EthoLoop: automated closed-loop neuroethology in naturalistic environments.

Accurate tracking and analysis of animal behavior is crucial for modern systems neuroscience. However, following freely moving animals in naturalistic, three-dimensional (3D) or nocturnal environments remains a major challenge. Here, we present EthoLoop, a framework for studying the neuroethology of freely roaming animals. Combining real-time optical tracking and behavioral analysis with remote-controlled stimulus-reward boxes, this system allows direct interactions with animals in their habitat. EthoLoop continuously provides close-up views of the tracked individuals and thus allows high-resolution behavioral analysis using deep-learning methods. The behaviors detected on the fly can be automatically reinforced either by classical conditioning or by optogenetic stimulation via wirelessly controlled portable devices. Finally, by combining 3D tracking with wireless neurophysiology we demonstrate the existence of place-cell-like activity in the hippocampus of freely moving primates. Taken together, we show that the EthoLoop framework enables interactive, well-controlled and reproducible neuroethological studies in large-field naturalistic settings.

Microribbons composed of directionally self-assembled nanoflakes as highly stretchable ionic neural electrodes.

Many natural materials possess built-in structural variation, endowing them with superior performance. However, it is challenging to realize programmable structural variation in self-assembled synthetic materials since self-assembly processes usually generate uniform and ordered structures. Here, we report the formation of asymmetric microribbons composed of directionally self-assembled two-dimensional nanoflakes in a polymeric matrix during three-dimensional direct-ink printing. The printed ribbons with embedded structural variations show site-specific variance in their mechanical properties. Remarkably, the ribbons can spontaneously transform into ultrastretchable springs with controllable helical architecture upon stimulation. Such springs also exhibit superior nanoscale transport behavior as nanofluidic ionic conductors under even ultralarge tensile strains (>1,000%). Furthermore, to show possible real-world uses of such materials, we demonstrate in vivo neural recording and stimulation using such springs in a bullfrog animal model. Thus, such springs can be used as neural electrodes compatible with soft and dynamic biological tissues.

Measuring fingerpad deformation during active object manipulation.

During active object manipulation, the finger-object interactions give rise to complex fingertip skin deformations. These deformations are in turn encoded by the local tactile afferents and provide rich and behaviorally relevant information to the central nervous system. Most of the work studying the mechanical response of the finger to dynamic loading has been performed under a passive setup, thereby precisely controlling the kinematics or the dynamics of the loading. However, to identify aspects of the deformations that are relevant to online control during object manipulation, it is desirable to measure the skin response in an active setup. To that end, we developed a device that allows us to monitor finger forces, skin deformations, and kinematics during fine manipulation. We describe the device in detail and test it to precisely describe how the fingertip skin in contact with the object deforms during a simple vertical oscillation task. We show that the level of grip force directly influences the fingerpad skin strains and that the strain rates are substantial during active manipulation (norm up to 100%/s). The developed setup will enable us to causally relate sensory information, i.e. skin deformation, to online control, i.e. grip force adjustment, in future studies.NEW & NOTEWORTHY We present a novel device, a manipulandum, that enables to image the contact between the finger and the contact surface during active manipulation of the device. The device is tested in a simple vertical oscillation task involving 18 participants. We demonstrate that substantial surface skin strains take place at the finger-object interface and argue that those deformations provide essential information for grasp stability during object manipulation.

Cellular-scale silicon probes for high-density, precisely localized neurophysiology.

Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared with the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at a cellular scale (5 × 10 µm cross section), with ultra-high-density packing (as little as 66 µm between shanks) and 64 or 256 closely spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and record large spikes in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal µ-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits and potentially for human brain-machine interfaces.NEW & NOTEWORTHY Devices with many electrodes penetrating into the brain are an important tool for investigating neural information processing, but they are typically large compared with neurons. This results in substantial damage and makes it harder to reconstruct recording locations within brain circuits. This paper presents high-channel-count silicon probes with much smaller features and a method for slicing through probe, brain, and skull all together. This allows probe tips to be directly observed relative to immunohistochemical markers.

A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents.

