Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments

Temporal gamma tACS and auditory stimulation affect verbal memory in healthy adults

Research suggests a potential of gamma oscillation entrainment for enhancing memory in Alzheimer's disease and healthy subjects. Gamma entrainment can be accomplished with oscillatory electrical, but also sensory stimulation. However, comparative studies between sensory stimulation and transcranial alternating current stimulation (tACS) effects on memory processes are lacking. This study examined the effects of rhythmic gamma auditory stimulation (rAS) and temporal gamma-tACS on verbal long-term memory (LTM) and working memory (WM) in 74 healthy individuals. Participants were assigned to two groups according to the stimulation techniques (rAS or tACS). Memory was assessed in three experimental blocks, in which each participant was administered with control, 40, and 60 Hz stimulation in counterbalanced order. All interventions were well-tolerated, and participants reported mostly comparable side effects between real stimulation (40 and 60 Hz) and the control condition. LTM immediate and delayed recall remained unaffected by stimulations, while immediate recall intrusions decreased during 60 Hz stimulation. Notably, 40 Hz interventions improved WM compared to control stimulations. These results highlight the potential of 60 and 40 Hz temporal cortex stimulation for reducing immediate LTM recall intrusions and improving WM performance, respectively, probably due to the entrainment of specific gamma oscillations in the auditory cortex. The results also shed light on the comparative effects of these neuromodulation tools on memory functions, and their potential applications for cognitive enhancement and in clinical trials.

Neuromodulation and meditation: A review and synthesis toward promoting well-being and understanding consciousness and brain

The neuroscience of meditation is providing insight into meditation's beneficial effects on well-being and informing understanding of consciousness. However, further research is needed to explicate mechanisms linking brain activity and meditation. Non-invasive brain stimulation (NIBS) presents a promising approach for causally investigating neural mechanisms of meditation. Prior NIBS-meditation research has predominantly targeted frontal and parietal cortices suggesting that it might be possible to boost the behavioral and neural effects of meditation with NIBS. Moreover, NIBS has revealed distinct neural signatures in long-term meditators. Nonetheless, methodological variations in NIBS-meditation research contributes to challenges for definitive interpretation of previous results. Future NIBS studies should further investigate core substrates of meditation, including specific brain networks and oscillations, and causal neural mechanisms of advanced meditation. Overall, NIBS-meditation research holds promise for enhancing meditation-based interventions in support of well-being and resilience in both non-clinical and clinical populations, and for uncovering the brain-mind mechanisms of meditation and consciousness.

In vivo photopharmacological inhibition of hippocampal activity via multimodal probes - perspective and opening steps on experimental and computational challenges

Neurological conditions such as epilepsy can have a significant impact on people's lives. Here, we discuss a new perspective for the study/treatment of these conditions using photopharmacology. A multimodal, intracranial implant that incorporates fluidic channels for localised drug delivery, electrodes for recording and stimulation, and a light source for photoswitching is used for in vivo administration and deactivation of a photoresponsive AMPA antagonist. We review current advancements in the relevant disciplines and show experimentally that the inhibition of seizure-like events induced in the hippocampus by electrical stimulation can be altered upon switching the drug with light. We discuss the interconnection of the drug's photopharmacological properties with the design of the device by modelling light penetration into the rat brain with Monte Carlo simulations. This work delivers a new perspective, including initial experimental and computational efforts on in vivo photopharmacology to understand and eventually treat neurological conditions.

Practice improves older adults' attentional control and prospective memory more than HD-tDCS: a randomized controlled trial

Frontal and parietal brain regions are involved in attentional control and prospective memory. It is debated, however, whether increased or decreased activity in those regions is beneficial for older adults' task performance. We therefore aimed to systematically modulate activity in those regions using high-definition transcranial direct current stimulation. We included n = 106 healthy adults (60-75 years old, 58% female) in a randomized, double-blind, and sham-controlled study. We evaluated task performance twice in the laboratory and at home and additionally assessed heart rates. Participants received cathodal, anodal, or sham stimulation of the left or right inferior frontal lobe, or the right superior parietal lobe (1 mA for 20 min). Performance improved at visit two in laboratory tasks but declined in at-home tasks. Stimulation did not modulate performance change in laboratory tasks but prevented decline in at home-tasks. Heart rates increased at visit two but only when right inferior frontal lobe activity was inhibited. Repeating a task seems more beneficial than stimulation for laboratory tasks. This might be different for at-home tasks. Inhibiting right frontal brain function increases heart rates, possibly due to a modulation of the frontal-vagal brain-heart axis.

