Carbon monofilament electrodes for unit recording and functional MRI in same subjects

Monolayer, open-mesh, pristine PEDOT:PSS-based conformal brain implants for fully MRI-compatible neural interfaces

Understanding brain function is essential for advancing our comprehension of human cognition, behavior, and neurological disorders. Magnetic resonance imaging (MRI) stands out as a powerful tool for exploring brain function, providing detailed insights into its structure and physiology. Combining MRI technology with electrophysiological recording system can enhance the comprehension of brain functionality through synergistic effects. However, the integration of neural implants with MRI technology presents challenges because of its strong electromagnetic (EM) energy during MRI scans. Therefore, MRI-compatible neural implants should facilitate detailed investigation of neural activities and brain functions in real-time in high resolution, without compromising patient safety and imaging quality. Here, we introduce the fully MRI-compatible monolayer open-mesh pristine PEDOT:PSS neural interface. This approach addresses the challenges encountered while using traditional metal-based electrodes in the MRI environment such as induced heat or imaging artifacts. PEDOT:PSS has a diamagnetic property with low electrical conductivity and negative magnetic susceptibility similar to human tissues. Furthermore, by adopting the optimized open-mesh structure, the induced currents generated by EM energy are significantly diminished, leading to optimized MRI compatibility. Through simulations and experiments, our PEDOT:PSS-based open-mesh electrodes showed improved performance in reducing heat generation and eliminating imaging artifacts in an MRI environment. The electrophysiological recording capability was also validated by measuring the local field potential (LFP) from the somatosensory cortex with an in vivo experiment. The development of neural implants with maximized MRI compatibility indicates the possibility of potential tools for future neural diagnostics.

Pupil Dynamics-derived Sleep Stage Classification of a Head-fixed Mouse Using a Recurrent Neural Network

The standard method for sleep state classification is thresholding the amplitudes of electroencephalography (EEG) and electromyography (EMG) data, followed by manual correction by an expert. Although popular, this method has some shortcomings: (1) the time-consuming manual correction by human experts is sometimes a bottleneck hindering sleep studies, (2) EEG electrodes on the skull interfere with wide-field imaging of the cortical activity of a head-fixed mouse under a microscope, (3) invasive surgery to fix the electrodes on the thin mouse skull risks brain tissue injury, and (4) metal electrodes for EEG and EMG recording are difficult to apply to some experimental apparatus such as that for functional magnetic resonance imaging. To overcome these shortcomings, we propose a pupil dynamics-based vigilance state classification method for a head-fixed mouse using a long short-term memory (LSTM) model, a variant of a recurrent neural network, for multi-class labeling of NREM, REM, and WAKE states. For supervisory hypnography, EEG and EMG recording were performed on head-fixed mice. This setup was combined with left eye pupillometry using a USB camera and a markerless tracking toolbox, DeepLabCut. Our open-source LSTM model with feature inputs of pupil diameter, pupil location, pupil velocity, and eyelid opening for 10 s at a 10 Hz sampling rate achieved vigilance state estimation with a higher classification performance (macro F1 score, 0.77; accuracy, 86%) than a feed-forward neural network. Findings from a diverse range of pupillary dynamics implied possible subdivision of the vigilance states defined by EEG and EMG. Pupil dynamics-based hypnography can expand the scope of alternatives for sleep stage scoring of head-fixed mice.

Solving brain circuit function and dysfunction with computational modeling and optogenetic fMRI

Can we construct a model of brain function that enables an understanding of whole-brain circuit mechanisms underlying neurological disease and use it to predict the outcome of therapeutic interventions? How are pathologies in neurological disease, some of which are observed to have spatial spreading mechanisms, associated with circuits and brain function? In this review, we discuss approaches that have been used to date and future directions that can be explored to answer these questions. By combining optogenetic functional magnetic resonance imaging (fMRI) with computational modeling, cell type-specific, large-scale brain circuit function and dysfunction are beginning to be quantitatively parameterized. We envision that these developments will pave the path for future therapeutics developments based on a systems engineering approach aimed at directly restoring brain function.

Focal electrical stimulation on an alcohol disorder model using magnetic resonance imaging-compatible chronic neural monopolar carbon fiber electrodes

Neuromodulation interventions, such as Deep Brain Stimulation (DBS) and repeated transcranial magnetic stimulation (rTMS), are proposed as possible new complementary therapies to treat substance use disorders (SUD) such as alcohol use disorder (AUD). It is hypothesized that neuromodulation may induce neural plasticity in the reward and frontostriatal systems via electrical field induction, possibly reducing symptoms. Preclinical self-administration rodent models of AUD may help us gain insight into the effects of neuromodulation therapies on different pathology, as well as the neural mechanisms behind the positive effects. DBS, or any type of brain stimulation using intracranial electrodes in rodents, would benefit from the use of magnetic resonance imaging (MRI) to study the longitudinal effects and mechanisms of stimulation as well as novel targets, as it is a non-invasive technique that allows the analysis of structural and functional changes in the brain. To do this, there is a need for MRI-compatible electrodes that allow for MRI acquisition with minimal distortion of the magnetic field. In this protocol, we present a method for the construction and surgery of chronically implantable monopolar carbon electrodes for use in rats. Unlike conventional electrodes, carbon electrodes are resistant to high temperatures, flexible, and generate fewer artifacts in MRI compared to conventional ones. We validated its use by using a focal electrical stimulation high-frequency (20 Hz) protocol that lasted ∼10 sessions. We propose that this technique can also be used for the research of the neurophysiological bases of the neuromodulatory treatment in other preclinical substance use disorders (SUD) models.