Tracking head position and orientation in small mammals is crucial for many applications in the field of behavioral neurophysiology, from the study of spatial navigation to the investigation of active sensing and perceptual representations. Many approaches to head tracking exist, but most of them only estimate the 2D coordinates of the head over the plane where the animal navigates. Full reconstruction of the pose of the head in 3D is much more more challenging and has been achieved only in handful of studies, which employed headsets made of multiple LEDs or inertial units. However, these assemblies are rather bulky and need to be powered to operate, which prevents their application in wireless experiments and in the small enclosures often used in perceptual studies. Here we propose an alternative approach, based on passively imaging a lightweight, compact, 3D structure, painted with a pattern of black dots over a white background. By applying a cascade of feature extraction algorithms that progressively refine the detection of the dots and reconstruct their geometry, we developed a tracking method that is highly precise and accurate, as assessed through a battery of validation measurements. We show that this method can be used to study how a rat samples sensory stimuli during a perceptual discrimination task and how a hippocampal place cell represents head position over extremely small spatial scales. Given its minimal encumbrance and wireless nature, our method could be ideal for high-throughput applications, where tens of animals need to be simultaneously and continuously tracked.NEW & NOTEWORTHY Head tracking is crucial in many behavioral neurophysiology studies. Yet reconstruction of the head's pose in 3D is challenging and typically requires implanting bulky, electrically powered headsets that prevent wireless experiments and are hard to employ in operant boxes. Here we propose an alternative approach, based on passively imaging a compact, 3D dot pattern that, once implanted over the head of a rodent, allows estimating the pose of its head with high precision and accuracy.

Characterization of in vitro neural functional connectivity on a neurofluidic device.

Understanding the mechanism of functional connectivity in neural system is of great benefit to lot of researches and applications. Microfluidics and microelectrode arrays (MEAs) have been frequently utilized for in vitro neural cultures study. However, there are few studies on the functional connectivity of neural cultures grown on a microfluidic chip. It is intriguing to unveil the influences of microfluidic structures on in vitro neuronal networks from the perspective of functional connectivity. Hence, in the present study, a device was established, which comprised a microfluidic chamber for cell growth and a MEA substrate for recording the electrophysiological response of the neuronal networks. The network topology, neural firing rate, neural bursting rate and network burst frequency were adopted as representative characteristics for neuronal networks analysis. Functional connectivity was estimated by means of cross-covariance analysis and graph theory. The results demonstrated that the functional connectivity of the in vitro neuronal networks formed in the microchannel has been apparently reinforced, corresponding to improve neuronal network density and increased small-worldness.

Fifty years of microneurography: learning the language of the peripheral sympathetic nervous system in humans.

As a primary component of homeostasis, the sympathetic nervous system enables rapid adjustments to stress through its ability to communicate messages among organs and cause targeted and graded end organ responses. Key in this communication model is the pattern of neural signals emanating from the central to peripheral components of the sympathetic nervous system. But what is the communication strategy employed in peripheral sympathetic nerve activity (SNA)? Can we develop and interpret the system of coding in SNA that improves our understanding of the neural control of the circulation? In 1968, Hagbarth and Vallbo (Hagbarth KE, Vallbo AB. Acta Physiol Scand 74: 96-108, 1968) reported the first use of microneurographic methods to record sympathetic discharges in peripheral nerves of conscious humans, allowing quantification of SNA at rest and sympathetic responsiveness to physiological stressors in health and disease. This technique also has enabled a growing investigation into the coding patterns within, and cardiovascular outcomes associated with, postganglionic SNA. This review outlines how results obtained by microneurographic means have improved our understanding of SNA outflow patterns at the action potential level, focusing on SNA directed toward skeletal muscle in conscious humans.

Improved methods for acrylic-free implants in nonhuman primates for neuroscience research.

Traditionally, head fixation devices and recording cylinders have been implanted in nonhuman primates (NHP) using dental acrylic despite several shortcomings associated with acrylic. The use of more biocompatible materials such as titanium and PEEK is becoming more prevalent in NHP research. We describe a cost-effective set of procedures that maximizes the integration of headposts and recording cylinders with the animal's tissues while reducing surgery time. Nine rhesus monkeys were implanted with titanium headposts, and one of these was also implanted with a recording chamber. In each case, a three-dimensional printed replica of the skull was created based on computerized tomography scans. The titanium feet of the headposts were shaped, and the skull thickness was measured preoperatively, reducing surgery time by up to 70%. The recording cylinder was manufactured to conform tightly to the skull, which was fastened to the skull with four screws and remained watertight for 8.5 mo. We quantified the amount of regression of the skin edge at the headpost. We found a large degree of variability in the timing and extent of skin regression that could not be explained by any single recorded factor. However, there was not a single case of bone exposure; although skin retracted from the titanium, skin also remained adhered to the skull adjacent to those regions. The headposts remained fully functional and free of complications for the experimental life of each animal, several of which are still participating in experiments more than 4 yr after implant.NEW & NOTEWORTHY Cranial implants are often necessary for performing neurophysiology research with nonhuman primates. We present methods for using three-dimensional printed monkey skulls to form and fabricate acrylic-free implants preoperatively to decrease surgery times and the risk of complications and increase the functional life of the implant. We focused on reducing costs, creating a feasible timeline, and ensuring compatibility with existing laboratory systems. We discuss the importance of using more biocompatible materials and enhancing osseointegration.

Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys.

Advances in techniques for recording large-scale brain activity contribute to both the elucidation of neurophysiological principles and the development of brain-machine interfaces (BMIs). Here we describe a neurophysiological paradigm for performing tethered and wireless large-scale recordings based on movable volumetric three-dimensional (3D) multielectrode implants. This approach allowed us to isolate up to 1,800 neurons (units) per animal and simultaneously record the extracellular activity of close to 500 cortical neurons, distributed across multiple cortical areas, in freely behaving rhesus monkeys. The method is expandable, in principle, to thousands of simultaneously recorded channels. It also allows increased recording longevity (5 consecutive years) and recording of a broad range of behaviors, such as social interactions, and BMI paradigms in freely moving primates. We propose that wireless large-scale recordings could have a profound impact on basic primate neurophysiology research while providing a framework for the development and testing of clinically relevant neuroprostheses.

Neurorehabilitation in upper limb amputation: understanding how neurophysiological changes can affect functional rehabilitation.

BACKGROUND: Significant advances have been made in developing new prosthetic technologies with the goal of restoring function to persons that suffer partial or complete loss of the upper limb. Despite these technological advances, many challenges remain in understanding barriers in patient adoption of technology, and what critical factors should be of focus in prosthetics development from a motor control perspective. This points to a potential opportunity to improve our understanding of amputation using neurophysiology and plasticity, and integrate this knowledge into the development of prosthetics technology in novel ways. Here, argument will be made to include a stronger focus on the neural and behavioral changes that result from amputation, and a better appreciation of the time-scale of changes which may significantly affect device adaptation, functional device utility, and motor learning implemented in rehabilitation environments. CONCLUSION: By strengthening our understanding of the neuroscience of amputation, we may improve the ability to couple neurorehabilitation with neuroengineering to support clinician needs in yielding improved outcomes in patients.

Neurophysiological techniques in the study of the excitability, connectivity, and plasticity of the human brain.

There is increasing evidence to support the concept that brain plasticity involves distinct functional and structural components, each requiring several cellular mechanisms operating at different time scales, synaptic loci, and developmental phases within an extremely complex framework. However, the precise relationship between functional and structural components of brain plasticity/connectivity phenomena is still unclear and its explanation represents a major challenge within modern neuroscience. The key feature of neurophysiological techniques described in this review paper is their pivotal role in tracking temporal dynamics and inner hierarchies of brain functional and effective connectivities, possibly clarifying some crucial issues underlying brain plasticity. Taken together, the findings presented in this review open an intriguing new field in neuroscience investigation and are important for the adoption of neurophysiological techniques as a tool for basic research and, in future, even for clinical diagnostics purposes.

Invasive Computational Psychiatry.

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.

In vivo measurement of hindlimb neuromuscular function in mice.

INTRODUCTION: In vitro or in situ methods to assess neuromuscular performance in rodents are invasive and inadequate to fully assess large hindlimb muscles. METHODS: An in vivo hindlimb exertion force test (HEFT) was developed to quantify muscle function peak force (PF), peak rate of force development (PRFD), and short- and long-latency reaction times (SLRT and LLRT, respectively) in C57BL/6J mice. RESULTS: PF did not change with one- and three-times-per-week repeated HEFT trials, demonstrating assessment reproducibility. However, PRFD decreased with trial, indicating that mice modified response behavior while achieving the same PF. Separately, mice were subjected to 14 days of hindlimb suspension (HS) to induce muscle atrophy. Concomitant with decreased lean carcass and individual muscle masses, HS mice showed reduced PF and LLRT. CONCLUSIONS: The results demonstrate that HEFT is an effective tool for evaluating in vivo hindlimb neuromuscular performance due to disuse muscle atrophy and potentially for other disease and injury models.

Arduino: a low-cost multipurpose lab equipment.

Typical experiments in psychological and neurophysiological settings often require the accurate control of multiple input and output signals. These signals are often generated or recorded via computer software and/or external dedicated hardware. Dedicated hardware is usually very expensive and requires additional software to control its behavior. In the present article, I present some accuracy tests on a low-cost and open-source I/O board (Arduino family) that may be useful in many lab environments. One of the strengths of Arduinos is the possibility they afford to load the experimental script on the board's memory and let it run without interfacing with computers or external software, thus granting complete independence, portability, and accuracy. Furthermore, a large community has arisen around the Arduino idea and offers many hardware add-ons and hundreds of free scripts for different projects. Accuracy tests show that Arduino boards may be an inexpensive tool for many psychological and neurophysiological labs.

