The human brain receives, processes, stores, and transmits complex information with great fidelity. The neuronal network that underlies these functions is comprised of an estimated 1011neurons linked by over 1014 synaptic connections between two structurally and functionally different neurites, axons and dendrites. Precise pattering of dendrites as well as axons is essential for correct wiring and function of neural circuits. We combine genetics, imaging, and biochemical approaches to investigate the interplay between genetic and epigenetic control of neural morphogenesis, and deduce the functional importance of these regulatory systems in disease etiology. We use fruit fly and mouse as research models.
1. Receptive field determination in sensory neurons
For precise sampling of sensory information, certain neurons arrange tiling of their dendrites to cover the receptive field completely and non-redundantly. By using fruit fly sensory neurons as a model system, we have shown that the dendritic tiling is mediated by homotypic repulsion between neighboring dendrites that the repulsive interaction is mediated by the NDR kinase signaling pathway (Cell 2004; Nature 2006; Neuron 2007; EMBO 2009). We are currently conducting a genome-wide genetic screen in Drosophila sensory neurons to identify the whole molecular network underlying the dendritic tiling.
2. Structural plasticity of neuronal circuits
Neuronal circuits in the brain are not static. In many systems, especially during critical periods of development, neurons exhibit a period of juvenile plasticity in which connectivity can be modified in response to sensory input or following specific experiences, thereby providing neurons with new response properties, tailored to the new environment. To achieve these changes in connectivity, certain neurons modify the shape of their axon and dendritic arbors in response to various stimuli. We have identifies novel mechanisms that regulate structural plasticity of dendritic arbors in fly sensory neurons (Genes Dev. 2007; Dev. Cell 2010). We are investigating how these mechanisms are related to the sensory-evoked plasticity in the fly and mice nervous system.
3. Neuronal mechanisms underlying preference change
The behavior of animals is flexible and can change dramatically based on the environment, nutritional state, or even age, among other factors. However, the neural basis of how external and internal cues modify innate behavior is not clearly understood. Appropriate preferences for light or dark conditions can be critical for an animal’s survival. Innate light preferences are not static in some animals, including the fruit fly, which prefers darkness in the feeding larval stage but prefers light in adulthood. This suggests that the neuronal circuits that determine the light preference have been modified during metamorphosis. To elucidate the neuronal mechanisms underlying the preference change, we examine neurons involved in larval phototactic behavior by regulating neuronal functions. To do that, we have established a quantitative assay system for larval phototaxis and started genetic screens. Through this study, we would like to understand how the brain makes decisions and also change the decision against the same sensory information.
4. Adult neurogenesis in the brain
Neural stem cells have been found in certain areas in the adult brain. Although the adult neurogeneis likely plays an important role in learning and memory, the information is still limited. We are investigating the roles of newborn neurons in the mouse and fruit fly brain.
5. Multimodal information integration
Virtual reality paradigm to assess how a fly’s behavior changes according to various combinations of stimuli. A fly is fixed on an air-supported ball and can walk freely. As inputs, computer-generated visual stimuli (black screen) as well as odorant, gustatory, and mechanical stimuli can be presented simultaneously. A fly’s walking movement is tracked by an optical sensor situated behind the ball (green), while movements in its head, legs and wings are recorded by a video camera (over a fly, blue)
Animals integrate information of multiple modalities, such as vision and taste, to select the best behavior in an ever-changing environment. We are trying to understand the neural basis of such integration by:
(i) developing new genetic tools to label and manipulate such integration circuits and through
(ii) developing a Drosophila virtual reality paradigm that enables an assessment of such integration at the level of behavior and its neuronal correlates.
6. Neural basis for human intelligence
Our species, human, is characterized by the higher cognitive functions such as the language-based communication and the conceptual thinking, Most of these functions are elicited by the computational power of the cerebral cortex. Human has significantly larger volume of cerebral cortex than the evolutionary cousins such as the chimpanzee and the gorilla, and such an extraordinarily expanded cortex facilitates our cognitive abilities. Recent advancement of genomics allowed us to identify a repertoire of genes specifically detected in the human genome but not in those of other species, most of which are originated by recent gene duplication. Some of these “human-specific genes” are actually involved in the brain development and function. For instances, we found that one of human-specific gene called NOTCH2NL has a pivotal role in expanding neuronal production and consequently the enlargement of cortical volume. Human-specific genes are also important to understand the disease mechanisms in addition to the evolution, because a significant fraction of genomic regions encoding human-specific genes including NOTCH2NL are reported to be linked to congenital neurodevelopmental and cognitive diseases. We aim to reveal the genetic and molecular mechanisms of human brain evolution by the comparative genomics and the experimental approaches based on in vitro models of human brain development using the pluripotent stem cells such as ES cell and iPS cell at the level of (1) genome, (2) cell, (3) brain structure and neural circuit embedded in it, and (4) behaviour and the disease phenotypes.