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Functional MRI methods and findings in schizophrenia

Functional MRI imaging methods have allowed researchers to combine neurocognitive testing with structural neuroanatomical measures, consider cognitive and affective paradigms, and create computer-aided diagnosis techniques and algorithms.[1][2] Functional MRI has several benefits, such as its non-invasive quality, relatively high spatial resolution, and decent temporal resolution. One particular method used in recent research is resting-state functional magnetic resonance imaging, rs-fMRI. fMRI imaging has been applied to numerous behavioral studies for schizophrenia, the findings of which have hinted toward potential brain regions that govern key characteristics in cognition and affect.

In a 'reformulation' of the binary-risk vulnerability model, researchers have suggested a multiple-hit hypothesis that utilizes several risk factors — some bestowing a greater probability than others — to identify at-risk individuals, often genetically predisposed to schizophrenia.[3] The process of defining clinical criteria of schizophrenia for early diagnosis has posed a great challenge for scientists.[4]

Methodology

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A rapid increase of studies in schizophrenia has covered topics such as abnormal activity in "motor tasks, working memory attention, word fluency, emotion processing, and decision making."[5] In contrast to the abundance of research centered on positive symptoms of the disorder, fMRI research for schizophrenia primarily analyzes the 'failures' of the neural system and consequent behavioral deficits.[5] To confirm that a task activates identical regions in schizophrenia patients vs. controls, the given task typically begins easily so that both patients and healthy comparison subjects perform close to 100% accuracy; the task is then increased in difficulty to distinguish activation between two groups with varying abilities of individuals.[5]

The 'basic symptoms' approach

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The 'basic symptoms' approach for schizophrenia, which emerged from "retrospective descriptions of the prodromal phase," represents a framework for a large portion of fMRI research, which evaluates changes in cognition and sensory perception that may affect higher-level information processes.[6][7] Some researchers oppose the tendency of researchers to attribute schizophrenia to higher-order processes like working memory, attention, and executive processing, instead choosing to inspect impairments in basic sensory and perceptual functions.[7] Deficits in basic sensory functions influence higher-order processes such as auditory emotion recognition, perceptual closure, object recognition, etc.[7] In the visual system, for example, rudimentary deficits in the function of the magnocellular system result in impairments in higher-order processes like perceptual closure, object recognition, and reading.[7] On the other hand, fMRI data has also suggested the opposite. In one study, researchers found significantly differing activity between healthy and schizophrenic patients in the left dorsal parietal cortex and left ventrolateral prefrontal cortex; as these regions are essential components of a frontal-parietal executive system, hypo-activity in these regions for schizophrenia patients during working memory tasks were theorized to be associated with deficits in executive functioning.[8]

Resting-state fMRI

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The 'disconnectivity hypothesis' is a key theory describing the failure of mechanisms underlying schizophrenia, specifically the failure to integrate information properly.[9] Functional connectivity, which fMRI evaluates, is the activity coordination between brain regions. It is measured as "temporal correlations of low-frequency oscillations in the BOLD signal between anatomically distinct brain areas" and can reveal resting state networks.[10] The cause for the correlations in fMRI measurements is theorized to be "correlated firing rates of interconnected neurons."[11] Resting-state functional magnetic resonance imaging (rs-fMRI) has become a powerful tool to examine networks' functional connectivity throughout the brain, such as the default mode network (DMN).[12]

