Transcript CMM for Web Development

Neuronformatics and Emerging
Technologies
February 19, 2007
Team 3 - Tensa Zangetsu
Chiranjeev Bordoloi
Koch Geevarghese
Romerl Elizes
Yonesy Nunez
Agenda







Introduction
Definitions
Background
Current Work and Experiments
Current Support
Links
References
Introduction




Understanding the human nervous system is one of
the greatest challenges of 21st century science
The topic we will focus on is neuroinformatics
The goal for this presentation is a general overview
of neuroinformatics
Brain informatics is a subset of neuroinformatics, but
most of the literature in neuroinformatics focuses on
the brain
Definitions
Neuroscience
 Field devoted to the scientific study of the
nervous system
 Disciplines include: structure, function,
development, genetics, biochemistry,
pharmacology, and pathology.
 Focuses on the investigation of the brain and
mind.
Definitions
Neuroinformatics
 intersection of neuroscience and information science.
 many points of contact between the neuroscience-related life-sciences
and the information sciences and related disciplines:
–
–

Life sciences: neuroscience, neurology, psychology, linguistics, biology,
chemistry, physics, etc.
Information sciences: computer science, mathematics, statistics, physics,
electrical engineering, robotics, etc.
Goals of neuroinformatics:
–
–
–
developing and applying computational methods to the study of brain and
behavior
applying advanced IT methods to deal with the huge quantity and great
complexity of neuroscientific data
exploiting our insights into the principles underlying brain function to
develop new IT technologies.
Background
Neuroscience
 In Egyptian times, the heart, not the brain, was classified as the
seat of intelligence.
 Hippocrates was the first to indicate that the brain was the seat
of intelligence.
 Roman physician, Galen, further backed this by providing
evidence that Roman gladiators lost their mental faculties when
they sustained severe damage to their brains.
 Further studies of the brain was stagnant until the invention of
the microscope. The work at first focused on the individual
neurons.
Background
Neuroscience
 Camillo Golgi in the 1890’s silver chromate salt to
reveal intricate structures of single neurons
 Santiago Ramon y Cajal used Golgi’s information to
develop the neuron doctrine. The hypothesis is that
the functional unit of the brain is the neuron.
 Santiago Ramon y Cajal and Camillo Golgi received
the Nobel Prize in 1906 for Physiology for their work
on the structure of the nervous system
Background
Neuroinformatics
 Neuroinformatics is formally established by the
National Institute of Mental Health in 1993 under the
Human Brain Project.
 In the Bioinformatics realm, the Institute for Genomic
Research was established in 1992 in Rockville,
Maryland.
 The exponential growth of information technologies
especially the Internet in the 1990’s has prompted
the growth of neuroinformatics.
Background
Neuroinformatics
 By 2000, 40 web-based projects with digital databases were
steered by the Human Brain Project
 This work impacts molecular biology and cellular physiology
 Society of Neuroscience is formally established in 2003 to
prompt the development and popularization of neuroscience to
the world community.
 In 2004, Program in International Neuroinformatics was
established by 16 countries and the EU commission to promote
international collaboration, dialogue, and support mechanisms
for neuroscience application research.
Current Work and Experiments

