Integrated MEG/fMRI Model Validated Using Real Auditory Data

The main objective of this paper is to present methods and results for the estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) model. We use real auditory MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data were acquired at different times, but the stimulus profile was the same for both techniques. We use independent component analysis (ICA) to extract activation-related signal from the MEG data. The stimulus-correlated ICA component is used to estimate MEG parameters of the model. The temporal and spatial information of the fMRI datasets are used to estimate fMRI parameters of the model. The estimated parameters have reasonable means and standard deviations for all subjects. Goodness of fit of the real data to our model shows the possibility of using the proposed model to simulate realistic datasets for evaluation of integrated MEG/fMRI analysis methods.     

Identifying Cortical Lateralization of Speech Processing in Infants Using Near-Infrared Spectroscopy

We investigate the utility of near-infrared spectroscopy (NIRS) as an alternative technique for studying infant speech processing. NIRS is an optical imaging technology that uses relative changes in total hemoglobin concentration and oxygenation as an indicator of neural activation. Procedurally, NIRS has the advantage over more common methods (e.g., fMRI) in that it can be used to study the neural responses of behaviorally active infants. Older infants (aged 6–9 months) were allowed to sit on their caretakers' laps during stimulus presentation to determine relative differences in focal activity in the temporal region of the brain during speech processing. Results revealed a dissociation of sensory-specific processing in two cortical regions, the left and right temporal lobes. These findings are consistent with those obtained using other neurophysiological methods and point to the utility of NIRS as a means of establishing neural correlates of language development in older (and more active) infants.     

Localization of Broca's area using verb generation tasks in the MEG: Validation against fMRI

Functional MRI (fMRI) is routinely used to non-invasively localize language areas. Magnetoencephalography (MEG) is being explored as an alternative technique. MEG tasks to localize receptive language are well established although there are no standardized tasks to localize expressive language areas. We developed two expressive language tasks for MEG and validated their localizations against fMRI data. Ten right-handed adolescents (μ = 17.5 years) were tested with fMRI and MEG on two tasks: verb generation to pictures and verb generation to words. MEG and fMRI data were normalized and overlaid. The number of overlapping voxels activated in fMRI and MEG were counted for each subject, for each task, at different thresholding levels. For picture verb generation, there was 100% concordance between MEG and fMRI lateralization, and for word verb generation, there was 75% concordance. A count showed 79.6% overlap of voxels activated by both MEG and fMRI for picture verb generation and 50.2% overlap for word verb generation. The percentage overlap decreased with increasingly stringent activation thresholds. Our novel MEG expressive language tasks successfully identified neural regions involved in language production and showed high concordance with fMRI laterality. Percentage overlap of activated voxels was also high when validated against fMRI, but showed task-specific and threshold-related effects. The high concordance and high percentage overlap between fMRI and MEG activations confirm the validity of our new MEG task. Furthermore, the higher concordance from the picture verb generation task suggests that this is a promising task for use in the young clinical population.     

Variability comparison of simultaneous brain near-infrared spectroscopy and functional magnetic resonance imaging during visual stimulation

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional magnetic resonance imaging (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We concluded that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties, which may be better accounted for by emerging NIRS technology.     

Variability comparison of simultaneous brain near-infrared spectroscopy and functional magnetic resonance imaging during visual stimulation

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional magnetic resonance imaging (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We concluded that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties, which may be better accounted for by emerging NIRS technology.     

A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study

fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging.     

Integrated MEG and fMRI Model: Synthesis and Analysis

Summary: An integrated model for magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) is proposed. In the model, the neural activity is related to the Post Synaptic Potentials (PSPs) which is common link between MEG and fMRI. Each PSP is modeled by the direction and strength of its current flow which are treated as random variables. The overall neural activity in each voxel is used for equivalent current dipole in MEG and as input of extended Balloon model in fMRI. The proposed model shows the possibility of detecting activation by fMRI in a voxel while the voxel is silent for MEG and vice versa. Parameters of the model can illustrate situations like closed field due to non-pyramidal cells, canceling effect of inhibitory PSP on excitatory PSP, and effect of synchronicity. In addition, the model shows that the crosstalk from neural activities of the adjacent voxels in fMRI may result in the detection of activations in these voxels that contain no neural activities. The proposed model is instrumental in evaluating and comparing different analysis methods of MEG and fMRI. It is also useful in characterizing the upcoming combined methods for simultaneous analysis of MEG and fMRI. This work was supported in part by the Research Council of the University of Tehran, Tehran, Iran. The authors would like to thank Dr. John Moran from the Neurology Department, Henry Ford Health System, Detroit, Michigan, USA for his helpful discussions and kind assistance.     

