「台灣聯合大學系統」整合計畫
子計畫二
「腦科學研究中心」
Brain Research Center
詳細計畫書
（修訂版）
中央大學
交通大學
清華大學
0
陽明大學
中華民國 91 年 12 月 30 日
Brain Research Center
Of
The University System of Taiwan
1
Contents
List of Figures ----------------------------------------------------------------------- 2
Summary (English) --------------------------------------------------------------------------- 3
Summary (Chinese) -------------------------------------------------------------------------- 4
Introduction ------------------------------------------------------------------------------------- 5
Organization ------------------------------------------------------------------------ 9
Temporary Management Office--------------------------------------------------------------
9
Management Office ---------------------------------------------------------------------------
9
Steering Committee ---------------------------------------------------------------------------
9
Advisory Board --------------------------------------------------------------------------------
9
Research Programs ----------------------------------------------------------------------------
10
Education Programs ---------------------------------------------------------------------------
10
Relationship with other research centers and facilities in the UST ---------------------
11
Collaborative work with clinicians and researchers in other research institutions----- 11
Research Programs --------------------------------------------------------------------------- 12
Molecular and Cellular Neuroscience ------------------------------------------------------- 12
Cognitive Neuroscience ----------------------------------------------------------------------- 20
Clinical Neuroscience -------------------------------------------------------------------------
21
Brain Imaging/Informatics -------------------------------------------------------------------
23
Computational and Theoretical Neuroscience ---------------------------------------------
24
Neuroengineering ------------------------------------------------------------------------------
25
Literatures Cited -------------------------------------------------------------------------------- 34
Education Programs -------------------------------------------------------------------------- 37
Significance and Impact ----------------------------------------------------------- 38
Progress Evaluation---------------------------------------------------------------------------- 38
Budget ----------------------------------------------------------------------------------------------- 39
Appendix ------------------------------------------------------------------------------------------- 39
2
List of Figures
1.Interdisciplinary and hierarchical organization of brain research---------------------
8
2. Brain database and expression of memory genes in the Drosophila brain----------
16
3. In situ hybridization technique to detect gene expression in developing brain
and in whole mount mouse embryos -----------------------------------------------------
18,19
4. Study of neuronal cell guidance and interconnections using
photolithographic patterning of extracellular matrix molecules that guide the
growth cone of neurons in culture--------------------------------------------------------
20
5. Flow diagram of major processing steps in the BCI strategy---------------------------
27
6. Mental Workload Model of a driver based on VR-car driving simulator--------------
28
7. The BJT-base silicon retina-------------------------------------------------------------------
31
8. The implantation of silicon retina------------------------------------------------------------
31
9. The electrode-----------------------------------------------------------------------------------
31
10. Configuration of a cochlear implant-------------------------------------------------------
31
11. Block diagram of major processing steps in the CIS------------------------------------
33
12. The appearance of wearing a cochlear implant-----------------------------------------
33
3
Summary
Brain research, one of the frontier research areas in this century, is inherently a
multi-disciplinary science that requires the participation of essentially all human intellectual
activities. Such research endeavor is difficult to carry out in the research community in
Taiwan because of the infrastructure with small and isolated research departments. With the
establishment of University System of Taiwan, we hope to build a multi-disciplinary,
multi-university center for brain research based on joint and complementary effort from the
best research areas of the four participating universities. The Center will be organized based
on the current research activities of molecular, cellular, system, cognitive and clinical
neurosciences, as well as neuroengineering in National Central University, National Chiao
Tung University, National Tsing Hua University, and National Yang Ming University. The
establishment of this Center should allow us to integrate and strengthen the collaborations
among the four universities and to encourage further interdisciplinary research activities as
well as extending the current research areas to include the development of theoretical and
computational neuroscience from a pool of excellent mathematicians, information scientists
and engineers. The strength of this Center will be derived from the integration and
cross-talk of diverse research activities with potential development of emerging new
paradigms and applications to practical and clinical problems. The initial research programs
of the center shall be selected from the research proposals submitted from four universities
after being critically reviewed by an advisory committee consisting of eminent neuroscientists
outside the four universities. We will also develop a comprehensive education program that
includes both MS and PhD programs as well medical fellow training program.
Undergraduate as well as summer courses will also be organized to attract students of diverse
backgrounds to this emerging and exciting field. The significance and impact of
establishing this research center is as follows: 1) it will enable Taiwan to compete
internationally in the brain research, 2) it will help to establish a multi-disciplinary research
model in Taiwan, 3) the interactions among scientists of diverse disciplines may forge new
and novel research paradigms, 4) the results of such concerted research activities may
potentially produce useful clinical and practical applications, 5) it will help the establishment
of biotechnology industry in Taiwan.
4
摘要
腦科學是本世紀最重要的尖端科技領域之一, 這個尖端科學領域的研究是需要密
切結合不同領域知識和人才, 而台灣研究單位卻都太小及分散、沒有整合, 因此進行這
方面的研究面臨相當大的瓶頸, 而在中央、交通、清華及陽明所組織的大學系統中, 由
於其研究領域的互補, 是以可推動台灣在腦尖端科學領域的最佳契機。因此本計畫之目
標是要建立一個跨校的腦科學中心以整合加強在中央、交大、清華及陽明進行的臨床、
認知、腦影像、分子細胞及神經工程研究, 並由數學、電腦、工程專家的加入，推展新
的領域如理論神經科學。本中心並將積極延聘國際著名學者參與。 這個中心最大的特
色是不同領域的人才進行新領域的研發和應用, 建立這個跨領域的中心可以有以下的
幾個效益：
1)
提升我國腦科學研究之國際競爭力
2)
建立跨領域的研究模式
3)
促成不同領域學者之合作
4)
整合我國生物醫學研究及其臨床應用
5)
推動我國生技工業之發展
5
Introduction
The origin of the mind has intrigued human beings since time immemorial. Humans are
distinguished from the other species on this planet by an intelligence that permits the building
of civilizations. How does this intellectual capability evolve from the neuronal systems of
the most primitive animals? How can a material organ weighing only about 1.4 kilograms
develop non-materialistic abstraction, consciousness, and other higher forms of mental
activities with immense flexibility in response to the external world? Even with the
tremendous advances in our understanding and knowledge of the physical world during the
past century, the problem of mind remains one of the deepest mysteries of nature.
Since the identification of the brain as the source of the human mind, the field has
shifted from philosophical debates and phenomenological observations of behavior to the
scientific analysis of the brain and its associated sensory organs. The beginnings of
neuroscience in the nineteenth and early twentieth centuries witnessed the brain being
explored for structural organization and functional correlations by pioneers such as Broca,
Golgi, Ramon y Cajal, Sherrington, Langley and Adrian. Later, with the advent of the
neuron theory through progress in cell physiology and cell biology by the work of Cole &
Curtis (1), Hodgkin & Huxley (2), Fatt and Katz (3) etc, a great leap in our understanding of
the basic mechanism of neuronal activity occurred with the discoveries of the ionic basis of
nerve impulses and synaptic junctions. The rise of molecular biology and its associated
technologies for the analysis of gene expression as well as protein structure and function
allowed powerful new insights into the molecular and genetic basis of nerve activities. This
reductionist approach succeeded to a remarkable extent in unpeeling the first layer of secrets
of brain action and function (4-11).
However, we still lack a comprehensive understanding of the brain/mind mystery.
What is needed is an integration of the reductionist approach with a holistic or system
analysis based on macroscopic observations (12-16). Traditional behavior and cognitive
analyses have undergone a paradigm shift, aided first by theoretical advances such as the
McCulloch-Pitts model, and second by the instrumental development of high-resolution
imaging capabilities for analyzing in situ brain activity. For example, electrophysiology has
led to fundamental insights in the study of human vision. Cognitive science has now
combined these powerful tools with the molecular genetic approach to open new windows on
the brain/mind problem. Clinical neurology and psychiatry have experienced a renaissance
because of an appreciation for the molecular basis of abnormal and pathological states of the
nervous system and human behavior (17). The addition of powerful imaging equipment to
the classical arsenal of clinical observations has both advanced the diagnosis and treatment of
patients and facilitated our understanding of the basic mechanisms underlying their abnormal
6
or pathological behaviors. The explicit recognition that the study of brain has become an
interdisciplinary scientific endeavor (please see Fig. 1) led Frank Schmitt to set up a
Neuroscience Research Program at MIT in 1962. The complexity of the problem requires
the participation of the best intellects in diverse fields: mathematicians, physicists, chemists,
information scientists, engineers, philosophers, artists, and humanists, in addition to the
biologists and physicians who dominated the subject in the twentieth century. The broad
perspective from many angles of attack can often generate breaches in an otherwise resilient
wall of ignorance.
The adoption of a multidisciplinary strategy motivates the establishment of the Brain
Research Center within the four campuses of the University System of Taiwan (UST). We
will integrate top-down, holistic clinical, cognitive neurosciences with bottom-up,
reductionist, cellular, and molecular approaches. Bridging the gap will be emerging
theoretical and computational efforts that organize detailed molecular mechanisms into
hierarchical models of the system as a whole. Imaging and informatics will also facilitate
the dialogue between those who ponder the basic questions from the microscopic and
macroscopic perspectives. The goal is to unite the separate disciplines through synergy of
effort and mutual stimulation of fruitful ideas.
Interdisciplinary and intercampus
collaborations will be the hallmark of this Center. Its advantages will derive from the existing
intellectual strengths at NCU, NCTU, NTHU, and NYMU in physical sciences, informatics,
engineering, biology, and medicine. Three Veterans General Hospitals, which are among the
best medical centers in Taiwan, will provide access to human subjects and frequent
interactions with practicing physicians.
An excellent foundation for forming a UST Brain Research Center already exists in the
Institute of Neuroscience at NYMU, established in 1980 and to which a cognitive section was
added two years ago. At the Institute of Neuroscience and Faculty of Medicine, an active
brain research group supported by Taipei Veterans General Hospital with the state-of-the-art
imaging and mapping instruments has been productively engaged in human brain research for
some time. Recently, NYMU was awarded a National Core Laboratory of MicroPET and
Microarray as well as a Genomics Center. A research program in Regenerative Medicine
was also inaugurated with one of its goals being nerve regeneration.
