Translational principles of deep brain stimulation

Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents

Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.

Attenuating midline thalamus bursting to mitigate absence epilepsy

Advancing the mechanistic understanding of absence epilepsy is crucial for developing new therapeutics, especially for patients unresponsive to current treatments. Utilizing a recently developed mouse model of absence epilepsy carrying the BK gain-of-function channelopathy D434G, here we report that attenuating the burst firing of midline thalamus (MLT) neurons effectively prevents absence seizures. We found that enhanced BK channel activity in the BK-D434G MLT neurons promotes synchronized bursting during the ictal phase of absence seizures. Modulating MLT neurons through pharmacological reagents, optogenetic stimulation, or deep brain stimulation effectively attenuates burst firing, leading to reduced absence seizure frequency and increased vigilance. Additionally, enhancing vigilance by amphetamine, a stimulant medication, or physical perturbation also effectively suppresses MLT bursting and prevents absence seizures. These findings suggest that the MLT is a promising target for clinical interventions. Our diverse approaches offer valuable insights for developing next generation therapeutics to treat absence epilepsy.

Topological Quantum Switching Enabled Neuroelectronic Synaptic Modulators for Brain Computer Interface

Aging and genetic-related disorders in the human brain lead to impairment of daily cognitive functions. Due to their neural synaptic complexity and the current limits of knowledge, reversing these disorders remains a substantial challenge for brain-computer interfaces (BCI). In this work, a solution is provided to potentially override aging and neurological disorder-related cognitive function loss in the human brain through the application of the authors' quantum synaptic device. To illustrate this point, a quantum topological insulator (QTI) Bi2Se2Te-based synaptic neuroelectronic device, where the electric field-induced tunable topological surface edge states and quantum switching properties make them a premier option for establishing artificial synaptic neuromodulation approaches, is designed and developed. Leveraging these unique quantum synaptic properties, the developed synaptic device provides the capability to neuromodulate distorted neural signals, leading to the reversal of age-related disorders via BCI. With the synaptic neuroelectronic characteristics of this device, excellent efficacy in treating cognitive neural dysfunctions through modulated neuromorphic stimuli is demonstrated. As a proof of concept, real-time neuromodulation of electroencephalogram (EEG) deduced distorted event-related potentials (ERP) is demonstrated by modulation of the synaptic device array.

Brain stimulation for patients with multiple sclerosis: an umbrella review of therapeutic efficacy

Multiple sclerosis patients often experience various symptoms that can greatly impact their quality of life. There are various brain stimulation techniques that have been evaluated for their ability to reduce the symptoms of multiple sclerosis. However, there is inconsistency in the specific stimulation methods used and the symptoms targeted in the existing research. This umbrella review conducted in order to evaluate the effectiveness of brain stimulation and identify limitations and gaps for further research. In this umbrella review, we conducted a searched on Web of Knowledge, PubMed, and Scopus database. We specifically looked for reviews, with or without meta-analyses, that have investigated the effects of brain stimulation methods on symptoms of multiple sclerosis. All articles were examined by AMSTAR 2 (A Measure Tool to Assess Systematic Review 2). We identified 155 articles, of which 14 were eligible for inclusion. Of those, five were qualitative studies and nine were meta-analyses. Among the included studies, four examined the use of deep brain stimulation, while ten investigated the therapeutic potential of noninvasive brain stimulation. Considering the heterogeneity of studies, the current evidence suggests that repetitive transcranial magnetic stimulation may be effective in treating pain and improving motor function, while transcranial direct current stimulation may be useful in alleviating fatigue and enhancing certain aspects of cognitive performance. Deep brain stimulation, on the other hand, appears to be effective in reducing tremors. However, further research is warranted to validate these findings and address the existing limitations in the field.

Clinical neuromodulatory effects of deep brain stimulation in disorder of consciousness: A literature review

BACKGROUND

The management of patients with disorders of consciousness (DOC) presents substantial challenges in clinical practice. Deep brain stimulation (DBS) has emerged as a potential therapeutic approach, but the lack of standardized regulatory parameters for DBS in DOC hinders definitive conclusions.

OBJECTIVE

This comprehensive review aims to provide a detailed summary of the current issues concerning patient selection, target setting, and modulation parameters in clinical studies investigating the application of DBS for DOC patients.

METHODS

A meticulous systematic analysis of the literatures was conducted, encompassing articles published from 1968 to April 2023, retrieved from reputable databases (PubMed, Embase, Medline, and Web of Science).

RESULTS

The systematic analysis of 21 eligible articles, involving 146 patients with DOC resulting from acquired brain injury or other disorders, revealed significant insights. The most frequently targeted regions were the Centromedian-parafascicular complex (CM-pf) nuclei and central thalamus (CT), both recognized for their role in regulating consciousness. However, other targets have also been explored in different studies. The stimulation frequency was predominantly set at 25 or 100 Hz, with pulse width of 120 μs, and voltages ranged from 0 to 4 V. These parameters were customized based on individual patient responses and evaluations. The overall clinical efficacy rate in all included studies was 39.7%, indicating a positive effect of DBS in a subset of DOC patients. Nonetheless, the assessment methods, follow-up durations, and outcome measures varied across studies, potentially contributing to the variability in reported efficacy rates.

CONCLUSION

Despite the challenges arising from the lack of standardized parameters, DBS shows promising potential as a therapeutic option for patients with DOC. However, there still remains the need for standardized protocols and assessment methods, which are crucial to deepen the understanding and optimizing the therapeutic potential of DBS in this specific patient population.

Cell-class-specific electric field entrainment of neural activity

Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.

Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease

PURPOSE

To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD).

METHODS

In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis.

RESULTS

Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively.

CONCLUSION

The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Flexible Organic Transistors for Biosensing: Devices and Applications

Flexible and stretchable biosensors can offer seamless and conformable biological-electronic interfaces for continuously acquiring high-fidelity signals, permitting numerous emerging applications. Organic thin film transistors (OTFTs) are ideal transducers for flexible and stretchable biosensing due to their soft nature, inherent amplification function, biocompatibility, ease of functionalization, low cost, and device diversity. In consideration of the rapid advances in flexible-OTFT-based biosensors and their broad applications, herein, a timely and comprehensive review is provided. It starts with a detailed introduction to the features of various OTFTs including organic field-effect transistors and organic electrochemical transistors, and the functionalization strategies for biosensing, with a highlight on the seminal work and up-to-date achievements. Then, the applications of flexible-OTFT-based biosensors in wearable, implantable, and portable electronics, as well as neuromorphic biointerfaces are detailed. Subsequently, special attention is paid to emerging stretchable organic transistors including planar and fibrous devices. The routes to impart stretchability, including structural engineering and material engineering, are discussed, and the implementations of stretchable organic transistors in e-skin and smart textiles are included. Finally, the remaining challenges and the future opportunities in this field are summarized.

