Neurofeedback using functional spectroscopy

Neurofeedback based on real‐time measurement of the blood oxygenation level‐dependent (BOLD) signal has potential for treatment of neurological disorders and behavioral enhancement. Commonly used methods are based on functional magnetic resonance imaging (fMRI) sequences that sacrifice speed and accuracy for whole‐brain coverage, which is unnecessary in most applications. We present multivoxel functional spectroscopy (MVFS): a system for computing the BOLD signal from multiple volumes of interest (VOI) in real‐time that improves speed and accuracy of neurofeedback. MVFS consists of a FS pulse sequence, a BOLD reconstruction component, a neural activation estimator, and a stimulus system. The FS pulse sequence is a single‐voxel, magnetic resonance spectroscopy sequence without water suppression that has been extended to allow acquisition of a different VOI at each repetition and real‐time subject head motion compensation. The BOLD reconstruction component determines the T2* decay rate, which is directly related to BOLD signal strength. The neural activation estimator discounts nuisance signals and scales the activation relative to the amount of ROI noise. Finally, the neurofeedback system presents neural activation‐dependent stimuli to experimental subjects with an overall delay of less than 1 s. Here, we present the MVFS system, validation of certain components, examples of its usage in a practical application, and a direct comparison of FS and echo‐planar imaging BOLD measurements. We conclude that in the context of realtime BOLD imaging, MVFS can provide superior accuracy and temporal resolution compared with standard fMRI methods. © 2014 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 24, 138–148, 2014     

A study of long‐term fMRI reproducibility using data‐driven analysis methods

The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI‐based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long‐term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet‐domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long‐term reproducibility. A multivariate support vector machine (SVM)‐based method was used to identify active voxels, and compared to a widely used general linear model (GLM)‐based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions‐of‐interest (ROI) related to a motor task were defined based upon which the long‐term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet‐based spatial smoothing and SVM‐based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within‐subject long‐term reproducibility. A reasonable long‐term reproducibility was also observed from the inter‐subject study. It was found that the short‐term reproducibility is usually higher than the long‐term reproducibility. Furthermore, the results indicate that brain regions with high contrast‐to‐noise ratio do not necessarily exhibit high reproducibility. These findings may provide supportive information for optimal design/implementation of fMRI studies and data interpretation.     

fMRI analysis of excessive binocular disparity on the human brain

The aim of this study is to evaluate brain regions related with excessive binocular disparity that may be linked to stereoscopic visual fatigue. In stereoscopic displays, excessive binocular disparity may generate blurring or double vision in the stereovision and induce unnatural oscillations in accommodation and vergence. These phenomena may lead to visual fatigue and activation (or deactivation) of human brain related with sensory and eye movement functions. A functional magnetic resonance imaging (fMRI) method is used to investigate the effect of excessive binocular disparity on human brain. Subjective assessments of visual fatigue are also conducted with the same stimuli as the fMRI experiment. Based on the subjective assessment results, participants are classified into low‐ and high‐fatigue groups. From the fMRI experiments, the high‐fatigue group showed more activation at the intraparietal sulcus (IPS) than the low‐fatigue group, when viewing an excessive disparity stimulus. The results showed that the excessive binocular disparity stimulus may induce overload to the IPS region, which is related with stereo processing and saccadic eye movement. In addition, it could be possible to use fMRI as an objective measurement method for understanding the stereoscopic visual fatigue when stimuli with excessive binocular disparity are applied.     

基于功能磁共振成像方法的单相抑郁症情绪加工特点研究

运用功能磁共振成像(fMRI)技术,采用适合中国人情绪加工特点的表情图片(愉快、悲伤和中性表情)作为刺激材料,选取15名严格入组的未服药单相抑郁症女性患者与15名条件匹配的正常志愿者,对其情绪加工的大脑活动进行了对比研究。结果发现,与中性表情相比,在加工愉快表情时,抑郁症患者激活了右侧前额叶,而正常对照组激活的是左侧前额叶;在悲伤表情条件下,抑郁症患者激活了双侧颞下回,而正常对照组激活的是双侧前额叶。结果还发现,与正常对照组相比,抑郁症患者在双侧额下回三角区、右侧眶额下回、右侧颞下回等脑区的激活范围和强度均有所减少,尤其在加工悲伤表情时表现得更明显。该结果表明,单相抑郁症病人不仅在情绪加工相关脑区的功能上出现异常,而且加工情绪的脑区也可能出现了转移。     

