The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Dynamic functional connectivity in bipolar disorder is associated with executive function and processing speed: A preliminary study
Open accessAbstract
OBJECTIVE: Disturbances in functional connectivity have been suggested to contribute to cognitive and emotion processing deficits observed in bipolar disorder (BD). Functional connectivity between medial prefrontal cortex (mPFC) and other brain regions may be particularly abnormal. The goal of the present study was to characterize the temporal dynamics of the default mode network (DMN) connectivity in BD and examine its association with cognition. METHOD: In a preliminary study, euthymic BD (n = 15) and healthy comparison (HC, n = 19) participants underwent resting-state functional MRI, using high-resolution sequences adapted from the Human Connectome Project, and completed neuropsychological measures of processing speed and executive function. A seed-based approach was used to measure DMN correlations in each participant, with regions of interest in the mPFC, posterior cingulate cortex (PCC), and lateral parietal cortex. Subsequently, to characterize temporal dynamics, correlational analyses between the mPFC and other DMN nodes were repeated using a sliding-window correlational analysis with subsets of the time series. RESULTS: When averaged across the entire scan, there were no group differences in overall connectivity strength between the mPFC and other regions of the DMN. However, dynamic connectivity between the mPFC and PCC was altered in BD, such that connectivity was less variable (i.e., more rigid) over time. Decreased connectivity variability was associated with slower processing speed and reduced cognitive set-shifting in BD patients. CONCLUSIONS: Variability in resting-state functional connectivity may be an index of internetwork flexibility that is reduced in BD and a correlate of ongoing cognitive impairment during periods of euthymia. (PsycINFO Database Record
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“In depression (the other pole), the precision might crash for positive priors, leading to the state described earlier of hypo-learning and negativity (68, 69).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [68]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817
The Positive and Negative Syndrome Scale (PANSS) for schizophrenia.
Kay, S. R., Fiszbein, A., & Opler, L. A. (1987) · Schizophrenia Bulletin · doi:10.1093/schbul/13.2.261 · Cited by 21,378
(1998) · The Journal of Clinical Psychiatry · Cited by 19,139
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
(1998) · PubMed · Cited by 10,216
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
The organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00338.2011 · Cited by 9,182
Cited by
Sorted by citations
Liu, J., Liao, X., Xia, M., & Yong He, A. (2017) · Human Brain Mapping · doi:10.1002/hbm.23890 · Cited by 212
Wang, J., Wang, Y., Huang, H., Jia, Y., Zheng, S., Zhong, S., Chen, G., Huang, L., & Huang, R. (2019) · Psychological Medicine · doi:10.1017/s003329171900028x · Cited by 139
Long, Y., Cao, H., Yan, C., Chen, X., Li, L., Castellanos, F. X., Bai, T., Bo, Q., Chen, G., Chen, N., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102163 · Cited by 133
Cottam, W. J., Iwabuchi, S. J., Drabek, M. M., Reckziegel, D., & Auer, D. P. (2018) · Pain · doi:10.1097/j.pain.0000000000001209 · Cited by 110
Pang, Y., Chen, H., Wang, Y., Long, Z., He, Z., Zhang, H., Liao, W., Cui, Q., & Chen, H. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.03.020 · Cited by 113
Li, Y., Zhu, Y., Nguchu, B. A., Wang, Y., Wang, H., Qiu, B., & Wang, X. (2020) · Autism Research · doi:10.1002/aur.2212 · Cited by 95
Default mode network activity in bipolar disorder
Zovetti, N., Rossetti, M. G., Perlini, C., Maggioni, E., Bontempi, P., Bellani, M., & Brambilla, P. (2020) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796020000803 · Cited by 82
Vellante, F., Ferri, F., Baroni, G., Croce, P., Migliorati, D., Pettorruso, M., Berardis, D. D., Martinotti, G., Zappasodi, F., & Giannantonio, M. D. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.03.175 · Cited by 70
Cotrena, C., Branco, L. D., Ponsoni, A., Samamé, C., Shansis, F., & Fonseca, R. P. (2019) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13121 · Cited by 69
Pang, Y., Zhang, H., Cui, Q., Yang, Q., Lu, F., Chen, H., He, Z., Wang, Y., Wang, J., & Chen, H. (2020) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867420924089 · Cited by 53
Nyatega, C. O., Li, Q., Adamu, M. J., Younis, A., & Kawuwa, H. B. (2021) · Applied Sciences · doi:10.3390/app112311392 · Cited by 55
Luo, Z., Chen, G., Jia, Y., Zhong, S., Gong, J., Chen, F., Wang, J., Qi, Z., Liu, X., Huang, L., et al. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.11.012 · Cited by 53
Bora, E. (2017) · European Psychiatry · doi:10.1016/j.eurpsy.2017.06.003 · Cited by 48
Little, B., Anwyll, M., Norsworthy, L., Corbett, L., Schultz‐Froggatt, M., & Gallagher, P. (2023) · Bipolar Disorders · doi:10.1111/bdi.13396 · Cited by 43
Cortico-limbic connectivity as a possible biomarker for bipolar disorder: where are we now?