Unraveling brain diseases: The promise of brain-on-a-chip models

Brain disorders, encompassing a wide spectrum of neurological and psychiatric conditions, present a formidable challenge in modern medicine. Despite decades of research, the intricate complexity of the human brain still eludes comprehensive understanding, impeding the development of effective treatments. Recent advancements in microfluidics and tissue engineering have led to the development of innovative platforms known as "Brain-on-a-Chip" (BoC) i.e., advanced in vitro systems that aim to replicate the microenvironment of the brain with the highest possible fidelity. This technology offers a promising test-bed for studying brain disorders at the cellular and network levels, providing insights into disease mechanisms, drug screening, and, in perspective, the development of personalized therapeutic strategies. In this review, we provide an overview of the BoC models developed over the years to model and understand the onset and progression of some of the most severe neurological disorders in terms of incidence and debilitation (stroke, Parkinson's, Alzheimer's, and epilepsy). We also report some of the cutting-edge therapeutic approaches whose effects were evaluated by means of these technologies. Finally, we discuss potential challenges, and future perspectives of the BoC models.

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

Neuroscience fundamentals relevant to neuromodulation: Neurobiology of deep brain stimulation in Parkinson's disease

Deep Brain Stimulation (DBS) has become a pivotal therapeutic approach for Parkinson's Disease (PD) and various neuropsychiatric conditions, impacting over 200,000 patients. Despite its widespread application, the intricate mechanisms behind DBS remain a subject of ongoing investigation. This article provides an overview of the current knowledge surrounding the local, circuit, and neurobiochemical effects of DBS, focusing on the subthalamic nucleus (STN) as a key target in PD management. The local effects of DBS, once thought to mimic a reversible lesion, now reveal a more nuanced interplay with myelinated axons, neurotransmitter release, and the surrounding microenvironment. Circuit effects illuminate the modulation of oscillatory activities within the basal ganglia and emphasize communication between the STN and the primary motor cortex. Neurobiochemical effects, encompassing changes in dopamine levels and epigenetic modifications, add further complexity to the DBS landscape. Finally, within the context of understanding the mechanisms of DBS in PD, the article highlights the controversial question of whether DBS exerts disease-modifying effects in PD. While preclinical evidence suggests neuroprotective potential, clinical trials such as EARLYSTIM face challenges in assessing long-term disease modification due to enrollment timing and methodology limitations. The discussion underscores the need for robust biomarkers and large-scale prospective trials to conclusively determine DBS's potential as a disease-modifying therapy in PD.

A High Precision, Wide Dynamic Range Closed-Loop Neuromodulation IC With Rapid Stimulation Artifact Recovery

This article presents a high precision, wide dynamic range (DR) closed-loop neuromodulation (CLNM) system that can completely reject stimulation artifacts (SA) and achieve rapid SA recovery. In the recorder, a novel SA quick-blanking scheme is proposed for rail-to-rail SA rejection while minimizing SA recovery time. Besides, a new analog front-end (AFE) architecture based on a frequency-shaping (FS) technique is developed to extend DR intrinsically. In the stimulator, a stimulation driver implemented with a proposed redundant crossfire (RXF) technique is incorporated to improve the effective resolution of the stimulation current. The designed CLNM system is implemented in a 180 nm Bipolar-CMOS-DMOS (BCD) process. Measurement results show that the system is capable of tolerating rail-to-rail (5 V) SA and reducing the SA recovery time from 12 ms to 0.15 ms. The FS recorder extends the DR at low frequencies (LF) to 17.5 bits to enhance tolerance to LF interferences. The proposed stimulator adopting the 4-way RXF topology improves the effective resolution to 12.75 bits without consuming much extra area and power. Animal experiments demonstrate that the designed system can acquire high-fidelity neural signals immediately after stimulation onsets, thus supporting concurrent recording and stimulation.

Fundamentals of deep brain stimulation for Parkinson's disease in clinical practice: part 1

Deep brain stimulation (DBS) is recognized as an established therapy for Parkinson's disease (PD) and other movement disorders in the light of the developments seen over the past three decades. Long-term efficacy is established for PD with documented improvement in the cardinal motor symptoms of PD and levodopa-induced complications, such as motor fluctuations and dyskinesias. Timing of patient selection is crucial to obtain optimal benefits from DBS therapy, before PD complications become irreversible. The objective of this first part review is to examine the fundamental concepts of DBS for PD in clinical practice, discussing the historical aspects, patient selection, potential effects of DBS on motor and non-motor symptoms, and the practical management of patients after surgery.

Recent Progress and Challenges of Implantable Biodegradable Biosensors

Implantable biosensors have evolved to the cutting-edge technology of personalized health care and provide promise for future directions in precision medicine. This is the reason why these devices stand to revolutionize our approach to health and disease management and offer insights into our bodily functions in ways that have never been possible before. This review article tries to delve into the important developments, new materials, and multifarious applications of these biosensors, along with a frank discussion on the challenges that the devices will face in their clinical deployment. In addition, techniques that have been employed for the improvement of the sensitivity and specificity of the biosensors alike are focused on in this article, like new biomarkers and advanced computational and data communicational models. A significant challenge of miniaturized in situ implants is that they need to be removed after serving their purpose. Surgical expulsion provokes discomfort to patients, potentially leading to post-operative complications. Therefore, the biodegradability of implants is an alternative method for removal through natural biological processes. This includes biocompatible materials to develop sensors that remain in the body over longer periods with a much-reduced immune response and better device longevity. However, the biodegradability of implantable sensors is still in its infancy compared to conventional non-biodegradable ones. Sensor design, morphology, fabrication, power, electronics, and data transmission all play a pivotal role in developing medically approved implantable biodegradable biosensors. Advanced material science and nanotechnology extended the capacity of different research groups to implement novel courses of action to design implantable and biodegradable sensor components. But the actualization of such potential for the transformative nature of the health sector, in the first place, will have to surmount the challenges related to biofouling, managing power, guaranteeing data security, and meeting today's rules and regulations. Solving these problems will, therefore, not only enhance the performance and reliability of implantable biodegradable biosensors but also facilitate the translation of laboratory development into clinics, serving patients worldwide in their better disease management and personalized therapeutic interventions.

Cell class-specific electric field entrainment of neural activity

Electric fields affect the activity of neurons and brain circuits, yet how this interaction happens at the cellular level remains enigmatic. Lack of understanding on how to stimulate the human brain to promote or suppress specific activity patterns significantly limits basic research and clinical applications. Here we study how electric fields impact the subthreshold and spiking properties of major cortical neuronal classes. We find that cortical neurons in rodent neocortex and hippocampus as well as human cortex exhibit strong and cell class-dependent entrainment that depends on the stimulation frequency. Excitatory pyramidal neurons with their typically slower spike rate entrain to slow and fast electric fields, while inhibitory classes like Pvalb and SST with their fast spiking predominantly phase lock to fast fields. We show this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties of spike-field and class-specific entrainment are present in cells across cortical areas and species (mouse and human). These findings open the door to the design of selective and class-specific neuromodulation technologies.

