Biology subjects

Nath, M.

Publications and source records attributed to Nath, M..

8 recordsLinked to original sources

bioRxiv2026

Meditation Depth Enhances the Functional Signal-to-Noise Ratio of the Brain

Across contemplative traditions, depper states of meditation are described as states of heightened clarity, vividness, and stillness of mind, yet what this clarity corresponds to in the brain has remained difficult to specify. The functional signal-to-noise ratio (f-SNR) framework frames mental clarity as a measurable property of neural signals: the degree to which brain activity tracks the causes of sensory signals rather than endogenous, irrelevant, fluctuations. It predicts that deepening meditation should raise f-SNR, expressing sensory events more faithfully in neural signals against ongoing background activity. We tested this prediction across different levels of meditative depth. Twenty-nine experienced Vipassana practitioners meditated while auditory tones were presented, periodically reporting their depth of meditation. f-SNR was quantified from event-related potentials (ERPs) in a fronto-central P3 window and from single-trial decodability of auditory tone-evoked activity against no-tone background EEG. High-depth states were associated with greater ERP signal-to-noise ratio, stronger single-trial signal consistency, and improved decodability of sound tones. These results suggest that meditative depth is expressed in the reproducibility and stimulus-background separability of sensory responses, consistent with deep meditation enhancing the brains functional signal-to-noise ratio by improving the clarity of sensory signals and reducing endogenous noise.

neuroscience↗

bioRxiv2022

Bi-Phasic Quasistatic Brain Communication for Fully Untethered Connected Brain Implants

Wireless communication using electro-magnetic (EM) fields acts as the backbone for information exchange among wearable devices around the human body. However, for Implanted devices, EM fields incur high amount of absorption in the tissue, while alternative modes of transmission including ultrasound, optical and magnetoelectric methods result in large amount of transduction losses due to conversion of one form of energy to another, thereby increasing the overall end-to-end energy loss. To solve the challenge of wireless powering and communication in a brain implant with low end-end channel loss, we present Bi-Phasic Quasistatic Brain Communication (BP-QBC), achieving < 60dB worst-case end-to-end channel loss at a channel length of ~55mm, by using Electro-quasistatic (EQS) Signaling that avoids transduction losses due to no field-modality conversion. BP-QBC utilizes dipole coupling based signal transmission within the brain tissue using differential excitation in the transmitter (TX) and differential signal pick-up at the receiver (RX), while offering ~41X lower power w.r.t. traditional Galvanic Human Body Communication (G-HBC) at a carrier frequency of 1MHz, by blocking any DC current paths through the brain tissue. Since the electrical signal transfer through the human tissue is electro-quasistatic up to several 10s of MHz range, BP-QBC allows a scalable (bps-10Mbps) duty-cycled uplink (UL) from the implant to an external wearable. The power consumption in the BP-QBC TX is only 0.52 W at 1Mbps (with 1% duty cycling), which is within the range of harvested power in the downlink (DL) from a wearable hub to an implant through the EQS brain channel, with externally applied electric currents < 1/5th of ICNIRP safety limits. Furthermore, BP-QBC eliminates the need for sub-cranial interrogators/repeaters, as it offers better signal strength due to no field transduction. Such low end-to-end channel loss with high data rates enabled by a completely new modality of brain communication and powering has deep societal and scientific impact in the fields of neurobiological research, brain-machine interfaces, electroceuticals and connected healthcare.

biophysics↗

bioRxiv2021

Preclinical Efficacy of IMM-BCP-01, a Highly Active Patient-Derived Anti-SARS-CoV-2 Antibody Cocktail

