Closed-loop stimulation using a multiregion brain-machine interface has analgesic effects in rodents

Revealing unexpected complex encoding but simple decoding mechanisms in motor cortex via separating behaviorally relevant neural signals

In motor cortex, behaviorally relevant neural responses are entangled with irrelevant signals, which complicates the study of encoding and decoding mechanisms. It remains unclear whether behaviorally irrelevant signals could conceal some critical truth. One solution is to accurately separate behaviorally relevant and irrelevant signals at both single-neuron and single-trial levels, but this approach remains elusive due to the unknown ground truth of behaviorally relevant signals. Therefore, we propose a framework to define, extract, and validate behaviorally relevant signals. Analyzing separated signals in three monkeys performing different reaching tasks, we found neural responses previously considered to contain little information actually encode rich behavioral information in complex nonlinear ways. These responses are critical for neuronal redundancy and reveal movement behaviors occupy a higher-dimensional neural space than previously expected. Surprisingly, when incorporating often-ignored neural dimensions, behaviorally relevant signals can be decoded linearly with comparable performance to nonlinear decoding, suggesting linear readout may be performed in motor cortex. Our findings prompt that separating behaviorally relevant signals may help uncover more hidden cortical mechanisms.

Large-scale foundation models and generative AI for BigData neuroscience

Recent advances in machine learning have led to revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved human-like intelligence thanks to BigData. With the help of self-supervised learning (SSL) and transfer learning, these models may potentially reshape the landscapes of neuroscience research and make a significant impact on the future. Here we present a mini-review on recent advances in foundation models and generative AI models as well as their applications in neuroscience, including natural language and speech, semantic memory, brain-machine interfaces (BMIs), and data augmentation. We argue that this paradigm-shift framework will open new avenues for many neuroscience research directions and discuss the accompanying challenges and opportunities.

Pathology of pain and its implications for therapeutic interventions

Pain is estimated to affect more than 20% of the global population, imposing incalculable health and economic burdens. Effective pain management is crucial for individuals suffering from pain. However, the current methods for pain assessment and treatment fall short of clinical needs. Benefiting from advances in neuroscience and biotechnology, the neuronal circuits and molecular mechanisms critically involved in pain modulation have been elucidated. These research achievements have incited progress in identifying new diagnostic and therapeutic targets. In this review, we first introduce fundamental knowledge about pain, setting the stage for the subsequent contents. The review next delves into the molecular mechanisms underlying pain disorders, including gene mutation, epigenetic modification, posttranslational modification, inflammasome, signaling pathways and microbiota. To better present a comprehensive view of pain research, two prominent issues, sexual dimorphism and pain comorbidities, are discussed in detail based on current findings. The status quo of pain evaluation and manipulation is summarized. A series of improved and innovative pain management strategies, such as gene therapy, monoclonal antibody, brain-computer interface and microbial intervention, are making strides towards clinical application. We highlight existing limitations and future directions for enhancing the quality of preclinical and clinical research. Efforts to decipher the complexities of pain pathology will be instrumental in translating scientific discoveries into clinical practice, thereby improving pain management from bench to bedside.

Modulating Neural Circuits of Pain in Preclinical Models: Recent Insights for Future Therapeutics

Chronic pain is a pathological state defined as daily pain sensation over three consecutive months. It affects up to 30% of the general population. Although significant research efforts have been made in the past 30 years, only a few and relatively low effective molecules have emerged to treat chronic pain, with a considerable translational failure rate. Most preclinical models have focused on sensory neurotransmission, with particular emphasis on the dorsal horn of the spinal cord as the first relay of nociceptive information. Beyond impaired nociceptive transmission, chronic pain is also accompanied by numerous comorbidities, such as anxiety-depressive disorders, anhedonia and motor and cognitive deficits gathered under the term "pain matrix". The emergence of cutting-edge techniques assessing specific neuronal circuits allow in-depth studies of the connections between "pain matrix" circuits and behavioural outputs. Pain behaviours are assessed not only by reflex-induced responses but also by various or more complex behaviours in order to obtain the most complete picture of an animal's pain state. This review summarises the latest findings on pain modulation by brain component of the pain matrix and proposes new opportunities to unravel the mechanisms of chronic pain.

