocks vs. 4 INCO blocks, with 6:1 ratios) in a randomized manner. A rest period of 16 s was accorded between blocks with a total series lasting 9 min. For a full description of the stimuli creation and the experimental procedure, see Poissant et al. (2012).

Image Acquisition

All scans were performed at the IUGM. Participants were ready for the scan session after practice in a mock scanner. Echo-planar fMRIs were collected with a Siemens TRIO 3.0 Tesla MRI scanner. The main acquisition parameters were Repetition Time (TR) of 2 s, Echo Time (TE) of 30 ms, flip angle 90°, 64 × 64 voxels, and field of view 192 mm (voxel size 3 × 3 × 3 mm³). Two-hundred seventy images were continuously acquired over a total duration of 540 s. Each whole brain volume consisted of 32 contiguous axial slices (slice thickness: 3 mm, interslice gap: 0.9 mm). Prior to the functional scans, an anatomical whole brain MR scan was obtained for anatomical co-registration.

Behavioral Data Analysis

The maximum correct response score was 56. Participants’ answers were classified into five categories: (a) hits (good answer in authorized delay), (b) miss (error in authorized delay), (c) omission (no answer during the authorized delay), (d) reaction time (RT; mean in ms), and (e) reaction time-per-hit (mean RT/hit score). For hits, miss, and omission measurements, we used the nonparametric statistical Kruskal–Wallis (χ²) test to assess diagnostic group comparison (ADHD vs. CTRL) and interaction effect (Diagnostic × Task) as well as two-tailed signed rank tests (S) for task comparison (CO vs. INCO). We performed independent sample t tests on the two measures of time (RT and RT/hit) and repeated measures ANOVAs to assess task and interaction effects. Potential covariates such as chronological age, gender, and intellectual abilities (VIQ, PIQ, FSIQ) were dropped from analyses because of their absence of effect in determining diagnostic group differences.

fMRI Data Analysis

To match the analyses of the children cohort (Poissant et al., 2012), we used images provided by the scanner with prospective acquisition correction. Functional images were first pre-processed using SPM8 (Wellcome Institute of London, United Kingdom). Images were realigned, normalized to the Montreal Neurological Institute (MNI) brain template, and were spatially smoothed with a 12 × 12 × 12 mm³ full width at half maximum Gaussian filter. The details of the exploratory whole brain statistical analysis are explained in Poissant et al. (2012). All the normalized and smoothed single-subject images were computed for the two conditions (CO and INCO), and each subject’s data were convolved with the canonical hemodynamic response function. Additional regressors representing estimated head movements (translation and rotation with 6 degrees of freedom) were added as covariates of no interest. INCO presents an unexpected outcome or novelty effect. The contrast between the two conditions (INCO–CO) reveals the detection of incongruency and was used to obtain the measure of forethought. One sample t tests were conducted to reveal the cerebral activations associated with the contrast of interest within each group. To reduce Type II error, the threshold level for statistical significance was set up at p = .001 uncorrected for multiple comparisons with no voxel limitations. Two samples t tests were performed for group comparisons at a threshold level of p = .005 uncorrected for multiple comparisons with a cluster threshold of 10 voxels. This more liberal threshold was used because the expected effects are broad but weak (Wolf et al., 2009). Anatomical regions were defined by the anatomical automatic labeling for SPM8 (aal; Tzourio-Mazoyer et al., 2002) with further help from Schmahmann et al. (1999) for cerebellar labeling.

Results

Behavioral Results

Table 2 presents the mean performance of each group on behavioral assessments. Kruskal–Wallis tests (χ²) indicated no significant group effects on the Hit, Miss, and Omission measures. Signed rank tests revealed no significant main effects for the task’s conditions—CO versus INCO (Hit: S = 18, p = .18; Miss: S = 18, p = .23; Omission: S = 18, p = 1)—nor interaction (task × diagnostic group; Hit: χ² = 1.46, p = .69; Miss: χ² = 2.64, p = .45; Omission: χ² = .09, p = .9). As for the measures of time, significant condition effects were found for both dependent variables: RT, F(1, 16) = 27, p < .001, and RT/hit, F(1, 16) = 25.14, p < .001. The CO condition obtained lower scores (faster RT) compared with the INCO condition. We neither found any interaction (task × group) for time dependent variables—RT: F(1, 16) = .15, p = .7; RT/Hit: F(1, 16) = .07, p = .8—nor any significant main effect of group.

Table 2.

