A scalable spiking amygdala model that explains fear conditioning, extinction, renewal and generalization.

The amygdala (AMY) is widely implicated in fear learning and fear behaviour, but it remains unclear how the many biological components present within AMY interact to achieve these abilities. Building on previous work, we hypothesize that individual AMY nuclei represent different quantities and that fear conditioning arises from error-driven learning on the synapses between AMY nuclei. We present a computational model of AMY that (a) recreates the divisions and connections between AMY nuclei and their constituent pyramidal and inhibitory neurons; (b) accommodates scalable high-dimensional representations of external stimuli; (c) learns to associate complex stimuli with the presence (or absence) of an aversive stimulus; (d) preserves feature information when mapping inputs to salience estimates, such that these estimates generalize to similar stimuli; and (e) induces a diverse profile of neural responses within each nucleus. Our model predicts (1) defensive responses and neural activities in several experimental conditions, (2) the consequence of artificially ablating particular nuclei and (3) the tendency to generalize defensive responses to novel stimuli. We test these predictions by comparing model outputs to neural and behavioural data from animals and humans. Despite the relative simplicity of our model, we find significant overlap between simulated and empirical data, which supports our claim that the model captures many of the neural mechanisms that support fear conditioning. We conclude by comparing our model to other computational models and by characterizing the theoretical relationship between pattern separation and fear generalization in healthy versus anxious individuals.

Neural interfacing architecture enables enhanced motor control and residual limb functionality postamputation.

Despite advancements in prosthetic technologies, patients with amputation today suffer great diminution in mobility and quality of life. We have developed a modified below-knee amputation (BKA) procedure that incorporates agonist-antagonist myoneural interfaces (AMIs), which surgically preserve and couple agonist-antagonist muscle pairs for the subtalar and ankle joints. AMIs are designed to restore physiological neuromuscular dynamics, enable bidirectional neural signaling, and offer greater neuroprosthetic controllability compared to traditional amputation techniques. In this prospective, nonrandomized, unmasked study design, 15 subjects with AMI below-knee amputation (AB) were matched with 7 subjects who underwent a traditional below-knee amputation (TB). AB subjects demonstrated significantly greater control of their residual limb musculature, production of more differentiable efferent control signals, and greater precision of movement compared to TB subjects (P < 0.008). This may be due to the presence of greater proprioceptive inputs facilitated by the significantly higher fascicle strains resulting from coordinated muscle excursion in AB subjects (P < 0.05). AB subjects reported significantly greater phantom range of motion postamputation (AB: 12.47 ± 2.41, TB: 10.14 ± 1.45 degrees) when compared to TB subjects (P < 0.05). Furthermore, AB subjects also reported less pain (12.25 ± 5.37) than TB subjects (17.29 ± 10.22) and a significant reduction when compared to their preoperative baseline (P < 0.05). Compared with traditional amputation, the construction of AMIs during amputation confers the benefits of enhanced physiological neuromuscular dynamics, proprioception, and phantom limb perception. Subjects' activation of the AMIs produces more differentiable electromyography (EMG) for myoelectric prosthesis control and demonstrates more positive clinical outcomes.

Complex Material Properties of Gel-Amin: A Transparent and Ionically Conductive Hydrogel for Neural Tissue Engineering.

The field of tissue engineering has benefited greatly from the broad development of natural and synthetic polymers. Extensive work in neural engineering has demonstrated the value of conductive materials to improve spontaneous neuron activity as well as lowering the necessary field parameters for exogenous electrical stimulation. Further, cell fate is directly coupled to the mechanical properties of the cell culture substrate. Increasing the conductivity of hydrogel materials often necessitates the addition of dopant materials that facilitate electron mobility. However, very little electron transfer is observed in native cell signaling and most of these materials are opaque, severely limiting microscopy applications commonly employed to assess cell culture morphology and function. To overcome these shortcomings, the inclusion of an ionic liquid, choline acrylate, into the backbone of a modified collagen polymer increases the bulk conductivity 5-fold at a 1:1 ratio while maintaining optical transmission of visible light. Here, we explore how the inclusion of choline acrylate influences bulk material properties including the mechanical, swelling, and optical properties of our hydrogels, referred to as Gel-Amin hydrogels, as a material for tissue culture. Despite an increase in swelling over traditional GelMA materials, the conductive hydrogels support whole dorsal root ganglia encapsulation and outgrowth. Our results indicate that our Gel-Amin system holds potential for neural engineering applications and lowering the required charge injection for the application of exogenous electrical stimulation. This is this first time an ionic liquid-hydrogel system has been used to culture and support primary neurons in vitro.