Using an unbiased interrogation of the memory B cell repertoire of convalescent COVID-19 patients, we identified human antibodies that demonstrated robust antiviral activity in vitro and efficacy in vivo against all tested SARS-CoV-2 variants. Here, we describe the pre-clinical characterization of an antibody cocktail, IMM-BCP-01, that consists of three unique, patient-derived recombinant neutralizing antibodies directed at non-overlapping surfaces on the SARS-CoV-2 spike protein. Two antibodies, IMM20184 and IMM20190 directly block spike binding to the ACE2 receptor. Binding of the third antibody, IMM20253, to its unique epitope on the outer surface of RBD, alters the conformation of the spike trimer, promoting release of spike monomers. These antibodies decreased SARS-CoV-2 infection in the lungs of Syrian golden hamsters, and efficacy in vivo efficacy was associated with broad antiviral neutralizing activity against multiple SARS-CoV-2 variants and robust antiviral effector function response, including phagocytosis, ADCC, and complement pathway activation. Our pre-clinical data demonstrate that the three antibody cocktail IMM-BCP-01 shows promising potential for preventing or treating SARS-CoV-2 infection in susceptible individuals. One sentence summaryIMM-BCP-01 cocktail triggers Spike Trimer dissociation, neutralizes all tested variants in vitro, activates a robust effector response and dose-dependently inhibits virus in vivo.

immunology↗

bioRxiv2021

Unbiased interrogation of memory B cells from convalescent COVID-19 patients reveals a broad antiviral humoral response targeting SARS-CoV-2 antigens beyond the spike protein

Patients who recover from SARS-CoV-2 infections produce antibodies and antigen-specific T cells against multiple viral proteins. Here, an unbiased interrogation of the anti-viral memory B cell repertoire of convalescent patients has been performed by generating large, stable hybridoma libraries and screening thousands of monoclonal antibodies to identify specific, high-affinity immunoglobulins (Igs) directed at distinct viral components. As expected, a significant number of antibodies were directed at the Spike (S) protein, a majority of which recognized the full-length protein. These full-length Spike specific antibodies included a group of somatically hypermutated IgMs. Further, all but one of the six COVID-19 convalescent patients produced class-switched antibodies to a soluble form of the receptor-binding domain (RBD) of S protein. Functional properties of anti-Spike antibodies were confirmed in a pseudovirus neutralization assay. Importantly, more than half of all of the antibodies generated were directed at non-S viral proteins, including structural nucleocapsid (N) and membrane (M) proteins, as well as auxiliary open reading frame-encoded (ORF) proteins. The antibodies were generally characterized as having variable levels of somatic hypermutations (SHM) in all Ig classes and sub-types, and a diversity of VL and VH gene usage. These findings demonstrated that an unbiased, function-based approach towards interrogating the COVID-19 patient memory B cell response may have distinct advantages relative to genomics-based approaches when identifying highly effective anti-viral antibodies directed at SARS-CoV-2.

immunology↗

bioRxiv2020

Bio-Physical Modeling of Galvanic Human Body Communication in Electro-Quasistatic Regime

Human Body Communication (HBC) is an alternative to radio wave-based Wireless Body Area Network (WBAN) because of its low-loss, wide bandwidth leading to enhanced energy efficiency. HBC also shows better performance in terms of physical security as most of the signal is confined within the body. To obtain optimum performance and usability, modeling of the body channel plays a vital role. Out of two HBC modalities, Galvanic HBC has the promise to provide lower loss compare to Capacitive HBC for shorter channel length. In this paper, we present the first lumped element based detailed model of Galvanic HBC channel which is used to explain the dependency of channel loss on the material property of skin, fat and muscle tissue layer along with electrode size, electrode separation, geometrical position of the electrodes and return path capacitance. The model considers the impedance of skin and muscle tissue layers and the effect of various coupling capacitances between the body and Tx/Rx electrodes to the Earth-ground. A 2D planner structure is simulated in HFSS to prove the validity of the proposed model. The effect of symmetry and asymmetry at the transmitter and receiver end are also explained using the model. The experimental results show that, due to the mismatch at the transmitter and receiver side, the loss increases gradually with channel length and saturates to a finite value as channel length becomes significantly longer compare to the transmitting or receiving electrode pair separation.

