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Abnormalities in the effective connectivity of visuothalamic circuitry in schizophrenia

Published online by Cambridge University Press:  12 January 2017

S. J. Iwabuchi  and
L. Palaniyappan
S. J. Iwabuchi
Affiliation:
Translational Neuroimaging for Mental Health, Division of Psychiatry and Applied Psychology, University of Nottingham, Nottingham, UK
L. Palaniyappan*
Affiliation:
Departments of Psychiatry & Medical Biophysics, University of Western Ontario, London, Ontario, Canada Robarts Research Institute & The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada Lawson Health Research Institute, London Ontario, Canada
*
*Address for correspondence: Dr L. Palaniyappan, Prevention & Early Intervention Program for Psychoses (PEPP), A2-636, LHSC-VH, 800 Commissioners Road, London, Ontario N6A 5W9, Canada. (Email: Lena.Palaniyappan@lhsc.on.ca)
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Abstract

Background

Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls.

Method

Using publicly available resting fMRI data of 71 controls and 62 schizophrenia patients, we derived conjunction maps of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) to inform further seed-based Granger causality analysis (GCA) to study effective connectivity patterns. ReHo, fALFF and GCA maps were entered into a multiple kernel learning classifier, to determine whether patterns of local and effective connectivity can differentiate controls from patients.

Results

Visual cortex shows both ReHo and fALFF reductions in patients. Visuothalamic effective connectivity in patients was significantly reduced. Local connectivity (ReHo) patterns discriminated patients from controls with the highest level of accuracy of 80.32%.

Conclusions

Both the inflow and outflow of Granger causal information between visual cortex and thalamus is affected in schizophrenia; this occurs in conjunction with highly discriminatory but localized dysconnectivity and reduced neural activity within the visual cortex. This may explain the visual-processing deficits that are present despite symptomatic remission in schizophrenia.

Keywords

Effective connectivityfractional amplitutude of low frequency fluctuationsmachine learningregional homogeneityschizophreniavisuothalamic.
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 7 , May 2017 , pp. 1300 - 1310
Copyright
Copyright © Cambridge University Press 2017 

