Abstract
Current evidence from neuroimaging studies investigating schizophrenia spectrum disorders (SSDs) has suggested alterations in grey and white matter [1–3], ventricular volume [4, 5], structural and functional connectivity [6, 7] and neurotransmitter levels [8]. Some of these findings have been consistent, for example, in the case of reduced cortical grey matter [1] and increased lateral ventricle volume [4]; however, others have been less clear with findings of both increased and decreased connectivity across several brain regions [6, 7]. Also of interest are regions that have consistently been associated with structural and neurochemical abnormalities, such as the striatum [8, 9] and the growing area of the role of the immune system in the pathology of SSDs [10].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- CHR:
-
Clinical high risk
- DTI:
-
Diffusion tensor imaging
- EEG:
-
Electroencephalography
- FA:
-
Fractional anisotropy
- FEP:
-
First-episode psychosis
- fMRI:
-
Functional magnetic resonance imaging
- MRI:
-
Magnetic resonance imaging
- PET:
-
Positron emission tomography
- SSDs:
-
Schizophrenia spectrum disorders
- SVM:
-
Support vector modelling
References
Ellison-Wright I, Glahn DC, Laird AR, Thelen SM, Bullmore E. The anatomy of first-episode and chronic schizophrenia: an anatomical likelihood estimation meta-analysis. Am J Psychiatry. 2008;165(8):1015–23.
Birur B, Kraguljac NV, Shelton RC, Lahti AC. Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature. NPJ Schizophr. 2017;3:15.
Canu E, Agosta F, Filippi M. A selective review of structural connectivity abnormalities of schizophrenic patients at different stages of the disease. Schizophr Res. 2015;161(1):19–28.
van Erp TG, Hibar DP, Rasmussen JM, Glahn DC, Pearlson GD, Andreassen OA, et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol Psychiatry. 2016;21(4):585.
Horga G, Bernacer J, Dusi N, Entis J, Chu K, Hazlett EA, et al. Correlations between ventricular enlargement and gray and white matter volumes of cortex, thalamus, striatum, and internal capsule in schizophrenia. Eur Arch Psychiatry Clin Neurosci. 2011;261(7):467–76.
Pettersson-Yeo W, Allen P, Benetti S, McGuire P, Mechelli A. Dysconnectivity in schizophrenia: where are we now? Neurosci Biobehav Rev. 2011;35(5):1110–24.
Fornito A, Bullmore ET. Reconciling abnormalities of brain network structure and function in schizophrenia. Curr Opin Neurobiol. 2015;30:44–50.
Howes OD, Kapur S. The dopamine hypothesis of schizophrenia: version III—the final common pathway. Schizophr Bull. 2009;35(3):549–62.
Sarpal DK, Robinson DG, Lencz T, Argyelan M, Ikuta T, Karlsgodt K, et al. Antipsychotic treatment and functional connectivity of the striatum in first-episode schizophrenia. JAMA Psychiatry. 2015;72(1):5–13.
Laskaris LE, Di Biase MA, Everall I, Chana G, Christopoulos A, Skafidas E, et al. Microglial activation and progressive brain changes in schizophrenia. Br J Pharmacol. 2016;173(4):666–80.
Yung AR, Phillips LJ, Yuen HP, Francey SM, McFarlane CA, Hallgren M, et al. Psychosis prediction: 12-month follow up of a high-risk (“prodromal”) group. Schizophr Res. 2003;60(1):21–32.
Sarpal DK, Robinson DG, Fales C, Lencz T, Argyelan M, Karlsgodt KH, et al. Relationship between duration of untreated psychosis and intrinsic corticostriatal connectivity in patients with early phase schizophrenia. Neuropsychopharmacology. 2017;42(11):2214–21.
Altamura AC, Delvecchio G, Paletta S, Di Pace C, Reggiori A, Fiorentini A, et al. Gray matter volumes may predict the clinical response to paliperidone palmitate long-acting in acute psychosis: a pilot longitudinal neuroimaging study. Psychiatry Res. 2017;261:80–4.
Cuesta MJ, Lecumberri P, Cabada T, Moreno-Izco L, Ribeiro M, López-Ilundain JM, et al. Basal ganglia and ventricle volume in first-episode psychosis. A family and clinical study. Psychiatry Res. 2017;269:90–6.
Chung Y, Haut KM, He G, van Erp TG, McEwen S, Addington J, et al. Ventricular enlargement and progressive reduction of cortical gray matter are linked in prodromal youth who develop psychosis. Schizophr Res. 2017;189:169.
