We use transcranial magnetic stimulation (TMS) as a tool for investigating the function of the brain in animal experiments. Application of TMS facilitates or inhibits the local neural activity, which in turn leads to the change of the network dynamics of the whole brain and the change of emotional or attentional state. By measuring the brain activity during this operation by various methods such as electrocorticogram (ECoG) or PET/fMRI, we aim to understand the operating principles of the brain network controlling emotion and attention. Furthermore, we try to understand various emotional/attentional disorders within this framework: there must be a shift in the network dynamics when the malfunction of emotion or attention is taking place.

 
Recent Publications
1. Tsutsui KI, Grabenhorst F, Kobayashi S, Schultz W (2016) A dynamic code for object valuation in prefrontal cortex neurons. Nature Communications, in print
2. Tsutsui KI, Hosokawa T, Yamada M, Iijima T (2016) Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection. Journal of Neuroscience 36: 3038-3048.
3. Oyama K, Tateyama Y, Hernádi I, Tobler PN, Iijima T, Tsutsui KI (2015) Discrete coding of stimulus value, reward expectation, and reward prediction error in the dorsal striatum. Journal of Neurophysiology 114, 2600-2615.

The emergence and development of complex skills are greatly influenced by social experiences after birth. One of the prominent examples is our ability of vocal communication, or human language. However, neural basis of learned vocal communication is largely unknown, because there is no suitable mammalian animal model that can learn vocalization or display imitative learning in laboratory spaces. In avian species, songbirds can provide an attractive animal model to address the brain mechanisms underlying socially learned vocalization. These avian species, much like humans, learn to imitate complex vocal signals during the postnatal development and maintain their learned vocal behaviors through the whole life. In this research project, we study circuit mechanisms involved in the switch from acquisition to consolidation of vocal skills by using in vivo electrophysiological and imaging techniques.
Because both learning and maintenance of complex vocalization in songbirds require a dedicated vocal control circuit homologous to cortico-basal ganglia circuits in mammals, circuit shift mechanisms from acquisition to consolidation of complex learned skills may be shared with these two animal classes. We therefore apply our in vivo electrophysiological and imaging techniques to the analyses of operantly learned behaviors in mice. The comparison may be helpful for our understanding not only for the conserved circuit mechanisms between two species, but also for the similarities and differences in circuit mechanisms between operant and imitative learning processes.

 
Recent Publications
1. Abe, K., Matsui, S., and Watanabe, D. (2015) Transgenic songbirds with suppressed or enhanced activity of CREB transcription factor. Proc Natl Acad Sci U S A. 112: 7599-7604.
2. Hasegawa, T., Fujimoto, H., Tashiro, K., Nonomura, M., Tsuchiya, A., and Watanabe, D. (2015) A wireless neural recording system with a precision motorized microdrive for freely behaving animals. Sci. Rep. 5: 7853.
3. Fujimoto, H., Hasegawa, T., and Watanabe, D. (2011) Neural coding of syntactic structure in learned vocalizations in the songbird. J Neurosci. 31: 10023–10033.

The overall goal of our team is to contribute to understanding pathological processes in the nervous system caused by changes in functional structures and to improve diagnostic and treatment strategies by using Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI). To accomplish our goal, we aim to develop three methods: (1) dynamic imaging for complex biological and cellular functions in the living state, (2) clarification of the spatio-temporal processes of functional expression for activation of unique neural network structures, and (3) dynamic imaging analysis for the development and correlation of high function structural networks among the organs and cells that maintain homeostasis in the living bodies of macaques and genetically modified model mice.

We have already started research in the following three areas: (1) dynamic changes in neural circuits with functional recovery following spinal cord injury in monkeys, (2) dynamic changes of nerve fiber connections associated with neurodegeneration by diffusion-weighted imaging processing using MRI coils for macaque monkeys, and (3) mouse brain imaging at 60 μm isotropic resolution, utilizing a high resolution 7-Tesla MRI scanner and ultra-high sensitivity MRI coil system.

This project aims to establish methodologies that spatio-temporally evaluate changes to functional brain networks in mammalian models in which a neural circuit has been selectively intercepted by gene-recombination technology or focal injection of viral vectors, and in nerve damage models in monkeys, including spiral cord injury and surgically-induced cerebral infarction, combining MRI, PET, and other imaging technologies. In the near future we expect that these noninvasive imaging methods will be applied to humans with brain and spinal cord injuries and neuropsychiatric disorders.