This section will focus on:
–
–
–
–
–
Posit Science
Brain-Gene Ontology Project
Human Brain Mapping
Brain Computer Interface
Snapshot of published papers in Neuroinformatics
Current Work and Experiments
Posit Science
 Dr. Michael Merzenich and Dr. Henry
Mahncke with other scientists developed a
hypothesis designed to rejuvenate the brain’s
plasticity.
 Posit Science Inc. was founded in 2003 in
San Francisco to develop a software
program that could test and validate these
neuroscientists’ hypothesis.
Current Work and Experiments
Posit Science
 The connections in the brain are plastic, meaning
that when we learn something, the properties of our
synapses and other neural circuits change, thus
improving their processing speed and the fidelity of
the information encoded.
 As we age, this natural learning process starts to
deteriorate. This slowing is at the root of some agerelated memory loss.
 Recent research has shown that reading the
newspaper or doing crosswords can help keep older
people mentally fit.
Current Work and Experiments
Posit Science
 Dr. Merzenich research study involves the subjects being asked
questions from recorded narratives.
 The narratives are played slowly at first and progressively become
faster.
 The narratives are easy at first and progressively become difficult.
 The narratives are delivered via a computer-based training module
with minimal interaction with researchers.
 The level of challenge is crucial component in triggering brain
plasticity.
 The study was conducted with 95 older people aged 63-94.
 The exercises were: speed of processing, spatial syllable match
memory, forward word recognition span, working memory, and
narrative memory.
 The goal was for the subjects to train one hour a day for eight weeks.
Current Work and Experiments
Posit Science
 Results
–
–
–
–
People who trained the full eight weeks significantly improved their
scores on memory tests.
People who progressed to the most difficult levels of the narratives
showed the greatest improvements.
Majority of participants gained ten neurocognitive years.
Exercise results:





Speed of Processing – 93% of participants improved by 41%
Spatial syllable match memory – 77% of participants improved by 10%
Forward word recognition span – 91% of participants improved by
18%
Working memory – 80% of participants improved by 13%
Narrative memory – 91% of participants improved by 18%
Current Work and Experiments
Posit Science
 Other disciplines affected: gerontology.
 Papers derived from this work:
–
–
Brain plasticity and functional losses in the aged:
scientific bases for a novel intervention
Memory enhancement in healthy older adults
using a brain plasticity-based training program: A
randomized, controlled study
Current Work and Experiments
Brain-Gene Ontology
 Nikola Kasabov, Vishal Jain, and other authors from Auckland
University of Technology in New Zealand undertook the Brain-Gene
Ontology (BGO) Project: mapping the relationship between the brain
and the genes.
 The goals of the BGO project, through a software application, are to
find if these relationships can be used for further investigations in
neuroinformatics and bioinformatics.
 A side goal of the BGO project is that it can be used as a training tool
for researchers and students.
 The project was presented in the Sixth Annual Conference of Hybrid
Intelligent Systems in December 2006 under the title: “Brain-Gene
Ontology: Integrating Bioinformatics and Neuroinformatics Data,
Information and Knowledge to Enable Discoveries.”
Current Work and Experiments
Brain-Gene Ontology
 BGO application consists of three parts:
–
–
–
Brain organization and function – contains information about
neurons, synapses and electroencephalogram (EEG) data
for normal and epileptic brain states.
Gene regulatory network – contains sections on neurogenetic processing, gene expression regulation, protein
synthesis, and abstract GRN.
Simulation modeling – contains sections on computational
neurogenetic modeling (CNGM), evolutionary computation,
evolving connectionist systems, spiking neural network,
simulation tools, and CNGM results
Snapshot of the BGO neuro-genetic simulation tool
Snapshot of the BGO detail showing relations between genes, proteins, neuronal functions and diseases
Neurons entering the brain: simulated activity
Snapshot signal propagation in neurons of the brain
Current Work and Experiments
Mitre Corporation – Human Brain Mapping
 Human brain mapping data (MRI, fMRI, Cryosection, EEG, etc.) is
rapidly accumulating worldwide (many terabytes)
–
–



