Transcranial Low-Intensity Focused Ultrasound Stimulation of the Visual Thalamus Produces Long-Term Depression of Thalamocortical Synapses in the Adult Visual Cortex

Transcranial focused ultrasound stimulation (tFUS) is a noninvasive neuromodulation technique, which can penetrate deeper and modulate neural activity with a greater spatial resolution (on the order of millimeters) than currently available noninvasive brain stimulation methods, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). While there are several studies demonstrating the ability of tFUS to modulate neuronal activity, it is unclear whether it can be used for producing long-term plasticity as needed to modify circuit function, especially in adult brain circuits with limited plasticity such as the thalamocortical synapses. Here we demonstrate that transcranial low-intensity focused ultrasound (LIFU) stimulation of the visual thalamus (dorsal lateral geniculate nucleus, dLGN), a deep brain structure, leads to NMDA receptor (NMDAR)-dependent long-term depression of its synaptic transmission onto layer 4 neurons in the primary visual cortex (V1) of adult mice of both sexes. This change is not accompanied by large increases in neuronal activity, as visualized using the cFos Targeted Recombination in Active Populations (cFosTRAP2) mouse line, or activation of microglia, which was assessed with IBA-1 staining. Using a model (SONIC) based on the neuronal intramembrane cavitation excitation (NICE) theory of ultrasound neuromodulation, we find that the predicted activity pattern of dLGN neurons upon sonication is state-dependent with a range of activity that falls within the parameter space conducive for inducing long-term synaptic depression. Our results suggest that noninvasive transcranial LIFU stimulation has a potential for recovering long-term plasticity of thalamocortical synapses in the postcritical period adult brain.

NSF DARE-transforming modeling in neurorehabilitation: perspectives and opportunities from US funding agencies

In recognition of the importance and timeliness of computational models for accelerating progress in neurorehabilitation, the U.S. National Science Foundation (NSF) and the National Institutes of Health (NIH) sponsored a conference in March 2023 at the University of Southern California that drew global participation from engineers, scientists, clinicians, and trainees. This commentary highlights promising applications of computational models to understand neurorehabilitation ("Using computational models to understand complex mechanisms in neurorehabilitation" section), improve rehabilitation care in the context of digital twin frameworks ("Using computational models to improve delivery and implementation of rehabilitation care" section), and empower future interdisciplinary workforces to deliver higher-quality clinical care using computational models ("Using computational models in neurorehabilitation requires an interdisciplinary workforce" section). The authors describe near-term gaps and opportunities, all of which encourage interdisciplinary team science. Four major opportunities were identified including (1) deciphering the relationship between engineering figures of merit-a term commonly used by engineers to objectively quantify the performance of a device, system, method, or material relative to existing state of the art-and clinical outcome measures, (2) validating computational models from engineering and patient perspectives, (3) creating and curating datasets that are made publicly accessible, and (4) developing new transdisciplinary frameworks, theories, and models that incorporate the complexities of the nervous and musculoskeletal systems. This commentary summarizes U.S. funding opportunities by two Federal agencies that support computational research in neurorehabilitation. The NSF has funding programs that support high-risk/high-reward research proposals on computational methods in neurorehabilitation informed by theory- and data-driven approaches. The NIH supports the development of new interventions and therapies for a wide range of nervous system injuries and impairments informed by the field of computational modeling. The conference materials can be found at https://dare2023.usc.edu/ .

Special Issue-Biosensors and Neuroscience: Is Biosensors Engineering Ready to Embrace Design Principles from Neuroscience?

In partnership with the Air Force Office of Scientific Research (AFOSR), the National Science Foundation's (NSF) Emerging Frontiers and Multidisciplinary Activities (EFMA) office of the Directorate for Engineering (ENG) launched an Emerging Frontiers in Research and Innovation (EFRI) topic for the fiscal years FY22 and FY23 entitled "Brain-inspired Dynamics for Engineering Energy-Efficient Circuits and Artificial Intelligence" (BRAID) [...].

