Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia

Common Data Elements for National Institute of Mental Health–Funded Translational Early Psychosis Research

The National Institutes of Health has established the PhenX Toolkit as a web-based resource containing consensus measures freely available to the research community. The National Institute of Mental Health (NIMH) has introduced the Mental Health Research Core Collection as part of the PhenX Toolkit and recently convened the PhenX Early Psychosis Working Group to generate the PhenX Early Psychosis Specialty Collection. The Working Group consisted of two complementary panels for clinical and translational research. We review the process, deliberations, and products of the translational research panel. The Early Psychosis Specialty Collection rationale for measure selection as well as additional information and protocols for obtaining each measure are available on the PhenX website (https://www.phenxtoolkit.org). The NIMH strongly encourages investigators to use instruments from the PhenX Mental Health Research Collections in NIMH-funded studies and discourages use of alternative measures to collect similar data without justification. We also discuss some of the potential advances that can be achieved by collecting common data elements across large-scale longitudinal studies of early psychosis

Investigation of Heschl's gyrus and planum temporale in patients with schizophrenia and bipolar disorder: A proton magnetic resonance spectroscopy study

Background: Superior temporal cortices include brain regions dedicated to auditory processing and several lines of evidence suggest structural and functional abnormalities in both schizophrenia and bipolar disorder within this brain region. However, possible glutamatergic dysfunction within this region has not been investigated in adult patients. Methods: Thirty patients with schizophrenia (38.67 ± 12.46. years of age), 28 euthymic patients with bipolar I disorder (35.32 ± 9.12. years of age), and 30 age-, gender- and education-matched healthy controls were enrolled. Proton magnetic resonance spectroscopy data were acquired using a 3.0. T Siemens MAGNETOM TIM Trio MR system and single voxel Point REsolved Spectroscopy Sequence (PRESS) in order to quantify brain metabolites within the left and right Heschl's gyrus and planum temporale of superior temporal cortices. Results: There were significant abnormalities in glutamate (Glu) (F(2,78) = 8.52, p < 0.0001), N-acetyl aspartate (tNAA) (F(2,81) = 5.73, p = 0.005), creatine (tCr) (F(2,83) = 5.91, p = 0.004) and inositol (Ins) (F(2,82) = 8.49, p < 0.0001) concentrations in the left superior temporal cortex. In general, metabolite levels were lower for bipolar disorder patients when compared to healthy participants. Moreover, patients with bipolar disorder exhibited significantly lower tCr and Ins concentrations when compared to schizophrenia patients. In addition, we have found significant correlations between the superior temporal cortex metabolites and clinical measures. Conclusion: As the left auditory cortices are associated with language and speech, left hemisphere specific abnormalities may have clinical significance. Our findings are suggestive of shared glutamatergic abnormalities in schizophrenia and bipolar disorder. © 2013 Elsevier B.V

Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia

Brain morphology differs markedly between individuals with schizophrenia, but the cellular and genetic basis of this heterogeneity is poorly understood. Here, we sought to determine whether cortical thickness (CTh) heterogeneity in schizophrenia relates to interregional variation in distinct neural cell types, as inferred from established gene expression data and person-specific genomic variation. This study comprised 1849 participants in total, including a discovery (140 cases and 1267 controls) and a validation cohort (335 cases and 185 controls). To characterize CTh heterogeneity, normative ranges were established for 34 cortical regions and the extent of deviation from these ranges was measured for each individual with schizophrenia. CTh deviations were explained by interregional gene expression levels of five out of seven neural cell types examined: (1) astrocytes; (2) endothelial cells; (3) oligodendrocyte progenitor cells (OPCs); (4) excitatory neurons; and (5) inhibitory neurons. Regional alignment between CTh alterations with cell type transcriptional maps distinguished broad patient subtypes, which were validated against genomic data drawn from the same individuals. In a predominantly neuronal/endothelial subtype (22% of patients), CTh deviations covaried with polygenic risk for schizophrenia (sczPRS) calculated specifically from genes marking neuronal and endothelial cells (r = −0.40, p = 0.010). Whereas, in a predominantly glia/OPC subtype (43% of patients), CTh deviations covaried with sczPRS calculated from glia and OPC-linked genes (r = −0.30, p = 0.028). This multi-scale analysis of genomic, transcriptomic, and brain phenotypic data may indicate that CTh heterogeneity in schizophrenia relates to inter-individual variation in cell-type specific functions. Decomposing heterogeneity in relation to cortical cell types enables prioritization of schizophrenia subsets for future disease modeling efforts

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks

Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping

A novel map of Broca's language region is proposed based on transmitter receptor distributions as functionally relevant molecular markers. It sheds new light on the relation between anatomy and functional segregation

Signaling pathways responsible for the rapid antidepressant-like effects of a GluN2A-preferring NMDA receptor antagonist

In a previous study we found that the preferring GluN2A receptor antagonist, NVP-AAM077, elicited rapid antidepressant-like effects in the forced swim test that was related to the release of glutamate and serotonin in the medial prefrontal cortex. In the present work we sought to examine the duration of this behavioral effect as well as the molecular readouts involved. Our results showed that NVP-AAM077 reduced the immobility in the forced swim test 30?min and 24?h after its administration. However, this effect waned 7 days later. The rapid antidepressant-like response seems to be associated with increases in the GluA1 subunit of ?-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, mammalian target of rapamycin (mTOR) signaling, glia markers such as glial fibrillary acidic protein (GFAP) and excitatory amino acid transporter 1 (EAAT1), and a rapid mobilization of intracellular stores of brain-derived neurotrophic factor (BDNF) in the medial prefrontal cortex.Acknowledgements: M.G.-S. was recipient of a contract from the Sistema Nacional de Garantía Juvenil co-funded by the European Social Fund. We also thank Novartis for the generous gift of NVP-AAM077. This work was supported by the Instituto de Salud Carlos III, Subdirección General del Evaluación y Fomento de la Investigación (FIS Grants PI13/00038 and PI16/00217) that were co-funded by the European Regional Development Fund (‘A way to build Europe’). Funding from the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III is also acknowledged

Glutamine-to-glutamate ratio in the nucleus accumbens predicts effort-based motivated performance in humans

Substantial evidence implicates the nucleus accumbens in motivated performance, but very little is known about the neurochemical underpinnings of individual differences in motivation. Here, we applied 1H magnetic resonance spectroscopy (1H-MRS) at ultra-high-field in the nucleus accumbens and inquired whether levels of glutamate (Glu), glutamine (Gln), GABA or their ratios predict interindividual differences in effort-based motivated task performance. Given the incentive value of social competition, we also examined differences in performance under self-motivated or competition settings. Our results indicate that higher accumbal Gln-to-Glu ratio predicts better overall performance and reduced effort perception. As performance is the outcome of multiple cognitive, motor and physiological processes, we applied computational modeling to estimate best-fitting individual parameters related to specific processes modeled with utility, effort and performance functions. This model-based analysis revealed that accumbal Gln-to-Glu ratio specifically relates to stamina; i.e., the capacity to maintain performance over long periods. It also indicated that competition boosts performance from task onset, particularly for low Gln-to-Glu individuals. In conclusion, our findings provide novel insights implicating accumbal Gln and Glu balance on the prediction of specific computational components of motivated performance. This approach and findings can help developing therapeutic strategies based on targeting metabolism to ameliorate deficits in effort engagement