Hits, Miss, Omission, Reaction Time (RT), and Reaction Time Per Hit (RT/H) for ADHD Parents and Control Parents.

	Hit		Miss		Omiss		RT		RT/H
Group	CO	INCO	CO	INCO	CO	INCO	CO	INCO	CO	INCO
ADHD (n = 10)
M	26.2	25.9	0.8	0.9	1.1	1.2	998.26	1106.1	38.93	43.94
SD	2.2	2.6	1.1	1.2	1.9	1.8	241.82	232.38	12.46	14.47
Range	21-28	20-28	0-3	0-3	0-6	0-5	645.5-1,344.1	774.1-1,535.8	23-64	27.6-76.8
Control (n = 8)
M	26.9	26.1	0.4	1	0.7	0.9	865.42	990.8	32.62	38.18
SD	1.3	1	0.5	0.7	0.8	1	263.86	214.74	11.26	9.35
Range	25-28	25-28	0-1	0-2	0-2	0-2	510-1,209.6	719.78-1,237.5	18.2-48.4	27.1-49.5
χ²	0.32	0.3	0.17	0.44	0.006	0.01
Levene’s F							0.26	0.128	0.03	0.1
T							1.34	−1.11	−1.08	−1.11

Note. CO–Hit = good answer in authorized delay for coherent condition; INCO–Hit = good answer in authorized delay for incoherent condition; CO–Miss = error in authorized delay for coherent condition; INCO–Miss = error in authorized delay for incoherent condition; CO–Omiss = no answer during the authorized delay for coherent condition; INCO–Omiss = no answer during the authorized delay for incoherent condition. CO–RT = mean reaction time (ms) for coherent condition; INCO–RT = mean reaction time (ms) for incoherent condition; CO–RT/H = mean reaction time (ms) per hit for coherent condition; INCO–RT/H = mean reaction time (ms) per hit for incoherent condition. Due to technical problems, responses of two ADHD parents and one control parent were not recorded.

p < .05. **p < .01, all ps are two-tailed.

fMRI Results

One sample t tests were performed on the contrast INCO versus CO for each group separately (Table 3). For the control-parent group, results revealed cerebral activations in the right middle frontal gyrus (MFG; BA 9). The ADHD-parent group exhibited neuronal activations in the bilateral anterior lobes (AL) of the cerebellum, the right calcarine fissure (BA 17), the right posterior lobe (PL) of the cerebellum, and the left IFG (BA 47). Within-group activation maps are shown in Figures 1A and 1B.

Table 3.

Within-Group and Between-Group Brain Activations for the Contrast INCO–CO for the Control and the ADHD Groups.

Region of activation	Brodmann area (BA)	Peak MNI coordinates (x y z)	N of voxels	T max
Controls parents
R-Middle Frontal Gyrus	9	45 29 31	5	5.05
ADHD parents
L-Cerebellar Culmen (AL)		0 −52 −23	74	5.13
L-Cerebellar AL; lobules IV, V		−24 −34 −35	26	5.71
R-Cerebellar AL; lobules IV, V		18 −34 −20	12	4.85
R-Calcarine Fissure	17	30 −61 4	7	4.91
R-Cerebellar PL; lobule VIII		39 −58 −50	6	4.36
L-Inferior Frontal Gyrus	47	−51 32 −11	5	4.34
Controls parents–ADHD parents
No activated voxels
ADHD parents–Control parents
L-Cerebellar PL; lobule X		−21 −34 −38	35	3.5
R-Cerebellar PL; lobule VIIb		42 −58 −50	29	3.99
R-Cerebellar PL; lobule IX		9 −55 −38	22	3.15
L-Inferior Frontal Gyrus	45	−54 20 −2	20	3.69
L-Cerebellar PL; crus II		−27 −76 −41	18	3.82

Note. MNI = Montreal Neurological Institute; N voxels = number of voxels; T max = maximum t value per cluster; L = left; R = right; AL = anterior lobe; PL = posterior lobe.

All ps ≤ .001.

Figure 1.

Within-group activation maps for control parents and ADHD parents (A and B) and between-group activation maps (C).

Two sample t tests performed on the INCO versus CO contrast revealed no greater cerebral activations in the control group compared with the ADHD group (Table 3). ADHD parents showed increased activation of several cerebellum regions: the bilateral PL (lobule VIIb & crus II; pyramis), the left lobule X (nodule), and the right lobule IX (uvula), as well as the left IFG (BA 45) compared with the control group (see Figure 1C).

