Closed-loop and activity-guided optogenetic control

Primate eye tracking with carbon-nanotube-paper-composite based capacitive sensors and machine learning algorithms

BACKGROUND

Accurate real-time eye tracking is crucial in oculomotor system research. While the scleral search coil system is the gold standard, its implantation procedure and bulkiness pose challenges. Camera-based systems are affected by ambient lighting and require high computational and electric power.

NEW METHOD

This study presents a novel eye tracker using proximity capacitive sensors made of carbon-nanotube-paper-composite (CPC). These sensors detect femtofarad-level capacitance changes caused by primate corneal movement during horizontal and vertical eye rotations. Data processing and machine learning algorithms are evaluated to enhance the accuracy of gaze angle prediction.

RESULTS

The system performance is benchmarked against the scleral coil during smooth pursuits, saccades tracking, and fixations. The eye tracker demonstrates up to 0.97 correlation with the coil in eye tracking and is capable of estimating gaze angle with a median absolute error as low as 0.30°.

COMPARISON

The capacitive eye tracker demonstrates good consistency and accuracy in comparison to the gold-standard scleral search coil method.

CONCLUSIONS

This lightweight, non-invasive capacitive eye tracker offers potential as an alternative to traditional coil and camera-based systems in oculomotor research and vision science.

NeuroART: Real-Time Analysis and Targeting of Neuronal Population Activity during Calcium Imaging for Informed Closed-Loop Experiments

Two-photon calcium imaging allows for the activity readout of large populations of neurons at single cell resolution in living organisms, yielding new insights into how the brain processes information. Holographic optogenetics allows us to trigger activity of this population directly, raising the possibility of injecting information into a living brain. Optogenetic triggering of activity that mimics "natural" information, however, requires identification of stimulation targets based on real-time analysis of the functional network. We have developed NeuroART (Neuronal Analysis in Real Time), software that provides real-time readout of neuronal activity integrated with downstream analysis of correlations and synchrony and of sensory metadata. On the example of auditory stimuli, we demonstrate real-time inference of the contribution of each neuron in the field of view to sensory information processing. To avoid the limitations of microscope hardware and enable collaboration of multiple research groups, NeuroART taps into microscope data streams without the need for modification of microscope control software and is compatible with a wide range of microscope platforms. NeuroART also integrates the capability to drive a spatial light modulator (SLM) for holographic photostimulation of optimal stimulation targets, enabling real-time modification of functional networks. Neurons used for photostimulation experiments were extracted from Sprague Dawley rat embryos of both sexes.

Nonlinear model predictive control of a conductance-based neuron model via data-driven forecasting

Objective. Precise control of neural systems is essential to experimental investigations of how the brain controls behavior and holds the potential for therapeutic manipulations to correct aberrant network states. Model predictive control, which employs a dynamical model of the system to find optimal control inputs, has promise for dealing with the nonlinear dynamics, high levels of exogenous noise, and limited information about unmeasured states and parameters that are common in a wide range of neural systems. However, the challenge still remains of selecting the right model, constraining its parameters, and synchronizing to the neural system.Approach. As a proof of principle, we used recent advances in data-driven forecasting to construct a nonlinear machine-learning model of a Hodgkin-Huxley type neuron when only the membrane voltage is observable and there are an unknown number of intrinsic currents.Main Results. We show that this approach is able to learn the dynamics of different neuron types and can be used with model predictive control (MPC) to force the neuron to engage in arbitrary, researcher-defined spiking behaviors.Significance.To the best of our knowledge, this is the first application of nonlinear MPC of a conductance-based model where there is only realistically limited information about unobservable states and parameters.

Multi-timescale neural dynamics for multisensory integration

Carrying out any everyday task, be it driving in traffic, conversing with friends or playing basketball, requires rapid selection, integration and segregation of stimuli from different sensory modalities. At present, even the most advanced artificial intelligence-based systems are unable to replicate the multisensory processes that the human brain routinely performs, but how neural circuits in the brain carry out these processes is still not well understood. In this Perspective, we discuss recent findings that shed fresh light on the oscillatory neural mechanisms that mediate multisensory integration (MI), including power modulations, phase resetting, phase-amplitude coupling and dynamic functional connectivity. We then consider studies that also suggest multi-timescale dynamics in intrinsic ongoing neural activity and during stimulus-driven bottom-up and cognitive top-down neural network processing in the context of MI. We propose a new concept of MI that emphasizes the critical role of neural dynamics at multiple timescales within and across brain networks, enabling the simultaneous integration, segregation, hierarchical structuring and selection of information in different time windows. To highlight predictions from our multi-timescale concept of MI, real-world scenarios in which multi-timescale processes may coordinate MI in a flexible and adaptive manner are considered.

Multimodal Technologies for Closed-Loop Neural Modulation and Sensing

Existing methods for studying neural circuits and treating neurological disorders are typically based on physical and chemical cues to manipulate and record neural activities. These approaches often involve predefined, rigid, and unchangeable signal patterns, which cannot be adjusted in real time according to the patient's condition or neural activities. With the continuous development of neural interfaces, conducting in vivo research on adaptive and modifiable treatments for neurological diseases and neural circuits is now possible. In this review, current and potential integration of various modalities to achieve precise, closed-loop modulation, and sensing in neural systems are summarized. Advanced materials, devices, or systems that generate or detect electrical, magnetic, optical, acoustic, or chemical signals are highlighted and utilized to interact with neural cells, tissues, and networks for closed-loop interrogation. Further, the significance of developing closed-loop techniques for diagnostics and treatment of neurological disorders such as epilepsy, depression, rehabilitation of spinal cord injury patients, and exploration of brain neural circuit functionality is elaborated.