Janus microparticles-based targeted and spatially-controlled piezoelectric neural stimulation via low-intensity focused ultrasound

Electrical stimulation is a fundamental tool in studying neural circuits, treating neurological diseases, and advancing regenerative medicine. Injectable, free-standing piezoelectric particle systems have emerged as non-genetic and wireless alternatives for electrode-based tethered stimulation systems. However, achieving cell-specific and high-frequency piezoelectric neural stimulation remains challenging due to high-intensity thresholds, non-specific diffusion, and internalization of particles. Here, we develop cell-sized 20 μm-diameter silica-based piezoelectric magnetic Janus microparticles (PEMPs), enabling clinically-relevant high-frequency neural stimulation of primary neurons under low-intensity focused ultrasound. Owing to its functionally anisotropic design, half of the PEMP acts as a piezoelectric electrode via conjugated barium titanate nanoparticles to induce electrical stimulation, while the nickel-gold nanofilm-coated magnetic half provides spatial and orientational control on neural stimulation via external uniform rotating magnetic fields. Furthermore, surface functionalization with targeting antibodies enables cell-specific binding/targeting and stimulation of dopaminergic neurons. Taking advantage of such functionalities, the PEMP design offers unique features towards wireless neural stimulation for minimally invasive treatment of neurological diseases.

Monolithic silicon for high spatiotemporal translational photostimulation

Electrode-based electrical stimulation underpins several clinical bioelectronic devices, including deep-brain stimulators1,2 and cardiac pacemakers3. However, leadless multisite stimulation is constrained by the technical difficulties and spatial-access limitations of electrode arrays. Optogenetics offers optically controlled random access with high spatiotemporal capabilities, but clinical translation poses challenges4-6. Here we show tunable spatiotemporal photostimulation of cardiac systems using a non-genetic platform based on semiconductor-enabled biomodulation interfaces. Through spatiotemporal profiling of photoelectrochemical currents, we assess the magnitude, precision, accuracy and resolution of photostimulation in four leadless silicon-based monolithic photoelectrochemical devices. We demonstrate the optoelectronic capabilities of the devices through optical overdrive pacing of cultured cardiomyocytes (CMs) targeting several regions and spatial extents, isolated rat hearts in a Langendorff apparatus, in vivo rat hearts in an ischaemia model and an in vivo mouse heart model with transthoracic optical pacing. We also perform the first, to our knowledge, optical override pacing and multisite pacing of a pig heart in vivo. Our systems are readily adaptable for minimally invasive clinical procedures using our custom endoscopic delivery device, with which we demonstrate closed-thoracic operations and endoscopic optical stimulation. Our results indicate the clinical potential of the leadless, lightweight and multisite photostimulation platform as a pacemaker in cardiac resynchronization therapy (CRT), in which lead-placement complications are common.

Neuronal and synaptic adaptations underlying the benefits of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) is a well-established and effective treatment for patients with advanced Parkinson's disease (PD), yet its underlying mechanisms remain enigmatic. Optogenetics, primarily conducted in animal models, provides a unique approach that allows cell type- and projection-specific modulation that mirrors the frequency-dependent stimulus effects of DBS. Opto-DBS research in animal models plays a pivotal role in unraveling the neuronal and synaptic adaptations that contribute to the efficacy of DBS in PD treatment. DBS-induced neuronal responses rely on a complex interplay between the distributions of presynaptic inputs, frequency-dependent synaptic depression, and the intrinsic excitability of postsynaptic neurons. This orchestration leads to conversion of firing patterns, enabling both antidromic and orthodromic modulation of neural circuits. Understanding these mechanisms is vital for decoding position- and programming-dependent effects of DBS. Furthermore, patterned stimulation is emerging as a promising strategy yielding long-lasting therapeutic benefits. Research on the neuronal and synaptic adaptations to DBS may pave the way for the development of more enduring and precise modulation patterns. Advanced technologies, such as adaptive DBS or directional electrodes, can also be integrated for circuit-specific neuromodulation. These insights hold the potential to greatly improve the effectiveness of DBS and advance PD treatment to new levels.

Altered beta band spatial-temporal interactions during negative emotional processing in major depressive disorder: An MEG study

BACKGROUND

The mood-concordance bias is a key feature of major depressive disorder (MDD), but the spatiotemporal neural activity associated with emotional processing in MDD remains unclear. Understanding the dysregulated connectivity patterns during emotional processing and their relationship with clinical symptoms could provide insights into MDD neuropathology.

METHODS

We enrolled 108 MDD patients and 64 healthy controls (HCs) who performed an emotion recognition task during magnetoencephalography recording. Network-based statistics (NBS) was used to analyze whole-brain functional connectivity (FC) across different frequency ranges during distinct temporal periods. The relationship between the aberrant FC and affective symptoms was explored.

RESULTS

MDD patients exhibited decreased FC strength in the beta band (13-30 Hz) compared to HCs. During the early stage of emotional processing (0-100 ms), reduced FC was observed between the left parahippocampal gyrus and the left cuneus. In the late stage (250-400 ms), aberrant FC was primarily found in the cortex-limbic-striatum systems. Moreover, the FC strength between the right fusiform gyrus and left thalamus, and between the left calcarine fissure and left inferior temporal gyrus were negatively associated with Hamilton Depression Rating Scale (HAMD) scores.

LIMITATIONS

Medication information was not involved.

CONCLUSION

MDD patients exhibited abnormal temporal-spatial neural interactions in the beta band, ranging from early sensory to later cognitive processing stages. These aberrant interactions involve the cortex-limbic-striatum circuit. Notably, aberrant FC in may serve as a potential biomarker for assessing depression severity.

Restoring the firing activity of ventral tegmental area neurons by lateral hypothalamic deep brain stimulation following morphine administration in rats: LH DBS and the spiking activity of VTA neurons

We have previously shown that high-frequency deep brain stimulation (DBS) of the lateral hypothalamus (LH) compromises morphine-induced addiction-like behavior in rats. The exact mechanism underlying this effect is not known. Here, we investigated the assumption that DBS in the LH influences the firing activity of neurons in the ventral tegmental area (VTA). To that end, male Wistar rats received morphine (5 mg/kg; s.c.) for three days and underwent extracellular single unit recording under general anesthesia one day later. During the recording, the rats received an intraoperative injection of morphine (5 mg/kg; s.c.) plus DBS in the LH (130 Hz pulse frequency, 150 μA amplitude, and 100 μs pulse width). One group of animals also received preoperative DBS after each morphine injection before the recording. The spiking frequency of VTA neurons was measured at three successive phases: (1) baseline (5-15 min); (2) DBS-on (morphine + DBS for 30 min); and (3) After-DBS (over 30 min after termination of DBS). Results showed that morphine suppressed the firing activity of a large population of non-DA neurons, whereas it activated most DA neurons. Intraoperative DBS reversed morphine suppression of non-DA firing, but did not alter the excitatory effect of morphine on DA neurons firing. With repeated preoperative application of DBS, non-DA neurons returned to the morphine-induced suppressive state, but DA neurons released from the excitatory effect of morphine. It is concluded that the development of morphine reward is associated with a hypoactivity of VTA non-DA neurons and a hyperactivity of DA neurons, and that DBS modulation of the spiking activity may contribute to the blockade of morphine addiction-like behavior.