Reliability and validity of functional neuroimaging techniques for identifying language-critical areas in children and adults

Advances in neuroimaging technologies over the last 15 years have prompted their relatively widespread use in the study of brain mechanisms supporting language function in children and adults. We reviewed reliability and external validity studies of 3 of the most common functional imaging methods, functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and positron emission tomography (PET). Although reliability and validity reports for fMRI are generally quite favorable, significant variability was found across studies with respect to methodology, preventing in some cases either the assessment of the reliability of individual datasets, or cross-study comparisons. Reliability and validity reports of MEG are strong, yet methodological questions regarding optimal modeling techniques remain. PET investigators report good concordance of language maps with data from more invasive brain mapping techniques, but its use of radioactive tracers and poorer spatial and temporal resolution make it the least optimal of the 3 methods for language mapping. Investigations of the cortical networks supporting language function during development and into adulthood should be viewed in the context of the validity and reliability of the methods used, with careful attention to details regarding the methodologies employed in the acquisition and analysis of statistical maps.     

Reliability and Validity of Functional Neuroimaging Techniques for Identifying Language-Critical Areas in Children and Adults

Advances in neuroimaging technologies over the last 15 years have prompted their relatively widespread use in the study of brain mechanisms supporting language function in children and adults. We reviewed reliability and external validity studies of 3 of the most common functional imaging methods, functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and positron emission tomography (PET). Although reliability and validity reports for fMRI are generally quite favorable, significant variability was found across studies with respect to methodology, preventing in some cases either the assessment of the reliability of individual datasets, or cross-study comparisons. Reliability and validity reports of MEG are strong, yet methodological questions regarding optimal modeling techniques remain. PET investigators report good concordance of language maps with data from more invasive brain mapping techniques, but its use of radioactive tracers and poorer spatial and temporal resolution make it the least optimal of the 3 methods for language mapping. Investigations of the cortical networks supporting language function during development and into adulthood should be viewed in the context of the validity and reliability of the methods used, with careful attention to details regarding the methodologies employed in the acquisition and analysis of statistical maps.     

Activation and deactivation in response to visual stimulation in the occipital cortex of 6-month-old human infants

In an infant's developing cortex, the explanation for the mechanisms underlying the activations and deactivations in response to visual stimuli remains controversial. While previous near-infrared spectroscopy (NIRS) studies in awake infants have demonstrated cortical activations in response to meaningful/attractive visual stimuli, functional magnetic resonance imaging (fMRI) studies performed on sleeping infants showed negative blood oxygenation level-dependent (BOLD) responses to high-luminance unpatterned stimulations, such as a photic stimulation. To examine the effect of the characteristics of visual stimuli on cortical processing in awake infants, we measured cortical hemodynamic responses in 6-month-old infants during the presentation of a high-luminance unpatterned stimulus by using a NIRS system with 94 measurement channels. Results from 35 infants showed dissociated cortical responses between the occipital region and the other parts of the cortex, including the temporal and prefrontal regions. Although the visual stimulus produced sustained increases in oxygenated hemoglobin (oxy-Hb) signals in the temporal and prefrontal regions, it produced a transient increase in oxy-Hb signals followed by a salient decrease in oxy-Hb signals during a trial in a focal region of the occipital visual region. This suggests that the deactivation of the occipital visual region in response to visual stimulation is not a phenomenon that occurs only in the sleeping state, but that a high-luminance unpatterned stimulus can induce deactivation even in the awake infants.     

Can the cerebral metabolic rate of oxygen be estimated with near-infrared spectroscopy?

