Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach

Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipol...

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Veröffentlicht in:Brain (London, England : 1878) England : 1878), 2016-09, Vol.139 (Pt 9), p.2554-2566
Hauptverfasser: Manelis, Anna, Almeida, Jorge R C, Stiffler, Richelle, Lockovich, Jeanette C, Aslam, Haris A, Phillips, Mary L
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container_end_page 2566
container_issue Pt 9
container_start_page 2554
container_title Brain (London, England : 1878)
container_volume 139
creator Manelis, Anna
Almeida, Jorge R C
Stiffler, Richelle
Lockovich, Jeanette C
Aslam, Haris A
Phillips, Mary L
description Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy con
doi_str_mv 10.1093/brain/aww157
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Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. 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These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. 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Almeida, Jorge R C ; Stiffler, Richelle ; Lockovich, Jeanette C ; Aslam, Haris A ; Phillips, Mary L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c450t-8bfc7a732b648938cdb3223d12d2fcda931e2ca4c34bd8847f951f5c7e592f2f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Anticipation, Psychological - physiology</topic><topic>Bipolar Disorder - diagnostic imaging</topic><topic>Bipolar Disorder - physiopathology</topic><topic>Connectome - methods</topic><topic>Depressive Disorder, Major - diagnostic imaging</topic><topic>Depressive Disorder, Major - physiopathology</topic><topic>Female</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Nerve Net - diagnostic imaging</topic><topic>Nerve Net - physiopathology</topic><topic>Original</topic><topic>Prefrontal Cortex - diagnostic imaging</topic><topic>Prefrontal Cortex - physiopathology</topic><topic>Reward</topic><topic>Ventral Striatum - diagnostic imaging</topic><topic>Ventral Striatum - physiopathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Manelis, Anna</creatorcontrib><creatorcontrib>Almeida, Jorge R C</creatorcontrib><creatorcontrib>Stiffler, Richelle</creatorcontrib><creatorcontrib>Lockovich, Jeanette C</creatorcontrib><creatorcontrib>Aslam, Haris A</creatorcontrib><creatorcontrib>Phillips, Mary L</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Brain (London, England : 1878)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Manelis, Anna</au><au>Almeida, Jorge R C</au><au>Stiffler, Richelle</au><au>Lockovich, Jeanette C</au><au>Aslam, Haris A</au><au>Phillips, Mary L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach</atitle><jtitle>Brain (London, England : 1878)</jtitle><addtitle>Brain</addtitle><date>2016-09-01</date><risdate>2016</risdate><volume>139</volume><issue>Pt 9</issue><spage>2554</spage><epage>2566</epage><pages>2554-2566</pages><issn>0006-8950</issn><eissn>1460-2156</eissn><abstract>Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. These findings suggest that different neurobiological mechanisms may underlie aberrant anticipation processes in BDD and MDD, and that distinct therapeutic strategies may be required for these individuals to improve coping strategies during expectation of positive and negative outcomes.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>27368345</pmid><doi>10.1093/brain/aww157</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record>
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subjects Adult
Anticipation, Psychological - physiology
Bipolar Disorder - diagnostic imaging
Bipolar Disorder - physiopathology
Connectome - methods
Depressive Disorder, Major - diagnostic imaging
Depressive Disorder, Major - physiopathology
Female
Humans
Magnetic Resonance Imaging
Male
Nerve Net - diagnostic imaging
Nerve Net - physiopathology
Original
Prefrontal Cortex - diagnostic imaging
Prefrontal Cortex - physiopathology
Reward
Ventral Striatum - diagnostic imaging
Ventral Striatum - physiopathology
title Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach
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