Vai, B., Bertocchi, C., & Benedetti, F. (2019) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2019.1562338 · Cited by 41
Transition and Dynamic Reconfiguration of Whole-Brain Network in Major Depressive Disorder
Wang, S., Wen, H., Hu, X., Xie, P., Qiu, S., Qian, Y., Qiu, J., & He, H. (2020) · Molecular Neurobiology · doi:10.1007/s12035-020-01995-2 · Cited by 44
Cattarinussi, G., Giorgio, A. D., Moretti, F., Bondi, E., & Sambataro, F. (2023) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2023.110827 · Cited by 52
Resting state networks activity in euthymic bipolar disorder
Bellani, M., Bontempi, P., Zovetti, N., Rossetti, M. G., Perlini, C., Dusi, N., Squarcina, L., Marinelli, V., Zoccatelli, G., Alessandrini, F., et al. (2020) · Bipolar Disorders · doi:10.1111/bdi.12900 · Cited by 40
van Geest, Q., Hulst, H. E., Meijer, K. A., Hoyng, L., Geurts, J. J. G., & Douw, L. (2018) · Brain and Behavior · doi:10.1002/brb3.954 · Cited by 38
Lu, F., Chen, Y., Cui, Q., Guo, Y., Pang, Y., Luo, W., Yu, Y., Chen, J., Gao, J., Sheng, W., et al. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhac534 · Cited by 37
Long, Y., Liu, X., & Liu, Z. (2023) · Brain Sciences · doi:10.3390/brainsci13030429 · Cited by 38
Shunkai, L., Su, T., Zhong, S., Chen, G., Zhang, Y., Zhao, H., Chen, P., Tang, G., Qi, Z., He, J., et al. (2021) · Psychological Medicine · doi:10.1017/s0033291721004906 · Cited by 37
Electroencephalographic Microstates in Schizophrenia and Bipolar Disorder
Wang, F., Hujjaree, K., & Wang, X. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.638722 · Cited by 34
Neural correlates of childhood trauma with executive function in young healthy adults
Lu, S., Pan, F., Gao, W., Wei, Z., Wang, D., Hu, S., Huang, M., Xu, Y., & Li, L. (2017) · Oncotarget · doi:10.18632/oncotarget.20051 · Cited by 36
Common and distinct functional stability abnormalities across three major psychiatric disorders
Zhu, J., Zhang, S., Cai, H., Wang, C., & Yu, Y. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102352 · Cited by 33
Long, Y., Ouyang, X., Yan, C., Wu, Z., Huang, X., Pu, W., Cao, H., Liu, Z., & Palaniyappan, L. K. (2023) · Human Brain Mapping · doi:10.1002/hbm.26202 · Cited by 32
Du, M., Zhang, L., Li, L., Ji, E., Han, X., Huang, G., Liang, Z., Shi, L., Yang, H., & Zhang, Z. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.04.005 · Cited by 32
Yue, J.-L., Li, P., Shi, L., Lin, X., Sun, H., & Lü, L. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.02.025 · Cited by 33
Massalha, Y., Maggioni, E., Callari, A., Brambilla, P., & Delvecchio, G. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.03.084 · Cited by 30
Disrupted default mode network connectivity in bipolar disorder: a resting-state fMRI study
Zhao, L., Bo, Q., Zhang, Z., Feng, L., Zhou, Y., & Wang, C. (2024) · BMC Psychiatry · doi:10.1186/s12888-024-05869-y · Cited by 33
Fateh, A. A., Cui, Q., Duan, X., Yang, Y., Chen, Y., Li, D., He, Z., & Chen, H. (2020) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2020.111149 · Cited by 28
Nyatega, C. O., Li, Q., Adamu, M. J., & Kawuwa, H. B. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1054380 · Cited by 27
Gong, J., Chen, G., Zhou, M., Jia, Y., Zhong, S., Chen, F., Lai, S., Luo, Z., Wang, J., Xu, H., et al. (2020) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867420948960 · Cited by 25
Abnormal intrinsic brain functional network dynamics in unmedicated depressed bipolar II disorder
Wang, J., Wang, Y., Huang, H., Jia, Y., Zheng, S., Zhong, S., Huang, L., & Huang, R. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.04.103 · Cited by 24
Rashid, B., Dev, S. I., Esterman, M. S., Schwarz, N. F., Ferland, T., Fortenbaugh, F. C., Milberg, W., McGlinchey, R. E., Salat, D. H., & Leritz, E. C. (2019) · Brain and Behavior · doi:10.1002/brb3.1333 · Cited by 24
Guo, Z., Xiao, S., Chen, G., Zhong, S., Zhong, H., Sun, S., Chen, P., Tang, X., Yang, H., Jia, Y., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03207-0 · Cited by 26