Berger GE, Bartholomeusz CF, Wood SJ, Ang A, Phillips LJ, Proffitt T, et al. Ventricular volumes across stages of schizophrenia and other psychoses. Aust N Z J Psychiatry. 2017;51(10):1041–51.
Konishi J, Del Re EC, Bouix S, Blokland GAM, Mesholam-Gately R, Woodberry K, et al. Abnormal relationships between local and global brain measures in subjects at clinical high risk for psychosis: a pilot study. Brain Imaging Behav. 2017. https://doi.org/10.1007/s11682-017-9758-z.
Bousman CA, Cropley V, Klauser P, Hess JL, Pereira A, Idrizi R, et al. Neuregulin-1 (NRG1) polymorphisms linked with psychosis transition are associated with enlarged lateral ventricles and white matter disruption in schizophrenia. Psychol Med. 2018;48:801–9.
Forns-Nadal M, Bergé D, Sem F, Mané A, Igual L, Guinart D, et al. Increased nucleus accumbens volume in first-episode psychosis. Psychiatry Res. 2017;263:57–60.
Dempster K, Norman R, Théberge J, Densmore M, Schaefer B, Williamson P. Cognitive performance is associated with gray matter decline in first-episode psychosis. Psychiatry Res. 2017;264:46–51.
Rhindress K, Robinson DG, Gallego JA, Wellington R, Malhotra AK, Szeszko PR. Hippocampal subregion volume changes associated with antipsychotic treatment in first-episode psychosis. Psychol Med. 2017;47(10):1706–18.
Knöchel C, Kniep J, Cooper JD, Stäblein M, Wenzler S, Sarlon J, et al. Altered apolipoprotein C expression in association with cognition impairments and hippocampus volume in schizophrenia and bipolar disorder. Eur Arch Psychiatry Clin Neurosci. 2017;267(3):199–212.
Landin-Romero R, Canales-Rodríguez EJ, Kumfor F, Moreno-Alcázar A, Madre M, Maristany T, et al. Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder. Aust N Z J Psychiatry. 2017;51(1):42–54.
Buchy L, Makowski C, Malla A, Joober R, Lepage M. Longitudinal trajectory of clinical insight and covariation with cortical thickness in first-episode psychosis. J Psychiatr Res. 2017;86:46–54.
Picchioni MM, Rijsdijk F, Toulopoulou T, Chaddock C, Cole JH, Ettinger U, et al. Familial and environmental influences on brain volumes in twins with schizophrenia. J Psychiatry Neurosci. 2017;42(2):122–30.
Mørch-Johnsen L, Nesvåg R, Jørgensen KN, Lange EH, Hartberg CB, Haukvik UK, et al. Auditory cortex characteristics in schizophrenia: associations with auditory hallucinations. Schizophr Bull. 2017;43(1):75–83.
Kuang C, Buchy L, Barbato M, Makowski C, MacMaster FP, Bray S, et al. A pilot study of cognitive insight and structural covariance in first-episode psychosis. Schizophr Res. 2017;179:91–6.
Castro-de-Araujo LFS, Kanaan RAA. First episode psychosis moderates the effect of gray matter volume on cognition. Psychiatry Res. 2017;266:108–13.
Squarcina L, Castellani U, Bellani M, Perlini C, Lasalvia A, Dusi N, et al. Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques. NeuroImage. 2017;145(Pt B):238–45.
Nieuwenhuis M, Schnack HG, van Haren NE, Lappin J, Morgan C, Reinders AA, et al. Multi-center MRI prediction models: predicting sex and illness course in first episode psychosis patients. NeuroImage. 2017;145(Pt B):246–53.
Cropley VL, Klauser P, Lenroot RK, Bruggemann J, Sundram S, Bousman C, et al. Accelerated gray and white matter deterioration with age in schizophrenia. Am J Psychiatry. 2017;174(3):286–95.
Koutsouleris N, Wobrock T, Guse B, Langguth B, Landgrebe M, Eichhammer P, et al. Predicting response to repetitive transcranial magnetic stimulation in patients with schizophrenia using structural magnetic resonance imaging: a multisite machine learning analysis. Schizophr Bull. 2017. https://doi.org/10.1093/schbul/sbx114.
Zhou Y, Liu J, Driesen N, Womer F, Chen K, Wang Y, et al. White matter integrity in genetic high-risk individuals and first-episode schizophrenia patients: similarities and disassociations. Biomed Res Int. 2017;2017:3107845.
Mallas E, Carletti F, Chaddock CA, Shergill S, Woolley J, Picchioni MM, et al. The impact of CACNA1C gene, and its epistasis with ZNF804A, on white matter microstructure in health, schizophrenia and bipolar disorder(1). Genes Brain Behav. 2017;16(4):479–88.