Online learning for orientation estimation during translation in an insect ring attractor network

Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

Cognitive swarming in complex environments with attractor dynamics and oscillatory computing

Neurobiological theories of spatial cognition developed with respect to recording data from relatively small and/or simplistic environments compared to animals' natural habitats. It has been unclear how to extend theoretical models to large or complex spaces. Complementarily, in autonomous systems technology, applications have been growing for distributed control methods that scale to large numbers of low-footprint mobile platforms. Animals and many-robot groups must solve common problems of navigating complex and uncertain environments. Here, we introduce the NeuroSwarms control framework to investigate whether adaptive, autonomous swarm control of minimal artificial agents can be achieved by direct analogy to neural circuits of rodent spatial cognition. NeuroSwarms analogizes agents to neurons and swarming groups to recurrent networks. We implemented neuron-like agent interactions in which mutually visible agents operate as if they were reciprocally connected place cells in an attractor network. We attributed a phase state to agents to enable patterns of oscillatory synchronization similar to hippocampal models of theta-rhythmic (5-12 Hz) sequence generation. We demonstrate that multi-agent swarming and reward-approach dynamics can be expressed as a mobile form of Hebbian learning and that NeuroSwarms supports a single-entity paradigm that directly informs theoretical models of animal cognition. We present emergent behaviors including phase-organized rings and trajectory sequences that interact with environmental cues and geometry in large, fragmented mazes. Thus, NeuroSwarms is a model artificial spatial system that integrates autonomous control and theoretical neuroscience to potentially uncover common principles to advance both domains.

Plasmonic coupled nanotorch structures leading to uniform surface enhanced Raman scattering detection

Nanocrescent-like structures have become important surface enhanced Raman scattering structures because instead of relying on a few nanometer gap inter-particle plasmonic coupling to achieve local field enhancement, intra-particle plasmonic coupling between the cavity modes and the tip edges are utilized to achieve high local field enhancement at the tips. Our fabrication approach creates 'nanotorch' structures with controllable cavity rim opening and deterministic orientation to yield uniform Raman measurements, consisting of three-dimensional upright-oriented nanocrescent structures resting on nanopillars. Each structure serves as a single SERS substrate. We demonstrate that a nanotorch with a smaller rim opening results in a higher enhancement factor compare to one with a larger opening. More importantly, the uniformity of all the analysed Raman modes of adsorbed benzenethiol is better than 80% due to the consistent, upright orientation of each single nanotorch SERS substrate, paving the way for practical implementation of SERS detection.

Collection of aerosolized human cytokines using Teflon® filters

BACKGROUND

Collection of exhaled breath samples for the analysis of inflammatory biomarkers is an important area of research aimed at improving our ability to diagnose, treat and understand the mechanisms of chronic pulmonary disease. Current collection methods based on condensation of water vapor from exhaled breath yield biomarker levels at or near the detection limits of immunoassays contributing to problems with reproducibility and validity of biomarker measurements. In this study, we compare the collection efficiency of two aerosol-to-liquid sampling devices to a filter-based collection method for recovery of dilute laboratory generated aerosols of human cytokines so as to identify potential alternatives to exhaled breath condensate collection.

METHODOLOGY/PRINCIPAL FINDINGS

Two aerosol-to-liquid sampling devices, the SKC® Biosampler and Omni 3000™, as well as Teflon® filters were used to collect aerosols of human cytokines generated using a HEART nebulizer and single-pass aerosol chamber setup in order to compare the collection efficiencies of these sampling methods. Additionally, methods for the use of Teflon® filters to collect and measure cytokines recovered from aerosols were developed and evaluated through use of a high-sensitivity multiplex immunoassay. Our results show successful collection of cytokines from pg/m(3) aerosol concentrations using Teflon® filters and measurement of cytokine levels in the sub-picogram/mL concentration range using a multiplex immunoassay with sampling times less than 30 minutes. Significant degradation of cytokines was observed due to storage of cytokines in concentrated filter extract solutions as compared to storage of dry filters.

