Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits.

Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle. Here we address the sparse neuronal firing and develop a model to replicate the behavior of individual neurons within rhythm-generating populations to increase biological plausibility and facilitate new insights into the underlying mechanisms of rhythm generation. The developed network architecture is able to produce sparse firing of individual neurons, creating a novel implementation for exploring the contribution of network architecture on rhythmic output. Furthermore, the introduction of sparse firing of individual neurons within the rhythm-generating circuits is one of the factors that allows for a broad neuronal phase representation of firing at the population level. This moves the model toward recent experimental findings of evenly distributed neuronal firing across phases among individual spinal neurons. The network is tested by methodically iterating select parameters to gain an understanding of how connectivity and the interplay of excitation and inhibition influence the output. This knowledge can be applied in future studies to implement a biologically plausible rhythm-generating circuit for testing biological hypotheses.

In vivo brain temperature mapping using polymer optical fiber Bragg grating sensors.

Variation of the brain temperature is strongly affected by blood flow, oxygen supply, and neural cell metabolism. Localized monitoring of the brain temperature is one of the most effective ways to correlate brain functions and diseases such as stroke, epilepsy, and mood disorders. While polymer optical fibers (POFs) are considered ideal candidates for temperature sensing in the brain, they have never been used so far in vivo. Here, we developed for the first, to the best of our knowledge, time an implantable probe based on a microstructured polymer optical fiber Bragg grating (FBG) sensor for intracranial brain temperature mapping. The temperature at different depths of the brain (starting from the cerebral cortex) and the correlation between the brain and body core temperature of a rat were recorded with a sensitivity of 33 pm/°C and accuracy <0.2°C. Our in vivo experimental results suggest that the proposed device can achieve real-time and high-resolution local temperature measurement in the brain, as well as being integrated with existing neural interfaces.

Neural Decoding for Intracortical Brain-Computer Interfaces.

Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.

Optoelectronic and mechanical properties of microstructured polymer optical fiber neural probes.

Multifunctional optical fiber-based neural interfaces have attracted significant attention for neural stimulation, recording, and photopharmacology towards understanding the central nervous system. In this work, we demonstrate the fabrication, optoelectrical characterization, and mechanical analysis of four types of microstructured polymer optical fiber neural probes using different soft thermoplastic polymers. The developed devices have integrated metallic elements for electrophysiology and microfluidic channels for localized drug delivery, and can be used for optogenetics in the visible spectrum at wavelengths spanning from 450 nm up to 800 nm. Their impedance, measured by electrochemical impedance spectroscopy, was found to be as low as 21 kΩ and 4.7 kΩ at 1kHz when indium and tungsten wires are used as the integrated electrodes, respectively. Uniform on-demand drug delivery can be achieved by the microfluidic channels with a measured delivery rate from 10 up to 1000 nL/min. In addition, we identified the buckling failure threshold (defined as the conditions for successful implantation) as well as the bending stiffness of the fabricated fibers. Using finite element analysis, we calculated the main critical mechanical properties of the developed probes to avoid buckling during implantation and maintain high flexibility of the probe within the tissue. Our results aim to demonstrate the impact of design, fabrication, and characteristics of the materials on the development of polymer fibers as next-generation implants and neural interfaces.

Soft monolithic infrared neural interface for simultaneous neurostimulation and electrophysiology.

Controlling neuronal activity using implantable neural interfaces constitutes an important tool to understand and develop novel strategies against brain diseases. Infrared neurostimulation is a promising alternative to optogenetics for controlling the neuronal circuitry with high spatial resolution. However, bi-directional interfaces capable of simultaneously delivering infrared light and recording electrical signals from the brain with minimal inflammation have not yet been reported. Here, we have developed a soft fibre-based device using high-performance polymers which are >100-fold softer than conventional silica glass used in standard optical fibres. The developed implant is capable of stimulating the brain activity in localized cortical domains by delivering laser pulses in the 2 µm spectral region while recording electrophysiological signals. Action and local field potentials were recorded in vivo from the motor cortex and hippocampus in acute and chronic settings, respectively. Immunohistochemical analysis of the brain tissue indicated insignificant inflammatory response to the infrared pulses while the signal-to-noise ratio of recordings still remained high. Our neural interface constitutes a step forward in expanding infrared neurostimulation as a versatile approach for fundamental research and clinically translatable therapies.

Bundle geodesic convolutional neural network for diffusion-weighted imaging segmentation.

