Reporting Guidelines and Issues to Consider for Using Intracranial Brain Stimulation in Studies of Human Declarative Memory

Participants with stimulating and recording electrodes implanted within the brain for clinical evaluation and treatment provide a rare opportunity to unravel the neuronal correlates of human memory, as well as offer potential for modulation of behavior. Recent intracranial stimulation studies of memory have been inconsistent in methodologies employed and reported conclusions, which renders generalizations and construction of a framework impossible. In an effort to unify future study efforts and enable larger meta-analyses we propose in this mini-review a set of guidelines to consider when pursuing intracranial stimulation studies of human declarative memory and summarize details reported by previous relevant studies. We present technical and safety issues to consider when undertaking such studies and a checklist for researchers and clinicians to use for guidance when reporting results, including targeting, placement, and localization of electrodes, behavioral task design, stimulation and electrophysiological recording methods, details of participants, and statistical analyses. We hope that, as research in invasive stimulation of human declarative memory further progresses, these reporting guidelines will aid in setting standards for multicenter studies, in comparison of findings across studies, and in study replications

Enhancing the Ecological Validity of fMRI Memory Research Using Virtual Reality

Functional magnetic resonance imaging (fMRI) is a powerful research tool to understand the neural underpinnings of human memory. However, as memory is known to be context-dependent, differences in contexts between naturalistic settings and the MRI scanner environment may potentially confound neuroimaging findings. Virtual reality (VR) provides a unique opportunity to mitigate this issue by allowing memories to be formed and/or retrieved within immersive, navigable, visuospatial contexts. This can enhance the ecological validity of task paradigms, while still ensuring that researchers maintain experimental control over critical aspects of the learning and testing experience. This mini-review surveys the growing body of fMRI studies that have incorporated VR to address critical questions about human memory. These studies have adopted a variety of approaches, including presenting research participants with VR experiences in the scanner, asking participants to retrieve information that they had previously acquired in a VR environment, or identifying neural correlates of behavioral metrics obtained through VR-based tasks performed outside the scanner. Although most such studies to date have focused on spatial or navigational memory, we also discuss the promise of VR in aiding other areas of memory research and facilitating research into clinical disorders

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

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

Acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans: A TD-fNIRS neuroimaging study

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 (fALFF), 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 studies demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine 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

Decoding of human identity by computer vision and neuronal vision

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL

The Priority Structure of Bank Regulatory Capital: The Case of Subordinated Debt

The aftermath of a crisis often brings reflections on the adequacy of regulatory capital against financial shocks. Accordingly, succeeding regulatory interventions focus on strengthening the resilience of the banking system by improving the quality and quantity of capital, and subordinated debt (sub-debt) remains key to these reforms. Whether, however, the regulatory motive underpins the decision of banks to issue sub-debt is unclear. Moreover, the perceptions of shareholders on the regulatory function of sub-debt are less understood. This thesis attempts to answer these questions by first reviewing other roles of sub-debt then testing if regulation drives its issuance and finally revealing shareholder incentives that weaken its regulatory function. Contrasting capital requirement motives with other explanations, and accounting for equity issuance, we find that banks issue sub-debt primarily to improve their regulatory capital buffer. While a few non-regulatory factors, related to easier entry conditions to debt market, influence the issuance decision, their economic impact is smaller than the impact of the buffer. By exploring how variations in tail risk and size influence the sub-debt and equity issuance decisions by banks with low buffers, we show that issuance choices do not reflect risk-shifting incentives. Next, we review shareholders’ perceptions of the regulatory value of sub-debt vis-a-vis the risk-shifting and wealth-expropriation incentives associated with senior debt by comparing the reaction of stocks to these security announcements. We find that senior debt incentives are more valuable than the regulatory benefit of sub-debt. Contrary to regulatory expectations, announcement of sub-debt (capital-improving) offers are valueless even when undertaken by risky or less-capitalized banks; rather, senior debt offered by these vulnerable banks generate significant shareholder value. Pursuant to these risk-shifting motives, senior debt issuers get riskier post-issuance. These findings suggest that the broader debt priority structure harbours perverse incentives that dilute the regulatory effectiveness of sub-debt

Kernel Flow:a high channel count scalable time-domain functional near-infrared spectroscopy system

Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.</p

Minute-scale periodicity of neuronal firing in the human entorhinal cortex

Summary: Grid cells in the entorhinal cortex demonstrate spatially periodic firing, thought to provide a spatial map on behaviorally relevant length scales. Whether such periodicity exists for behaviorally relevant time scales in the human brain remains unclear. We investigate neuronal firing during a temporally continuous experience by presenting 14 neurosurgical patients with a video while recording neuronal activity from multiple brain regions. We report on neurons that modulate their activity in a periodic manner across different time scales—from seconds to many minutes, most prevalently in the entorhinal cortex. These neurons remap their dominant periodicity to shorter time scales during a subsequent recognition memory task. When the video is presented at two different speeds, a significant percentage of these temporally periodic cells (TPCs) maintain their time scales, suggesting a degree of invariance. The TPCs’ temporal periodicity might complement the spatial periodicity of grid cells and together provide scalable spatiotemporal metrics for human experience