Low-intensity ultrasound stimulation modulates time-frequency patterns of cerebral blood oxygenation and neurovascular coupling of mouse under peripheral sensory stimulation state

Previous studies have demonstrated that transcranial ultrasound stimulation (TUS) not only modulates cerebral hemodynamics, neural activity, and neurovascular coupling characteristics in resting samples but also exerts a significant inhibitory effect on the neural activity in task samples. However, the effect of TUS on cerebral blood oxygenation and neurovascular coupling in task samples remains to be elucidated. To answer this question, we first used forepaw electrical stimulation of the mice to elicit the corresponding cortical excitation, and then stimulated this cortical region using different modes of TUS, and simultaneously recorded the local field potential using electrophysiological acquisition and hemodynamics using optical intrinsic signal imaging. The results indicate that for the mice under peripheral sensory stimulation state, TUS with a duty cycle of 50% can (1) enhance the amplitude of cerebral blood oxygenation signal, (2) reduce the time-frequency characteristics of evoked potential, (3) reduce the strength of neurovascular coupling in time domain, (4) enhance the strength of neurovascular coupling in frequency domain, and (5) reduce the time-frequency cross-coupling of neurovasculature. The results of this study indicate that TUS can modulate the cerebral blood oxygenation and neurovascular coupling in peripheral sensory stimulation state mice under specific parameters. This study opens up a new area of investigation for potential applicability of TUS in brain diseases related to cerebral blood oxygenation and neurovascular coupling.

Water-soluble conjugated polymers for bioelectronic systems

Bioelectronics is an interdisciplinary field of research that aims to establish a synergy between electronics and biology. Contributing to a deeper understanding of bioelectronic processes and the built bioelectronic systems, a variety of new phenomena, mechanisms and concepts have been derived in the field of biology, medicine, energy, artificial intelligence science, etc. Organic semiconductors can promote the applications of bioelectronics in improving original performance and creating new features for organisms due to their excellent photoelectric and electrical properties. Recently, water-soluble conjugated polymers (WSCPs) have been employed as a class of ideal interface materials to regulate bioelectronic processes between biological systems and electronic systems, relying on their satisfying ionic conductivity, water-solubility, good biocompatibility and the additional mechanical and electrical properties. In this review, we summarize the prominent contributions of WSCPs in the aspect of the regulation of bioelectronic processes and highlight the latest advances in WSCPs for bioelectronic applications, involving biosynthetic systems, photosynthetic systems, biophotovoltaic systems, and bioelectronic devices. The challenges and outlooks of WSCPs in designing high-performance bioelectronic systems are also discussed.

A systematic review of the effects of transcranial photobiomodulation on brain activity in humans

In recent years, transcranial photobiomodulation (tPBM) has been developing as a promising method to protect and repair brain tissues against damages. The aim of our systematic review is to examine the results available in the literature concerning the efficacy of tPBM in changing brain activity in humans, either in healthy individuals, or in patients with neurological diseases. Four databases were screened for references containing terms encompassing photobiomodulation, brain activity, brain imaging, and human. We also analysed the quality of the included studies using validated tools. Results in healthy subjects showed that even after a single session, tPBM can be effective in influencing brain activity. In particular, the different transcranial approaches - using a focal stimulation or helmet for global brain stimulation - seemed to act at both the vascular level by increasing regional cerebral blood flow (rCBF) and at the neural level by changing the activity of the neurons. In addition, studies also showed that even a focal stimulation was sufficient to induce a global change in functional connectivity across brain networks. Results in patients with neurological disease were sparser; nevertheless, they indicated that tPBM could improve rCBF and functional connectivity in several regions. Our systematic review also highlighted the heterogeneity in the methods and results generated, together with the need for more randomised controlled trials in patients with neurological diseases. In summary, tPBM could be a promising method to act on brain function, but more consistency is needed in order appreciate fully the underlying mechanisms and the precise outcomes.

Nanomedicine and nanobiotechnology applications of magnetoelectric nanoparticles

Unlike any other nanoparticles known to date, magnetoelectric nanoparticles (MENPs) can generate relatively strong electric fields locally via the application of magnetic fields and, vice versa, have their magnetization change in response to an electric field from the microenvironment. Hence, MENPs can serve as a wireless two-way interface between man-made devices and physiological systems at the molecular level. With the recent development of room-temperature biocompatible MENPs, a number of novel potential medical applications have emerged. These applications include wireless brain stimulation and mapping/recording of neural activity in real-time, targeted delivery across the blood-brain barrier (BBB), tissue regeneration, high-specificity cancer cures, molecular-level rapid diagnostics, and others. Several independent in vivo studies, using mice and nonhuman primates models, demonstrated the capability to deliver MENPs in the brain across the BBB via intravenous injection or, alternatively, bypassing the BBB via intranasal inhalation of the nanoparticles. Wireless deep brain stimulation with MENPs was demonstrated both in vitro and in vivo in different rodents models by several independent groups. High-specificity cancer treatment methods as well as tissue regeneration approaches with MENPs were proposed and demonstrated in in vitro models. A number of in vitro and in vivo studies were dedicated to understand the underlying mechanisms of MENPs-based high-specificity targeted drug delivery via application of d.c. and a.c. magnetic fields. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery > Emerging Technologies.

From disabled tourists to impaired cyborg tourists: What would it take to transform?

Despite the media reports and governments promoting tourism as a fundamental right for everyone, traveling is still not accessible for disabled people. This study has highlighted the need to make tourists with disabilities accessable for inaccessible destinations. Cyborg products in the form of technological implants can make tourists with disabilities accessable for inaccessible destinations. Since tourists with a mobility disability (TMD) will be one of the primary beneficiaries of technological implants, little is known about their acceptance of technological implants during traveling.Therefore, this study assesses the willingness of TMD to use technological implants during traveling through a qualitative research approach. The results from thematic analysis identified two main themes: the use of assistive devices during traveling with four sub-themes (freedom of traveling, physical and attitudinal barriers, cost, and additional assistance and battery issues), and drivers of impaired cyborg tourists with seven sub-themes (independence, improved well-being, convenience/ease of use, social inclusion, positive emotions, motivation, and other issues). The study contributed to the literature by introducing drivers of impaired cyborg tourists along with previously identified concepts. The results also provided implications for the stakeholders of the tourism industry.

Deep brain stimulation of the lateral hypothalamus to block morphine reward: Does the intensity of stimulation matter?