We have measured the changes in oxy-haemoglobin and deoxy-haemoglobin in the adult human brain during a brief finger tapping exercise using near-infrared spectroscopy (NIRS). The cerebral metabolic rate of oxygen (CMRO2) can be estimated from these NIRS data provided certain model assumptions. The change in CMRO2 is related to changes in the total haemoglobin concentration, deoxy-haemoglobin concentration and blood flow. As NIRS does not provide a measure of dynamic changes in blood flow during brain activation, we relied on a Windkessel model that relates dynamic blood volume and flow changes, which has been used previously for estimating CMRO2 from functional magnetic resonance imaging (fMRI) data. Because of the partial volume effect we are unable to quantify the absolute changes in the local brain haemoglobin concentrations with NIRS and thus are unable to obtain an estimate of the absolute CMRO2 change. An absolute estimate is also confounded by uncertainty in the flow-volume relationship. However, the ratio of the flow change to the CMRO2 change is relatively insensitive to these uncertainties. For the linger tapping task, we estimate a most probable flow-consumption ratio ranging from 1.5 to 3 in agreement with previous findings presented in the literature, although we cannot exclude the possibility that there is no CMRO2 change. The large range in the ratio arises from the large number of model parameters that must be estimated from the data. A more precise estimate of the flow-consumption ratio will require better estimates of the model parameters or flow information, as can be provided by combining NIRS with fMRI.     

Paradoxical correlation between signal in functional magnetic resonance imaging and deoxygenated haemoglobin content in capillaries: a new theoretical explanation

Signal increases in functional magnetic resonance imaging (fMRI) are believed to be a result of decreased paramagnetic deoxygenated haemoglobin (deoxyHb) content in the neural activation area. However, discrepancies in this canonical blood oxygenation level dependent (BOLD) theory have been pointed out in studies using optical techniques, which directly measure haemoglobin changes. To explain the discrepancies, we developed a new theory bridging magnetic resonance (MR) signal and haemoglobin changes. We focused on capillary influences, which have been neglected in most previous fMRI studies and performed a combined fMRI and near-infrared spectroscopy (NIRS) study using a language task. Paradoxically, both the MR signal and deoxyHb content increased in Broca's area. On the other hand, fMRI activation in the auditory area near large veins correlated with a mirror-image decrease in deoxyHb and increase in oxygenated haemoglobin (oxyHb), in agreement with canonical BOLD theory. All fMRI signal changes correlated consistently with changes in oxyHb, the diamagnetism of which is insensitive to MR. We concluded that the discrepancy with the canonical BOLD theory is caused by the fact that the BOLD theory ignores the effect of the capillaries. Our theory explains the paradoxical phenomena of the oxyHb and deoxyHb contributions to the MR signal and gives a new insight into the precise haemodynamics of activation by analysing fMRI and NIRS data.     

Evidence for interhemispheric processing of inputs from the hands in human S2 and PV

In the present investigation, we identified cortical areas involved in the integration of bimanual inputs in human somatosensory cortex. Using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG), we compared the responses to unilateral versus bilateral stimulation in anterior parietal cortex and areas in the Sylvian fissure of the contralateral hemisphere. The extent of fMRI activation on the upper bank of the Sylvian fissure, in the second somatosensory (S2) and the parietal ventral (PV) areas, was significantly larger for bilateral stimulation than for unilateral stimulation. Using MEG, we were able to describe the latency of response in S1 and S2/PV to unilateral and bilateral stimulation. The MEG response had three components under both stimulus conditions. An early peak in S1 at 40 ms, a middle peak in S2/PV at 80-160 ms, and three late peaks in S2/PV at 250-420 ms. There was an increase in magnetic field strength in S2/PV to bilateral stimulation at 300-400 ms post stimulus. The fMRI results indicate that, as in monkeys, S2/PV receives inputs from both the contralateral and ipsilateral hand. The MEG data suggest that information is processed serially from S1 to S2. The very late response in S2/PV indicates that extensive intrahemispheric processing occurs before information is transferred to the opposite hemisphere. The neural substrate for the increased activation and field strength at long latencies during bilateral stimulation can be accounted for in three ways. Under bilateral stimulus conditions, more neurons may be active, neuronal firing rate may increase, and/or neural activity may be more synchronous.     

