Yoshio Imai

A pairwise maximum entropy model accurately describes resting-state human brain networks

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks.

Functional Dissociation between Anterior and Posterior Temporal Cortical Regions during Retrieval of Remote Memory

Retrieval of remote memory is considered to differentially involve the anterior and posterior temporal neocortices. Previous neuropsychological studies suggest that the different posterior temporal cortical regions are involved in the retrieval of remote memory of different categories of stimuli, whereas the anterior region is involved more generally in remote memory retrieval. In the present study, using functional magnetic resonance imaging of human brains, we tested this dissociation by examining the more precise characteristics of the anterior and posterior temporal cortical regions. Two categories of stimuli, faces and scenes, were used for paired stimuli to be retrieved, and the brain activity during retrieval of paired stimuli that were learned immediately before the scanning was compared with that during retrieval of paired stimuli that were learned ∼8 weeks earlier. We found that the different posterior temporal cortical regions were activated during retrieval of different categories of remote memory in a category-specific manner, whereas the anterior temporal cortical region was activated during retrieval of remote memory in a category-general manner. Furthermore, by applying a multivariate pattern analysis to psychophysiological interactions during retrieval of remote memory relative to recent memory, we revealed the significant interaction from the category-specific posterior temporal cortical regions to the category-general anterior temporal region. These results suggest that the posterior temporal cortical regions are involved in representation and retrieval of category-specific remote memory, whereas the anterior cortical temporal region is involved in category-general retrieval process of remote memory.

Energy landscapes of resting-state brain networks

During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs) including the default-mode network (DMN) and frontoparietal network (FPN). Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics), the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant local minima were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.

Prediction of subsequent recognition performance using brain activity in the medial temporal lobe.

Application of multivoxel pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data enables reconstruction and classification of cognitive status from brain activity. However, previous studies using MVPA have extracted information about cognitive status that is experienced simultaneously with fMRI scanning, but not one that will be observed after the scanning. In this study, by focusing on activity in the medial temporal lobe (MTL), we demonstrate that MVPA on fMRI data is capable of predicting subsequent recognition performance. In this experiment, six runs of fMRI signals were acquired during encoding of phonogram stimuli. In the analysis, using data acquired in runs 1-3, we first conducted MVPA-based voxel-wise search for the clusters in the MTL whose signals contained the most information about subsequent recognition performance. Next, using the fMRI signals acquired in runs 1-3 from the selected clusters, we trained a classifier function in MVPA. Finally, the trained classifier function was applied to fMRI signals acquired in runs 4-6. Consequently, we succeeded in predicting the subsequent recognition performance for stimuli studied in runs 4-6 with significant accuracy. This accurate prediction suggests that MVPA can extract information that is associated not only with concurrent cognitive status, but also with behavior in the near future.

Functional Relevance of Micromodules in the Human Association Cortex Delineated with High-Resolution fMRI

Recent advancement of resting-state functional connectivity magnetic resonance imaging (MRI) has provided a method for drawing boundaries of brain areas. However, it remains to be elucidated how the parcellated areas in the association cortex relate to the spatial extent of the brain activation which ought to reflect a functional unit in the neural network supporting that particular function. To address this issue, in the present study, we first mapped boundaries and 2 adjacent activations in the human inferior frontal cortex, and then examined the spatial relationship between the boundaries and the 2 activations. The boundaries mapped with high-resolution functional magnetic resonance imaging revealed a collection of micromodules, the size of which was approximately only 12 mm on average, much smaller than the Brodmann areas. Each of the 2 activations associated with 2 functions, response inhibition and feedback processing, was smaller in size than the micromodules. By comparing the spatial patterns between the boundaries and the 2 activations, it was revealed that the brain activations were less likely to be located on the boundaries. These results suggest the functional relevance of the areas in the association cortex delineated by the boundary mapping method based on resting-state functional connectivity MRI.