It has been shown that high-frequency deep brain stimulation (DBS) of the lateral hypothalamus (LH) prevents morphine-induced conditioned place preference (CPP) in rats. However, our previous study demonstrated that the application of DBS at 150 µA did not block morphine CPP in all rats. Here, we investigated the possibility to completely block morphine CPP by increasing the intensity of LH DBS. Morphine reward was assessed by the CPP paradigm in male Wistar rats. DBS was applied in the LH during the conditioning trials with morphine (5 mg/kg, S.C.) at 130 Hz pulse frequency, 100 µs pulse duration, and either 150 µA or 200 µA pulse amplitude. Results showed that repeated morphine injections produced a robust CPP that was blocked partially by DBS at 150 µA and completely by DBS at 200 µA. Response rate was 47% with 150-µA and 100% with 200-µA stimulation. DBS treatment was not associated with changes in motor activity. In conclusion, the development of morphine reward was modulated by LH DBS in an intensity-dependent manner.

Commonly Overlooked Factors in Biocompatibility Studies of Neural Implants

Biocompatibility of cutting-edge neural implants, surgical tools and techniques, and therapeutic technologies is a challenging concept that can be easily misjudged. For example, neural interfaces are routinely gauged on how effectively they determine active neurons near their recording sites. Tissue integration and toxicity of neural interfaces are frequently assessed histologically in animal models to determine tissue morphological and cellular changes in response to surgical implantation and chronic presence. A disconnect between histological and efficacious biocompatibility exists, however, as neuronal numbers frequently observed near electrodes do not match recorded neuronal spiking activity. The downstream effects of the myriad surgical and experimental factors involved in such studies are rarely examined when deciding whether a technology or surgical process is biocompatible. Such surgical factors as anesthesia, temperature excursions, bleed incidence, mechanical forces generated, and metabolic conditions are known to have strong systemic and thus local cellular and extracellular consequences. Many tissue markers are extremely sensitive to the physiological state of cells and tissues, thus significantly impacting histological accuracy. This review aims to shed light on commonly overlooked factors that can have a strong impact on the assessment of neural biocompatibility and to address the mismatch between results stemming from functional and histological methods.

Deep brain stimulation by blood-brain-barrier-crossing piezoelectric nanoparticles generating current and nitric oxide under focused ultrasound

Deep brain stimulation via implanted electrodes can alleviate neuronal disorders. However, its applicability is constrained by side effects resulting from the insertion of electrodes into the brain. Here, we show that systemically administered piezoelectric nanoparticles producing nitric oxide and generating direct current under high-intensity focused ultrasound can be used to stimulate deep tissue in the brain. The release of nitric oxide temporarily disrupted tight junctions in the blood-brain barrier, allowing for the accumulation of the nanoparticles into brain parenchyma, and the piezoelectrically induced output current stimulated the release of dopamine by dopaminergic neuron-like cells. In a mouse model of Parkinson's disease, the ultrasound-responsive nanoparticles alleviated the symptoms of the disease without causing overt toxicity. The strategy may inspire the development of other minimally invasive therapies for neurodegenerative diseases.

Fornix degeneration in risk factors of Alzheimer's disease, possible trigger of cognitive decline

Risk factors of late-onset Alzheimer's disease (AD) such as aging, type 2 diabetes, obesity, heart failure, and traumatic brain injury can facilitate the appearance of cognitive decline and dementia by triggering cerebrovascular pathology and neuroinflammation. White matter (WM) microstructure and function are especially vulnerable to these conditions. Microstructural WM changes, assessed with diffusion weighted magnetic resonance imaging, can already be detected at preclinical stages of AD, and in the presence of the aforementioned risk factors. Particularly, the limbic system and cortico-cortical association WM tracts, which myelinate late during brain development, degenerate at the earliest stages. The fornix, a C-shaped WM tract that originates from the hippocampus, is one of the limbic tracts that shows early microstructural changes. Fornix integrity is necessary for ensuring an intact executive function and memory performance. Thus, a better understanding of the mechanisms that cause fornix degeneration is critical in the development of therapeutic strategies aiming to prevent cognitive decline in populations at risk. In this literature review, i) we deepen the idea that partial loss of forniceal integrity is an early event in AD, ii) we describe the role that common risk factors of AD can play in the degeneration of the fornix, and iii) we discuss some potential cellular and physiological mechanisms of WM degeneration in the scenario of cerebrovascular disease and inflammation.

Deep Brain Stimulation of the Interposed Cerebellar Nuclei in a Conditional Genetic Mouse Model with Dystonia

Dystonia is a neurological disease that is currently ranked as the third most common motor disorder. Patients exhibit repetitive and sometimes sustained muscle contractions that cause limb and body twisting and abnormal postures that impair movement. Deep brain stimulation (DBS) of the basal ganglia and thalamus can be used to improve motor function when other treatment options fail. Recently, the cerebellum has garnered interest as a DBS target for treating dystonia and other motor disorders. Here, we describe a procedure for targeting DBS electrodes to the interposed cerebellar nuclei to correct motor dysfunction in a mouse model with dystonia. Targeting cerebellar outflow pathways with neuromodulation opens new possibilities for using the expansive connectivity of the cerebellum to treat motor and non-motor diseases.

Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling

Traditionally, in neuroimaging, model-free analyses are used to find significant differences between brain states via signal detection theory. Depending on the a priori assumptions about the underlying data, different spatio-temporal features can be analysed. Alternatively, model-based techniques infer features from the data and compare significance from model parameters. However, to assess transitions from one brain state to another remains a challenge in current paradigms. Here, we introduce a "Dynamic Sensitivity Analysis" framework that quantifies transitions between brain states in terms of stimulation ability to rebalance spatio-temporal brain activity towards a target state such as healthy brain dynamics. In practice, it means building a whole-brain model fitted to the spatio-temporal description of brain dynamics, and applying systematic stimulations in-silico to assess the optimal strategy to drive brain dynamics towards a target state. Further, we show how Dynamic Sensitivity Analysis extends to various brain stimulation paradigms, ultimately contributing to improving the efficacy of personalised clinical interventions.

Radio-frequency induced heating of intra-cranial EEG electrodes: The more the colder?

Many neurological disorders are analyzed and treated with implantable electrodes. Many patients with such electrodes have to undergo MRI examinations - often unrelated to their implant - at the risk of radio-frequency induced heating. The number of electrode contact sites of these implants keeps increasing due to improvements in manufacturing and computational algorithms. Electrode grids with multiple receive channels couple to the RF fields present in MRI, but, due to their proximity, a combination of leads has a coupling response which is not a superposition of the individual leads' response. To investigate the problem of RF-induced heating of coupled multi-lead implants, temperature mapping was performed on a set of intra-cranial electroencephalogram (icEEG) electrode grid prototypes with increasing number of contact sites (1-16). Additionally, electric field measurements were used to investigate the radio-frequency heating characteristics of the implants in different media combinations, simulating the device being partially immersed inside the patient. MR measurements show RF-induced heating up to 19.6 K for the single electrode, reducing monotonically with larger number of contact sites to a minimum of 0.9 K for the largest grid. The SAR calculated from temperature measurements agrees well with electric field mapping: The same trend is visible for different insertion lengths, however, the energy dissipated by the whole implant varies with the grid size and insertion length. Thus, in the tested circumstances, a larger electrode number either reduced or had a similar risk of RF induced heating, indicating, that the size of electrode grids is a design parameter, which can be used to change an implants RF response and in turn to reduce the risk of RF induced heating and improve the safety of patient with neuro-implants undergoing MRI examinations.