In addition, we
already have in place education programs in molecular, cellular, and cognitive neurosciences.
These pilot research and educational programs can form a firm basis for the establishment of
more comprehensive endeavors.
Why is it important for Taiwan to have a comprehensive Brain Research Center? First,
brain research is one of the frontier investigative areas of this epoch. As a consequence,
many nations have invested heavily in the establishment of neuroscience research centers.
Characteristically, the United States got an early and impatient start on the rest of the world,
declaring the 1990s as the “Decade of the Brain,” and launching a “Human Brain Project”
7
which culminated in 1999 with the establishment of a NIH Biomedical Brain Research Center.
Europe followed with a program centered on the “European Decade of the Brain,” and Japan
began its Brain Science Institute in 1998 with a NT$2 billion budget, and handsome annual
increases thereafter. Korea and India have since also established their brain research centers.
Recently, MIT set up its neuroscience research institute with a gift of NT$ 10 billion from the
McGovern family. While it is not necessary to follow every international bandwagon, brain
research is such an intrinsically important field of scientific and humanistic endeavor that
Taiwan cannot afford to lag far behind. We may differ, however, in opinion as to how much
time will be required realistically to make significant contributions to the overall enterprise.
We suggest that the twenty-first century should be hailed as the “Century of the Brain,” and
that patience, steady funding, and sustained effort will all be required to obtain satisfactory
answers to this very complex problem.
Second, the aging populations of the developed countries of the world are imposing huge
social and fiscal burdens on their governments. Attending an aging citizenry are
neurological and psychiatric disorders for which there is an urgent outcry for better diagnosis
and treatment or preventive measures. A rational and humane basis for meeting these
demands cannot be constructed without research into a basic scientific understanding of the
disorders. As a beneficial byproduct, the development of diagnosis protocols, drugs, and
therapeutic agents will help to promote the biotechnology industry of Taiwan.
Third, research in cross-disciplinary topics requires interdisciplinary organization and
collaboration. Cross-fertilization of the ideas from several fields is a proven source of
innovation and creativity, characteristics that have been markedly rare in the R & D activities
of Taiwan, where projects have typically been carried out by individuals, small groups, or
narrowly focused laboratories. The organization of the Brain Research Center within the
four-campus structure of UST can form a new paradigm for doing research on big topics in
Taiwan. It will teach the value of cooperation and collegiality. It will demonstrate the
economies of scale available when diverse groups pool their resources in pursuit of common
goals. It will force priority setting on a community that has been conditioned by scarce
resources to act otherwise in an over-interpretation of the meaning of democracy. In a
sentence, brain research can make the R & D enterprise in Taiwan behave more intelligently.
8
Fig. 1. Interdisciplinary and hierarchical organization of brain research
9
Organization
The Brain Research Center is composed of a Management Office, Advisory Board,
Research Programs, and Education and Clinical Training Programs. It is clear for a research
center to be successful it needs to have a high concentration of good scientists with diverse
approaches in close proximity. In the first year of the program when the center is being set
up there will be a temporary management office working closely with the steering committee
for setting the direction of the Center as well as searching for the new director. The UST
system will search for a suitable site for the Brain Research Center either using the existing
available spaces or, preferably, through soliciting for funds from the government for the
construction of a new building to house the new center. The short term and long term
organization of the Center is described as follows:
Temporary Management Office: Before the suitable site has been specified for the Center
and before the new Director is recruited the Center will be managed by a committee
composed of neuroscience representatives from the four campuses. The Office will work
closely with the Steering Committee (see below) to carry out the administrative work such as
budget matters, coordination the research activities and research discussion sessions etc.
Management Office: A Center Director will manage the administrative business of the center
through a Management Office. The Director and this Office will be responsible for
managing the budget; setting research priorities and strategic directions; directing personnel
policies and facility operations; promoting interactions among the different internal scientific
programs of the Center (see below) and with external organizations; assessing and
documenting overall research progress; as well as communicating with and reporting to the
Steering Committee of the UST.
Steering Committee: Before the Director is recruited the Center will be operated by a
steering committee consisting of experts in brain research. The committee will work closely
with a working group of research scientists from UST to set the research priorities and
directions as well as to search for the new director.
Advisory Board: A panel of advisors (please see the list in the Appendix) will give advice on
research directions and strategies for the Center. Together with the Director, this Board will
assist the MOE and the UST Steering Committee in their periodic evaluations of the Center’s
research progress and operational efficiency.
10
Research Programs: The research will initially be based on the current research activities in
clinical, cognitive, molecular and cellular neuroscience with excellent supporting modern
facilities such as fMRI, MEG, PET, microPET, major genomic science technologies,
computational capabilities etc. The direction of the research program will be subjected to
the review of the steering committee to set the priorities of research goals in the short term
based on the current research activities in the four campuses and in the long term based on the
recruitment of faculties in the desired research areas. In the initial period of Center
operation, research priorities will be based on the results of review of the proposals submitted
by the faculties in the four campuses subjected to the review by a panel of experts. Current
research programs in the four campuses can be divided into four basic areas: 1) clinical
neuroscience including neurodegenerative diseases, strokes, and tumors; 2) neurogenomics,
and molecular neuroanatomy and physiology using bottom-up approaches; 3) cognitive
neuroscience and brain imaging/informatics using top-down approaches; and 4) applied
neuroscience targeting the brain-computer interface for practical and clinical applications.
Discussion sessions and workshops, open to the faculties, staff members, postdocs, and
students of the UST and by invitation to other members of the national and international
research community, will provide the key mechanism for attracting scientists and students
from other fields into brain research. As the Center matures and gains critical mass, we hope
increasingly to involve experts from the arts, humanities, and social sciences, in addition to
colleagues in mathematics, physics, chemistry, computer science, and engineering.
Neuroscience research can ultimately achieve its fullest potential only by drawing on a free
exchange of ideas across the whole spectrum of human intellectual endeavor.
Education Program: A forefront education program is essential if Taiwan is to have an
adequate future supply of medical and scientific staff for clinical neurology and
brain/neuroscience research. The neuroscience program will have a common core course so
all students and medical staff can be exposed to current concepts and developments in the
general field. The clinical program will consist of a combination of lecture-based courses
and clinical training, whereas the graduate programs will rely on elective courses and a
written thesis. Participation of students and faculties in program discussions and workshops
will form an integral part of the curriculum. Because of the current format of university and
college education in Taiwan, we will set up both a Masters and a PhD program, with early
transfer from MS to PhD possible, dependent on the potential and performance of the student.
We hope that we can also institute in the near future a MD-PhD program for the education of
physician scientists in brain research.
11
Relationship with Other Research Centers and Facilities in the UST. The Center will
share facilities and human resources with related research centers and research laboratories
that exist in the UST. This includes the Genomics Center and its associated core laboratories
(molecular pathology, gene expression, antibody and phage display, genotyping, yeast,
Drosophila and C. elegans model systems), and the Proteomics Center. The Brain Research
Center will also interact strongly with the three Veterans General Hospitals, the Neuroscience
Institute, and the Regenerative Medicine Program.
Collaborative work with clinicians and researchers in other research institutions. The
Center wishes to have extensive collaborations with and eventually includes excellent
scientists and clinicians working in neuroscience areas from other research institutions such
as Academia Sinica, National Chungshan University and National Cheng-Kung University.
For example, there are a number of excellent scientists in Academia Sinica working in the
area of neuroscience such as Dr. E. H. Y. Lee who has been working on molecular and
cellular mechanisms of long term memory in rat and Dr. Yijuang Chern is working on the role
of adenosine in neuronal secretion and locomotor activities. These investigators have long
term association with the Institute of Neuroscience in National Yang Ming University. Taipei
Medical University is establishing a Stroke Center headed by its new President, Dr. T. Y. Hsu
who headed the Stroke Center in Washington University for many years. Close
collaboration with this new clinical center and with Dr. Hsu will enhance and benefit the
research program in this Center.
12
Research Programs
Goal:
The goal of the Center’s research platform is to integrate theoretical, molecular,
anatomical, functional, and clinical approaches with a basic understanding of the mechanisms
and processes underlying the normal as well as the pathological activities of the brain. The
information thus gained could be applied to clinical diagnosis and therapy as well as to the
development of new computer and informatics algorithms, thereby promoting progress at the
brain-computer interface as well as benefiting from such new technologies.
Research Program: In the initial phase of the Center the program will be based on the
research proposals submitted from the four campuses. These proposals will be critically
reviewed by a panel of external experts in the Steering Committee. Those programs selected
by the committee based on merits and on the collaborations among the four campuses will
constitute the research programs in the initial phase of the Center. In particular, novel
programs initiated by the collaborations between diverse research fields in the four campuses
will be encouraged.
A synopsis of the current research areas in the four campuses:
Molecular and Cellular Neuroscience Program
Neurogenomics:
The reductionist approach of molecular biology during the past four decades has given
tremendous insight into the molecular mechanisms of many biological processes. The
cloning of genes and the analysis of the three-dimensional structures of proteins involved in
neurological function have also helped to establish the great complexity of the molecular
pathways that define neural networks, brain organization, and brain laterality. For example,
the recent landmark discovery of immuglobulin-like genetic mechanisms of synapse
connection through recombination of variable and constant regions of protocadherins by Wu
and Maniatis (20) has interesting implication in predetermnation of brain neural network (21).
This type of work has exemplified the power of molecular genetic approach in elucidating the
basic mechanism of brain functions. However, integration of these vast amounts of
molecular information and the study of dynamics of the molecular pathways are needed for us
to begin an a priori mechanistic understanding of the problem of brain functions.
The arrival of the genomics era offers unprecedented opportunities for examining genetic
13
influences in the neuronal network system in a comprehensible way. Top-down genomic
approaches such as transcriptome (microarray, SAGE, subtractive hybridization) and
proteomic analysis using two-dimensional gel electrophoresis plus mass spectrometric
techniques may help to uncover novel genes and pathways that are involved in brain
development, normal and pathological. The recent genomics discovery of a novel
polymorphic gene implicated in Alzheimer disease, nested within the intron of the tau gene,
exemplifies the power of such an approach (22).