Lateral–Medial Dissociation in Orbitofrontal Cortex–Hypothalamus Connectivity

The orbitofrontal cortex (OFC) is involved in cognitive functions, and is also closely related to autonomic functions. The OFC is densely connected with the hypothalamus, a heterogeneous structure controlling autonomic functions that can be divided into two major parts: the lateral and the medial. Resting-state functional connectivity has allowed us to parcellate the cerebral cortex into putative functional areas based on the changes in the spatial pattern of connectivity in the cerebral cortex when a seed point is moved from one voxel to another. In the present high spatial-resolution fMRI study, we investigate the connectivity-based organization of the OFC with reference to the hypothalamus. The OFC was parcellated using resting-state functional connectivity in an individual subject approach, and then the functional connectivity was examined between the parcellated areas in the OFC and the lateral/medial hypothalamus. We found a functional double dissociation in the OFC: the lateral OFC (the lateral orbital gyrus) was more likely connected with the lateral hypothalamus, whereas the medial OFC (the medial orbital and rectal gyri) was more likely connected with the medial hypothalamus. These results demonstrate the fundamental heterogeneity of the OFC, and suggest a potential neural basis of the OFC–hypothalamic functional interaction.

Relatedness-dependent rapid development of brain activity in anterior temporal cortex during pair-association retrieval

Functional MRI studies have revealed that the brain activity in the anterior temporal cortex during memory retrieval increases over months after memory encoding. Behavioral evidence has demonstrated that long-term memory can sometimes be consolidated more rapidly in one or two days. In the present functional MRI study, we manipulated the relatedness between paired faces to be retrieved in a pair-association task. The brain activity in the anterior temporal cortex during retrieval of paired associates increased rapidly in one day, as shown in previous studies. We found that the speed of the brain activity development was dependent on the level of semantic relatedness of paired faces. The results suggest that the semantic relatedness enhances the speed of formation of memory representation in the anterior temporal cortex.

平成22 年度診断用X 線装置アンケート調査報告（撮影条件を中心として）

This is the eighth investigation which has been carried out every 5 years since 1974 for the purpose of grasping the trend of X-ray devices and the radiographic condition. We gathered it up mainly on a radiographic condition, in this report. As for the chest radiography and double contrast gastrography, introduction of the flat panel detector (FPD) advanced in comparison with the last survey. Ratio of the imaging system at chest radiography was 65% for computed radiography (CR), 33% for FPD, 1% for screen/film (S/F), and 1% for others. The radiographic condition of FPD was current time product less than CR. Ratio of the imaging system at gastrography was 3% for CR, 48% for FPD, 34% for image intensifier-digital radiography (I.I.-DR), and 15% for S/F. The tube voltage and the exposure time were similar to the last survey time, but the tube current became lower. Through this survey, the change of the radiographic condition was seen in the radiography part where introduction of the FPD advanced. We think the continuous survey is necessary in future.

[Report based on Fiscal 2000 Diagnostic X-ray Equipment Questionnaire Survey (conditions of X-ray units and similar equipment)].

On X-ray diagnostic technology, it is important to grasp a change of the X-ray high-voltage equipment and radiographic technique factors. The 1st questionnaire was performed in 1974, and it carried out after that every five years, and conducted 8th investigation. As a result, we requested 656 institutions and got a reply from 103 institutions. The response rate was 15.7%. For X-ray high-voltage equipment, the inverter-type device shifts to 83.6% from 73.4% of last time. X-ray high-voltage equipment will be shifted to inverter-type device the near future. For X-ray tube device, the target angle becomes more smaller than usual, and maximum anode heat content is increasing tendency. The spread of digital devices is being advanced, and especially the flat panel detector (FPD) increases in the devices. The spread of soft copy diagnoses is 73.8% for chest image diagnoses, and 49.5% for breast image diagnosis. For the device management, the ratio of institutions measured at purchase time was 91.2%. But, the ratio of institutions performed an invariability examination was 58.4%. It is required to grasp the performance of an X-ray equipment and peripheral equipment, and to perform accuracy control in order to obtain proper radiographic technique factors and imaging. In order to use it for the improvement in photography technology, we would like to continue to conduct this investigation periodically.