New fMRI analysis method for multiple stimuli using reference estimation

The stimulation paradigms of a functional MRI (fMRI) usually consist of one or more stimulations and a resting state in the block‐based and event‐related designs. To localize the activation areas in the human brain, each voxel is statistically analyzed using the fMRI data measured with the stimulation. The conventional method can be inefficient for experiments with multiple stimuli because of measuring the resting‐state signals repeatedly, causing redundancy in the scanning process. Although the phase mapping method can be applied to reduce the redundant resting‐state measurements, there are still limitations in the detection of regions activated by multiple stimuli and the periodic sequence of the multiple stimuli. In this article, a new fMRI data analysis method is presented that enables the detection of functional activations without the resting‐state images. This method estimates the reference signal from the signals acquired during multiple stimuli, and a random sequence and various durations of the multiple stimuli can be applied. Therefore, it can be used in the event‐related design as well as the block‐based design. The results of simulation and fMRI experiments show that the proposed method can correctly detect the activation regions of multiple stimuli, even for overlap regions, and can reduce the imaging time by skipping the resting‐state imaging. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 315–322, 2011     

Spatio-temporal skin strain distributions evoke low variability spike responses in cuneate neurons

A common method to explore the somatosensory function of the brain is to relate skin stimuli to neurophysiological recordings. However, interaction with the skin involves complex mechanical effects. Variability in mechanically induced spike responses is likely to be due in part to mechanical variability of the transformation of stimuli into spiking patterns in the primary sensors located in the skin. This source of variability greatly hampers detailed investigations of the response of the brain to different types of mechanical stimuli. A novel stimulation technique designed to minimize the uncertainty in the strain distributions induced in the skin was applied to evoke responses in single neurons in the cat. We show that exposure to specific spatio-temporal stimuli induced highly reproducible spike responses in the cells of the cuneate nucleus, which represents the first stage of integration of peripheral inputs to the brain. Using precisely controlled spatio-temporal stimuli, we also show that cuneate neurons, as a whole, were selectively sensitive to the spatial and to the temporal aspects of the stimuli. We conclude that the present skin stimulation technique based on localized differential tractions greatly reduces response variability that is exogenous to the information processing of the brain and hence paves the way for substantially more detailed investigations of the brain''s somatosensory system.     

Variations in BOLD response latency estimated from event‐related fMRI at 3T: Comparisons between gradient‐echo and Spin‐echo

Functional magnetic resonance imaging (fMRI) commonly uses gradient‐recalled echo (GRE) signals to detect regional hemodynamic variations originating from neural activities. While the spatial localization of activation shows promising applications, indexing temporal response remains a poor mechanism for detecting the timing of neural activity. Particularly, the hemodynamic response may fail to resolve sub‐second temporal differences between brain regions because of its signal origin or noise in data, or both. This study aimed at evaluating the performance of latency estimation using different fMRI techniques, with two event‐related experiments at 3T. Experiment I evaluated latency variations within the visual cortex and their relationship with contrast‐to‐noise ratios (CNRs) for GRE, spin echo (SE), and diffusion‐weighted SE (DWSE). Experiment II used delayed visual stimuli between two hemifields (delay time = 0, 250, and 500 ms, respectively) to assess the temporal resolving power of three protocols: GRE_TR1000, GRE_TR500, and SE_TR1000. The results of experiment I showed the earliest latency with DWSE, followed by SE, and then GRE. Latency variations decreased as CNR increased. However, similar variations were found between GRE and SE, when the latter had lower CNR. In experiment II, measured stimulus delays from all conditions were significantly correlated with preset stimulus delays. Inter‐subject variation in the measured delay was found to be greatest with GRE_TR1000, followed by GRE_TR500, and the least with SE_TR1000. Conclusively, blood oxygenation level‐dependent responses obtained from GRE exhibit greater CNR but no compromised latency variations in the visual cortex. SE is potentially capable of improving the performance of latency estimation, especially for group analysis. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 215–221, 2013     

Ideal observer analysis for task normalization of pattern classifier performance applied to EEG and fMRI data

