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Neuroimaging can help reveal the spatial and temporal diversity of neural activity, which is of utmost importance for understanding the brain. However, conventional non-invasive neuroimaging methods do not have the advantage of high temporal and spatial resolution, which greatly hinders clinical and basic research. The acoustoelectric (AE) effect is a fundamental physical phenomenon based on the change of dielectric conductivity that has recently received much attention in the field of biomedical imaging. Based on the AE effect, a new imaging method for the biological current source has been proposed, combining the advantages of high temporal resolution of electrical measurements and high spatial resolution of focused ultrasound. This paper first describes the mechanism of the AE effect and the principle of the current source imaging method based on the AE effect. The second part summarizes the research progress of this current source imaging method in brain neurons, guided brain therapy, and heart. Finally, we discuss the problems and future directions of this biological current source imaging method. This review explores the relevant research literature and provides an informative reference for this potential non-invasive neuroimaging method.

Non-invasive neuroimaging techniques provide a wide array of possibilities to study human brain function. A number of approaches are available that improve our understanding of the anatomical location of brain activation patterns, including the development of probabilistic conversion tools to register individual data to population based neuroanatomical templates. Two elegant examples were published by Horn et al. (2017) in which a method was described to warp DBS electrode coordinates, and histological data to MNI-space (Ewert et al., 2017). The conversion of individual brain scans to a standard space is done assuming that individual anatomical scans provide a reliable image of the underlying neuroanatomy. It is unclear to what extent spatial distortions related to tissue properties, or MRI artifacts exist in these scans. Therefore, the question rises whether the anatomical information from the individual scans can be considered a real ground truth. To accommodate the knowledge-gap as a result of limited anatomical information, generative brain models have been developed circumventing these challenges through the application of assumption sets without recourse to any ground truth. We would like to argue that, although these efforts are valuable, the definition of an anatomical ground truth is preferred. Its definition requires a system in which non-invasive approaches can be validated using invasive methods of investigation. We argue that the application of MRI studies in combination with microscopy analyses brings an anatomical ground truth for the human brain within reach, which is of importance for all research within the human neuroimaging field.

Non-invasive transcranial brain stimulation (NTBS) techniques such as transcranial magnetic stimulation (TMS) and transcranial current stimulation (TCS) are important tools in human systems and cognitive neuroscience because they are able to reveal the relevance of certain brain structures or neuronal activity patterns for a given brain function. It is nowadays feasible to combine NTBS, either consecutively or concurrently, with a variety of neuroimaging and electrophysiological techniques. Here we discuss what kind of information can be gained from combined approaches, which often are technically demanding. We argue that the benefit from this combination is twofold. Firstly, neuroimaging and electrophysiology can inform subsequent NTBS, providing the required information to optimize where, when, and how to stimulate the brain. Information can be achieved both before and during the NTBS experiment, requiring consecutive and concurrent applications, respectively. Secondly, neuroimaging and electrophysiology can provide the readout for neural changes induced by NTBS. Again, using either concurrent or consecutive applications, both “online” NTBS effects immediately following the stimulation and “offline” NTBS effects outlasting plasticity-inducing NTBS protocols can be assessed. Finally, both strategies can be combined to close the loop between measuring and modulating brain activity by means of closed-loop brain state-dependent NTBS. In this paper, we will provide a conceptual framework, emphasizing principal strategies and highlighting promising future directions to exploit the benefits of combining NTBS with neuroimaging or electrophysiology. •A conceptual framework for combining NTBS and functional brain mapping•Neuroimaging and electrophysiology inform about where, when and how to apply NTBS.•Neuroimaging and electrophysiology provide readouts of NTBS-induced neuronal effects.•Informed open-loop NTBS allows to characterize (e.g. oscillatory) brain states.•Closed-loop NTBS allows to target and manipulate specific brain states.