 
Recent Publications
1. Sawada M, Kato K, Kunieda T, Mikuni N, Miyamoto S, Onoe H, Isa T, Nishimura Y. Function of the nucleus accumbens in motor control during recovery after spinal cord injury. Science. 2015 Oct 2;350(6256):98-101. doi:10.1126/science.aab3825. Epub 2015 Oct 1.
2. Hayashi T, Shimazawa M, Watabe H, Ose T, Inokuchi Y, Ito Y, Yamanaka H, Urayama S, Watanabe Y, Hara H, Onoe H. Kinetics of neurodegeneration based on a risk-related biomarker in animal model of glaucoma. Mol Neurodegener. 2013 Jan 18;8:4. doi: 10.1186/1750-1326-8-4.
3. Takata N, Yoshida K, Komaki Y, Xu M, Sakai Y, Hikishima K, Mimura M, Okano H, Tanaka KF. Optogenetic activation of CA1 pyramidal neurons at the dorsal and ventral hippocampus evokes distinct brain-wide responses revealed by mouse fMRI. PLoS One. 2015 Mar 20;10(3):e0121417. doi:10.1371/journal.pone.0121417.eCollection 2015.

Musculoskeletal system model is the basis of the body movement, and is intended to connect the behavior and neural activity. In order to understand the the functional shift of brain neural circuit for behavioral adaptation, this model plays crucial role for analyzing the behavioral and neural activities through the dynamics of the body. In this study, a mathematical model analysis technique is applied to learning process, including the recovery from the damage of neural circuit.

The brain allows for skillful manipulation of the body to interact with the external environment. This sophisticated and flexible operation involves transformations between coordinate frames of the internal body and external environment, possibly computed in distributed brain regions. The intrinsic coordinate frame is body- and/or muscle-centered, whereas the extrinsic coordinate frame refers to points outside the body. However, it is still unclear how these two coordinate frames are represented in the brain. Extensive studies using monkeys have shown that the primary motor cortex and the premotor cortex are important in coding coordinate frames. The supplementary motor area is also included in the medial portion of premotor cortex. To our knowledge, no previous studies have examined the neural representation of distinct coordinate frames in SMA. We have been developing a novel approach for analyzing the representation of the motor control and planning using EEG and fMRI. Non-inva
sive method can be applied to human behavioral analysis.

 
Recent Publications
1. Natsue Yoshimura, Koji Jimura, DaSalla Charles S., Duk Shin, Hiroyuki Kambara, Takashi Hanakawa, Yasuharu Koike. Dissociable neural representations of wrist motor coordinate frames in human motor cortices, NeuroImage, Vol. 97, pp. 53-61, Apr. 2014.
2. Hiroyuki Kambara, Duk Shin, Yasuharu Koike. A computational model for optimal muscle activity considering muscle viscoelasticity in wrist movements, Journal of Neurophysiology, Vol. 109, No. 8, pp. 2145-2160, Apr. 2013.
3. Natsue Yoshimura, Charles S. DaSalla, Takashi Hanakawa, Masa-aki Sato, Yasuharu Koike. Reconstruction of flexor and extensor muscle activities from electroencephalography cortical currents, Neuroimage, Elsevier, Vol. 59, No. 2, pp. 1324-1337, Jan. 2012.

Animals often acquire an appropriate behavior for their optimal goal by operant learning, and the behavior will be adapted and changed as a habit eventually after its heavy repetition. Although this process has been believed to be accomplished by a functional shift in parallel cortex-basal ganglia loops, little is known about the circuit mechanism itself in detail. So far, we have established a useful behavioral task system in which rats operantly learn a lever manipulation with their forelimb in a head-fixed condition, and have tried to characterize functional activities of neurons in the cerebral cortex (motor cortex, hippocampus) and basal ganglia (striatum) in the behaving rats, by using electrophysiological measurements such as multi-neuronal and juxtacellular recordings.

In our present study, we are aiming to understand the dynamics of functional circuit shift among the limbic cortex-basal ganglia loop (emotion, motivation), the prefrontal cortex-basal ganglia loop (learning of goal-directed behaviors), and the motor cortex-basal ganglia loop (motor control, habituation). To address this issue, we combine our original behavioral experiments with the electrophysiological measurements and optogenetics, analyze functional changes in neuronal activity in these loops during the operant learning, and verify its mechanism by theoretical models, to elucidate the dynamics of functional circuit shift for a progress of operant learning.