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References

Ananth, H, Popescu, I, Critchley, HD, Good, CD, Frackowiak, RSJ, Dolan, RJ (2002). Cortical and subcortical gray matter abnormalities in schizophrenia determined through structural magnetic resonance imaging with optimized volumetric voxel-based morphometry. American Journal of Psychiatry 159, 1497–1505.CrossRefGoogle ScholarPubMed
Andreasen, NC, O'Leary, DS, Cizadlo, T, Arndt, S, Rezai, K, Ponto, LL, Watkins, GL, Hichwa, RD (1996). Schizophrenia and cognitive dysmetria: a positron-emission tomography study of dysfunctional prefrontal-thalamic-cerebellar circuitry. Proceedings of the National Academy of Sciences USA 93, 9985–9990.Google Scholar
Andreasen, NC, Pressler, M, Nopoulos, P, Miller, D, Ho, B-C (2010). Antipsychotic dose equivalents and dose-years: a standardized method for comparing exposure to different drugs. Biological Psychiatry 67, 255–262.CrossRefGoogle ScholarPubMed
Anticevic, A, Cole, MW, Repovs, G, Murray, JD, Brumbaugh, MS, Winkler, AM, Savic, A, Krystal, JH, Pearlson, GD, Glahn, DC (2014). Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness. Cerebral Cortex 24, 3116–3130.CrossRefGoogle ScholarPubMed
Anticevic, A, Gancsos, M, Murray, JD, Repovs, G, Driesen, NR, Ennis, DJ, Niciu, MJ, Morgan, PT, Surti, TS, Bloch, MH, Ramani, R, Smith, MA, Wang, X-J, Krystal, JH, Corlett, PR (2012). NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia. Proceedings of the National Academy of Sciences USA 109, 16720–16725.Google Scholar
Anticevic, A, Haut, K, Murray, JD, Repovs, G, Yang, GJ, Diehl, C, McEwen, SC, Bearden, CE, Addington, J, Goodyear, B, Cadenhead, KS, Mirzakhanian, H, Cornblatt, BA, Olvet, D, Mathalon, DH, McGlashan, TH, Perkins, DO, Belger, A, Seidman, LJ, Tsuang, MT, van Erp, TG, Walker, EF, Hamann, S, Woods, SW, Qiu, M, Cannon, TD (2015). Association of thalamic dysconnectivity and conversion to psychosis in youth and young adults at elevated clinical risk. JAMA Psychiatry 72.Google Scholar
Arbabshirani, MR, Kiehl, KA, Pearlson, GD, Calhoun, VD (2013). Classification of schizophrenia patients based on resting-state functional network connectivity. Frontiers in Neuroscience 7, 133.Google Scholar
Ashburner, J (2007). A fast diffeomorphic image registration algorithm. NeuroImage 38, 95–113.Google Scholar
Behrens, TEJ, Johansen-Berg, H, Woolrich, MW, Smith, SM, Wheeler-Kingshott, CAM, Boulby, PA, Barker, GJ, Sillery, EL, Sheehan, K, Ciccarelli, O, Thompson, AJ, Brady, JM, Matthews, PM (2003). Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nature Neuroscience 6, 750–757.Google Scholar
Boutros, NN, Arfken, C, Galderisi, S, Warrick, J, Pratt, G, Iacono, W (2008). The status of spectral EEG abnormality as a diagnostic test for schizophrenia. Schizophrenia Research 99, 225–237.CrossRefGoogle ScholarPubMed
Butler, PD, Javitt, DC (2005). Early-stage visual processing deficits in schizophrenia. Current Opinion in Psychiatry 18, 151–157.CrossRefGoogle ScholarPubMed
Butler, PD, Martinez, A, Foxe, JJ, Kim, D, Zemon, V, Silipo, G, Mahoney, J, Shpaner, M, Jalbrzikowski, M, Javitt, DC (2007). Subcortical visual dysfunction in schizophrenia drives secondary cortical impairments. Brain 130, 417–430.Google Scholar
Chang, L, Friedman, J, Ernst, T, Zhong, K, Tsopelas, ND, Davis, K (2007). Brain metabolite abnormalities in the white matter of elderly schizophrenic subjects: implication for glial dysfunction. Biological Psychiatry 62, 1396–1404.Google Scholar
Chao-Gan, Y, Yu-Feng, Z (2010). DPARSF: a MATLAB toolbox for ‘Pipeline’ data analysis of resting-state fMRI. Frontiers in Systems Neuroscience 4, 13.Google Scholar
Cheng, W, Palaniyappan, L, Li, M, Kendrick, KM, Zhang, J, Luo, Q, Liu, Z, Yu, R, Deng, W, Wang, Q, Ma, X, Guo, W, Francis, S, Liddle, P, Mayer, AR, Schumann, G, Li, T, Feng, J (2015). Voxel-based, brain-wide association study of aberrant functional connectivity in schizophrenia implicates thalamocortical circuitry. npj Schizophrenia 1, 15016.Google Scholar
Chyzhyk, D, Graña, M, Öngür, D, Shinn, AK (2015). Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI. International Journal of Neural Systems 25, 1550007.Google Scholar
Deco, G, Ponce-Alvarez, A, Hagmann, P, Romani, GL, Mantini, D, Corbetta, M (2014). How local excitation–inhibition ratio impacts the whole brain dynamics. Journal of Neuroscience 34, 7886–7898.CrossRefGoogle ScholarPubMed