Magnetoencephalography: in search of neural processes for visual motion information

Magnetoencephalography (MEG) has become a standard approach to the investigation of human brain functions. This review starts with a brief review of the human visual system and studies on visual motion detection mechanisms is followed by the presentation of MEG studies that have contributed to the field. Emphasis is placed on the fact that because the neural activities measured in functional magnetic resonance imaging (fMRI) differ substantially from those measured in MEG--fMRI data cannot be used directly to estimate MEG signal sources. The basic ideas behind the methods of signal processing and analyses generally used in MEG studies are described and theoretical considerations of the neural mechanisms determining MEG response latency and amplitude changes are discussed. Here, scalar fields theory is proposed to explain MEG responses to incoherent motions, and the ways in which detection of complex motions such as transparency, rotation and expansion can be explained by this theory are also presented. Relationships between human behavioral reaction time and MEG response latency suggest a new concept underlying the reasons why humans are late in detecting slow motion.     

Two Dimensional Inverse Imaging (2DII) of Current Sources in Magnetoencephalography

A new magnetoencephalographic (MEG) technique for imaging the cortical distribution of neuronal activity is described. An iterative algorithm is employed, which successively alters an initial estimate of cortical source structure until it corresponds to the measured magnetic field data. In this new technique, the continuum of electrical activity across the cortical surface is modeled as a dense grid of thousands of single equivalent current dipoles. MEG imaging of both compact and extended sources is facilitated by a wavelet-like transformation of the source space into a sequence of successively smaller composite source structures. Two of these composite source structures are combined during each iterative step to generate an improved estimate of the cortical source structure. Thus, inversion of the complete gain matrix corresponding to thousands of cortical sources is not performed. The technique requires only moderate PC based resources even for very large source grids. In contrast to minimum norm MEG imaging methods, this new algorithm is insensitive to random noise in the data. If available, prior knowledge of source structure from other imaging techniques, such as PET, MRI and fMRI, is easily incorporated as additional constraints on the source structure solution. Source images solutions corresponding to simulated data are presented. In addition, the technique is applied to source imaging of real MEG data incorporating cortical structure from volumetric MRI data. These results demonstrate the capability of our new technique for imaging combinations of compact and extended source structures.     

Near-infrared spectroscopy: does it function in functional activation studies of the adult brain?

Changes in optical properties of biological tissue can be examined by near-infrared spectroscopy (NIRS). The relative transparency of tissues including the skull to near-infrared light is the prerequisite to apply the method to brain research. We describe the methodology with respect to its applicability in non-invasive functional research of the adult cortex. A summary of studies establishing the 'typical' response in NIRS vascular parameters, i.e. changes in the concentration of oxygenated and deoxygenated haemoglobin, over an activated area is followed by the validation of changes in the cytochrome-oxidase redox state in response to a visual stimulus. Proceeding from these findings a rough mapping of this metabolic response over the motion-sensitive extrastriate visual area is demonstrated. NIRS measures concentration changes in deoxygenated haemoglobin [deoxy-Hb] which are assumed to be the basis of fMRI BOLD contrast (blood oxygenation level-dependent). The method is therefore an excellent tool to validate assumptions on the physiological basis underlying the fMRI signal, due to its high specificity as to the parameters measured. Questions concerning the concept of 'activation'/'deactivation' and that of the linearity of the vascular response are discussed. To challenge the method we finally present results from a complex single-trial motor paradigm study testing the hypothesis, that premotor potentials (contingent negative variation) can be examined by functional techniques relying on the vascular response. Some of the work described here has been published elsewhere.     

The Importance of Properly Compensating for Head Movements During MEG Acquisition Across Different Age Groups

Unlike EEG sensors, which are attached to the head, MEG sensors are located outside the head surface on a fixed external device. Subject head movements during acquisition thus distort the magnetic field distributions measured by the sensors. Previous studies have looked at the effect of head movements, but no study has comprehensively looked at the effect of head movements across age groups, particularly in infants. Using MEG recordings from subjects ranging in age from 3 months through adults, here we first quantify the variability in head position as a function of age group. We then combine these measured head movements with brain activity simulations to determine how head movements bias source localization from sensor magnetic fields measured during movement. We find that large amounts of head movement, especially common in infant age groups, can result in large localization errors. We then show that proper application of head movement compensation techniques can restore localization accuracy to pre-movement levels. We also find that proper noise covariance estimation (e.g., during the baseline period) is important to minimize localization bias following head movement compensation. Our findings suggest that head position measurement during acquisition and compensation during analysis is recommended for researchers working with subject populations or age groups that could have substantial head movements. This is especially important in infant MEG studies.     