A 0.43 g Wireless Battery-Less Neural Recorder With On-Chip Microelectrode Array and Integrated Flexible Antenna.

This work presents a single-chip battery-less neural recorder with 12 on-die microelectrodes. It can be powered wirelessly up to 16 cm away from a horn antenna at 915 MHz and only consumes 104 µW dc power for accessing 10 enabled recording sites simultaneously, transmitting at 5 Mbps. The implantable device integrated with a flexible antenna weighs only 0.43 gram. In vivo measurements on an unrestricted mouse have been successfully conducted, showing response to visual stimuli.

Decoding kinetic features of hand motor preparation from single-trial EEG using convolutional neural networks.

Building accurate movement decoding models from brain signals is crucial for many biomedical applications. Predicting specific movement features, such as speed and force, before movement execution may provide additional useful information at the expense of increasing the complexity of the decoding problem. Recent attempts to predict movement speed and force from the electroencephalogram (EEG) achieved classification accuracies at or slightly above chance levels, highlighting the need for more accurate prediction strategies. Thus, the aims of this study were to accurately predict hand movement speed and force from single-trial EEG signals and to decode neurophysiological information of motor preparation from the prediction strategies. To these ends, a decoding model based on convolutional neural networks (ConvNets) was implemented and compared against other state-of-the-art prediction strategies, such as support vector machines and decision trees. ConvNets outperformed the other prediction strategies, achieving an overall accuracy of 84% in the classification of two different levels of speed and force (four-class classification) from pre-movement single-trial EEG (100 ms and up to 1,600 ms prior to movement execution). Furthermore, an analysis of the ConvNet architectures suggests that the network performs a complex spatiotemporal integration of EEG data to optimize classification accuracy. These results show that movement speed and force can be accurately predicted from single-trial EEG, and that the prediction strategies may provide useful neurophysiological information about motor preparation.

Entropy in Image Analysis II.

Image analysis is a fundamental task for any application where extracting information from images is required [...].

The Reconnecting the Hand and Arm with Brain (ReHAB) Commentary on "An Integrated Brain-Machine Interface Platform With Thousands of Channels".

Intracortical brain-machine interfaces are a promising technology for allowing people with chronic and severe neurological disorders that resulted in loss of function to potentially regain those functions through neuroprosthetic devices. The penetrating microelectrode arrays used in almost all previous studies of intracortical brain-machine interfaces in people had a limited recording life (potentially due to issues with long-term biocompatibility), as well as a limited number of recording electrodes with limited distribution in the brain. Significant advances are required in this array interface to deal with the issues of long-term biocompatibility and lack of distributed recordings. The Musk and Neuralink manuscript proposes a novel and potentially disruptive approach to advancing the brain-electrode interface technology, with the potential of addressing many of these hurdles. Our commentary addresses the potential advantages of the proposed approach, as well as the remaining challenges to be addressed.

Developing Next-generation Brain Sensing Technologies - A Review.

Advances in sensing technology raise the possibility of creating neural interfaces that can more effectively restore or repair neural function and reveal fundamental properties of neural information processing. To realize the potential of these bioelectronic devices, it is necessary to understand the capabilities of emerging technologies and identify the best strategies to translate these technologies into products and therapies that will improve the lives of patients with neurological and other disorders. Here we discuss emerging technologies for sensing brain activity, anticipated challenges for translation, and perspectives for how to best transition these technologies from academic research labs to useful products for neuroscience researchers and human patients.

Insulation of thin-film parylene-C/platinum probes in saline solution through encapsulation in multilayer ALD ceramic films.

The long-term electrical leakage performance of parylene-C/platinum/parylene-C (Px/Pt/Px) interconnect in saline is evaluated using electrochemical impedance spectroscopy (EIS). Three kinds of additional ceramic encapsulation layers between the metal and Px are characterized: 50 nm-thick alumina (Al2O3), 50 nm-thick titania (TiO2), and 80 nm-thick Al2O3-TiO2 nanolaminate (NL). The Al2O3 and TiO2 encapsulation layers worsen the overall insulation properties. The NL encapsulation layer improves the insulation when combined with a TiO2 outer layer to promote adhesion to the Px. Experiments are performed with various insulation promotion treatments: A-174 silane (A174) treatment before Px deposition (to promote adhesion); SF6 plasma treatment (F) after Px deposition (to increase hydrophobicity); and ion-milling descum (IM) after Px deposition (to prevent parylene oxidation). A174 and F treatments do not have a significant impact, while IM leads to worse insulation performance. A circuit model elucidates the insulation characteristics of Px-ceramic-Pt-ceramic-Px interconnect. These studies provide a foundation for processing ultra-compliant neural probes with long-term chronic utility.