bioengineering↗

bioRxiv2020

Advanced Biophysical Model to Capture Channel Variability for EQS Capacitive HBC

Human Body Communication (HBC) has come up as a promising alternative to traditional radio frequency (RF) Wireless Body Area Network (WBAN) technologies. This is essentially due to HBC providing a broadband communication channel with enhanced signal security in the physical layer due to lower radiation from the human body as compared to its RF counterparts. An in-depth understanding of the mechanism for the channel loss variability and associated biophysical model needs to be developed before EQS-HBC can be used more frequently in WBAN consumer and medical applications. Biophysical models characterizing the human body as a communication channel didnt exist in literature for a long time. Recent developments have shown models that capture the channel response for fixed transmitter and receiver positions on the human body. These biophysical models do not capture the variability in the HBC channel for varying positions of the devices with respect to the human body. In this study, we provide a detailed analysis of the change in path loss in a capacitive-HBC channel in the electroquasistatic (EQS) domain. Causes of channel loss variability namely: inter-device coupling and effects of fringe fields due to bodys shadowing effects are investigated. FEM based simulation results are used to analyze the channel response of human body for different positions and sizes of the device which are further verified using measurement results to validate the developed biophysical model. Using the bio-physical model, we develop a closed form equation for the path loss in a capacitive HBC channel which is then analyzed as a function of the geometric properties of the device and the position with respect to the human body which will help pave the path towards future EQS-HBC WBAN design.

bioengineering↗

bioRxiv2020

Understanding The Role of Magnetic and Magneto-Quasistatic Fields in Human Body Communication

With the advent of wearable technologies, Human Body Communication (HBC) has emerged as a physically secure and power-efficient alternative to the otherwise ubiquitous Wireless Body Area Network (WBAN). Whereas the most investigated nodes of HBC have been Electric and Electro-quasistatic (EQS) Capacitive and Galvanic, recently Magnetic HBC (M-HBC) has been proposed as a viable alternative. Previous works have investigated M-HBC through an application point of view, without developing a fundamental working principle for the same. In this paper, for the first time, a ground up analysis has been performed to study the possible effects and contributions of the human body channel in M-HBC over a broad frequency range (1kHz to 10 GHz), by detailed electromagnetic simulations and supporting experiments. The results show that while M-HBC can be successfully operated as a body area network, the human body itself plays a minimal or negligible role in its functionality. For frequencies less than[~] 30 Hz, in the domain of operation of Magneto-quasistatic (MQS) HBC, the human body is transparent to the quasistatic magnetic field. Conversely for higher frequencies, the conductive nature of human tissues end up attenuating Magnetic HBC fields due to Eddy currents induced in body tissues, eliminating the possibility of the body to support efficient waveguide modes. With this better understanding at hand, different modes of operations of MQS HBC have been outlined for both high impedance capacitive and 50{Omega} termination cases, and their performances have been compared with EQS HBC for similar sized devices, over varying distance between TX and RX. The resulting report presents the first fundamental understanding towards M-HBC operation and its contrast with EQS HBC, aiding HBC device designers to make educated design decisions, depending on mode of applications.

bioengineering↗

bioRxiv2017

Determining whether a class of random graphs is consistent with an observed contact network

We demonstrate a general method to analyze the sensitivity of attack rate in a network model of infectious disease epidemiology to the structure of the network. We use Moore and Shannons \"network reliability\" statistic to measure the epidemic potential of a network. A number of networks are generated using exponential random graph models based on the properties of the contact network structure of one of the Add Health surveys. The expected number of infections on the original Add Health network is significantly different from that on any of the models derived from it. Because individual-level transmissibility and network structure are not separately identifiable parameters given population-level attack rate data it is possible to re-calibrate the transmissibility to fix this difference. However, the temporal behavior of the outbreak remains significantly different. Hence any estimates of the effectiveness of time dependent interventions on one network are unlikely to generalize to the other. Moreover, we show that in one case even a small perturbation to the network spoils the re-calibration. Unfortunately, the set of sufficient statistics for specifying a contact network model is not yet known. Until it is, estimates of the outcome of a dynamical process on a particular network obtained from simulations on a different network are not reliable.

epidemiology↗