Galvanic vestibular stimulation down-regulated NMDA receptors in vestibular nucleus of PD model

Parkinsonian symptoms relief by electrical stimulation is constructed by modulating neural network activity, and Galvanic vestibular stimulation (GVS) is known to affect the neural activity for motor control by activating the vestibular afferents. However, its underlying mechanism is still elusive. Due to the tight link from the peripheral vestibular organ to vestibular nucleus (VN), the effect by GVS was investigated to understand the neural mechanism. Using Sprague Dawley (SD) rats, behavioral response, extracellular neural recording, and immunohistochemistry in VN were conducted before and after the construction of Parkinson's disease (PD) model. Animals' locomotion was tested using rota-rod, and single extracellular neuronal activity was recorded in VN. The immunohistochemistry detected AMPA and NMDA receptors in VN to assess the effects by different amounts of electrical charge (0.018, 0.09, and 0.18 coulombs) as well as normal and PD with no GVS. All PD models showed the motor impairment, and the loss of TH⁺ neurons in medial forebrain bundle (mfb) and striatum was observed. Sixty-five neuronal extracellular activities (32 canal & 33 otolith) were recorded, but no significant difference in the resting firing rates and the kinetic responding gain were found in the PD models. On the other hand, the numbers of AMPA and NMDA receptors increased after the construction of PD model, and the effect by GVS was significantly evident in the change of NMDA receptors (p < 0.018). In conclusion, the increased glutamate receptors in PD models were down-regulated by GVS, and the plastic modulation mainly occurred through NMDA receptor in VN.

Strength-dependent perturbation of whole-brain model working in different regimes reveals the role of fluctuations in brain dynamics

Despite decades of research, there is still a lack of understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used whole-brain computational models capable of presenting different dynamical regimes to reproduce empirical data's turbulence level. We showed that the model's fluctuations regime fitted to turbulence more faithfully reproduces the empirical functional connectivity compared to oscillatory and noise regimes. By applying global and local strength-dependent perturbations and subsequently measuring the responsiveness of the model, we revealed each regime's computational capacity demonstrating that brain dynamics is shifted towards fluctuations to provide much-needed flexibility. Importantly, fluctuation regime stimulation in a brain region within a given resting state network modulates that network, aligned with previous empirical and computational studies. Furthermore, this framework generates specific, testable empirical predictions for human stimulation studies using strength-dependent rather than constant perturbation. Overall, the whole-brain models fitted to the level of empirical turbulence together with functional connectivity unveil that the fluctuation regime best captures empirical data, and the strength-dependent perturbative framework demonstrates how this regime provides maximal flexibility to the human brain.

Organic Neuroelectronics: From Neural Interfaces to Neuroprosthetics

Requirements and recent advances in research on organic neuroelectronics are outlined herein. Neuroelectronics such as neural interfaces and neuroprosthetics provide a promising approach to diagnose and treat neurological diseases. However, the current neural interfaces are rigid and not biocompatible, so they induce an immune response and deterioration of neural signal transmission. Organic materials are promising candidates for neural interfaces, due to their mechanical softness, excellent electrochemical properties, and biocompatibility. Also, organic nervetronics, which mimics functional properties of the biological nerve system, is being developed to overcome the limitations of the complex and energy-consuming conventional neuroprosthetics that limit long-term implantation and daily-life usage. Examples of organic materials for neural interfaces and neural signal recordings are reviewed, recent advances of organic nervetronics that use organic artificial synapses are highlighted, and then further requirements for neuroprosthetics are discussed. Finally, the future challenges that must be overcome to achieve ideal organic neuroelectronics for next-generation neuroprosthetics are discussed.

Intracranial direct electrical mapping reveals the functional architecture of the human basal ganglia

The basal ganglia play a key role in integrating a variety of human behaviors through the cortico–basal ganglia–thalamo–cortical loops. Accordingly, basal ganglia disturbances are implicated in a broad range of debilitating neuropsychiatric disorders. Despite accumulating knowledge of the basal ganglia functional organization, the neural substrates and circuitry subserving functions have not been directly mapped in humans. By direct electrical stimulation of distinct basal ganglia regions in 35 refractory epilepsy patients undergoing stereoelectroencephalography recordings, we here offer currently the most complete overview of basal ganglia functional characterization, extending not only to the expected sensorimotor responses, but also to vestibular sensations, autonomic responses, cognitive and multimodal effects. Specifically, some locations identified responses weren’t predicted by the model derived from large-scale meta-analyses. Our work may mark an important step toward understanding the functional architecture of the human basal ganglia and provide mechanistic explanations of non-motor symptoms in brain circuit disorders.

Direct electrical stimulation of the basal ganglia using implanted SEEG electrodes produced a variety of motor and non-motor effects in human participants, providing insight into the functional architecture of this key brain region.

Multitasking smart hydrogels based on the combination of alginate and poly(3,4-ethylenedioxythiophene) properties: A review

Poly(3,4-ethylenedioxythiophene) (PEDOT), a very stable and biocompatible conducting polymer, and alginate (Alg), a natural water-soluble polysaccharide mainly found in the cell wall of various species of brown algae, exhibit very different but at the same complementary properties. In the last few years, the remarkable capacity of Alg to form hydrogels and the electro-responsive properties of PEDOT have been combined to form not only layered composites (PEDOT-Alg) but also interpenetrated multi-responsive PEDOT/Alg hydrogels. These materials have been found to display outstanding properties, such as electrical conductivity, piezoelectricity, biocompatibility, self-healing and re-usability properties, pH and thermoelectric responsiveness, among others. Consequently, a wide number of applications are being proposed for PEDOT-Alg composites and, especially, PEDOT/Alg hydrogels, which should be considered as a new kind of hybrid material because of the very different chemical nature of the two polymeric components. This review summarizes the applications of PEDOT-Alg and PEDOT/Alg in tissue interfaces and regeneration, drug delivery, sensors, microfluidics, energy storage and evaporators for desalination. Special attention has been given to the discussion of multi-tasking applications, while the new challenges to be tackled based on aspects not yet considered in either of the two polymers have also been highlighted.