Bottom-up approaches using gene targeting, gene product localization, transfection cell
models, as well as transgenic models and mutagenesis, could also help to reveal the functions
of genes and their signaling pathways. On the UST campuses, several laboratories have
taken such an approach to study, for example, Pksc, Lgec-18 and ApoE models and
sulfotransferase and dihydropyrimidinase isoforms in brain development and diseases.
Through the funding of the Program for Promoting Academic Excellence from the Ministry
of Education, a Genomic Center and its associated core labs, including the transcriptome
analysis lab, was established at National Yang Ming University. UST also hosts the
Proteomics Center, which has a state-of-the-art 2-D gel apparatus, gel picker, tandem-Mass
and MALTI-TOF mass spectrometer. Furthermore, single cell molecular biological
techniques such as optical tweezer, confocal microscopy, in situ hybridization, FRET,
single-cell amplified antisense RNA (aRNA) technique are available at UST and provide
powerful tools for analyzing gene expression pattern and regulation in specific neuron types.
We will use these facilities to examine the gene expression patterns at mRNA and protein
levels in diseased brain versus normal brain tissue.
A protein chip and sensor technology is under development at National Chiao-Tung
University. We plan to examine the oligopeptide profiles during brain development and in
diseased states using capillary electrophoresis-microelectrospray-tandem mass spectrometry
(23) and the newly uncovered developmental regulatory microRNA (24, 25) profiles using
polyacrylamide gel electrophoresis. These analyses will be complemented by a study
utilizing a mutant amyloid precursor transgenic mouse model for Alzheimer’s disease. The
transgenic mouse lab is practiced at producing transgenic mice models, and we will utilize
this facility for such neurogenomic analyses.
Besides genetic factors, epigenetic mechanisms play a major role in shaping brain
function. Genomic imprinting has been shown recently to be an important source of human
diseases including genes involved in psychosis (26) and methylation of cytosine in DNA can
play an important role in regulating neuronal functions in CNS (27, 28). Several faculty
members in the UST have been interested in the DNA-methylation mechanism for regulating
brain gene function. For example, Dr. T. F. Tsai has been working on the Prader-Willi
Syndrome, a neurodevelopmental disorder, and she has recently published her results in
Nature Genetics. The complexity of methylation profiling during brain development may
14
provide a key for understanding many of the neuronal phenotypes.
For this reason,
brain-specific library of methylated sequences have been generated through the development
of novel PCR-fingerprinting based techniques. These libraries may help unveil novel
molecular mechanisms in the specification of neuronal functions in the brain.
Another area of interest at UST is the study of mitochondrial genome mutations that
have been shown to result in several types of neurological diseases. Prof. Y. H. Wei has
collaborated closely with physicians in this field. Although the specific mutations are
known, the molecular pathways leading to specific pathologies remain unclear. Resolving
this problem is the future thrust of this part of the research program.
Faculty members in the UST have also formed a cancer genomics group to analyze
genetic alterations in human tumors. Several modern analytical tools, such as Comparative
Genomic Hybridization, Spectrokaryotyping, BAC array CGH, comparative genomic
fingerprintings, etc., have promising applications in these studies. The techniques can also
probe for genomic changes associated with neurodegenerative and psychiatric disorders.
Cellular and molecular study of neural network and plasticity
Human brain consists of 1011-1012 neurons. Each neuron receives inputs, via synapses,
from hundreds to tens of thousands of other neurons, integrates these inputs, and then
transmits the resultant information to other neurons. Human brain can hence be considered
as a network composed of a very large number of synapses. The hard wiring of this network
of synapses serves as the base for the diverse functions of the brain. In addition, the
working capacity of this network of synapses is dramatically augmented by a remarkable
feature of synapses, that the synaptic functions are potentiated or depressed in a
use-dependent manner. This latter feature forms the basis of the higher functions of the
brain, e.g., learning and memory. A complete understanding of the molecular mechanisms
underlying synaptic plasticity shall lay the foundation for our striving toward understanding
how human brain functions and how brain disorders are derived from circuitry malfunctions.
However, the magnitude of this task appears to be formidable due to the involvement of large
number of molecules at different levels; to accomplish this task, systematic analyses of the
gene and protein expression, as well as thorough studies of neural functions are required.
Modern genomic and proteomic technologies have fortunately progressed to a stage to
meet the demand for systematic analyzing the gene and protein expression in organisms.
Based on the excellent performance of the scientists in the UST campuses in genomics and
proteomics and neurophysiology, the neuroscientist group of National Tsing Hua University
shall join forces with all proteomics and genomics specialists in the UST system to launch a
multi-disciplinary research program aiming for the understanding of the molecular
mechanisms underlying the use-dependent synaptic plasticity and complex information
processing by brain circuits. These goals shall be reached by the following three
15
approaches:
1. Functional and proteomic analyses of mammalian brain slices. Microarray and
proteomic techniques will be employed to analyze the expression of numerous genes and
proteins efficiently, systematically and quantitatively. In addition, proteomic techniques
shall be exploited here to investigate the correlative relationship between the posttranslational
modifications of various proteins and neural plasticity. We shall prepare brain slices from
rat hippocampus or cerebral cortex, induce long-term changes in synaptic functions by
electrical or pharmacological means, confirm the induction of synaptic changes by
electrophysiological and/or imaging technologies, collect tissues from areas where long-term
synaptic changes have been induced, and finally carry out proteomic and microarray analyses
for alterations in proteins, posttranslational modifications and mRNAs. The proteins whose
expression correlates with the induction of long-term synaptic changes shall be further studied
by cell biology means. Models for the intracellular signaling network consisting of various
interacting proteins shall be made to describe the induction of long-term synaptic alterations.
These models shall be made on the basis of data not only from the above experimental studies
but also from data mining of various data bases and literature.
2. Functional and genomic analyses of Drosophila learning and memory. As the first phase
of several genome projects approaches completion, attention shifts from questions of genome
structure to problems of gene function. Recent advances in imaging and molecular tagging
are opening up exciting new ways to visualize gene expression patterns and follow the
process of protein interactions in time and space. One area of interest at UST is to study
gene function and hard wiring involved in the process of learning and memory. Drosophila
shares similar mechanisms of learning and memory with vertebrates at the molecular level;
and many of the genes identified in human mental diseases are evolutionarily conserved.
Drosophila can learn. They can be trained to run from an odor that they previously
experienced with an electric shock. A number of single gene mutations dramatically reduce
the ability of fruit flies to learn or to remember the association between two cues, the odor
and the electric shock. This allows discovery of about 10 genes, when mutated, affecting
memory. Modern studies of the genetic control of memory have increased the need for an
accurate and comprehensive storage and display of gene expression data. To understand
how genes contribute to learning and memory, we must identify and characterize the units of
function: the neuronal networks that receive, process, store and retrieve information.
16
a
b
Fig. 2. Brain database and expression of memory genes in the Drosophila brain. a,
Spatial coordinates of GH146 expression patterns (gold) in a standard brain.
Mushroom bodies (grey), optic lobes (yellow), central complex (blue). b, Brain circuits
expression five memory genes. muraska (gold), mampus (blue), derailed (orange),
GH146 (green), amnesiac (purple). Gene expression patterns of memory Gal4 lines
are indicated by UAS-GFP reporters.
Volume models are generated from
high-resolution confocal images followed by brain warping.
Faculty members in the National Tsing-Hwa University have recently developed a series
of imaging tools allowing visualization of neural networks at single-bouton resolution in the
whole-mount Drosophila brain. They have also written special softwares for 3D image
processing such as 3D montage, segmentation, and neuropil averaging methods. This allows
volume modeling of the whole Drosophila brain in a common 3D framework (Fig. 2). The
first virtual fly brain has been recently installed in the Virtual Reality room in the National
Center of High-performance Computing in Taiwan. When viewing this 3D brain in the
Virtual Reality room, audients will feel like touring inside the fly brain. In collaboration
with Dr. Tim Tully at Cold Spring Harbor Laboratory, we have recently mapped the
expression patterns of 47 novel genes involved in memory formation in Drosophila. Our
goal is to build the first 3D database of the fly brain showing expression of specific genes
involving in learning and memory. Figure 2b shows the expression of five memory genes in
the whole-mount Drosophila brain. The established 3D brain database will provide the
basic information of hard wiring and genes involving in learning and memory in Drosophila
brain. One can anticipate that, in the future, neuroinformatics will include simulation
models not only as exploratory tools, but also as framework data to encode complex causal
relationships and as part of the tools for hypothesis generation for complex systems such as
memory formation.
3. Study of the temporal, spatial and cellular processing of visual information from retina to
primary visual cortex in living animals by silicon-based multi-electrode array technology.
Because of its clearly defined stimuli, vision is the most extensively studied one among
sensory systems. The goal of this project is to elucidate how visual information is processed
at the retina and primary visual cortex of rabbits. Light stimuli impinging on retina consist of
17
a collection of photons of different energies. Various cell types in the retina not only detect
these characteristics of light stimuli, but also register the temporal and spatial correlates
among photons. These different kinds of information then flow into deeper areas of the brain
via a string of stops, e.g., lateral geniculate nucleus, primary and secondary visual cortices,
etc. At different stops, local neural circuits allow the extraction of various features out of light
stimulus, and more abstract features are detected as visual information flows deeper into the
brain. It is well accepted that the neurons in different stages of visual information flow and
processing do not respond independently, rather they often fire in synchrony. This
synchronous firing has been implicated to play important roles in information processing and
coding. Therefore, an ideal instrumentation for studying visual information processing should
possess the following capabilities: recording the electrical activities of a population of
spatially-related neurons simultaneous, correlating the electrical activities to different cell
types, and handling and analyzing the huge amounts of data collected. In this proposal,
scientists from four colleges, i.e., the College of Life Science, the College of Engineering, the
College of Science and the College of Electrical Engineering and Computer Science, of
NTHU shall form the core work together with the remaining neuroscientists in UST system to
develop an ideal instrumentation that possess the aforementioned capabilities for studying
visual information processing. The overall goal of this part of our research program is to
investigate how visual information is transmitted to and processed by the neural circuit of
primary visual cortex. To reach for this goal, better tools including multi-electrode arrays and
computational and mathematical methods will be developed. Initially, we shall use isolated
rabbit retina as the testing ground for the development and characterization of various tools.