The role of left and right hemisphere brain regions in language recovery after stroke-induced aphasia remains controversial. Here, we summarize how neuroimaging studies increase the current understanding of functional interactions, reorganization and plasticity in the language network. We first discuss the temporal dynamics across the time course of language recovery, with a main focus on longitudinal studies from the acute to the chronic phase after stroke. These studies show that the functional contribution of perilesional and spared left hemisphere as well as contralesional right hemisphere regions to language recovery changes over time. The second section introduces critical variables and recent advances on early prediction of subsequent outcome. In the third section, we outline how multi-method approaches that combine neuroimaging techniques with non-invasive brain stimulation elucidate mechanisms of plasticity and reorganization in the language network. These approaches provide novel insights into general mechanisms of plasticity in the language network and might ultimately support recovery processes during speech and language therapy. Finally, the neurobiological correlates of therapy-induced plasticity are discussed. We argue that future studies should integrate individualized approaches that might vary the combination of language therapy with specific non-invasive brain stimulation protocols across the time course of recovery. The way forward will include the combination of such approaches with large data sets obtained from multicentre studies. •Language recovery is a dynamic process.•Contribution of left and right hemisphere regions changes across time.•Neuroimaging can elucidate neurobiological bases of language recovery.•Treatment-induced plasticity can be mapped with neuroimaging.•Combining imaging and neurostimulation unravels the brain's potential for plasticity.

Transcranial alternating current stimulation (tACS) is a noninvasive method used to modulate activity of superficial brain regions. Deeper and more steerable stimulation could potentially be achieved using transcranial temporal interference stimulation (tTIS): two high-frequency alternating fields interact to produce a wave with an envelope frequency in the range thought to modulate neural activity. Promising initial results have been reported for experiments with mice. In this study we aim to better understand the electric fields produced with tTIS and examine its prospects in humans through simulations with murine and human head models. A murine head finite element model was used to simulate previously published experiments of tTIS in mice. With a total current of 0.776 mA, tTIS electric field strengths up to 383 V/m were reached in the modeled mouse brain, affirming experimental results indicating that suprathreshold stimulation is possible in mice. Using a detailed anisotropic human head model, tTIS was simulated with systematically varied electrode configurations and input currents to investigate how these parameters influence the electric fields. An exhaustive search with 88 electrode locations covering the entire head (146M current patterns) was employed to optimize tTIS for target field strength and focality. In all analyses, we investigated maximal effects and effects along the predominant orientation of local neurons. Our results showed that it was possible to steer the peak tTIS field by manipulating the relative strength of the two input fields. Deep brain areas received field strengths similar to conventional tACS, but with less stimulation in superficial areas. Maximum field strengths in the human model were much lower than in the murine model, too low to expect direct stimulation effects. While field strengths from tACS were slightly higher, our results suggest that tTIS is capable of producing more focal fields and allows for better steerability. Finally, we present optimal four-electrode current patterns to maximize tTIS in regions of the pallidum (0.37 V/m), hippocampus (0.24 V/m) and motor cortex (0.57 V/m). •Temporal interference stimulation (tTIS) can be simulated with finite element methods.•Simulations show similar field strengths in deep brain regions for tTIS and tACS.•tTIS stimulates smaller areas outside target regions compared to tACS.•tTIS in small animals can reach field strengths similar to DBS but not in humans.•tTIS in humans could be a more focal and steerable alternative to tACS.