Discussion

This study examined cerebral activations during a crucial aspect of executive functioning related to anticipation of events by using a forethought task in 12 parents of children with ADHD and in 9 parents of typically developing (control) children. Our main purpose was to extend previous findings in children with or without ADHD. By adding a biological aspect, “parents” rather than solely “adults,” we also intended to further the comprehension of ADHD in families. As expected, controls, either children (Poissant et al., 2012) or parents, rely on a frontal circuitry for forethought. In contrast, the ADHD-parent group exhibited activations in several cerebellum sites and in the IFG. Parents of children with ADHD demonstrated more diffuse areas of cerebral activation with a higher number of voxels to execute the forethought task with the same rate of success, compared with control parents. This was confirmed by increased neural activations mostly in bilateral parts of the PL of the cerebellum and in left IFG in ADHD parents relative to control parents. The finding of increased cerebellar activation in ADHD parents relative to control parents is consistent with previous findings in ADHD children (Poissant et al., 2012) as well as findings in the ADHD literature (Cubillo et al., 2012; Dickstein et al., 2006). Overall, this suggests that forethought leads to atypical fronto-cerebellar activations in ADHD in children and parents. The cerebellum (specifically its PLs) is involved in higher order functions such as learning, memory, visual–spatial, and executive functions (Desmond & Fiez, 1998). Garavan, Hester, Murphy, Fassbender, and Kelly (2006) examined brain activity related to individual differences in inhibitory control. They found that slow pacers (i.e., long RTs) compared with fast pacers activated significantly more PL. In our task, ADHD parents tended to show longer RT compared with control parents. Interestingly, they also observed that the level of absentmindness (high vs. low) was correlated with increased activation in the PL of the cerebellum. Absentmindness can be seen as a deficit in sustained attention, a major symptom in adult ADHD, also observed in our study. Increased activation of the PL in ADHD parents could therefore reveal a higher propensity to absentmindness during the task.

Activation of the IFG during the forethought task in ADHD parents replicated findings in children with ADHD, which also showed IFG activation during forethought (Poissant et al., 2012). This suggests that forethought is associated with inferior frontal activation in people concerned with ADHD condition both for diagnosed children and parents of children with ADHD having inattention problems. However, the laterality of the IFG activation differed, as it was right-sided in children and left-sided in parents. Functional imaging in children supports right-sided abnormalities in children with ADHD; yet, it is not as clear in ADHD adult population (Schneider et al., 2006). Our finding is coherent with this model and supported by Epstein et al. (2007) who found a right-sided IFG activation in ADHD youths and a left-sided activation in ADHD parents during a response inhibition, a task known to be hierarchically related to working memory and forethought (Barkley, 2006). They interpreted the change of laterality as a passing of frontal regions that may evolve through maturity from a right-sided to a more bilateral circuit in adulthood. Yet, the finding of increased left-IFG activation in parents of children with ADHD relative to control parents is somewhat surprising as many studies point to IFG hypoactivation during executive function tasks in ADHD (Cubillo et al., 2012; Dickstein et al., 2006; Epstein et al., 2007). The novel use of parents of children with ADHD mostly characterized with inattention symptoms may explain the discrepancy between these findings.

Some studies have shown similar behavioral performance and yet neural activation differences between control and ADHD groups (McLoughlin et al., 2011) as in our study. This pattern of results suggests an underlying “neural processing atypicality” and stresses the limits of diagnoses only based on behavioral assessment. Neuronal activity characteristics can be a more sensitive indicator of the presence of ADHD (McLoughlin et al., 2011; Paloyelis, Mehta, Kuntsi, & Asherson, 2007). Parents of children with ADHD seem to rely on alternative brain regions such as the cerebellum, and possibly different cognitive strategies, to successfully perform the forethought task. This confirms that the ability to perform, as well as control, results in altered neuronal activations (Durston, 2003). Overall, increased activations of the PL of the cerebellum and of the left IFG in ADHD parents suggest that forethought elicits high cerebral demands in this population and that these regions may act as compensatory mechanisms for a deficient fronto-striatal circuit.

Limitations

The small sample sizes used in our study may have affected the power to detect significant group differences in behavioral performances. The use of first-degree relatives (parents) as samples limited our recruitment capacity. Yet, having a well-defined restricted sample is also the strength of our study in terms of people at risk and heritability investigation. Future studies of parents at risk of ADHD or with a formal diagnosis of ADHD would reinforce the findings of an altered fronto-cerebellar circuit inheritable in ADHD during forethought.

