Human Brain Simulation for Robotic Applications
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Human Brain Simulation for Robotic Applications was presented by Dr. P.S. Jagadeesh Kumar of Harvard University. The presentation discussed modelling the human brain to control robots, including how neurons connect and transmit signals, different types of brain-computer interfaces, and potential robotic applications like prosthetics and gaming. While BCI research offers advantages like movement restoration for the disabled, current technology is still crude and ethical issues remain as the field develops.
Human Brain Simulation for Robotic Applications
- 1. Human Brain Simulation for Robotic Applications Prepared and Presented by Dr.P.S.Jagadeesh Kumar, Research Scientist, Harvard University, Cambridge, United States
- 2. Introduction • Human Brain simulation is the concept of creating a functioning computer model of a human brain or part of a brain. • Modelling a brain (or brain subsystem) involves both modelling neurons' electrical and bulk chemical properties. • The connectome is extremely complex, and its detailed wiring is not yet understood.
- 3. Basic block diagram of a Brain Computer Interaction (BCI)
- 4. How the brain turns thoughts into action ? • The brain is full of neurons; these neurons are connected to each other by dendrites and axons. • Your neurons - as you think about anything or do anything - are at work. • Your neurons connect with each other to form a super highway for nerve impulses to travel from neuron to neuron to produce thought, hearing, speech, or movement. • If you have an itch and you reach to scratch it; you received a stimulus (an itch) and reacted in response to the stimulus by scratching. • The electrical signals that generated the thought and action travel at a rate of about 250 feet per second or faster, in some cases.
- 6. BCI Model
- 7. Interface The easiest and least non-invasive method is a set of electrodes -- a device known as an electroencephalograph (EEG) -- attached to the scalp. The electrodes can read brain signals. To get a higher-resolution signal, scientists can implant electrodes directly into the gray matter of the brain itself, or on the surface of the brain, beneath the skull.
- 8. Basic Mechanism • Wires from each electrode transmit their measurements to a computer. • The electrodes measure minute differences in the voltage between neurons. • The signal is then amplified and filtered. • The computer produces a graph showing the readings from each electrode. Digital EEG
- 11. Invasive BCIs • Invasive BCIs are implanted directly into the grey matter of the brain by neurosurgery. • As they rest in the grey matter, invasive devices produce the highest quality signals of BCI devices. • But are prone to scar tissue build-up, causing the signal to become weaker or even lost as the body reacts to a foreign object in the brain. BrainGate Neural Interface System
- 13. Partially Invasive • It is another brain signal reading process which is applied to the inside the skull but outside the grey matter. • Electrocorticography(ECoG) is the example of partially invasive BCI. • An electrocorticograph (ECoG) records the activity of the brain inside the skull, but from the surface of the membranes that protect it. • An electrode Grid is being implanted by surgical incision.
- 14. Non-Invasive It is the most useful neuron signal imaging method which is applied to the outside of the skull, just applied on the scalp. Techniques • Electroencephalography (EEG) • Magnetoencephalography(MEG) • functional Magnetic Resonance Imaging (fMRI)
- 15. Electroencephalography EEG In conventional scalp EEG, the recording is obtained by placing electrodes on the scalp with a conductive gel or paste, usually after preparing the scalp area by light abrasion to reduce impedance due to dead skin cells. Many systems typically use electrodes, each of which is attached to an individual wire. Magnetoencephalography (MEG) MEG detects the tiny magnetic fields created as individual neurons "fire" within the brain. It can pinpoint the active region with a millimeter, and can follow the movement of brain activity as it travels from region to region within the brain.
- 16. Functional Magnetic Resonance Imaging fMRI • It exploits the changes in the magnetic properties of hemoglobin as it carries oxygen. • Activation of a part of the brain increases oxygen levels there increasing the ratio of oxyhemoglobin to deoxyhemoglobin.
- 17. Robotic Applications • Provide disabled people with communication, environment control, and movement restoration. • Provide enhanced control of devices such as wheelchairs, vehicles, or assistance robots for people with disabilities. • Provide additional channel of control in computer games. • Monitor attention in long-distance drivers or aircraft pilots, send out alert and warning for aircraft pilots.
- 18. • Control robots that function in dangerous or inhospitable situations (e.g., underwater or in extreme heat or cold). • Create a feedback loop to enhance the benefits of certain therapeutic methods. • Develop passive devices for monitoring function, such as monitoring long- term drug effects, evaluating psychological state, etc. • Monitor stages of sleep, Bionics/Cybernetics, Memory Upload/Download, Dream Capture etc. Robotic Applications (Cont…)
- 19. Advantages • Allow paralyzed people to control prosthetic limbs with their mind. • Transmit visual images to the mind of a blind person, allowing them to see. • Transmit auditory data to the mind of a deaf person, allowing them to hear. • Allow gamers to control video games with their minds. • Allow a mute person to have their thoughts displayed and spoken by a computer.
- 20. Disadvantages • Research is still in beginning stages. • The current technology is crude. • Ethical issues may prevent its development. • Electrodes outside of the skull can detect very few electric signals from the brain. • Electrodes placed inside the skull create scar tissue in the brain.
- 21. Conclusion As technology advances, brain tissue may one day give way to implanted silicon chips thereby creating a completely computerized simulation of the human brain that can be augmented at will. Futurists predict that from there, superhuman artificial intelligence won't be far behind.
- 22. Thank You