Cortical Thickness Changes and Their Relationship to Dual-Task Performance following Mild Traumatic Brain Injury in Youth

Abstract

Mild traumatic brain injury (mTBI) is common in youth, especially in those who participate in sport. Recent investigations from our group have shown that asymptomatic children and adolescents with mTBI continue to exhibit alterations in neural activity and cognitive performance compared with those without a history of mTBI. This is an intriguing finding, given that current return-to-learn and return-to-play protocols rely predominately on subjective symptom reports, which may not be sensitive enough to detect subtle injury-related changes. As a result, youth may be at greater risk for re-injury and long-term consequences if they are cleared for activity while their brains continue to be compromised. It is currently unknown whether mTBI also affects brain microstructure in the developing brain, particularly cortical thickness, and whether such changes are also related to cognitive performance. The present study examined cortical thickness in 13 asymptomatic youth (10–14 years old) who had sustained an mTBI 3–8 months prior to testing compared with 14 age-matched typically developing controls. Cortical thickness was also examined in relation to working memory performance during single and dual task paradigms. The results show that youth who had sustained an mTBI had thinner cortices in the left dorsolateral prefrontal region and right anterior and posterior inferior parietal lobes. Additionally, cortical thinning was associated with slower reaction time during the dual-task condition in the injured youth only. The results also point to a possible relationship between functional and structural alterations as a result of mTBI in youth, and lend evidence for neural changes beyond symptom resolution.

Introduction

Mild traumatic brain injury (mTBI) is one of the leading causes of injury in youth, with 54% of injuries occurring during participation in sport.^1,2 The high speed and physical contact inherent in many sports can result in biomechanical forces causing linear and/or rotational acceleration–deceleration injuries to the brain.³ These forces may cause an mTBI that is diagnosed by the presence of symptoms including alterations in cognition, physical state, and/or mood, in addition to the absence of evidence of structural brain damage on standard clinical brain scans.⁴ The young brain is particularly vulnerable to the effects of brain injury as it is still undergoing substantial neurodevelopment.^5,6 Although diagnosis relies on “return to school/play” by self- and parent-report of symptoms, recent evidence shows that even a single mTBI can result in neurocognitive alterations persisting beyond symptom resolution.⁷ For example, we recently showed that asymptomatic young athletes who had incurred an mTBI 3–8 months prior to testing displayed altered activation in dorsolateral prefrontal (DLPFC) and parietal cortices during working memory performance in both single- and dual-task (i.e., performing two tasks at once) conditions.⁷ Interestingly, injured youth performed similarly to controls in the single-task condition, but had slower reaction time during the dual-task. This suggested decreased cognitive efficiency with more challenging tasks following mTBI with corresponding neural alterations, despite intact neuropsychological test performance and symptom resolution.⁷

What is unknown is whether mTBI in youth can result in microstructural brain changes and whether these changes are associated with functional sequelae at the neural and performance level. Although a TBI is considered “mild” in the absence of positive imaging findings, most methods evaluate gross or macrostructural changes on CT scans, and to a lesser extent, on MRI.⁸ Development of newer analysis techniques that evaluate microstructural damage has provided new knowledge on the subtle effects of mTBIs.⁹ For example, decreases in hippocampal volume have been linked to poorer performance in older adults after mTBI.¹⁰ However, cortical volume is defined by both the surface area (gyri and sulci) and cortical thickness; therefore, it may be possible that the long-term effects of mTBI on cortical volume may mask some of the effects of mTBI given that thickness analysis may be a finer measurement of subtle changes in brain microstructure and morphology.¹¹

Developmentally, cortical thinning occurs as a natural process of maturation, with both linear and cubic trajectories occurring across and between brain regions from childhood to early adulthood.^11

–15 These changes are thought to be reflective of normal synaptic proliferation and pruning, with regional differences in maturational trajectories seeming to reflect functional differences between systems.^16,17 Therefore, any alterations to the cortical microstructure can presumably alter subsequent cognitive development. Cortical thinning can also reflect a pathological change to the brain as a result of a neurodevelopmental disorder (e.g., autism), neuroinflammation (e.g., multiple sclerosis), neurodegenerative diseases, and mental illness (e.g., schizophrenia).^18