Neurophysiology and neural engineering: a review.

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight.

A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex.

Subjects performing simple reaction-time tasks can improve reaction times by learning the expected timing of action-imperative stimuli and preparing movements in advance. Success or failure on the previous trial is often an important factor for determining whether a subject will attempt to time the stimulus or wait for it to occur before initiating action. The medial prefrontal cortex (mPFC) has been implicated in enabling the top-down control of action depending on the outcome of the previous trial. Analysis of spike activity from the rat mPFC suggests that neural integration is a key mechanism for adaptive control in precisely timed tasks. We show through simulation that a spiking neural network consisting of coupled neural integrators captures the neural dynamics of the experimentally recorded mPFC. Errors lead to deviations in the normal dynamics of the system, a process that could enable learning from past mistakes. We expand on this coupled integrator network to construct a spiking neural network that performs a reaction-time task by following either a cue-response or timing strategy, and show that it performs the task with similar reaction times as experimental subjects while maintaining the same spiking dynamics as the experimentally recorded mPFC.

3D Printed Anatomical Nerve Regeneration Pathways.

An imaging-coupled 3D printing methodology for the design, optimization, and fabrication of a customized nerve repair technology for complex injuries is presented. The custom scaffolds are deterministically fabricated via a microextrusion printing principle which enables the simultaneous incorporation of anatomical geometries, biomimetic physical cues, and spatially controlled biochemical gradients in a one-pot 3D manufacturing approach.

Two theories of consciousness: Semantic pointer competition vs. information integration.

Consciousness results from three mechanisms: representation by firing patterns in neural populations, binding of representations into more complex representations called semantic pointers, and competition among semantic pointers to capture the most important aspects of an organism's current state. We contrast the semantic pointer competition (SPC) theory of consciousness with the hypothesis that consciousness is the capacity of a system to integrate information (IIT). We describe computer simulations to show that SPC surpasses IIT in providing better explanations of key aspects of consciousness: qualitative features, onset and cessation, shifts in experiences, differences in kinds across different organisms, unity and diversity, and storage and retrieval.

Aligned Bioelectronic Polypyrrole/Collagen Constructs for Peripheral Nerve Interfacing.

Electrical stimulation has shown promise in clinical studies to treat nerve injuries. This work is aimed to create an aligned bioelectronic construct that can be used to bridge a nerve gap, directly interfacing with the damaged nerve tissue to provide growth support. The conductive three-dimensional bioelectronic scaffolds described herein are composite materials, comprised of conductive polypyrrole (PPy) nanoparticles embedded in an aligned collagen hydrogel. The bioelectronic constructs are seeded with dorsal root ganglion derived primary rat neurons and electrically stimulated in vitro. The PPy loaded constructs support a 1.7-fold increase in neurite length in comparison to control collagen constructs. Furthermore, upon electrical stimulation of the PPy-collagen construct, a 1.8-fold increase in neurite length is shown. This work illustrates the potential of bioelectronic constructs in neural tissue engineering and lays the groundwork for the development of novel bioelectronic materials for neural interfacing applications.

Unintentionally intentional: unintended effects of spinal stimulation as a platform for multi-modal neurorehabilitation after spinal cord injury.

Electrical stimulation of spinal neurons has emerged as a valuable tool to enhance rehabilitation after spinal cord injury. In separate parameterizations, it has shown promise for improving voluntary movement, reducing symptoms of autonomic dysreflexia, improving functions mediated by muscles of the pelvic floor (e.g., bowel, bladder, and sexual function), reducing spasms and spasticity, and decreasing neuropathic pain, among others. This diverse set of actions is related both to the density of sensorimotor neural networks in the spinal cord and to the intrinsic ability of electrical stimulation to modulate neural transmission in multiple spinal networks simultaneously. It also suggests that certain spinal stimulation parameterizations may be capable of providing multi-modal therapeutic benefits, which would directly address the complex, multi-faceted rehabilitation goals of people living with spinal cord injury. This review is intended to identify and characterize reports of spinal stimulation-based therapies specifically designed to provide multi-modal benefits and those that report relevant unintended effects of spinal stimulation paradigms parameterized to enhance a single consequence of spinal cord injury.

