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Visual selective attention studies generally tend to apply cuing paradigms to instructively direct observers’ attention to certain locations, features or objects. However, in real situations, attention in humans often flows spontaneously without any specific instructions. Recently, a concept named “willed attention” was raised in visuospatial attention, in which participants are free to make volitional attention decisions. Several ERP components during willed attention were found, along with a perspective that ongoing alpha activity may bias the subsequent attentional choice. However, it remains unclear whether similar neural mechanisms exist in feature- or object-based willed attention. Here, we included choice cues and instruct cues in a feature-based selective attention paradigm, allowing participants to freely choose or to be instructed to attend a color for the subsequent target detection task. Pre-cue ongoing alpha oscillations, cue-evoked potentials and target-related steady-state visual evoked potentials (SSVEPs) were simultaneously measured as markers of attentional processing. As expected, SSVEP responses were similarly modulated by attention between choice and instruct cue trials. Similar to the case of spatial attention, a willed-attention component (Willed Attention Component, WAC) was isolated during the cue-related choice period by comparing choice and instruct cues. However, pre-cue ongoing alpha oscillations did not predict the color choice (yellow vs blue), as indicated by the chance level decoding accuracy (50%). Overall, our results revealed both similarities and differences between spatial and feature-based willed attention, and thus extended the understanding toward the neural mechanisms of volitional attention.

Laser speckle contrast imaging (LSCI) is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo, but its applications are limited by shallow penetration depth under reflective imaging configuration. The traditional LSCI setup has been used in transmissive imaging for depth extension up to [Formula: see text]–[Formula: see text] ([Formula: see text] is the transport mean free path), but the blood flow estimation is biased due to the depth uncertainty in large depth of field (DOF) images. In this study, we propose a transmissive multifocal LSCI for depth-resolved blood flow in thick tissue, further extending the transmissive LSCI for tissue thickness up to [Formula: see text]. The limited-DOF imaging system is applied to the multifocal acquisition, and the depth of the vessel is estimated using a robust visibility parameter [Formula: see text] in the coherent domain. The accuracy and linearity of depth estimation are tested by Monte Carlo simulations. Based on the proposed method, the model of contrast analysis resolving the depth information is established and verified in a phantom experiment. We demonstrated its effectiveness in acquiring depth-resolved vessel structures and flow dynamics in in vivo imaging of chick embryos.

Visible light optical coherence tomography (vis-OCT) provides a unique tool for imaging both structure and oxygen metabolism in ophthalmology. Working in visible light bandwidth, it suffers from noises due to strong scattering, especially in the blood. This work established the random matrix (RM) description of vis-OCT’s k-space data as ballistic and multiple scattering components. The eigenvalue density of the hybrid RM follows a low-rank biased Marčenko–Pastur law. The ballistic component can thus be separated out using a generalized likelihood ratio test algorithm. The RM-based method was validated by both the Monte Carlo simulation and ex vivo pure blood phantom study. We further demonstrated that the RM-based method could significantly improve the imaging quality in the human fundus, showing more details of the layered structure than current vis-OCT with ∼23.6% increase of signal-to-noise ratio, measuring the blood oxygen value more accurately, and enabling better structure visualization than the traditional method, a 1.6-fold higher contrast-to-noise ratio in raster scan mode. The isolated ballistic component also fits the Beer–Lambert law better, giving more accurate oxygen saturation in arc scan mode. The RM-based method significantly improves the reconstruction quality in 3D and facilitates clinical diagnostics. As a general framework, random matrix description also provides a new separation strategy to estimate the ballistic component in other spectral domain OCT techniques.