These tools are then used to record neural activities in rabbit primary visual cortex. When the
usefulness of these new tools has been demonstrated first in retina and then in primary visual
cortex, we shall actively seek collaboration with other fellow scientists, particularly those
who are interested in cognitive neuroscience, in the remaining campuses of the UST system.
Because the members participating in this project will have accumulated extensive
experiences about these tools then, they shall be able to adopt or/and modify these new tools
to other animal for different studies. It is conceivable that these collaborative works shall
proceed rather rapidly and productively.
Molecular neuroanatomy and physiology
Neuroanatomy was the major tool for the founding of the field of neuroscience in the
landmark work of Santiago Ramon y Cajal at the turn of the last century. Because the
molecular and genetic approaches have proven so pertinent in other branches of neuroscience,
it is natural to ask whether a holitistic neuroanatomical viewpoint can contribute equally to
the unraveling of the functional roles of newly discovered biomolecules and genes that have a
clear relationship to the structures and modules of the brain. The rich spatial and temporal
18
information of the structural organization of neurons in the normal brain as well as in
pathological states, as deduced by microscopic and imaging techniques, combined with the
molecular information generated by modern genomics and molecular biological techniques,
should interface well with physiological activity to lend insight into the molecular
mechanisms of brain function. The recent development of 3-D imaging technique of gene
expression in the brain, the voxelation technique, has allowed a detailed molecular and
functional analysis of brain function (29, 30).
Several faculty members in the UST have expertise in neuroanatomy and in situ
hybridization and immunohistochemistry techniques for analyzing gene expression patterns in
brain sections (see e.g. Figure 3). Since our university system is also equipped with a
state-of-the-art laser-dissection machine, we can combine these techniques and use a
micro-dissection technique to isolate a particular area of functional interest in the brain. The
dissected tissue will be analyzed for the expression of specific neuropeptides, or
neurotransmitters, by microcolumn-coupled mass-spectrometry. We will also use in-situ
hybridization or immunohistochemistry to look for transcription factors, integrins, or
receptors. These molecules are implicated in the differentiation of neuronal cell types. The
characterization of their fine-grained distribution in the brain with respect to the development
and diseased states would have great value. We could also analyze the gene expression
profiles in the area of interest by transcriptomic and proteomic techniques, comparing normal
tissues at different development times or with diseased tissues. A detailed description of the
global gene expression pattern could be discerned by using the recently developed voxelation
technique to examine the differential gene expression of diseased brain or in brains in
different physiological states.
Expression of a novel gene, Lgec-18, in the
developing striatum of forebrain
The expressio pattern of Lgec-18 mRNA in the developing brain was studied
using in situ hydridization technique with a 35S-riboprobe. A-C: X-ray film
images of an embryonic day 20 rat brain at rosrtal (A), middle (B) and caudal
(C) levels. D-F: X-ray film images of a newborn rat brain at corresponding
anatomical levels as those of A-C. In either ages, signals were primarily present
in the developing striatum (dark areas).
19
Fig. 3. In situ hybridization technique to detect gene expression in developing brain
(previous page) and in whole mount mouse embryos (top).
Cellular neuroscience
The recent advances in neurogenesis in adult brain have caused a paradigm shift in the
study of brain function (31, 32). The fact that neurogenesis can occur in an activity
dependent manner has tremendous implications both in cognitive neuroscience and in clinical
neurology. Neuronal stem cells also hold great promise for cell-based therapies of
neurodegnerative diseases and nerve injuries (33, 34). These advances have stimulated the
enthusiasm for studying the biology of neuronal stem cells and its plasticity. The
VGH-NYMU campus has formed a Regenerative Medicine Research Program with one of the
efforts focused on nerve-cell regeneration and stem-cell analysis. Study of stem or
progenitor cells in the brain is of great interest for both basic research and clinical
applications. A new mode of thinking is that some neurological or psychiatric disorders may
actually be “stem-cell disease.’’ An analysis of the regulation of stem cell growth versus
differentiation may also allow us to understand neurogenesis in the different areas of the brain
and its pathological consequences following abnormal differentiation. In our proposed
program, we will characterize neuronal stem or progenitor cells in culture, and then study
20
mouse models of nerve regeneration.
One of our groups is particularly interested in using semiconductor-based technology to
manipulate neuronal growth and interconnection in cell culture (see the Figure 4 below).
This research would allow us to examine the regulation of neuronal connection in a
well-defined and controlled quantitative manner.
Fig.4. Study of neuronal cell guidance and interconnections using photolithographic
patterning of extracellular matrix molecules that guide the growth cone of neurons in
culture.
Cognitive Neuroscience Program
Cognitive neuroscience attempts to understand mental abilities of the human brain such
as memory, perception, and other higher processes through an interdisciplinary merger of the
techniques of cognitive psychology, neurochemistry, physiology, brain imaging, and
molecular neuroscience (18, 19). Exciting and novel results are beginning to emerge from
the marriage of the holistic methods of classical psychology and psychiatry and the
reductionist methods of the molecular biology of neurological functions. One day this union
may enable us to understand the mechanistic basis of consciousness and intelligence.
One area of emphasis in this program is the cognitive neuroscience of human languages.
The laboratories of Prof. Ovid Tseng and Daisy Hong have collaborated with Dr. Elizabeth
Bates of the University of California at San Diego to establish facilities and recruit personnel
to carry out cognitive neuroscienctific studies of language behaviors from a cross-linguistic
perspective. Cross-linguistic studies of normal and aphasic language behaviors permit the
separation of universal mechanisms from language-specific content. By uncovering the range
of variations that are possible under normal and abnormal conditions, cross-language studies
21
also address the critical issues of behavioral and neural plasticity.
In our new studies, the program will conduct comparative studies of language processing
and language breakdown in aphasic patients and controls. We focus on three languages
(English, Italian and Chinese) that differ dramatically in their lexical and grammatical
structure (e.g. amounts of word order variation, inflectional morphology, constituent omission,
consistency vs. irregularity of words and morphemes, potential for lexical ambiguity, and the
internal structure of words). Patient studies (the classical method of lesion-behavior mapping)
are complemented by brain-imaging studies of normals in the same three languages (using
functional magnetic resonance imaging, or fMRI). The brain imaging studies will be in
collaboration with Prof. Jen-Chuen Hsieh and his lab. The same materials are used in
behavioral and fMRI experiments, in ‘on-line’, computer-controlled tasks that yield
information about the temporal dynamics of word and sentence processing. Nonverbal control
tasks are designed to match linguistic tasks in key respects (visual, auditory, and motor
activation; demands on memory, attention, decision-making), testing hypotheses about the
contributions of modality and sensorimotor demands to language activation (fMRI) and
language breakdown (lesion studies).
We also expand the concept of “normal control” to include comparisons of normals
tested under adverse processing conditions (perceptual degradation, temporal compression,
cognitive overload), to uncover “breakpoints” in processing and to “simulate” processing
disorders in patients. Selection of word and picture stimuli is based on massive norming
information collected at all sites in the last funding cycle. The aphasia subgroups under study
include nonfluent Broca’s aphasics, fluent Wernicke’s aphasics, and anomic patients who
commit few overt grammatical errors but still struggle to “find the right word.”
Acknowledging the limitations of traditional aphasia categories, we take a new multivariate
approach, analyzing patients’ performance on experiments within a continuous,
multidimensional symptom space, defined for each language by using large archival data sets
(more than 200 patients per language). Results are interpreted within two merged theoretical
frameworks: the Competition Model (a processing model that assumes interactive activation
over distributed, probabilistic representations) and Embodiment Theory (a theory of neural
organization for language).
Clinical Neuroscience Program
One of many envisions of the Clinical Neuroscience Program is to provide an
environment for rapid and effective integration and implementation of knowledge obtained
from technical and basic science programs as well as to provide, through pathology, a
mechanism for basic science programs to study localized and limited perturbations to the
22
complex neurological network of the human brain and its peripheries. It is the goal that the
knowledge obtained through the Clinical Neuroscience Program will lead to improved or new
diagnostic approaches and therapeutic strategies (pharmacology, surgery, rehabilitation and
psychology) and shed light on mechanisms of plastic changes in the brain induced by
injury/disorders and through recovery of neurological diseases.
This program will be developed initially on the basis of the research direction
established by the existing teams that include both basic and clinical research scientists
primarily from Taipei Veterans General Hospital and National Yang-Ming University. One of
the major focuses of this program will be on non-invasive studies of brain-related disorders
by means of brain mapping/imaging, which are readily available through the efforts of
scientists from Taipei Veterans General Hospital and National Yang-Ming University. The
techniques utilized will span multimodal imaging/mapping facilities, e.g fMRI, EEG, MEG,
PET, SPECT, and TMS. All state-of-the-art imaging modalities make the visualization of
information processing in the human brain possible. In addition, several cell and animal
models will be established to study the neuronal network, temporal cascade, and biochemical
pathways that generate disorders in the nervous system in order to shed light on new
diagnostic approaches and therapeutic (pharmacology, surgery, rehabilitation and psychology)
strategies.
The major direction including: (1) Neurodegenerative diseases including Alzheimer's
disease and Parkinson's disease. The aim will be to study the pathogenesis process using cell
and animal models and to develop therapeutic strategy for the diseases. (2) Spinal cord injury
and neural regeneration. Study will include using cell and animal model to the study of the
molecular mechanisms involved during neural regeneration and to develop clinical
therapeutic strategy for neural regeneration. (3) Brain tumor. To establish parameters for
evaluating functionally eloquent cortical areas in patients with brain tumors for tissue and
function preservation; and to incorporate functional localization by imaging modalities to
serve as surgical navigators. (4) Drug abuse. The aim will be to establish the mechanistic
relationship between genes and behaviors under the influence of substance abuse and
addiction. (5) Psychiatric disorders including schizophrenia, attention deficit, and depression.