Significant need for an appropriate information infrastructure.
Our goal:
“The goal of this proposal is to enable the world-wide
exploration, analysis, and dissemination of the growing
corpus of human brain mapping information.”
Three basic architecture components:
–

but it is not widely shared
potential value of it’s scale is not being realized
digital library, associated repository, warehouse
Five basic workflows:
–
submission, retrieval, migration, definition, exploration
Overview Of Proposed System: 5 Processes
4
Warehouse
Exploration
- brain attributes
- visualization
- spatial reasoning
- content-based
retrieval
Features
Probabilistic
Atlases
Volume
= 3.2
3
Migration
Digital Library
Retrieval
Data Archive
partitions
2
Metadata
Repository
gender
race
test score ....
1
Submission
5
Atlas
Generation
Process 1: Submission To Library
Data Archive
noncore
core
images
(structural MRI
partition)
race
gender
age
test scores
genetic info
scan conditions
etc....
tissue-labeled,
scalped, normalized
noise (motion)
corrected
*
reconstructed
T1
T2
Metadata
Repository
PD
* (256 x 256 x 170 voxel matrix)
Data Validation Tests
Mapping Data
Associated Metadata
survey
test (1)
test (2)
etc.
Process 2: Retrieval From Library
Query
Selected Data
Data Archive
(structural MRI
partition)
Apply Access Policy
noncore
core
images
Repository
LRR*
tissue-labeled,
scalped, normalized
noise (motion)
corrected
*
reconstructed
T1
T2
PD
race
gender
age
test scores
genetic info
etc....
* (Library Retrieval Request)
Process 3: Migration Into Warehouse
Individual
Brain
Object*:
+
Labeled Brain
Volume
* (One instance per
core scanned brain)
Deformation
Field
+
Feature
Attributes
Structural
Brain Hierarchy
Data
Warehouse
Extract Features And
Annotate Structure Hierarchy
Replicate
Associated
Metadata
Voxel-Label Anatomic Regions
Warp To A Standard Space,
(Generate Deformation Field)
core images
T1 / tissue labeled
brain volume
Digital
Library
Repository
Process 4: Exploration Of Warehouse
Describe Query
Spatial
Reasoning
Visualization
Standard
Attribute/Value
Data
Warehouse
Content-based
Retrieval
“Extended”
Feature
Query
Interface
Queries
Answers
Optimization
Individual
Brain
Objects
+
Labeled Brain
Volume
Deformation
Field
+
Structural
Brain Hierarchy
Feature
Attributes
Optional
LRR
Process 5: Atlas Definition Within Warehouse
genotype
gender = male
25 < age < 30
“fact
table”
disease
state
Describe
Subpopulation
Characteristics
etc (extensible)
feature (e.g. hippocampal
volume size)
Atlas
Definition
Data Warehouse
Composite
Brain
Objects:
+
+
Deformation Field Of
Labeled
Structural
Population Center
Probabilistic
Brain
Hierarchy
To Standard Space
Brain Volume
Feature
Attributes
Process 4 (revisited): Exploration (Atlases)
Describe Query
Spatial
Reasoning
Visualization
Population
Comparison
Standard
Attribute/Value
Query
Interface
Queries
Optimization
Data
Warehouse
Atlas
Data
Model:
Answers
+
+
Deformation Field Of
Labeled
Structural
Population Center
Probabilistic
To Standard Space Brain Hierarchy
Brain Volume
Feature
Attributes
Current Work and Experiment
Brain Computer Interface
 Nick Chisolm is a man who became paralyzed in a rugby
accident at age 23 in 1998.
 He suffers from locked-in syndrome which is a condition where
you have lost almost all physical motion in the body but not the
brain. The brain is still working at 100% efficiency.
 Nick only had physical movement with his eyes. When he
needed to compose a sentence or word, he had to use his eyes
to indicate the validity of a letter of a word.
 This rehabilitation process is time consuming and extremely
frustrating for the victim.
 His suffering prompted the work on BCI for paralyzed people.
Introduction





Brain-Computer Interface (BCI) is a device which
allows the human to control electronic devices just
by thinking.
Current BCIs are based on Electroencephalogram
(EEG) .
Peirre Glorr and Hans Berger discovered EEG in
1969.
First BCI was built by Vidal in 1973
For more than 2 decades no real development was
done in BCIs, mostly waiting for the technology to
catch up.
BCI- How does it Works?
–
–
–
–
–
Amplify the EEG signals.
Digitize the signals.
Elimination of unwanted signals
Other necessary manipulation.
Translate the signals to computer commands.
BCI- Goes Wireless


