Neural correlates of cognitive flexibility in children at risk for bipolar disorder
Introduction
In this study, to examine a potential neurobiological endophenotype of bipolar disorder (BD), we compared neural activity in youth with BD, unaffected youth at familial risk for BD, and healthy volunteers while they completed a cognitive flexibility task. Cognitive flexibility, the ability to adapt one’s behavior to changes in the environment, is essential to higher cognitive functions such as decision-making, problem-solving, reward processing and emotion regulation (Davidson et al., 2006, Dempster, 1992, Stemme et al., 2005). Cognitive flexibility deficits have been found in both children and adults with BD across mood states (Arts et al., 2008, Dickstein et al., 2007), as well as in other psychiatric disorders including schizophrenia (Daban et al., 2006) and attention-deficit hyperactivity disorder (ADHD) (Walshaw et al., 2010). Such deficits may limit patients’ ability to consider and execute alternative response options (Goldberg and Chengappa, 2009), thus leading to severe impairment in decision making and social functioning (Leibenluft and Rich, 2008, Pavuluri et al., 2005).
Cognitive flexibility is measured using various paradigms that involve switching stimuli, responses, rules and/or tasks. Across such paradigms, regions activated during cognitive flexibility include ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex (DLPFC), parietal association cortex, and striatum. The striatum primarily mediates motor control during such tasks (Vink et al., 2005), while VLPFC (BA44/45/47) and DLPFC (9/46) play a role in response inhibition and switching (Aron et al., 2004, Bunge, 2004, Rubia, 2010). Together, the prefrontal and parietal cortex mediate top-down attention control (Barber and Carter, 2005, Sohn et al., 2000).
In this study, we used the change task to study the circuitry mediating cognitive flexibility. The change task is adapted from the stop-signal paradigm developed by Logan et al. (1997). It is a response switching task that requires individuals to inhibit a prepotent response and switch rapidly to an alternative response when the change cue is presented (Kenner et al., 2010). Therefore, the change task engages three major components of cognitive flexibility: attention control, response inhibition, and response switching. A previous study using the change task in healthy adults demonstrated that cognitive flexibility during the task is associated with recruitment of VLPFC, DLPFC, and parietal cortex, as well as striatum (Kenner et al., 2010).
Data indicate that both youth and adults with BD show behavioral deficits on cognitive flexibility tasks, including the change (Dickstein et al., 2007, McClure et al., 2005), Wisconsin Card Sort (Fleck et al., 2008, Martinez-Aran et al., 2004), reversal learning (Gorrindo et al., 2005), set-shifting (McKirdy et al., 2009), and response inhibition tasks (McClure et al., 2005, Pavuluri et al., 2006). Functional MRI studies suggest that such deficits are mediated by dysfunction in a variety of regions that participate in flexible responding including DLPFC, VLPFC, parietal association cortex, and striatum (Blumberg et al., 2003, Chang et al., 2004, Dickstein et al., 2010, Passarotti et al., 2010, Singh et al., 2010, Strakowski et al., 2005). For example, a study using the change task found hyperactivity, which may reflect inefficiency, in DLPFC among BD youth compared to healthy controls during successful response substitution (Nelson et al., 2007). In addition, abnormalities in VLPFC, parietal, striatal activity have been found among BD youth during successful response inhibition (Leibenluft et al., 2007, Passarotti et al., 2010).
In addition to these findings in probands, unaffected adult relatives of adults with BD exhibit deficits in cognitive flexibility (Balanza-Martinez et al., 2008, Bora et al., 2009), although findings are somewhat inconsistent (Schulze et al., 2011). The only existing study of cognitive function in unaffected youth at familial risk for BD found behavioral impairment on attention control (Brotman et al., 2009) and a working memory/interference control task (Doyle et al., 2009). Recent fMRI studies reveal altered prefrontal and parietal activation among relatives of BD adult patients during working memory (Drapier et al., 2008, Thermenos et al., 2009). Effective deployment of working memory is an important component of cognitive flexibility (Bunge and Wright, 2007). Specifically, working memory deficits may lead to failed inhibition of goal-irrelevant responses and inability to select appropriate alternative responses. However, to our knowledge, no published fMRI study has yet examined neural activity during a cognitive flexibility task in unaffected first-degree relatives (either children or adults) of patients with BD.
Thus, the current study aims to identify neurobiological deficits during a cognitive flexibility task in unaffected, medication-naïve, psychopathology-free youth at risk for BD. Such deficits would be a candidate endophenotype for BD (Gottesman and Gould, 2003). Compared to studying adults at risk for BD, examining youths at risk for the illness has two advantages. First, the adult relatives of subjects with BD have passed the age of risk for the illness, so findings in that population may reflect resilience as much as risk. Second, data in unaffected youth at familial risk for BD may contribute to efforts to prevent such youth from developing BD or other mood disorders.
