Download - Team 3: Neuroinformatics
Neuronformatics and Emerging Technologies
February 19, 2007
Team 3 - Tensa ZangetsuChiranjeev BordoloiKoch GeevargheseRomerl ElizesYonesy 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 age-related 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 neuro-genetic 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)– but it is not widely shared– potential value of it’s scale is not being realized
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:– digital library, associated repository, warehouse
Five basic workflows:– submission, retrieval, migration, definition, exploration
Overview Of Proposed System: 5 Processes
Warehouse
Digital Library
Submission1
Retrieval
2
Exploration- brain attributes- visualization- spatial reasoning- content-based retrieval
4
Migration3
AtlasGeneration
5
Data Archive Metadata Repositorygender
racetest score ....
Features Probabilistic AtlasesVolume
= 3.2
partitions
Process 1: Submission To Library
Data Archive (structural MRI
partition)
Metadata Repository
Mapping Datasurveytest (1)test (2)
etc.
core images
non-core
T1 T2 PD
tissue-labeled, scalped, normalized
noise (motion) corrected
reconstructed
race gender age test scores genetic info scan conditions etc....
Associated Metadata
Data Validation Tests
* (256 x 256 x 170 voxel matrix)
*
Process 2: Retrieval From Library
LRR*
* (Library Retrieval Request)
Selected Data
Apply Access Policy
Query
Data Archive (structural MRI
partition)Repository
core images
non-core
T1 T2 PD
tissue-labeled, scalped, normalized
noise (motion) corrected
reconstructed
race gender age test scores genetic info etc....
*
Process 3: Migration Into Warehouse
IndividualBrain
Object*: Labeled BrainVolume
Voxel-Label Anatomic Regions
Extract Features AndAnnotate Structure Hierarchy
StructuralBrain Hierarchy
FeatureAttributes
Warp To A Standard Space,(Generate Deformation Field)
Digital Library
Data WarehouseDeformation
Field
core images
+ +
T1 / tissue labeledbrain volume
* (One instance percore scanned brain)
Repository
ReplicateAssociatedMetadata
Process 4: Exploration Of Warehouse
Queries
SpatialReasoning
VisualizationContent-based
Retrieval“Extended”
Feature
Data Warehouse
Labeled BrainVolume Structural
Brain Hierarchy
FeatureAttributes
DeformationField
+ +IndividualBrain
Objects
Answers
StandardAttribute/Value
Describe Query
Optimization
OptionalLRR
QueryInterface
Process 5: Atlas Definition Within Warehouse
Data Warehouse
Labeled Probabilistic
Brain Volume
StructuralBrain Hierarchy
FeatureAttributes
Deformation Field OfPopulation CenterTo Standard Space
+ +CompositeBrain
Objects:
AtlasDefinition
gender = male
diseasestate
genotype
feature (e.g. hippocampalvolume size)
etc (extensible)
25 < age < 30
“fact table”
DescribeSubpopulationCharacteristics
Process 4 (revisited): Exploration (Atlases)
Queries
SpatialReasoning
PopulationComparison
Data Warehouse
Labeled Probabilistic
Brain Volume
StructuralBrain Hierarchy
FeatureAttributes
Deformation Field OfPopulation CenterTo Standard Space
+ +AtlasData
Model:
Answers
StandardAttribute/Value
Describe Query
Optimization
QueryInterface
Visualization
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 neuromorphic-
procedural 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