 
Recent Publications
1. Saiki, A. et al. (2014) Different modulation of common motor information in rat primary and secondary motor cortices. PLoS ONE 9: e98662.
2. Isomura, Y. et al. (2013) Reward-modulated motor information in identified striatum neurons. J. Neurosci. 33: 10209-10220.
3. Kimura, R. et al. (2012) Reinforcing operandum: rapid and reliable learning of skilled forelimb movements by head-fixed rodents. J. Neurophysiol. 108: 1781-1792.

When the animals face the environmental challenge as stress, they are supposed to cope with stress by decision making in behavior. In such conditions with stress, we observe the mouse exhibits alternation of two coping behaviors, i.e., struggling and immobility. Despite the significance of these adaptive choices of behaviors in survival, neural mechanism underlying it remains unclear.

We previously found that mice with suppressed activity in the dopaminergic and serotonergic neurons in the brain stem more frequently showed the passive coping under tail suspension and the social avoidance behaviors than control group. These results led us to the hypothesis that monoamines and its regulation play pivotal roles in behavioral choice to cope with stress.

To address this, we will examine role of the neural pathways regulating monoamine metabolisms in stress-coping behaviors by genetic manipulation of activity in these pathways. We also study temporal changes of neural circuit activities of these pathways along stress-coping to see how the brain adapts to the environmental challenge using electrophysiology and electrochemistry.

 
Recent Publications
1. Cui W, Mizukami H, Yanagisawa M, Aida T, Nomura M, Isomura Y, Takayanagi R, Ozawa K, Tanaka K, Aizawa H. Glial dysfunction in the mouse habenula causes depressive-like behaviors and sleep disturbance. J Neurosci 34:16273–16285. 2014
2. Aizawa, H., Yanagihara, S., Kobayashi, M., Niisato, K., Takekawa, T., Harukuni, R., McHugh, TJ., Fukai, F., Isomura, Y., Okamoto, H. The synchronous activity of lateral habenular neurons is essential for regulating hippocampal theta oscillation. J Neurosci 33:8909-8921. 2013
3. Aizawa H, Kobayashi M, Tanaka S, Fukai T, Okamoto H. Molecular characterization of the subnuclei in rat habenula. J Comp Neurol. 520:4051-4066. 2012

Operation of the large-scaled network of the brain is dynamically and flexibly regulated depending on its inner status and environmental impact. Recovery after the brain and/or spinal cord injury is its typical example and understanding the functional recovery at large-scaled network would be help designing the effective neurorehabilitation therapies. We have been working on the neural mechanism of functional recovery of dexterous finger movements after the partial spinal cord injury in macaque monkeys. Combination of multi-disciplinary approaches such as neuroimaging with PET, electrophysiology, pharmacological reversible inactivation, pathway-selective manipulation by using viral vectors and behavioral analysis, revealed that the dynamical changes occur not only in the spinal cord, but also in the large-scaled networks spanning the cerebral motor-related areas and even in the limbic systems such as the nucleus accumbens. Another animal model of functional recovery is the “blindsight”, in which visually guided goal directed movements with eye and forearm recovers after the injury to the primary visual cortex (V1). In the current project of “Adaptive Circuit Shift”, we will aim at clarifying the dynamics of the large-scaled networks during the recovery of dexterous finger movements from the spinal cord injury and visuo-motor functions after V1 lesion, combining large-scaled (whole brain) ECoG recordings, circuit manipulation using viral vectors in the macaque monkey brain, and large-scaled computation of the circuit dynamics.

 
Recent Publications
1. Sawada M, Kato K, Kunieda T, Mikuni N, Miyamoto S, Onoe H, Isa T, Nishimura Y (2015) Function of nucleus accumbens in motor control during recovery after spinal cord injury. Science, 350: 98-101.
2. Kinoshita M, Matsui R, Kato S, Hasegawa T, Kasahara H, Isa K, Watakabe A, Yamamori T, Nishimura Y, Alstermark B., Watanabe D, Kobayashi K, Isa T (2012) Genetic dissection of the circuit for hand dexterity in primates. Nature, 487: 235-238.
3. Nishimura Y, Onoe T, Morichika Y, Perfiliev S, Tsukada H, Isa T (2007) Time-dependent central compensatory mechanism of finger dexterity after spinal-cord injury. Science, 318: 1150-1155.