Current perioperative nociception monitoring and potential directions

Perioperative nociception-antinociception balance is essential for the prevention of adverse postoperative events. Estimating the nociception level helps optimize intraoperative management. In the past two decades, various nociception monitoring devices have been developed for the identification of intraoperative nociception. However, each type of nociception monitoring device has advantages and disadvantages, limiting their clinical application in particular patients and settings. Therefore, this review aimed to summarize the information on nociceptor monitoring in current clinical settings, explore each technique's particularities, and possible future directions to provide a reference for clinicians and researchers.

Targeting Prefrontal Cortex Dysfunction in Pain

The prefrontal cortex (PFC) has justifiably become a significant focus of chronic pain research. Collectively, decades of rodent and human research have provided strong rationale for studying the dysfunction of the PFC as a contributing factor in the development and persistence of chronic pain and as a key supraspinal mechanism for pain-induced comorbidities such as anxiety, depression, and cognitive decline. Chronic pain alters the structure, chemistry, and connectivity of PFC in both humans and rodents. In this review, we broadly summarize the complexities of reported changes within both rodent and human PFC caused by pain and offer insight into potential pharmacological and nonpharmacological approaches for targeting PFC to treat chronic pain and pain-associated comorbidities. SIGNIFICANCE STATEMENT: Chronic pain is a significant unresolved medical problem causing detrimental changes to physiological, psychological, and behavioral aspects of life. Drawbacks of currently approved pain therapeutics include incomplete efficacy and potential for abuse producing a critical need for novel approaches to treat pain and comorbid disorders. This review provides insight into how manipulation of prefrontal cortex circuits could address this unmet need of more efficacious and safer pain therapeutics.

Magnetically Compatible Brain Electrode Arrays Based on Single-Walled Carbon Nanotubes for Long-Term Implantation

Advancements in brain-machine interfaces and neurological treatments urgently require the development of improved brain electrodes applied for long-term implantation, where traditional and polymer options face challenges like size, tissue damage, and signal quality. Carbon nanotubes are emerging as a promising alternative, combining excellent electronic properties and biocompatibility, which ensure better neuron coupling and stable signal acquisition. In this study, a new flexible brain electrode array based on 99.99% purity of single-walled carbon nanotubes (SWCNTs) was developed, which has 30 um × 40 um size, about 5.1 kΩ impedance, and 14.01 dB signal-to-noise ratio (SNR). The long-term implantation experiment in vivo in mice shows the proposed brain electrode can maintain stable LFP signal acquisition over 12 weeks while still achieving an SNR of 3.52 dB. The histological analysis results show that SWCNT-based brain electrodes induced minimal tissue damage and showed significantly reduced glial cell responses compared to platinum wire electrodes. Long-term stability comes from SWCNT's biocompatibility and chemical inertness, the electrode's flexible and fine structure. Furthermore, the new brain electrode array can function effectively during 7-Tesla magnetic resonance imaging, enabling the collection of local field potential and even epileptic discharges during the magnetic scan. This study provides a comprehensive study of carbon nanotubes as invasive brain electrodes, providing a new path to address the challenge of long-term brain electrode implantation.

Optogenetic Neuromodulation in Inflammatory Pain

Inflammatory pain is one of the most prevalent forms of pain and negatively influences the quality of life. Neuromodulation has been an expanding field of pain medicine and is accepted by patients who have failed to respond to several conservative treatments. Despite its effectiveness, neuromodulation still lacks clinically robust evidence on inflammatory pain management. Optogenetics, which controls particular neurons or brain circuits with high spatiotemporal accuracy, has recently been an emerging area for inflammatory pain management and studying its mechanism. This review considers the fundamentals of optogenetics, including using opsins, targeting gene expression, and wavelength-specific light delivery techniques. The recent evidence on application and development of optogenetic neuromodulation in inflammatory pain is also summarised. The current limitations and challenges restricting the progression and clinical transformation of optogenetics in pain are addressed. Optogenetic neuromodulation in inflammatory pain has many potential targets, and developing strategies enabling clinical application is a desirable therapeutic approach and outcome.

