The functional neuroanatomy of bipolar disorder: A consensus model

Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH 45267-0559, USA.
Bipolar Disorders (Impact Factor: 4.89). 06/2012; 14(4):313-25. DOI: 10.1111/j.1399-5618.2012.01022.x
Source: PubMed

ABSTRACT Functional neuroimaging methods have proliferated in recent years, such that functional magnetic resonance imaging, in particular, is now widely used to study bipolar disorder. However, discrepant findings are common. A workgroup was organized by the Department of Psychiatry, University of Cincinnati (Cincinnati, OH, USA) to develop a consensus functional neuroanatomic model of bipolar I disorder based upon the participants' work as well as that of others.
Representatives from several leading bipolar disorder neuroimaging groups were organized to present an overview of their areas of expertise as well as focused reviews of existing data. The workgroup then developed a consensus model of the functional neuroanatomy of bipolar disorder based upon these data.
Among the participants, a general consensus emerged that bipolar I disorder arises from abnormalities in the structure and function of key emotional control networks in the human brain. Namely, disruption in early development (e.g., white matter connectivity and prefrontal pruning) within brain networks that modulate emotional behavior leads to decreased connectivity among ventral prefrontal networks and limbic brain regions, especially the amygdala. This developmental failure to establish healthy ventral prefrontal-limbic modulation underlies the onset of mania and ultimately, with progressive changes throughout these networks over time and with affective episodes, a bipolar course of illness.
This model provides a potential substrate to guide future investigations and areas needing additional focus are identified.

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Available from: Andrew Mark Mcintosh, Apr 04, 2014
    • "Several authors suggested that abnormalities in fronto-limbic structures might identify a neurobiological basis for the pathophysiology and maintenance of bipolar disorder (BD) (Frey et al., 2013; Strakowski et al., 2012; Vai et al., 2014). Neuroimaging studies confirmed alterations within this network in BD (Strakowski et al., 2012, 2005) and consistently reported a reduced functional and effective connectivity (Almeida et al., 2009a, 2009b; Anticevic et al., 2012; Dickstein et al., 2010; Liu et al., 2013; Radaelli et al., 2015; Rich et al., 2008; Townsend et al., 2013; Vizueta et al., 2012). A core structure in this circuitry is amygdala (Amy), involved in perceiving stimuli with affective salience (Amaral and Price, 1984; LeDoux, 2000). "
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    ABSTRACT: The identification of antidepressant response predictors in bipolar disorder (BD) may provide new potential enhancements in treatment selection. Repeated total sleep deprivation combined with light therapy (TSD+LT) can acutely reverse depressive symptoms and has been proposed as a model antidepressant treatment. This study aims at investigating the effect of TSD+LT on effective connectivity and neural response in cortico-limbic circuitries during implicit processing of fearful and angry faces in patients with BD. fMRI and Dynamic Causal Modeling (DCM) were combined to study the effect of chronotherapeutics on neural responses in healthy controls (HC, n=35) and BD patients either responder (RBD, n=26) or non responder (nRBD, n=11) to 3 consecutive TSD+LT sessions. Twenty-four DCMs exploring connectivity between anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), Amygdala (Amy), fusiform gyrus and visual cortex were constructed. After treatment, patients significantly increased their neural responses in DLPFC, ACC and insula. nRBD showed lower baseline and endpoint neural responses than RBD. The increased activity in ACC and in medial prefrontal cortex, associated with antidepressant treatment, was positively associated with the improvement of depressive symptomatology. Only RBD patients increased intrinsic connectivity from DLPFC to ACC and reduced the modulatory effect of the task on Amy-DLPFC connection. A successful antidepressant treatment was associated with an increased functional activity and connectivity within cortico-limbic networks, suggesting the possible role of these measures in providing possible biomarkers for treatment efficacy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    07/2015; DOI:10.1016/j.pscychresns.2015.07.015
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    • "The ventral striatum is a key component of neural circuitry underlying reward processing including the ventral prefrontal cortex and the anterior cingulated brain regions. Strakowski et al. (2012) report that BD Type I arises from abnormalities in the structure and function of key emotional control networks in the brain, implicating ventral prefrontal networks and limbic brain regions. Caseras et al. (2013) found that ventral striatum activity in subjects with BD Type II was significantly greater than in those with BD Type I or controls subjects and had higher volume in the left putamen than those with BD Type I. Furthermore, Liu et al. () reported BD Type II patients to show more fiber alterations in the temporal and inferior prefrontal regions. "
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    ABSTRACT: Background Bipolar disorder (BD) is a debilitating psychiatric disorder affecting millions of people worldwide with mean time to diagnosis estimated to be at least 10 years. Whilst many brain imaging studies have compared those with BD to controls, few have attempted to investigate differences between BD Type I and II and matched controls. Methods Thirty-one patients with BD (16 Type I and 15 Type II) and 31 matched healthy controls were MRI brain scanned with conventional T1-weighted and diffusion tensor imaging methods. Results There was significantly reduced regional brain volume and thickness among the BD subjects, but also between BD Type I when compared to Type II. White matter integrity also differed between the groups and BD severity correlated significantly with regional brain volume and thickness. Limitations Future investigations will consider length of time each BD patient had been diagnosed with BD, as well as assessing controls for family history of psychiatric illness, specifically BD. Similarly, genetic assessment will be conducted as well. Conclusions These findings suggest that there are not only regional brain volumetric, thickness and white matter integrity differences between BD and matched controls, but also between those with BD Type I and Type II, such that reduced regional brain volume may underlie BD Type I whereas white matter integrity is more altered in BD Type II.
    Journal of Affective Disorders 12/2014; 169:118–127. DOI:10.1016/j.jad.2014.08.016 · 3.71 Impact Factor
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    • "Structural variations in amygdala and hippocampal volume are also common in BD (Strakowski et al., 2012; Phillips and Swartz, 2014), suggesting the involvement of BAS, FFFS and BIS. Yet, results in these regions vary with respect to the type of abnormality (e.g., Pearlson et al., 1997; Altshuler et al., 1998), possibly due to inter-study variations in medication regimes and comorbidities. "
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    ABSTRACT: Motivation is a key neurobehavioral concept underlying adaptive responses to environmental incentives and threats. As such, dysregulation of motivational processes may be critical in the formation of abnormal behavioral patterns/tendencies. According to the long standing model of the Reinforcement Sensitivity Theory (RST), motivation behaviors are driven by three neurobehavioral systems mediating the sensitivity to punishment, reward or goal-conflict. Corresponding to current neurobehavioral theories in psychiatry, this theory links abnormal motivational drives to abnormal behavior; viewing depression and mania as two abnormal extremes of reward driven processes leading to either under or over approach tendencies, respectively. We revisit the RST framework in the context of bipolar disorder (BD) and challenge this concept by suggesting that dysregulated interactions of both punishment and reward related processes better account for the psychological and neural abnormalities observed in BD. We further present an integrative model positing that the three parallel motivation systems currently proposed by the RST model, can be viewed as subsystems in a large-scale neurobehavioral network of motivational decision making.
    Frontiers in Behavioral Neuroscience 11/2014; 8:378. DOI:10.3389/fnbeh.2014.00378 · 4.16 Impact Factor
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