The aim will be to address the functional, architectural, biochemical psychobiology of
patients with psychiatric disorders using multimodality approaches; and to integrate cognitive
neuropsychology into the quantitative assessment of mental dysfunction. (6) Cerebrovascular
diseases. To investigate the central plasticity of motor, sensory, and language-related
functions in patients with cerebrovascular diseases; to probe novel therapeutic intervention;
and to study the mechanisms of stroke and its prevention.
The aforementioned research includes a close interactions and collaboration among
scientists and clinicians of basic science, clinical, brain imaging, and cognitive neuroscience
groups for the molecular and genetic studies and higher function analysis. Through these
23
interactions and facilities, the biomedical research efforts of all the campuses of UST would
receive immeasurable benefits.
Brain Imaging/Informatics Program
Mind and consciousness can not be studied from the molecular or cellular level but
needs a macroscopic view in order to appreciate the synergistic effects between functional
brain regions. Recent technical advances in brain mapping/imaging, e.g. PET, fMRI, EEG,
MEG, TMS, NIRS/I (near infrared spectroscopy/imaging), have initiated an explosive
development of innovative methods for data analysis and visualization and made it possible to
study entire neuronal networks of the brain in action. The Brain Informatics/Imaging
Program aims at unraveling brain dynamics and structural architecture through
spatiotemporal and multimodal approaches.
Brain structure and dynamics are so complex, and vary so markedly across subjects, that
any meaningful modeling effort to explain data from many different sources will require a
sophisticated multidisciplinary approach. The task force to be established is based on the
Integrated Brain Research Laboratory of Taipei Veterans General Hospital and the UST. It
will bring together physicists, mathematicians, computer scientists, and engineers to work in
collaboration with neuroscientists and clinicians to drive relevant technological advances in
medical imaging.
The Brain Informatics Group will emphasize EEG/MEG source modeling, including
brain rhythms and connectivity between neuronal ensembles. This group will also seek to
expand the facilities to include stereotaxic TMS in order to track neural activation
mechanisms. The nonlinear approaches, such as chaos theory, phase synchronization and
resonance, will be applied to understand the characteristics of spatial and temporal brain
signals or the coherence between electromyographs (EMG) and EEG/MEG. Through these
mathematical-grounded methods, we can explore the brain dynamics from a macroscopic
viewpoint. Specific advantages of fMRI, EEG, and MEG can be combined through
multimodal co-registration to provide more abundant, accurate, and robust data for further
mechanism pursuit of the human brain. By using morphometric techniques, we can quantify
the anatomical aberration of patient’s brain, develop the Chinese brain atlas to store the
anatomical and functional information based on population variability, and visualize the
cortical surface for both sulci and gyri together with their functional mapping.
The Brian Imaging Group emphasizes the combination of data from the different
scanners for interactive multi-modality image analysis. On-going projects are listed below: (1)
Multi-modal Dynamic Brain Imaging Techniques are integrated to dissect dynamic brain
system by stereotaxic TMS, fMRI in high spatial/temporal resolution, MR perfusion
technique, functional computed tomography (fCT), simultaneous acquisition techniques (e.g.
24
EEG-fMRI simultaneous recording) and interactive approaches, (2) Real-time Processing and
Feedback Systems are developed for real-time fMRI, EEG and MEG analyses using
conventional hypothesis-driven methods, data-driven approach and pattern/feature
recognition, and (3) Image-guided Neurosurgical and Neuroradiological Intervention will
provide clinical applications using the acquisition, analysis and display of 3-D images for
interventional planning and guidance. Integration of real-time processing systems and brain
informatics benefits lots of clinical interventional procedures and possible in vivo brain
studies of human brain.
Computational and theoretical neuroscience
With billions of neurons and trillions of neuronal connections, neural networking in the
brain is an extremely complex system, capable of highly plastic and adaptive responses and
the generation of yet unfathomable mental activities. The ultimate goal of computational
and theoretical neuroscience is to simulate the macroscopic and mesoscopic dynamic patterns
of the brain from the highly interconnected microstates of neuronal circuitry using
mathematical principles and modeling. The emerging fields of self-organizing systems,
non-linear dynamics, and graph-network theory of coupled dynamical systems offer new
strategies for understanding the cooperative behaviors of neural networks. The small-world
effect of clustered networking, as inferred from Hebb’s cell assembly theory (35, 36),
suggests both robustness and sensitivity in the emerging patterns of such a complex network
system. This type of modeling may help to bridge the mesoscopic gap between the
microscopic genetic information obtained from bottom-up approaches to brain function and
the macroscopic behavioral patterns inferred from top-down descriptions of brain action.
Mathematical modeling may also provides guidance for interpreting complex experimental
results and in formulating a theoretical framework for understanding and unifying the
underlying mechanisms associated with the observed phenomena. At a practical level,
modeling of the dynamic processes observed in EEG, MEG, and other neuroimaging
techniques, may help with decision making in clinical diagnosis.
The computational approach is becoming increasingly more powerful thanks to the
exponential growth of the capability and speed of modern computers. Research in the field
requires inputs from clinicians, computer scientists, and mathematicians. The faculties in
National Tsing Hwa University have interested in modeling of the intracellular signaling
network related to synaptic plasticity and the functional consequences of neural networks
with use-dependent synaptic plasticity. Cooperative research is the focus of ongoing
collaborations between the neuroimaging lab at VGH-NYMU and computer scientists and
25
mathematicians at the other campuses of UST. The establishment of the Brain Research
Center at UST will further cement these fruitful joint efforts. The Center can play a unique
unifying role to tie together Taiwan universities that have strong mathematical and
information-sciences departments. Indeed, several faculty members at NCU and NCTU have
already expressed interest in applying non-linear dynamics and lattice-dynamics theories, as
well as wavelet analysis, to the study of neural networks and brain imaging.
Neuroengineering Program
Based on the knowledge obtained from brain dynamics and brain modeling, we can
consider neuroengineering applications at the so-called brain-computer interface (BCI).
Even more promising may be brain-actuated devices (BAD) that facilitate user
communication and control, through output channels that do not depend on the brain’s
connection to peripheral nerves and muscles. Current interest in BCI and BAD include the
motivation to provide augmentative communication options for those with severe living
disabilities that prevent them from using conventional communication technologies, all of
which require some degree of voluntary muscle control. One only has to think of the
example of the astrophysicist Stephen Hawking to appreciate what a difference such devices
could make to the intellectual progress of an individual or society as a whole.
Over the past five years, the volume and pace of BCI research have grown rapidly.
Conventionally, BCI researchers focus on brain electrical activity, recorded from the scalp by
electroencephalography (EEG), as the basis for this new communication and control
technology. We will consider not only EEG signals, but also other neurophysiological and
cognitive markers based on brain-mind-body interactions as visualized by the aforementioned
multimodalities for displaying brain information-processing.
There are three areas of BCI research currently being carried out at NCTU in collaboration
from VGH-NYMU. They are as follows:
EEG-based BCI
Our goal is to develop a system that performs real-time EEG signal analysis in order to
generate commands for environmental control, communication, or even simple driving
instructions. There are many brain-computer interface (BCI) research groups in the world
studying how to provide a more immersed and intimate interaction between humans and
computers; Table 1 gives a partial listing.
26
Table 1. Brain-computer interfaces’ research groups in the world.
University
Researchers Year EEG-Signal Feed-back Country
University of Michigan
Biomedical Engineering
Department
Huggins et al.
1999
University Rochester
Department of Computer
Science
Bayliss and
Ballard
University of Technology
Ramoser et al.
Graz Institute of Biomedical
Guger et al.
Engineering
Oscillatory
Freq. Comp.
No
USA
1999 P300
No
USA
1999 Oscillatory
2000 Freq. Comp.
No
University of Tübingen
Institute of Medical
Psychology and Behavioral
Neurobiology
Kotchoubey
Kübler
Birbaumer
1997
University degli Studi Tor
Vergata
Babiloni et al.
Wadsworth Center
Wadsworth Center for
Laboratories and Research
Wolpaw et al.
Austria
Yes
Slow wave
Yes
Germany
1999
Oscillatory
Frequ. Comp.
No
Italy
1998
Oscillatory
Frequ. Comp.
Yes
USA
1999
Developing so-called “bionic” applications faces the current practical obstacle of maximum
information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends
on improvements in signal processing, translation algorithms, and user training. We wish to
provide disabled users with a more speedy and accurate BCI.
Real-time EEG signals, picked up from the scalp by array electrodes, carry the electrical
activity related to the response of brain. EEG signals consist of voltage changes of tens of
microvolts at frequencies ranging from below 1Hz to about 50 Hz. Such P300 signals can be
analyzed and quantified in the time domain, as voltage versus time, or in the frequency
domain, as voltage or power versus frequency. In the time domain, the form or magnitude of
the voltage change evoked by a stereotypical stimulus, referred to as an evoked potential or
evoked response, can serve as a command. For example, the evoked potential produced by
the flash of a certain letter can indicate whether the user wants to select that letter. In the
frequency domain, the amplitude of the EEG in a particular frequency band, referred to as a
rhythm, can also function as a command. For example, that amplitude can be used to
control movement of a cursor on a computer screen. Figure 5 summarizes the protocol of
BCI.
27
Figure 5. Flow diagram of major processing steps in the BCI strategy [37]
To develop a system that performs real-time EEG signal analysis to generate control
commands, the following tasks need to be performed:
1. Matching the BCI and its input to the user
Matching the user with his or her optimal BCI input features is essential if BCI is ever to
be broadly applied to the communication needs of users with different disabilities.
2. EEG signal analysis
In a practical BCI system, we need to maximize the signal-to-noise ratio of the EEG or
other measures that carry the user’s messages and commands. Autoregression (AR) model
parameter estimation is a useful method for describing EEG activity, and it may prove
invaluable in BCI application. When additive outlier contamination is present, a robust
maximum likelihood estimator can find utility. The method is based on a modified Kalman
filter, with wavelet transforms combined in a time-frequency analysis with a nonlinear scale.
