Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS

Abstract

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings.

Time-Domain Diffuse Optical Tomography for Precision Neuroscience

“…The data preprocessing procedures have been extensively detailed in our previous studies ( 15 ). Initially, we applied a channel selection method based on histogram shape criteria ( 14 ).…”

“…We previously published on the characterization and validation of our prototype system, Kernel Flow1 ( 14 ). While the prototype system was used in several scientific studies ( 13, 15, 16 ), it had some limitations: there were gaps in spatial coverage over the head; pre-recorded instrument response functions (IRFs) were not sufficiently stable in time to ensure accuracy of absolute metrics; detectors had limited sensitivity; and the system had high power requirements. As such, we had confined our prior analyses to those performed in channel space and did not fully explore Flow1’s whole-head DOT capabilities.…”

Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System

“…Various features spanning physiological, optical and neural domains can be extracted from Flow2 headset recordings during resting state. In the current study, we focused on a non-exhaustive set of features, which were affected by pharmacological manipulation in our prior studies 37 , and/or which have strong literature support in terms of relating to individual differences. These features are from the four following categories: (1) absolute HbO/HbR in the prefrontal region, (2) effective attenuation coefficient (EAC) 45 calculated at two different wavelengths (3) fractional amplitude of low frequency fluctuations (fALFF) within the left and and right prefrontal regions for HbO/HbR, (4) and functional connectivity (FC) within the left and right prefrontal regions for HbO/HbR (Methods).…”

“…Data preprocessing and relative hemoglobin concentrations Data preprocessing steps are described at length in prior work 37 . We first implemented a channel selection procedure using histogram shape criteria 35 .…”

“…Until the development of Kernel Flow, this technology was not widely used and had been relatively inaccessible due to its bulky, expensive, and complex nature 34 . Kernel’s first-generation Flow headset was benchmarked using a set of standardized protocols for TD-fNIRS systems 35 and validated in human studies 36,37 . Nonetheless, to our knowledge—barring a few reports 38 —very few studies to date have done a comprehensive TRR quantification of TD-fNIRS measurements and if so, they only focused on very limited features of the modality.…”