In the present study, we prioritized the inclusion of biological parents (formally diagnosed or not) to form the ADHD-parents group. Our criterion was primarily based on the presence of a formal diagnosis of ADHD in children of these parents. Yet, given the heritability of ADHD and the outcome of our screening measures, it is reasonable to consider ADHD parents as ADHD-adult-at-risk, a much less studied population. By considering non-formally diagnosed parents, a situation we suspect to be frequent in families with children with ADHD (Kessler et al., 2006), we draw rising attention to this specific population and improve the ecological validity of this research. By considering biological parents, we planned to catch a glimpse at a biological transmission, or at least familial transmission, of ADHD between parents and children. The downside of this choice is a limitation in extrapolation to existing results with more homogeneous adult ADHD.

In summary, we collected brain-imaging data in 12 parents of children with ADHD and 9 parents of control children during a forethought task. Significant increased neural activations in bilateral parts of the PL of the cerebellum and in the left IFG were observed in ADHD parents relative to control parents. This result supports fronto-cerebellar circuits’ abnormalities during forethought in parents at risk of ADHD. Moreover, this finding is consistent with previous findings in ADHD children (Poissant et al., 2012) suggesting that forethought leads to atypical cerebellar activations in ADHD, possibly used as compensatory mechanisms. Although there is a growing body of literature on cerebellum abnormalities related to ADHD in children, few studies have concentrated on possible impairments in adults with ADHD (Schneider et al., 2006). More studies on parent–child dyads are also needed to fully understand the extent of the fronto-cerebellar heritability.

Footnotes

Acknowledgements

We would like to thank the Parents Aptes à Négocier le Déficit d’Attention association (PANDA; Québec ADHD Support Group) as well as the Centre de Consultation Psychopédagogique (CCPP; learning disorders clinic) for their collaboration in the recruitment process. We would also like to thank the Institute Universitaire de Gériatrie de Montréal (IUGM) for their technical assistance with Functional Magnetic Resonance Imaging (fMRI).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Social Sciences and Humanities Research Council of Canada (SSHRC) as well as by the Fonds de Recherche en Santé du Québec (FRSQ): 410-2010-1787.

Author Biographies

Lucile Rapin is a postdoctorate researcher at the linguistic department of UQÀM. Her work focuses on the neurocognitive correlates of various psychiatric disorders such as ADHD, schizophrenia and ASD. Specifically, her research looks at speech production and perception processes as well as control monitoring in such processes.

Hélène Poissant is a professor at the Education Department of UQÀM. She has been studying ADHD and its cognitive processes for years. She is also interested in metacognition processes and their links to a better teaching and learning experience.

Adrianna Mendrek is a psychology professor at Bishop University. Her research themes center around neurocognitive function in psychopathology; functional neuroanatomy of psychiatric disorders and motivation, emotion and reward circuitry.

References

Achenbach

T. M.

Rescorla

L. A.

(2003). Manual for the ASEBA adult forms & profiles. Burlington: University of Vermont, Research Center for Children, Youth, & Families.

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.

Barkley

R. A.

(2006). Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment. (3rd ed.). New York, NY: Guilford Press.

Barkley

R. A.

Fischer

Smallish

Fletcher

(2002). The persistence of attention-deficit/hyperactivity disorder into young adulthood as a function of reporting source and definition of the disorder. Journal of Abnormal Psychology, 111, 279-289.

Biederman

Faraone

S. V.

Spencer

Wilens

(1993). Patterns of psychiatric comorbidity, cognition, and psychosocial functioning in adults with attention deficit hyperactivity disorder. American Journal of Psychiatry, 150, 1792-1798.

Burgess

G. C.

Depue

B. E.

Ruzic

Willcutt

E. G.

Y. P.

Banich

M. T.

(2010). Attentional control activation relates to working memory in attention-deficit/hyperactivity disorder. Biological Psychiatry, 67, 632-640.

Casey

B. J.

Epstein

J. N.

Buhle

Liston

Davidson

M. C.

Tonev

S. T.

. . . Glover

(2007). Frontostriatal connectivity and its role in cognitive control in parent–child dyads with ADHD. American Journal of Psychiatry, 164, 1729-1736.

Conners

C. K.

Erhardt

Sparrow

E. P.

(1999). Conners’ Adult ADHD Rating Scales: Technical manual. New York, NY: Multi-Health Systems.

10.

