Evaluation of Cerebral Cortex Function in Clients with Bipolar Mood Disorder I (BMD I) Compared With BMD II Using QEEG Analysis
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Abstract
Objective: Early diagnosis of type I and type II bipolar mood disorder is very challenging particularly in adolescence. Hence, we aimed to investigate the cerebral cortex function in these patients, using quantitative electroencephalography analysis to obtain significant differences between them.
Methods: Thirty- eight adolescents (18 patients with bipolar disorder I and 20 with BMD II) participated in this study. We recorded the electroencephalogram signals based on 10-20 international system by 21 electrodes in eyes open and eyes closed condition resting conditions. Forty seconds segments were selected from each recorded signals with minimal noise and artifacts. Periodogram Welch was used to estimate power spectrum density from each segment. Analysis was performed in five frequency bands (delta, theta, alpha, beta and gamma), and we assessed power, mean, entropy, variance and skewness of the spectrums, as well as mean of the thresholded spectrum and thresholded spectrogram. We only used focal montage for comparison. Eventually, data were analyzed by independent Mann-Whitney test and independent t test.
Results: We observed significant differences in some brain regions and in all frequency bands. There were significant differences in prefrontal lobe, central lobe, left parietal lobe, occipital lobe and temporal lobe between BMD I and BMD II (P < 0.05). In patients with BMD I, spectral entropy was compared to patients with BMD II. The most significant difference was observed in the gamma frequency band. Also, the power and entropy of delta frequency band was larger in the left parietal lobe in the BMD I patients compared to BMD II patients (P < 0.05). In the temporal lobe, significant differences were observed in the spectrum distribution of beta and gamma frequency bands (P < 0.05).
Conclusion: The QEEG and entropy measure are simple and available tools to help detect cerebral cortex deficits and distinguish BMD I from BMD II.
Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Text Revision: DSM IV TR. Washington DC: American Psychiatric Association; 2000.
Bauer M, Pfenning A. Epidemiology of bipolar disorders. Epilepsia 2005; 4: 8-13.
Pini S, de Queiroz V, Pagnin D, Pezawas L, Angst J, Cassano GB, et al. Prevalence and burden of bipolar disorders in European countries. European Neuro psychopharmacology 2005:15: 425-434.
Sadock BJ, Sadock VA. Kaplan & Sadock's Synopsis of Psychiatry,10th eds. New York: Lippincott Williams & Wilkins; 2007.
Hadjipavlou GH, Yatham L. Bipolar II Disorder: an overview of recent developments. Canadian Journal of Psychiatry 2004; 49: 802–812.
Vieta E, Gastó C, Otero A, Nieto E, Vallejo J. Differential features between bipolar I and bipolar II disorder. Comprehensive Psychiatry 1997; 38: 98-101.
Ghaemi SN, Ko JY, Goodwin FK. "Cade's disease" and beyond: misdiagnosis, antidepressant use, and a proposed definition for bipolar spectrum disorder. Can J Psychiatry 2002; 47:125-134.
Yatham L. Diagnosis and management of patients with Bipolar II Disorder. Journal of Clinical Psychiatry 2004; 66(Suppl. 1), S13–17.
Angst J. Do many patients with depression suffer from bipolar disorder? Journal of Psychiatry 2006; 51: 3–5.
Chun J, Karam ZN, Marzinzik F, Kamali M, O'Donnell L, Tso IF, Manschreck TC, McInnis M, Deldin PJ. Can P300 distinguish among schizophrenia, schizoaffective and bipolar I disorders? An ERP study of response inhibition. Schizophrenia research 2013; 151: 175-184.
Boutros NN. Standard electroencephalography in clinical psychiatry: a practical handbook. Wiley practicalhandbooks for psychiatry series. Wiley-Blackwell, Chichester, West Sussex; Hoboken, NJ; 2011.
Prichep LS, John ER. QEEG profiles of psychiatric disorders. Brain topography 1992; 4: 249-257.
Shagass C, Roemer RA, Straumanis JJ (1982) Relationships between psychiatric diagnosis and some quantitative EEG variables. Archives of general psychiatry 1982; 39: 1423-1435.
Coutin-Churchman P, Añez Y, Uzcátegui M, Alvarez L, Vergara F, Mendez L, Fleitas R. Quantitative spectral analysis of EEG in psychiatry revisited: drawing signs out of numbers in a clinical setting. Clinical Neurophysiology 2003; 114: 2294-2306.
Nuwer M. Assessment of digital EEG, quantitative EEG, and EEG brain mapping: Report of the American Academy of Neurology and the American Clinical Neurophysiology Society*. Neurology 1997; 49: 277-292.
Oluboka OJ, Stewart SL, Sharma V, Mazmanian D, Persad E. Preliminary assessment of intrahemispheric QEEG measures in bipolar mood disorders 2002; 47: 368-374.
