シンポジウム（Symposium）

Symposium Whole brain physiology by a combination of fMRI and neurophysiology in rodents シンポジウム全脳生理学: げっ歯類fMRIと神経生理学とを融合した試み

7月25日（木）16:55～17:18　第6会場（朱鷺メッセ　2F　201A） 1S06e-1 視床を抑制する視床網様核の新規振動活動が安静時全脳活動へ及ぼす作用の探索 Norio Takata（高田則雄）慶應大医精神・神経科学 The brain exhibits low frequency activity that is correlated across brain regions during rest that is called "resting state networks" (RSNs). Ten to twenty RSNs have been identified in the human brain, and several ones in the rodents'. Relevance of RSNs to physiological and pathological conditions of the brain is widely acknowledged. However, physiological mechanism of RSNs that manifest distributed, large-scale networks is not elucidated completely. Thalamic reticular nucleus (TRN) is a thin layered nucleus that covers latero-dorsal part of the thalamus. As with the thalamus that is regarded as a sensory 'gate', TRN is proposed as a 'gate keeper' to regulate information transfer from the thalamus to the cortex and among cortices based on its anatomical characteristics; 1) TRN neurons receive glutamatergic input from thalamocortical and corticothalamic fibers that pass through TRN, and 2) TRN sends GABAergic projections mostly on thalamocortical neurons. Despite the hypothetical importance of TRN as a regulator of information flow in the brain, investigation of TRN activity has been difficult due to its thin morphology. Indeed, TRN activity cannot be measured with functional magnetic resonance imaging (fMRI) due to lack of resolution. To investigate a relationship between TRN activity and whole brain RSNs dynamics, we first developed a retiometric optical fiber photometry (FP) system (Natsubori et al. 2017 J Neurosci; Tsutsui-Kimura et al. 2017 Current Biology) and transgenic (Tg) mice expressing the calcium (Ca²⁺) indicator yellow cameleon-Nano 50 in a cell that expresses a Ca²⁺ binding protein, parvalbumin (PV). Our FP system using the Tg mice enabled reliable detection of compound Ca²⁺ activity of TRN, because 1) the effective detection range of our FP system using an optical fiber (Φ 400 μm) was estimated to be ~700 um, and 2) TRN neurons express high levels of PV, while thalamic nuclei of rodents scarcely expresses PV. We then combined this FP system and fMRI in awake mice (Yoshida et al. 2016 J Neurosci Methods) to monitor TRN activity and RSNs simultaneously. We found a novel, spontaneous oscillation of population-level Ca²⁺ signals of TRN. The oscillation was ultra-slow at a frequency of 0.01-0.2 Hz that corresponds to the frequency range of RSNs. In the symposium, a relationship between RSNs and TRN activity will be discussed.		7月25日（木）17:18～17:41　第6会場（朱鷺メッセ　2F　201A） 1S06e-2 ラットfMRIに神経生理学的手法を融合した試み Akira Sumiyoshi（住吉晃）^1,2,3 ¹量研機構放医研 ²NIDA-IRP, NIH ³東北大加齢研 Characterizing the nature and underlying neurobiological causes of psychiatric and neurological diseases at the circuitry and network levels has remained elusive and necessitates the use of robust animal models. Noninvasive functional magnetic resonance imaging (fMRI) allows systems-level insight into disease phenotype in humans and animals, and fMRI represents an ideal platform for translational and reverse-translational research, with common measurements collected across species. Animal neuroimaging study allows tight environmental and genetic control, circumventing the inherent heterogeneity of human populations. Furthermore, animal studies rely on quantitative measures of physiological processes and behavior, as compared to heavily subjective measures in human populations. In the talk, I would like to summarize my most recent work in rats and will cover several research topics including; 1) development of simultaneous EEG and fMRI recording; 2) construction of in vivo MRI template and cortical parcellation atlas; 3) electrophysiological signature of resting-state fMRI signal; 4) chemogenetic approach to understand the basis of neurovascular coupling; and 5) structural and functional connectome analysis of brain development. Using animal fMRI in combination with in vivo neurophysiological techniques is essential for understanding of brain function in health and disease and offers an exemplary bridge between human and animal research studies. References 1. Sumiyoshi et al., Biol Psychiatry: CNN, in press. 2. Sumiyoshi et al., NeuroImage, 98, 82-90, 2014. 3. Sumiyoshi et al., JCBFM, 32, 1853-8, 2012. 4. Sumiyoshi et al., NeuroImage, 60, 738-746. 2012. 5. Sumiyoshi et al., NeuroImage, 54, 1951-1965, 2011.

