Interhemispheric Differences Observed during the Performance of Cognitive Tasks Using Doppler Ultrasound

Mikadze, Yu. V.; Лысенко, Елена; Bogdanova, M.; Abuzaid, S.; Shakhnovich, A. R.

doi:10.1134/s0362119718020135

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…Processing speed may mediate the demonstrated differences in hemodynamic pattern according to symptom severity and cognitive demand for the TMT-A and TMT-B. This lends further support to the notion that neuronal activity and cerebral blood flow are closely coupled; with MFV resulting from the activation of (or correspondingly the failure to deactivate) cortical areas in the MCA's irrigation territory (9,12,19,39,40). Patients with schizophrenia demonstrate increased brain activity (as indicated by a higher MFV) for lower performance (i.e., slower processing speed) compared to healthy controls (16).…”

Section: Discussionsupporting

confidence: 62%

Psychopathological Symptom Load and Distinguishable Cerebral Blood Flow Velocity Patterns in Patients With Schizophrenia and Healthy Controls: A Functional Transcranial Doppler Study

et al. 2021

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Introduction: Schizophrenia is a severe psychiatric disorder, with executive dysfunction and impaired processing speed playing a pivotal role in the course of the disease. In patients with schizophrenia, neurocognitive deficits appear to be related to alterations in cerebral hemodynamics. It is not fully understood if psychopathological symptom load (i.e., presence and severity of symptoms) is also related to alterations in cerebral hemodynamics. We aim to study the relationship between psychopathological symptom load and cerebral hemodynamics in the Middle Cerebral Artery (MCA) during a cognitive task in patients with schizophrenia and healthy controls.Methodology: Cerebral hemodynamics in the MCA were examined in 30 patients with schizophrenia and 15 healthy controls using functional Transcranial Doppler (fTCD) during the Trail Making Test (TMT). Psychopathological symptoms were measured using the Brief Psychiatric Rating Scale (BPRS). Patients were dichotomized according to BPRS scores: mild-moderate (BPRS < 41, n = 15) or marked-severe (BPRS ≧ 41, n = 15). Mean blood flow velocity (MFV) in the MCA and processing speed of the TMT were analyzed. Cerebral hemodynamics were analyzed using the general additional model (GAM) with a covariate analysis of variance (ANCOVA) for group comparisons.Results: Patients and healthy controls were comparable regarding demographics. Patients had a slower processing speed for the TMT-A (patients-severe: 52s, patients-moderate: 40s, healthy-controls: 32s, p = 0.019) and TMT-B [patients-severe: 111s, patients-moderate: 76s, healthy-controls: 66s, p < 0.001)]. Patients demonstrated differing hemodynamic profiles in both TMTs: TMT- A [F(6, 1,792) = 17, p < 0.000); TMT-B [F(6, 2,692) = 61.93, p < 0.000], with a delay in increase in MFV and a failure to return to baseline values.Conclusions: Patients with schizophrenia demonstrated slower speeds of processing during both the TMT-A and TMT-B. The speed of processing deteriorated with increasing psychopathological symptom load, additionally a distinct cerebral hemodynamic pattern in the MCA was observed. Our results further support the view that severity of schizophrenia, particularly psychopathological symptom load, influences performance in neurocognitive tasks and is related to distinct patterns of brain hemodynamics.

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Section: Discussionsupporting

confidence: 62%

Psychopathological Symptom Load and Distinguishable Cerebral Blood Flow Velocity Patterns in Patients With Schizophrenia and Healthy Controls: A Functional Transcranial Doppler Study

et al. 2021

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“…The resulting hemodynamic curve probably results from the activation of brain areas responsible for visuo‐motor activity 32,33 . The left MCA showed a slightly greater increase in MFV; this finding is most likely attributable to the fact that our study sample was exclusively right‐handed 33,34 …”

Section: Discussionmentioning

confidence: 89%

“…32,33 The left MCA showed a slightly greater increase in MFV; this finding is most likely attributable to the fact that our study sample was exclusively righthanded. 33,34 Through the assessment of MFV, during a visuo-motor task in healthy probands, we avoid the effects of cognitive effort and pathophysiological anomalies of any given disorder. 22,27,31,35,36 This removes the requirement for clinical interpretation of our hemodynamic findings, 5,18,37,38 allowing the focus to remain on the statistical analysis and visual representation of MFV.…”