Optogenetic Brain-Computer Interfaces

The brain-computer interface (BCI) is one of the most powerful tools in neuroscience and generally includes a recording system, a processor system, and a stimulation system. Optogenetics has the advantages of bidirectional regulation, high spatiotemporal resolution, and cell-specific regulation, which expands the application scenarios of BCIs. In recent years, optogenetic BCIs have become widely used in the lab with the development of materials and software. The systems were designed to be more integrated, lightweight, biocompatible, and power efficient, as were the wireless transmission and chip-level embedded BCIs. The software is also constantly improving, with better real-time performance and accuracy and lower power consumption. On the other hand, as a cutting-edge technology spanning multidisciplinary fields including molecular biology, neuroscience, material engineering, and information processing, optogenetic BCIs have great application potential in neural decoding, enhancing brain function, and treating neural diseases. Here, we review the development and application of optogenetic BCIs. In the future, combined with other functional imaging techniques such as near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI), optogenetic BCIs can modulate the function of specific circuits, facilitate neurological rehabilitation, assist perception, establish a brain-to-brain interface, and be applied in wider application scenarios.

Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed

Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop control that effect powerful causal interventions. At the same time, improved computational models are capable of reproducing behavior and neural activity with increasing fidelity. Unfortunately, these advances have drastically increased the complexity of integrating different lines of research, resulting in the missed opportunities and untapped potential of suboptimal experiments. Experiment simulation can help bridge this gap, allowing model and experiment to better inform each other by providing a low-cost testbed for experiment design, model validation, and methods engineering. Specifically, this can be achieved by incorporating the simulation of the experimental interface into our models, but no existing tool integrates optogenetics, two-photon calcium imaging, electrode recording, and flexible closed-loop processing with neural population simulations. To address this need, we have developed Cleo: the Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed. Cleo is a Python package enabling injection of recording and stimulation devices as well as closed-loop control with realistic latency into a Brian spiking neural network model. It is the only publicly available tool currently supporting two-photon and multi-opsin/wavelength optogenetics. To facilitate adoption and extension by the community, Cleo is open-source, modular, tested, and documented, and can export results to various data formats. Here we describe the design and features of Cleo, validate output of individual components and integrated experiments, and demonstrate its utility for advancing optogenetic techniques in prospective experiments using previously published systems neuroscience models.

Real-time analysis of large-scale neuronal imaging enables closed-loop investigation of neural dynamics

Large-scale imaging of neuronal activities is crucial for understanding brain functions. However, it is challenging to analyze large-scale imaging data in real time, preventing closed-loop investigation of neural circuitry. Here we develop a real-time analysis system with a field programmable gate array-graphics processing unit design for an up to 500-megabyte-per-second image stream. Adapted to whole-brain imaging of awake larval zebrafish, the system timely extracts activity from up to 100,000 neurons and enables closed-loop perturbations of neural dynamics.

Shining Light in Mechanobiology: Optical Tweezers, Scissors, and Beyond

Mechanobiology helps us to decipher cell and tissue functions by looking at changes in their mechanical properties that contribute to development, cell differentiation, physiology, and disease. Mechanobiology sits at the interface of biology, physics and engineering. One of the key technologies that enables characterization of properties of cells and tissue is microscopy. Combining microscopy with other quantitative measurement techniques such as optical tweezers and scissors, gives a very powerful tool for unraveling the intricacies of mechanobiology enabling measurement of forces, torques and displacements at play. We review the field of some light based studies of mechanobiology and optical detection of signal transduction ranging from optical micromanipulation-optical tweezers and scissors, advanced fluorescence techniques and optogenentics. In the current perspective paper, we concentrate our efforts on elucidating interesting measurements of forces, torques, positions, viscoelastic properties, and optogenetics inside and outside a cell attained when using structured light in combination with optical tweezers and scissors. We give perspective on the field concentrating on the use of structured light in imaging in combination with tweezers and scissors pointing out how novel developments in quantum imaging in combination with tweezers and scissors can bring to this fast growing field.

All-optical interrogation of brain-wide activity in freely swimming larval zebrafish

We introduce an all-optical technique that enables volumetric imaging of brain-wide calcium activity and targeted optogenetic stimulation of specific brain regions in unrestrained larval zebrafish. The system consists of three main components: a 3D tracking module, a dual-color fluorescence imaging module, and a real-time activity manipulation module. Our approach uses a sensitive genetically encoded calcium indicator in combination with a long Stokes shift red fluorescence protein as a reference channel, allowing the extraction of Ca2+ activity from signals contaminated by motion artifacts. The method also incorporates rapid 3D image reconstruction and registration, facilitating real-time selective optogenetic stimulation of different regions of the brain. By demonstrating that selective light activation of the midbrain regions in larval zebrafish could reliably trigger biased turning behavior and changes of brain-wide neural activity, we present a valuable tool for investigating the causal relationship between distributed neural circuit dynamics and naturalistic behavior.

Dynamical flexible inference of nonlinear latent factors and structures in neural population activity

Modelling the spatiotemporal dynamics in the activity of neural populations while also enabling their flexible inference is hindered by the complexity and noisiness of neural observations. Here we show that the lower-dimensional nonlinear latent factors and latent structures can be computationally modelled in a manner that allows for flexible inference causally, non-causally and in the presence of missing neural observations. To enable flexible inference, we developed a neural network that separates the model into jointly trained manifold and dynamic latent factors such that nonlinearity is captured through the manifold factors and the dynamics can be modelled in tractable linear form on this nonlinear manifold. We show that the model, which we named 'DFINE' (for 'dynamical flexible inference for nonlinear embeddings') achieves flexible inference in simulations of nonlinear dynamics and across neural datasets representing a diversity of brain regions and behaviours. Compared with earlier neural-network models, DFINE enables flexible inference, better predicts neural activity and behaviour, and better captures the latent neural manifold structure. DFINE may advance the development of neurotechnology and investigations in neuroscience.

Opto-electronic feedback control of membrane potential for real-time control of action potentials

To unlock new research possibilities by acquiring control of action potential (AP) morphologies in excitable cells, we developed an opto-electronic feedback loop-based system integrating cellular electrophysiology, real-time computing, and optogenetic approaches and applied it to monolayers of heart muscle cells. This allowed accurate restoration and preservation of cardiac AP morphologies in the presence of electrical perturbations of different origin in an unsupervised, self-regulatory manner, without any prior knowledge of the disturbance. Moreover, arbitrary AP waveforms could be enforced onto these cells. Collectively, these results set the stage for the refinement and application of opto-electronic control systems to enable in-depth investigation into the regulatory role of membrane potential in health and disease.