Purpose: Applying machine learning techniques to magnetic resonance diffusion-weighted imaging (DWI) data is challenging due to the size of individual data samples and the lack of labeled data. It is possible, though, to learn general patterns from a very limited amount of training data if we take advantage of the geometry of the DWI data. Therefore, we present a tissue classifier based on a Riemannian deep learning framework for single-shell DWI data. Approach: The framework consists of three layers: a lifting layer that locally represents and convolves data on tangent spaces to produce a family of functions defined on the rotation groups of the tangent spaces, i.e., a (not necessarily continuous) function on a bundle of rotational functions on the manifold; a group convolution layer that convolves this function with rotation kernels to produce a family of local functions over each of the rotation groups; a projection layer using maximization to collapse this local data to form manifold based functions. Results: Experiments show that our method achieves the performance of the same level as state-of-the-art while using way fewer parameters in the model ( < 10 % ). Meanwhile, we conducted a model sensitivity analysis for our method. We ran experiments using a proportion (69.2%, 53.3%, and 29.4%) of the original training set and analyzed how much data the model needs for the task. Results show that this does reduce the overall classification accuracy mildly, but it also boosts the accuracy for minority classes. Conclusions: This work extended convolutional neural networks to Riemannian manifolds, and it shows the potential in understanding structural patterns in the brain, as well as in aiding manual data annotation.

Movement is governed by rotational neural dynamics in spinal motor networks.

Although the generation of movements is a fundamental function of the nervous system, the underlying neural principles remain unclear. As flexor and extensor muscle activities alternate during rhythmic movements such as walking, it is often assumed that the responsible neural circuitry is similarly exhibiting alternating activity1. Here we present ensemble recordings of neurons in the lumbar spinal cord that indicate that, rather than alternating, the population is performing a low-dimensional 'rotation' in neural space, in which the neural activity is cycling through all phases continuously during the rhythmic behaviour. The radius of rotation correlates with the intended muscle force, and a perturbation of the low-dimensional trajectory can modify the motor behaviour. As existing models of spinal motor control do not offer an adequate explanation of rotation1,2, we propose a theory of neural generation of movements from which this and other unresolved issues, such as speed regulation, force control and multifunctionalism, are readily explained.

Viral strategies for targeting spinal neuronal subtypes in adult wild-type rodents.

Targeting specific subtypes of interneurons in the spinal cord is primarily restricted to a small group of genetic model animals. Since the development of new transgenic model animals can be expensive and labor intensive, it is often difficult to generalize these findings and verify them in other model organisms, such as the rat, ferret or monkey, that may be more beneficial in certain experimental investigations. Nevertheless, endogenous enhancers and promoters delivered using an adeno-associated virus (AAV) have been successful in providing expression in specific subtypes of neurons in the forebrain of wildtype animals, and therefore may introduce a shortcut. GABAergic interneurons, for instance, have successfully been targeted using the mDlx promoter, which has recently been developed and is now widely used in wild type animals. Here, we test the specificity and efficiency of the mDlx enhancer for robust targeting of inhibitory interneurons in the lumbar spinal cord of wild-type rats using AAV serotype 2 (AAV2). Since this has rarely been done in the spinal cord, we also test the expression and specificity of the CamKIIa and hSynapsin promoters using serotype 9. We found that AAV2-mDlx does in fact target many neurons that contain an enzyme for catalyzing GABA, the GAD-65, with high specificity and a small fraction of neurons containing an isoform, GAD-67. Expression was also seen in some motor neurons although with low correlation. Viral injections using the CamKIIa enhancer via AAV9 infected in some glutamatergic neurons, but also GABAergic neurons, whereas hSynapsin via AAV9 targets almost all the neurons in the lumbar spinal cord.

Adaptive polymer fiber neural device for drug delivery and enlarged illumination angle for neuromodulation.

Objective. Optical fiber devices constitute significant tools for the modulation and interrogation of neuronal circuitry in the mid and deep brain regions. The illuminated brain area during neuromodulation has a direct impact on the spatio-temporal properties of the brain activity and depends solely on the material and geometrical characteristics of the optical fibers. In the present work, we developed two different flexible polymer optical fibers (POFs) with integrated microfluidic channels (MFCs) and an ultra-high numerical aperture (UHNA) for enlarging the illumination angle to achieve efficient neuromodulation.Approach. Three distinct thermoplastic polymers: polysulfone, polycarbonate, and fluorinated ethylene propylene were used to fabricate two step-index UHNA POF neural devices using a scalable thermal drawing process. The POFs were characterized in terms of their illumination map as well as their fluid delivery capability in phantom and adult rat brain slices. Main results.A 100-fold reduced bending stiffness of the proposed fiber devices compared to their commercially available counterparts has been found. The integrated MFCs can controllably deliver dye (trypan blue) on-demand over a wide range of injection rates spanning from 10 nl min-1to 1000 nl min-1. Compared with commercial silica fibers, the proposed UHNA POFs exhibited an increased illumination area by 17% and 21% under 470 and 650 nm wavelength, respectively. In addition, a fluorescent light recording experiment has been conducted to demonstrate the ability of our UHNA POFs to be used as optical waveguides in fiber photometry.Significance. Our results overcome the current technological limitations of fiber implants that have limited illumination area and we suggest that soft neural fiber devices can be developed using different custom designs for illumination, collection, and photometry applications. We anticipate our work to pave the way towards the development of next-generation functional optical fibers for neuroscience.