–21 Cortical thickness changes are also observed mainly following moderate to severe TBIs from as early as 3 months to up to 5 years post-injury.^22

–25 Commonly affected areas include vast frontal areas (frontal pole, and middle, superior, oribital, lateral/dorsolateral, and medial areas); the anterior cingulate cortex; fusiform, superior and inferior parietal, temporal areas; and cuneus.^22,23,25

Cortical thinning has also been observed following single and repetitive mTBIs in young to middle-aged adults, particularly in the frontal, temporal, and parietal areas.^26
–28 There is some evidence in the adult literature to suggest that injury-related thinning may be associated with changes in cognition. Former athletes who had sustained several mTBIs, exhibit accelerated cortical thinning with aging in frontal, temporal, and parietal brain regions related to declines in episodic memory.²⁹ Another study showed that significant cortical thinning in the right precuneus and anterior cingulate a year after mTBI are asociated with poorer performance on memory and attention tasks.³⁰ Overall, it seems pausible that cortical thinnning as a result of mTBI during critical neural developmental periods may also lead to long-term thinning in brain regions particularly susceptable to damage (i.e., frontal, temporal, and parietal cortices), and as well as affecting the neurocongitve processses that these regions subserve.³¹

If such changes in cortical thickness exist following mTBI in youth and if they are related to abnormal cognitive performance, the implications are multi-fold. First, this may provide a structural basis for functional neural alterations observed previously.⁷ Second, it provides support for the idea that even a single mTBI may be more consequential to development than is currently assumed. Third, it provides evidence for further investigations into using cortical microstructure analyses as a clinical tool to evaluate post-injury changes, which is arguably more time and cost efficient than functional brain scans. A previous study revealed cortical thickness changes 4 months following mTBI in adolescents;³² therefore, the first objective of the current study was to replicate such findings. Specifically, we wanted to evaluate whether there are changes in gray matter microstructure (cortical thickness) following mTBI in children and adolescents in the chronic period (3–8 months after injury). We hypothesized that there would be a decrease in cortical thickness in frontal, temporal, and parietal brain regions; areas commonly impacted in TBI.³³ Another main objective was to evaluate whether cortical thickness is related to behavioral performance during working memory performance in both single- and dual-task conditions. Cortical thinning following TBI has been associated with everyday social difficulties, difficulties with emotional control and behavioral regulation, weak event-based prospective memory, poor social problem-solving, and parent ratings of poor working memory.^{22,23,25,34,35} Therefore, we hypothesized that abnormalities in working memory performance would be associated with a reduction in cortical thickness in key working memory nodes including the DLPFC and parietal cortices.

Methods

Participants

The following groups are described in detail elsewhere.⁷ Briefly, the mTBI group consisted of 13 male participants 10–14 years of age who had sustained an mTBI 3–8 months prior to participation in the study. Two participants had sustained more than one mTBI. Although the mean time since injury was 120.69 (+2.05) days, the vast majority of the mTBI participants (8/13) incurred their injuries 3–4 months prior to participation, and their data do not appear any different on visual inspection from the remaining four participants with injuries 6–8 months prior to testing.

Inclusion criteria for the mTBI group required a physician diagnosis in the past 3–8 months, and mTBI history was probed at study recruitment (using criteria by the 3rd International Consensus Conference on Concussion in Sport in Zurich [2008] and by the World Health Organization) and at the time of study participation (ThinkFirst Concussion Questionnaire created by Drs. J. Scott Delaney and Karen M. Johnston on behalf of the ThinkFirst-SportSmart Concussion Education and Awareness Committee). Fourteen age- and sex-matched participants without a known history of TBI (confirmed via the criteria and questionnaires listed) were included in the healthy control group. Exclusion criteria for both groups included history of moderate to severe TBI, motor disturbances, psychiatric disorders, pre-existing neurological conditions, and any contraindication on MRI. No participants were currently taking any medications. The descriptive characteristics of the participants are presented in Table 1.

