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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Hum Brain Mapp. Author manuscript; available in PMC 2010 October 1.
Published in final edited form as:
PMCID: PMC2748172

The fMRI success rate of children and adolescents: typical development, epilepsy, attention deficit/hyperactivity disorder, and autism spectrum disorders


FMRI in children is increasingly used in clinical application and in developmental research; however, little is known how pediatric patient and typically developing populations successfully complete studies. We examined pediatric success rates with Epilepsy, Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorders (ASD), and typically developing children (TYP). We also examined the affect of age, and, for ADHD populations, medication status on success rates. We defined a successful fMRI individual run when the data were interpretable and included in group statistics. For unsuccessful runs, datasets with excessive motion or floor task performance were categorized when possible. All clinical groups scanned less successfully than controls; medication status did not affect ADHD success (Epilepsy: 80%; ADHD (off methylphenidate): 77%; ADHD (on methylphenidate): 81%; ASD: 70%; TYP: 87%). Ten to 18-year-olds had a significantly greater scan success rate than 4–6-year-olds; adolescents (13–18-year-olds) demonstrated greater scan success rates than 7–9-year-olds. Success rate for completing an entire battery of experimental runs (n=2–6), varied between 50–59% for patient populations and 69% for TYP (79% when excluding 4–6-year-olds). Success rate for completing one run from a battery was greater than 90% for all groups, except for ASD (81%). These data suggest 20–30% more children should be recruited in these patient groups, but only 10–20% for TYP for research studies. Studies with 4–6-year-olds may require 20–40% additional participants; studies with 10–18-year-olds may require 10–15% additional participants.

Functional magnetic resonance imaging (fMRI) is an established tool in the study of brain function in children with developmental disorders, acquired disorders, and typical development (TYP) and has a clinical application in pre-surgical planning for children with Epilepsy (Medina et al., 2007). Unlike structural MRI where participants are required to lie still (and may do so while sleeping), fMRI requires awake and cooperative participants which precludes the use of sedation. There is a paucity of data examining the success rate of scanning children in fMRI paradigms.

One study has examined scan success rate in over 200 TYP children between 5-to 18-years of age (Byars et al., 2002). This study defined scan success as children completing at least one of four fMRI tasks and an anatomical reference scan. Children between the ages of five and six had a success rate of 47%; children between the ages of seven and nine had a success rate of 76%; and children above the age of ten had a success rate of 96%. It is unknown whether children with neurological or developmental disorders complete fMRI paradigms with the same rate of success as TYP children. Furthermore, no investigation has examined whether the use of psychopharmacological medications targeting core disorder symptoms affects scan success.

We aimed to determine whether the fMRI scan success rates differed by age or among a group of TYP control children and three pediatric patient groups: Epilepsy, Attention Deficit/Hyperactivity Disorder (ADHD), and Autism Spectrum Disorder (ASD). Furthermore, we incorporated psychopharmacological data from the ADHD group to examine whether the success rate differs when on or off psychostimulant medication.



409 children, 4–18-years of age, participated in one of seven fMRI studies (see Table 1). The typically developing (TYP) control group included 137 children across six research studies. Participants in the TYP group were excluded if parents reported any significant history of neurological, language, learning, or major psychiatric disorders, cognitive or developmental delays, or IQ< 80. Children in the TYP group were matched on age, IQ, and gender for the corresponding clinical group.

Table 1
Participant characteristics: means (standard deviations)

The Epilepsy group consisted of 183 children aggregated from two studies (one was a clinical pre-surgical language mapping study, the other a patient language research study). All children in the Epilepsy group were evaluated by a child neurologist and epileptologist. In addition, they also had localization-related epilepsy as characterized by participant history, a neurological examination, standard EEG/vEEG, and structural MRI. Participants in the Epilepsy research group had complex partial epilepsy and a normal MRI, and were excluded if they had developmental delays or IQ< 70. The pre-surgical Epilepsy clinical participants had complex partial epilepsy and either a normal MRI or a structural abnormality such as mesial temporal sclerosis, focal cortical dysplasia, brain tumor, stroke, or vascular malformation; none had an IQ < 55.

