Functional Near-infrared Spectroscopy Of Prefrontal Cortex During Memory Encoding And Recall In Elderly With Type 2 Diabetes Mellitus

Zhao, Fei; Tomita, Machiko; Dutta, Anirban

doi:10.20944/preprints202202.0045.v1

Cited by 2 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Case report procedures were performed according to the local regulations for research on human subjects at the University at Buffalo. Portable brain imaging was performed using four sources and two detectors of a portable fNIRS (Octamon+, Artinis Medical Systems, Gelderland, the Netherlands) placed at the forehead (see the optode montage from [ 20 ]). Figure 9 a shows the sensitivity profile of the optode montage that covered the middle frontal gyrus (orbital part) and superior frontal gyrus (dorsolateral part) bilaterally [ 62 ].…”

Section: Human-in-the-loop Optimization For Model Predictive Control ...mentioning

confidence: 99%

“…Additionally, 0.01–0.02 Hz oscillations are known to be crucial for supporting higher oxygen concentrations distant from the small vessels [ 19 ]. Zhao et al [ 20 ] found a drop in the oscillatory power in the 0.01–0.02 Hz frequency band during Mini-Cog assessment for dementia, where this drop was more significant in type 2 diabetes mellitus (T2DM) patients than in age-matched normoglycemic elderly controls. Small-vessel oscillations support nutrient supply, where low-frequency Fahraeus–Lindqvist-driven (not blood-pressure-driven) oscillations in the small vessels are crucial [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective

Arora

Dutta

2022

Brain Sciences

View full text Add to dashboard Cite

Individual differences in the responsiveness of the brain to transcranial electrical stimulation (tES) are increasingly demonstrated by the large variability in the effects of tES. Anatomically detailed computational brain models have been developed to address this variability; however, static brain models are not “realistic” in accounting for the dynamic state of the brain. Therefore, human-in-the-loop optimization at the point of care is proposed in this perspective article based on systems analysis of the neurovascular effects of tES. First, modal analysis was conducted using a physiologically detailed neurovascular model that found stable modes in the 0 Hz to 0.05 Hz range for the pathway for vessel response through the smooth muscle cells, measured with functional near-infrared spectroscopy (fNIRS). During tES, the transient sensations can have arousal effects on the hemodynamics, so we present a healthy case series for black-box modeling of fNIRS–pupillometry of short-duration tDCS effects. The block exogeneity test rejected the claim that tDCS is not a one-step Granger cause of the fNIRS total hemoglobin changes (HbT) and pupil dilation changes (p < 0.05). Moreover, grey-box modeling using fNIRS of the tDCS effects in chronic stroke showed the HbT response to be significantly different (paired-samples t-test, p < 0.05) between the ipsilesional and contralesional hemispheres for primary motor cortex tDCS and cerebellar tDCS, which was subserved by the smooth muscle cells. Here, our opinion is that various physiological pathways subserving the effects of tES can lead to state–trait variability, which can be challenging for clinical translation. Therefore, we conducted a case study on human-in-the-loop optimization using our reduced-dimensions model and a stochastic, derivative-free covariance matrix adaptation evolution strategy. We conclude from our computational analysis that human-in-the-loop optimization of the effects of tES at the point of care merits investigation in future studies for reducing inter-subject and intra-subject variability in neuromodulation.

show abstract

Section: Human-in-the-loop Optimization For Model Predictive Control ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective

Arora

Dutta

2022

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…Then, 0.01-0.02Hz oscillations are known to be crucial to support higher oxygen concentration distant from the small vessels [19]. Zhao et al [20] found a drop in the oscillatory power in the 0.01-0.02Hz frequency band during Mini-Cog assessment for dementia, where this drop was more significant in type 2 diabetes Mellitus (T2DM) than age-matched normoglycemic elderly. Small vessel oscillations support nutrient supply where low-frequency Fahraeus-Lindqvist-driven (not blood pressure-driven) oscillations in the small vessels are crucial [19].…”

mentioning

confidence: 99%

“…Case report procedures were performed according to the local regulations for human subjects' research at the University at Buffalo. Portable brain imaging was performed using four sources and two detectors of a portable fNIRS (Octamon+, Artinis Medical Systems, Netherlands) placed at the forehead (optode montage from [20]). Figure 11a shows the sensitivity profile of the optode montage that covered the middle frontal gyrus (orbital part) and superior frontal gyrus (dorsolateral part) bilaterally [69] 30sec fNIRS data epoch after the end of the tOCS ON period was performed in Matlab using functions from the open-source HOMER3 package (https://github.com/BUNPC/Homer3).…”

mentioning

confidence: 99%

Human-In-The-Loop Optimization of Transcranial Electrical Stimulation Effects: A Computational Perspective Based on Systems Analysis

Arora¹,

Dutta²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

Individual differences in the responsiveness of the brain to transcranial electrical stimulation (tES) is increasingly demonstrated in large variability in the tES effects. Anatomically detailed computational brain models have been developed to address this variability; however, static brain models are not ‘realistic’ in accounting for the dynamic state of the brain. Therefore, human-in-the-loop optimization is proposed in this perspective article based on an extensive systems analysis of the tES neurovascular effects. First, modal analysis was conducted using a physiologically detailed neurovascular model that found stable modes in the 0 Hz to 0.05 Hz range for the pathway for vessel response through the smooth muscle cells, measured with functional near-infrared spectroscopy (fNIRS). tES effects in the 0 Hz to 0.05 Hz range can also be measured with functional magnetic resonance imaging (fMRI)-tDCS data with a maximum TR=10sec. Therefore, we investigated an open-source fMRI-tDCS dataset that used a TR=3.36sec. We found that both the anodal tDCS condition and sham tDCS condition had similar Finite Impulse Response at the region of interest underlying the anode and a remote location, which indicated a global hemodynamic effect of sham tDCS beyond the intended transient sensations. Here, transient sensations can have arousal effects on the hemodynamics so we conducted a healthy case series for black box modeling of fNIRS-pupillometry of short-duration tDCS effects. The block exogeneity test rejected the claim that tDCS is not a 1-step Granger-cause of the fNIRS total hemoglobin changes (HbT) and pupil dilation changes (p<0.05). Also, grey-box modeling using fNIRS of the tDCS effects in chronic stroke showed HbT response to be significantly different (paired-sample t-test, p<0.05) between the ipsilesional and the contralesional hemisphere for primary motor cortex tDCS and cerebellar tDCS which was subserved by the smooth muscle cells. Here, our perspective is that various physiological pathways subserving tES effects can lead to state-trait variability that can be challenging for clinical translation. Therefore, we conducted a case study on human-in-the-loop optimization using our reduced dimension model and a stochastic, derivative-free Covariance Matrix Adaptation Evolution Strategy. Future studies need to investigate human-in-the-loop optimization of tES for reducing inter-subject and intra-subject variability in tES effects.

show abstract

Functional Near-infrared Spectroscopy Of Prefrontal Cortex During Memory Encoding And Recall In Elderly With Type 2 Diabetes Mellitus

Cited by 2 publications

References 22 publications

Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective

Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective

Human-In-The-Loop Optimization of Transcranial Electrical Stimulation Effects: A Computational Perspective Based on Systems Analysis

Contact Info

Product

Resources

About