Identification of directed interactions in networks.

Multichannel data collection in the neurosciences is routine and has necessitated the development of methods to identify the direction of interactions among processes. The most widely used approach for detecting these interactions in such data is based on autoregressive models of stochastic processes, although some work has raised the possibility of serious difficulties with this approach. This article demonstrates that these difficulties are present and that they are intrinsic features of the autoregressive method. Here, we introduce a new method taking into account unobserved processes and based on coherence. Two examples of three-process networks are used to demonstrate that although coherence measures are intrinsically non-directional, a particular network configuration will be associated with a particular set of coherences. These coherences may not specify the network uniquely, but in principle will specify all network configurations consistent with their values and will also specify the relationships among the unobserved processes. Moreover, when new information becomes available, the values of the measures of association already in place do not change, but the relationships among the unobserved processes may become further resolved.

Measurement of axonal excitability: Consensus guidelines.

Measurement of axonal excitability provides an in vivo indication of the properties of the nerve membrane and of the ion channels expressed on these axons. Axonal excitability techniques have been utilised to investigate the pathophysiological mechanisms underlying neurological diseases. This document presents guidelines derived for such studies, based on a consensus of international experts, and highlights the potential difficulties when interpreting abnormalities in diseased axons. The present manuscript provides a state-of-the-art review of the findings of axonal excitability studies and their interpretation, in addition to suggesting guidelines for the optimal performance of excitability studies.

Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals.

BACKGROUND: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity - especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. RESULTS: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. CONCLUSION: The tool is publicly available as a freeware at the address: http://www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html.

Extracellular recordings from locally dense microelectrode arrays coupled to dissociated cortical cultures.

High-density microelectrode arrays (MEAs) enabled by recent developments of microelectronic circuits (CMOS-MEA) and providing spatial resolutions down to the cellular level open the perspective to access simultaneously local and overall neuronal network activities expressed by in vitro preparations. The short inter-electrode separation results in a gain of information on the micro-circuit neuronal dynamics and signal propagation, but requires the careful evaluation of the time resolution as well as the assessment of possible cross-talk artifacts. In this respect, we have realized and tested Pt high-density (HD)-MEAs featuring four local areas with 10microm inter-electrode spacing and providing a suitable noise level for the assessment of the high-density approach. First, simulated results show how possible artifacts (duplicated spikes) can be theoretically observed on nearby microelectrodes only for very high-shunt resistance values (e.g. R(sh)=50 kOmega generates up to 60% of false positives). This limiting condition is not compatible with typical experimental conditions (i.e. dense but not confluent cultures). Experiments performed on spontaneously active cortical neuronal networks show that spike synchronicity decreases by increasing the time resolution and analysis results show that the detected synchronous spikes on nearby electrodes are likely to be unresolved (in time) fast local propagations. Finally, functional connectivity analysis results show stronger local connections than long connections spread homogeneously over the whole network demonstrating the expected gain in detail provided by the spatial resolution.

Optimal spectral tracking--with application to speed dependent neural modulation of tibialis anterior during human treadmill walking.

A novel method of optimal spectral tracking is presented which permits the characterisation of trial-varying parameters. Many experimental studies suffer from the limitations of available analysis methodologies, which often impose a condition of stationarity. This severely limits our ability to track slow varying or dynamic responses with any statistical certainty. Presented is a complete framework for the non-stationary analysis of trial-varying data. Theory is introduced and developed in the characterisation of speed dependent neural modulation of the locomotor drive to tibialis anterior (TA) during healthy treadmill locomotion. The approach adopts adaptive filter theory while retaining a spectral focus, thus remaining compatible with much of the current literature. Spectral tracking procedures are evaluated using both surrogate and neurophysiological time-series. Confidence intervals are derived in both empiric and numerical form. Analysis of the pre-synaptic drive to TA under the modulation of treadmill belt speed follows, with results demonstrating clear speed dependent influences on the spectral content of TA, suggesting dynamic neural modulation of the locomotor drive. Findings include speed-modulated components at 7-12Hz (early swing) and 15-20Hz (pre-stance). Speed invariant components were identified at 8-15 and 15-20Hz during early and late swing, in agreement with previous studies. Modification to the method permits a sub-optimal alternative, encouraging the exploration of short epoched data.