Duncan, KJ, Pattamadilok, C, Knierim, I, Devlin, JT (2009). Consistency and variability in functional localisers. NeuroImage 46, 1018–1026.Google Scholar
Friston, KJ, Ashburner, J, Frith, CD, Poline, J-B, Heather, JD, Frackowiak, RSJ (1995). Spatial registration and normalization of images. Human Brain Mapping 3, 165–189.Google Scholar
Guo, S, Palaniyappan, L, Liddle, PF, Feng, J (2016). Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study. Psychological Medicine 46, 1–14.Google Scholar
Hampson, M, Driesen, N, Roth, JK, Gore, JC, Constable, RT (2010). Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance. Magnetic Resonance Imaging 28, 1051–1057.Google Scholar
Hoptman, MJ, Zuo, X-N, Butler, PD, Javitt, DC, D'Angelo, D, Mauro, CJ, Milham, MP (2010). Amplitude of low-frequency oscillations in schizophrenia: a resting state fMRI study. Schizophrenia Research 117, 13–20.CrossRefGoogle ScholarPubMed
Iwabuchi, SJ, Peng, D, Fang, Y, Jiang, K, Liddle, EB, Liddle, PF, Palaniyappan, L (2014). Alterations in effective connectivity anchored on the insula in major depressive disorder. European Neuropsychopharmacology. 24 Google Scholar
James, G, Witten, D, Hastie, T, Tibshirani, R (2013). An Introduction to Statistical Learning, vol. 103. Springer Texts in Statistics: Springer New York: New York, NY.Google Scholar
Jardri, R, Denève, S (2013). Circular inferences in schizophrenia. Brain 136, 3227–3241.Google Scholar
Javitt, DC (2009). Sensory processing in schizophrenia: neither simple nor intact. Schizophrenia Bulletin 35, 1059–1064.CrossRefGoogle ScholarPubMed
Javitt, DC (2010). Glutamatergic theories of schizophrenia. Israel Journal of Psychiatry and Related Sciences 47, 4–16.Google ScholarPubMed
Javitt, DC, Freedman, R (2015). Sensory processing dysfunction in the personal experience and neuronal machinery of schizophrenia. American Journal of Psychiatry 172, 17–31.Google Scholar
Jones, EG (1997). Cortical development and thalamic pathology in schizophrenia. Schizophrenia Bulletin 23, 483–501.Google Scholar
Kambeitz, J, Kambeitz-Ilankovic, L, Leucht, S, Wood, S, Davatzikos, C, Malchow, B, Falkai, P, Koutsouleris, N (2015). Detecting neuroimaging biomarkers for schizophrenia: a meta-analysis of multivariate pattern recognition studies. Neuropsychopharmacology 40, 1742–1751.Google Scholar
Kehrer, C, Maziashvili, N, Dugladze, T, Gloveli, T (2008). Altered excitatory-inhibitory balance in the NMDA-Hypofunction model of schizophrenia. Frontiers in Molecular Neuroscience 1.CrossRefGoogle ScholarPubMed
Kelly, AMC, Uddin, LQ, Biswal, BB, Castellanos, FX, Milham, MP (2008). Competition between functional brain networks mediates behavioral variability. NeuroImage 39, 527–537.Google Scholar
Klingner, CM, Langbein, K, Dietzek, M, Smesny, S, Witte, OW, Sauer, H, Nenadic, I (2014). Thalamocortical connectivity during resting state in schizophrenia. European Archives of Psychiatry and Clinical Neuroscience 264, 111–119.Google Scholar
Krystal, JH, D'Souza, DC, Mathalon, D, Perry, E, Belger, A, Hoffman, R (2003). NMDA receptor antagonist effects, cortical glutamatergic function, and schizophrenia: toward a paradigm shift in medication development. Psychopharmacology 169, 215–233.Google Scholar
Lin, F-H, Chu, Y-H, Hsu, Y-C, Lin, J-FL, Tsai, KW-K, Tsai, S-Y, Kuo, W-J (2015). Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals. NeuroImage 121, 69–77.Google Scholar
Liu, H, Liu, Z, Liang, M, Hao, Y, Tan, L, Kuang, F, Yi, Y, Xu, L, Jiang, T (2006). Decreased regional homogeneity in schizophrenia: a resting state functional magnetic resonance imaging study. Neuroreport 17, 19–22.CrossRefGoogle ScholarPubMed
Liu, Z, Xu, C, Xu, Y, Wang, Y, Zhao, B, Lv, Y, Cao, X, Zhang, K, Du, C (2010). Decreased regional homogeneity in insula and cerebellum: a resting-state fMRI study in patients with major depression and subjects at high risk for major depression. Psychiatry Research 182, 211–215.Google Scholar
Marsman, A, Mandl, RCW, Klomp, DWJ, Bohlken, MM, Boer, VO, Andreychenko, A, Cahn, W, Kahn, RS, Luijten, PR, Hulshoff Pol, HE (2014). GABA and glutamate in schizophrenia: a 7 T 1H-MRS study. NeuroImage. Clinical 6, 398–407.Google Scholar
Narr, KL, Toga, AW, Szeszko, P, Thompson, PM, Woods, RP, Robinson, D, Sevy, S, Wang, Y, Schrock, K, Bilder, RM (2005). Cortical thinning in cingulate and occipital cortices in first episode schizophrenia. Biological Psychiatry 58, 32–40.Google Scholar
