The long-term goal of this unit is to elucidate the molecular and synaptic bases of learning and memory and to establish how alterations in synaptic plasticity contribute to neurological and psychiatric disorders. This unit will study how genetic/molecular/synaptic/neuronal/local circuit-level brain mechanisms (red squares in Fig 1A and red rectangles in Fig 2A) enable cognitive faculties such as memory, learning, emotion, and sensation (red squares in Fig 1B) by integrating neurometric techniques at different depths (from genetic manipulation to live cell imaging, red squares in Fig 1C) with psychometric techniques such as maze learning tasks and behavioral genetics (red squares in Fig 1D). Bong-Kiun Kaang (Table 1A-1) will lead this unit joined by Graham Collingridge, Min Zhuo and Sang Jeong Kim (Table 1A-2~4).

The long-term goal of this unit is to understand neuronal mechanisms involved in the encoding of sensory inputs, the representation and decoding of relevant information from populations of active neurons, and the maintenance and retrieval of information within those populations. This unit will study how neuronal/local circuit/global circuit-level brain mechanisms (green triangles in Fig 1A and green rectangles in Fig 2A) enable cognitive processes such as sensation, perception, memory, decision making and attention (green triangles in Fig 1B); the aim is to integrate neurometric techniques including single/multi-unit cell recordings, micro/macro-brain imaging and brain stimulation (green triangles in Fig 1C) with psychometric techniques encompassing various forms of perceptual and memory tasks (green triangles in Fig 1D). Computational approaches will play a major role in bridging studies from individual researchers with expertise using different types of measurement (Fig 1E). Sang-Hun Lee (Table 1B-1) will lead this unit teamed up with Randolph Blake, Inah Lee and Marcus Kaiser (Table 1B-2~4).

The long-term goal of this unit is to understand psychiatric disorders, with an eye toward identifying means for correcting those disorders or minimizing their consequences. Furthermore, work carried out in this unit will promote development of computational and mathematical tools for handling neuroimaging data analyses which, in turn, will contribute to integrative evaluation of functional, structural and biochemical aspects of the brain, both disordered and healthy. This unit, led by Jun Soo Kwon (Table 1C-1), consists of two subunits. The ‘Clinical Neuroscience’ subunit, comprising Jun Soo Kwon and Sohee Park (Table 1C-2), will focus on studies of the pathophysiology of mental/brain disorders, including schizophrenia, depression, bipolar disorder and obsessive-compulsive disorder (Fig 1F), they will deploy an integrative set of neurometric (large-scale brain imaging techniques on human brains, blue circles in Fig 1C) and psychometric (various forms of high cognitive tasks, blue circles in Fig 1D) measurement tools. The ‘Computational Anatomy’ subunit, led by the collaboration between Jae Sung Lee and Moo K. Chung (Table 1C-3,4), will integrate neurometric data obtained from functional (fMRI, PET) and structural (DTI, MRI) images - major large-scale neurometric data from humans in modern cognitive neuroscience (Fig 1C) - into a single, coherent processing and analysis framework. The successful development of such tools will substantially help the other units to advance understanding of cortical and subcortical circuitries crucial for the target cognitive functions.