The ADHD group comprised 52 children from one study. All participants had a diagnosis based on DSM-IV criteria and symptom presentation, as confirmed by the Behavior Assessment Scale for Children (BASC; Reynolds & Kamphaus, 1998); all responded to methylphenidate (MPH). Participants were excluded if diagnosed with comorbid neurological or psychiatric disorders (with the exception of Oppositional Defiant Disorder) or IQ< 85.

The autism spectrum disorders (ASD) group comprised 37 children culled from four studies. Participants in the ASD group were given a formal diagnosis (autism, asperger’s disorder, or pervasive developmental disorder- not otherwise specified) as determined by clinical assessment using standard diagnostic tools (Lord et al., 2000; Lord et al., 1994) and DSM-IV criteria (APA, 2000). ASD were initially screened with a telephone interview, and medical/family history questionnaires. Exclusion criteria included parent reports of comorbid genetic neurological, language, learning, or major psychiatric disorders. The exclusion criterion across three ASD research studies was IQ< 70; for one research study IQ< 80.

Participants in the patient groups were recruited for research studies on cognitive function from neurology, psychiatry, developmental pediatric and neuropsychological clinics at Children’s National Medical Center in Washington, DC, and also included 64 participants from the NINDS, NIH clinical study. Participants in the TYP group were recruited from the greater Washington, DC metro area.

Study Procedure

All groups, except ADHD, completed a single, one hour fMRI and structural scan session. Across all studies, children 7–18-years scanned for at least 30 minutes and attempted a minimum of three to four fMRI runs in a scan session, with no more than six runs for children enrolled in both Epilepsy studies. Only the Epilepsy studies enrolled 4–6-year-old children, and their total scan time lasted less than 30 minutes and attempted only two fMRI runs. The ADHD group attempted two separate, counterbalanced scan sessions as part of a research study examining brain function while off and on MPH. Only the first scan session for each participant was included in this analysis to limit familiarity with MRI environment. For the “off MPH” condition, stimulant medication was withheld 24–30 hours prior to scanning. For the “on MPH” condition, children received their regularly prescribed dose of MPH. Moreover, all children in the ADHD study scanned for a maximum of 30 minutes and were then removed from the MRI environment for a break. All studies were conducted with IRB approval. Prior to scanning, parental consent and child assent was obtained. A mock scanner was available for all children to acclimate to MRI setting. All 4–10-year-old children enrolled in the Epilepsy studies used either the mock scanner or a tunnel and were exposed to gradient sounds for practice, while older children and adolescents in the Epilepsy studies viewed pictures of the scanner rather than used the tunnel. No children enrolled in the ADHD studies used the mock scanner. Few participants in the ASD group used the mock scanner as it either heightened anxiety or children disliked subtle differences between mock and actual MRI environments.

Task Procedures

The studies investigated varying functions, including executive control, working memory, inhibition, implicit learning, semantic decision, language, and visual perception. All tasks were block designs, except one event-related design (implicit learning task). Task duration ranged from 5 minutes to 6 minutes 30 seconds. Experimental paradigms were presented with E-Prime software, and data were collected with MRI compatible button boxes, when necessary. To limit participant motion, all studies used foam cushions to pad the space between headphones and the head coil, leg cushions were used except when refused, and some children had a weighted sand bag on their feet.

Imaging Parameters and Data Analysis

Functional images were acquired on a Siemens 1.5T, 3.0T, or GE 3.0T scanner using a T2*-sensitive gradient echo pulse sequence. Data were analyzed with IDL, SPM99, SPM2, or SPM5, depending on which software was most commonly used during data collection. Preprocessing included estimating motion parameters, normalization to the EPI template from SPM, and smoothing. Data collected in the pre-surgical clinical study at the National Institutes of Health were processed by co-registering images in the patient’s native space and not normalized to the EPI template. All studies performed some form of motion correction for participants that had more than one voxel of movement – volumes were either realigned after estimating motion or the realignment parameters were included as covariates of no interest in the individual results model.

