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The intention was to associate blood pressure (BP) variability (BPV) measurements to Local field potentials (LFPs). Thus, assessing how LFPs can co-vary with BPV to permit implantable brain devices (via LFPs) to control output. Elevated BPV is a considerable cardiovascular disease risk factor. Often patients are resistant to pharmacotherapies. An alternative treatment is Deep Brain Stimulation (DBS). Mathematical techniques based on nonlinear dynamics assessed their correlation of BPV chaotic global metrics to LFPs. Chaos Forward Parameter (CFP6) was computed for LFPs, at three electrode depths in the mid-brain and sensory thalamus. Mean, root mean square of the successive differences (RMSSD) and the chaotic global metrics (CFP1 to CFP7) were computed for the BP signal. The right ventroposterolateral (RVPL) nucleus provided a substantial correlation via CFP6 for BP with R-squared up to approximately 79% by means of LFP gamma oscillations. Investigation of BPV via LFPs as a proxy marker might allow therapies to be attuned in a closed-loop system. Whilst all patients were chronic pain patients the chaotic global relationship should be unperturbed. LFPs correlation does not unconditionally predict its causation. There is no certainty DBS in these locations would be therapeutic but can be used as an assessment tool.

Although previous studies have reported correlations between alpha oscillations and the “retention” sub-process of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain. Conventional tACS is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention sub-process). Here, we developed an online phase-corrected closed-loop transcranial alternating current stimulation (tACS) system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits both up- and down-regulation of brain oscillations at the target stimulation frequency within a short stimulation period, and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to 39 participants during the retention sub-processes of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. Moreover, the in-phase tACS-induced changes in WM performance were positively correlated with alpha oscillatory activity. These findings strongly support a causal link between alpha oscillations and WM retention, and illustrate the broad application prospects of phase-corrected tACS.

Background: Gait impairments including shuffling gait and hesitation are common in people with Parkinson's disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD. Objective: This study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS). Methods: A total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated. Results: The results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F-1,F-48=69.75, P<.001, partial eta-square=0.59), initial step angle (F-1,F-48=15.56, P<.001, partial eta-square=0.25), and last step angle (F-1,F-48=61.99, P<.001, partial eta-square=0.56). Within the PD cohort, both the ALCT and DBS induced greater mean step angles (ACLT: F-1,F-38=5.77, P=.02, partial eta-square=0.13; DBS: F-1,F-52=8.53, P=.005, partial eta-square=0.14) and last step angles (ACLT: F-1,F-38=1