BLA-involved circuits in neuropsychiatric disorders

The basolateral amygdala (BLA) is the subregion of the amygdala located in the medial of the temporal lobe, which is connected with a wide range of brain regions to achieve diverse functions. Recently, an increasing number of studies have focused on the participation of the BLA in many neuropsychiatric disorders from the neural circuit perspective, aided by the rapid development of viral tracing methods and increasingly specific neural modulation technologies. However, how to translate this circuit-level preclinical intervention into clinical treatment using noninvasive or minor invasive manipulations to benefit patients struggling with neuropsychiatric disorders is still an inevitable question to be considered. In this review, we summarized the role of BLA-involved circuits in neuropsychiatric disorders including Alzheimer's disease, perioperative neurocognitive disorders, schizophrenia, anxiety disorders, depressive disorders, posttraumatic stress disorders, autism spectrum disorders, and pain-associative affective states and cognitive dysfunctions. Additionally, we provide insights into future directions and challenges for clinical translation.

Synaptic Plasticity in the Injured Brain Depends on the Temporal Pattern of Stimulation

Neurostimulation protocols are increasingly used as therapeutic interventions, including for brain injury. In addition to the direct activation of neurons, these stimulation protocols are also likely to have downstream effects on those neurons' synaptic outputs. It is well known that alterations in the strength of synaptic connections (long-term potentiation, LTP; long-term depression, LTD) are sensitive to the frequency of stimulation used for induction; however, little is known about the contribution of the temporal pattern of stimulation to the downstream synaptic plasticity that may be induced by neurostimulation in the injured brain. We explored interactions of the temporal pattern and frequency of neurostimulation in the normal cerebral cortex and after mild traumatic brain injury (mTBI), to inform therapies to strengthen or weaken neural circuits in injured brains, as well as to better understand the role of these factors in normal brain plasticity. Whole-cell (WC) patch-clamp recordings of evoked postsynaptic potentials in individual neurons, as well as field potential (FP) recordings, were made from layer 2/3 of visual cortex in response to stimulation of layer 4, in acute slices from control (naive), sham operated, and mTBI rats. We compared synaptic plasticity induced by different stimulation protocols, each consisting of a specific frequency (1 Hz, 10 Hz, or 100 Hz), continuity (continuous or discontinuous), and temporal pattern (perfectly regular, slightly irregular, or highly irregular). At the individual neuron level, dramatic differences in plasticity outcome occurred when the highly irregular stimulation protocol was used at 1 Hz or 10 Hz, producing an overall LTD in controls and shams, but a robust overall LTP after mTBI. Consistent with the individual neuron results, the plasticity outcomes for simultaneous FP recordings were similar, indicative of our results generalizing to a larger scale synaptic network than can be sampled by individual WC recordings alone. In addition to the differences in plasticity outcome between control (naive or sham) and injured brains, the dynamics of the changes in synaptic responses that developed during stimulation were predictive of the final plasticity outcome. Our results demonstrate that the temporal pattern of stimulation plays a role in the polarity and magnitude of synaptic plasticity induced in the cerebral cortex while highlighting differences between normal and injured brain responses. Moreover, these results may be useful for optimization of neurostimulation therapies to treat mTBI and other brain disorders, in addition to providing new insights into downstream plasticity signaling mechanisms in the normal brain.

Non-Invasive Brain Sensing Technologies for Modulation of Neurological Disorders

The non-invasive brain sensing modulation technology field is experiencing rapid development, with new techniques constantly emerging. This study delves into the field of non-invasive brain neuromodulation, a safer and potentially effective approach for treating a spectrum of neurological and psychiatric disorders. Unlike traditional deep brain stimulation (DBS) surgery, non-invasive techniques employ ultrasound, electrical currents, and electromagnetic field stimulation to stimulate the brain from outside the skull, thereby eliminating surgery risks and enhancing patient comfort. This study explores the mechanisms of various modalities, including transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), highlighting their potential to address chronic pain, anxiety, Parkinson's disease, and depression. We also probe into the concept of closed-loop neuromodulation, which personalizes stimulation based on real-time brain activity. While we acknowledge the limitations of current technologies, our study concludes by proposing future research avenues to advance this rapidly evolving field with its immense potential to revolutionize neurological and psychiatric care and lay the foundation for the continuing advancement of innovative non-invasive brain sensing technologies.