Serpa MH, Doshi J, Erus G, Chaim-Avancini TM, Cavallet M, van de Bilt MT, et al. State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis. Psychol Med. 2017;47(15):2613–27.
Klauser P, Baker ST, Cropley VL, Bousman C, Fornito A, Cocchi L, et al. White matter disruptions in schizophrenia are spatially widespread and topologically converge on brain network hubs. Schizophr Bull. 2017;43(2):425–35.
Rae CL, Davies G, Garfinkel SN, Gabel MC, Dowell NG, Cercignani M, et al. Deficits in neurite density underlie white matter structure abnormalities in first-episode psychosis. Biol Psychiatry. 2017;82(10):716–25.
Ren HY, Wang Q, Lei W, Zhang CC, Li YF, Li XJ, et al. The common variants implicated in microstructural abnormality of first episode and drug-naïve patients with schizophrenia. Sci Rep. 2017;7(1):11750.
Crossley NA, Marques TR, Taylor H, Chaddock C, Dell’Acqua F, Reinders AA, et al. Connectomic correlates of response to treatment in first-episode psychosis. Brain. 2017;140(2):487–96.
Schmidt A, Crossley NA, Harrisberger F, Smieskova R, Lenz C, Riecher-Rössler A, et al. Structural network disorganization in subjects at clinical high risk for psychosis. Schizophr Bull. 2017;43(3):583–91.
Li P, Jing RX, Zhao RJ, Ding ZB, Shi L, Sun HQ, et al. Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study. NPJ Schizophr. 2017;3(1):21.
Peters H, Riedl V, Manoliu A, Scherr M, Schwerthöffer D, Zimmer C, et al. Changes in extra-striatal functional connectivity in patients with schizophrenia in a psychotic episode. Br J Psychiatry. 2017;210(1):75–82.
Wu S, Wang H, Chen C, Zou J, Huang H, Li P, et al. Task performance modulates functional connectivity involving the dorsolateral prefrontal cortex in patients with schizophrenia. Front Psychol. 2017;8:56.
Xu Y, Qin W, Zhuo C, Xu L, Zhu J, Liu X, et al. Selective functional disconnection of the orbitofrontal subregions in schizophrenia. Psychol Med. 2017;47(9):1637–46.
Anderson EJ, Tibber MS, Schwarzkopf DS, Shergill SS, Fernandez-Egea E, Rees G, et al. Visual population receptive fields in people with schizophrenia have reduced inhibitory surrounds. J Neurosci. 2017;37(6):1546–56.
Gong Q, Hu X, Pettersson-Yeo W, Xu X, Lui S, Crossley N, et al. Network-level dysconnectivity in drug-naïve first-episode psychosis: dissociating transdiagnostic and diagnosis-specific alterations. Neuropsychopharmacology. 2017;42(4):933–40.
Schmack K, Rothkirch M, Priller J, Sterzer P. Enhanced predictive signalling in schizophrenia. Hum Brain Mapp. 2017;38(4):1767–79.
Braeutigam S, Dima D, Frangou S, James A. Dissociable auditory mismatch response and connectivity patterns in adolescents with schizophrenia and adolescents with bipolar disorder with psychosis: a magnetoencephalography study. Schizophr Res. 2018;193:313.
Mason L, Peters E, Williams SC, Kumari V. Brain connectivity changes occurring following cognitive behavioural therapy for psychosis predict long-term recovery. Transl Psychiatry. 2017;7(8):e1209.
Koike S, Satomura Y, Kawasaki S, Nishimura Y, Kinoshita A, Sakurada H, et al. Application of functional near infrared spectroscopy as supplementary examination for diagnosis of clinical stages of psychosis spectrum. Psychiatry Clin Neurosci. 2017;71:794.
Rikandi E, Pamilo S, Mäntylä T, Suvisaari J, Kieseppä T, Hari R, et al. Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland. Psychol Med. 2017;47(3):495–506.
Spilka MJ, Goghari VM. Similar patterns of brain activation abnormalities during emotional and non-emotional judgments of faces in a schizophrenia family study. Neuropsychologia. 2017;96:164–74.
Falkenberg I, Valli I, Raffin M, Broome MR, Fusar-Poli P, Matthiasson P, et al. Pattern of activation during delayed matching to sample task predicts functional outcome in people at ultra high risk for psychosis. Schizophr Res. 2017;181:86–93.
Martinelli C, Rigoli F, Shergill SS. Aberrant force processing in schizophrenia. Schizophr Bull. 2017;43(2):417–24.
Hager B, Yang AC, Brady R, Meda S, Clementz B, Pearlson GD, et al. Neural complexity as a potential translational biomarker for psychosis. J Affect Disord. 2017;216:89–99.
