PSY 511.001 Spr 2026
“Major challenges facing neuroimaging studies of BD and how the ENIGMA BD Working Group meets these challenges”
“Principles underlying the main distinction between affective psychosis (eg, bipolar disorder and psychotic depression) and non-affective psychosis (eg, schizophrenia and schizophreniform disorder).”
“Three hypothetical typical patients diagnosed with a combination of categorical and dimensional representations of psychopathology. Categorical diagnoses of schizophrenia (blue), bipolar disorder (green), and schizoaffective disorder (violet) are accompanied by a patient’s quantitative scores (connected by red lines) on five main dimensions of psychopathology.”
“MRI Coronal Views from Two Sets of Monozygotic Twins Discordant for Schizophrenia Showing Subtle Enlargement of the Lateral Ventricles in the Affected Twins (Panels B and D) as Compared with the Unaffected Twins (Panels A and C), Even When the Affected Twin Had Small Ventricles.”
“De-coupling of network structure and function in schizophrenia. (a) Shows an example of a brain-wide map of structural connectivity deficits in patients with schizophrenia, highlighting a relatively diffuse impairment that particularly affects fronto-posterior anatomical connectivity. In this whole-brain analysis, no increases of structural connectivity were found. Letters denote different regions (see below for key). (b) Illustrates frontal regions showing decreased and increased functional connectivity with seed regions in the dorsal (top) and ventral (bottom) caudate nucleus, respectively, in patients with schizophrenia (yellow, blue) and their unaffected, first-degree relatives (magenta, green). Thus, despite a fairly global impairment of structural connectivity (depicted in (a)), systems-specific increases in functional connectivity can be observed (b). (c,d) Brain-wide alterations of structural (c) and functional (d) connectivity in the same sample of patients with schizophrenia. Blue and green depict links where anatomical and functional connectivity, respectively, were reduced in patients; red depicts links where functional connectivity was increased in the patient group. (a) reproduced from [24•], (b) from [18•], and (c,d) from [23••] with permission. Regional abbreviations in (a) are as follow: A. Left Superior Frontal, B. Right Superior Frontal, C. Left Supplementary Motor Area, D. Left Superior Medial Frontal, E. Right Supplementary Motor Area, F. Right Superior Medial Frontal, G. Right Superior Parietal, H. Right Superior Occipital, I. Left Cuneus, J. Left Superior Occipital, K. Left Precuneus, L. Right Precuneus, M. Left Middle Temporal, N. Left Middle Occipital, O. Left Inferior Temporal, P. Left Fusiform, Q. Right Cuneus, R. Left Hippocampus, S. Left Middle Cingulum.”
“Power and variance of CGm signal in SCZ and BD. (A) Power of CGm signal in 90 SCZ patients (red) relative to 90 HCS (black) (see SI Appendix, Table S1 for demographics). (B) Mean power across all frequencies before and after GSR indicating an increase in SCZ [F(1, 178) = 7.42, P < 0.01], and attenuation by GSR [F(1, 178) = 5.37, P < 0.025]. (C) CGm variance also showed increases in SCZ [F(1, 178) = 7.25, P < 0.01] and GSR-induced reduction in SCZ [F(1, 178) = 5.25, P < 0.025]. (D–F) Independent SCZ sample (see SI Appendix, Table S2 for demographics), confirming increased CGm power [F(1, 143) = 9.2, P < 0.01] and variance [F(1, 143) = 9.25, P < 0.01] effects, but also the attenuating impact of GSR on power [F(1, 143) = 7.75, P < 0.01] and variance [F(1, 143) = 8.1, P < 0.01]. (G–I) Results for BD patients (n = 73) relative to matched HCS (see SI Appendix, Table S3 for demographics) did not reveal GSR effects observed in SCZ samples [F(1, 127) = 2.89, P = 0.092, n.s.] and no evidence for increase in CGm power or variance. All effects remained when examining all gray matter voxels (SI Appendix, Fig. S1). Error bars mark ± 1 SEM. ***P < 0.001 level of significance. n.s., not significant.”