Section: Discussionmentioning

confidence: 99%

Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity

Egger

Bobes

Seifritz

et al. 2021

Health Science Reports

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Introduction Transcranial Doppler (TCD) is a method used to study cerebral hemodynamics. In the majority of TCD studies, regression analysis and analysis of variance are the most frequently applied statistical methods. However, due to the dynamic and interdependent nature of flow velocity, nonparametric tests may allow for better statistical analysis and representation of results. Method The sample comprised 30 healthy participants, aged 33.87 ± 7.48 years; with 33% (n = 10) females. During a visuo‐motor task, the mean flow velocity (MFV) in the middle cerebral artery (MCA) was measured using TCD. The MFV was converted to values relative to the resting state. The results obtained were analyzed using the general linear model (GLM) and the general additional model (GAM). The fit indices of both analysis methods were compared with each other. Results Both MCAs showed a steady increase in MFV during the visuo‐motor task, smoothly returning to resting state values. During the first 20 seconds of the visuo‐motor task, the MFV increased by a factor of 1.06 ± 0.07 in the right‐MCA and by a factor of 1.08 ± 0.07 in the left‐MCA. GLM and GAM showed a statistically significant change in MFV (GLM:F(2, 3598) = 16.76, P < .001; GAM:F(2, 3598) = 21.63, P < .001); together with effects of hemispheric side and gender (GLM:F(4, 3596) = 7.83, P < .005; GAM:F(4, 3596) = 2.13, P = .001). Comparing the models using the χ2 test for goodness of fit yields a significant difference χ2 (9.9556) = 0.6836, P < .001. Conclusions Both the GLM and GAM yielded valid statistical models of MFV in the MCA in healthy subjects. However, the model using the GAM resulted in improved fit indices. The GAM's advantage becomes even clearer when the MFV curves are visualized; yielding a more realistic approach to brain hemodynamics, thus allowing for an improvement in the interpretation of the mathematical and statistical results. Our results demonstrate the utility of the GAM for the analysis and representation of hemodynamic parameters.

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Section: Discussionmentioning

confidence: 99%

Functional Transcranial Doppler: selection of methods for statistical analysis and representation of changes in flow velocity.

Egger,

Bobes,

Seifritz

et al. 2024

Preprint

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Introduction Transcranial Doppler (TCD) is method used to study cerebral hemodynamics. The analysis majority of TCD studies are conducted at group level, pooling change in flow velocity over several subjects. Analysis of variance are the most frequently applied statistical methods However, due to the dynamic nature of flow velocity, non- parametric tests, may allow for a better representation of results. Methods During a visuo-motor task, the mean flow velocity (MFV) in the middle cerebral artery (MCA) in healthy-subjects was measured using TCD. All MFV values were converted to relative values, i.e. compared with resting values. The results obtained were analyzed using the general linear model (GLM) and the general additional models (GAM). Both methods of analysis were compared against with each other. Results The sample comprised 30 healthy participants, aged 33.87±7.48 years; 33% females. The MFV for the first 20 seconds was 1.06±0.07 in the right-MCA and 1.08±0.07 in the left-MCA. Both MCAs showed a steady increase in MFV, returning to resting state. GL- and GA-Models showed a statistically significant change in MFC (GLM: F (2, 3598) = 16.76, p<0.001; GAM: F (2, 3598) = 21.63, p<0.001); as well as differences in hemispheric side and gender. Comparing the models using a Chi-square test for goodness of fit yields a significant difference X2 (9.9556) = 0.6836, p= <0.000. With a superiority of the models using GAM. Discussion GLM and GAM of the MFV yielded similar results; the model using the GAM resulted in a better measurement of fit. The GAM’s advantage becomes clearer when the mean flow velocity curves are visualised; yielding a more realistic approach to brain hemodynamics, thus allowing for an improvement in interpretation of the mathematical and statistical results. Conclusion Our results demonstrate the utility of the GAM for the analysis of hemodynamic measurements.

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Interhemispheric Differences Observed during the Performance of Cognitive Tasks Using Doppler Ultrasound

Cited by 3 publications

References 7 publications

Psychopathological Symptom Load and Distinguishable Cerebral Blood Flow Velocity Patterns in Patients With Schizophrenia and Healthy Controls: A Functional Transcranial Doppler Study

Psychopathological Symptom Load and Distinguishable Cerebral Blood Flow Velocity Patterns in Patients With Schizophrenia and Healthy Controls: A Functional Transcranial Doppler Study

Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity

Functional Transcranial Doppler: selection of methods for statistical analysis and representation of changes in flow velocity.

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