Table 1.

Participant Demographics and Characteristics for Control and mTBI Groups

Group	Control (n = 14)	mTBI (n = 13)
Age	12.6 ± 1.6	12.2 ± 1.6
Handedness (right)
n (%)	13 (93%)	13 (100%)
Days after injury
mean±SD	N/A	120.69 (+2.05)
Minimum		90.07
Maximum		240.27
Cause of injury
Hockey n (%)	N/A	10 (93%)
Martial arts n (%)		3 (7%)
Number of previous mTBIs
0 n (%)	14 (100%)	0 (0%)
1 n (%)	0 (0%)	11(85%)
2 n (%)	0 (0%)	2 (15%)

mTBI, mild traumatic brain injury.

All participants were administered standardized neuropsychological tests to assess for potential cognitive differences in the domains of general intellectual ability, visuospatial memory, inhibitory control and behavioral flexibility, fine motor speed and dexterity, and processing speed. There were no significant differences between groups on any test measure (for further detail on neuropsychological tests used please see the study by Sinopoli and coworkers⁷). This study was approved by the Research Ethics Boards at the University of Toronto and the Hospital for Sick Children in Toronto. Informed consent was obtained from all participants or their legal guardians, and assent was obtained where appropriate.

Procedures

Experimental tasks and analysis

Participants completed three experimental tasks using Eprime software (Psychology Software Tools, Inc., Sharpsburg, PA) on a laptop computer while in the MRI: 1) visuospatial working memory task (single-task condition), 2) motor task, and 3) both tasks simultaneously (dual-task condition). The visuospatial working memory task was an n-back task with three working memory loads (0-back, 1-back, 2-back).³⁶ Participants were instructed to respond to a blue square by pressing a button with their left index finger when it appeared in a prespecified location (0-back, simple target detection task), or when it appeared in the same location as one or two screens previously (1- and 2-back conditions, respectively). In the motor task, participants were instructed to press alternating buttons with their right index and middle finger at a rate of two beats per second (2 Hz). In the dual-task condition, participants were instructed to complete the visuospatial working memory and the motor tasks simultaneously. Working memory performance in both single- and dual-task conditions was indexed by accuracy (the percentage of hits minus false alarms) and median reaction time of “hit” or correct trials (RT; milliseconds). Prior to entering the scanner, participants completed practice trials of the experimental tasks to ensure task comprehension. The functional MRI (fMRI) protocol and results are discussed in detail in our previous article.⁷

Imaging protocol

All participants completed a series of structural scans including T1, T2, diffusion tensor imaging (DTI), fluid-attenuated inversion recovery (FLAIR), and susceptibility weighted imaging (SWI). Structural data were acquired using a Siemens 3-T scanner with a 32 channel head coil (Siemens, HealthCare Global, Germany). High-resolution whole-brain T1-weighted images were obtained using 3D Magnetization Prepared Rapid Gradient Echo (MP-RAGE) sequence (repetition time [TR] = 2300 ms, echo time [TE] = 2.96 ms, slice thickness = 1 mm, image matrix = 256 × 256, flip angle = 9 degrees, field of view [FOV] = 256 mm, interleaved excitation).

Cortical thickness and analysis

Cortical thickness measurements were calculated using the CIVET image processing pipeline for each subject (version 1.1.11, Montreal Neurological Institute).³⁷ Multiple sequential procedures were used to measure cortical thickness across the entire brain.^38,39 The N3 algorithm was then used to remove non-uniformity artifacts from T1 images.⁴⁰ The images were then registered into standardized stereotaxic coordinates with the Talairach atlas space using a nine parameter linear transformation.^41,42 Registration was completed into the anterior commissure (AC)-posterior commissure (PC) axis in order to account for individual differences in brain volume and shape. Next, automatic brain tissue classification was completed and deformable meshes were used to extract white and gray boundaries and pial surface with the constrained laplacian-based automatic segmentation algorithm (CLASP).^38,43 Finally, native space cortical thickness was measured as the distance between two corresponding points from each cortical surface and blurred throughout the cortex using a 20 mm surface-based kernel.^37,44
–46