Abnormal brain connectivity has long been theorized as a fundamental cause of psychosis in schizophrenia.[13] rs-fMRI can help evaluate regional interactions at rest and whether there are altered, reduced, or hyperactive connections in psychiatric disorders like schizophrenia. During resting-state fMRI experiments, participants are instructed to relax and stay awake but not think of anything. It is important to note that resting-state networks can change between eyes open and eyes closed conditions.[14] Researchers then measure spontaneous brain activation.[10] There are several advantages to studying the resting state of brain networks — the primary reason is that spontaneous neural activity accounts for most of the brain's activity in contrast to task-based neural activity.[14] Additionally, rs-fMRI eliminates confounding effects such as differing performances between healthy subjects and patients in tasks; rs-fMRI also requires less movement than task-based fMRI studies.[14] Seed-based analysis/ROI approaches to analyzing functional connectivity are common in rs-fMRI for schizophrenia. A seed (region of interest) is first selected, and BOLD time series are then extracted from the seed and all other voxels. After preprocessing, the temporal correlation between the seed and other brain voxels is determined, and the software produces a functional connectivity map.[10] Seed-based comparisons in rs-fMRI have revealed functional disconnectivity in schizophrenia patients in numerous studies, using different ROIs for their seeds — in general, schizophrenia patients show reduced connectivity.[10] Recent studies using resting-state fMRI (rs-fMRI) have identified significant disruptions in functional connectivity across multiple brain networks in schizophrenia, including the default mode, frontotemporal, and cerebellar networks. These findings provide additional support for the dysconnectivity hypothesis, which suggests that impaired coordination between brain regions contributes to the cognitive and behavioral symptoms of schizophrenia.[15][16] This information is compatible with experiment findings suggesting reduced activation in the amygdala in schizophrenia patients during sadness mood induction, for example.[17]