McPhilemy, G., Nabulsi, L., Kilmartin, L., Whittaker, J. R., Martyn, F. M., Hallahan, B. P., McDonald, C., Murphy, K., & Cannon, D. M. (2020) · Brain Connectivity · doi:10.1089/brain.2019.0709 · Cited by 22
Advances in the fMRI analysis of the default mode network: a review
Sanz‐Morales, E., & Melero, H. (2024) · Brain Structure and Function · doi:10.1007/s00429-024-02888-z · Cited by 24
Zhang, H., Palaniyappan, L. K., Wu, Y., Cong, E., Wu, C., Ding, L., Jin, F., Qiu, M., Huang, Y., Wu, Y., et al. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.05.148 · Cited by 20
Ye, J., Sun, H., Gao, S., Dadashkarimi, J., Rosenblatt, M., Rodriguez, R. X., Mehta, S., Jiang, R., Noble, S., Westwater, M. L., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.03.024 · Cited by 20
Cui, G., Wang, Y., Wang, X., Zheng, L., Li, L., Li, P., Zhang, L., Guo, Y. Q., Chen, Y., Sun, Z., et al. (2019) · Behavioural Brain Research · doi:10.1016/j.bbr.2019.112335 · Cited by 20
Tassi, E., Boscutti, A., Mandolini, G. M., Moltrasio, C., Delvecchio, G., & Brambilla, P. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.11.019 · Cited by 18
Chen, P., Chen, G., Zhong, S., Chen, F., Ye, T., Gong, J., Tang, G., Pan, Y., Luo, Z., Qi, Z., et al. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.03.023 · Cited by 18
Wu, Y., Su, Y., Zhu, L.-L., Li, J., Li, Q., Dai, Y., Lin, J., Li, K., & Si, T. (2023) · BMC Psychiatry · doi:10.1186/s12888-023-05083-2 · Cited by 21
Luperdi, S. C., Correa‐Ghisays, P., Vila‐Francés, J., Selva‐Vera, G., Salazar-Fraile, J., Cardoner, N., Ruíz-Veguilla, M., Livianos, L., Tabarés‐Seisdedos, R., & Balanzá‐Martínez, V. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2021.07.008 · Cited by 18
Zhong, S., Chen, P., Lai, S., Chen, G., Zhang, Y., Lv, S., He, J., Tang, G., Pan, Y., Wang, Y., et al. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.09.050 · Cited by 17
Liang, Y., Jiang, X., Zhu, W., Shen, Y., Xue, F., Li, Y., & Chen, Z. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.537981 · Cited by 16
Wang, H., Zhu, R., Tian, S., Zhang, S., Dai, Z., Shao, J., Li, X., Yao, Z., & Lü, Q. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.03.010 · Cited by 14
Biomarker identification in bipolar disorder
Martella, F., Caporali, A., Macellaro, M., Cafaro, R., de Pasquale, F., Dell’Osso, B. M., & D’Addario, C. (2025) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2025.108823 · Cited by 13
Xu, Y., Shang, H., Lu, H., Zhang, J., Yao, L., & Long, Z. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.758137 · Cited by 15
Balsa, L. B., Abu-Akel, A. M., & Mevorach, C. (2024) · Autism Research · doi:10.1002/aur.3117 · Cited by 12
Sastry, N. C., & Banerjee, A. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02929-5 · Cited by 10
Sun, H., Yan, R., Hua, L., Xia, Y. X., Chen, Z., Huang, Y., Wang, X., Xia, Q., Yao, Z., & Lü, Q. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.01.028 · Cited by 10
Shaw, A. D., Sumner, R. L., & Berndt, L. C. S. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1713833 · Cited by 9
State and Trait Anxiety Share Common Network Topological Mechanisms of Human Brain
Li, Y., & Jiang, L. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.859309 · Cited by 9
Cai, L., Shi, J., Dong, Q., Wei, J., & Chen, H. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00696-9 · Cited by 9
Zhuo, C., Ji, F., Lin, X., Tian, H., Wang, L., Xu, Y. J., Wang, W., & Jiang, D. (2020) · Brain and Behavior · doi:10.1002/brb3.1637 · Cited by 7
Qiu, L., Ye, J., Ji, F., Li, G., Li, G., Ma, X., Li, R., Tian, H., Wang, L., Chen, G., et al. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00222-4 · Cited by 6
Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers
Marschall, T. M., Koops, S., Brederoo, S., Cabral, J., Ćurĉić‐Blake, B., & Sommer, I. E. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103351 · Cited by 4
An Overview of Machine Learning Applications in Mood Disorders