Why Firing Rate Distributions Are Important for Understanding Spinal Central Pattern Generators.

Networks in the spinal cord, which are responsible for the generation of rhythmic movements, commonly known as central pattern generators (CPGs), have remained elusive for decades. Although it is well-known that many spinal neurons are rhythmically active, little attention has been given to the distribution of firing rates across the population. Here, we argue that firing rate distributions can provide an important clue to the organization of the CPGs. The data that can be gleaned from the sparse literature indicate a firing rate distribution, which is skewed toward zero with a long tail, akin to a normal distribution on a log-scale, i.e., a "log-normal" distribution. Importantly, such a shape is difficult to unite with the widespread assumption of modules composed of recurrently connected excitatory neurons. Spinal modules with recurrent excitation has the propensity to quickly escalate their firing rate and reach the maximum, hence equalizing the spiking activity across the population. The population distribution of firing rates hence would consist of a narrow peak near the maximum. This is incompatible with experiments, that show wide distributions and a peak close to zero. A way to resolve this puzzle is to include recurrent inhibition internally in each CPG modules. Hence, we investigate the impact of recurrent inhibition in a model and find that the firing rate distributions are closer to the experimentally observed. We therefore propose that recurrent inhibition is a crucial element in motor circuits, and suggest that future models of motor circuits should include recurrent inhibition as a mandatory element.

What are the gray and white matter volumes of the human spinal cord?

The gray matter of the spinal cord is the seat of somata of various types of neurons devoted to the sensory and motor activities of the limbs and trunk as well as a part of the autonomic nervous system. The volume of the spinal gray matter is an indicator of the local neuronal processing, and this can decrease due to atrophy associated with degenerative diseases and injury. Nevertheless, the absolute volume of the human spinal cord has rarely been reported, if ever. Here, we use high-resolution magnetic resonance imaging, with a cross-sectional resolution of 50 × 50 µm and a voxel size of 0.0005 mm3 to estimate the total gray and white matter volume of a post mortem human female spinal cord. Segregation of gray and white matter was accomplished using deep learning image segmentation. Furthermore, we include data from a male spinal cord of a previously published study. The gray and white matter volumes were found to be 2.87 and 11.33 mL, respectively, for the female and 3.55 and 19.33 mL, respectively, for the male. The gray and white matter profiles along the vertebral axis were found to be strikingly similar, and the volumes of the cervical, thoracic, and lumbosacral sections were almost equal.NEW & NOTEWORTHY Here, we combine high-field MRI (9.4 T) and deep learning for a post mortem reconstruction of the gray and white matter in human spinal cords. We report a minuscule total gray matter volume of 2.87 mL for a female and 3.55 mL for a male. For comparison, these volumes correspond approximately to the distal digit of the little finger.

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord.

During the generation of rhythmic movements, most spinal neurons receive an oscillatory synaptic drive. The neuronal architecture underlying this drive is unknown, and the corresponding network size and sparseness have not yet been addressed. If the input originates from a small central pattern generator (CPG) with dense divergent connectivity, it will induce correlated input to all receiving neurons, while sparse convergent wiring will induce a weak correlation, if any. Here, we use pairwise recordings of spinal neurons to measure synaptic correlations and thus infer the wiring architecture qualitatively. A strong correlation on a slow timescale implies functional relatedness and a common source, which will also cause correlation on fast timescale due to shared synaptic connections. However, we consistently find marginal coupling between slow and fast correlations regardless of neuronal identity. This suggests either sparse convergent connectivity or a CPG network with recurrent inhibition that actively decorrelates common input.

Estimation of Synaptic Conductances in Presence of Nonlinear Effects Caused by Subthreshold Ionic Currents.

Subthreshold fluctuations in neuronal membrane potential traces contain nonlinear components, and employing nonlinear models might improve the statistical inference. We propose a new strategy to estimate synaptic conductances, which has been tested using in silico data and applied to in vivo recordings. The model is constructed to capture the nonlinearities caused by subthreshold activated currents, and the estimation procedure can discern between excitatory and inhibitory conductances using only one membrane potential trace. More precisely, we perform second order approximations of biophysical models to capture the subthreshold nonlinearities, resulting in quadratic integrate-and-fire models, and apply approximate maximum likelihood estimation where we only suppose that conductances are stationary in a 50-100 ms time window. The results show an improvement compared to existent procedures for the models tested here.

Advances and perspectives in tissue clearing using CLARITY.

