Masaya Misaki

Human brain activity time-locked to rapid eye movements during REM sleep.

To identify the neural substrate of rapid eye movements (REMs) during REM sleep in humans, we conducted simultaneous functional magnetic resonance imaging (fMRI) and polysomnographic recording during REM sleep. Event-related fMRI analysis time-locked to the occurrence of REMs revealed that the pontine tegmentum, ventroposterior thalamus, primary visual cortex, putamen and limbic areas (the anterior cingulate, parahippocampal gyrus and amygdala) were activated in association with REMs. A control experiment during which subjects made self-paced saccades in total darkness showed no activation in the visual cortex. The REM-related activation of the primary visual cortex without visual input from the retina provides neural evidence for the existence of human ponto-geniculo-occipital waves (PGO waves) and a link between REMs and dreaming. Furthermore, the time-course analysis of blood oxygenation level-dependent responses indicated that the activation of the pontine tegmentum, ventroposterior thalamus and primary visual cortex started before the occurrence of REMs. On the other hand, the activation of the putamen and limbic areas accompanied REMs. The activation of the parahippocampal gyrus and amygdala simultaneously with REMs suggests that REMs and/or their generating mechanism are not merely an epiphenomenon of PGO waves, but may be linked to the triggering activation of these areas.

Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback

Neurofeedback is a promising approach for non-invasive modulation of human brain activity with applications for treatment of mental disorders and enhancement of brain performance. Neurofeedback techniques are commonly based on either electroencephalography (EEG) or real-time functional magnetic resonance imaging (rtfMRI). Advances in simultaneous EEG-fMRI have made it possible to combine the two approaches. Here we report the first implementation of simultaneous multimodal rtfMRI and EEG neurofeedback (rtfMRI-EEG-nf). It is based on a novel system for real-time integration of simultaneous rtfMRI and EEG data streams. We applied the rtfMRI-EEG-nf to training of emotional self-regulation in healthy subjects performing a positive emotion induction task based on retrieval of happy autobiographical memories. The participants were able to simultaneously regulate their BOLD fMRI activation in the left amygdala and frontal EEG power asymmetry in the high-beta band using the rtfMRI-EEG-nf. Our proof-of-concept results demonstrate the feasibility of simultaneous self-regulation of both hemodynamic (rtfMRI) and electrophysiological (EEG) activities of the human brain. They suggest potential applications of rtfMRI-EEG-nf in the development of novel cognitive neuroscience research paradigms and enhanced cognitive therapeutic approaches for major neuropsychiatric disorders, particularly depression.

Resting-State Functional Connectivity Modulation and Sustained Changes After Real-Time Functional Magnetic Resonance Imaging Neurofeedback Training in Depression

Amygdala hemodynamic responses to positive stimuli are attenuated in major depressive disorder (MDD) and normalize with remission. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) training with the goal of upregulating amygdala activity during recall of happy autobiographical memories (AMs) has been suggested, and recently explored, as a novel therapeutic approach that resulted in improvement in self-reported mood in depressed subjects. In this study, we assessed the possibility of sustained brain changes as well as the neuromodulatory effects of rtfMRI-nf training of the amygdala during recall of positive AMs in MDD and matched healthy subjects. MDD and healthy subjects went through one visit of rtfMRI-nf training. Subjects were assigned to receive active neurofeedback from the left amygdale (LA) or from a control region putatively not modulated by AM recall or emotion regulation, that is, the left horizontal segment of the intraparietal sulcus. To assess lasting effects of neurofeedback in MDD, the resting-state functional connectivity before and after rtfMRI-nf in 27 depressed subjects, as well as in 27 matched healthy subjects before rtfMRI-nf was measured. Results show that abnormal hypo-connectivity with LA in MDD is reversed after rtfMRI-nf training by recalling positive AMs. Although such neuromodulatory changes are observed in both MDD groups receiving feedback from respective active and control brain regions, only in the active group are larger decreases of depression severity associated with larger increases of amygdala connectivity and a significant, positive correlation is found between the connectivity changes and the days after neurofeedback. In addition, active neurofeedback training of the amygdala enhances connectivity with temporal cortical regions, including the hippocampus. These results demonstrate lasting brain changes induced by amygdala rtfMRI-nf training and suggest the importance of reinforcement learning in rehabilitating emotion regulation in depression.

Characteristic cortical thickness patterns in adolescents with autism spectrum disorders: interactions with age and intellectual ability revealed by canonical correlation analysis.