Topolski, N., Jeong, S. H., & Mwangi, B. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.017 · Cited by 4
Rich club characteristics of dynamic brain functional networks in resting state
Jiao, Z., Wang, H., Cai, M., Cao, Y., Zou, L., & Wang, S. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6424-4 · Cited by 4
Hanna, S., Ho, V. M., Lucas, M., Vadera, S., Qing, K. Y., Deng, D., King‐Stephens, D., Sazgar, M., Mnatsakanyan, L., Lin, J., et al. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae60d0 · Cited by 3
Zhang, C., Liang, J., Yan, H., Yu, Y. H., Li, X., Huang, W., Li, X., Tang, C., Xu, J., Ou, Y., et al. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119572 · Cited by 3
Yoon, H., Dev, S. I., Sutherland, A. N., & Eyler, L. T. (2018) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2018.03.005 · Cited by 3
Dissociation Pattern in Default-Mode Network Homogeneity in Drug-Naive Bipolar Disorder
Li, S., Teng, Z., Qiu, Y., Pan, P., Wu, C., Jin, K., Wang, L., Chen, J., Tang, H., Xiang, H., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.699292 · Cited by 3
(2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018 · Cited by 3
Chen, Y., Fang, C., Xie, J., Zheng, J., He, Y., Liu, X., Roberts, N., Shen, Y. M., Bai, Y., Wei, W., et al. (2025) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2025.111612 · Cited by 2
Neuroimaging Studies of Effects of Psychotherapy in Depression
Bauer, I. E., & Meyer, T. D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.021 · Cited by 2
Zhang, X., Cheng, X., Chen, J., Sun, J., Yang, X., Li, W., Chen, L., Mao, Y., Liu, Y., Zeng, X., et al. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.04.063 · Cited by 2
Electrophysiological Biomarkers for Mood Disorders
Ramakrishnan, N., Murphy, N., Selvaraj, S., & Cho, R. Y. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.015 · Cited by 2
Zhao, L., Bo, Q., Zhang, Z., Li, F., Zhou, Y., & Wang, C. (2021) · Research Square · doi:10.21203/rs.3.rs-194210/v1 · Cited by 2
Ye, J., Mehta, S., Peterson, H., Ibrahim, A., Saeed, G., Linsky, S., Kreinin, I., Tsang, S. W., Nwanaji-Enwerem, U., Raso, A., et al. (2024) · medRxiv · doi:10.1101/2024.02.25.24303340 · Cited by 2
Na, W.-Q., Su, W., Sun, J., Chen, H.-Z., Wu, L.-N., Li, J., & Mei, L.-F. (2020) · Iranian Red Crescent Medical Journal · doi:10.32592/ircmj.2020.22.12.65 · Cited by 1
Fateh, A. A., Smahi, A., Hassan, M. H. U. H., Cañete‐Massé, C., Mohammed, A. A. Q., Yue, F., Hu, Z., & Zeng, H. (2025) · Epilepsy Research · doi:10.1016/j.eplepsyres.2025.107665 · Cited by 1
Soleimani, N., Wiafe, S.-L., Iraji, A., Pearlson, G. D., & Calhoun, V. D. (2025) · Network Neuroscience · doi:10.1162/netn.a.505 · Cited by 1
Olivo, D., Miola, A., Comini, F. F., Trevisan, N., Librizzi, G., Toffanin, T., Manara, R., & Sambataro, F. (2025) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2025.11.015 · Cited by 1
The impact of functional architecture dynamics in bipolar disorder staging
Caporali, A., Martella, F., Saluzzi, S., Girone, N., Feliciani, B., Cavallotto, C., Pettorruso, M., Gerevini, S., Bondi, E., Perrotta, C., et al. (2026) · NeuroImage Clinical · doi:10.1016/j.nicl.2026.104045 · Cited by 1
Wu, Y.-K., Zhu, L.-L., Li, J., Li, Q., Dai, Y.-R., Li, K., Mitchell, P. B., Si, T., & Su, Y. (2024) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2024.04.014 · Cited by 1
Mechanisms underpinning neurocognitive dysfunction in bipolar disorder
Bora, E. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819182-8.00007-7 · Cited by 1
Brain Imaging and the Mechanisms of Antidepressant Action
Godlewska, B. R., Selvaraj, S., & Cowen, P. J. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.020 · Cited by 1
Effects of Lithium on Brain Structure in Bipolar Disorder
Kaur, J., Kafantaris, V., & Szeszko, P. R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.018 · Cited by 1
Functional Connectome in Bipolar Disorder
Cha, J., & Anand, A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.008 · Cited by 1