Success Rate Data Analysis Plan

For all studies but the pre-surgical clinical study, success was defined as completion of the fMRI run and with acceptable amount of head motion and adequate task performance – yielding a technically useful individual map. The guideline for head motion was less than 1 voxel of movement in any direction during a run. If the head movement exceeded 1 voxel, then motion parameters were included as covariates or volumes were re-aligned based on motion parameters. For the clinical, pre-surgical language mapping study, success was defined as completion of the fMRI run and a technically useful individual map providing useful information about language function (i.e., individual map showed activation in known regions supporting language function). Because of this difference all analyses were conducted with and without the clinical, pre-surgical group.

The analyses addressed four issues regarding fMRI success rate. First, we examined the likelihood that a child successfully completes an individual fMRI run. For each child, a success rate was calculated based on the number of successes (following the above criteria), divided by the total number of runs ( equation M1). Second, we examined the likelihood that a child successfully completed an entire battery of fMRI runs (number of children who have a Success Rate of one). Third, we examined the likelihood that a child successfully completes at least one fMRI run from a battery (see Figure 1 for depiction of different success rate calculation and analysis methods). Finally, we also reported reasons for an unsuccessful fMRI run.

Figure 1
This figure outlines the specific data analyses conducted to answer each of the three types of success rate questions: 1) the likelihood a child completes a fMRI run; 2) the likelihood a child completes an entire fMRI battery; 3) the likelihood a child ...

The primary analysis for success rate of an individual fMRI run included a diagnostic group (TYP, Epilepsy, ADHD, ASD) by age group (4–6-year-olds, 7–9 year-olds, 10–12 year-olds, 13–18-year-olds) ANOVA with success rate as the dependent variable. Both main effects and interactions between diagnostic groups and age groups were examined. The secondary analyses included independent t-tests and univariate ANOVAs to examine success rates within the individual studies (e.g., Epilepsy versus matched TYP controls and 7–9-year-old versus 10–12-year-old age groups). These analyses controlled for task difficulty across studies. The adolescent data (13–18 years) were only included in the overall ANOVA because this age group only contained one diagnostic group (adolescents with Epilepsy enrolled in the pre-surgical study). We also examined the success rates of ADHD off and on MPH with a paired-samples t-test.

The primary analysis for successful completion of an entire fMRI battery was defined categorically as either “complete battery” or “incomplete battery”. The analysis included a series of chi-square (χ2)tests between clinical groups and their matched controls, as well as the various age groups.

The primary analysis for successful completion of at least one run from an entire fMRI battery was also defined categorically as either “completed at least one fMRI run” or “no fMRI runs completed”. We report the percentage of children in each group that completed a single task. This analysis parallels the success rate analysis carried out previously in a TYP sample (Byars et al., 2002) with the more stringent criteria that a successful run had to yield technically useful data for group analyses or clinical gain.

In order to examine whether fMRI task or fMRI parameters affected success rates, we conducted a subset analysis only on our 7–12-year-old TYP group. This allowed us to hold age and diagnosis constant across different tasks of interest, such as language, semantic decision, executive control, visual perception, working memory, inhibition, and implicit memory. To examine whether event-related or block design tasks affected success rate, we compared controls only within the ASD studies; this set of studies was the only one to include event-related designs and the comparison block design tasks are more similar in nature.

Finally, scan failures are reported and tallied. Determining the reason for a scan failure is at times subjective and multi-factorial, thus, these data are discussed qualitatively.


