Numerous studies report that BOLD fMRI signal variance (SD BOLD ) decreases with age. However, these associations may partly reflect cardiovascular contributions to the BOLD signal. For example, heart rate variability (HRV) has been positively associated with Resting State Fluctuation Amplitude (RSFA), which captures low frequency components of BOLD fMRI variability. HRV is also negatively associated with age, which could potentially confound age-SD BOLD associations. Yet, limited research has examined HRV-SD BOLD associations or tested within-person HRV-SD BOLD coupling using sliding window analyses of simultaneous HRV and SD BOLD . We analyzed resting-state fMRI data from two independent Midlife in the United States (MIDUS) samples: Core at M3 (n=115) and Refresher at MR1 (n=101). Partial Least Squares (PLS) analyses revealed significant positive HRV-SD BOLD associations (Core: permutation p=0.018; Refresher: permutation p<0.001). Whole brain age-SD BOLD PLS associations were non-significant via permutation tests across several models (Core: permutation p=0.201; Refresher: permutation p=0.121). We found age-related decreases in SD BOLD across ∼70% of voxels in both samples. Concordance analyses showed 67-69% of brain voxels exhibited negative age-SD BOLD but positive HRV-SD BOLD relationships, suggesting that regions showing age-related decreases in SD BOLD also showed HRV-related increases in SD BOLD . Sliding-window analyses demonstrated robust positive within-person associations between person-centered HRV and SD BOLD via different HRV metrics: SDNN (Core: p < 0.001; Refresher: p < 0.001), RMSSD (Core: p = 0.072; Refresher: p = 0.009), and low frequency (Core: p < 0.001; Refresher: p < 0.001), with non-significant effects of high frequency (Core: p = 0.516; Refresher: p = 0.12) HRV. Thus, regardless of baseline levels, windows with higher HRV corresponded to higher SD BOLD , suggesting that cardiovascular factors partially explain age-SD BOLD associations and HRV may mechanistically influence SD BOLD . These results suggest that controlling for HRV, especially low-frequency HRV or SDNN, may be necessary when analyzing SD BOLD to isolate neural effects.
Background/Objectives: Intracranial macroelectrode implantation is a pivotal clinical tool in the evaluation of drug-resistant epilepsy, allowing further insights into the localization of the epileptogenic zone and the delineation of eloquent cortical regions through cortical stimulation. Additionally, it provides an avenue to study brain functions by analyzing cerebral responses during neuropsychological paradigms. By combining macroelectrodes with microelectrodes, which allow to record the activity of individual neurons or smaller neural clusters, recordings could provide deeper insights into neuronal microcircuits and the brain’s transitions in epilepsy and contribute to a better understanding of neuropsychological functions. In this study, one or two hybrid macro-micro electrodes were implanted in the anterior-inferior insular region in patients with refractory epilepsy. We report our experience and share some preliminary results; we also provide some recommendations regarding the implantation procedure of hybrid electrodes in the insular cortex. Methods: Stereoelectroencephalography was performed in 13 patients, with one or two hybrid macro-microelectrodes positioned in the insular region in each patient. Research neuropsychological paradigms could not be done in two patients for clinical reasons. In total, 23 hybrid macro-microelectrodes with 8 microcontacts each were implanted, of which 20 were recorded. Spiking activity was detected and assessed using WaveClus3. Results: No spiking neural activity was detected in the microcontacts of the first 7 patients. After iterative refinement during this process, successful recordings were obtained from 13 microcontacts in the anterior-inferior insula in the last four patients (13/64, 20.3%). Hybrid electrode implantation was uneventful with no complications. Obstacles included the absence of spiking activity signals, unsuccessful microwire dispersion, and the interference of environmental electrical noise on recordings. Conclusions: Human microelectrode recording presents a complex array of challenges; yet it holds the potential to facilitate a more comprehensive understanding of individual neuronal attributes and their specific stimulus responses.
Background/Objectives: Intracranial macroelectrode implantation is a pivotal clinical tool in the evaluation of drug-resistant epilepsy, allowing further insights into the localization of the epileptogenic zone and the delineation of eloquent cortical regions through cortical stimulation. Additionally, it provides an avenue to study brain functions by analyzing cerebral responses during neuropsychological paradigms. By combining macroelectrodes with microelectrodes, which allow recording the activity of individual neurons or smaller neural clusters, recordings could provide deeper insights into neuronal microcircuits and the brain’s transitions in epilepsy and contribute to a better understanding of neuropsychological functions. In this study, one or two hybrid macro-micro electrodes were implanted in the anterior-inferior insular region in patients with refractory epilepsy. We report our experience and share some preliminary results; we also provide some recommendations regarding the implantation procedure for hybrid electrodes in the insular cortex. Methods: Stereoelectroencephalography was performed in 13 patients, with one or two hybrid macro-microelectrodes positioned in the insular region in each patient. Research neuropsychological paradigms could not be implemented in two patients for clinical reasons. In total, 23 hybrid macro-microelectrodes with eight microcontacts each were implanted, of which 20 were recorded. Spiking activity was detected and assessed using WaveClus3. Results: No spiking neural activity was detected in the microcontacts of the first seven patients. After iterative refinement during this process, successful recordings were obtained from 13 microcontacts in the anterior-inferior insula in the last four patients (13/64, 20.3%). Hybrid electrode implantation was uneventful with no complications. Obstacles included the absence of spiking activity signals, unsuccessful microwire dispersion, and the interference of environmental electrical noise in recordings. Conclusions: Human microelectrode recording presents a complex array of challenges; however, it holds the potential to facilitate a more comprehensive understanding of individual neuronal attributes and their specific stimulus responses.