In the current study, we compared brain activation during the change task among unaffected at-risk youth with a first-degree relative with BD, BD youth, and healthy volunteer youth. We focused on group differences in brain activations on three contrasts – (1) successful response substitution (successful change) vs. successful execution of the prepotent response (successful go); (2) unsuccessful response substitution (unsuccessful change) vs. successful go; (3) successful change vs. unsuccessful change contrast. Based on previous studies in BD probands and adult relatives of BD patients (Drapier et al., 2008, Leibenluft et al., 2007, Nelson et al., 2007, Passarotti et al., 2010, Singh et al., 2010, Thermenos et al., 2009), we hypothesized that BD youth and unaffected at-risk youth would show altered activation relative to controls in VLPFC, DLPFC, parietal, and striatal regions, regions known to mediate cognitive flexibility during the change task.
Section snippets
Participants
Participants were patients with pediatric bipolar disorder (BD), at-risk (AR) youth, and healthy volunteer (HV) youth. Participants aged 8–17 were enrolled in an Institutional Review Board-approved protocol at the National Institute of Mental Health. Parents and youth provided written informed consent and assent, respectively. BD patients were recruited through advertisements placed on support groups’ websites and distributed to psychiatrists nationwide. AR youth were recruited by advertisement
Demographic, clinical and behavioral data
Participant groups did not differ on age, race, IQ, or gender (Table 1). Clinical characteristics of BD youth, including comorbid illnesses, mood state, and medications are reported in Table 1. Means and standard deviations of behavioral performance are also reported in Table 1. No between-group differences were found for any behavioral measure, including percent accuracy on go trials, F(2,59) = .79, or on change trials, F(2,59) = .55, mean inhibit delay, F(2,59) = 2.24, mean reaction time on
Discussion
The current study examined group differences in the neural correlates of cognitive flexibility among BD youth, youth at risk for BD (AR), and healthy volunteers (HV) using the change task. Despite having similar behavioral performance on the task, during successful response switching, BD youth showed greater activation in right VLPFC (BA45) than HV youth, while AR youth showed greater activation in right VLPFC (BA44/45/47) than both HV and BD youth. In addition, compared to HV, both BD and AR
Contributors
Pilyoung Kim took the lead in every process including the project design, data process, data analysis, manuscript writing and revision. Sarah Jenkins, Megan Connolly, and Christen Deveney assisted in conducting the experiments, data process, data analysis and manuscript revision. Stephen Fromm contributed to data process and data analysis. Melissa Brotman contributed to participant recruitment, and manuscript revision. Eric Nelson, and Daniel Pine contributed to data analysis, and manuscript
Role of funding sources
Funding for this study was provided exclusively by the Intramural Research Program of the National Institute of Mental Health, National Institutes of Health. The funding sources had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Conflict of interest
The authors have no conflicts to disclose.
Acknowledgments
We would like to thank the staffs of the Emotion and Development Branch at NIMH and the children and families for their participation.
References (62)
- et al.
Neurocognitive endophenotypes (endophenocognitypes) from studies of relatives of bipolar disorder subjects: a systematic review
Neuroscience and Biobehavioral Reviews
(2008) - et al.
Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives
Journal of Affective Disorders
(2009) - et al.
Neurodevelopmental changes in working memory and cognitive control
Current Opinion in Neurobiology
(2007) - et al.
Development of cognitive control and executive functions from 4 to 13 years: evidence from manipulations of memory, inhibition, and task switching
Neuropsychologia
(2006) The rise and fall of the inhibitory mechanism: toward a unified theory of cognitive development and aging
Developmental Review
(1992)- et al.
Cognitive flexibility in phenotypes of pediatric bipolar disorder
Journal of the American Academy of Child and Adolescent Psychiatry
(2007) - et al.
Genetic liability for bipolar disorder is characterized by excess frontal activation in response to a working memory task
Biological Psychiatry
(2008) - et al.
Schedule for Affective disorders and schizophrenia for School-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data
Journal of the American Academy of Child and Adolescent Psychiatry
(1997) - et al.
Neural correlates of response inhibition in pediatric bipolar disorder and attention deficit hyperactivity disorder
Psychiatry Research
(2010) - et al.
Pediatric bipolar disorder: a review of the past 10 years
Journal of the American Academy of Child and Adolescent Psychiatry
(2005)