Wearable or Wireless BCI is developed
because of the advanced communication
devices.
Wireless BCI interact with a PDA equipped
with is the best visualization.
- Bluetooth – for portability
–
–
GPS -- to be aware of the environment
WLAN 802.11b– For access to the processing
power in Office/Home.
BCI- Wireless Visualization
BCI- Current Issues


BCI is interested only in EEG wavelets from the
Cerebrum (Thinking Center) .Eliminating other
wavelets like Electrooculogram (EOG) ,
Electromaygram (EMG), etc. is one issue.
Other Problems are:
–
–
–
–
–
Slow user response times
Excessive error rates
High cost
Actual appearance
Long initial training periods
Current Work and Experiments
Brain Computer Interface
 Paper from K. Navarro: “Wearable, Wireless Brain Computer
Interfaces In Augmented Reality Environments”
–
–
–
Current BCI does not currently follow design principles of the
Human Computer Interaction (HCI) discipline. BCI should use this
knowledge and follow this “pattern language.”
Author proposes the use of Augmented Reality Environments (AR)
for the BCI wearer. Augmented Reality systems enhance the real
world by superimposing information onto it. Ex: pair of glasses with
information overlaid on the screen.
Problem with making it reality: Developing a BCI for an AR
environment addresses a specific problem. The goal of the BCI is
to work in a highly changing environment.
Current Work and Experiments
Brain Computer Interface
 Dr. Jonathan Wolpow, Chief of Laboratory of
Nervous Systems Disorders in NYS Department of
Health: Wadsworth Center spearheads an
extraordinary BCI initiative.
 Dr. Scott Mackler is one of his success stories. Dr.
Mackler suffers from progressive neurodegenerative
disease. He lost all movement in 1999.
 With the help of Wolpow’s innovative approaches to
BCI implementation, Dr. Mackler still goes to work.
Current Work and Experiments
Published papers from the Institute of Neuroinformatics for 2007:
 Fast sensory motor control based on event-based neuromorphicprocedural systems
 The role of first and second order stimulus features of human overt
attention
 Modulation of synchrony without changes in firing rates
 Sleep-related spike bursts in HVC are driven by the nucleus
interface of the nidopallium
 Time and space are complementary in encoding dimensions in the
moth antennal lobe.
 Gamma range cortico-muscular coherence during dynamic force
output
 Implementing homeostatic plasticity in VLSI networks of spiking
neurons
Current Support
Human Brain Project
 Sponsored by the National Institute of Mental Health
of the National Institutes of Health
 Established in 1993 to support the research efforts in
neuroinformatics.
 Find new ways in spearheading neuroinformatics
research
 Develop informatics tools and resources for
neuroscience.
Current Support
Human Brain Project - Agenda of Annual Meeting – April 24, 2006
 Current Initiatives:
–
–
–

Improving Image Analysis Tools
Create physiological data and exploit using simulation
Creation of ASTYNAX: A pilot exploration of web technology
Problems with Data gathering:
–
Data



–
Data heterogeneity
Lack of data standards
Cultural gap requires paradigm shift
Practice