The application of multivariate techniques to neuroimaging and electrophysiological data has greatly enhanced the ability to detect where, when, and how functional neural information is processed during a variety of behavioral tasks. With the extension to single-trial analysis, neuroscientists are able to relate brain states to perceptual, cognitive, and motor processes. Using pattern classification methods, the neuroscientist can extract neural performance measures in a manner analogous to human behavioral performance, allowing for a consistent information content metric across measurement modalities. However, as with behavioral psychophysical performance, pattern classifier performances are a product of both the task-relevant information inherent in the brain and in the task/stimuli. Here, we argue for the use of an ideal observer framework with which the researcher can effectively normalize the observed neural performance given the task's inherent objective difficulty. We use data from a face versus car discrimination task and compare classifier performance applied to electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data with corresponding human behavior through the absolute and relative efficiency metrics. We show that confounding variables that can lead to erroneous interpretations of information content can be accounted for through comparisons to an ideal observer, allowing for more confident interpretation of the neural mechanisms involved in the task of interest. Finally, we discuss limitations of interpretation due to the transduction of indirect measures of neural activity, underlying assumptions in the optimality of the pattern classifiers, and dependence of efficiency results on signal contrast.     

Tactile sensor based on piezoelectric resonance

We discuss here the realization of tactile sensors based on the principle of change in piezoelectric resonance frequency with the applied pressure. An array of electrodes has been adopted on either side of the PZT material to have independent resonators. The common areas sandwiched between the electrodes and excitable at resonance frequency of the PZT material are used to form the sensitive area of the tactile sensor. The electrodes were deposited using sputtering technique. Tactile sensors with 3/spl times/3, 7/spl times/7, and 15/spl times/15 array of electrodes are developed with different electrode dimensions and separation between the electrodes. The tactile sensor has been interfaced to computer for the convenience of automatic scanning and making it more user interactive. The tactile sensors developed with different spatial resolution were tested for different shaped objects placed in contact with the sensor. The 3/spl times/3 matrix tactile sensor showed relatively poor spatial resolution, whereas the 15/spl times/15- matrix tactile sensor showed improved spatial resolution. The sensor with 7/spl times/7 matrix elements was tested for its sensitivity to different extents of applied force/pressure. The output response study carried out on the sensors indicated that these sensors can provide information not only about the extent of force/pressure applied on the object, but also the contour of the object which is in contact with the sensor.     

Senescence of spatial chromatic contrast sensitivity. I. Detection under conditions controlling for optical factors

Chromatic contrast thresholds for spatially varying patterns of various spatial frequencies (0.5, 1, 2, and 4 cycles per degree) were measured for ten older (65-77 yr of age) and ten younger (18-30 yr of age) observers. The stimuli were Gabor patches modulated along S-varying or (L - M)-varying chromatic axes. Thresholds were determined for two sets of stimuli. For one set of stimuli, the mean chromaticity and luminance were equated at the cornea for all observers. The second set of stimuli was corrected for ocular media density differences to equate stimulation of each of the three cone types at the retina for each individual. Chromatic contrast thresholds were higher for older observers for all stimuli tested. The magnitude of this difference showed little dependence on spatial frequency. When stimuli were equated at the cornea, this difference was greater for S-varying stimuli. When stimuli were equated at the retina, the age-related difference in thresholds for S-varying stimuli was reduced. Both optical and neural factors contribute to these age-related losses in spatial chromatic contrast sensitivity.     

Color tuning in alert macaque V1 assessed with fMRI and single-unit recording shows a bias toward daylight colors

Colors defined by the two intermediate directions in color space, "orange-cyan" and "lime-magenta," elicit the same spatiotemporal average response from the two cardinal chromatic channels in the lateral geniculate nucleus (LGN). While we found LGN functional magnetic resonance imaging (fMRI) responses to these pairs of colors were statistically indistinguishable, primary visual cortex (V1) fMRI responses were stronger to orange-cyan. Moreover, linear combinations of single-cell responses to cone-isolating stimuli of V1 cone-opponent cells also yielded stronger predicted responses to orange-cyan over lime-magenta, suggesting these neurons underlie the fMRI result. These observations are consistent with the hypothesis that V1 recombines LGN signals into "higher-order" mechanisms tuned to noncardinal color directions. In light of work showing that natural images and daylight samples are biased toward orange-cyan, our findings further suggest that V1 is adapted to daylight. V1, especially double-opponent cells, may function to extract spatial information from color boundaries correlated with scene-structure cues, such as shadows lit by ambient blue sky juxtaposed with surfaces reflecting sunshine.     