Transcranial brain stimulation (TBS) has been established as a method for modulating and mapping the function of the human brain, and as a potential treatment tool in several brain disorders. Typically, the stimulation is applied using a one-size-fits-all approach with predetermined locations for the electrodes, in electric stimulation (TES), or the coil, in magnetic stimulation (TMS), which disregards anatomical variability between individuals. However, the induced electric field distribution in the head largely depends on anatomical features implying the need for individually tailored stimulation protocols for focal dosing. This requires detailed models of the individual head anatomy, combined with electric field simulations, to find an optimal stimulation protocol for a given cortical target. Considering the anatomical and functional complexity of different brain disorders and pathologies, it is crucial to account for the anatomical variability in order to translate TBS from a research tool into a viable option for treatment. In this article we present a new method, called CHARM, for automated segmentation of fifteen different head tissues from magnetic resonance (MR) scans. The new method compares favorably to two freely available software tools on a five-tissue segmentation task, while obtaining reasonable segmentation accuracy over all fifteen tissues. The method automatically adapts to variability in the input scans and can thus be directly applied to clinical or research scans acquired with different scanners, sequences or settings. We show that an increase in automated segmentation accuracy results in a lower relative error in electric field simulations when compared to anatomical head models constructed from reference segmentations. However, also the improved segmentations and, by implication, the electric field simulations are affected by systematic artifacts in the input MR scans. As long as the artifacts are unaccounted for, this can lead to local simulation differences up to 30% of the peak field strength on reference simulations. Finally, we exemplarily demonstrate the effect of including all fifteen tissue classes in the field simulations against the standard approach of using only five tissue classes and show that for specific stimulation configurations the local differences can reach 10% of the peak field strength. •We introduce a new automated method for whole-head segmentation.•The method segments 15 different head tissues covering also the neck.•The segmentation accuracy and robustness compare favorably to existing tools.•Choice of scan parameters can cause segmentation and simulation errors up to 30%.•Including extra tissues into the simulation affects the electric field locally.

Motor and cognitive functions are organized in large-scale networks in the human brain that interact to enable flexible adaptation of information exchange to ever-changing environmental conditions. In this review, we discuss the unique potential of the consecutive combination of repetitive transcranial magnetic stimulation (rTMS) and functional neuroimaging to probe network organization and reorganization in the healthy and lesioned brain. First, we summarize findings highlighting the flexible (re-)distribution and short-term reorganization in motor and cognitive networks in the healthy brain. Plastic after-effects of rTMS result in large-scale changes on the network level affecting both local and remote activity within the stimulated network as well as interactions between the stimulated and distinct functional networks. While the number of combined rTMS-fMRI studies in patients with brain lesions remains scarce, preliminary evidence suggests that the lesioned brain flexibly (re-)distributes its computational capacities to functionally reorganize impaired brain functions, using a similar set of mechanisms to achieve adaptive network plasticity compared to short-term reorganization observed in the healthy brain after rTMS. In general, both short-term reorganization in the healthy brain and stroke-induced reorganization seem to rely on three general mechanisms of adaptive network plasticity that allow to maintain and recover function: i) interhemispheric changes, including increased contribution of homologous regions in the contralateral hemisphere and increased interhemispheric connectivity, ii) increased interactions between differentially specialized networks and iii) increased contributions of domain-general networks after disruption of more specific functions. These mechanisms may allow for computational flexibility of large-scale neural networks underlying motor and cognitive functions. Future studies should use complementary approaches to address the functional relevance of adaptive network plasticity and further delineate how these general mechanisms interact to enable network flexibility. Besides furthering our neurophysiological insights into brain network interactions, identifying approaches to support and enhance adaptive network plasticity may result in clinically relevant diagnostic and treatment approaches.