Group Differences for Successful Completion of a fMRI Run

Overall success rate for an individual fMRI run collapsing across diagnostic groups and age groups was 81.22%. Overall success rate for a fMRI run showed all clinical groups achieving a significantly lower success rate for a fMRI run than TYP controls, and the youngest age group (4–6 year olds) achieving a significantly lower success rate than children ages 10 and up. The age by diagnostic group ANOVA yielded significant main effects for diagnostic group (F(3, 398)=7.73, p<0.001), and age group (F(2, 398)=9.73, p<0.001), but no interaction (F(4, 398)=0.42, p=0.80) for completion of an individual fMRI run (see Figure 2). This ANOVA violated homogeneity, (F(9, 398)=6.82, p<0.001), thus a Games-Howell post-hoc analysis was included to correct for unequal variances. Furthermore, follow-up t-tests listed below used a Welch t-test to correct for unequal variance between groups. Games-Howell post-hoc analysis revealed that all clinical groups had significantly lower success rates for fMRI runs than TYP controls. No other diagnostic group differences were significant. Games-Howell post-hoc analyses revealed the oldest age group (13–18-years-old, which only included children with Epilepsy) had a greater success rate than the two youngest age groups (4–6 year-olds and 7–9 year-olds); the 10–12-year-olds had a greater success rate than the 4–6-year-olds. No other age group differences were significant.

Figure 2
This figure shows the proportional success rate for the completion of an individual fMRI run in each diagnostic group by age group.

The within study analysis confirmed the main effect of diagnostic group from the overall ANOVA by showing all clinical groups had significantly lower success rates for a fMRI run relative to their matched TYP controls (Epilepsy: t(194)=2.21, p<0.05; ADHD (off MPH) t(82)=3.48, p<0.01; ADHD (on MPH): t(79)=3.34, p<0.001; ASD: t(68)=2.21, p<0.05). The within study analysis only revealed an age finding within the ADHD (on MPH) group where 10–12 year olds had a higher success rate for a fMRI run relative to the 7–9 year olds (see Table 2). There were no differences in success rate for a fMRI run for children with ADHD on or off their prescribed MPH dosage; the paired t-test was non-significant (t(48)=0.89, p=0.38).

Table 2
Fmri Success Rate* Proportion for Diagnostic Group by Age Group

Age did not interact significantly with diagnostic group for the success rate of a fMRI run in all studies (all F<1, p>0.40), except a marginal finding within the ADHD (on MPH) group compared to their TYP controls (F(1,77)=3.03, p=0.09). Follow-up t-tests revealed that the success rate for an individual run within the ADHD (on MPH) group was significantly higher for the 10–12-year-olds compared to the 7–9-year-olds (t(47)=1.99, p=.05).

Group Differences for Successful Completion of an Entire fMRI Battery

The overall success rate for completion of an entire fMRI battery when collapsing across diagnostic and age groups was 60.39%. Success rate of a complete battery revealed no differences between the Epilepsy group and their TYP controls when the clinical, pre-surgical group was included; whereas the non pre-surgical group Epilepsy group, the ADHD (regardless of MPH status) and ASD groups completed significantly fewer fMRI batteries relative to their TYP controls (see Table 3). Moreover, within the ADHD group, MPH improved the ability to complete an entire fMRI battery. The TYP group matched to the non-presurgical Epilepsy group achieved a significantly higher complete fMRI battery success rate when collapsing across age, (χ2(N=132)=5.95, p<0.05). The TYP group matched to the ADHD group achieved a significantly higher complete fMRI battery success rate when collapsing across age groups within each medication status group (χ2>4.00, p<0.05). Within the ADHD group, children had a higher success rate for completing the fMRI battery when taking their prescribed MPH dose than off (χ2(N=50)=20.51, p<0.001). The TYP group matched to the ASD group achieved a significantly higher complete fMRI battery success rate (χ2(N=70)=7.12, p<0.01). This higher fMRI battery success rate in the ASD study was only significant within the 7–9-year-olds (χ2(N=29)=3.99, p<0.05), and marginal in the 10–12-year-olds (χ2(N=41)=2.98, p=0.08).