Fornito A, Yücel M, Patti J, Wood SJ, Pantelis C. Mapping grey matter reductions in schizophrenia: an anatomical likelihood estimation analysis of voxel-based morphometry studies. Schizophr Res. 2009;108(1-3):104–13.
Hu ML, Zong XF, Mann JJ, Zheng JJ, Liao YH, Li ZC, et al. A review of the functional and anatomical default mode network in schizophrenia. Neurosci Bull. 2017;33(1):73–84.
Kindler J, Schultze-Lutter F, Hauf M, Dierks T, Federspiel A, Walther S, et al. Increased striatal and reduced prefrontal cerebral blood flow in clinical high risk for psychosis. Schizophr Bull. 2018;44:182.
Di Biase MA, Zalesky A, O’keefe G, Laskaris L, Baune BT, Weickert CS, et al. PET imaging of putative microglial activation in individuals at ultra-high risk for psychosis, recently diagnosed and chronically ill with schizophrenia. Transl Psychiatry. 2017;7(8):e1225.
Selvaraj S, Bloomfield PS, Cao B, Veronese M, Turkheimer F, Howes OD. Brain TSPO imaging and gray matter volume in schizophrenia patients and in people at ultra high risk of psychosis: an [(11)C]PBR28 study. Schizophr Res. 2018;195:206.
Hafizi S, Da Silva T, Gerritsen C, Kiang M, Bagby RM, Prce I, et al. Imaging microglial activation in individuals at clinical high risk for psychosis: an in vivo PET study with [(18)F]FEPPA. Neuropsychopharmacology. 2017;42:2474.
Artiges E, Leroy C, Dubol M, Prat M, Pepin A, Mabondo A, et al. Striatal and extrastriatal dopamine transporter availability in schizophrenia and its clinical correlates: a voxel-based and high-resolution PET study. Schizophr Bull. 2017;43(5):1134–42.
Solé-Padullés C, Castro-Fornieles J, de la Serna E, Sánchez-Gistau V, Romero S, Puig O, et al. Intrinsic functional connectivity of fronto-temporal networks in adolescents with early psychosis. Eur Child Adolesc Psychiatry. 2017;26(6):669–79.
Kim M, Cho KI, Yoon YB, Lee TY, Kwon JS. Aberrant temporal behavior of mismatch negativity generators in schizophrenia patients and subjects at clinical high risk for psychosis. Clin Neurophysiol. 2017;128(2):331–9.
Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo-Facorro B, et al. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet. 2018;177:21.
Amann BL, Canales-Rodríguez EJ, Madre M, Radua J, Monte G, Alonso-Lana S, et al. Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder. Acta Psychiatr Scand. 2016;133(1):23–33.
Dazzan P, Soulsby B, Mechelli A, Wood SJ, Velakoulis D, Phillips LJ, et al. Volumetric abnormalities predating the onset of schizophrenia and affective psychoses: an MRI study in subjects at ultrahigh risk of psychosis. Schizophr Bull. 2012;38(5):1083–91.
Cannon TD, Chung Y, He G, Sun D, Jacobson A, van Erp TG, et al. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry. 2015;77(2):147–57.
Steen RG, Mull C, McClure R, Hamer RM, Lieberman JA. Brain volume in first-episode schizophrenia: systematic review and meta-analysis of magnetic resonance imaging studies. Br J Psychiatry. 2006;188:510–8.
Chan RC, Di X, McAlonan GM, Gong QY. Brain anatomical abnormalities in high-risk individuals, first-episode, and chronic schizophrenia: an activation likelihood estimation meta-analysis of illness progression. Schizophr Bull. 2011;37(1):177–88.
Olabi B, Ellison-Wright I, McIntosh AM, Wood SJ, Bullmore E, Lawrie SM. Are there progressive brain changes in schizophrenia? A meta-analysis of structural magnetic resonance imaging studies. Biol Psychiatry. 2011;70(1):88–96.
Zipursky RB, Reilly TJ, Murray RM. The myth of schizophrenia as a progressive brain disease. Schizophr Bull. 2013;39(6):1363–72.
Fusar-Poli P, Smieskova R, Kempton MJ, Ho BC, Andreasen NC, Borgwardt S. Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies. Neurosci Biobehav Rev. 2013;37(8):1680–91.
Vita A, De Peri L, Deste G, Barlati S, Sacchetti E. The effect of antipsychotic treatment on cortical gray matter changes in schizophrenia: does the class matter? A meta-analysis and meta-regression of longitudinal magnetic resonance imaging studies. Biol Psychiatry. 2015;78(6):403–12.