A Digital−Analog Bimodal Memristor Based on CsPbBr3 for Tactile Sensory Neuromorphic Computing

Memristor with digital and analog bipolar bimodal resistive switching offers a promising opportunity for the information-processing component. However, it still remains a huge challenge that the memristor enables bimodal digital and analog types and fabrication of artificial sensory neural network system. Here, a proposed CsPbBr₃-based memristor demonstrates a high ON/OFF ratio (>10³), long retention (>10⁴ s), stable endurance (100 cycles), and multilevel resistance memory, which acts as an artificial synapse to realize fundamental biological synaptic functions and neuromorphic computing based on controllable resistance modulation. Moreover, a 5 × 5 spinosum-structured piezoresistive sensor array (sensitivity of 22.4 kPa⁻¹, durability of 1.5 × 10⁴ cycles, and fast response time of 2.43 ms) is constructed as a tactile sensory receptor to transform mechanical stimuli into electrical signals, which can be further processed by the CsPbBr₃-based memristor with synaptic plasticity. More importantly, this artificial sensory neural network system combined the artificial synapse with 5 × 5 tactile sensing array based on piezoresistive sensors can recognize the handwritten patterns of different letters with high accuracy of 94.44% under assistance of supervised learning. Consequently, the digital−analog bimodal memristor would demonstrate potential application in human–machine interaction, prosthetics, and artificial intelligence.     

基于振动触觉感知研究的头戴预警设备开发设计

目的 在预警场景下应用振动触觉传递警报信号以弥补受损的感觉通道,探索头戴振动设备的合理形式,从而为头戴振动设备的工业设计提供指导.方法 围绕空间分布位置、时间和振动参数设置实验,研究振动触觉的特征,提出一种振动触觉系统.在实验一中,对头部进行触觉感知性测量以比较不同位置的灵敏性,确定振动作用于头部的适宜部位.在实验二中,组合不同的时间模式以及强弱程度形成7种振动模式,通过比较得出适于传达警报信息的触觉模式.基于实验结论,设计出一款应用于建筑工地场景下的工程预警头盔.结果 前额无毛区域与颞部中央区域感受性最灵敏;时间间隔短、强度高的振动模式更适于传达警报信息.结论 感知实验的结论为振动组件的布置和振动警报模式的参数设定提供了依据,并有效地被运用于针对具体场景的头戴设备设计中.     

Decoding visual network-related dynamic functional connectivity for eyes-open and eyes-closed using machine learning

Eyes-open (EO) and eyes-closed (EC) are the two experimental conditions during resting state functional magnetic resonance imaging (fMRI) scan sessions. However, the dynamic neural mechanisms of EO/EC based on intrinsic connectivity networks (ICNs) remains largely unexplored. This paper aimed to decode the dynamic internetwork neural mechanisms for EO/EC using data mining and to identify EO/EC resting state fMRI scans based on machine learning. To achieve these goals, the two states were analyzed using the discriminative models, resulting in total accuracy of 85.87%, a sensitivity of 91.3%, and a specificity of 80.43%. In addition, the discriminative features discovered using data mining were related to previous findings. In summary, we applied visual network-related inter-ICN features to decode the neural mechanisms of EO/EC. The reproducible results suggested that visual network-related inter-ICN dynamic features could be beneficial for decoding visual attentions, and had potential as neuroimaging-markers to identify EO/EC resting state fMRI scans.     

Robotic tactile recognition of pseudorandom encoded objects

This paper discusses an original model-based method for blind robotic tactile recognition of three-dimensional objects. Conveniently shaped geometric symbols representing terms of a pseudorandom array (PRA) are embossed on object surfaces. Symbols recovered by tactile probing are recognized using a neural network and then clustered in a PRA window that contains enough information to fully identify the absolute coordinates of the recovered window within the encoding PRA. By knowing how different object models were mapped to the PRA, it is possible to unambiguously identify the object face and the exact position of the recovered symbols on the face.     

Contrast sensitivity loss with aging: sampling efficiency and equivalent noise at different spatial frequencies

The relative contributions of optical and neural factors to the decrease in visual function with aging were investigated by measurement of contrast detection at three different spatial frequencies, in the presence of external noise, on young and older subjects. Contrast detection in noise functions allows two parameters to be measured: sampling efficiency, which indicates neural changes, and equivalent noise, which demonstrates optical effects. Contrast thresholds were measured in the presence of four levels (including zero) of externally added visual noise. Measurements were obtained from eight young and eight older visually normal observers. Compared with young subjects, older subjects showed significantly (p < 0.05) lower sampling efficiencies at spatial frequencies of 1 and 4 cycles per degree (c/deg) and significantly higher equivalent noise levels for gratings of 10 c/deg. Neural and optical factors affect contrast sensitivity loss with aging differently, depending on the spatial frequency tested, implying the existence of different mechanisms.     