Table 3
Fmri Success Rate for Completion of fMRI Battery* for Diagnostic Group by Age Group

To examine further the effect of age on complete fMRI battery success rates, we conducted within diagnostic group analyses. We found that 10-year-olds and up completed an entire fMRI battery at a significantly higher rate than the 4–6-year-olds in both TYP and Epilepsy diagnostic groups, and no significant differences within the ADHD or ASD groups. In the TYP group, (collapsed across all studies) the 10–12-year-olds achieved a significantly higher complete fMRI battery success rate than all other TYP age groups (all χ2>4.85, p<0.05). In the Epilepsy group, the 13–18-year-olds achieved a significantly higher success rate for a complete fMRI battery than all other Epilepsy age groups (all χ2>3.75, p≤0.05); while 10–12-year-olds achieved a significantly higher success rate for a complete fMRI battery than the 4–6-year-olds (χ2(N=80)=4.27, p<0.05), and marginally higher than the 7–9-year-olds (χ2(N=98)=3.27, p=0.07). No other analyses revealed significant age group or age by diagnostic group differences.

Group Differences for Completion of a Single fMRI Run from an Entire fMRI Battery

All groups completed at least one fMRI task from an entire battery over 90% of the time, except for the ASD group. Age did not appear to play a role in the TYP, ADHD, or ASD groups for completing a single run from an entire battery, but may have played a role in the 4–6-year-old Epilepsy group. TYP controls completed at least one fMRI task from an entire fMRI battery 97.08% of the time (133/137 children) with one child in the 4–6-year-old and one child in the 7–9-year-old age group and two children in the 10–12-year-old group not completing any runs. The Epilepsy group completed at least one fMRI task from an entire fMRI battery 92.89% of the time (170/183 children) with six children in the 4–6-year-old group, three children in the 7–9-year-old group, and two children in the 10–12-year-old and 13–18-year-old groups not completing any runs. The ADHD (off MPH) group completed at least one fMRI task from an entire fMRI battery 96.15% of the time (50/52) with one child in the 7–9-year-old group and one child in the 10–12-year-old group not completing any runs; while the ADHD (on MPH) group completed at least one fMRI task from an entire fMRI battery 94.00% of the time (47/50 children) with two children in the 7–9-year-old group and one in the 10–12-year-old group not completing any runs. The ASD group completed at least one fMRI task from an entire fMRI battery 81.08% of the time (30/37) with four children in the 7–9-year-old group and three children in the 10–12-year-old group not completing any runs.

Probing fMRI Tasks and fMRI Task Parameters That May Affect Success Rates

This analysis revealed no consistent effect of task type or task parameters affecting success rates. A one-way ANOVA on task type, revealed no differences across the TYP groups (language tasks in Epilepsy study vs. executive control tasks in ADHD study vs. executive control and implicit learning tasks in ASD studies) for success rate of completing an individual fMRI run, F(2, 112)= 2.30, p=0.11), but there were significant differences in success rate of completing an entire battery, (χ2(N=115)=17.93, p<0.001), and for completion of a single run, (χ2(N=115)=7.65, p<0.05). Follow-up χ2 analyses show that the controls in the Epilepsy study had a significantly lower success rate for completing an fMRI battery (52%) compared to ADHD controls (88%) and ASD controls (88%). As for the significant χ2 in completing a single run, the ASD group was significantly lower (91%) relative to the Epilepsy (100%) and ADHD (100%). With respect to experimental design on success rate, we compared controls from the ASD group who completed event-related versus those who completed block designs. This specific sub-group was selected because the groups of controls recruited and the tasks selected are most similar. We found no significant differences in any of the success rates, all p’s>.15).