3. BCI translation algorithm
A translation algorithm is a series of computations that transforms the BCI input features
derived by the signal processing stage into actual device control commands. Different BCIs
use different translation algorithms. An artificial neural network or a recursive
self-organization fuzzy neural network may work as a nonlinear transfer function between the
input features and output commands.
4. BCI technology application in locomotion
A relatively strong signal like P300 can be recognized via single-trial recognition
28
algorithmms to trigger commands in a virtual reality (VR) car. Alternatively, we can also
build a mental workload model of a driver based on the VR-car driving simulator (see Figure
6) by correlating the relationship between driver’s EEG signals and his/her reactions in
different driving sceneries.
[38]
Fig. 6.
Mental Workload Model of a driver based on VR-car driving simulator
Artificial-Eye BCI
The objective of this task is to develop a biological-inspired vision chip set, called a
“silicon retina,” which mimics the structure as well as the functions of a human eye. The
silicon retina can be used for artificial retina prostheses. Animal/human clinical trials will be
performed when the chip is ready.
A great research challenge exists for both IC designers and ophthalmologists to help the
patients suffering from blindness due to retinitis pigmentosa (RP) or age-related macular
degeneration (AMD). The challenge is to restore vision with artificial retinal prostheses
using implanted IC chips. In these patients, the photoreceptors, which convert photon inputs
to electrical signals, or possibly other cells like bipolar or horizontal cells in the retina, are
destroyed. But the ganglion cells in the retina remain healthy. The engineering goal is then to
use a functional semiconductor chip to replace the photoreceptors or other cells in the retina
region of patients, especially in the macular region.
There are two main approaches to implement artificial retina prostheses with implanted
chips. One approach is to use the photodiode array implanted at the bottom of the retina to
replace the retinal photoreceptors. The other approach is to use an extraocular module to
receive the images and an intraocular electrode array to stimulate healthy retina cells. The
extraocular module is composed of a camera, a suitable image processor, and the required
signal transmitter. The camera receives images and then the signal processor converts image
29
signals into neuromorphic types. The transmitter sends neuromorphic signals to the
intraocular electrode array to stimulate the remaining healthy ganglion cells to give vision.
The past few years have seen pushes to mimic biology in the development of VLSI
computational sensors for visual information processing. Major bottlenecks exist in
simulatinging the natural movements of a real eye, attaining high contrast and motion
sensitivity, minimizing the energy dissipation, and maintaining high signal-to-noise ratios.
Edge enhancements, large size, complex wiring, and real-time operations contribute to the
difficulties.
Silicon retina research has gained increasing attention because of the maturation of
analog VLSI technology. Mahowald’s silicon retina chip ranks among the first of several
semiconductor devices which implement a biological facet of vision on silicon. Improved
versions have since been proposed. One example is the Harvard-MIT collaboration project,
which started in 1988 with the ambitious long-term goal of proving that implantable
electronics can deliver a workable visual signal to the brain. However, the production of a
practical silicon retina based on the layered neural networks of the central nervous system
remains a challenging research problem. Most of the existing silicon retinas are based on
CMOS VLSI technology.
Professor Chung-Yu Wu proposed the world’s first BJT-based silicon retina. It has the
advantages of simplicity, no complex network wiring, and is easily implemented in a small
chip area. Recently, Professor Wu further suggested an improved device structure called the
neuron-bipolar junction transistor (vBJT). It is our hope that this device will allow a
practical solution to problem of the compact implementation of large-neighborhood cellular
neural networks (CNN) and retinal processing components.
Several major challenges remain before we have artificial retina prostheses with
implanted chips. First, a reliable power supply must be provided for long-term operation. An
external power supply through wires to the chip will damage the eyes amd is not an
acceptable solution. Second, retinal signals generation, transmission, and stimulation to
ganglion cells require more testing before suitable IC chips can be designed and implanted.
To fulfill the engineering goals of an artificial silicon retina, the following tasks must be
accomplished:
1. Commercial retina implants
The artificial retina under development is intended to replace an existing one. For model
experiments, we require a suitable commercial retina implant system.
2. Central nervous system (CNS) and vision models
We shall adopt the latest findings on CNS and vision science (e.g., CNS spatiotemporal
dynamics, visual attention mechanism) to understand the human visual system to help
30
develop our biology-inspired vision chip set. A recent study at Washington University shows
that a population of interacting neurons can sustain a wavelike activity that discriminates
among different geometric positions of the incoming stimulus. Varying stimuli in vision space
produce different waves in the visual cortex, suggesting that information about the stimulus is
encoded in the spatiotemporal dynamics of the cortical response. This new finding gives us a
hint on how to build the spatiotemporal and chaotic dynamics analysis power into our silicon
retina chip.
3. Perception Learning Loop
We shall develop an integrated computer vision system called Perception Learning Loop
(PLL) for object recognition based on the latest findings from vision science such as the
dual-process visual model and the active learning behavioral paradigm. Although the basic
idea of the two visual systems, the ventral and the dorsal, is far from novel, originating in the
late 1960s, several new findings of a detailed nature were obtained only recently. We shall
apply these concepts to construct our model. The dual-process approach inspires this research.
In turn, our research will elucidate the synergistic interactions between the two visual systems.
Active learning aids finding and memorizing the functional relationships between the applied
actions and the resulting changes in sensory information. Hence, the internal representation
contains chains of alternating traces in “motor” and “sensory” memories. We suggest that the
brain uses chains of “behavioral programs” in subconscious “behavioral recognition” when
the object is (assumed) known. The active learning behavioral paradigm and the dual-process
approach of the two ventral and dorsal visual systems form the brain-science theoretic
backbone of the proposed PLL model.
4. Silicon retina design and technologies
Our research on efficient physical structures for the implementation of the bionic silicon
retina functions or smart retinal processing will progress extensively toward nanoscale
devices or integration. Further research on large-neighborhood vBJT CNNs will be on the
CNN universal machine (CNNUM).
We propose a new BJT-based silicon retina (see Fig. 7) for animal and human
implantation to replace the neural circuit of the outer retina consisting of photoreceptors,
horizontal cells and bipolar cells. Two novel mechanisms will be used to achieve high quality.
One is a light-adaptive mechanism and the other is a noise compensation mechanism using
sample/hold circuits embedded in each pixel. Also, the new silicon retina shall require no
extra power supply, and be very compact for implantation (Fig. 8).
31
Figure 7. The BJT-base silicon retina.
retina.
Figure 8. The implantation of silicon
Artificial-Ear BCI
The goal here is to develop a coding strategy of cochlear implants for mandarin Chinese.
Although coding strategies of cochlear implants exist in the world, none of them were
specially designed for mandarin Chinese. In view of the pronunciation differences between
mandarin Chinese and English, this research can make significant contributions to the quality
of life of profoundly deaf people living in mandarin-Chinese speaking societies.
A cochlear implant is different from a hearing aid in that it provides profoundly deaf patients
with perceptions of speech by directly feeding electrical signals of the speech to the auditory
nerves in the human cochlea. A hearing aid merely magnifies the sounds and thus it is not
appropriate for deaf patients with impaired auditory nerves.
Cochlear implants consist of an implanted electrode array, a microphone, a speech
processor, a transmitter, and a receiver (Fig. 9). The electrode array (Fig. 10) and the receiver
are surgically implanted. In contrast, the microphone hangs over the ear and the transmitter is
attached to the scalp. The speech processor may be put in the pocket or integrated with the
microphone. Radio frequency signals link the transmitter and the receiver.
Figure 9. The electrode array [39].
Figure 10. Configuration of a
cochlear implant [39].
32
When acoustic sounds in real world are picked up by the microphone, the electrical
signals associated with the sounds are translated by the speech processor with a special
coding strategy. Coding strategies define the way in which the acoustic sounds are
transformed into electrical signals that can be understood by the brain. The speech processors
analyze the sounds and transform them. They divide speech into different frequency bands
defined by filters and determine the amplitude relationships of the sounds within the filters.
They also define where to send stimulation (tonotopic location) and how often to send the
stimulation (stimulation rate). The speech processors also define how much to send in order to
preserve amplitude relationships.
There are several coding strategies used by cochlear implant manufacturers in the world
(Table 2). The most popular coding strategy is continuous interleaved sampling (CIS). The
CIS strategy addresses the problem of channel interaction through the use of interleaved
non-simultaneous stimuli. Fig. 4 shows an example of 6 electrodes. Although the CIS strategy
can support high levels of open-set recognition, the information presented by this strategy is
limited to envelope variations of typically 400Hz
Table 2. Cochlear implant manufacturers in the world.
Company
Country
Cochlear (since
Australia
1983)
Advanced
Bionics
(since 1988)
Medical
Electronics
(since 1989)
MXM
AllHear
1987)
(since
Product
NUCLEUS 24
USA
Clarion CII
Austria
COMBI 40+
France
Digisonic CI
USA
AllHear OTH
33
Features
22 channels (25mm long)
14,400 pps
SPEAK, CIS and ACE
8 channels（16 electrodes）
91,000pps（82,500pps）
 SAS, MPS and CIS
12 channels
18,000 pps
CIS+
15 channels
122 to 7800Hz.
1 channel (6mm long)
Preamp
Filter
Band
BPF
1
envelope
Rect. /
BPF
1
LPF 1
Rect. /
LPF 1
Compressi Modulatio
oNonlinear
n
n
EL
map
1
Nonlinear
map
EL
6
Figure 12. Block diagram of major
processing steps in the CIS
strategy.
Figure 13. The appearance of
wearing a cochlear implant [39].
To fulfill our objective of developing a coding strategy for speech in mandarin Chinese to be
used in cochlear implants, we need to perform the following tasks:
1. Commercial cochlear implants
The speech processor under development is intended to replace an existing one. To be able to
conduct experiments, we require a suitable commercial cochlear implant system.
2. The features of mandarin Chinese
To improve speech perception and recognition, we need to understand better the typical
features of spoken mandarin Chinese for superior filtering designs.
3. Testing methods of speech recognition and coding strategies
Cooperation on these topics would require the collaboration of researchers and otologists.
4. Implementation of new speech processors
The main steps of any new coding strategy needs to be invented and implemented. The RF
section of the new speech processors could follow existing practices.
5. Testing efficacy of the device
Clinical trials would be conducted in hospitals with volunteer patients and suitable protocols.