Lener MS, Wong E, Tang CY, Byne W, Goldstein KE, Blair NJ, et al. White matter abnormalities in schizophrenia and schizotypal personality disorder. Schizophr Bull. 2015;41(1):300–10.
Lynall ME, Bassett DS, Kerwin R, McKenna PJ, Kitzbichler M, Muller U, et al. Functional connectivity and brain networks in schizophrenia. J Neurosci. 2010;30(28):9477–87.
van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci. 2011;31(44):15775–86.
Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A. 2009;106(4):1279–84.
Fornito A, Harrison BJ, Goodby E, Dean A, Ooi C, Nathan PJ, et al. Functional dysconnectivity of corticostriatal circuitry as a risk phenotype for psychosis. JAMA Psychiatry. 2013;70(11):1143–51.
Dandash O, Fornito A, Lee J, Keefe RS, Chee MW, Adcock RA, et al. Altered striatal functional connectivity in subjects with an at-risk mental state for psychosis. Schizophr Bull. 2014;40(4):904–13.
Anticevic A, Cole MW, Repovs G, Murray JD, Brumbaugh MS, Winkler AM, et al. Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness. Cereb Cortex. 2014;24(12):3116–30.
Hoffman RE, Fernandez T, Pittman B, Hampson M. Elevated functional connectivity along a corticostriatal loop and the mechanism of auditory/verbal hallucinations in patients with schizophrenia. Biol Psychiatry. 2011;69(5):407–14.
Millan MJ, Andrieux A, Bartzokis G, Cadenhead K, Dazzan P, Fusar-Poli P, et al. Altering the course of schizophrenia: progress and perspectives. Nat Rev Drug Discov. 2016;15(7):485–515.
Fusar-Poli P, Bonoldi I, Yung AR, Borgwardt S, Kempton MJ, Valmaggia L, et al. Predicting psychosis: meta-analysis of transition outcomes in individuals at high clinical risk. Arch Gen Psychiatry. 2012;69(3):220–9.
Koutsouleris N, Meisenzahl EM, Davatzikos C, Bottlender R, Frodl T, Scheuerecker J, et al. Use of neuroanatomical pattern classification to identify subjects in at-risk mental states of psychosis and predict disease transition. Arch Gen Psychiatry. 2009;66(7):700–12.
Koutsouleris N, Borgwardt S, Meisenzahl EM, Bottlender R, Möller HJ, Riecher-Rössler A. Disease prediction in the at-risk mental state for psychosis using neuroanatomical biomarkers: results from the FePsy study. Schizophr Bull. 2012;38(6):1234–46.
Koutsouleris N, Riecher-Rössler A, Meisenzahl EM, Smieskova R, Studerus E, Kambeitz-Ilankovic L, et al. Detecting the psychosis prodrome across high-risk populations using neuroanatomical biomarkers. Schizophr Bull. 2015;41(2):471–82.
McGuire P, Sato JR, Mechelli A, Jackowski A, Bressan RA, Zugman A. Can neuroimaging be used to predict the onset of psychosis? Lancet Psychiatry. 2015;2(12):1117–22.
Gifford G, Crossley N, Fusar-Poli P, Schnack HG, Kahn RS, Koutsouleris N, et al. Using neuroimaging to help predict the onset of psychosis. NeuroImage. 2017;145(Pt B):209–17.
Kapur S, Seeman P. Antipsychotic agents differ in how fast they come off the dopamine D2 receptors. Implications for atypical antipsychotic action. J Psychiatry Neurosci. 2000;25(2):161–6.
Tamminga CA. Treatment mechanisms: traditional and new antipsychotic drugs. Dialogues Clin Neurosci. 2000;2(3):281–6.
Navari S, Dazzan P. Do antipsychotic drugs affect brain structure? A systematic and critical review of MRI findings. Psychol Med. 2009;39(11):1763–77.
Abbott CC, Jaramillo A, Wilcox CE, Hamilton DA. Antipsychotic drug effects in schizophrenia: a review of longitudinal FMRI investigations and neural interpretations. Curr Med Chem. 2013;20(3):428–37.
Demjaha A, Murray RM, McGuire PK, Kapur S, Howes OD. Dopamine synthesis capacity in patients with treatment-resistant schizophrenia. Am J Psychiatry. 2012;169(11):1203–10.
Demjaha A, Egerton A, Murray RM, Kapur S, Howes OD, Stone JM, et al. Antipsychotic treatment resistance in schizophrenia associated with elevated glutamate levels but normal dopamine function. Biol Psychiatry. 2014;75(5):e11–3.