Cardiac optogenetics: shining light on signaling pathways

In the early 2000s, the field of neuroscience experienced a groundbreaking transformation with the advent of optogenetics. This innovative technique harnesses the properties of naturally occurring and genetically engineered rhodopsins to confer light sensitivity upon target cells. The remarkable spatiotemporal precision offered by optogenetics has provided researchers with unprecedented opportunities to dissect cellular physiology, leading to an entirely new level of investigation. Initially revolutionizing neuroscience, optogenetics quickly piqued the interest of the wider scientific community, and optogenetic applications were expanded to cardiovascular research. Over the past decade, researchers have employed various optical tools to observe, regulate, and steer the membrane potential of excitable cells in the heart. Despite these advancements, achieving control over specific signaling pathways within the heart has remained an elusive goal. Here, we review the optogenetic tools suitable to control cardiac signaling pathways with a focus on GPCR signaling, and delineate potential applications for studying these pathways, both in healthy and diseased hearts. By shedding light on these exciting developments, we hope to contribute to the ongoing progress in basic cardiac research to facilitate the discovery of novel therapeutic possibilities for treating cardiovascular pathologies.

Transcranial ultrasound stimulation at the peak-phase of theta-cycles in the hippocampus improve memory performance

The present study aimed to investigate the effectiveness of closed-loop transcranial ultrasound stimulation (closed-loop TUS) as a non-invasive, high temporal-spatial resolution method for modulating brain function to enhance memory. For this purpose, we applied closed-loop TUS to the CA1 region of the rat hippocampus for 7 consecutive days at different phases of theta cycles. Following the intervention, we evaluated memory performance through behavioral testing and recorded the neural activity. Our results indicated that closed-loop TUS applied at the peak phase of theta cycles significantly improves the memory performance in rats, as evidenced by behavioral testing. Furthermore, we observed that closed-loop TUS modifies the power and cross-frequency coupling strength of local field potentials (LFPs) during memory task, as well as modulates neuronal activity patterns and synaptic transmission, depending on phase of stimulation relative to theta rhythm. We demonstrated that closed-loop TUS can modulate neural activity and memory performance in a phase-dependent manner. Specifically, we observed that effectiveness of closed-loop TUS in regulating neural activity and memory is dependent on the timing of stimulation in relation to different theta phase. The findings implied that closed-loop TUS may have the capability to alter neural activity and memory performance in a phase-sensitive manner, and suggested that the efficacy of closed-loop TUS in modifying neural activity and memory was contingent on timing of stimulation with respect to the theta rhythm. Moreover, the improvement in memory performance after closed-loop TUS was found to be persistent.

FIOLA: an accelerated pipeline for fluorescence imaging online analysis

Optical microscopy methods such as calcium and voltage imaging enable fast activity readout of large neuronal populations using light. However, the lack of corresponding advances in online algorithms has slowed progress in retrieving information about neural activity during or shortly after an experiment. This gap not only prevents the execution of real-time closed-loop experiments, but also hampers fast experiment-analysis-theory turnover for high-throughput imaging modalities. Reliable extraction of neural activity from fluorescence imaging frames at speeds compatible with indicator dynamics and imaging modalities poses a challenge. We therefore developed FIOLA, a framework for fluorescence imaging online analysis that extracts neuronal activity from calcium and voltage imaging movies at speeds one order of magnitude faster than state-of-the-art methods. FIOLA exploits algorithms optimized for parallel processing on GPUs and CPUs. We demonstrate reliable and scalable performance of FIOLA on both simulated and real calcium and voltage imaging datasets. Finally, we present an online experimental scenario to provide guidance in setting FIOLA parameters and to highlight the trade-offs of our approach.

Optogenetics for controlling seizure circuits for translational approaches

The advent of optogenetic tools has had a profound impact on modern neuroscience research, revolutionizing our understanding of the brain. These tools offer a remarkable ability to precisely manipulate specific groups of neurons with an unprecedented level of temporal precision, on the order of milliseconds. This breakthrough has significantly advanced our knowledge of various physiological and pathophysiological processes in the brain. Within the realm of epilepsy research, optogenetic tools have played a crucial role in investigating the contributions of different neuronal populations to the generation of seizures and hyperexcitability. By selectively activating or inhibiting specific neurons using optogenetics, researchers have been able to elucidate the underlying mechanisms and identify key players involved in epileptic activity. Moreover, optogenetic techniques have also been explored as innovative therapeutic strategies for treating epilepsy. These strategies aim to halt seizure progression and alleviate symptoms by utilizing the precise control offered by optogenetics. The application of optogenetic tools has provided valuable insights into the intricate workings of the brain during epileptic episodes. For instance, researchers have discovered how distinct interneuron populations contribute to the initiation of seizures (ictogenesis). They have also revealed how remote circuits in regions such as the cerebellum, septum, or raphe nuclei can interact with hyperexcitable networks in the hippocampus. Additionally, studies have demonstrated the potential of closed-loop systems, where optogenetics is combined with real-time monitoring, to enable precise, on-demand control of seizure activity. Despite the immense promise demonstrated by optogenetic approaches, it is important to acknowledge that many of these techniques are still in the early stages of development and have yet to reach potential clinical applications. The transition from experimental research to practical clinical use poses numerous challenges. In this review, we aim to introduce optogenetic tools, provide a comprehensive survey of their application in epilepsy research, and critically discuss their current potential and limitations in achieving successful clinical implementation for the treatment of human epilepsy. By addressing these crucial aspects, we hope to foster a deeper understanding of the current state and future prospects of optogenetics in epilepsy treatment.