基于正则化方法的加权最小模估计在脑磁源成像中的应用

脑磁图 ( m agnetoencephalography,MEG)逆问题的研究 ,根据点源和分布源两种源模型 ,可分为偶极子定位和磁源成像两大类求逆方法。采用非参数的分布源模型 ,MEG逆问题转化为一个病态的欠定方程组的求解。本文系统地阐述了结合 Tikhonov正则技术的加权最小模磁源重建方法 ,着重介绍了深度归一化算法、低分辨率脑电磁断层成像技术、局部欠定系统解法、选择性最小模方法 ,此外还从广义的加权最小模估计角度对最大熵重建方法 ,融合其它脑功能成像技术的方法以及最大后验概率估计方法加以解释和分析。不同的磁源成像方法目的都是通过引入合适的约束条件 ,从算法公式本身及神经细胞活动的特性中加以修正 ,减少逆问题的不适定程度 ,因此均可认为是使用正则方法来约束解空间 ,从而获得与测量磁场数据相拟合的并具有神经生理学和解剖学意义下的最合理的解。基于正则化技术的加权最小模估计是 MEG逆问题研究中最早开展、并已被广泛应用的磁源分布图像重建方法 ,本文给出了一个较为完整的理论发展框架     

Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI

A sudden change in the direction of motion is a particularly salient and relevant feature of visual information. Extensive research has identified cortical areas responsive to visual motion and characterized their sensitivity to different features of motion, such as directional specificity. However, relatively little is known about responses to sudden changes in direction. Electrophysiological data from animals and functional imaging data from humans suggest a number of brain areas responsive to motion, presumably working as a network. Temporal patterns of activity allow the same network to process information in different ways. The present study in humans sought to determine which motion-sensitive areas are involved in processing changes in the direction of motion and to characterize the temporal patterns of processing within this network of brain regions. To accomplish this, we used both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). The fMRI data were used as supplementary information in the localization of MEG sources. The change in the direction of visual motion was found to activate a number of areas, each displaying a different temporal behavior. The fMRI revealed motion-related activity in areas MT+ (the human homologue of monkey middle temporal area and possibly also other motion sensitive areas next to MT), a region near the posterior end of the superior temporal sulcus (pSTS), V3A, and V1/V2. The MEG data suggested additional frontal sources. An equivalent dipole model for the generators of MEG signals indicated activity in MT+, starting at 130 ms and peaking at 170 ms after the reversal of the direction of motion, and then again at approximately 260 ms. Frontal activity began 0-20 ms later than in MT+, and peaked approximately 180 ms. Both pSTS and FEF+ showed long-duration activity continuing over the latency range of 200-400 ms. MEG responses in the region of V3A and V1/V2 were relatively small, and peaked at longer latencies than the initial peak in MT+. These data revealed characteristic patterns of activity in this cortical network for processing sudden changes in the direction of visual motion.     

Transcranial magnetic stimulation--a new tool for functional imaging of the brain

Recent progress in the theory and technology of transcranial magnetic stimulation (TMS) is leading to novel approaches in brain mapping. TMS becomes a powerful functional brain mapping tool when other imaging methods are used to record TMS-evoked activity or when peripheral effects are observed as a function of stimulus location. TMS-evoked activity currently can be recorded by EEG, PET, and fMRI. In addition to providing indices of cortical excitability, these methods allow one to study brain connectivity directly, without the need for behavioral activations. When the coordinate systems in the different imaging modalities are combined, anatomical structures seen in MRI and activation sites determined by PET, fMRI, or MEG/EEG can be used for the selection of target areas in the brain. PET and fMRI can be used to map the spatial distribution of TMS-evoked activity. On the other hand, the combination of TMS and high-resolution EEG may often be the method of choice for basic neuroscience and for clinical diagnosis, for example, in the assessment of brain connectivity in patients suffering from neurodegenerative diseases or head injuries.