Kumari V, Tercer T. Cognitive behaviour therapy for psychosis: insights from neuroimaging. J Neuroimaging Psychiatry Neurol. 2017;2:11–9.
Wykes T, Huddy V, Cellard C, McGurk SR, Czobor P. A meta-analysis of cognitive remediation for schizophrenia: methodology and effect sizes. Am J Psychiatry. 2011;168(5):472–85.
Stafford MR, Jackson H, Mayo-Wilson E, Morrison AP, Kendall T. Early interventions to prevent psychosis: systematic review and meta-analysis. BMJ. 2013;346:f185.
van der Gaag M, Smit F, Bechdolf A, French P, Linszen DH, Yung AR, et al. Preventing a first episode of psychosis: meta-analysis of randomized controlled prevention trials of 12 month and longer-term follow-ups. Schizophr Res. 2013;149(1-3):56–62.
Sommer IE, van Westrhenen R, Begemann MJ, de Witte LD, Leucht S, Kahn RS. Efficacy of anti-inflammatory agents to improve symptoms in patients with schizophrenia: an update. Schizophr Bull. 2014;40(1):181–91.
Zhu F, Zhang L, Ding YQ, Zhao J, Zheng Y. Neonatal intrahippocampal injection of lipopolysaccharide induces deficits in social behavior and prepulse inhibition and microglial activation in rats: implication for a new schizophrenia animal model. Brain Behav Immun. 2014;38:166–74.
Müller N. The role of anti-inflammatory treatment in psychiatric disorders. Psychiatr Danub. 2013;25(3):292–8.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix: Neuroimaging Studies Published in 2017 Investigated Schizophrenia Spectrum Disorders, First-Episode Psychosis or Clinical High-Risk Populations
Appendix: Neuroimaging Studies Published in 2017 Investigated Schizophrenia Spectrum Disorders, First-Episode Psychosis or Clinical High-Risk Populations
Authors | Neuroimaging method | Participants | Diagnostic manual | Outcome |
---|---|---|---|---|
Berger [16] | MRI | 89 SCZ, 162 FEP, 135 CHR, 87 HC | DSM-III | A linear trend for increasing ventricular volume across progression of illness, reaching significance only for SCZ patients |
Bousman [18] | MRI + DTI | 290 SCZ, 175 HC | DSM-IV | SCZ patients with risk single-nucleotide polymorphisms had larger lateral ventricle volumes (left and right) compared to schizophrenics without risk genes |
Buchy [24] | MRI | 128 FEP | DSM-IV | Clinical insight was not associated with cortical thickness at baseline, but worsening of clinical insight over time was linked with thinning in the dorsal postcentral and precentral gyri |
Castro-de-Araujo [28] | MRI | 100 FEP, 94 HC | DSM-IV | The presence of FEP altered the relationship between grey matter volume and cognition |
Chung [15] | MRI | 267 CHR, 132 HC | DSM-IV | Ventricular enlargement over time was linked to grey matter reduction in the prefrontal cortex, superior temporal gyrus and parietal cortices in people at CHR |
Cropley [31] | MRI + DTI | 326 SCZ and schizoaffective, 197 HC | Significant loss of grey matter progressively across illness, reduced FA after age of 35 | |
Crossley [39] | DTI | 76 FEP 74 HC | At baseline FEPs who subsequently responded to antipsychotic medication showed better efficiency in structural connectomes, and these group differences were not apparent after 12 weeks of treatment | |
Cuesta [14] | MRI | 50 FEP, 24 HC, 21 unaffected relatives | DSM-IV | Patients had enlarged left lateral and right lateral ventricles compared with family and larger third ventricle than controls |
Dempster [20] | MRI | 16 FEP | DSM-IV | Reductions in grey matter in the nucleus accumbens, right globus pallidus, left inferior parietal lobe, Brodmann’s areas 40 and 7 and left superior parietal lobule were associated with poorer cognitive performance over time |
Forns-Nadal [19] | MRI | 31 FEP + 27 HC | DSM-IV | FEPs had increased nucleus accumbens volumes, and this was not correlated with negative symptoms of psychosis |
Klauser [36] | DTI | 326 SSD, 197 HC | DSM-IV | Patients showed reduced FA and increased MD in all lobes, and differences were pronounced in the thalamus, cingulum, corpus callosum and areas involved in the rich club organisation |
Konishi [17] | MRI | 19 CHR, 20 HC | DSM-IV | Enlarged temporal horn area of the lateral ventricle but reductions in amygdala and whole-brain volume leading to an abnormal ratio of temporal horn to total brain volume in CHR patients |
Koutsouleris [32] | MRI | 92 SCZ | ICD-10 | Individual responses to transcranial magnetic stimulation were predicted with 85% accuracy using measures of grey matter density |