CLARITY is a tissue clearing method, which enables immunostaining and imaging of large volumes for 3D-reconstruction. The method was initially time-consuming, expensive and relied on electrophoresis to remove lipids to make the tissue transparent. Since then several improvements and simplifications have emerged, such as passive clearing (PACT) and methods to improve tissue staining. Here, we review advances and compare current applications with the aim of highlighting needed improvements as well as aiding selection of the specific protocol for use in future investigations.

Intense Activity of the Raphe Spinal Pathway Depresses Motor Activity via a Serotonin Dependent Mechanism.

Motor fatigue occurring during prolonged physical activity has both peripheral and central origins. It was previously demonstrated that the excitability of motoneurons was decreased when a spillover of serotonin could activate extrasynaptic 5-HT1A receptors at the axon initial segment (AIS) of motoneurons. Here we investigated the impact of massive synaptic release of serotonin on motor behavior in an integrated preparation of the adult turtle performing fictive scratching behaviors. We found that a prolonged electrical stimulation of the raphe spinal pathway induced a reversible inhibition of the motor behavior that lasted several tens of seconds. The effect disappeared when the spinal cord was perfused with an antagonist for 5-HT1A receptors. By demonstrating a direct impact of serotonin on motor behavior, we suggest a central role of this monoamine behind central fatigue.

Spinal Cord Preparation from Adult Red-eared Turtles for Electrophysiological Recordings during Motor Activity.

Although it is known that the generation of movements is performed to a large extent in neuronal circuits located in the spinal cord, the involved mechanisms are still unclear. The turtle as a model system for investigating spinal motor activity has advantages, which far exceeds those of model systems using other animals. The high resistance to anoxia allows for investigation of the fully developed and adult spinal circuitry, as opposed to mammals, which are sensitive to anoxia and where using neonates are often required to remedy the problems. The turtle is mechanically stable and natural sensory inputs can induce multiple complex motor behaviors, without the need for application of neurochemicals. Here, we provide a detailed protocol of how to make the adult turtle preparation, also known as the integrated preparation for electrophysiological investigation. Here, the hind-limb scratch reflex can be induced by mechanical sensory activation, while recording single cells, and the network activity, via intracellular-, extracellular- and electroneurogram recordings. The preparation was developed for the studies by Petersen et al. (2014) and Petersen and Berg (2016), and other ongoing studies.

Neuronal Population Activity in Spinal Motor Circuits: Greater Than the Sum of Its Parts.

The core elements of stereotypical movements such as locomotion, scratching and breathing are generated by networks in the lower brainstem and the spinal cord. Ensemble activities in spinal motor networks had until recently been merely a black box, but with the emergence of ultra-thin Silicon multi-electrode technology it was possible to reveal the spiking activity of larger parts of the network. A series of experiments revealed unexpected features of spinal networks, such as multiple spiking regimes and lognormal firing rate distributions. The lognormality renders the widespread idea of a typical firing rate ± standard deviation an ill-suited description, and therefore these findings define a new arithmetic of motor networks. Focusing on the population activity behind motor pattern generation this review summarizes this advance and discusses its implications.

Lognormal firing rate distribution reveals prominent fluctuation-driven regime in spinal motor networks.

When spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits of turtles and establish the neuronal fraction that operates within either a 'mean-driven' or a 'fluctuation-driven' regime. Fluctuation-driven neurons have a 'supralinear' input-output curve, which enhances sensitivity, whereas the mean-driven regime reduces sensitivity. We find a rich diversity of firing rates across the neuronal population as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50 % of the time in the 'fluctuation-driven' regime regardless of behavior. Because of the disparity in input-output properties for these two regimes, this fraction may reflect a fine trade-off between stability and sensitivity in order to maintain flexibility across behaviors.

CLARITY-compatible lipophilic dyes for electrode marking and neuronal tracing.

Fluorescent lipophilic dyes, such as DiI, stain cellular membranes and are used extensively for retrograde/anterograde labeling of neurons as well as for marking the position of extracellular electrodes after electrophysiology. Convenient histological clearing techniques, such as CLARITY, enable immunostaining and imaging of large volumes for 3D-reconstruction. However, such clearing works by removing lipids and, as an unintended consequence, also removes lipophilic dyes. To remedy this wash-out, the molecular structure of the dye can be altered to adhere to both membranes and proteins so the dye remains in the tissue after lipid-clearing. Nevertheless, the capacity of such modified dyes to remain in tissue has not yet been tested. Here, we test dyes with molecular modifications that make them aldehyde-fixable to proteins. We use three Dil-analogue dyes, CM-DiI, SP-DiI and FM 1-43FX that are modified to be CLARITY-compatible candidates. We use the challenging adult, myelin-rich spinal cord tissue, which requires prolonged lipid-clearing, of rats and mice. All three dyes remained in the tissue after lipid-clearing, but CM-DiI had the sharpest and FM 1-43FX the strongest fluorescent signal.