Theta-phase-specific modulation of dentate gyrus memory neurons

The theta rhythm, a quasi-periodic 4-10 Hz oscillation, is observed during memory processing in the hippocampus, with different phases of theta hypothesized to separate independent streams of information related to the encoding and recall of memories. At the cellular level, the discovery of hippocampal memory cells (engram neurons), as well as the modulation of memory recall through optogenetic activation of these cells, has provided evidence that certain memories are stored, in part, in a sparse ensemble of neurons in the hippocampus. In previous research, however, engram reactivation has been carried out using open-loop stimulation at fixed frequencies; the relationship between engram neuron reactivation and ongoing network oscillations has not been taken into consideration. To address this concern, we implemented a closed-loop reactivation of engram neurons that enabled phase-specific stimulation relative to theta oscillations in the local field potential in CA1. Using this real-time approach, we tested the impact of activating dentate gyrus engram neurons during the peak (encoding phase) and trough (recall phase) of theta oscillations. Consistent with previously hypothesized functions of theta oscillations in memory function, we show that stimulating dentate gyrus engram neurons at the trough of theta is more effective in eliciting behavioral recall than either fixed-frequency stimulation or stimulation at the peak of theta. Moreover, phase-specific trough stimulation is accompanied by an increase in the coupling between gamma and theta oscillations in CA1 hippocampus. Our results provide a causal link between phase-specific activation of engram cells and the behavioral expression of memory.

Behavioral optogenetics in nonhuman primates; a psychological perspective

Optogenetics has been a promising and developing technology in systems neuroscience throughout the past decade. It has been difficult though to reliably establish the potential behavioral effects of optogenetic perturbation of the neural activity in nonhuman primates. This poses a challenge on the future of optogenetics in humans as the concepts and technology need to be developed in nonhuman primates first. Here, I briefly summarize the viable approaches taken to improve nonhuman primate behavioral optogenetics, then focus on one approach: improvements in the measurement of behavior. I bring examples from visual behavior and show how the choice of method of measurement might conceal large behavioral effects. I will then discuss the "cortical perturbation detection" task in detail as an example of a sensitive task that can record the behavioral effects of optogenetic cortical stimulation with high fidelity. Finally, encouraged by the rich scientific landscape ahead of behavioral optogenetics, I invite technology developers to improve the chronically implantable devices designed for simultaneous neural recording and optogenetic intervention in nonhuman primates.

MicroLED/LED electro-optical integration techniques for non-display applications

MicroLEDs offer an extraordinary combination of high luminance, high energy efficiency, low cost, and long lifetime. These characteristics are highly desirable in various applications, but their usage has, to date, been primarily focused toward next-generation display technologies. Applications of microLEDs in other technologies, such as projector systems, computational imaging, communication systems, or neural stimulation, have been limited. In non-display applications which use microLEDs as light sources, modifications in key electrical and optical characteristics such as external efficiency, output beam shape, modulation bandwidth, light output power, and emission wavelengths are often needed for optimum performance. A number of advanced fabrication and processing techniques have been used to achieve these electro-optical characteristics in microLEDs. In this article, we review the non-display application areas of the microLEDs, the distinct opto-electrical characteristics required for these applications, and techniques that integrate the optical and electrical components on the microLEDs to improve system-level efficacy and performance.

MicroLED light source for optical sectioning structured illumination microscopy

Optical sectioning structured illumination microscopy (OS-SIM) provides optical sectioning capability in wide-field microscopy. The required illumination patterns have traditionally been generated using spatial light modulators (SLM), laser interference patterns, or digital micromirror devices (DMDs) which are too complex to implement in miniscope systems. MicroLEDs have emerged as an alternative light source for patterned illumination due to their extreme brightness capability and small emitter sizes. This paper presents a directly addressable striped microLED microdisplay with 100 rows on a flexible cable (70 cm long) for use as an OS-SIM light source in a benchtop setup. The overall design of the microdisplay is described in detail with luminance-current-voltage characterization. OS-SIM implementation with a benchtop setup shows the optical sectioning capability of the system by imaging within a 500 µm thick fixed brain slice from a transgenic mouse where oligodendrocytes are labeled with a green fluorescent protein (GFP). Results show improved contrast in reconstructed optically sectioned images of 86.92% (OS-SIM) compared with 44.31% (pseudo-widefield). MicroLED based OS-SIM therefore offers a new capability for deep tissue widefield imaging.

A prototype closed-loop brain-machine interface for the study and treatment of pain

Chronic pain is characterized by discrete pain episodes of unpredictable frequency and duration. This hinders the study of pain mechanisms and contributes to the use of pharmacological treatments associated with side effects, addiction and drug tolerance. Here, we show that a closed-loop brain-machine interface (BMI) can modulate sensory-affective experiences in real time in freely behaving rats by coupling neural codes for nociception directly with therapeutic cortical stimulation. The BMI decodes the onset of nociception via a state-space model on the basis of the analysis of online-sorted spikes recorded from the anterior cingulate cortex (which is critical for pain processing) and couples real-time pain detection with optogenetic activation of the prelimbic prefrontal cortex (which exerts top-down nociceptive regulation). In rats, the BMI effectively inhibited sensory and affective behaviours caused by acute mechanical or thermal pain, and by chronic inflammatory or neuropathic pain. The approach provides a blueprint for demand-based neuromodulation to treat sensory-affective disorders, and could be further leveraged for nociceptive control and to study pain mechanisms.

Closed-loop optogenetic control of the dynamics of neural activity in non-human primates

Electrical neurostimulation is effective in the treatment of neurological disorders, but associated recording artefacts generally limit its applications to open-loop stimuli. Real-time and continuous closed-loop control of brain activity can, however, be achieved by pairing concurrent electrical recordings and optogenetics. Here we show that closed-loop optogenetic stimulation with excitatory opsins enables the precise manipulation of neural dynamics in brain slices from transgenic mice and in anaesthetized non-human primates. The approach generates oscillations in quiescent tissue, enhances or suppresses endogenous patterns in active tissue and modulates seizure-like bursts elicited by the convulsant 4-aminopyridine. A nonlinear model of the phase-dependent effects of optical stimulation reproduced the modulation of cycles of local-field potentials associated with seizure oscillations, as evidenced by the systematic changes in the variability and entropy of the phase-space trajectories of seizures, which correlated with changes in their duration and intensity. We also show that closed-loop optogenetic neurostimulation could be delivered using intracortical optrodes incorporating light-emitting diodes. Closed-loop optogenetic approaches may be translatable to therapeutic applications in humans.