AMPAkines have site-specific analgesic effects in the cortex

Different brain areas have distinct roles in the processing and regulation of pain and thus may form specific pharmacological targets. Prior research has shown that AMPAkines, a class of drugs that increase glutamate signaling, can enhance descending inhibition from the prefrontal cortex (PFC) and nucleus accumbens. On the other hand, activation of neurons in the anterior cingulate cortex (ACC) is known to produce the aversive component of pain. The impact of AMPAkines on ACC, however, is not known. We found that direct delivery of CX516, a well-known AMPAkine, into the ACC had no effect on the aversive response to pain in rats. Furthermore, AMPAkines did not modulate the nociceptive response of ACC neurons. In contrast, AMPAkine delivery into the prelimbic region of the prefrontal cortex (PL) reduced pain aversion. These results indicate that the analgesic effects of AMPAkines in the cortex are likely mediated by the PFC but not the ACC.

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients

Introduction

Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known.

Methods

We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data.

Results

As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia.

Discussion

These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.

Anterior cingulate cortex regulates pain catastrophizing-like behaviors in rats

Negative pain expectation including pain catastrophizing is a well-known clinical phenomenon whereby patients amplify the aversive value of a painful or oftentimes even a similar, non-painful stimulus. Mechanisms of pain catastrophizing, however, remain elusive. Here, we modeled pain catastrophizing behavior in rats, and found that rats subjected to repeated noxious pin pricks on one paw demonstrated an aversive response to similar but non-noxious mechanical stimuli delivered to the contralateral paw. Optogenetic inhibition of pyramidal neuron activity in the anterior cingulate cortex (ACC) during the application of repetitive noxious pin pricks eliminated this catastrophizing behavior. Time-lapse calcium (Ca2+) imaging in the ACC further revealed an increase in spontaneous neural activity after the delivery of noxious stimuli. Together these results suggest that the experience of repeated noxious stimuli may drive hyperactivity in the ACC, causing increased avoidance of subthreshold stimuli, and that reducing this hyperactivity may play a role in treating pain catastrophizing.

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

Oxytocin promotes prefrontal population activity via the PVN-PFC pathway to regulate pain

Neurons in the prefrontal cortex (PFC) can provide top-down regulation of sensory-affective experiences such as pain. Bottom-up modulation of sensory coding in the PFC, however, remains poorly understood. Here, we examined how oxytocin (OT) signaling from the hypothalamus regulates nociceptive coding in the PFC. In vivo time-lapse endoscopic calcium imaging in freely behaving rats showed that OT selectively enhanced population activity in the prelimbic PFC in response to nociceptive inputs. This population response resulted from the reduction of evoked GABAergic inhibition and manifested as elevated functional connectivity involving pain-responsive neurons. Direct inputs from OT-releasing neurons in the paraventricular nucleus (PVN) of the hypothalamus are crucial to maintaining this prefrontal nociceptive response. Activation of the prelimbic PFC by OT or direct optogenetic stimulation of oxytocinergic PVN projections reduced acute and chronic pain. These results suggest that oxytocinergic signaling in the PVN-PFC circuit constitutes a key mechanism to regulate cortical sensory processing.

Hierarchical predictive coding in distributed pain circuits

Predictive coding is a computational theory on describing how the brain perceives and acts, which has been widely adopted in sensory processing and motor control. Nociceptive and pain processing involves a large and distributed network of circuits. However, it is still unknown whether this distributed network is completely decentralized or requires networkwide coordination. Multiple lines of evidence from human and animal studies have suggested that the cingulate cortex and insula cortex (cingulate-insula network) are two major hubs in mediating information from sensory afferents and spinothalamic inputs, whereas subregions of cingulate and insula cortices have distinct projections and functional roles. In this mini-review, we propose an updated hierarchical predictive coding framework for pain perception and discuss its related computational, algorithmic, and implementation issues. We suggest active inference as a generalized predictive coding algorithm, and hierarchically organized traveling waves of independent neural oscillations as a plausible brain mechanism to integrate bottom-up and top-down information across distributed pain circuits.