Bahrami B, Seyedsajadi R, Babadi B, Nooroozian M. Brain complexity increases in mania. Neuroreport 2005; 16: 187–191.
Harmon-Jones E, Abramson L Y, Nusslock, R, Sigelman JD, Urosevic S, Turonie LD, et al. Effect of bipolar disorder on left frontal cortical responses to goals differing in valence and task difficulty, Clinical Neurophysiology 2008; 116: 1455–1463.
Adeleh Dehghani Nazhvani, Reza Boostani, Somayeh Afrasiabi, Khadijeh Sadatnezhad, Classification of ADHD and BMD patients using visual evoked potential, Clinical Neurology and Neurosurgery 2013; 115: 2329–2335.
Alimardani F, Boostani R, Azadehdel M, Ghanizadeh A, Rastegar K. Presenting a new search strategy to select synchronization values for classifying bipolar mood disorders from schizophrenic patients, Elsevier, Engineering Applications of Artificial Intelligence, 2012.
Sadatnezhad K, Boostani R, Ghanizadeh A, Classification of BMD and ADHD patients using their EEG signals, Elsevier,Expert Systems with Applications 2011; 38: 1956–1963.
Venables NC, Bernat EM, Sponheim SR. Genetic and disorder-specific aspects of resting state EEG abnormalities in Schizophrenia. Schizophr Bull 2009; 35: 826–839.
Gudmundsson S, Runarsson T, Sigurdsson S, Eiriksdottir G, Johnsen K, Reliability of quantitative EEG features, Elsevier, Clinical Neurophysiology 2007; 118: 2162–2171.
Sheikhani A, Behnam H, Noroozian M, Mohammadi M, Mohammadi M. Abnormalities of quantitative electroencephalography in children with Asperger disorder in various conditions Research in Autism Spectrum Disorders 2009; 3: 538–546.
Ambrosi E, Rossi-Espagnet MC, Kotzalidis GD, Comparelli A, Del Casale A, Carducci F, Romano A, Manfredi G, Tatarelli R, Bozzao A, Girardi P, Structural brain alterations in bipolar disorder II: a combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) study, J Affect Disord. 2013; 150: 610-615.
James A. Harley, J. Elisabeth Wells, Christopher M. A. Frampton, Peter R. Joyce, Bipolar Disorder and the TCI: Higher Self-Transcendence in Bipolar Disorder Compared to Major Depression, Depress Res Treat. 2011.
Liang M, Zhou Q, Yang K, Yang X, Fang J, Chen W, Huang Z, Identify Changes of Brain Regional Homogeneity in Bipolar Disorder and Unipolar Depression Using Resting-State fMRI. PLoS One 2013; 8.
Lan MJ, Chhetry BT, Oquendo MA, Sublette ME, Sullivan G, Mann JJ, Parsey RV, Cortical thickness differences between bipolar depression and major depressive disorder, Bipolar Disord 2014; 16.
Liu CH, Li F, Li SF, Wang YJ, Tie CL, Wu HY, Zhou Z, Zhang D, Dong J, Yang Z, Wang CY, Abnormal baseline brain activity in bipolar depression: a resting state functional magnetic resonance imaging study, Psychiatry Res. 2012; 203:175-179.
Xu K, Liu H, Li H, Tang Y, Womer F, Jiang X, Chen K, Zhou Y, Jiang W, Luo X, Fan G, Wang F, Amplitude of low-frequency fluctuations in bipolar disorder: a resting state fMRI study, J Affect Disord. 2014; 154: 237-242.
Frith CD, Frith U, Interacting minds–a biological basis. Science 1999; 286: 1692–1695.
Lockwood KA, Alexopoulos GS, van Gorp WG, Executive dysfunction in geriatric depression. Am J Psychiatry 2002; 159: 1119–1126.
Clementz B, Sponheim S, Iacono G, Beiser M. Resting EEG in first - episode schizophrenia patients, bipolar psychosis patients, and their first- degree relatives. Psychophysiology, 1994; 31: 486–494.
Koles J, Lind C, Flor-Henry P. Spatial patterns in the background EEG underlying mental disease in man. Electroencephalogr. Clin. Neurophysiol 1994; 91: 319–328.
Schnack HG, Nieuwenhuis M, van Haren NE, Abramovic L, Scheewe TW, Brouwer RM, Hulshoff Pol HE, Kahn RS, Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects, Neuroimage. 2014; 84: 299-306.
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| Issue | Vol 10 No 2 (2015) | |
| Section | Original Article(s) | |
| Keywords | ||
| Bipolar Mood Disorder I Bipolar Mood Disorder II Quantitative Electroencephalography Entropy | ||
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