7月25日（木）17:41～18:04　第6会場（朱鷺メッセ　2F　201A） 1S06e-3 Visualizing whole-brain activity in the mouse with functional Magnetic Resonance Imaging Joanes Grandjean（Grandjean Joanes） Singapore Bioimaging Consoritum A comprehensive understanding of the architecture and function of the healthy and diseased brain, often referred to as the "connectome", is arguably one of the biggest challenges in neuroscience. Whole-brain analysis of structure and function using neuroimaging tools provides valuable insight into information processing at the macroscopic level. Functional imaging has been extensively used to map the healthy and diseased human brain, to localize brain activity evoked by specific cognitive tasks or estimate large-scale brain networks during rest. Advances in high field magnets and radio-frequency coils now enable researchers to extend these studies to animal models, where brain circuits can be further dissected using precise circuit manipulation tools such as optogenetics. In this talk, I will detail the development and considerations for functional connectivity analysis in mice and its application in the field of affective disorder. Finally, I will expend on the application of optogenetic together with functional magnetic resonance imaging (ofMRI) to manipulate and visualize circuits in the living mouse. The relevance of ofMRI is accentuated as it remains to-date the only available method to visualize functional activity evoked with optogentics across the whole-brain non-invasively. These studies offer a strong translational perspective to investigate the molecular mechanisms behind MRI-based fingerprints of human brain disorders, or to partake in the drug development process.		7月25日（木）18:04～18:27　第6会場（朱鷺メッセ　2F　201A） 1S06e-4 安静時機能的結合に基づく精神疾患の神経基盤探索 Noriaki Yahata（八幡憲明）量子科学技術研究開発機構放射線医学総合研究所 There has been growing interest in the use of resting-state functional connectivity (rs-FC) magnetic resonance imaging (MRI) to delineate the neural substrates of psychiatric disorders. In particular, machine-learning techniques have enabled data-driven identification of disorder-specific patterns of FC, the use of which has led to automatic case-control classification of individuals. In this symposium, I will present the recent progress in the field, including our development of an autism spectrum disorder (ASD) classifier and its application to explore quantitative relationships among multiple psychiatric disorders. By effectively resolving the technical issues that critically hampered the generalization of a classifier for an independent cohort, we identified 16 abnormal FCs in ASD (0.2% of all FCs considered) from a multi-site dataset from Japan. The resultant classifier attained high accuracy for a Japanese discovery cohort [85%, area under the curve (AUC) = 0.93]. Furthermore, it demonstrated a remarkable degree of site generalization for two independent validation cohorts in the US ABIDE Project (75%, AUC = 0.76) and in Japan (70%, AUC = 0.77). The same set of FCs in the classifier accurately predicted the communication domain score on the standard diagnostic instrument. Thus, we have established a reliable rs-FC-based biomarker for ASD that revealed a direct link between the underlying neural mechanisms and the behavioral characteristics of ASD. We examined the specificity of the ASD classifier by investigating its generalizability to other psychiatric disorders. We found that our classifier did not distinguish individuals with major depressive disorder or attention-deficit hyperactivity disorder from controls; but it exhibited a moderate ability to distinguish patients with schizophrenia from controls. Our findings support that exploration of neuroimaging-based dimensions to quantify the multiple-disorder spectrum may contribute to more biologically oriented diagnostic systems in clinical psychiatry. Moreover, such a data-driven investigation using rs-FC may facilitate translation of findings between human and animals, thereby accelerating preclinical studies to elucidate neural mechanisms of disorders and to develop novel therapeutic targets.

7月25日（木）18:27～18:50　第6会場（朱鷺メッセ　2F　201A） 1S06e-5 Circuits of depression in rodent functional connectivity MRI Alexander Sartorius（Sartorius Alexander）¹，Wolfgang Weber-Fahr（Weber-Fahr Wolfgang）²，Natalia Gass（Gass Natalia）²，Christian Clemm von Hohenberg（Clemm von Hohenberg Christian）² ¹Central Institute of Mental Health, Uni Heidelberg ²Workgroup Translational Imaging, Dept. Neuroimaging, Central Institute of Mental Health, Mannheim, University of Heidelberg Depression is a highly prevalent illness with an enormous individual and societal burden. Treatment-resistant depression (TRD) remains a pressing clinical problem. Optimizing treatment requires better definition of the specificity of the involved brain circuits. The utilization of magnetic resonance imaging (MRI) methods in rodent models of psychiatric disorders provides considerable benefits for the identification of disease-associated brain circuits. Species-conserved (intermediate) phenotypes that can be quantified and compared across species offer important advantages for translational research and drug discovery. Here, we investigate the utility of network science methods to assess the pharmacological (e.g. ketamine) alterations of the large-scale architecture of brain networks in rats and humans. Additionally, hyperconnectivity of the default-mode network (DMN) is one of the most widely replicated neuroimaging findings in major depressive disorder (MDD). Further, there is growing evidence for a central role of the lateral habenula (LHb) in the pathophysiology of MDD. We combined optogenetics and functional magnetic resonance imaging (fMRI), to establish a relationship between LHb and DMN hyperconnectivity, using an animal model of treatment-resistant depression.