Summary: Background: There have been mixed reports on the beneficial effects of meditation in cardiovascular disease (CVD), which is widely considered the leading cause of death worldwide. Methods: To clarify the role of meditation in modulating the heart-brain axis, we implemented an extreme phenotype strategy, i.e., Tibetan monks (BMI > 30) who practised 19.20 ± 7.82 years of meditation on average and their strictly matched non-meditative Tibetan controls. Hypothesis-free advanced proteomics strategies (Data Independent Acquisition and Targeted Parallel Reaction Monitoring) were jointly applied to systematically investigate and target the plasma proteome underlying meditation. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo B) and lipoprotein (a) [Lp(a)] as the potential cardiovascular risk factors were evaluated. Heart rate variability (HRV) was assessed by electrocardiogram. Findings: Obesity, hypertension, and reduced HRV is offset by long-term meditation. Notably, meditative monks have blood pressure and HRV comparable to their matched Tibetan controls. Meditative monks have a protective plasma proteome, related to decreased atherosclerosis, enhanced glycolysis, and oxygen release, that confers resilience to the development of CVD. In addition, clinical risk factors in plasma were significantly decreased in monks compared with controls, including total cholesterol, LDL-C, Apo B, and Lp(a). Interpretation: To our knowledge, this work is the first well-controlled proteomics investigation of long-term meditation, which opens up a window for individuals characterized by a sedentary lifestyle to improve their cardiovascular health with an accessible method practised for more than two millennia. Funding: See the Acknowledgements section.

Background: Intracellular acidosis in the ischemic penumbra can contribute to further cell death, effectively enlarging the infarct core. Restoring the acid-base balance may enhance tissue survivability after cerebral ischemia. Objective: This study investigated whether translocating protons out of penumbral neurons could mitigate tissue acidification and induce neuroprotection in a rodent model of acute cerebral ischemia. Methods: We modulated the penumbral neurons via a light-driven pump to translocate protons out (i.e., archaerhodopsin/ArchT group) or into (i.e., channelrhodopsin-2/ChR2 group) neurons after focal cerebral ischemia in rats. Intracellular pH values were imaged via neutral red (NR) fluorescence and cerebral blood flow (CBF) was monitored through laser speckle contrast imaging (LSCI). Global CBF responses to electrical stimulation of the hindlimbs were obtained 24 h and 48 h after ischemia to assess neurological function. Behavioral and histological outcomes were evaluated 48 h after ischemia. A control group without gene modification was included. Results: The reduction of relative pH (RpH), the amplitude of negative peak of hypoemic response (RNP) and the hemispheric lateralization index (LI) in ArchT group were significantly less than those of the ChR2 or control group. Moreover, RpH was strongly correlated with RNP (r = 0.60) and LI (r24h = 0.80, r48h = 0.59). In addition, behavioral and histological results supported a neuroprotective effect of countering neuronal acidosis in penumbra through optogenetic stimulation. Conclusion(s): These results indicate that countering intracellular acidosis by optogenetically translocating protons out of penumbral neurons during the acute ischemic stage could induce protection after ischemic brain injury.

Pain is a multidimensional process, which can be modulated by emotions; however, the mechanisms underlying this modulation are unknown. We used pictures with different emotional valence (negative, positive, and neutral) as primes and applied electrical painful stimuli as targets to healthy participants. We assessed pain intensity and unpleasantness ratings and recorded electroencephalograms (EEGs). We found that pain unpleasantness and not pain intensity ratings were modulated by emotion, with increased ratings for negative and decreased ratings for positive pictures. We also found two consecutive gamma band oscillations (GBOs) related to pain processing from time frequency analyses of the EEG signals. The early GBO had a cortical distribution contralateral to the painful stimulus and its amplitude was positively correlated with intensity and unpleasantness ratings, but not with prime valence. The late GBO had a centroparietal distribution and its amplitude was larger for negative compared to neutral and positive pictures. The emotional modulation effect (negative vs. positive) of the late GBO amplitude was positively correlated with pain unpleasantness. The early GBO might reflect the overall pain perception, possibly involving the thalamocortical circuit, while the late GBO might be related to the affective dimension of pain and top-down-related processes.

Summary: It has been 40 years since the report of long-term synaptic plasticity on the rodent brain. Transcranial ultrasound stimulation (TUS) shows advantages in spatial resolution and penetration depth when compared with electrical or magnetic stimulation. The repetitive TUS (rTUS) can induce cortical excitability alteration on animals, and persistent aftereffects were observed. However, the effects of rTUS on synaptic plasticity in humans remain unelucidated. In the current study, we applied a 15-min rTUS protocol to stimulate left primary motor cortex (l-M1) in 24 male healthy participants. The single-pulsed transcranial magnetic stimulation-evoked motor evoked potential and Stop-signal task was applied to measure the rTUS aftereffects. Here, we report that conditioning the human motor cortex using rTUS may produce long-lasting and statistically significant effects on motor cortex excitability as well as motor behavior, without harmful side effects observed. These findings suggest a considerable potential of rTUS in cortical plasticity modulation and clinical intervention for impulsivity-related disorders.