Alzheimer's disease as a synaptopathy: Evidence for dysfunction of synapses during disease progression

The synapse has consistently been considered a vulnerable and critical target within Alzheimer's disease, and synapse loss is, to date, one of the main biological correlates of cognitive decline within Alzheimer's disease. This occurs prior to neuronal loss with ample evidence that synaptic dysfunction precedes this, in support of the idea that synaptic failure is a crucial stage within disease pathogenesis. The two main pathological hallmarks of Alzheimer's disease, abnormal aggregates of amyloid or tau proteins, have had demonstrable effects on synaptic physiology in animal and cellular models of Alzheimer's disease. There is also growing evidence that these two proteins may have a synergistic effect on neurophysiological dysfunction. Here, we review some of the main findings of synaptic alterations in Alzheimer's disease, and what we know from Alzheimer's disease animal and cellular models. First, we briefly summarize some of the human evidence to suggest that synapses are altered, including how this relates to network activity. Subsequently, animal and cellular models of Alzheimer's disease are considered, highlighting mouse models of amyloid and tau pathology and the role these proteins may play in synaptic dysfunction, either in isolation or examining how the two pathologies may interact in dysfunction. This specifically focuses on neurophysiological function and dysfunction observed within these animal models, typically measured using electrophysiology or calcium imaging. Following synaptic dysfunction and loss, it would be impossible to imagine that this would not alter oscillatory activity within the brain. Therefore, this review also discusses how this may underpin some of the aberrant oscillatory patterns seen in animal models of Alzheimer's disease and human patients. Finally, an overview of some key directions and considerations in the field of synaptic dysfunction in Alzheimer's disease is covered. This includes current therapeutics that are targeted specifically at synaptic dysfunction, but also methods that modulate activity to rescue aberrant oscillatory patterns. Other important future avenues of note in this field include the role of non-neuronal cell types such as astrocytes and microglia, and mechanisms of dysfunction independent of amyloid and tau in Alzheimer's disease. The synapse will certainly continue to be an important target within Alzheimer's disease for the foreseeable future.

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

A hardware system for real-time decoding of in vivo calcium imaging data

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.

Phase-adaptive brain stimulation of striatal D1 medium spiny neurons in dopamine-depleted mice

Brain rhythms are strongly linked with behavior, and abnormal rhythms can signify pathophysiology. For instance, the basal ganglia exhibit a wide range of low-frequency oscillations during movement, but pathological "beta" rhythms at ~ 20 Hz have been observed in Parkinson's disease (PD) and in PD animal models. All brain rhythms have a frequency, which describes how often they oscillate, and a phase, which describes the precise time that peaks and troughs of brain rhythms occur. Although frequency has been extensively studied, the relevance of phase is unknown, in part because it is difficult to causally manipulate the instantaneous phase of ongoing brain rhythms. Here, we developed a phase-adaptive, real-time, closed-loop algorithm to deliver optogenetic stimulation at a specific phase with millisecond latency. We combined this Phase-Adaptive Brain STimulation (PABST) approach with cell-type-specific optogenetic methods to stimulate basal ganglia networks in dopamine-depleted mice that model motor aspects of human PD. We focused on striatal medium spiny neurons expressing D1-type dopamine receptors because these neurons can facilitate movement. We report three main results. First, we found that our approach delivered PABST within system latencies of 13 ms. Second, we report that closed-loop stimulation powerfully influenced the spike-field coherence of local brain rhythms within the dorsal striatum. Finally, we found that both 4 Hz PABST and 20 Hz PABST improved movement speed, but we found differences between phase only with 4 Hz PABST. These data provide causal evidence that phase is relevant for brain stimulation, which will allow for more precise, targeted, and individualized brain stimulation. Our findings are applicable to a broad range of preclinical brain stimulation approaches and could also inform circuit-specific neuromodulation treatments for human brain disease.

Optogenetics: Emerging strategies for neuropathic pain treatment

Neuropathic pain (NP) is a chronic health condition that presents a significant burden on patients, society, and even healthcare systems. However, in recent years, an emerging field in the treatment of neuropathic pain - optogenetic technology has dawned, heralding a new era in the field of medicine, and which has brought with it unlimited possibilities for studying the mechanism of NP and the treatment of research. Optogenetics is a new and growing field that uses the combination of light and molecular genetics for the first time ever. This rare combination is used to control the activity of living cells by expressing photosensitive proteins to visualize signaling events and manipulate cell activity. The treatments for NP are limited and have hardly achieved the desirable efficacy. NP differs from other types of pain, such as nociceptive pain, in that the treatments for NP are far more complex and highly challenging for clinical practice. This review presents the background of optogenetics, current applications in various fields, and the findings of optogenetics in NP. It also elaborates on the basic concepts of neuropathy, therapeutic applications, and the potential of optogenetics from the bench to the bedside in the near future.

GRINtrode: a neural implant for simultaneous two-photon imaging and extracellular electrophysiology in freely moving animals

Significance

In vivo imaging and electrophysiology are powerful tools to explore neuronal function that each offer unique complementary information with advantages and limitations. Capturing both data types from the same neural population in the freely moving animal would allow researchers to take advantage of the capabilities of both modalities and further understand how they relate to each other.

Aim

Here, we present a head-mounted neural implant suitable for in vivo two-photon imaging of neuronal activity with simultaneous extracellular electrical recording in head-fixed or fiber-coupled freely moving animals.

Approach

A gradient refractive index (GRIN) lens-based head-mounted neural implant with extracellular electrical recording provided by tetrodes on the periphery of the GRIN lens was chronically implanted. The design of the neural implant allows for recording from head-fixed animals, as well as freely moving animals by coupling the imaging system to a coherent imaging fiber bundle.

Results

We demonstrate simultaneous two-photon imaging of GCaMP and extracellular electrophysiology of neural activity in awake head-fixed and freely moving mice. Using the collected information, we perform correlation analysis to reveal positive correlation between optical and local field potential recordings.

Conclusion

Simultaneously recording neural activity using both optical and electrical methods provides complementary information from each modality. Designs that can provide such bi-modal recording in freely moving animals allow for the investigation of neural activity underlying a broader range of behavioral paradigms.