Real-time closed-loop brainstem stimulation modality for enhancing temporal blood pressure reduction

BACKGROUND

Traditional pharmacological interventions are well tolerated in the management of elevated blood pressure (BP) for individuals with resistant hypertension. Although neuromodulation has been investigated as an alternative solution, its open-loop (OL) modality cannot follow the patient's physiological state. In fact, neuromodulation for controlling highly fluctuating BP necessitates a closed-loop (CL) stimulation modality based on biomarkers to monitor the patient's continuously varying physiological state.

OBJECTIVE

By leveraging its intuitive linkage with BP responses in ongoing efforts aimed at developing a CL system to enhance temporal BP reduction effect, this study proposes a CL neuromodulation modality that controls nucleus tractus solitarius (NTS) activity to effectively reduce BP, thus reflecting continuously varying physiological states.

METHOD

While performing neurostimulation targeting the NTS in the rat model, the arterial BP response and neural activity of the NTS were simultaneously measured. To evaluate the temporal BP response effect of CL neurostimulation, OL (constant parameter; 20 Hz, 200 μA) and CL (Initial parameter; 11 Hz, 112 μA) stimulation protocols were performed with stimulation 180 s and rest 600 s, respectively, and examined NTS activity and BP response to the protocols.

RESULTS

In-vivo experiments for OL versus CL protocol for direct NTS stimulation in rats demonstrated an enhancement in temporal BP reduction via the CL modulation of NTS activity.

CONCLUSION

This study proposes a CL stimulation modality that enhances the effectiveness of BP control using a feedback control algorithm based on neural signals, thereby suggesting a new approach to antihypertensive neuromodulation.

Never-Ending Learning for Explainable Brain Computing

Exploring the nature of human intelligence and behavior is a longstanding pursuit in cognitive neuroscience, driven by the accumulation of knowledge, information, and data across various studies. However, achieving a unified and transparent interpretation of findings presents formidable challenges. In response, an explainable brain computing framework is proposed that employs the never-ending learning paradigm, integrating evidence combination and fusion computing within a Knowledge-Information-Data (KID) architecture. The framework supports continuous brain cognition investigation, utilizing joint knowledge-driven forward inference and data-driven reverse inference, bolstered by the pre-trained language modeling techniques and the human-in-the-loop mechanisms. In particular, it incorporates internal evidence learning through multi-task functional neuroimaging analyses and external evidence learning via topic modeling of published neuroimaging studies, all of which involve human interactions at different stages. Based on two case studies, the intricate uncertainty surrounding brain localization in human reasoning is revealed. The present study also highlights the potential of systematization to advance explainable brain computing, offering a finer-grained understanding of brain activity patterns related to human intelligence.

Innovation at the Intersection: Emerging Translational Research in Neurology and Psychiatry

Translational research in neurological and psychiatric diseases is a rapidly advancing field that promises to redefine our approach to these complex conditions [...].

U-shaped convolutional transformer GAN with multi-resolution consistency loss for restoring brain functional time-series and dementia diagnosis

Introduction

The blood oxygen level-dependent (BOLD) signal derived from functional neuroimaging is commonly used in brain network analysis and dementia diagnosis. Missing the BOLD signal may lead to bad performance and misinterpretation of findings when analyzing neurological disease. Few studies have focused on the restoration of brain functional time-series data.

Methods

In this paper, a novel U-shaped convolutional transformer GAN (UCT-GAN) model is proposed to restore the missing brain functional time-series data. The proposed model leverages the power of generative adversarial networks (GANs) while incorporating a U-shaped architecture to effectively capture hierarchical features in the restoration process. Besides, the multi-level temporal-correlated attention and the convolutional sampling in the transformer-based generator are devised to capture the global and local temporal features for the missing time series and associate their long-range relationship with the other brain regions. Furthermore, by introducing multi-resolution consistency loss, the proposed model can promote the learning of diverse temporal patterns and maintain consistency across different temporal resolutions, thus effectively restoring complex brain functional dynamics.