Laser speckle contrast imaging (LSCI) is a full-field, high spatiotemporal resolution and low-cost optical technique for measuring blood flow, which has been successfully used for neurovascular imaging. However, due to the low signal–noise ratio and the relatively small sizes, segmenting the cerebral vessels in LSCI has always been a technical challenge. Recently, deep learning has shown its advantages in vascular segmentation. Nonetheless, ground truth by manual labeling is usually required for training the network, which makes it difficult to implement in practice. In this manuscript, we proposed a deep learning-based method for real-time cerebral vessel segmentation of LSCI without ground truth labels, which could be further integrated into intraoperative blood vessel imaging system. Synthetic LSCI images were obtained with a synthesis network from LSCI images and public labeled dataset of Digital Retinal Images for Vessel Extraction, which were then used to train the segmentation network. Using matching strategies to reduce the size discrepancy between retinal images and laser speckle contrast images, we could further significantly improve image synthesis and segmentation performance. In the testing LSCI images of rodent cerebral vessels, the proposed method resulted in a dice similarity coefficient of over 75%.

Abstract Cognitive training has been shown effective in improving the cognitive function of older adults. While training related plasticity of the brain has been observed at different levels, it is still open to exploration whether local functional connectivity (FC) may be affected by training. Here, we examined the neuroimaging data from a previous randomized-controlled double-blinded behavioural study, in which healthy older adults participated in a 3-month cognitive training program. Resting-state fMRI was acquired at baseline and one year after training. The local FC in the brain was estimated using the regional homogeneity (ReHo), and the high ReHo clusters (HRCs) were extracted to quantify the level of local FC integration. Results showed that: (i) HRCs exhibited a power-law size distribution; (ii) local FC were less integrated in older participants than in younger participants; (iii) local FC in older participants of the training group became more integrated after training than the control group; (iv) the baseline local FC integration was positively correlated with educational level. These results indicated a training-related alteration in local FC.

Abstract Cerebrovascular dysfunction characterized by the neurovascular unit (NVU) impairment contributes to the pathogenesis of Alzheimer's disease (AD). In this study, a cerebrovascular‐targeting multifunctional lipoprotein‐biomimetic nanostructure (RAP‐RL) constituted with an antagonist peptide (RAP) of receptor for advanced glycation end‐products (RAGE), monosialotetrahexosyl ganglioside, and apolipoprotein E3 is developed to recover the functional NVU and normalize the cerebral vasculature. RAP‐RL accumulates along the cerebral microvasculature through the specific binding of RAP to RAGE, which is overexpressed on cerebral endothelial cells in AD. It effectively accelerates the clearance of perivascular Aβ, normalizes the morphology and functions of cerebrovasculature, and restores the structural integrity and functions of NVU. RAP‐RL markedly rescues the spatial learning and memory in APP/PS1 mice. Collectively, this study demonstrates the potential of the multifunctional nanostructure RAP‐RL as a disease‐modifying modality for AD treatment and provides the proof of concept that remodeling the functional NVU may represent a promising therapeutic approach toward effective intervention of AD.

Parkinson’s disease (PD) is a neurodegenerative disease characterized by dysfunction in distributed functional brain networks. Previous studies have reported abnormal changes in static functional connectivity using resting-state functional magnetic resonance imaging (fMRI). However, the dynamic characteristics of brain networks in PD is still poorly understood. This study aimed to quantify the characteristics of dynamic functional connectivity in PD patients at nodal, intra- and inter-subnetwork levels. Resting-state fMRI data of a total of 42 PD patients and 40 normal controls (NCs) were investigated from the perspective of the temporal variability on the connectivity profiles across sliding windows. The results revealed that PD patients had greater nodal variability in precentral and postcentral area (in sensorimotor network, SMN), middle occipital gyrus (in visual network), putamen (in subcortical network) and cerebellum, compared with NCs. Furthermore, at the subnetwork level, PD patients had greater intra-network variability for the subcortical network, salience network and visual network, and distributed changes of inter-network variability across several subnetwork pairs. Specifically, the temporal variability within and between subcortical network and other cortical subnetworks involving SMN, visual, ventral and dorsal attention networks as well as cerebellum was positively associated with the severity of clinical symptoms in PD patients. Additionally, the increased inter-network variability of cerebellum-auditory pair was also correlated with clinical severity of symptoms in PD patients. These observations indicate that temporal variability can detect the distributed abnormalities of dynamic functional network of PD patients at nodal, intra- and inter-subnetwork scales, and may provide new insights into understanding PD.