Driving singing behaviour in songbirds using a multi-modal, multi-agent virtual environment

Interactive biorobotics provides unique experimental potential to study the mechanisms underlying social communication but is limited by our ability to build expressive robots that exhibit the complex behaviours of birds and small mammals. An alternative to physical robots is to use virtual environments. Here, we designed and built a modular, audio-visual 2D virtual environment that allows multi-modal, multi-agent interaction to study mechanisms underlying social communication. The strength of the system is an implementation based on event processing that allows for complex computation. We tested this system in songbirds, which provide an exceptionally powerful and tractable model system to study social communication. We show that pair-bonded zebra finches (Taeniopygia guttata) communicating through the virtual environment exhibit normal call timing behaviour, males sing female directed song and both males and females display high-intensity courtship behaviours to their mates. These results suggest that the environment provided is sufficiently natural to elicit these behavioral responses. Furthermore, as an example of complex behavioral annotation, we developed a fully unsupervised song motif detector and used it to manipulate the virtual social environment of male zebra finches based on the number of motifs sung. Our virtual environment represents a first step in real-time automatic behaviour annotation and animal–computer interaction using higher level behaviours such as song. Our unsupervised acoustic analysis eliminates the need for annotated training data thus reducing labour investment and experimenter bias.

Nonlinear optimal control of a mean-field model of neural population dynamics

We apply the framework of nonlinear optimal control to a biophysically realistic neural mass model, which consists of two mutually coupled populations of deterministic excitatory and inhibitory neurons. External control signals are realized by time-dependent inputs to both populations. Optimality is defined by two alternative cost functions that trade the deviation of the controlled variable from its target value against the “strength” of the control, which is quantified by the integrated 1- and 2-norms of the control signal. We focus on a bistable region in state space where one low- (“down state”) and one high-activity (“up state”) stable fixed points coexist. With methods of nonlinear optimal control, we search for the most cost-efficient control function to switch between both activity states. For a broad range of parameters, we find that cost-efficient control strategies consist of a pulse of finite duration to push the state variables only minimally into the basin of attraction of the target state. This strategy only breaks down once we impose time constraints that force the system to switch on a time scale comparable to the duration of the control pulse. Penalizing control strength via the integrated 1-norm (2-norm) yields control inputs targeting one or both populations. However, whether control inputs to the excitatory or the inhibitory population dominate, depends on the location in state space relative to the bifurcation lines. Our study highlights the applicability of nonlinear optimal control to understand neuronal processing under constraints better.

Real-Time Image Processing Toolbox for All-Optical Closed-Loop Control of Neuronal Activities

The development of in vivo imaging and optogenetic tools makes it possible to control neural circuit activities in an all-optical, closed-loop manner, but such applications are limited by the lack of software for online analysis of neuronal imaging data. We developed an analysis software ORCA (Online Real-time activity and offline Cross-session Analysis), which performs image registration, neuron segmentation, and activity extraction at over 100 frames per second, fast enough to support real-time detection and readout of neural activity. Our active neuron detection algorithm is purely statistical, achieving a much higher speed than previous methods. We demonstrated closed-loop control of neurons that were identified on the fly, without prior recording or image processing. ORCA also includes a cross-session alignment module that efficiently tracks neurons across multiple sessions. In summary, ORCA is a powerful toolbox for fast imaging data analysis and provides a solution for all-optical closed-loop control of neuronal activity.

Connecting the dots between cell populations, whole-brain activity, and behavior

Simultaneously manipulating and monitoring both microscopic and macroscopic brain activity in vivo and identifying the linkage to behavior are powerful tools in neuroscience research. These capabilities have been realized with the recent technical advances of optogenetics and its combination with fMRI, here termed "opto-fMRI." Opto-fMRI allows for targeted brain region-, cell-type-, or projection-specific manipulation and targeted Ca 2 + activity measurement to be linked with global brain signaling and behavior. We cover the history, technical advances, applications, and important considerations of opto-fMRI in anesthetized and awake rodents and the future directions of the combined techniques in neuroscience and neuroimaging.

All-optical interrogation of neural circuits in behaving mice

Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such 'all-optical' techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3-6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3-5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.

Tapered fibertrodes for optoelectrical neural interfacing in small brain volumes with reduced artefacts

Deciphering the neural patterns underlying brain functions is essential to understanding how neurons are organized into networks. This deciphering has been greatly facilitated by optogenetics and its combination with optoelectronic devices to control neural activity with millisecond temporal resolution and cell type specificity. However, targeting small brain volumes causes photoelectric artefacts, in particular when light emission and recording sites are close to each other. We take advantage of the photonic properties of tapered fibres to develop integrated 'fibertrodes' able to optically activate small brain volumes with abated photoelectric noise. Electrodes are positioned very close to light emitting points by non-planar microfabrication, with angled light emission allowing the simultaneous optogenetic manipulation and electrical read-out of one to three neurons, with no photoelectric artefacts, in vivo. The unconventional implementation of two-photon polymerization on the curved taper edge enables the fabrication of recoding sites all around the implant, making fibertrodes a promising complement to planar microimplants.

Optogenetics: A new tool for cancer investigation and treatment

Despite the progress made in the diagnosis and treatment of cancer, it has remained the second cause of death in industrial countries. Cancer is a complex multifaceted disease with unique genomic and proteomic hallmarks. Optogenetics is a biological approach, in which the light-sensitive protein modules in combination with effector proteins that trigger reversibly fundamental cell functions without producing a long-term effect. The technology was first used to address some key issues in neurology. Later on, it was also used for other diseases such as cancer. In the case of cancer, there exist several signaling pathways with key proteins that are involved in the initiation and/or progression of cancer. Such aberrantly expressed proteins and the related signaling pathways need to be carefully investigated in terms of cancer diagnosis and treatment, which can be managed with optogenetic tools. Notably, optogenetics systems offer some advantages compared to the traditional methods, including spatial-temporal control of protein or gene expression, cost-effective and fewer off-target side effects, and reversibility potential. Such noticeable features make this technology a unique drug-free approach for diagnosis and treatment of cancer. It can be used to control tumor cells, which is a favorable technique to investigate the heterogeneous and complex features of cancerous cells. Remarkably, optogenetics approaches can provide us with outstanding tool to extend our understanding of how cells perceive, respond, and behave in meeting with complex signals, particularly in terms of cancer evasion from the anticancer immune system functions.