Knöchel [22] | MRI | 29 SCZ, 25 BPD, 93 HC | DSM-IV | Increased changes in apolipoprotein levels were associated with cognitive impairments and reduced volume in the right hippocampus of SCZ patients |
Kuang [27] | MRI | 15 FEP, 15 HC (historical) | Cortical thickness in ventrolateral PFC did not covary with other brain areas in FEPs | |
Landin-Romero [23] | MRI | 45 schizoaffective, 45 HC | DSM-IV | People with schizoaffective disorder showed grey and white matter reductions in the frontal cortices, left insula, bilateral temporal lobes and posterior cingulate cortex and precuneus and fusiform cortex |
Li [41] | MRI | 34 SCZ, 34 HC | Better connectivity in the default mode network, the temporal lobe, the language network, the corticostriatal network, the frontoparietal network and the cerebellum was predictive of increased response to electroconvulsive therapy in patients | |
Mallas [34] | DTI | 63 SCZ, 124 HC | DSM-IV | People with CACNA1C gene and SCZ had reduced FA compared to those without the gene, and FA was reduced in SCZ in general compared with controls |
Mørch-Johnsen [26] | MRI | 194 SSD | DSM-IV | Patients with auditory hallucinations had thinner cortex in left Heschl’s gyrus; no differences in planum temporale or superior temporal gyrus compared with those without hallucinations |
Nieuwenhuis [30] | MRI | 389 FEP | DSM-IV | Gender but not diagnosis or prognosis of psychotic disorders could be accurately predicted |
Picchioni [53] | MRI | 70 SCZ, 16 MZ discordant twins, 6 DZ discordant twins, 76 HC | DSM-IV | Whole-brain, grey matter and white matter volumes were reduced in SCZ, and there was a correlation between these volume reductions and schizophrenia liability in discordant co-twins |
Rae [37] | DWI + MRI | 35 FEP, 19 HC | FEP patients had reduced FA in multiple commissural, corticospinal and association tracts; this was associated with abnormalities in fibre number, density and myelination | |
Ren [38] | DTI | 100 FEP, 140 HC | DSM-IV | Reduced FA in left anterior cingulate cortex, right anterior cingulate cortex, left inferior parietal cortex, left posterior cingulate cortex and right posterior cingulate cortex which were associated with eight gene variations and one cell cycle pathway variation |
Rhindress [21] | MRI | 29 FEP, 29 HC | DSM-IV | Following antipsychotic treatment, patients showed reductions in dentate gyrus/CA4 volume and increases in subiculum, and there were no significant changes in hippocampal volume in healthy controls |
Schmidt [40] | DTI | 24 CHR, 24 HC | ICD-10 | Rich club organisation was impaired in people at risk of psychosis, and greater impairments were correlated with increased severity of negative symptoms |
Serpa [35] | MRI + DTI | 25 FEP, 1 HC | DSM-IV | Reduced FA in white matter tracts in the fronto-limbic and the associative, projective and commissural fasciculi in FEP; FA increased upon symptom remission following antipsychotic medication |
Squarcina [29] | MRI | 127 FEP, 127 HC | ICD-10 | Fronto-temporal cortical thickness can be used as a potential marker to classify patients with FEP |
Zhou [33] | DTI | 48 FEP, 37 GHR, 67 HC | DSM-IV | Decreased FA in corpus callosum, anterior cingulum and uncinate fasciculus for both SCZ and GHR groups, decreased FA in fornix and superior longitudinal fasciculus in SCZ |
Anderson [45] | fMRI | 18 SCZ, 2 HC | DSM-IV | Patients showed a reduction in the population receptive field of neurons and a reduction in the inhibitory surround in V1, V2 and V4 |
Braeutigam [48] | MEG | 15 SCZ, 16 BPD, 14 HC (all adolescents) | DSM-IV | Adolescents with schizophrenia (FEP) displayed reduced amplitude of MEG waves following mismatch negativity task, and connections appeared to be dominated by the right hemisphere |
Falkenberg [53] | fMRI | 34 CHR, 20 HC | Altered frontal and cuneus/posterior cingulate activation in UHR; amongst those with poor outcome, there was altered activation of frontal temporal and striatal regions | |
Gong [46] | fMRI | 50 FEP, 122 HC | DSM-IV | FEPs showed decreased intranetwork connectivity and increased internetwork connectivity in drug-naive FEP compared with HC, and aberrant internetwork connectivity was particularly associated with psychotic symptoms and not MDD or PTSD |