•Diagnosis and management of chronic neuropathic pain are challenging.•Biomarkers as measurable and objective indicators of chronic neuropathic pain are missing.•Resting-state electroencephalography (rsEEG) could provide such biomarkers.•A systematic literature review identified 14 rsEEG studies of patients with neuropathic pain.•Continuous neuropathic pain was associated with an EEG signal power increase in the θ band and possibly the high-β band, but a decrease in the high-α−low-β band.•The location of regional pain-related EEG changes in the pain connectome, as the perspectives offered by advanced techniques of EEG signal analysis and neuromodulation were discussed. Diagnosis and management of chronic neuropathic pain are challenging, leading to current efforts to characterize ‘objective’ biomarkers of pain using imaging or neurophysiological techniques, such as electroencephalography (EEG). A systematic literature review was conducted in PubMed-Medline and Web-of-Science until October 2021 to identify EEG biomarkers of chronic neuropathic pain in humans. The risk of bias was assessed by the Newcastle-Ottawa-Scale. Experimental, provoked, or chronic non-neuropathic pain studies were excluded. We identified 14 studies, in which resting-state EEG spectral analysis was compared between patients with pain related to a neurological disease and patients with the same disease but without pain or healthy controls. From these heterogeneous exploratory studies, some conclusions can be drawn, even if they must be weighted by the fact that confounding factors, such as medication and association with anxio-depressive disorders, are generally not taken into account. Overall, EEG signal power was increased in the θ band (4-7Hz) and possibly in the high-β band (20-30Hz), but decreased in the high-α−low-β band (10-20Hz) in the presence of ongoing neuropathic pain, while increased γ band oscillations were not evidenced, unlike in experimental pain. Consequently, the dominant peak frequency was decreased in the θ-α band and increased in the whole-β band in neuropathic pain patients. Disappointingly, pain intensity correlated with various EEG changes across studies, with no consistent trend. This review also discusses the location of regional pain-related EEG changes in the pain connectome, as the perspectives offered by advanced techniques of EEG signal analysis (source location, connectivity, or classification methods based on artificial intelligence). The biomarkers provided by resting-state EEG are of particular interest for optimizing the treatment of chronic neuropathic pain by neuromodulation techniques, such as transcranial alternating current stimulation or neurofeedback procedures.

Neuroplasticity, which is the dynamic structural and functional reorganization of central nervous system connectivity due to environmental and internal demands, is recognized as a major physiological basis for adaption of cognition, and behavior, and thus of utmost importance for normal brain function. Pathological alterations of plasticity are increasingly explored as pathophysiological foundation of diverse neurological and psychiatric diseases. Non-invasive brain stimulation techniques (NIBS), such as repetitive transcranial magnetic stimulation (rTMS), and transcranial direct current stimulation (tDCS), are able to induce and modulate neuroplasticity in humans. Therefore, they have potential to alter pathological plasticity on the one hand, and foster physiological plasticity on the other, in neuropsychiatric diseases to reduce symptoms, and enhance rehabilitation. tDCS is an emerging NIBS tool, which induces glutamatergic plasticity via application of relatively weak currents through the scalp in humans. In the last years its efficacy to treat neuropsychiatric diseases has been explored increasingly. In this review, we will give an overview of pathological alterations of plasticity in neuropsychiatric diseases, gather clinical studies involving tDCS to ameliorate symptoms, and discuss future directions of application, with an emphasis on optimizing stimulation effects. •tDCS induces neuroplasticity in the human brain.•Pathological plasticity is involved in numerous neuropsychiatric diseases.•tDCS reduces pain and tinnitus symptoms.•tDCS might be valuable for treatment of depression, and other psychiatric diseases.•New stimulation protocols might enhance therapeutic efficacy of tDCS.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation tool that is now being widely used in neuroscientific and clinical research in humans. While initial studies focused on modulation of cortical excitability, the technique quickly progressed to studies on motor and cognitive functions in healthy humans and in patients with neurological diseases. In the present review we will first provide the reader with a brief background on the basic principles of tDCS. In the main part, we will outline recent studies with tDCS that aimed at enhancing behavioral outcome or disease-specific symptoms in patients suffering from mild cognitive impairment, Alzheimer's disease, movement disorders, and epilepsy, or persistent deficits after stroke. The review will close with a summary statement on the present use of tDCS in the treatment of neurological disorders, and an outlook to further developments in this realm. tDCS may be an ideal tool to be administered in parallel to intensive cognitive or motor training in neurological disease, but efficacy for the areas of activities and participation still needs to be established in controlled randomized trials. Its use in reducing disease-specific symptoms like dystonia or epileptic seizures is still unclear. •tDCS shown to modulate cortical excitability and plasticity.•tDCS enhances memory functions in AD.•tDCS enhances motor and language function after stroke.•Impact of tDCS on activities and participation still unclear.