Results

We theoretically tested our model on the public Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and our experiments demonstrate that the proposed model outperforms existing methods in terms of both quantitative metrics and qualitative assessments. The model's ability to preserve the underlying topological structure of the brain functional networks during restoration is a particularly notable achievement.

Conclusion

Overall, the proposed model offers a promising solution for restoring brain functional time-series and contributes to the advancement of neuroscience research by providing enhanced tools for disease analysis and interpretation.

A scientometric review of the growing trends in transcranial alternating current stimulation (tACS)

Objective

The aim of the current study was to provide a comprehensive picture of tACS-related research in the last decade through a bibliometric approach in order to systematically analyze the current status and cutting-edge trends in this field.

Methods

Articles and review articles related to tACS from 2013 to 2022 were searched on the Web of Science platform. A bibliometric analysis of authors, journals, countries, institutions, references, and keywords was performed using CiteSpace (6.2.R2), VOSviewer (1.6.19), Scimago Graphica (1.0.30), and Bibliometrix (4.2.2).

Results

A total of 602 papers were included. There was an overall increase in annual relevant publications in the last decade. The most contributing author was Christoph S. Herrmann. Brain Stimulation was the most prolific journal. The most prolific countries and institutions were Germany and Harvard University, respectively.

Conclusion

The findings reveal the development prospects and future directions of tACS and provide valuable references for researchers in the field. In recent years, the keywords "gamma," "transcranial direct current simulation," and "Alzheimer's disease" that have erupted, as well as many references cited in the outbreak, have provided certain clues for the mining of research prefaces. This will act as a guide for future researchers in determining the path of tACS research.

Frequency-dependent membrane polarization across neocortical cell types and subcellular elements by transcranial alternating current stimulation

Objective.Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that directly interacts with ongoing brain oscillations in a frequency-dependent manner. However, it remains largely unclear how the cellular effects of tACS vary between cell types and subcellular elements.Approach.In this study, we use a set of morphologically realistic models of neocortical neurons to simulate the cellular response to uniform oscillating electric fields (EFs). We systematically characterize the membrane polarization in the soma, axons, and dendrites with varying field directions, intensities, and frequencies.Main results.Pyramidal cells are more sensitive to axial EF that is roughly parallel to the cortical column, while interneurons are sensitive to axial EF and transverse EF that is tangent to the cortical surface. Membrane polarization in each subcellular element increases linearly with EF intensity, and its slope, i.e. polarization length, highly depends on the stimulation frequency. At each frequency, pyramidal cells are more polarized than interneurons. Axons usually experience the highest polarization, followed by the dendrites and soma. Moreover, a visible frequency resonance presents in the apical dendrites of pyramidal cells, while the other subcellular elements primarily exhibit low-pass filtering properties. In contrast, each subcellular element of interneurons exhibits complex frequency-dependent polarization. Polarization phase in each subcellular element of cortical neurons lags that of field and exhibits high-pass filtering properties. These results demonstrate that the membrane polarization is not only frequency-dependent, but also cell type- and subcellular element-specific. Through relating effective length and ion mechanism with polarization, we emphasize the crucial role of cell morphology and biophysics in determining the frequency-dependent membrane polarization.Significance.Our findings highlight the diverse polarization patterns across cell types as well as subcellular elements, which provide some insights into the tACS cellular effects and should be considered when understanding the neural spiking activity by tACS.

A classification-based generative approach to selective targeting of global slow oscillations during sleep

Background

Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability.

Objective/Hypothesis

This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile.

Methods

We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance.

Results

Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization.

Conclusion

Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.

Converging Evidence for Frontopolar Cortex as a Target for Neuromodulation in Addiction Treatment

Noninvasive brain stimulation technologies such as transcranial electrical and magnetic stimulation (tES and TMS) are emerging neuromodulation therapies that are being used to target the neural substrates of substance use disorders. By the end of 2022, 205 trials of tES or TMS in the treatment of substance use disorders had been published, with heterogeneous results, and there is still no consensus on the optimal target brain region. Recent work may help clarify where and how to apply stimulation, owing to expanding databases of neuroimaging studies, new systematic reviews, and improved methods for causal brain mapping. Whereas most previous clinical trials targeted the dorsolateral prefrontal cortex, accumulating data highlight the frontopolar cortex as a promising therapeutic target for transcranial brain stimulation in substance use disorders. This approach is supported by converging multimodal evidence, including lesion-based maps, functional MRI-based maps, tES studies, TMS studies, and dose-response relationships. This review highlights the importance of targeting the frontopolar area and tailoring the treatment according to interindividual variations in brain state and trait and electric field distribution patterns. This converging evidence supports the potential for treatment optimization through context, target, dose, and timing dimensions to improve clinical outcomes of transcranial brain stimulation in people with substance use disorders in future clinical trials.

