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Kehnemouyi, Y. M.

Publications and source records attributed to Kehnemouyi, Y. M..

2 recordsLinked to original sources

Multimodal Reorganization of Gut--Brain Physiology During the Cephalic Phase of Digestion

The vagus nerve plays a central role in gut--brain communication, yet the physiological dynamics associated with cholinergic vagal signaling remain difficult to characterize non-invasively in humans. The cephalic phase response, which prepares the gastrointestinal system for food ingestion through anticipatory vagal pathways, offers a unique opportunity to investigate these interactions. Here, we used simultaneous recordings of cortical, gastric, cardiac, and swallow physiology in healthy adults to characterize brain--body responses during food anticipation and subsequent ingestion. Food-related sensory cues increased gastric myoelectric activity as well as swallow and heart rate while eliciting frequency-specific changes in cortical oscillations. Strikingly, anticipation was accompanied by opposing changes in physiological coordination: synchronization within cortical and gastric networks decreased, whereas coupling between the brain and stomach increased. These changes largely returned toward baseline following ingestion, suggesting a distinct anticipatory organization of brain--body activity. Moreover, gastric responses were associated with various aspects of subjective appetite, whereas cortical responses were selectively associated with craving. Both gastric and cortical responses independently explained the variation in participants' self-reported craving. Together, these findings reveal that food anticipation reorganizes physiological coordination within and across central and peripheral systems, establishing the cephalic phase as a non-invasive framework for investigating brain--body interactions associated with cholinergic vagal signaling in humans.

neuroscience↗

A Novel Method for Calculating Beta Band Burst Durations in Parkinson's Disease Using a Physiological Baseline

BackgroundPathological bursts of neural activity in Parkinsons disease present as exaggerated subthalamic neuronal oscillations in the 8-30 Hz frequency range and are related to motor impairment. New MethodThis study introduces a novel method for determining burst dynamics using a baseline that matches physiological 1/f spectrum activity. We used resting state local field potentials from people with Parkinsons disease and a simulated 1/f signal to measure beta burst durations, to demonstrate how tuning parameters (i.e., bandwidth and center frequency) affect burst durations, to compare this with high power threshold methods, and to study the effect of increasing neurostimulation intensities on burst duration. ResultsBurst durations calculated using the Anderson method captured the longest and broadest distribution of burst durations in a pathological beta band compared to previous methods. Mean beta band burst durations were significantly shorter on compared to off neurostimulation (p = 0.011), and their distribution was shifted towards that of the physiological 1/f spectrum during increasing intensities of stimulation. Comparison with Existing MethodExisting methods of measuring local field potential power either lack temporal specificity to detect bursts (power spectral density diagrams and spectrograms) or include only higher power bursts and portions of the neural signal. ConclusionsWe suggest that this novel method is well suited to quantify the full range of fluctuations in beta band neural activity in the Parkinsonian brain. This method may reveal more relevant feedback biomarkers than averaged beta band power for future closed loop algorithms. HighlightsA novel method for measuring variability in subthalamic local field potential oscillations in Parkinsons disease using a physiological baseline of power. Modeling normal brain activity using a physiological 1/f spectrum. Burst durations depend on choice of bandwidth and center frequency. Defining an inert frequency band whose mean burst duration overlap the physiological 1/f spectrum, from which the baseline was determined. Burst durations progressively shortened during increasing intensities of deep brain stimulation.

neuroscience↗