MRI magnetic compatible electrical neural interface: From materials to application

Neural electrical interfaces are important tools for local neural stimulation and recording, which potentially have wide application in the diagnosis and treatment of neural diseases, as well as in the transmission of neural activity for brain-computer interface (BCI) systems. At the same time, magnetic resonance imaging (MRI) is one of the effective and non-invasive techniques for recording whole-brain signals, providing details of brain structures and also activation pattern maps. Simultaneous recording of extracellular neural signals and MRI combines two expressions of the same neural activity and is believed to be of great importance for the understanding of brain function. However, this combination makes requests on the magnetic and electronic performance of neural interface devices. MRI-compatibility refers here to a technological approach to simultaneous MRI and electrode recording or stimulation without artifacts in imaging. Trade-offs between materials magnetic susceptibility selection and electrical function should be considered. Herein, prominent trends in selecting materials of suitable magnetic properties are analyzed and material design, function and application of neural interfaces are outlined together with the remaining challenge to fabricate MRI-compatible neural interface.

Carbon-based neural electrodes: promises and challenges

Neural electrodes are primary functional elements of neuroelectronic devices designed to record neural activity based on electrochemical signals. These electrodes may also be utilized for electrically stimulating the neural cells, such that their response can be simultaneously recorded. In addition to being medically safe, the electrode material should be electrically conductive and electrochemically stable under harsh biological environments. Mechanical flexibility and conformability, resistance to crack formation and compatibility with common microfabrication techniques are equally desirable properties. Traditionally, (noble) metals have been the preferred for neural electrode applications due to their proven biosafety and a relatively high electrical conductivity. Carbon is a recent addition to this list, which is far superior in terms of its electrochemical stability and corrosion resistance. Carbon has also enabled 3D electrode fabrication as opposed to the thin-film based 2D structures. One of carbon's peculiar aspects is its availability in a wide range of allotropes with specialized properties that render it highly versatile. These variations, however, also make it difficult to understand carbon itself as a unique material, and thus, each allotrope is often regarded independently. Some carbon types have already shown promising results in bioelectronic medicine, while many others remain potential candidates. In this topical review, we first provide a broad overview of the neuroelectronic devices and the basic requirements of an electrode material. We subsequently discuss the carbon family of materials and their properties that are useful in neural applications. Examples of devices fabricated using bulk and nano carbon materials are reviewed and critically compared. We then summarize the challenges, future prospects and next-generation carbon technology that can be helpful in the field of neural sciences. The article aims at providing a common platform to neuroscientists, electrochemists, biologists, microsystems engineers and carbon scientists to enable active and comprehensive efforts directed towards carbon-based neuroelectronic device fabrication.

Intracortical Microelectrode Array Unit Yield under Chronic Conditions: A Comparative Evaluation

While microelectrode arrays (MEAs) offer the promise of elucidating functional neural circuitry and serve as the basis for a cortical neuroprosthesis, the challenge of designing and demonstrating chronically reliable technology remains. Numerous studies report “chronic” data but the actual time spans and performance measures corresponding to the experimental work vary. In this study, we reviewed the experimental durations that constitute chronic studies across a range of MEA types and animal species to gain an understanding of the widespread variability in reported study duration. For rodents, which are the most commonly used animal model in chronic studies, we examined active electrode yield (AEY) for different array types as a means to contextualize the study duration variance, as well as investigate and interpret the performance of custom devices in comparison to conventional MEAs. We observed wide-spread variance within species for the chronic implantation period and an AEY that decayed linearly in rodent models that implanted commercially-available devices. These observations provide a benchmark for comparing the performance of new technologies and highlight the need for consistency in chronic MEA studies. Additionally, to fully derive performance under chronic conditions, the duration of abiotic failure modes, biological processes induced by indwelling probes, and intended application of the device are key determinants.

Multi-scale neural decoding and analysis

Objective.

Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment.

Approach.

We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes.

Main results.

We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches.

Significance.

This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.

Nanotechnology in neurosurgery: a systematic review

BACKGROUND

The application of nanotechnology in medicine encompasses an interdisciplinary field of sciences for the diagnosis, treatment, and monitoring of medical conditions. This study aims to systematically review and summarize the advances of nanotechnology applicable to neurosurgery.

METHODS

We performed a PubMed advanced search of reports exploring the advances of nanotechnology and nanomedicine relating to diagnosis, treatment, or both, in neurosurgery, for the last decade. The search was performed according to PRISMA guidelines, and the following data were extracted from each paper: title; authors; article type; PMID; DOI; year of publication; in vitro, in vivo model; nanomedical, nanotechnological material; nanofield; neurosurgical field; the application of the system; and main conclusions of the study.

RESULTS

A total of 78 original studies were included in this review. The results were organized into the following categories: functional neurosurgery, head trauma, neurodegenerative diseases, neuro-oncology, spinal surgery and peripheral nerves, vascular neurosurgery, and studies that apply to more than one field. A further categorization applied in terms of nanomedical field such as neuroimaging, neuro-nanotechnology, neuroregeneration, theranostics, and neuro-nanotherapy.

CONCLUSION

In reviewing the literature, significant advances in imaging and treatment of central nervous system diseases are underway and are expected to reach clinical practice in the next decade by the application of the rapidly evolving nanotechnology techniques.