Few repositories available for willing stakeholders
Information sparseness
Lack of Incentive
Current Support
Insititute of Neuroinformatics
 Established in 1995 by the University of Zurich
 States that $1 trillion dollars is spent on neuroinformatics mosty
on communications, processing, and information management.
Creating autonomous intelligent systems is slow.
 Projects pursued within the institute are:
–
–
–
–
–
Behavior and Learning in Intelligent Autonomous Systems
Representation and Sensory Motor Integration
Neuronal Architectures and Computation
Neuromorphic Chips and Systems
Neurotechnologies
Current Support
Computational Neuroscience/Neuroinformatics
 Aims to unravel the complex structure-function relationships of
the brain at all levels from molecular to behavioral in an
integrative effort with many scientific disciplines.
 Based in Europe, the organization is one of the primary
sponsors in conferences geared toward computational
informatics. Some of these conferences are in United States
and Canada as well.
–
–
–
Sixteenth Annual Computational Neuroscience Meeting CNS,
Toronto, Canada – July 2007
MBX – Special Topic Courses – Neuroinformatics, Wood
Holes, MA – August 2006
Tenth Annual Conference on Cognitive and Neural Systems,
Boston MA – May 2006
Current Support
NYS Department of Health: Wadsworth Center
 Under Dr. Jonathan Wolpow’s supervision, are working on bring
the BCI technology into home use.
 Streamlined version of the Wadsworth BCI consists of:
–
–
–
–


laptop computer
portable amplifier
breathable cap which contains just 8 electrodes, down from the
original 64
currently about $4,000, but will price will drop as technology
improves
Dr. Wolpow estimates that 70-80% with severe disabilities could
use the Wadsworth BCI System.
Heavy funding from NIH for the next few years.
Links
•
•
•
•





“Brain-Computer Interfaces Come Home.” National Institutes of Health:
National Institute of Biomedical Imaging and Bioengineering. November 28,
2006. http://www.nibib.nih.gov/HealthEdu/PubsFeatures/eAdvances/28Nov06
“The Brain Computer Interface with Natasha Mitchell.” AllInTheMind, ABC
National Radio, Austraila. December 2, 2006.
http://abc.net.au/rn/allinthemind/stories/2006/1799619.htm
Computational Neuroscience/Neuroinformatics.
http://www.hirnforschung.net/cneuro/
The Human Brain Project. National Institutes of Health: National Institute of
Mental Health. http://www.nimh.nih.gov/neuroinformatics/
Institute of Neuroinformatics. University of Zurich. http://www.ini.unizh.ch/public/
Mitre Corporation : Neuroinformatics website.
http://neuroinformatics.mitre.org/index.html
Neuroinformatics. Wiki site. http://en.wikipedia.org/wiki/Neuroinformatics
Neuroscience. Wiki site. http://en.wikipedia.org/wiki/Neuroscience
Wadsworth Center: New York State Department of Health. Home page.
http://www.wadsworth.org/index.html
References







N. Kasabov, V. Jain, P. Gottgtroy, L. Benuskova, F. Joseph. “Brain-Gene Ontology: Integrating
Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries.”
Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (HIS'06), pp. 13.
December 2006.
H. Mahnke, A Bronstone, MM Merzenich. “Brain plasticity and functional losses in the aged: scientific
bases for a novel intervention.” Journal of Progress in Brain Research. Volume 157. p. 81-109. 2006
H. Mahnke, B. Connor, J. Appelman, O. Ahsanuddin, J. Hardy, R. Wood, N. Joyce, T. Boniske, S. Atkins,
M. Merzenich. “Memory enhancement in healthy older adults using a brain plasticity-based training
program: A randomized, controlled study.” Procceedings of the National Academy of Sciences. August 23,
2006.
K. Navarro. “Wearable, wireless brain computer interfaces in augmented reality environments.”
Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04)
Volume 2, p. 643. April 2004
E. Singer. “Exercising the Brain: Innovative training software could turn back the clock on aging brains.”
Technology Review, Massachusetts Institute of Technology, Cambridge, MA. November 21, 2005
Wearable, Wireless Brain Computer Interfaces In Augmented Reality Environments. By Karla Felix
Navarro, University of Technology, Sydney IEEE 2004
P300 Detection for Brain-Computer Interface from Electroencephalogram Contaminated by
Electrooculogram. By Motoki Sakai, Hiroyuki Ishita, Yuuki Ohshiba, Wenxi Chen, and Daining Wei
Graduate School of Computer Science and Engineering, The University of Aizu,
Ikki-machi, Aizu- Wakamatsu City, Fukushima 965-8580, Japan IEEE 2006