“Relationship between SCZ symptoms and CGm BOLD signal power. We extracted average CGm power for each patient with available symptom ratings (n = 153). (A) Significant positive relationship between CGm power and symptom ratings in SCZ (r = 0.18, P < 0.03), verified using Spearman’s ρ given somewhat nonnormally distributed data (ρ = 0.2, P < 0.015). (B and C) Results held across SCZ samples, increasing confidence in the effect (i.e., joint probability of independent effects P < 0.002, marked in blue boxes). All identified relationships held when examining Gm variance (SI Appendix, Fig. S4). Notably, all effects were no longer significant after GSR, suggesting GS carries clinically meaningful information. The shaded area marks the 95% confidence interval around the best-fit line.”
“Sensitivity and specificity scores were derived using data from the classifier in each manuscript. All manuscripts were able to reliably differentiate participants with psychosis from healthy controls independent of neuroimaging type aside from [169]. The size of points is scaled according to sample size and modality of analysis is shown in various colors.”
“Summary forest plot for log diagnostic odds ratio for all imaging modalities presented at the bottom of the plot. Multimodal: classification that used at least two of the following: rs-FC, T1, and/or DTI as features. RS-FC: resting state functional connectivity. DTI: diffusion tensor imaging. T1: T1 weighted imaging. The point size of squares and polygons are a function of the precision of the estimates.”
“Colors represent different imaging modalities; estimated summary receiver operating curves are shown overlaid for each of the imaging modalities with respective confidence interval regions surrounding mean sensitivity and specificity values. No significant differences were found for classification of internal datasets . When external datasets were used for classification, rs-FC studies (red) have a significant advantage in classification relative to T1 studies (blue).”
Blocks an open ion channel (Sleigh et al., 2014; Zhang et al., 2021).
“Outcome heterogeneity in schizophrenia. Summary of 18 prospectively designed outcome studies of first admission and first diagnosis of schizophrenia with follow-up of more than 1 year with variably defined good and poor outcomes, showing balanced proportions of good and poor outcomes across studies. Studies 1 to 18 are 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93. Examples of good outcomes: symptomatic recovery with no social or intellectual deficit throughout follow-up (study 2, reference 77); full recovery over follow-up (study 12, reference 87); complete remission and never readmitted (study 16, reference 91). Examples of poor outcome definition: severe chronic social or intellectual deficit (study 2, reference 77); moderate-to-severe symptoms at time of follow-up (study 12, reference 87); chronic continuous psychotic symptoms over full follow up time (study 16, reference 91). For full description of all outcome definitions see reference 94.”
“Multiple illustrative data from bipolar and schizophrenia network for intermediate phenotyping (BSNIP) study. (a) Social function quantified with the Birchwood Social Function Scale in the BSNIP sample. Details in reference 13. Schizophrenia (SZ) and schizoaffective disorder (SAD) groups were almost identical, while bipolar disorder (BDP) showed slightly higher scores. Relatives of all groups were modestly impaired. The patterns of impairment were similar across diagnostic groups. (b) The Schizo-Bipolar scale was developed from the SCID diagnostic criteria for these psychotic diagnoses.12 There was almost continuous overlap between these diagnoses with no point of rarity over this spectrum, lacking support for distinct illness groups based on phenomenology. (c) Cognition was measured with the BACS.14 Group scores are depicted for the diagnostic subgroups, showing the greatest impairment in the SZ group and the least in the BDP group with SAD in between, separated by severity; however groups did not show distinctive qualitative cognitive alterations from each other, except for the severity. (d) In the evoked potential auditory oddball paradigm, the patient groups (SZ and BDP) resembled each other rather broadly, with minimal, distinctive differences, discussed in reference 15. (e) The antisaccade error rates were increased in all patient groups, highest in SZ and lower in BDP, without any differences across relatives.16 Again, while severity differences were present, no other distinctions existed across diagnostic groups. (f) Differences between SZ and BPP groups are present after a pair auditory stimulus, including differences in both patient groups in baseline levels, especially before S2.17 (g) Using VBM analysis to determine grey matter volume,21 a distinctive difference between SZ/SAD, on the one hand and BDP on the other, emerged; specifically, SA and SAD groups demonstrated significant and widespread grey matter volume reduction, while the BDP showed very little grey matter reduction in any area. This would represent a difference between diagnostic groups of a qualitative as well as quantitative nature. (h) FreeSurfer showed a similar outcome, with grey matter reductions widespread in all cortical regions in SZ and SAD, while no distinctive reductions in BDP. (i). Resting state fMRI analysis shows a number of distinctive cerebral networks based on ICA, that were distinctive in some or all of the diagnostic groups.18 In general, these networks were different between all probands and all healthy controls.”