Statistical analysis

To investigate whether there were behavioral differences between the control and mTBI groups, we conducted separate, two way repeated measures analysis of variance (ANOVA) for accuracy and RT, with working memory load as a within-subject variable (0-back, 1-back, and 2-back), group (control, mTBI) as a between-subject factor, and age as a covariate. A Bonferroni correction was used to correct for multiple comparisons. The assumptions of the ANOVA were assessed and met (i.e., homogeneity, linearity, and normal distribution). Effect sizes were conducted for each ANOVA and reported as “partial ²,” where 0.1 was a small, 0.25 a medium or moderate, and >0.5 a strong effect size.

A Kolmogorov–Smirnov test revealed no significant difference in the distribution of age (t = 0.91; p = 0.200). To assess potential group differences in cortical thickness, we compared the mTBI group to the controls using the general linear model using in-house Montreal Neurological Institute (MNI) software package (http://wiki.phenogenomics.ca/display/MICePub/RMINC last accessed February 17, 2016) through the “R” statistical toolkit (version 2.14.1, The R Foundation for Statistical Computing).⁴⁶ Statistical thresholds for cortical thickness analyses were corrected for multiple comparisons using the false discovery rate (FDR) technique at a level of q = 0.05. For each statistical comparison, p values were pooled across all vertices to determine the FDR threshold used in the statistical toolkit. T statistic values were obtained by using the highest t value in the cluster for each region of interest. Cohen's d was used to evaluate the effect size for the cortical thickness analysis, where Cohen's d between 0.2 and 0.5 was a small, 0.5–0.8 a medium, and >0.8 a large effect size.

Pearson correlation (p value of 0.05, two tailed) was used to investigate the potential relationship between cortical thickness and working memory performance (during single- and dual-task conditions), which was significantly different between the control and mTBI groups (i.e., accuracy and reaction time). We also examined whether time since injury and age at injury were correlated with cortical thickness measures.

Results

Working memory performance during the single- and dual-task conditions

These data have been reported previously (see also Table 2).⁷ They have been included here for the purpose of adding context to the current results. In summary, accuracy on the n-back tasks was not statistically significantly different between the control and mTBI groups during either the single- and dual-task conditions. Similarly, working memory RT during the single-task was not statistically significantly different between groups. However, there was an interaction between group and RT (linear effect, F[2,44] = 3.777; p = 0.030; partial ² = 0.141) such that the mTBI group exhibited slower RT during the dual-task condition as the cognitive load of the task increased. This speed-accuracy tradeoff in the mTBI group was thought to reflect reduced cognitive efficiency during more challenging tasks.⁷

Table 2.

Results of Visual-Spatial Working Memory for Control and mTBI Groups

		Control (n = 14)	mTBI (n = 13)
a) Single task paradigm
0 n-back
Accuracy	Mean % (SEM)	88 (2)	87 (3)
Reaction time (ms)	Median (SEM)	519 (21)	545 (18)
1 n-back
Accuracy	Mean % (SEM)	88 (3)	90 (2)
Reaction time (ms)	Median (SEM)	465 (26)	479 (38)
2 n-back
Accuracy	Mean % (SEM)	66 (6)	80 (5)
Reaction time (ms)	Median (SEM)	496 (61)	624 (32)
b) Dual task paradigm
0 n-back
Accuracy	Mean % (SEM)	92 (3)	93 (2)
Reaction time (ms)	Median (SEM)	559 (29)	608 (18)
1 n-back
Accuracy	Mean % (SEM)	88 (3)	90 (2)
Reaction time (ms)	Median (SEM)	465 (26)	479 (38)
2 n-back
Accuracy	Mean % (SEM)	66 (6)	80 (5)
Reaction time (ms)	Median (SEM)	496 (61)	624 (32)

Performance accuracy and median reaction time during the a) single- and b) dual-task conditions for control and mTBI groups for working memory difficulties: 0-back, 1-back, and 2-back. Accuracy values are shown as mean and SEM, whereas reaction time (ms) is shown as the median and SEM values.

mTBI, mild traumatic brain injury.