Changes in myelinated nerve fibers induced by pulsed electrical stimulation: A microstructural perspective on the causes of electrical stimulation side effects

Electrical brain stimulation technology is widely used in the clinic to treat brain neurological disorders. However, during treatment, patients may experience side effects such as pain, poor limb coordination, and skin rash. Previous reports have focused on the brilliant chapter on electrical brain stimulation technology and have not paid attention to patients' suffering caused by side effects during treatment. In this study, electrodes were arranged on the medulla oblongata. Pulsed electric fields of different frequencies were used to perform electrical stimulation to study the impact of electric fields on myelinated nerve fibers and reveal the possible microstructural origin of side effects. Transmission electron microscopy was used to analyze and quantify the changes in microstructure. The results illustrated that myelinated nerve fibers underwent atrophy under pulsed electric fields, with the mildest degree of atrophy under high-frequency (400 Hz) electric fields. Myelin sheaths experienced plate separation under pulsed electric fields, and a distinct laminar structure appeared. The microstructure changes may be related to the side effects of clinical electrical stimulation. This study can provide pathological possibilities for exploring the causes of the side effects of electrical stimulation and supply guidance for selecting electrical parameters for clinical electrical stimulation therapy from a distinctive perspective.

Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses

Neuroprostheses show potential in restoring lost sensory function and enhancing human capabilities, but the sensations produced by current devices often seem unnatural or distorted. Exact placement of implants and differences in individual perception lead to significant variations in stimulus response, making personalized stimulus optimization a key challenge. Bayesian optimization could be used to optimize patient-specific stimulation parameters with limited noisy observations, but is not feasible for high-dimensional stimuli. Alternatively, deep learning models can optimize stimulus encoding strategies, but typically assume perfect knowledge of patient-specific variations. Here we propose a novel, practically feasible approach that overcomes both of these fundamental limitations. First, a deep encoder network is trained to produce optimal stimuli for any individual patient by inverting a forward model mapping electrical stimuli to visual percepts. Second, a preferential Bayesian optimization strategy utilizes this encoder to optimize patient-specific parameters for a new patient, using a minimal number of pairwise comparisons between candidate stimuli. We demonstrate the viability of this approach on a novel, state-of-the-art visual prosthesis model. We show that our approach quickly learns a personalized stimulus encoder, leads to dramatic improvements in the quality of restored vision, and is robust to noisy patient feedback and misspecifications in the underlying forward model. Overall, our results suggest that combining the strengths of deep learning and Bayesian optimization could significantly improve the perceptual experience of patients fitted with visual prostheses and may prove a viable solution for a range of neuroprosthetic technologies.

The Rehabilitation Potential of Neurostimulation for Mild Traumatic Brain Injury in Animal and Human Studies

Neurostimulation carries high therapeutic potential, accompanied by an excellent safety profile. In this review, we argue that an arena in which these tools could provide breakthrough benefits is traumatic brain injury (TBI). TBI is a major health problem worldwide, with the majority of cases identified as mild TBI (mTBI). MTBI is of concern because it is a modifiable risk factor for dementia. A major challenge in studying mTBI is its inherent heterogeneity across a large feature space (e.g., etiology, age of injury, sex, treatment, initial health status, etc.). Parallel lines of research in human and rodent mTBI can be collated to take advantage of the full suite of neuroscience tools, from neuroimaging (electroencephalography: EEG; functional magnetic resonance imaging: fMRI; diffusion tensor imaging: DTI) to biochemical assays. Despite these attractive components and the need for effective treatments, there are at least two major challenges to implementation. First, there is insufficient understanding of how neurostimulation alters neural mechanisms. Second, there is insufficient understanding of how mTBI alters neural function. The goal of this review is to assemble interrelated but disparate areas of research to identify important gaps in knowledge impeding the implementation of neurostimulation.