Pathway of transient electronics towards connected biomedical applications

Transient electronic devices have shown promising applications in hardware security and medical implants with diagnosing therapeutics capabilities since their inception. Control of the device transience allows the device to "dissolve at will" after its functional operation, leading to the development of on-demand transient electronics. This review discusses the recent developments and advantages of triggering strategies (e.g., electrical, thermal, ultrasound, and optical) for controlling the degradation of on-demand transient electronics. We also summarize bioresorbable sensors for medical diagnoses, including representative applications in electrophysiology and neurochemical sensing. Along with the profound advancements in medical diagnosis, the commencement of therapeutic systems such as electrical stimulation and drug delivery for the biomedical or medical implant community has also been discussed. However, implementing a transient electronic system in real healthcare infrastructure is still in its infancy. Many critical challenges still need to be addressed, including strategies to decouple multimodal sensing signals, dissolution selectivity in the presence of multiple stimuli, and a complete sensing-stimulation closed-loop system. Therefore, the review discusses future opportunities in transient decoupling sensors and robust transient devices, which are selective to a particular stimulus and act as hardware-based passwords. Recent advancements in closed-loop controller-enabled electronics have also been analyzed for future opportunities of using data-driven artificial intelligence-powered controllers in fully closed-loop transient systems.

Temporal pain processing in the primary somatosensory cortex and anterior cingulate cortex

Pain is known to have sensory and affective components. The sensory pain component is encoded by neurons in the primary somatosensory cortex (S1), whereas the emotional or affective pain experience is in large part processed by neural activities in the anterior cingulate cortex (ACC). The timing of how a mechanical or thermal noxious stimulus triggers activation of peripheral pain fibers is well-known. However, the temporal processing of nociceptive inputs in the cortex remains little studied. Here, we took two approaches to examine how nociceptive inputs are processed by the S1 and ACC. We simultaneously recorded local field potentials in both regions, during the application of a brain-computer interface (BCI). First, we compared event related potentials in the S1 and ACC. Next, we used an algorithmic pain decoder enabled by machine-learning to detect the onset of pain which was used during the implementation of the BCI to automatically treat pain. We found that whereas mechanical pain triggered neural activity changes first in the S1, the S1 and ACC processed thermal pain with a reasonably similar time course. These results indicate that the temporal processing of nociceptive information in different regions of the cortex is likely important for the overall pain experience.

On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders

Emerging brain technologies have significantly transformed human life in recent decades. For instance, the closed-loop brain-computer interface (BCI) is an advanced software-hardware system that interprets electrical signals from neurons, allowing communication with and control of the environment. The system then transmits these signals as controlled commands and provides feedback to the brain to execute specific tasks. This paper analyzes and presents the latest research on closed-loop BCI that utilizes electric/magnetic stimulation, optogenetic, and sonogenetic techniques. These techniques have demonstrated great potential in improving the quality of life for patients suffering from neurodegenerative or psychiatric diseases. We provide a comprehensive and systematic review of research on the modalities of closed-loop BCI in recent decades. To achieve this, the authors used a set of defined criteria to shortlist studies from well-known research databases into categories of brain stimulation techniques. These categories include deep brain stimulation, transcranial magnetic stimulation, transcranial direct-current stimulation, transcranial alternating-current stimulation, and optogenetics. These techniques have been useful in treating a wide range of disorders, such as Alzheimer's and Parkinson's disease, dementia, and depression. In total, 76 studies were shortlisted and analyzed to illustrate how closed-loop BCI can considerably improve, enhance, and restore specific brain functions. The analysis revealed that literature in the area has not adequately covered closed-loop BCI in the context of cognitive neural prosthetics and implanted neural devices. However, the authors demonstrate that the applications of closed-loop BCI are highly beneficial, and the technology is continually evolving to improve the lives of individuals with various ailments, including those with sensory-motor issues or cognitive deficiencies. By utilizing emerging techniques of stimulation, closed-loop BCI can safely improve patients' cognitive and affective skills, resulting in better healthcare outcomes.

Large-scale, closed-loop interrogation of neural circuits underlying cognition

Cognitive functions are increasingly understood to involve coordinated activity patterns between multiple brain regions, and their disruption by neuropsychiatric disorders is similarly complex. Closed-loop neurostimulation can directly modulate neural signals with temporal and spatial precision. How to leverage such an approach to effectively identify and target distributed neural networks implicated in mediating cognition remains unclear. We review current conceptual and technical advances in this area, proposing that devices that enable large-scale acquisition, integrated processing, and multiregion, arbitrary waveform stimulation will be critical for mechanistically driven manipulation of cognitive processes in physiological and pathological brain networks.