Hydrogen-bonded organic framework nanotransducers enabled sono-optogenetics for Parkinsonian rats.

Cell-type-specific activation of parvalbumin (PV)-expressing neurons in the external globus pallidus (GPe) through optogenetics has shown promise in facilitating long-lasting movement dysfunction recovery in mice with Parkinson's disease. However, its translational potential is hindered by adverse effects stemming from the invasive implantation of optical fibers into the brain. In this study, we have developed a non-invasive optogenetics approach, utilizing focused ultrasound-triggered mechanoluminescent nanotransducers to enable remote photon delivery deep in the brain for genetically targeted neuromodulation.

Multiscale effective connectivity analysis of brain activity using neural ordinary differential equations.

Neural mechanisms and underlying directionality of signaling among brain regions depend on neural dynamics spanning multiple spatiotemporal scales of population activity. Despite recent advances in multimodal measurements of brain activity, there is no broadly accepted multiscale dynamical models for the collective activity represented in neural signals. Here we introduce a neurobiological-driven deep learning model, termed multiscale neural dynamics neural ordinary differential equation (msDyNODE), to describe multiscale brain communications governing cognition and behavior.

Adaptation and learning as strategies to maximize reward in neurofeedback tasks.

Introduction: Adaptation and learning have been observed to contribute to the acquisition of new motor skills and are used as strategies to cope with changing environments. However, it is hard to determine the relative contribution of each when executing goal directed motor tasks. This study explores the dynamics of neural activity during a center-out reaching task with continuous visual feedback under the influence of rotational perturbations.

Spatial resolution enhancement in photon-starved STED imaging using deep learning-based fluorescence lifetime analysis.

As a super-resolution imaging method, stimulated emission depletion (STED) microscopy has unraveled fine intracellular structures and provided insights into nanoscale organizations in cells. Although image resolution can be further enhanced by continuously increasing the STED-beam power, the resulting photodamage and phototoxicity are major issues for real-world applications of STED microscopy. Here we demonstrate that, with 50% less STED-beam power, the STED image resolution can be improved up to 1.

Estimating Intrinsic Manifold Dimensionality to Classify Task-Related Information in Human and Non-Human Primate Data.

Feature selection, or dimensionality reduction, has become a standard step in reducing large-scale neural datasets into usable signals for brain-machine interface and neurofeedback decoders. Current techniques in fMRI data reduce the number of voxels (features) by performing statistics on individual voxels or using traditional techniques that utilize linear combinations of features (e.g.

Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions.

Short-training Algorithm for Online Brain-machine Interfaces Using One-photon Microendoscopic Calcium Imaging.

Calcium imaging has great potential to be applied to online brain-machine interfaces (BMIs). As opposed to two-photon imaging settings, a one-photon microendoscopic imaging device can be chronically implanted and is subject to little motion artifacts. Traditionally, one-photon microendoscopic calcium imaging data are processed using the constrained nonnegative matrix factorization (CNMFe) algorithm, but this batched processing algorithm cannot be applied in real-time.

Multi-scale neural decoding and analysis.

. Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code.

Head-mounted microendoscopic calcium imaging in dorsal premotor cortex of behaving rhesus macaque.

Microendoscopic calcium imaging with one-photon miniature microscopes enables unprecedented readout of neural circuit dynamics during active behavior in rodents. In this study, we describe successful application of this technology in the rhesus macaque, demonstrating plug-and-play, head-mounted recordings of cellular-resolution calcium dynamics from large populations of neurons simultaneously in bilateral dorsal premotor cortices during performance of a naturalistic motor reach task. Imaging is stable over several months, allowing us to longitudinally track individual neurons and monitor their relationship to motor behavior over time.

Making the jump: Expert guidance on transitioning to academic independence.

Obtaining a position as an independent investigator is a daunting prospect, and often requires skill sets that are not emphasized during graduate or postdoctoral training. Here, we present insight from a seminar series designed to guide young researchers looking to "make the jump", covering the fundamental steps of the job search (preparation of an application package, Skype/remote interview, campus visit, and negotiations). We summarize the many useful insights distilled throughout these roundtable sessions with the goal of providing information and guidance to a broader community of researchers on the best way to prepare for and tackle the faculty job market.

A wireless and artefact-free 128-channel neuromodulation device for closed-loop stimulation and recording in non-human primates.

Closed-loop neuromodulation systems aim to treat a variety of neurological conditions by delivering and adjusting therapeutic electrical stimulation in response to a patient's neural state, recorded in real time. Existing systems are limited by low channel counts, lack of algorithmic flexibility, and the distortion of recorded signals by large and persistent stimulation artefacts. Here, we describe an artefact-free wireless neuromodulation device that enables research applications requiring high-throughput data streaming, low-latency biosignal processing, and simultaneous sensing and stimulation.

A high-density carbon fiber neural recording array technology.

Objective: Microwire and Utah-style neural recording arrays are the predominant devices used for cortical neural recording, but the implanted electrodes cause a significant adverse biological response and suffer from well-studied performance degradation. Recent work has demonstrated that carbon fiber electrodes do not elicit this same adverse response, but these existing designs are not practically scalable to hundreds or thousands of recording sites. We present technology that overcomes these issues while additionally providing fine electrode pitch for spatial oversampling.

Recent advances in neural dust: towards a neural interface platform.

The neural dust platform uses ultrasonic power and communication to enable a scalable, wireless, and batteryless system for interfacing with the nervous system. Ultrasound offers several advantages over alternative wireless approaches, including a safe method for powering and communicating with sub mm-sized devices implanted deep in tissue. Early studies demonstrated that neural dust motes could wirelessly transmit high-fidelity electrophysiological data in vivo, and that theoretically, this system could be miniaturized well below the mm-scale.

Caudate Microstimulation Increases Value of Specific Choices.

Value-based decision-making involves an assessment of the value of items available and the actions required to obtain them. The basal ganglia are highly implicated in action selection and goal-directed behavior [1-4], and the striatum in particular plays a critical role in arbitrating between competing choices [5-9]. Previous work has demonstrated that neural activity in the caudate nucleus is modulated by task-relevant action values [6, 8].