Closed-loop stimulation using a multiregion brain-machine interface has analgesic effects in rodents

Effective treatments for chronic pain remain limited. Conceptually, a closed-loop neural interface combining sensory signal detection with therapeutic delivery could produce timely and effective pain relief. Such systems are challenging to develop because of difficulties in accurate pain detection and ultrafast analgesic delivery. Pain has sensory and affective components, encoded in large part by neural activities in the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC), respectively. Meanwhile, studies show that stimulation of the prefrontal cortex (PFC) produces descending pain control. Here, we designed and tested a brain-machine interface (BMI) combining an automated pain detection arm, based on simultaneously recorded local field potential (LFP) signals from the S1 and ACC, with a treatment arm, based on optogenetic activation or electrical deep brain stimulation (DBS) of the PFC in freely behaving rats. Our multiregion neural interface accurately detected and treated acute evoked pain and chronic pain. This neural interface is activated rapidly, and its efficacy remained stable over time. Given the clinical feasibility of LFP recordings and DBS, our findings suggest that BMI is a promising approach for pain treatment.

Platforms for Optogenetic Stimulation and Feedback Control

Harnessing the potential of optogenetics in biology requires methodologies from different disciplines ranging from biology, to mechatronics engineering, to control engineering. Light stimulation of a synthetic optogenetic construct in a given biological species can only be achieved via a suitable light stimulation platform. Emerging optogenetic applications entail a consistent, reproducible, and regulated delivery of light adapted to the application requirement. In this review, we explore the evolution of light-induction hardware-software platforms from simple illumination set-ups to sophisticated microscopy, microtiter plate and bioreactor designs, and discuss their respective advantages and disadvantages. Here, we examine design approaches followed in performing optogenetic experiments spanning different cell types and culture volumes, with induction capabilities ranging from single cell stimulation to entire cell culture illumination. The development of automated measurement and stimulation schemes on these platforms has enabled researchers to implement various in silico feedback control strategies to achieve computer-controlled living systems—a theme we briefly discuss in the last part of this review.

Implantable Micro-Light-Emitting Diode (µLED)-based optogenetic interfaces toward human applications

Optogenetics has received wide attention in biomedical fields because of itsadvantages in temporal precision and spatial resolution. Beyond contributions to important advances in fundamental research, optogenetics is inspiring a shift towards new methods of improving human well-being and treating diseases. Soft, flexible and biocompatible systems using µLEDs as a light source have been introduced to realize brain-compatible optogenetic implants, but there are still many technical challenges to overcome before their human applications. In this review, we address progress in the development of implantable µLED probes and recent achievements in (i) device engineering design, (ii) driving power, (iii) multifunctionality and (iv) closed-loop systems. (v) Expanded optogenetic applications based on remarkable advances in µLED implants will also be discussed.

Electro-optical mechanically flexible coaxial microprobes for minimally invasive interfacing with intrinsic neural circuits

Central to advancing our understanding of neural circuits is developing minimally invasive, multi-modal interfaces capable of simultaneously recording and modulating neural activity. Recent devices have focused on matching the mechanical compliance of tissue to reduce inflammatory responses. However, reductions in the size of multi-modal interfaces are needed to further improve biocompatibility and long-term recording capabilities. Here a multi-modal coaxial microprobe design with a minimally invasive footprint (8-14 µm diameter over millimeter lengths) that enables efficient electrical and optical interrogation of neural networks is presented. In the brain, the probes allowed robust electrical measurement and optogenetic stimulation. Scalable fabrication strategies can be used with various electrical and optical materials, making the probes highly customizable to experimental requirements, including length, diameter, and mechanical properties. Given their negligible inflammatory response, these probes promise to enable a new generation of readily tunable multi-modal devices for long-term, minimally invasive interfacing with neural circuits.

Discovering sparse control strategies in neural activity

Biological circuits such as neural or gene regulation networks use internal states to map sensory input to an adaptive repertoire of behavior. Characterizing this mapping is a major challenge for systems biology. Though experiments that probe internal states are developing rapidly, organismal complexity presents a fundamental obstacle given the many possible ways internal states could map to behavior. Using C. elegans as an example, we propose a protocol for systematic perturbation of neural states that limits experimental complexity and could eventually help characterize collective aspects of the neural-behavioral map. We consider experimentally motivated small perturbations—ones that are most likely to preserve natural dynamics and are closer to internal control mechanisms—to neural states and their impact on collective neural activity. Then, we connect such perturbations to the local information geometry of collective statistics, which can be fully characterized using pairwise perturbations. Applying the protocol to a minimal model of C. elegans neural activity, we find that collective neural statistics are most sensitive to a few principal perturbative modes. Dominant eigenvalues decay initially as a power law, unveiling a hierarchy that arises from variation in individual neural activity and pairwise interactions. Highest-ranking modes tend to be dominated by a few, “pivotal” neurons that account for most of the system’s sensitivity, suggesting a sparse mechanism of collective control.

Retinitis Pigmentosa: Progress in Molecular Pathology and Biotherapeutical Strategies

Retinitis pigmentosa (RP) is genetically heterogeneous retinopathy caused by photoreceptor cell death and retinal pigment epithelial atrophy that eventually results in blindness in bilateral eyes. Various photoreceptor cell death types and pathological phenotypic changes that have been disclosed in RP demand in-depth research of its pathogenic mechanism that may account for inter-patient heterogeneous responses to mainstream drug treatment. As the primary method for studying the genetic characteristics of RP, molecular biology has been widely used in disease diagnosis and clinical trials. Current technology iterations, such as gene therapy, stem cell therapy, and optogenetics, are advancing towards precise diagnosis and clinical applications. Specifically, technologies, such as effective delivery vectors, CRISPR/Cas9 technology, and iPSC-based cell transplantation, hasten the pace of personalized precision medicine in RP. The combination of conventional therapy and state-of-the-art medication is promising in revolutionizing RP treatment strategies. This article provides an overview of the latest research on the pathogenesis, diagnosis, and treatment of retinitis pigmentosa, aiming for a convenient reference of what has been achieved so far.