Cortese

Kelly

Chabernaud

Proal

Di Martino

Milham

M. P.

Castellanos

F. X.

(2012). Toward systems neuroscience of ADHD: A meta-analysis of 55 fMRI studies. American Journal of Psychiatry, 169, 1038-1055.

11.

Cubillo

Halari

Smith

Taylor

Rubia

(2012). A review of fronto-striatal and fronto-cortical brain abnormalities in children and adults with Attention Deficit Hyperactivity Disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attention. Cortex, 48, 194-215.

12.

Cubillo

Rubia

(2010). Structural and functional brain imaging in adult attention-deficit/hyperactivity disorder. Expert Review of Neurotherapeutics, 10, 603-620.

13.

Desmond

J. E.

Fiez

J. A.

(1998). Neuroimaging studies of the cerebellum: Language, learning and memory. Trends in Cognitive Sciences, 2, 355-362.

14.

Dickstein

Bannon

Castellanos

Milham

M. P.

(2006). The neural correlates of attention deficit hyperactivity disorder: An ALE meta-analysis. Journal of Child Psychology and Psychiatry, 47, 1051-1062.

15.

Durston

(2003). A review of the biological bases of ADHD: What have we learned from imaging studies? Mental Retardation and Developmental Disabilities Research Reviews, 9, 184-195.

16.

Durston

Davidson

M. C.

Mulder

M. J.

Spicer

J. A.

Galvan

Tottenham

. . . Casey

B. J.

(2007). Neural and behavioral correlates of expectancy violations in attention-deficit hyperactivity disorder. Journal of Child Psychology and Psychiatry, 48, 881-889.

17.

Durston

Mulder

Casey

B. J.

Ziermans

van Engeland

(2006). Activation in ventral prefrontal cortex is sensitive to genetic vulnerability for attention-deficit hyperactivity disorder. Biological Psychiatry, 60, 1062-1070.

18.

Ehlis

A. C.

Bahne

C. G.

Jacob

C. P.

Herrmann

M. J.

Fallgatter

A. J.

(2008). Reduced lateral prefrontal activation in adult patients with attention-deficit/hyperactivity disorder (ADHD) during a working memory task: A functional near-infrared spectroscopy (fNIRS) study. Journal of Psychiatric Research, 42, 1060-1067.

19.

Epstein

J. N.

Casey

B. J.

Tonev

S. T.

Davidson

M. C.

Reiss

A. L.

Garrett

. . . Spicer

(2007). ADHD- and medication-related brain activation effects in concordantly affected parent–child dyads with ADHD. Journal of Child Psychology and Psychiatry, 48, 899-913.

20.

Faraone

S. V.

(2004). Genetics of adult attention-deficit/hyperactivity disorder. Psychiatric Clinics of North America, 27, 303-321.

21.

Faraone

S. V.

Perlis

R. H.

Doyle

A. E.

Smoller

J. W.

Goralnick

J. J.

Holmgren

M. A.

Sklar

(2005). Molecular genetics of attention-deficit/hyperactivity disorder. Biological Psychiatry, 57, 1313-1323.

22.

Fuster

J. M.

(1997). The prefrontal cortex (3rd ed.). Philadelphia, PA: Lippincott.

23.

Garavan

Hester

Murphy

Fassbender

Kelly

(2006). Individual differences in the functional neuroanatomy of inhibitory control. Brain Research, 1105, 130-142.

24.

Goldman-Rakic

P. S.

(1995). Anatomical and functional circuits in prefrontal cortex of non-human primates: Relevance to epilepsy. In Jasper

Riggio

Goldman-Racik

P. S.

(Eds.), Epilepsy and the functional anatomy of the frontal lobe (pp. 85-96). New York, NY: Raven.

25.

Hale

T. S.

Smalley

Dang

Hanada

Macion

Loo

S. K.

(2010). ADHD familial loading and abnormal EEG alpha asymmetry in children with ADHD. Journal of Psychiatric Research, 44, 605-615.

26.

Kaufman

A. S.

Kaufman

N. L.

(1990). Kaufman Brief Intelligence Test. Circle Pines, MN: American Guidance Services.

27.

Kessler

R. C.

Adler

Barkley

Biederman

Conners

C. K.

Demler

. . . Zalavsky

A. M.

(2006). The prevalence and correlates of adult ADHD in the United States: Results from the National Comorbidity Survey Replication. American Journal of Psychiatry, 163, 716-723.

28.