34
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2002. High-resolution imaging of brain gene expression. Genome Res. 12:244-25.4
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2002. Functional neurogenesis in the adult hippocampus. Nature 415:1030-1034.
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Neuroci. 1:67-73.
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diseases: dreams and reality. Nat. Rev. Neurosci. 3:401-409.
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2000. Computational analysis of functional connectivity between areas of primate
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36. Calvin, W. H. 1996. The cerebral code. Published by MIT Press.
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39. http://www.bionicear.com/
37
Education Programs
Graduate Programs
The goal of the Neuroscience Graduate Programs is 1) to provide students the most
up-to-date knowledge and concepts of modern neuroscience, 2) to train students the skills to
solve problems in neuroscience, 3) to train students as independent and creative scientists.
The graduate programs will offer Master and PhD degrees in the area of Basic Neuroscience,
Theoretical and Computational Neuroscience, Neuroengineering, Brain Imaging and
Informatics, and Cognitive Neuroscience.
Interdisciplinary research programs are
encouraged. PhD students will do lab rotation in the first year to round out his or her choice
of research program. Through the design of entrance exams, students with physical science
or engineering backgrounds are especially encouraged to apply. A common core course will
be offered for the MS or PhD program. Students will be required to participate in graduate
seminars, in regular research colloquia and in Neuroscience frontier seminars. Electives will
be offered in the research areas of interest to the student. Because of distance constraints
between campuses, we will allow electives in the form of verbal and written tutorials.
Clinical Neuroscience Training Program
The goal of the Clinical Neuroscience Training Program is to attract physicians into the
field of modern neuroscience and to prepare them with the skills and knowledge required of
an effective researcher. Students will participate in the core course of the graduate program.
In addition, a problem-based-learning clinical neurology course will be offered with joint
participation of the basic research faculties. The three participating Veteran General
Hospitals will provide clinical training. Students will also participate in colloquia and in the
research activities of the programs of their choice.
Undergraduate Neuroscience Program
To attract beginners into neuroscience, we will also offer introductory courses to
undergraduate students with diverse backgrounds. The design of courses should have
special appeal to medical students who wish to participate in neuroscience research.
Summer Student Training Program and Workshops
We also plan to offer summer training programs and workshops for undergraduates to
38
encourage their participation in the various brain research programs.
Special instruction in
the various techniques employed in current neuroscience research will be designed for faculty
members, technicians, and students interested in learning such techniques.
Significance and Impact
The significance and impact for the establishment of Brain Research Center in the University
System of Taiwan is as follows:
1) It enables Taiwan to compete internationally in the frontier research in brain science.
2) It can serve as a model for multi-disciplinary research in Taiwan with the potential to
develop novel research paradigms.
3) The results of such multi-disciplinary endeavor can have interesting applications in
clinical as well as practical applications.
4) It will help the development of biotechnology industry in Taiwan.
Progress Evaluation
We suggest the following metrics to be used in the future evaluation of the accomplishments
of the Center:
1. Annual site visits by advisory board members, followed every three years by a written
evaluation.
2. Periodic independent scrutiny by a committee appointed by the Ministry of Education.
3. Annual written progress reports of on-going research projects submitted to the
Coordinator of the Program, with a copy to the Director of the Center.
Publications in
international prominent journals of relevant fields will be one of the key indices for successful
implementation of the research programs. So will be appropriate measures of scientific
impact.
39
4. For the teaching programs, course evaluations conducted each semester will serve as a
basic reference for individual courses. Similar questionnaires can be distributed to summer
school and workshop attendees. Evaluation of the effectiveness of a Program as a whole
will have to wait until there are a sufficient number of graduates who have passed through the
Program to do a meaningful post-graduation survey.
Budget
The first period (between 10.1.2002 and 12.31.2003) budget has been set at NT$120
millions by the Ministry of Education. The distribution of this fund will be based on the
scientific merit of the research proposals reviewed by a panel of experts. Since this fund is
to be used mostly for purchasing equipment as specified by the budget category it will be
used to set up the infrastructures necessary to start the brain research program.
Appendix
Advisory Board
Name
Mu-Ming Poo
Terrence Sejnowski
Martin Ingvar
Horace Lo
Ovid J.L. Tzeng
Che-Kun James Shen
Chung Y. Hsu
Jean C. Shih
Position
Professor of Department of Molecular & Cell BiologyUniversity
of California, Berkeley
Director of Computational Neurobiology Laboratory
The Salk Institute
Professor , Karolinska Hospital/Institute
Stark Professor and Department Head
Pharmacology Department, Medical School
University of Minnesota
Vice President
Academia Sinica
Director & Professor
Institute of Molecular Biology
Academia Sinica
President
Taipei Medical University
University Professor, Boyd and Elsie Welin Professor
Department of Molecular Pharmacology and Toxicology,
Pharmaceutical Sciences Center
Department of Cell and Neurobiology, Keck School of Medicine
University of Southern California
40
Steering Committee
There will be a Steering Committee to oversee the initial phase of operation of
BRC. The members of this committee will be composed of experts in the field of
neuroscience appointed by the UST Steering Committee.
Working Group of BRC
To facilitate the operation of BRC before the new Director is recruited the administrative
work will be carried out by a Working Group composed of faculty representatives from the
four campuses. Their names are listed below:
中央大學：蔣研發長偉寧、葉院長永烜、曾教授清秀、洪教授蘭
交通大學：張研發長仲儒、林進燈教授、毛仁淡教授、楊裕雄教授、林志
生教授
清華大學：張研發長石麟、吳院長文桂、張教授兗君、江教授安世
陽明大學：翟研發長建富、李院長德章、錢教授嘉韻、洪教授蘭、謝教
授仁俊、范教授明基
Collaboration Scholars
International
Thomas Curren (St. Jude Children’s Research Hospital)
Craig McGregor (SUNY, Stony Brook)
James Morgan (St. Jude Children Research Hospital)
Heidi Scrable (University of Virginia)
Joe Tsien (Princeton University)
National
National Cheng-Kung University
簡伯武 (Institute of Pharmacology, School of Medicine)
National Defense Medical Center
陶寶綠 (Institute of Pharmacology)
顏茂雄 (Institute of Pharmacology)
蔣永孝 (Dept. NeuroSurgery)
National Sun Yat-Sien University
陳慶鏗 (Center for Neuroscience)
崋瑜 (Center for Neuroscience)
National Taiwan University
符文美 (Institute of Pharmacology, School of Medicine)
41
郭鍾金 (Institute of Physiology, School of Medicine)
梁庚辰 (Institute of Psychology)
Academia Sinica
李小媛 (IBMS)
陳儀莊 (IBMS)
孫以瀚 (IMB)
簡正鼎 (IMB)
Participating Faculties
Participants of University System of Taiwan in the concerted effort for the Center for Brain
Science：
National Central University
Name
Title
Affiliation
Specialized Area of Research
Daisy Hung
Professor Institute Neural Science,
Cognitive Neuroscience
National Yang Ming University
Shing-Tsaan
Professor College of EE&CS
Distributed Computing, Tolerant Computing
Professor Dep. of Computer Science &
Learning Technology , Network Teaching ,
Huang
De-Hai Chan
Information Engineering
Guo-Dong Chen Associate Dep. of Computer Science &
Professor Information Engineering
Intelligent Agent
Mobile Learning Information System ,
Intelligent Learning Web Site , Database
System
Hwa-Wei Ko
Professor Department of Psychology,
National Chung Cheng
Instructional and Developmental
Psychology, Cognitive Development
University
Jonathan Lee
Professor Department of Computer
Science & Information
Software Engineering, Fuzzy Theory,
Intelligent Agent
Engineering
Jang-Ping Sheu Professor Department of Computer
Science & Information
Wireless Networks & Mobile Computing ,
Parallel Processing & Distributed Systems
Engineering
Chih-Wei Hue
Professor
Cognitive Psychology
Dep. of Psychology, National
Taiwan University
Po-Chang Chen Professor Dep. of Education, National
Taiwan Normal University
42
Program Design, Educational Sociology
Huo-Ming. Jiang Associate Dep. of Atmospheric Sciences
劉子鍵
Jie Chi Yang
Min-Sheng
Synoptic Meteorology, Atmospheric
Professor
Dynamics
Assistant Education Center of National
教育心理學、教育研究法、電腦在教育上
Professor Central University
之應用
Assistant Dep. of Computer Science &
Natural Language, Machine Translate,
Professor Information Engineering
Language Learning, Education System
Professor Dep. of Physic
Quantum measurement theory, Stochastic
Wang
mechanics
Chung-Ming Ko Professor Dep. of Physics
Astrophysics
Pik-Yin Lai
Professor Dep. of Physics
Statistical physics, Soft condensed matter
Zhen Ye
Professor Dep. of Physics
Condensed matter . Acoustic
Pei-Long Chen
Associate Dep. of Physics
Pattern formation, Complex system,
Professor
matter
Assistant Dep.t of Physics
Soft Condensed Matter Physics
C.-Y. David Lu
Soft
Professor
Hsuan-Yi Chen
Assistant Dep. of Physics
Soft condensed matter theory
Professor
Professor Dep. of Mathematics
Differential Equations、Matrix Computations
Cheng-Hsiung
Assistant Dep. of Mathematics
Differential Equations
Hsu
Professor
Jann-Long
Chern
Hwa-Long Gau Assistant Dep. of Mathematics
Functional Analysis
Professor
Suh-Yuh Yang
Assistant Dep. of Mathematics
Numerical Analysis, Differential Equations
Professor
National Chiao Tung University
Name
Title
Affiliation
Specialized Area of Research
Chin-Teng Lin
Professor Dep. of Electrical and Control
Human Computer Interface
Engineering
Kuu-Young
Young
Chi-Cheng Jou
Professor Dep. of Electrical and Control
Human Computer Interface
Engineering
Associate Dep. of Electrical and Control
Human Computer Interface
Professor Engineering
Jyh-Yeong
Associate Dep. of Electrical and Control
43
Human Computer Interface
Chang
Professor Engineering
鍾翊方
Assistant Dep. of Electrical and Control
Human Computer Interface
Professor Engineering
Pei-Chen Lo
Professor Dep. of Electrical and Control
Brainwave Dynamics
Engineering
Jin-Chern Chiou Professor Dep. of Electrical and Control
Bio-microelectromechanical systems
Engineering
Kai-Tai Song
Professor Dep. of Electrical and Control
Bio-microelectromechanical systems
Engineering
Lanrong Dung
Assistant Dep. of Electrical and Control
Artificial Eye
Professor Engineering
Yu-Tai Ching
Associate Dep. of Computer and
Brain Image Processing
Professor Information Science
Jen-Hui Chuang Professor Dep. of Computer and
Brain Image Processing
Information Science
Mingsian R. Bai Professor Dep. of Mechanical
Artificial Ear
Engineering
C. P. Tseng
Professor Dep. of Biological Science and
Stem Cell Therapy, Genetic Therapy
Technology
SIMON J.T.