Control of Neuronal Survival and Development Using Conductive Diamond.

This study demonstrates the control of neuronal survival and development using nitrogen-doped ultrananocrystalline diamond (N-UNCD). We highlight the role of N-UNCD in regulating neuronal activity via near-infrared illumination, demonstrating the generation of stable photocurrents that enhance neuronal survival and neurite outgrowth and foster a more active, synchronized neuronal network. Whole transcriptome RNA sequencing reveals that diamond substrates improve cellular-substrate interaction by upregulating extracellular matrix and gap junction-related genes. Our findings underscore the potential of conductive diamond as a robust and biocompatible platform for noninvasive and effective neural tissue engineering.

Merging Humans and Neuroprosthetics through Regenerative Peripheral Nerve Interfaces.

Limb amputations can be devastating and significantly affect an individual's independence, leading to functional and psychosocial challenges in nearly 2 million people in the United States alone. Over the past decade, robotic devices driven by neural signals such as neuroprostheses have shown great potential to restore the lost function of limbs, allowing amputees to regain movement and sensation. However, current neuroprosthetic interfaces have challenges in both signal quality and long-term stability. To overcome these limitations and work toward creating bionic limbs, the Neuromuscular Laboratory at University of Michigan Plastic Surgery has developed the Regenerative Peripheral Nerve Interface (RPNI). This surgical construct embeds a transected peripheral nerve into a free muscle graft, effectively amplifying small peripheral nerve signals to provide enhanced control signals for a neuroprosthetic limb. Furthermore, the RPNI has the potential to provide sensory feedback to the user and facilitate neuroprosthesis embodiment. This review focuses on the animal studies and clinical trials of the RPNI to recapitulate the promising trajectory toward neurobionics where the boundary between an artificial device and the human body becomes indistinct. This paper also sheds light on the prospects of the improvement and dissemination of the RPNI technology.

Nanoparticle-based drug delivery for the treatment of traumatic brain injury.

INTRODUCTION: Traumatic brain injuries (TBIs) impact the breadth of society and remain without any approved pharmacological treatments. Despite successful Phase II clinical trials, the failure of many Phase III clinical trials may be explained by insufficient drug targeting and retention, preventing the proper attainment of an observable dosage threshold. To address this challenge, nanoparticles can be functionalized to protect pharmacological payloads, improve targeted drug delivery to sites of injury, and can be combined with supportive scaffolding to improve secondary outcomes. AREAS COVERED: This review briefly covers the pathophysiology of TBIs and their subtypes, the current pre-clinical and clinical management strategies, explores the common models of focal, diffuse, and mixed traumatic brain injury employed in experimental animals, and surveys the existing literature on nanoparticles developed to treat TBIs. EXPERT OPINION: Nanoparticles are well suited to improve secondary outcomes as their multifunctionality and customizability enhance their potential for efficient targeted delivery, payload protection, increased brain penetration, low off-target toxicity, and biocompatibility in both acute and chronic timescales.

Neurorobotics and neuroprostheses: Towards a new anatomy.

The idea of this Special Issue arose from the technological advances in bionic, robotic, and neural rehabilitation systems and the common need to comprehend in detail how human anatomical structures can be replicated or controlled. Motor control theories, among others, include the generalized control program theory, the equilibrium point hypothesis, or the optimal control approach in which neural commands to the muscles are a result of the central nervous system solving an optimization problem for a specific cost function. No matter the alternative interpretation selected to replicate biological control of human movements, artificial "anatomies" should consider not only motor capabilities from the central nervous system but integrate bioinspired mechanical features (such as compliance) in artificial limbs. The development of wearable robotics and neuroprosthetic systems for human movement compensation and control is naturally inspired by human anatomy and biology. Cutting-edge technological advances in the field of biomedical and neural engineering are bringing us more and more close to a new artificial anatomy with which humans could augment their motor capabilities or replace them after they are compromised. Either augmentative/assistive or rehabilitation technologies in the near future will require engineering solutions based on novel approaches to create usable neurorobotic and neuroprosthetic systems for the most relevant societal needs.