Age-related changes in wavelength discrimination

Wavelength discrimination functions (420 to 620-650 nm) were measured for four younger (mean 30.9 years) and four older (mean 72.5 years) observers. Stimuli consisted of individually determined isoluminant monochromatic lights (10 Td) presented in each half of a 2 degrees circular bipartite field with use of a Maxwellian-view optical system. A spatial two-alternative forced-choice method was used in combination with a staircase procedure to determine discrimination thresholds across the spectrum. Small but consistent elevations in discrimination thresholds were found for older compared with younger observers. Because the retinal illuminance of the stimuli was equated across all observers, these age-related losses in discrimination are attributable to neural changes. Analyses of these data reveal a significant change in Weber fraction across adulthood for a chromatically opponent pathway receiving primarily antagonistic signals from middle-wavelength-sensitive and long-wavelength-sensitive cones but not for a short-wavelength-sensitive cone pathway.     

Stretchable Triboelectric–Photonic Smart Skin for Tactile and Gesture Sensing

Smart skin is expected to be stretchable and tactile for bionic robots as the medium with the ambient environment. Here, a stretchable triboelectric–photonic smart skin (STPS) is reported that enables multidimensional tactile and gesture sensing for a robotic hand. With a grating‐structured metal film as the bioinspired skin stripe, the STPS exhibits a tunable aggregation‐induced emission in a lateral tensile range of 0–160%. Moreover, the STPS can be used as a triboelectric nanogenerator for vertical pressure sensing with a maximum sensitivity of 34 mV Pa^?1. The pressure sensing characteristics can remain stable in different stretching conditions, which demonstrates a synchronous and independent sensing property for external stimuli with great durability. By integrating on a robotic hand as a conformal covering, the STPS shows multidimensional mechanical sensing abilities for external touch and different gestures with joints bending. This work has first demonstrated a triboelectric–photonic coupled multifunctional sensing terminal, which may have great applications in human–machine interaction, soft robots, and artificial intelligence.     

Group inference of default‐mode networks from functional magnetic resonance imaging data: comparison of random‐ and mixed‐effects group statistics

Default‐mode network (DMN) activity measured with functional magnetic resonance imaging (fMRI) represents dominant intrinsic neuronal activations of the human brain during rest as opposed to task periods. Previous studies have demonstrated the utility of DMNs in identifying characteristic traits such as hyperactivation and hypoactivation from group‐level fMRI data. However, these group‐level spatial patterns (SPs) were mostly based on random‐effect (RFX) statistics determined using only the intersubject variability. To reduce the potentially significant level of variability in group‐level SPs in RFX due to intrasubject variability, we were motivated to adopt a mixed‐effects (MFX) statistics that is using both intrasubject and intersubject variability. Publicly available group fMRI database during resting state was analyzed using a temporal concatenation‐based group independent component (IC) analysis, and DMN‐related ICs at the group‐level were automatically selected. The individual‐level SPs of these DMN‐related ICs were subsequently estimated using a dual‐regression approach. Using these individual‐level SPs, we evaluated the reproducibility and potential variability of the DMNs from the RFX and MFX statistics using performance measures including (1) neuronal activation levels, (2) percentages of overlap, (3) Pearson's spatial correlation coefficients, and (4) the distances between center‐of‐clusters. The resulting SPs from the MFX‐based group inference showed a significantly greater level of reproducibility than those from the RFX‐based group inference as tested in a bootstrapping framework Family‐wise error (FWE)‐corrected p < 10^?10, one‐way analysis of variance (ANOVA)). The reported findings may provide a valuable supplemental option for investigating the neuropsychiatric group‐ or condition‐dependent characteristic traits implicated in DMNs. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 121–131, 2012     

Stereoscopic 3D objects evoke stronger saliency for nonverbal working memory: An fMRI study

Effective working memory (WM) training is often desired to improve WM. Recent studies have suggested that WM training is more successful when participants monitor scenes in three‐dimensional (3D) environments. Although previous neuroimaging studies have examined visuospatial WM in relation to a 3D scene or object, these studies did not investigate WM using stereoscopic 3D object stimuli. We used functional magnetic resonance imaging (fMRI) to identify brain activation during an N‐back task with 3D object stimuli, and determined the difference in activation pattern between stereoscopic versus shaded 3D objects. We found that the anterior insula, ventral striatum, and posterior orbitofrontal cortex showed greater activation during the 2‐back task with stereoscopic 3D objects than with shaded 3D objects. These regions have previously been associated with a salience network.