Hager [55] | fMRI | 107 SCZ, 156 HC, 125 BPD, 98 schizoaffective, 230 healthy relatives | DSM-IV | People with SCZ showed decreased neural complexity towards a regular signal in hypothalamus, and SCZ and schizoaffective patients showed increased complexity in PFC |
Koike [50] | fNIRS | 47 CHR, 30 FEP, 34 SCZ, 33 HC | DSM-IV | The sum of signal changes during the task and the timing of the blood response relative to the task had an 80–90% accuracy in classifying people as non-patient, UHR, FEP or SCZ |
Martinelli [54] | fMRI | 21 SCZ, 26 HCs | DSM-IV | Patients showed greater brain activation when force was self-generated as opposed to externally produced; this was the opposite of HCs |
Mason [49] | fMRI | 22 SCZ intervention, 16 SCZ controls | Following CBT for psychosis, long-term psychotic symptoms were predicted by alterations in connectivity in the prefrontal cortex; alterations in connectivity between the amygdala and parietal lobe were predictive of long-term affective symptoms | |
Rikandi [51] | fMRI | 46 FEP 32 HC | DSM-IV | Activity in the precuneus during a fantasy film could be used to classify patients as FEP or healthy controls with 79.5% accuracy |
Peters [42] | fMRI | 21 SCZ, 42 HC | DSM-IV | Decreased in functional connectivity between the putamen and right interior insula, dorsomedial and dorsolateral PFC and ventral striatum and left anterior insula in people with SCZ during a psychotic episode compared with healthy controls |
Schmack [47] | fMRI | 21 SCZ, 28 HC | ICD-10 | Belief-related connectivity between the orbitofrontal cortex and visual cortex was higher in patients compared with HC |
Spilka [52] | fMRI | 28 SCZ, 27 GHR, 27 HC | DSM-IV | Patients with SCZ showed impairments in both age and emotion discrimination during a task and showed reduced activation of the medial prefrontal cortex |
Xu [44] | fMRI | 98 SCZ, 102 HC | DSM-IV | Patients showed decreased functional connectivity between the orbitofrontal cortex subregions |
Wu [43] | fMRI | 45 SCZ, 45 HC | DSM-IV | Patients with impaired working memory capacity and decreased brain activation/deactivation showed decreased functional activation of the dorsolateral prefrontal cortex with the angular cortex compared with controls |
Di Biase [59] | PET | 10 CHR, 18 FEP, 15 SCZ, 27 HC | DSM-IV | No evidence of altered microglial activation in UHR, FE or SCZ |
Artiges [62] | PET + MRI | 21 SCZ, 30 HC | DSM-IV | Higher dopamine transporter availability in the midbrain, in striatal and limbic regions and in amygdala/hippocampus positively correlated with positive symptoms |
Hafizi [61] | PET + MRI | 24 CHR, 23 HC | DSM-IV | No significant activation of microglia in dorsolateral prefrontal cortex or hippocampus in CHR compared with HC |
Kim [64] | EEG + MRI | 29 SCZ, 40 CHR, 47 HC | DSM-IV | Significant deficits in mismatch negativity and current source density strength found in temporal and frontal cortices in people with SCZ and CHR |
Kindler [58] | MRI + fMRI | 32 SCZ, 31 HC, 29 CHR, 12 FEP, 31 HC | ICD-10 | Increased regional blood flow in the striatum and decreased regional blood flow in the prefrontal cortex in CHR, FEP and SCZ compared with controls |
Ranlund [65] | MRI + EEG | 703 SCZ, 68 schizophreniform, 60 schizoaffective, 2794 HC | DSM-IV | Polygenic risk scores predicted poorer performance on a cognitive block task for people with SCZ, relatives and controls; SCZ patients had higher polygenic risk scores |
Selvaraj [60] | PET + MRI | 14 SCZ, 14 CHR, 22 HC | DSM-IV | Microglia activation was associated with cortical grey matter loss in SCZ, and there was a trend for this in UHR |
Solé-Padullés [63] | fMRI + DTI | 44 CHR, 34 FEP, 35 HC (all adolescents) | DSM-IV | Reduced intrinsic functional connectivity in the right middle/inferior gyrus in patients compared with controls; values for CHR were intermediate between FEP and controls |
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Scutt, E., Borgwardt, S., Fusar-Poli, P. (2019). Research Perspectives for Neuroimaging of Schizophrenia Spectrum Disorders. In: Galderisi, S., DeLisi, L., Borgwardt, S. (eds) Neuroimaging of Schizophrenia and Other Primary Psychotic Disorders . Springer, Cham. https://doi.org/10.1007/978-3-319-97307-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-97307-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97306-7
Online ISBN: 978-3-319-97307-4
eBook Packages: MedicineMedicine (R0)