Scan Failures

Among children who entered the MRI scanner, 155 of 409 (38%) children failed at least one run. There were six reasons for failed runs: 1) excessive head motion; 2) refusal to begin or finish a run after entering the MRI scanner; 3) inattention (e.g., forgetting task rules or falling asleep); 4) other – either undocumented reason or – in the case of pre-surgical clinical Epilepsy study – child’s individual map did not provide a technically useful map for language function (null activation map); 5) combination of excessive head motion with another category (head motion in one task, refusal in another); 6) refusal to enter the MRI scanner. In summary, 41 of 137 (29.9%)children in TYP control group failed at least one fMRI run, 29 of183 (15.8%) children in the Epilepsy group failed at least one run, 25 of 52 (48.1%) children in the ADHD (off MPH) group failed at least one run, and 24 of 50 (48%) children in the ADHD (on MPH) group failed at least one run, and 15 of 37 (40.5%) children in ASD group failed at least one fMRI run. The predominant reason for run failure was excessive head motion representing 75 of 155 children (48.4%), followed by other representing 54 of 155 (34.8%), combination of head motion and other category representing 18 of155 (11.6%), refusal representing 7 of 155 (4.5%), and finally inattention representing 1 of 155 (0.6%).

Excessive head motion accounts for 33% to 63% of failures occurring within a diagnostic group (see Figure 3); notably, the ADHD group (on MPH) has the lowest percentage of failures due to head motion (see Figure 2 for remaining failure rates of other categories). A total of seven children scheduled for fMRI sessions attended but failed to enter the MRI scanner. Four of these children were in the epilepsy group, one was in the TYP group, one was in the ADHD (off MPH) group, and one was in the ADHD (on MPH) group.

Figure 3
This bar graph depicts the percentage of failed runs for each category type within each diagnostic group.


Clinical pediatric populations have a lower success rate for completing fMRI runs than typically developing children matched on age, IQ, and gender. Adolescents completed more fMRI runs than younger children. The success rate for children with ADHD while on or off their prescribed MPH dose did not differ significantly, although 10–12-year-olds on MPH achieved a higher success rate than 7–9-year-olds on MPH. Completion of an entire fMRI battery was equivalent for the Epilepsy group (non pre-surgical and pre-surgical) and their matched controls for 4–12-year-olds, whereas 7–9-year-olds with ADHD (on or off MPH) and 7–12-year-olds with ASD were less successful than their TYP controls. When examining whether task difficulty contributed to success rates, we found lower success rates for completing an fMRI battery for the 7–12-year-old TYP group in the Epilepsy study than in the ADHD or ASD studies. The TYP group in the ASD study was also less likely to complete at least one fMRI run compared to the TYP groups in the Epilepsy or ADHD studies. When examining task design (event-related versus blocked) within the TYP ASD group, we did not find a difference in any of the success rates. Excessive head motion was the leading cause for an unsuccessful run across all groups.

Acquiring valid fMRI data in pediatric patient populations requires accounting for the success rates of different clinical populations and ages. While children with ASD would require the most additional participants (26–34% more), all clinical groups below 13-years-old have a failure rate of at least 15%. In contrast, the TYP controls have a failure rate of 10–15%, with the exception of 4–6-year-olds who have a failure rate of 22%.

Age plays an important role in completing an entire fMRI battery. TYP controls completed an entire battery more readily (69%); when 4–6-year-olds are excluded their complete fMRI battery success rate increases to 79%. Moreover, within 7–12-year-olds the Epilepsy group (51%) completed an entire fMRI battery at the same rate as ADHD (off MPH: 50%; on MPH: 50%), and ASD (59%). The significant age related findings within the Epilepsy and TYP control groups suggest that age may play a larger role in completing fMRI batteries than diagnosis. This age finding is strengthened when considering that 4–6-year-olds received a shortened, developmentally appropriate battery designed to improve their success rates. Of note, the TYP controls in the Epilepsy studies had the lowest success rates of all TYP control groups. While all TYP children scanned within 1 hour time blocks, the Epilepsy studies had the most fMRI runs (4 to 6), and the higher failure rate may have occurred in the later runs.