The future perspectives of psychiatric neurosurgery

The future of psychiatric neurosurgery can be viewed from two separate perspectives: the immediate future and the distant future. Both show promise, but the treatment strategy for mental diseases and the technology utilized during these separate periods will likely differ dramatically. It can be expected that the initial advancements will be built upon progress of neuroimaging and stereotactic targeting while surgical technology becomes adapted to patient-specific symptomatology and structural/functional imaging parameters. This individualized approach has already begun to show significant promise when applied to deep brain stimulation for treatment-resistant depression and obsessive-compulsive disorder. If effectiveness of these strategies is confirmed by well designed, double-blind, placebo-controlled clinical studies, further technological advances will continue into the distant future, and will likely involve precise neuromodulation at the cellular level, perhaps using wireless technology with or without closed-loop design. This approach, being theoretically less invasive and carrying less risk, may ultimately propel psychiatric neurosurgery to the forefront in the treatment algorithm of mental illness. Despite prominent development of non-invasive therapeutic options, such as stereotactic radiosurgery or transcranial magnetic resonance-guided focused ultrasound, chances are there will still be a need in surgical management of patients with most intractable psychiatric conditions.

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally intensive and time-consuming, making online frame-by-frame analysis challenging. This is especially true for large field-of-view (FOV) imaging. Here, we present CITE-On (Cell Identification and Trace Extraction Online), a convolutional neural network-based algorithm for fast automatic cell identification, segmentation, identity tracking, and trace extraction in two-photon calcium imaging data. CITE-On processes thousands of cells online, including during mesoscopic two-photon imaging, and extracts functional measurements from most neurons in the FOV. Applied to publicly available datasets, the offline version of CITE-On achieves performance similar to that of state-of-the-art methods for offline analysis. Moreover, CITE-On generalizes across calcium indicators, brain regions, and acquisition parameters in anesthetized and awake head-fixed mice. CITE-On represents a powerful tool to speed up image analysis and facilitate closed-loop approaches, for example in combined all-optical imaging and manipulation experiments.

Neuromodulation of cognition in Parkinson's disease

Neuromodulation is a widely used treatment for motor symptoms of Parkinson's disease (PD). It can be a highly effective treatment as a result of knowledge of circuit dysfunction associated with motor symptoms in PD. However, the mechanisms underlying cognitive symptoms of PD are less well-known, and the effects of neuromodulation on these symptoms are less consistent. Nonetheless, neuromodulation provides a unique opportunity to modulate motor and cognitive circuits while minimizing off-target side effects. We review the modalities of neuromodulation used in PD and the potential implications for cognitive symptoms. There have been some encouraging findings with both invasive and noninvasive modalities of neuromodulation, and there are promising advances being made in the field of therapeutic neuromodulation. Substantial work is needed to determine which modulation targets are most effective for the different types of cognitive deficits of PD.

Breaking Down a Rhythm: Dissecting the Mechanisms Underlying Task-Related Neural Oscillations

A century worth of research has linked multiple cognitive, perceptual and behavioral states to various brain oscillations. However, the mechanistic roles and circuit underpinnings of these oscillations remain an area of active study. In this review, we argue that the advent of optogenetic and related systems neuroscience techniques has shifted the field from correlational to causal observations regarding the role of oscillations in brain function. As a result, studying brain rhythms associated with behavior can provide insight at different levels, such as decoding task-relevant information, mapping relevant circuits or determining key proteins involved in rhythmicity. We summarize recent advances in this field, highlighting the methods that are being used for this purpose, and discussing their relative strengths and limitations. We conclude with promising future approaches that will help unravel the functional role of brain rhythms in orchestrating the repertoire of complex behavior.

Multimodal neural probes for combined optogenetics and electrophysiology

To understand how brain functions arise from interconnected neural networks, it is necessary to develop tools that can allow simultaneous manipulation and recording of neural activities. Multimodal neural probes, especially those that combine optogenetics with electrophysiology, provide a powerful tool for the dissection of neural circuit functions and understanding of brain diseases. In this review, we provide an overview of recent developments in multimodal neural probes. We will focus on materials and integration strategies of multimodal neural probes to achieve combined optogenetic stimulation and electrical recordings with high spatiotemporal precision and low invasiveness. In addition, we will also discuss future opportunities of multimodal neural interfaces in basic and translational neuroscience.

A high-throughput method to deliver targeted optogenetic stimulation to moving C. elegans populations

We present a high-throughput optogenetic illumination system capable of simultaneous closed-loop light delivery to specified targets in populations of moving Caenorhabditis elegans. The instrument addresses three technical challenges: It delivers targeted illumination to specified regions of the animal's body such as its head or tail; it automatically delivers stimuli triggered upon the animal's behavior; and it achieves high throughput by targeting many animals simultaneously. The instrument was used to optogenetically probe the animal's behavioral response to competing mechanosensory stimuli in the the anterior and posterior gentle touch receptor neurons. Responses to more than 43,418 stimulus events from a range of anterior-posterior intensity combinations were measured. The animal's probability of sprinting forward in response to a mechanosensory stimulus depended on both the anterior and posterior stimulation intensity, while the probability of reversing depended primarily on the anterior stimulation intensity. We also probed the animal's response to mechanosensory stimulation during the onset of turning, a relatively rare behavioral event, by delivering stimuli automatically when the animal began to turn. Using this closed-loop approach, over 9,700 stimulus events were delivered during turning onset at a rate of 9.2 events per worm hour, a greater than 25-fold increase in throughput compared to previous investigations. These measurements validate with greater statistical power previous findings that turning acts to gate mechanosensory evoked reversals. Compared to previous approaches, the current system offers targeted optogenetic stimulation to specific body regions or behaviors with many fold increases in throughput to better constrain quantitative models of sensorimotor processing.