Background: The capacity for TMS to elicit neural activity and manipulate cortical excitability has created significant expectation regarding its use in both cognitive and clinical neuroscience. However, the absence of an ability to quantify stimulation effects, particularly outside of the motor cortex, has led clinicians and researchers to pair noninvasive brain stimulation with noninvasive neuroimaging techniques. fNIRS, as an optical and wearable neuroimaging technique, is an ideal candidate for integrated use with TMS. Together, TMS+fNIRS may offer a hybrid alternative to “blind” stimulation to assess NIBS in therapy and research.Objective: In this systematic review, the current body of research into the transient and prolonged effects of TMS on fNIRS-based cortical hemodynamic measures while at rest and during tasks are discussed. Additionally, studies investigating the relation of fNIRS to measures of cortical excitability as produced by TMS-evoked Motor-Evoked-Potential (MEP) are evaluated. The aim of this review is to outline the integrated use of TMS+fNIRS and consolidate findings related to use of fNIRS to monitor changes attributed to TMS and the relationship of fNIRS to cortical excitability itself.Methods: Key terms were searched in PubMed and Web-of-Science to identify studies investigating the use of both fNIRS and TMS. Works from Google-Scholar and referenced works in identified papers were also assessed for relevance. All published experimental studies using both fNIRS and TMS techniques in the study methodology were included.Results: A combined literature search of neuroimaging and neurostimulation studies identified 53 papers detailing the joint use of fNIRS and TMS. 22/53 investigated the immediate effects of TMS at rest in the DLPFC and M1 as measured by fNIRS. 21/22 studies reported a significant effect in [HbO] for 40/54 stimulation conditions with 14 resulting an increase and 26 in a decrease. While 15/22 studies also reported [HbR], only 5/37 conditions were significant. Task effects of fNIRS+TMS were detailed in 16 studies, including 10 with clinical populations. Most studies only reported significant changes in [HbO] related measures. Studies comparing fNIRS to changes in MEP-measured cortical excitability suggest that fNIRS measures may be spatially more diffuse but share similar traits.Conclusion: This review summarizes the progress in the development of this emerging hybrid neuroimaging & neurostimulation methodology and its applications. Despite encouraging progress and novel applications, a lack of replicated works, along with highly disparate methodological approaches, highlight the need for further controlled studies. Interpretation of current research directions, technical challenges of TMS+fNIRS, and recommendations regarding future works are discussed.

In this paper, we review the current state-of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering: neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity (via a neuroimaging modality) through a neural interface (invasive or noninvasive) and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering—to develop neurotechniques for enhancing the understanding of whole-brain function and dysfunction, and the management of neurological and mental disorders.

The intact crossed pathway via which the contralesional hemisphere responds to the ipsilesional somatosensory input has shown to be affected by unilateral stroke. The aim of this study was to investigate the plasticity of the intact crossed pathway in response to different intensities of stimulation in a rodent photothrombotic stroke model. Using optical intrinsic signal imaging, an overall increase of the contralesional cortical response was observed in the acute phase (≤48 hours) after stroke. In particular, the contralesional hyperactivation is more prominent under weak stimulations, while a strong stimulation would even elicit a depressed response. The results suggest a distinct stimulation-response pattern along the intact crossed pathway after stroke. We speculate that the contralesional hyperactivation under weak stimulations was due to the reorganization for compensatory response to the weak ipsilateral somatosensory input.