CONCLUSIONS

Use of filter collection methods resulted in significantly higher efficiency of collection than the two aerosol-to-liquid samplers evaluated in our study. The results of this study provide the foundation for a potential new technique to evaluate biomarkers of inflammation in exhaled breath samples.

A model-based tool to predict the propagation of infectious disease via airports

Epidemics of novel or re-emerging infectious diseases have quickly spread globally via air travel, as highlighted by pandemic H1N1 influenza in 2009 (pH1N1). Federal, state, and local public health responders must be able to plan for and respond to these events at aviation points of entry. The emergence of a novel influenza virus and its spread to the United States were simulated for February 2009 from 55 international metropolitan areas using three basic reproduction numbers (R(0)): 1.53, 1.70, and 1.90. Empirical data from the pH1N1 virus were used to validate our SEIR model. Time to entry to the U.S. during the early stages of a prototypical novel communicable disease was predicted based on the aviation network patterns and the epidemiology of the disease. For example, approximately 96% of origins (R(0) of 1.53) propagated a disease into the U.S. in under 75 days, 90% of these origins propagated a disease in under 50 days. An R(0) of 1.53 reproduced the pH1NI observations. The ability to anticipate the rate and location of disease introduction into the U.S. provides greater opportunity to plan responses based on the scenario as it is unfolding. This simulation tool can aid public health officials to assess risk and leverage resources efficiently.

Detection of respiratory viruses on air filters from aircraft

Aims:  To evaluate the feasibility of identifying viruses from aircraft cabin air, we evaluated whether respiratory viruses trapped by commercial aircraft air filters can be extracted and detected using a multiplex PCR, bead‐based assay.

Methods and Results:  The ResPlex II assay was first tested for its ability to detect inactivated viruses applied to new filter material; all 18 applications of virus at a high concentration were detected. The ResPlex II assay was then used to test for 18 respiratory viruses on 48 used air filter samples from commercial aircraft. Three samples tested positive for viruses, and three viruses were detected: rhinovirus, influenza A and influenza B. For 33 of 48 samples, internal PCR controls performed suboptimally, suggesting sample matrix effect.

Conclusion:  In some cases, influenza and rhinovirus RNA can be detected on aircraft air filters, even more than 10 days after the filters were removed from aircraft.

Significance and Impact of the Study:  With protocol modifications to overcome PCR inhibition, air filter sampling and the ResPlex II assay could be used to characterize viruses in aircraft cabin air. Information about viruses in aircraft could support public health measures to reduce disease transmission within aircraft and between cities.

An analysis on the detection of biological contaminants aboard aircraft

The spread of infectious disease via commercial airliner travel is a significant and realistic threat. To shed some light on the feasibility of detecting airborne pathogens, a sensor integration study has been conducted and computational investigations of contaminant transport in an aircraft cabin have been performed. Our study took into consideration sensor sensitivity as well as the time-to-answer, size, weight and the power of best available commercial off-the-shelf (COTS) devices. We conducted computational fluid dynamics simulations to investigate three types of scenarios: (1) nominal breathing (up to 20 breaths per minute) and coughing (20 times per hour); (2) nominal breathing and sneezing (4 times per hour); and (3) nominal breathing only. Each scenario was implemented with one or seven infectious passengers expelling air and sneezes or coughs at the stated frequencies. Scenario 2 was implemented with two additional cases in which one infectious passenger expelled 20 and 50 sneezes per hour, respectively. All computations were based on 90 minutes of sampling using specifications from a COTS aerosol collector and biosensor. Only biosensors that could provide an answer in under 20 minutes without any manual preparation steps were included. The principal finding was that the steady-state bacteria concentrations in aircraft would be high enough to be detected in the case where seven infectious passengers are exhaling under scenarios 1 and 2 and where one infectious passenger is actively exhaling in scenario 2. Breathing alone failed to generate sufficient bacterial particles for detection, and none of the scenarios generated sufficient viral particles for detection to be feasible. These results suggest that more sensitive sensors than the COTS devices currently available and/or sampling of individual passengers would be needed for the detection of bacteria and viruses in aircraft.