MAO
Professor Dep. of Biological Science and
Stem Cell Therapy, Genetic Therapy
Technology
Chich-Sheng Lin Assistant Dep. of Biological Science and
Professor Technology
Comparative medicine, Gene therapy,
Gene chip
Yun-Liang Yang Assistant Dep. of Biological Science and
Genetic Expression, metabolism
Professor Technology
Hwei-Ling Peng Associate Dep. of Biological Science and
Genetic Expression, metabolism
Professor Technology
Hsien-Tai Chiu
Assistant Dept. of Biological Science &
Gene expression, metabolism
professor Technology
Cheng Chang
Professor Dept. of Biological Science &
Gene expression, metabolism
Technology
Yu-Shiung Yang Associate Dept. of Biological Science &
Protreome, enzyme
Professor Technology
Jenn-Kang
Hwang
Tiao-Yin Lin
Professor Dept. of Biological Science &
Protreome, bioinformation
Technology
Associate Dept. of Biological Science &
Professor Technology
44
Protreome, biophysics
Dung-Kuen Wu Assistant Dept. of Biological Science &
Protreome, directed evolution
professor Technology
Chiun-Jye Yuan Assistant Dept. of Biological Science &
Protreme, cell culture
professor Technology
Jing-Mu Yang
Assistant Dept. of Biological Science &
Protreome, bioinformation
professor Technology
National Tsing Hua University
Name
Title
Affiliation
Yen-Chung
Professor Dept. of Life Science
Specialized Area of Research
Neurophysiology, electrophysiology, cellular
Chang
biology (basic neuroscience)
Wei-Yuan Chow Professor Dept. of Life Science
Molecular neurobiology (basic neuroscience)
Ann-Shyn
Learning and memory of fruit fly, electron
Professor Dept. of Life Science
Chiang
microscope and confocal microscope (basic
neuroscience)
Pin-Jiang Lyn
Margaret
Associate Dept. of Life Science
Structure biology, bio-information, protein
Professor
engineering (basic neuroscience)
Associate Dept. of Life Science
Molecular biology (basic neuroscience)
Dah-Tsyr Chang Professor
Jui-Chou Hsu
Yuh-Ju Sun
Associate Dept. of Life Science
Developmental molecular biology of fly (basic
Professor
neuroscience)
Assistant
Dept. of Life Science
Professor
Structure biology, X-ray diffraction crystallography,
proteinic chemistry, computer simulation (basic
neuroscience)
Chuan-Jing Jiau Assistant
Dept. of Life Science
Professor
Shr-Rung Yeh
Assistant
biology (basic neuroscience)
Dept. of Life Science
Professor
Hua –Wen Fu
Assistant
Neurophysiology, electrophysiology, cellular
Neurophysiology, electrophysiology, cellular
biology (basic neuroscience)
Dept. of Life Science
Cellular biology (basic neuroscience)
Professor
Von-Wen Soo
Professor Dept. of Computer
Science
Artificial intelligence, Machine learning, Intelligent
agent, acquisition of natural language, biomedical
application (brain information)
Chuan-Yi Tang Professor Dept. of Computer
Bioinformation (brain information)
Science
45
Chung-Chin Lu Professor Dept. of Computer
Bioinformation (brain information)
Science
Shyang Chang
Professor Dept. of Computer
Biosignal (brian information)
Science
Chinfa Lien
Professor Graduate Institute of
Linguistic
H. Samuel Wang Professor Dept. of Foreign
Language
方聖平
professor Department of foreign
Chang
趙之振
(cognitive neuroscience)
Experimental phonology, psycholinguistics
(cognitive neuroscience)
professor Department of Chinese Cognitive psychology、psychological
language and literature
Yueh-chin
Semantics, morphology, historical linguistics
language and literature
Associated Institute of Philosophy
phonology(cognitive neuroscience)
Experimental phonology、phonology(cognitive
neuroscience)
知識論、語言哲學、美國哲學(認知神經科學)
professor
吳瑞媛
Associated Institute of Philosophy
心靈哲學、心理學哲學(認知神經科學)
professor
蘇宜如
Assistant
外國語文系
心理語言學(認知神經科學)
professor
National Yang-Ming University
Name
Title
Affiliation
Mau-song
Professor School of medicine
Specialized Area of Research
Internal medicine
Chang
Ming-Ta Hsu
Professor The institute of
Genetic science
biochemistry, NYMU
Low-Tone Ho
Professor School of medicine
Daisy L. Hung
Professor The institute of
Endocrinology
Cognitive neuroscience, neurapsychology
neuroscience, NYMU
Alice Chien
Chang
Synthia Sun
Professor The institute of
Molecular, cellular and developmental
neuroscience, NYMU
neurobiology
Professor The institute of
Molecular and Cellular Biology
neuroscience, NYMU
Tsai-Hsien Chiu Professor The institute of physiology,
Neurophysiology
NYMU
Fung-Fang Chen Professor The institute of
Molecular and cellular bioscience
biochemistry, NYMU
46
Nan-chi chang
Professor The institute of
microbiology and
Molecular and cellular bioscience
immunology
Wynn Pan
Professor The institute of
Neuropharmacology
pharmacology
Lung-Sen Kao
Professor Dep. of Life Science
Liang-Shong
Professor School of medicine
Molecular and cellular bioscience
neurosurgery
Lee
Shiu-chih Liu
Professor School of medicine
neuromedicine
Mu-Huo Ten
Professor School of medicine
Radiology
Jeun-shenn Lee Professor The institute of radiological
Biomedical engineering
science
Huihua Chiang
Professor The institute of biomedical
Signal processing, biophotonics
engineering
Woei-chyn chu
Professor The institute of biomedical
Biomedical engineering
engineering
Cheng-Kung
Professor The institute of biomedical
orthopaedic
cheng
Chien chou
engineering
Professor The institute of radiological
Radiation physics, biophotonics
science
Jen-Chuen Hsieh Associate The institute of neuroscience Brain science, clinical medicine, painscience,
Professor
Ren-Xian Liu
anesthesiology, functional brain imagin
Associate
Faculty of Medicine
Nuclear Medicine
Faculty of Medicine
Psychiatry
Professor
Associate
Tung-ping Su
Professor
Associate
Neurosurgery
Li-Tung Huang Professor Faculty of Medicine
Associate
Neurosurgery, Neural Chemistry, Cell Biology
Hung-Chih Chen Professor Faculty of Medicine
Jiun-An Wu
Associate
Neurology, Electromyography, Evoked
Professor Faculty of Medicine
Potential
Associate
Neurosurgery
Hung-Chi Cheng Professor Faculty of Medicine
Associate
Neural Radiology
Wan-Yu Kau
Professor Faculty of Medicine
47
Ying-Hsueh
Associate
Chen
Professor Faculty of Medicine
Psychiatry
Associate
Liang-Chih Wu
Biomedical Engineering, Information
Faculty of Medicine
Professor
Engineering
Associate
Mei-Ling Tsao
Faculty of Medicine
Radiology, Magnetic Resonance Image,
Professor
Associate
Meei-Ling Tsaur
Molecular Cell Neurobiology,
Institute of Neuroscience
Professor
Electrophysiology
Associate
Huey-Jen Tsay
Institute of Neuroscience
Molecular Cell Neurobiology
Professor
Associate
Fu-Chin Liu
Molecular Cell Neurobiology, Developmental
Institute of Neuroscience
Professor
Neurobiology
Associate
Yun-Chia Chou
Institute of Physiology
Molecular Cell Neurobiology
Professor
Associate Department of
Jyh-Fei Liao
Neural pharmacology
Professor Pharmacology
Associate
Mei-Yu Chen
Department of Biochemistry Molecular Cell Biology
Professor
Associate
Ming-Ji Fann
Molecular Cell Neurobiology, Developmental
Faculty of Life Science
Professor
Neurobiology
Associate Institute of
Wey-Jing Lin
Molecular Cell Neurobiology
Professor Biopharmaceutical Sciences
Associate Institute of Biomedical
Yin Chang
Biophotonic Engineering
Professor Engineering
Associate Medical Radiation
Jyh-Cheng Chen
Radiology, Nuclear Medicine
Professor Technology
Associate Medical Radiation
Yi-Hsuan Kao
Radiology, Magnetic Resonance Image,
Professor Technology
Institute of Health
Associate
Der-Ming Liou
Informatics and Decision
Data warehouse
Professor
Making
Assistant
Tzu-Cheng Yeh
Radiology, Magnetic Resonance Image, Cell
Faculty of Medicine
Professor
Biology, Functional MRI
Brain Information Science, Brain Image
Assistant
Institute of Radiological
Yu-Te Wu
Science, Brain Rhythm Recognition, Brain
Professor Sciences
Computer Interface
48
Assistant
Department of
Chun-Cheng Yen
Neural pharmacology
Professor Pharmacology
Assistant
Yung-Yang Lin
Faculty of Medicine
Neurology, Magnetic Resonance Image
Professor
Hsiang-Yu You
Instructor Faculty of Medicine
Neurology
Clinical
Kuang-Kan Liao Assistant
Faculty of Medicine
Neurology
Neuroscience Research
Biomedical Engineering, Information
Professor
Assistant
Li-Fen Chen
Researcher Center
Engineering
49