On the surface, fMRI task type may appear to play a role in success rate (e.g., language tasks may appear more difficult based on data above); however, two alternatives may explain the lower success rate for completing a battery in the TYP group in the Epilepsy studies better than task difficulty. Children in the Epilepsy group were asked to complete anywhere from four to six runs, whereas children in the other groups were asked to complete three to four runs. Thus, the lengthier battery may be driving the group differences rather than the language tasks being more difficult than the executive control and learning tasks. Another potential explanation is that an “other” category existed for tallying undocumented reasons for failed scans in research participants, and this category accounted for 33% of failed runs in the 7–12-year-old TYP group in the Epilepsy studies. Therefore, it is possible that some portion of these incomplete batteries may have resulted from a technical issue (e.g., E-prime did not trigger in synch with scan), or a non-task related reason for stopping the scanner (e.g., scan was stopped so child could use the restroom). As a result, this group difference may result from an overly conservative estimate of failures in the Epilepsy study that do not reflect task differences.

Success rate differences in the TYP children in the ASD studies may also be driven by factors other than task type. Although this sub-group of TYP children was also less likely to complete a single task, an examination of the data reveals a potential ceiling effect. The TYP children in the ASD studies had a success rate of 91%, in comparison to 100% from the other groups. Moreover, TYP children in the ASD group completed fewer runs than TYP children in the other studies, and this may have afforded them fewer opportunities to complete at least one run. Taken together, these data suggest that while there may have been some statistically significant differences for success rates across different fMRI task types, it is more likely that other factors such as battery length and ceiling effects may be driving the observed group differences.

As the failure data are descriptive, these findings should be considered preliminary. Excessive head motion was the leading cause for failed scans across all groups. While the use of MPH in children with ADHD did not affect overall fMRI success rate, our failure data suggest that children taking their prescribed dose of MPH had the lowest failed fMRI runs due to excessive head motion. After movement, the second most common reason for failure differed by diagnostic group. Null activation was the reason for the Epilepsy group, undocumented reason for the ADHD group, and refusal to complete a run for the ASD group. These secondary reasons may or may not be specific to the diagnostic group. For example, the higher refusal rate inside the scanner for the ASD group may result from sensitivity to auditory stimuli (Tomchek & Dunn, 2007) or anxiety common in this population (Leyfer et al., 2007). On the other hand, the null activation in the clinical pre-surgical Epilepsy group may be related to the scan time that the clinical study runs (4–8pm on a weeknight) resulting in a higher likelihood that a child falls asleep in one or more runs.

When using a similar definition of scan success as a previous report (Byars et al., 2002), all groups with the exception of the ASD group completed at least one fMRI run over 90% of the time. Twenty-one of 22 (95%) of the TYP 4–6-year-olds completed at least one run, which exceeded the previous report of 47% of TYP 5–6-year olds completing at least one run (Byars et al., 2002). One notable difference between the current Epilepsy study that recruited 4–6-year-old TYP children and the previous study is the number of fMRI runs in the batteries – two in the Epilepsy study and four in the previous study. The Epilepsy study also reduced cognitive demands by not presenting instructions for multiple runs all at one time. Thus, these small changes in the protocol execution may have contributed to the difference in single run success rate for our 4–6-year-olds.

There are potential factors that limit the generalization of our findings. The pre-surgical Epilepsy study had a different aim than the other studies, and therefore employed a different definition for success. The pre-surgical study deemed “null activation” maps (individual maps with no significant clusters of activation) as failed runs because of the need to derive pre-surgical language maps; whereas a null activation map in the other studies was considered successful because sub-threshold maps at the individual level contribute meaningfully to the random effects group maps. Another factor is that our studies varied in how stringently the one voxel rule for head movement was applied. In the pre-surgical Epilepsy study, knowledge of expected and variant patterns of activation at the individual level allowed clinicians to read through motion artifact, and therefore the one voxel rule was violated for clinical gain. This approach likely contributed to the different findings within the Epilepsy group for completing an entire fMRI battery. The ADHD study strictly adhered to the one voxel rule and children were excluded if head movement exceeded one voxel. The ASD study adhered to the one voxel rule except in the case of four runs (from a total of 176) where children moved greater than one voxel once during the run; children who moved more than one voxel repeatedly were excluded. A future study could examine head movement across diagnosis and age as an additional measure of fMRI compliance.