High-throughput detection and sizing of individual low-index nanoparticles and viruses for pathogen identification

Rapid, chip-scale, and cost-effective single particle detection of biological agents is of great importance to human health and national security. We report real-time, high-throughput detection and sizing of individual, low-index polystyrene nanoparticles and H1N1 virus. Our widefield, common path interferometer detects nanoparticles and viruses over a very large sensing area, orders of magnitude larger than competing techniques. We demonstrate nanoparticle detection and sizing down to 70 nm in diameter. We clearly size discriminate nanoparticles with diameters of 70, 100, 150, and 200 nm. We also demonstrate detection and size characterization of hundreds of individual H1N1 viruses in a single experiment.

Characterizing the ERP Old-New effect in a short-term memory task

The early and late components of the event-related potential (ERP) Old-New effect are well characterized with respect to long-term memory, and have been associated with processes of familiarity and recollection, respectively. Now, using a short-term memory paradigm with verbal and nonverbal stimuli, we explored the way that these two components respond to variation in recency and stimulus type. We found that the amplitude of the early component (or frontal N400, FN400) showed Old-New effects only for verbal stimuli and increased with recency. In contrast, the later component (or late positive component, LPC) showed Old-New effects across a range of stimulus types and did not scale with recency. These results are consistent with the way that these same ERP components have been characterized in long-term memory, supporting the idea that some of the same processes underlie long- and short-term item recognition.

Pharmacokinetics of fosinoprilat in Chinese and whites after intravenous administration

The pharmacokinetics of fosinoprilat was studied in 12 healthy Chinese men after a 7.5 mg intravenous dose of fosinoprilat. The data were compared with those from an earlier study using the same protocol in nine healthy white men. Blood and urine samples were obtained before and at various time intervals after fosinoprilat administration up to 24 hours and 48 hours, respectively. Pharmacokinetic parameters were calculated by fitting the plasma or serum concentrations to a three-compartment model. The total clearance (Clt), renal clearance (ClT), and nonrenal clearance (ClNR) were significantly lower in Chinese (16.29 +/- 6.92, 6.85 +/- 2.97, and 9.44 +/- 5.08 mL.hr-1.kg-1) than those obtained in whites (29.88 +/- 6.36, 13.55 +/- 3.45, and 16.33 +/- 5.07 mL.hr-1.kg-1). The Chinese subjects had a significantly lower volume of distribution (Vc [volume of distribution of central compartment] and Vdss [volume of distribution at steady state]) (29.38 +/- 21.12 and 73.67 +/- 40.20 mL/kg) than white men (58.14 +/- 15.01 and 152.49 +/- 24.89 mL/kg). The Chinese men also had a shorter elimination half-life than whites, although not statistically significant. The respective half-lives in Chinese and whites were 5.51 +/- 1.53 and 8.24 +/- 1.99 hours. The significant differences in ClNR and ClR may be related to lower liver elimination function and lower kidney excretory function, respectively. Plasma protein binding may contribute to part of the difference in the volume of distribution. Chinese men have smaller volume of distribution and clearances of fosinoprilat after intravenous administration compared with white men. The cumulative urine excretion of fosinoprilat was not different between Chinese and whites. Chinese may require a lower fosinoprilat dosage to obtain plasma concentrations similar to whites after intravenous administration. However, since a relatively high variation was found in fosinopril oral absorption, the oral dosage of fosinopril for Chinese and whites may not be different. Further study is obviously needed to elucidate whether the pharmacodynamic effect may be different between Chinese and whites.