References

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  1. ^ Morgan, Kevin D.; Dazzan, Paola; Morgan, Craig; Lappin, Julia; Hutchinson, Gerard; Suckling, John; Fearon, Paul; Jones, Peter B.; Leff, Julian; Murray, Robin M.; David, Anthony S. (August 2010). "Insight, grey matter and cognitive function in first-onset psychosis". The British Journal of Psychiatry. 197 (2): 141–148. doi:10.1192/bjp.bp.109.070888. ISSN 0007-1250. PMID 20679268. S2CID 17223664.
  2. ^ Algumaei, Ali H.; Algunaid, Rami F.; Rushdi, Muhammad A.; Yassine, Inas A. (2022-05-24). "Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data". PLOS ONE. 17 (5): e0265300. Bibcode:2022PLoSO..1765300A. doi:10.1371/journal.pone.0265300. ISSN 1932-6203. PMC 9129055. PMID 35609033.
  3. ^ Davis, Justin; Eyre, Harris; Jacka, Felice N; Dodd, Seetal; Dean, Olivia; McEwen, Sarah; Debnath, Monojit; McGrath, John; Maes, Michael; Amminger, Paul; McGorry, Patrick D; Pantelis, Christos; Berk, Michael (2016-06-01). "A review of vulnerability and risks for schizophrenia: Beyond the two hit hypothesis". Neuroscience & Biobehavioral Reviews. 65: 185–194. doi:10.1016/j.neubiorev.2016.03.017. ISSN 0149-7634. PMC 4876729. PMID 27073049.
  4. ^ Jablensky, Assen (2010-09-30). "The diagnostic concept of schizophrenia: its history, evolution, and future prospects". Dialogues in Clinical Neuroscience. 12 (3): 271–287. doi:10.31887/DCNS.2010.12.3/ajablensky. PMC 3181977. PMID 20954425.
  5. ^ a b c Gur, Raquel E.; Gur, Ruben C. (2010-09-30). "Functional magnetic resonance imaging in schizophrenia". Dialogues in Clinical Neuroscience. 12 (3): 333–343. doi:10.31887/DCNS.2010.12.3/rgur. PMC 3181978. PMID 20954429.
  6. ^ Schultze-Lutter, Frauke; Theodoridou, Anastasia (February 2017). "The concept of basic symptoms: its scientific and clinical relevance". World Psychiatry. 16 (1): 104–105. doi:10.1002/wps.20404. PMC 5269478. PMID 28127912.
  7. ^ a b c d Javitt, Daniel C. (2009-04-01). "When Doors of Perception Close: Bottom-up Models of Disrupted Cognition in Schizophrenia". Annual Review of Clinical Psychology. 5 (1): 249–275. doi:10.1146/annurev.clinpsy.032408.153502. ISSN 1548-5943. PMC 4501390. PMID 19327031.
  8. ^ Rudert, Thomas; Lohmann, Gabriele (December 2008). "Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics". Journal of Magnetic Resonance Imaging. 28 (6): 1533–1539. doi:10.1002/jmri.21518. PMID 19025961. S2CID 206097466.
  9. ^ Gomez-Pilar, Javier (30 June 2020). Characterization of neural activity using complex network theory : an application to the study of schizophrenia. Springer. ISBN 978-3-030-49900-6. OCLC 1176541540.
  10. ^ a b c d Li, Peng; Fan, Teng-Teng; Zhao, Rong-Jiang; Han, Ying; Shi, Le; Sun, Hong-Qiang; Chen, Si-Jing; Shi, Jie; Lin, Xiao; Lu, Lin (2017-07-14). "Altered Brain Network Connectivity as a Potential Endophenotype of Schizophrenia". Scientific Reports. 7 (1): 5483. Bibcode:2017NatSR...7.5483L. doi:10.1038/s41598-017-05774-3. ISSN 2045-2322. PMC 5511161. PMID 28710394.
  11. ^ Wu, Lei; Eichele, Tom; Calhoun, Vince D. (October 2010). "Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: A concurrent EEG-fMRI study". NeuroImage. 52 (4): 1252–1260. doi:10.1016/j.neuroimage.2010.05.053. ISSN 1053-8119. PMC 3059127. PMID 20510374.
  12. ^ Schneider, F.; Weiss, U.; Kessler, C.; Salloum, J.B.; Posse, S.; Grodd, W.; Müller-Gärtner, H.W. (November 1998). "Differential amygdala activation in schizophrenia during sadness". Schizophrenia Research. 34 (3): 133–142. doi:10.1016/s0920-9964(98)00085-1. ISSN 0920-9964. PMID 9850979. S2CID 13213002.
  13. ^ Karbasforoushan, H.; Woodward, N.D. (2012-11-01). "Resting-State Networks in Schizophrenia". Current Topics in Medicinal Chemistry. 12 (21): 2404–2414. doi:10.2174/156802612805289863. PMID 23279179.
  14. ^ a b c Yu, Qingbao; A. Allen, Elena; Sui, Jing; R. Arbabshirani, Mohammad; Pearlson, Godfrey; D. Calhoun, Vince (2012-11-01). "Brain Connectivity Networks in Schizophrenia Underlying Resting State Functional Magnetic Resonance Imaging". Current Topics in Medicinal Chemistry. 12 (21): 2415–2425. doi:10.2174/156802612805289890. PMC 4429862. PMID 23279180.
  15. ^ Dabiri, Mona; Dehghani Firouzabadi, Fatemeh; Yang, Kun; Barker, Peter B.; Lee, Roland R.; Yousem, David M. (2022-11-15). "Neuroimaging in schizophrenia: A review article". Frontiers in Neuroscience. 16. doi:10.3389/fnins.2022.1042814. ISSN 1662-453X.
  16. ^ Tuovinen, Noora; Hofer, Alex (2023-04-06). "Resting-state functional MRI in treatment-resistant schizophrenia". Frontiers in Neuroimaging. 2. doi:10.3389/fnimg.2023.1127508. ISSN 2813-1193.
  17. ^ Barch, Deanna M.; Csernansky, John G. (2007-07-01). "Abnormal Parietal Cortex Activation During Working Memory in Schizophrenia: Verbal Phonological Coding Disturbances Versus Domain-General Executive Dysfunction". American Journal of Psychiatry. 164 (7): 1090–1098. doi:10.1176/ajp.2007.164.7.1090. ISSN 0002-953X. PMID 17606661.
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