A PVT-Robust AFE-Embedded Error-Feedback Noise-Shaping SAR ADC With Chopper-Based Passive High-Pass IIR Filtering for Direct Neural Recording

This paper presents a PVT-robust error-feedback (EF) noise-shaping SAR (NS-SAR) ADC for direct neural-signal recording. For closed-loop bidirectional neural interfaces enabling the next generation neurological devices, a wide-dynamic-range neural recording circuit is required to accommodate stimulation artifacts. A recording structure using an NS-SAR ADC can be a good candidate because the high resolution and wide dynamic range can be obtained with a low oversampling ratio and power consumption. However, NS-SAR ADCs require an additional gain stage to obtain a well-shaped noise transfer function (NTF), and a dynamic amplifier is often used as the gain stage to minimize power overhead at the cost of vulnerability to PVT variations. To overcome this limitation, the proposed work reutilizes the capacitive-feedback amplifier, which is the analog front-end of the neural recording circuit, as a PVT-robust gain stage to achieve a reliable NS performance. In addition, a new chopper-based implementation of a passive high-pass IIR filter is proposed, achieving an improved NTF compared to prior EF NS-SAR ADCs. Fabricated in a 180-nm CMOS process, the proposed NS-SAR ADC consumes 4.3-μW power and achieves a signal-to-noise-and-distortion ratio (SNDR) of 71.7 dB and 82.7 dB for a bandwidth of 5 kHz and 300 Hz, resulting in a Schreier figure of merit (FOM) of 162.4 dB and 162.1 dB, respectively. Direct neural recording using the proposed NS-SAR ADC is demonstrated successfully in vivo, and also its tolerance against stimulation artifacts is validated in vitro.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Implantable acousto-optic window for monitoring ultrasound-mediated neuromodulation in vivo

Significance: Ultrasound has recently received considerable attention in neuroscience because it provides noninvasive control of deep brain activity. Although the feasibility of ultrasound stimulation has been reported in preclinical and clinical settings, its mechanistic understanding remains limited. While optical microscopy has become the "gold standard" tool for investigating population-level neural functions in vivo, its application for ultrasound neuromodulation has been technically challenging, as most conventional ultrasonic transducers are not designed to be compatible with optical microscopy. Aim: We aimed to develop a transparent acoustic transducer based on a glass coverslip called the acousto-optic window (AOW), which simultaneously provides ultrasound neuromodulation and microscopic monitoring of neural responses in vivo. Approach: The AOW was fabricated by the serial deposition of transparent acoustic stacks on a circular glass coverslip, comprising a piezoelectric material, polyvinylidene fluoride-trifluoroethylene, and indium-tin-oxide electrodes. The fabricated AOW was implanted into a transgenic neural-activity reporter mouse after open craniotomy. Two-photon microscopy was used to observe neuronal activity in response to ultrasonic stimulation through the AOW. Results: The AOW allowed microscopic imaging of calcium activity in cortical neurons in response to ultrasound stimulation. The optical transparency was ∼ 40 % over the visible and near-infrared spectra, and the ultrasonic pressure was 0.035 MPa at 10 MHz corresponding to 10    mW / cm 2 . In anesthetized Gad2-GCaMP6-tdTomato mice, we observed robust ultrasound-evoked activation of inhibitory cortical neurons at depths up to 200    μ m . Conclusions: The AOW is an implantable ultrasonic transducer that is broadly compatible with optical imaging modalities. The AOW will facilitate our understanding of ultrasound neuromodulation in vivo.

Unifying turbulent dynamics framework distinguishes different brain states

Significant advances have been made by identifying the levels of synchrony of the underlying dynamics of a given brain state. This research has demonstrated that non-conscious dynamics tend to be more synchronous than in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that different brain states are underpinned by dissociable spatiotemporal dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep and disorders of consciousness after coma). The model-free approach was based on Kuramoto’s turbulence framework using coupled oscillators. This was extended by a measure of the information cascade across spatial scales. Complementarily, the model-based approach used exhaustive in silico perturbations of whole-brain models fitted to these measures. This allowed studying of the information encoding capabilities in given brain states. Overall, this framework demonstrates that elements from turbulence theory provide excellent tools for describing and differentiating between brain states.

A unifying turbulent dynamics framework using both model-free and modelbased measures of whole-brain information provides insights into brain states.

Gentle Patterning Approaches toward Compatibility with Bio-Organic Materials and Their Environmental Aspects

Advances in material science, bioelectronic, and implantable medicine combined with recent requests for eco-friendly materials and technologies inevitably formulate new challenges for nano- and micropatterning techniques. Overall, the importance of creating micro- and nanostructures is motivated by a large manifold of fundamental and applied properties accessible only at the nanoscale. Lithography is a crucial family of fabrication methods to create prototypes and produce devices on an industrial scale. The pure trend in the miniaturization of critical electronic semiconducting components has been recently enhanced by implementing bio-organic systems in electronics. So far, significant efforts have been made to find novel lithographic approaches and develop old ones to reach compatibility with delicate bio-organic systems and minimize the impact on the environment. Herein, such delicate materials and sophisticated patterning techniques are briefly reviewed.

Things you wanted to know (but might have been afraid to ask) about how and why to explore and modulate brain plasticity with non-invasive neurostimulation technologies

Brain plasticity can be defined as the ability of local and extended neural systems to organize either the structure and/or the function of their connectivity patterns to better adapt to changes of our inner/outer environment and optimally respond to new challenging behavioral demands. Plasticity has been traditionally conceived as a spontaneous phenomenon naturally occurring during pre and postnatal development, tied to learning and memory processes, or enabled following neural damage and their rehabilitation. Such effects can be easily observed and measured but remain hard to harness or to tame 'at will'. Non-invasive brain stimulation (NIBS) technologies offer the possibility to engage plastic phenomena, and use this ability to characterize the relationship between brain regions, networks and their functional connectivity patterns with cognitive process or disease symptoms, to estimate cortical malleability, and ultimately contribute to neuropsychiatric therapy and rehabilitation. NIBS technologies are unique tools in the field of fundamental and clinical research in humans. Nonetheless, their abilities (and also limitations) remain rather unknown and in the hands of a small community of experts, compared to widely established methods such as functional neuroimaging (fMRI) or electrophysiology (EEG, MEG). In the current review, we first introduce the features, mechanisms of action and operational principles of the two most widely used NIBS methods, Transcranial Magnetic Stimulation (TMS) and Transcranial Current Stimulation (tCS), for exploratory or therapeutic purposes, emphasizing their bearings on neural plasticity mechanisms. In a second step, we walk the reader through two examples of recent domains explored by our team to further emphasize the potential and limitations of NIBS to either explore or improve brain function in healthy individuals and neuropsychiatric populations. A final outlook will identify a series of future topics of interest that can foster progress in the field and achieve more effective manipulation of brain plasticity and interventions to explore and improve cognition and treat the symptoms of neuropsychiatric diseases.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Excitatory deep brain stimulation quenches beta oscillations arising in a computational model of the subthalamo-pallidal loop