Separation of arteries and veins in the cerebral cortex is of significant importance in the studies of cortical hemodynamics, such as the changes of cerebral blood flow, perfusion or oxygen concentration in arteries and veins under different pathological and physiological conditions. Yet the cerebral vessel segmentation and vessel-type separation are challenging due to the complexity of cortical vessel characteristics and low spatial signal-to-noise ratio. In this work, we presented an effective full-field method to differentiate arteries and veins in cerebral cortex using dual-modal optical imaging technology including laser speckle imaging (LSI) and optical intrinsic signals (OIS) imaging. The raw contrast images were acquired by LSI and processed with enhanced laser speckle contrast analysis (eLASCA) algorithm. The vascular pattern was extracted and segmented using region growing algorithm from the eLASCA-based LSI. Meanwhile, OIS images were acquired alternatively with 630 and 870 nm to obtain an oxyhemoglobin concentration map over cerebral cortex. Then the separation of arteries and veins was accomplished by Otsu threshold segmentation algorithm based on the OIS information and segmentation of LSI. Finally, the segmentation and separation performances were assessed using area overlap measure (AOM). The segmentation and separation of cerebral vessels in cortical optical imaging have great potential applications in full-field cerebral hemodynamics monitoring and pathological study of cerebral vascular diseases, as well as in clinical intraoperative monitoring.

Although motor imagery could improve motor rehabilitation, the detailed neural mechanisms of motor imagery cognitive process of stroke patients, particularly from functional network perspective, remain unclear. This study investigated functional brain network properties in each cognitive sub-stage of motor imagery of stroke patients with ischemic lesion in left hemisphere to reveal the impact of stroke on the cognition of motor imagery. Both stroke patients and control subjects participated in mental rotation task, which includes three cognitive sub-stages: visual stimulus perception, mental rotation and response cognitive process. Event-related electroencephalograph was recorded and interdependence between two different cortical areas was assessed by phase synchronization. Both global and nodal properties of functional networks in three sub-stages were statistically analyzed. Phase synchronization of stroke patients significantly reduced in mental rotation sub-stage. Longer characteristic path length and smaller global clustering coefficient of functional network were observed in patients in mental rotation sub-stage which implied the impaired segregation and integration. Larger nodal clustering coefficient and betweenness in contralesional occipitoparietal and frontal area respectively were observed in patients in all sub-stages. In addition, patients also showed smaller betweenness in ipsilesional central-parietal area in response sub-stage. The compensatory effects on local connectedness and centrality indicated the neuroplasticity in contralesional hemisphere. The functional brain networks of stroke patients demonstrated significant alterations and compensatory effects during motor imagery.

BACKGROUND: Motor imagery training is a promising rehabilitation strategy for stroke patients. However, few studies had focused on the neural mechanisms in time course of its cognitive process. This study investigated the cognitive alterations after left hemispheric ischemic stroke during motor imagery task. METHODOLOGY/PRINCIPAL FINDINGS: Eleven patients with ischemic stroke in left hemisphere and eleven age-matched control subjects participated in mental rotation task (MRT) of hand pictures. Behavior performance, event-related potential (ERP) and event-related (de)synchronization (ERD/ERS) in beta band were analyzed to investigate the cortical activation. We found that: (1) The response time increased with orientation angles in both groups, called "angle effect", however, stoke patients' responses were impaired with significantly longer response time and lower accuracy rate; (2) In early visual perceptual cognitive process, stroke patients showed hypo-activations in frontal and central brain areas in aspects of both P200 and ERD; (3) During mental rotation process, P300 amplitude in control subjects decreased while angle increased, called "amplitude modulation effect", which was not observed in stroke patients. Spatially, patients showed significant lateralization of P300 with activation only in contralesional (right) parietal cortex while control subjects showed P300 in both parietal lobes. Stroke patients also showed an overall cortical hypo-activation of ERD during this sub-stage; (4) In the response sub-stage, control subjects showed higher ERD values with more activated cortical areas particularly in the right hemisphere while angle increased, named "angle effect", which was not observed in stroke patients. In addition, stroke patients showed significant lower ERD for affected hand (right) response than that for unaffected hand. CONCLUSIONS/SIGNIFICANCE: Cortical activation was altered differently in each cognitive sub-stage of motor imagery after left hemispheric ischemic stroke. These results will help to understand the underlying neural mechanisms of mental rotation following stroke and may shed light on rehabilitation based on motor imagery training.