Cortical thickness

See Table 3 for mean cortical thickness values for control and mTBI groups and MNI coordinates for each brain region. Figure 1 illustrates cortical thickness results on a statistical map. Whole-brain analyses revealed that the mTBI participants had significantly thinner cortex in the left DLPFC (t = 2.542, p = 0.018, d = 0.963) and in the right anterior and posterior inferior parietal lobule (IPL) (anterior, t = 3.025, p = 0.002, d = 1.152; posterior, t = 2.605, p = 0.015, d = 1.002) compared with controls. There was no significant difference in any other brain regions between the control and mTBI groups. There were no significant correlations between cortical thickness and age or time since injury.

FIG. 1.

Significant cortical thickness differences are displayed on the surface of a standardized brain in terms of a t statistical color map. Cortical thickness values were significantly lower in the left dorsolateral prefrontal cortex (DLPFC) (p = 0.018), right anterior inferior parietal lobule (IPL) (p = 0.002), and posterior IPL (p = 0.015) of the mild traumatic brain injury (mTBI) group in comparison with control group values. *Cortical thickness values are scaled differently across regions of interest.

Table 3.

Cortical Thickness Values for Control and mTBI Groups

Brain region	MNI coordinate (x, y, z)	Control (n = 14) (mean ± SEM)	mTBI (n = 14) (mean ± SEM)
Right anterior IPL	62, −32, 32	3.320 ± 0.061	2.928 ± 0.118^*
Right posterior IPL	45, −52 30	3.464 ± 0.052	3.262 ± 0.057^*
Left DLPFC	−22, 28, 46	3.299 ± 0.047	2.898 ± 0.156^*

Average cortical thickness values for control and mTBI groups in the right anterior IPL, right posterior IPL, and left DLPFC. Brain region location is based on Montreal Neurological Institute (MNI) map. Values are shown by mean and SEM.

mTBI, mild traumatic brain injury; IPL, inferior parietal lobe; DLPFC, dorsal lateral prefrontal cortex.

Relationship between cortical thickness and task performance

In the control group, better accuracy during the 0-back single-task condition was associated with an increase in cortical thickness in the left DLPFC (r = 0.537; p < 0.05). Controls also displayed a significant association between faster RT during the single-task 1-back condition and greater cortical thickness in the anterior (r = −0.640; p < 0.01) and posterior IPL (r = −0.562; p < 0.04). Typically developing youth did not exhibit any significant correlations between cortical thickness measures and performance during the dual-task condition.

The mTBI group displayed a significant relationship between poorer accuracy and a thicker left DLPFC during the 1-back, single-task condition (r = −0.554; p = 0.049). In contrast, during the dual-task condition, thinner left DLPFC was associated with slower median RT during all three conditions (0-back, r = −0.643, p < 0.02; 1-back, r = −0.592, p < 0.02; 2-back, r = −0.627, p < 0.02; see Fig. 2). Speed of performance in the 2-back, dual-task condition was also associated with thickness in the anterior IPL in the mTBI group (r = −0.604; p = 0.029), such that slower speed was correlated with a thinner cortex. Interestingly, the areas in which we found significant thinning and correlations with performance overlapped with abnormalities observed in fMRI activation⁷ (i.e., the brain areas were registered to the same MNI template using the same registration algorithms).

FIG. 2.

Comparison between reaction time during dual task protocol of a) 0-back, b) 1-back, and c) 2-back working memory difficulty level and cortical thickness in the left dorsolateral prefrontal cortex (DLPFC) for control and mild traumatic brain injury (mTBI) participants. There was no significant association in the control group between dual-task (a–c) medium reaction time (ms) and cortical thickness. In the mTBI group, thinner cortices in the left DLPFC were associated with slower reaction time (ms) during a) 0-back (p < 0.02), b) 1-back (p < 0.02), and c) 2-back (p < 0.02).