Parkinson’s disease (PD) is associated with abnormal \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β band oscillations (13–30 Hz) in the cortico-basal ganglia circuits. Abnormally increased striato-pallidal inhibition and strengthening the synaptic coupling between subthalamic nucleus (STN) and globus pallidus externa (GPe), due to the loss of dopamine, are considered as the potential sources of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations in the basal ganglia. Deep brain stimulation (DBS) of the basal ganglia subregions is known as a way to reduce the pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations and motor deficits related to PD. Despite the success of the DBS, its underlying mechanism is poorly understood and, there is controversy about the inhibitory or excitatory role of the DBS in the literature. Here, we utilized a computational network model of basal ganglia which consists of STN, GPe, globus pallidus interna, and thalamic neuronal population. This model can reproduce healthy and pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations similar to what has been observed in experimental studies. Using this model, we investigated the effect of DBS to understand whether its effect is excitatory or inhibitory. Our results show that the excitatory DBS is able to quench the pathological synchrony and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations, while, applying inhibitory DBS failed to quench the PD signs. In light of simulation results, we conclude that the effect of the DBS on its target is excitatory.

Wearable Bioelectronics for Chronic Wound Management

Chronic wounds are a major healthcare issue and can adversely affect the lives of millions of patients around the world. The current wound management strategies have limited clinical efficacy due to labor-intensive lab analysis requirements, need for clinicians' experiences, long-term and frequent interventions, limiting therapeutic efficiency and applicability. The growing field of flexible bioelectronics enables a great potential for personalized wound care owing to its advantages such as wearability, low-cost, and rapid and simple application. Herein, recent advances in the development of wearable bioelectronics for monitoring and management of chronic wounds are comprehensively reviewed. First, the design principles and the key features of bioelectronics that can adapt to the unique wound milieu features are introduced. Next, the current state of wound biosensors and on-demand therapeutic systems are summarized and highlighted. Furthermore, we discuss the design criteria of the integrated closed loop devices. Finally, the future perspectives and challenges in wearable bioelectronics for wound care are discussed.

Brain pathological changes during neurodegenerative diseases and their identification methods: How does QSM perform in detecting this process?

The presence of iron is essential for many biological processes in the body. But sometimes, for various reasons, the amount of iron deposition in different areas of the brain increases, which leads to problems related to the nervous system. Quantitative susceptibility mapping (QSM) is one of the newest magnetic resonance imaging (MRI)-based methods for assessing iron accumulation in target areas. This Narrative Review article aims to evaluate the performance of QSM compared to other methods of assessing iron deposition in the clinical field. Based on the results, we introduced related basic definitions, some neurodegenerative diseases, methods of examining iron deposition in these diseases, and their advantages and disadvantages. This article states that the QSM method can be introduced as a new, reliable, and non-invasive technique for clinical evaluations.

The Convergence Model of Brain Reward Circuitry: Implications for Relief of Treatment-Resistant Depression by Deep-Brain Stimulation of the Medial Forebrain Bundle

Deep-brain stimulation of the medial forebrain bundle (MFB) can provide effective, enduring relief of treatment-resistant depression. Panksepp provided an explanatory framework: the MFB constitutes the core of the neural circuitry subserving the anticipation and pursuit of rewards: the “SEEKING” system. On that view, the SEEKING system is hypoactive in depressed individuals; background electrical stimulation of the MFB alleviates symptoms by normalizing activity. Panksepp attributed intracranial self-stimulation to excitation of the SEEKING system in which the ascending projections of midbrain dopamine neurons are an essential component. In parallel with Panksepp’s qualitative work, intracranial self-stimulation has long been studied quantitatively by psychophysical means. That work argues that the predominant directly stimulated substrate for MFB self-stimulation are myelinated, non-dopaminergic fibers, more readily excited by brief electrical current pulses than the thin, unmyelinated axons of the midbrain dopamine neurons. The series-circuit hypothesis reconciles this view with the evidence implicating dopamine in MFB self-stimulation as follows: direct activation of myelinated MFB fibers is rewarding due to their trans-synaptic activation of midbrain dopamine neurons. A recent study in which rats worked for optogenetic stimulation of midbrain dopamine neurons challenges the series-circuit hypothesis and provides a new model of intracranial self-stimulation in which the myelinated non-dopaminergic neurons and the midbrain dopamine projections access the behavioral final common path for reward seeking via separate, converging routes. We explore the potential implications of this convergence model for the interpretation of the antidepressant effect of MFB stimulation. We also discuss the consistent finding that psychomotor stimulants, which boost dopaminergic neurotransmission, fail to provide a monotherapy for depression. We propose that non-dopaminergic MFB components may contribute to the therapeutic effect in parallel to, in synergy with, or even instead of, a dopaminergic component.

Flexible Electronics and Devices as Human-Machine Interfaces for Medical Robotics

Medical robots are invaluable players in non-pharmaceutical treatment of disabilities. Particularly, using prosthetic and rehabilitation devices with human-machine interfaces can greatly improve the quality of life for impaired patients. In recent years, flexible electronic interfaces and soft robotics have attracted tremendous attention in this field due to their high biocompatibility, functionality, conformability, and low-cost. Flexible human-machine interfaces on soft robotics will make a promising alternative to conventional rigid devices, which can potentially revolutionize the paradigm and future direction of medical robotics in terms of rehabilitation feedback and user experience. In this review, the fundamental components of the materials, structures, and mechanisms in flexible human-machine interfaces are summarized by recent and renowned applications in five primary areas: physical and chemical sensing, physiological recording, information processing and communication, soft robotic actuation, and feedback stimulation. This review further concludes by discussing the outlook and current challenges of these technologies as a human-machine interface in medical robotics.

Highly Conducting and Stretchable Double-Network Hydrogel for Soft Bioelectronics

Conducting polymer hydrogels are promising materials in soft bioelectronics because of their tissue-like mechanical properties and the capability of electrical interaction with tissues. However, it is challenging to balance electrical conductivity and mechanical stretchability: pure conducting polymer hydrogels are highly conductive, but they are brittle; while incorporating the conducting network with a soft network to form a double network can improve the stretchability, its electrical conductivity significantly decreases. Here, the problem is addressed by concentrating a poorly crosslinked precursor hydrogel with a high content ratio of the conducting polymer to achieve a densified double-network hydrogel (5.5 wt% conducting polymer), exhibiting both high electrical conductivity (≈10 S cm^-1 ) and a large fracture strain (≈150%), in addition to high biocompatibility, tissue-like softness, low swelling ratio, and desired electrochemical properties for bioelectronics. A surface grafting method is further used to form an adhesive layer on the conducting hydrogel, enabling robust and rapid bonding on the tissues. Furthermore, the proposed hydrogel is applied to show high-quality physiological signal recording and reliable, low-voltage electrical stimulation based on an in vivo rat model. This method provides an ideal strategy for rapid and reliable tissue-device integration with high-quality electrical communications.