Another limiting factor to discuss is the usefulness of the mock scanner protocol employed by the Epilepsy study. The Epilepsy study only employed the mock scanner protocol for children 4–10-years-old, and this did not appear to be an important factor in improving fMRI success rates. No analysis showed that the Epilepsy group or the TYP group in the Epilepsy study, completed fMRI runs or batteries at a greater percentage relative to ASD and ADHD groups and their respective matched control TYP groups. Although speculative, one explanation may be that our research group makes a concerted effort for participants to interact with the same staff members at multiple research appointments (neuroimaging and psychological testing). Maintaining the same staff across settings may reduce parent and child anxiety, and increase compliance in task completion. Another potential explanation is that the lengths of the fMRI batteries are adjusted based on the child’s age. Children under the age of seven completed only two runs, and their success rates were comparable to the closest age group (7–9-year-olds). The youngest children may have been less fatigued and more likely to successfully complete this shorter fMRI battery, whereas children over 10 years of age are able to complete up to six runs successfully.

There are recent improvements in mock scanner protocols, such as using head motion feedback to inform the child if movement is within acceptable limits. One pilot study showed that an extensive mock scanner protocol that included eight mock scans lasting seven minutes each in conjunction with operant conditioning techniques (e.g., inform child of baseline motion and then positively reinforce small increments of improvement) reduced head motion from a baseline of 31.3 mm/min to 0.98 mm/min. in 7–10-year-olds (Slifer, Koontz, & Cataldo, 2002). Other recent feedback techniques include computer monitoring of head motion. During this technique, children watch a video or engage in the task of interest and the computer pauses the video or task if head motion exceeds a given threshold (e.g., 1 mm in any direction). The current study did not use such extensive mock scanning protocols, and therefore it is unknown whether they would substantially improve fMRI success rates. Therefore, a future study on pediatric fMRI success rate could compare the use of such mock scanner protocols to older protocols (or no protocols).

In addition to mock scanner procedures, other strategies that may prove useful for increasing scan success include explaining task directions and the MRI environment at developmentally appropriate levels, as well as limiting the length of fMRI batteries. For children under the age of seven, our research group only provides instructions for one fMRI task prior to the child entering the MRI environment; instructions for the second fMRI task are given while the child is already in the MRI environment. Avoiding overloading very young children with multiple task instructions may aid in limiting performance anxiety or anxiety about the MRI environment. While this study did not explicitly manipulate fMRI battery length, using a shorter battery thought to be more developmentally appropriate based on the child’s age helped maintain the individual run success rates for 4–7-year-old children similar to 7–9-year-old children.

Taken as a whole, our data indicate that research and clinical application fMRI studies need to establish appropriate recruitment goals in order to reach their desired sample size if patient and/or younger populations are involved. Furthermore, strategies that increase success rate in these populations need to be applied (i.e. maintaining the the same staff across appointments, presenting instructions one run at a time for young children, limiting time in scanner), and investigators need to plan for the possibility of only analyzing partial data sets.


This work was supported by the National Institute of Neurological Disorders and Stroke (R01-NS44280; Clinical Epilepsy Section), National Institute of Mental Health (R01-MH65395), the Frederick and Elizabeth Singer Foundation, and the Studies for the Advancement of Autism Research and Treatment (STAART: NIMH U54 MH066417) for supporting data collection. This work was also supported in part by the Intellectual and Developmental Disabilities Research Center at Children’s National Medical Center (NIH IDDRC P30HD40677) and the General Clinic Research Center (NIH GCRC M01-RR13297). This work was also supported by a T-32 post-doctoral to BEY through the IDDRC (NIH T32HD046388), and an Avery Scholar Award to MMB.


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