Imaging Genetic and Epigenetic Markers in Mood Disorders
Poletti, S., Mazza, E. A., Vai, B., & Benedetti, F. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.012
Brain Imaging of Reward Dysfunction in Unipolar and Bipolar Disorders
Kumar, P., Jiang, Y., & Whitton, A. E. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.006
Resting-State Functional Connectivity in Unipolar Depression
Chen, Z., & Gong, Q. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.007
Brain Imaging Methods in Mood Disorders
Selvaraj, S., Brambilla, P., & Soares, J. C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.002
Kious, B. M., & Renshaw, P. F. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.009
Neuroimaging Brain Inflammation in Mood Disorders
Meyer, J. H. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.011
Functional Near-Infrared Spectroscopy Studies in Mood Disorders
Matsuo, K., & Matsubara, T. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.014
Neuroanatomical Findings in Unipolar Depression and the Role of the Hippocampus
Arnone, D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.003
Neuroimaging Biomarkers in Pediatric Mood Disorders
West, M. P., Tang, W. J., & Singh, M. K. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.005
fMRI Neurofeedback as Treatment for Depression
Skottnik, L., & Linden, D. E. J. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.013
Neuroanatomical Findings in Bipolar Disorder
Tronchin, G., & McDonald, C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.004
Imaging Glutamatergic and GABAergic Abnormalities in Mood Disorders
Scotti-Muzzi, E., Otaduy, M. C. G., Soeiro‐de‐Souza, M. G., & Machado‐Vieira, R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.010
Molecular Imaging of Dopamine and Antipsychotics in Bipolar Disorder
Jauhar, S. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.019
Magnetoencephalography Studies in Mood Disorders
Nugent, A. C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.016
Executive Function Deficits in Bipolar Disorder
Jiang, W., Xu, Z., & Zhao, J. (2021) · Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research · doi:10.2991/assehr.k.210806.095
Selvaraj, S., Brambilla, P., & Soares, J. C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.022
Selvaraj, S., Brambilla, P., & Soares, J. C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108623018.001
Ye, J., Sun, H., Gao, S., Dadashkarimi, J., Rosenblatt, M., Rodriguez, R. X., Mehta, S., Jiang, R., Noble, S., Westwater, M. L., et al. (2022) · medRxiv · doi:10.1101/2022.10.07.22280835
Metadata
- Authors
- Nguyen, T. T., Kovacevic, S., Dev, S. I., Lu, K., Liu, T. T., & Eyler, L. T.
- Affiliations
- VA San Diego Healthcare System (US)
- San Diego State University (US)
- University of California San Diego (US)
- Venue
- Neuropsychology
- Published
- 2017-01
- Volume
- 31
- Issue
- 1
- Pages
- 73-83
- ISSN
- 0894-4105 (ISSN-L)
- 1931-1559
- PMC
- PMC5471616
- OpenAlex
- W2538606748
- Cited by
- 109
- References
- 67
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 11 · 2023: 11 · 2022: 7 · 2021: 33 · 2020: 17 · 2019: 7 · 2018: 6 · 2017: 3
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neuropsychology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (5r01mh083968-05)
- National Institute of Mental Health (R01-MH083968, T32MH019934)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- bipolar disorder, dynamic functional connectivity, default mode network, medial prefrontal cortex, posterior cingulate cortex, processing speed, executive function, set-shifting, cognitive flexibility, euthymia, cognitive impairment
- MeSH terms
- Adult, Bipolar Disorder, Brain, Brain Mapping, Cognition, Cognition Disorders, Emotions, Female, Gyrus Cinguli, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Neuropsychological Tests, Parietal Lobe, Psychometrics, Reaction Time, Reference Values, Prefrontal Cortex, Executive Function
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