Discussion

This study provides evidence for differences in cortical thickness in asymptomatic youth who sustained an mTBI in the chronic phase post-injury. Our main findings were that the mTBI group displayed thinner cortices in the left DLPFC and the right anterior and posterior IPL than did uninjured, typically developing controls. Further, the mTBI group displayed associations between thinning left DLPFC and slower performance during all difficulty levels of the working memory dual-task condition, and a thinner right anterior IPL was associated with slower performance during the highest working memory load of the dual-task condition. These relationships were not observed in the control group. Rather, faster reaction time was associated with thicker right anterior and posterior IPL in conditions of low working-memory demands (i.e., single working memory task), more accurate performance was associated with thicker left DLPFC during the low working memory single task. It is important to recognize that accuracy of performance during both the single and dual tasks was similar between groups, whereas participants with mTBI slowed their performance during the dual-task condition.

Cortical thickness is an aggregate measure of the size, density, and organization of neurons and glia in the cortex.⁴⁸ Young and middle-aged adults with multiple mTBIs display cortical thinning, particularly in the frontal and temporal cortices, consistent with findings of decreased gray matter volume in frontal and temporal cortices in moderate TBI.^{27,32,49
–51} Importantly, our results show that such cortical thickness changes can occur in children and adolescents following one relatively “mild” injury. Similar to our findings, Mayer and colleagues discovered a reduction in cortical thickness 4 months after mTBI in adolescents in the left inferior parietal lobule.³² This study also found a reduction in cortical thickness in the left superior and medial frontal, left middle temporal, left postcentral, left cuneus, and left middle occipital gyrus.³² In contrast to the current study, there is evidence for a dose-dependent effect of multiple mTBIs on cortical thinning in the right temporal lobe and left insula, whereas removal of the two participants with multiple mTBIs did not change our pattern of results.²⁸

Although we cannot confirm the mechanism by which the mTBI participants exhibited cortical thinning relative to the control group, it may be that injury disrupts typical neural maturation evident in the post-acute injury phase.²² Histological studies suggest that reduced cortical thickness may represent abnormal pruning and/or loss of neuropils.^21,52,53 Acceleration–deceleration forces can result in localized cellular injury and corresponding cell apoptosis in the long term, as the brain compensates for this injury.³ A longitudinal MRI study suggests that TBI-related cortical thinning may be the result of trauma-induced changes to developmentally appropriate apoptosis, in addition to deleterious neural pruning caused by the injury itself.²² Although white matter disruptions have been observed following mTBI in addition to cortical atrophy and damage to white matter tracts, it is not clear whether cortical thickness changes may alternatively (or additionally) be the result of altered connectivity.^54,55 Recent developmental studies suggest that cortical thickness is not primarily driven by alterations in adjacent white matter; rather, white and gray matter maturation seem to be distinct processes.⁵⁶ On the other hand, cortical thinning has been found to correlate with white matter damage in the frontal and parietal cortices after TBI, despite widespread evidence of both processes in other areas of the brain.⁵⁵ Further studies are needed to clarify if, how, and the extent to which injury-related white matter degeneration influences cortical thickness changes following mTBI.

In line with our hypotheses, slower performance in the mTBI group was associated with thinner cortex in key working memory and dual-task nodes (parietal and DLPFC). These results are consistent with other research that has examined cortical thickness changes in youth with TBI and found alterations in behavior observed post-injury. For example, with respect to parent ratings, associations have been found between social difficulties and thinner frontal poles, emotional dyscontrol and thinning in the medial frontal and right anterior cingulate gyrus, and poor behavioral regulation and thinning in the left frontal lobe.^22,34 A significant relationship between cortical thickness in the inferior temporal, left fusiform, and superior and inferior parietal cortices has also been shown, but the authors failed to describe the direction of such associations.²³ Cortical thickness changes have been associated with poorer task performance in youth with TBI, including weak social problem solving and thinner orbitofrontal regions, frontal poles, cuneus, and temporal poles; and poor prospective memory and thinner bilateral middle and inferior frontal, middle and inferior temporal, and parahippocampal and cingulate gyri, especially on the left.^25,35 The literature suggests then that performance and everyday behavior deficits have a structural substrate underlying functional disruptions. Therefore, given the current findings, we propose that even a single known mTBI can lead to changes in cortical thickness that are related to subtle working memory deficits during conditions of increased task difficulty.