To investigate patterns and correlates of cortical thickness in adolescent males with autism spectrum disorders (ASD) versus matched typically developing controls, we applied kernel canonical correlation analysis to whole brain cortical thickness with the explaining variables of diagnosis, age, full-scale IQ, and their interactions. The analysis found that canonical variates (patterns of cortical thickness) correlated with each of these variables. The diagnosis- and age-by-diagnosis-related canonical variates showed thinner cortex for participants with ASD, which is consistent with previous studies using a univariate analysis. In addition, the multivariate statistics found larger affected regions with higher sensitivity than those found using univariate analysis. An IQ-related effect was also found with the multivariate analysis. The effects of IQ and age-by-IQ interaction on cortical thickness differed between the diagnostic groups. For typically developing adolescents, IQ was positively correlated with cortical thickness in orbitofrontal, postcentral and superior temporal regions, and greater thinning with age was seen in dorsal frontal areas in the superior IQ (>120) group. These associations between IQ and cortical thickness were not seen in the ASD group. Differing relationships between IQ and cortical thickness implies independent associations between measures of intelligence and brain structure in ASD versus typically developing controls. We discuss these findings vis-à-vis prior results obtained utilizing univariate methods.

Neural mechanisms of spatial stimulus-response compatibility: the effect of crossed-hand position.

Previous psychological experiments have indicated the existence of a visual–proprioceptive interaction in spatial stimulus–response compatibility (SSRC) tasks, but there is little specific information on the neural basis of such interaction in humans. Using functional magnetic resonance imaging (fMRI), we compared the neural activity associated with two different aspects of spatial coding: the coding of the “internal” spatial position of motor-response effectors (i.e., the position of body parts) as obtained through proprioception, and the coding of “external” positions, i.e., the positions of visual stimuli. A 2×2 factorial design was used to investigate the spatial compatibility (incompatible versus compatible) between a visual stimulus and hand position (crossed versus uncrossed). The subjects were instructed to respond to stimuli presented to the right or left visual field with either the ipsilateral (compatible condition) or the contralateral hand (incompatible condition). The incompatible condition produced stronger activation in the bilateral superior parietal lobule, inferior parietal lobule, and bilateral superior frontal gyrus than the compatible condition. The crossed-hand condition produced stronger activation in the bilateral precentral gyrus, superior frontal gyrus, superior parietal lobule, and superior temporal gyrus than the uncrossed-hand condition. These results suggest that activity in the frontal–parietal regions is related to two functions: (1) representation of the visual stimulus–motor response spatial configuration in an SSRC task, and (2) integration between external visual and internal proprioceptive sensory information. The activation in the superior temporal gyrus was not affected by the visual stimulus–motor response spatial configuration in an SSRC task; rather, it was affected by the crossed-hand posture. Thus, it seems to be related to representing internal proprioceptive sensory information necessary to carry out motor actions.

Network-dependent modulation of brain activity during sleep

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks.

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subjects motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average correction efficiency over the 305 fMRI scans is 18% and the largest achieved efficiency is 71%. The utility of aE-REMCOR on the resting state fMRI connectivity of the default mode network is also examined. The motion-induced position-dependent error in the DMN connectivity analysis is shown to be reduced when aE-REMCOR is utilized. These results demonstrate that aE-REMCOR can be conveniently and efficiently used to improve fMRI motion correction in large clinical EEG-fMRI studies.

Mirror symmetrical transfer of perceptual learning by prism adaptation.

Recent study of [Sugita, Y. (1996) Global plasticity in adult visual cortex following reversal of visual input. Nature, 380, 523-526.] demonstrated that prism adaptation to reversed retinal input generates the transfer of neuronal activities in monkey V1 to the opposite visual cortex. This raises the question if perceptual learning on one side of the visual field can transfer to the other side. We tested this in using the Gabor lateral masking paradigm. Before adaptation, long-range interaction was induced vertically on one side (i.e., the right) of the visual field with training (perceptual learning). Prism adaptation was achieved by wearing right-left reversing goggles. During adaptation period, perceptual learning transferred to a mirror symmetrical region across the vertical meridian. Results in the post adaptation period revealed that both learning and transfer persisted for over three months. These results provide direct evidence of transferred perceptual plasticity across the visual field, the underlying mechanism of which is supported by the mirror symmetrical connection between the right and left cortices.

Application of artificial neural network to fMRI regression analysis

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Dissociation in accessing space and number representations in pathologic pain patients

Space is represented by integrating egocentric and allocentric reference frames; however, little is known about the role of these independent reference frames in number representation. Using patients with unilateral pathologic pain in one limb, we investigated whether number representation is closely linked to space representation by evaluating visual subjective body-midline judgments in dark and light conditions (egocentric and allocentric space, respectively). To evaluate the number representation, pairs of numbers were read aloud to the participant, who was then asked to state the midpoint number that they intuitively perceived to be at the middle of each interval. All of the patients perceived allocentric space accurately in the light condition. However, each of the patients showed perceptual shifts in egocentric space and number representation in the dark as compared with control subjects. Direct comparison showed a consistent relationship between number representation and egocentric space. We suggest that numbers are represented spatially by integrating these independent reference frames.