Onitsuka, T, McCarley, RW, Kuroki, N, Dickey, CC, Kubicki, M, Demeo, SS, Frumin, M, Kikinis, R, Jolesz, FA, Shenton, ME (2007). Occipital lobe gray matter volume in male patients with chronic schizophrenia: a quantitative MRI study. Schizophrenia Research 92, 197–206.Google Scholar
Palaniyappan, L, Al-Radaideh, A, Mougin, O, Gowland, P, Liddle, PF (2013 a). Combined white matter imaging suggests myelination defects in visual processing regions in schizophrenia. Neuropsychopharmacology 38, 1808–1815.Google Scholar
Palaniyappan, L, Liddle, PF (2014). Diagnostic discontinuity in psychosis: a combined study of cortical gyrification and functional connectivity. Schizophrenia Bulletin 40, 675–684.Google Scholar
Palaniyappan, L, Simmonite, M, White, TP, Liddle, EB, Liddle, PF (2013 b). Neural primacy of the salience processing system in schizophrenia. Neuron 79, 814–828.Google Scholar
Power, JD, Barnes, KA, Snyder, AZ, Schlaggar, BL, Petersen, SE (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142–2154.Google Scholar
Schnack, HG, Kahn, RS (2016). Detecting neuroimaging biomarkers for psychiatric disorders: sample size matters. Frontiers in Psychiatry 7.Google Scholar
Schobel, SA, Chaudhury, NH, Khan, UA, Paniagua, B, Styner, MA, Asllani, I, Inbar, BP, Corcoran, CM, Lieberman, JA, Moore, H, Small, SA (2013). Imaging patients with psychosis and a mouse model establishes a spreading pattern of hippocampal dysfunction and implicates glutamate as a driver. Neuron 78, 81–93.CrossRefGoogle Scholar
Shen, H, Wang, L, Liu, Y, Hu, D (2010). Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI. NeuroImage 49, 3110–3121.Google Scholar
Taylor, SF, Tso, IF (2015). GABA abnormalities in schizophrenia: a methodological review of in vivo studies. Schizophrenia Research 167, 84–90.Google Scholar
Turner, JA, Damaraju, E, van Erp, TGM, Mathalon, DH, Ford, JM, Voyvodic, J, Mueller, BA, Belger, A, Bustillo, J, McEwen, S, Potkin, SG, FBIRN, Calhoun, VD (2013). A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia. Frontiers in Neuroscience 7.Google Scholar
Venkataraman, A, Whitford, TJ, Westin, C-F, Golland, P, Kubicki, M (2012). Whole brain resting state functional connectivity abnormalities in schizophrenia. Schizophrenia Research 139, 7–12.Google Scholar
Wang, H, Zeng, L-L, Chen, Y, Yin, H, Tan, Q, Hu, D (2015). Evidence of a dissociation pattern in default mode subnetwork functional connectivity in schizophrenia. Scientific Reports 5.Google Scholar
Woodward, ND, Karbasforoushan, H, Heckers, S (2012). Thalamocortical dysconnectivity in schizophrenia. American Journal of Psychiatry 169, 1092–1099.Google Scholar
Wynn, JK, Green, MF, Engel, S, Korb, A, Lee, J, Glahn, D, Nuechterlein, KH, Cohen, MS (2008). Increased extent of object-selective cortex in schizophrenia. Psychiatry Research – Neuroimaging 164, 97–105.Google Scholar
Xu, Y, Zhuo, C, Qin, W, Zhu, J, Yu, C (2015). Altered spontaneous brain activity in schizophrenia: a meta-analysis and a large-sample study. BioMed Research International 2015, e204628.Google Scholar
Yang, GJ, Murray, JD, Repovs, G, Cole, MW, Savic, A, Glasser, MF, Pittenger, C, Krystal, JH, Wang, X-J, Pearlson, GD, Glahn, DC, Anticevic, A (2014). Altered global brain signal in schizophrenia. Proceedings of the National Academy of Sciences USA 111, 7438–7443.Google Scholar
Yu, R, Chien, Y-L, Wang, H-LS, Liu, C-M, Liu, C-C, Hwang, T-J, Hsieh, MH, Hwu, H-G, Tseng, W-YI (2014). Frequency-specific alternations in the amplitude of low-frequency fluctuations in schizophrenia. Human Brain Mapping 35, 627–637.Google Scholar
Yu, R, Hsieh, MH, Wang, H-LS, Liu, C-M, Liu, C-C, Hwang, T-J, Chien, Y-L, Hwu, H-G, Tseng, W-YI (2013). Frequency dependent alterations in regional homogeneity of baseline brain activity in schizophrenia. PLoS ONE 8, e57516.Google Scholar
Zang, Y, Jiang, T, Lu, Y, He, Y, Tian, L (2004). Regional homogeneity approach to fMRI data analysis. NeuroImage 22, 394–400.Google Scholar
Zhuo, C, Zhu, J, Qin, W, Qu, H, Ma, X, Tian, H, Xu, Q, Yu, C (2014). Functional connectivity density alterations in schizophrenia. Frontiers in Behavioral Neuroscience 8.Google Scholar
Zou, Q-H, Zhu, C-Z, Yang, Y, Zuo, X-N, Long, X-Y, Cao, Q-J, Wang, Y-F, Zang, Y-F (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. Journal of Neuroscience Methods 172, 137–141.Google Scholar
Zuo, X-N, Di Martino, A, Kelly, C, Shehzad, ZE, Gee, DG, Klein, DF, Castellanos, FX, Biswal, BB, Milham, MP (2010). The oscillating brain: complex and reliable. NeuroImage 49, 1432–1445.Google Scholar
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