We previously showed late activation of the key brain regions of the working memory circuit (DLPFC and bilateral parietal lobes) in the mTBI group relative to the typically developing youth.⁷ The mTBI group also failed to progressively activate the left DLPFC during dual-task performance; a key area involved in dual-task behavior.^57,58 The current data suggest a structural substrate for the underlying functional changes. That is, the lack of activation in the left DLPFC corresponds to the cortical thinning observed in this brain region, whereas intact behavioral performance in the control group corresponds to functional activation of expected nodes and a thicker left DLPFC. Additionally, delayed hypoactivation of the bilateral parietal lobes during dual task performance in the mTBI group corresponds with the evident cortical thinning in the anterior and posterior IPL.⁷ Similarly, the control group exhibited constant activation of bilateral parietal lobes and faster reaction times during the dual task, which was also related to greater cortical thickness in the posterior IPL. Despite evidence for cortical thinning in the anterior and posterior IPL in the mTBI group, these changes were not correlated to working memory performance, suggesting that these brain regions are involved in other recognized brain functions.⁵⁹ It is also possible that other brain regions are recruited to compensate for disruption in these areas to complete working memory tasks.⁶⁰

Despite the provocative results, the current findings need to be interpreted with caution. First, our findings are limited by the small sample size, and must be replicated with a larger group of participants. Second, the study was cross-sectional in nature; therefore, we were unable to evaluate development trajectories of change. Future studies are needed to explore longitudinal changes in cortical thickness following mTBI, although progressive changes are not expected.^22,26 Future work will also need to explore sex differences (if any), and should include younger children and young adults as well in order to fully describe changes across brain maturation. Moreover, prospective studies are needed to explore whether such functional and structural alterations are present prior to mTBI, as it is possible that the children who exhibited neural abnormalities exhibited some premorbid differences as well. If such a neural vulnerability exists, then cortical thinning may be a risk factor for mTBI and not a consequence of the injury.

Several studies have explored the presence of white matter damage following mTBI.^61
–63 The majority of these studies have used DTI to evaluate white matter integrity in adults and children.^64
–66 These results suggest that other underlying microstructural deficits are evident after mTBI and continue to be present several months after injury. We are currently examining DTI-related changes and possible associations in performance in our current sample of participants. Given our functional and structural findings thus far, we expect to see significant alterations in white matter tracts in the DLPFC and parietal lobes; changes we also expect to see associated with performance.

Conclusion

In conclusion, we have shown that asymptomatic youth who sustained an mTBI 3–8 months prior had thinner cortices in the left DLPFC and right anterior and posterior IPL than did typically developing youth. This cortical thinning was associated with slower reaction time during visual-spatial and working memory dual-task paradigms. Thinning was also associated with functional abnormalities in the mTBI group. Taken together, the results suggest possible long-term effects of mTBI, which may ultimately affect how recovery from mTBI is assessed, and may influence rehabilitation programs. For example, specific paradigms need to be developed to evaluate performance with increased cognitive demand, as the results suggest that associations between microscopic changes (i.e., cortical thinning) and functional alterations were more pronounced during dual-task conditions. Additionally, our research also points to the need for more ecologically valid research protocols to evaluate mTBI so as to increase the sensitivity of our measures of post-injury deficits.

Footnotes

Acknowledgments

This project was funded by the Ontario Neurotrauma Foundation (ONF 2009-ABI-IMAGING-750) awarded to Drs. Keightley and Wells, and the Rita G. Rudel Early Career Award awarded to Dr. Sinopoli. We thank Dr. Elysa Widjaja (staff neuroradiologist, Hospital for Sick Children) for reviewing the clinical MRI scans, and Nick Reed, Sam Liu, and Sabrina Agnihotri for their assistance in the development of the imaging protocols.

Author Disclosure Statement

No competing financial interests exist.

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