Kuntsi

Wood

A. C.

RijSDijk

Johnson

K. A.

Andreou

Albrecht

. . . Asherson

(2010) Separation of cognitive impairments in attention deficit hyperactivity disorder into two familial factors. Archives of General Psychiatry, 67, 1159-1166.

29.

McLoughlin

Asherson

Albrecht

Banaschewski

Rothenberger

Brandeis

Kuntsi

(2011). Cognitive-electrophysiological indices of attentional and inhibitory processing in adults with ADHD: Familial effects. Behavioral and Brain Functions, 7(1), Article 26.

30.

Mulder

M. J.

Baeyens

Davidson

M. C.

Casey

B. J.

van den Ban

van Engeland

Durston

(2008). Familial vulnerability to ADHD affects activity in the cerebellum in addition to the prefrontal systems. Journal of American Academy of Child & Adolescent Psychiatry, 47, 68-75.

31.

Paloyelis

Mehta

M. A.

Kuntsi

Asherson

(2007). Functional MRI in ADHD: A systematic literature review. Expert Review of Neurotherapeutics, 7, 1337-1356.

32.

Poissant

Mendrek

Senhadji

(2012). Neural correlates of forethought in attention-deficit and hyperactivity disorder (ADHD). Journal of Attention Disorders. doi:10.1177/1087054712439418

33.

Poissant

Rapin

(2012). Facteurs de risque dans le Trouble Déficitaire de l’Attention et de l’Hyperactivité: étude familial [Risk factors in attention deficit disorder and hyperactivity: Family study]. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 21, 253-260.

34.

Rubia

Smith

Halari

Matsukura

Mohammad

Taylor

Brammer

(2009). Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure ADHD during sustained attention. American Journal of Psychiatry, 166, 83-94.

35.

Schmahmann

J. D.

Doyon

McDonald

Holmes

Lavoie

Hurwitz

A. S.

. . . Petrides

(1999). Three-dimensional MRI atlas of the human cerebellum in proportional stereotaxic space. NeuroImage, 10, 233-260.

36.

Schneider

Retz

Coogan

Thome

Rosler

(2006). Anatomical and functional brain imaging in adult attention-deficit/hyperactivity disorder (ADHD)—A neurological view. European Archives of Psychiatry & Clinical Neurosciences, 256(Suppl. 1), i32-i41.

37.

Schneider

M. F.

Krick

C. M.

Retz

Hengesch

Retz-Junginger

Reith

Rösler

(2010). Impairment of fronto-striatal and parietal cerebral networks correlates with attention deficit hyperactivity disorder (ADHD) psychopathology in adults—A functional magnetic resonance imaging (fMRI) study. Psychiatry Research: Neuroimaging, 183, 75-84.

38.

Slaats-Willemse

D. I.

Swaab-Barneveld

H. J.

de Sonneville

L. M.

Buitelaar

J. K.

(2007). Family-genetic study of executive functioning in attention-deficit/hyperactivity disorder: Evidence for an endophenotype? Neuropsychology, 21, 751-760.

39.

Smith

A. B.

Taylor

Brammer

Halari

Rubia

(2008). Reduced activation in right lateral prefrontal cortex and anterior cingulate gyrus in medication-naïve adolescents with attention deficit hyperactivity disorder during time discrimination. Journal of Child Psychology and Psychiatry, 49, 977-985.

40.

Sprich

Biederman

Crawford

M. H.

Mundy

Faraone

S. V.

(2000). Adoptive and biological families of children and adolescents with ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 1432-1437.

41.

Tzourio-Mazoyer

Landeau

Papathanassiou

Crivello

Etard

Delcroix

. . . Joliot

(2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 15, 273-289.

42.

Valera

E. M.

Faraone

S. V.

Biederman

Poldrack

R. A.

Seidman

L. J.

(2005). Functional neuroanatomy of working memory in adults with attention-deficit/hyperactivity disorder. Biological Psychiatry, 57, 439-447.

43.

Willcutt

E. G.

Doyle

A. E.

Nigg

J. T.

Faraone

S. V.

Pennington

B. F.

(2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57, 1336-1346.

44.

Wolf

R. C.

Plichta

M. M.

Sambataro

Fallgatter

A. J.

Jacob

Lesch

K. P.

. . . Vasic

(2009). Regional brain activation changes and abnormal functional connectivity of the ventrolateral prefrontal cortex during working memory processing in adults with attention-deficit/hyperactivity disorder. Human Brain Mapping, 30, 2252-2266.