Computers with Brains? A neuroscience perspective

1. Computers with Brains? A neuroscience perspective Khurshid Ahmad, Professor of Computer Science, Department of Computer Science Trinity College, Dublin-2, IRELAND October 29th , 2009. https://www.cs.tcd.ie/Khurshid.Ahmad/Teaching/ComputersBrains.pdf

2. Brain – The Processor! http://www.cs.duke.edu/brd/Teaching/Previous/AI/pix/noteasy1.gif

3. Brain – The Processor! Neural computing systems are trained on the principle that if a network can compute then it will learn to compute. Multi-net neural computing systems are trained on the principle that if two or more networks learn to compute simultaneously or sequentially , then the multi-net will learn to compute. Our project is to build a neural computing system comprising networks that can not only process unisensory input and learn to process but that the interaction between networks produces multisensory interaction, integration, enhancement/suppression, and information fusion. Tim Shallice (2006). From lesions to cognitive theory. Nature Neuroscience Vol 6, pp 215 (Book Review: Mark D’Esposito (2002). Neurological Foundations of Cognitive Neuroscience

4. What humans do?

5. What animals do? Dendritic computation. The task of a brainstem auditory neuron performing coincidence detection in the sound localization system of birds is to respond only if the inputs arriving from both ears coincide in a precise manner (10–100 μs), while avoiding a response when the input comes from only one ear. London, Michael and Michael Häusser (2005). Dendritic Computation. Annual Review of Neuroscience. Vol. 28, pp 503–32

6. What computer scientists do? The study of the behaviour of neurons, either as 'single' neurons or as cluster of neurons controlling aspects of perception, cognition or motor behaviour, in animal nervous systems is currently being used to build information systems that are capable of autonomous and intelligent behaviour.

7. What animals do? Neurons are known to be involved in much more sophisticated computations, such as face recognition [..]. An algorithm to solve a face recognition task is one of the holy grails of computer science. At present, we do not know precisely how single neurons are involved in this computation. An essential first step is feature extraction from the image, which clearly involves a lot of network pre-processing before features are fed into the individual cortical neuron. The flowchart implements a three-layer model of dendritic processing […] to integrate the input. The way such a flowchart is mapped onto the real geometry of a cortical pyramidal neuron remains unknown. London, Michael and Michael Häusser (2005). Dendritic Computation. Annual Review of Neuroscience. Vol. 28, pp 503–32

8. What animals do? Neurons, and indeed networks of neurons perform highly specialised tasks. The dendrites bring the input in, the soma processes the input and then the axon outputs. However, it appears that the dendrites also have processing power: it is the equivalent of the wires that connects your computer to its printer and the network hub performing computations – helping the computer to perform computations!!! London, Michael and Michael Häusser (2005). Dendritic Computation. Annual Review of Neuroscience. Vol. 28, pp 503–32

9. What humans think about what computers will do? http://www.longbets.org/1

10. What humans do? They have an intricate brain

11. Neural Nets and Neurosciences Observed Biological Processes(Data) Neural Networks & Neurosciences Biologically Plausible Mechanisms for Neural Processing & Learning (Biological Neural Network Models) Theory (Statistical Learning Theory & Information Theory) http://en.wikipedia.org/wiki/Neural_network#Neural_networks_and_neuroscience

12. Real Neuroscience Cognitive neuroscience has many intellectual roots. The experimental side includes the very different methods of systems neuroscience, human experimental psychology and, functional imaging. The theoretical side has contrasting approaches from neural networks or connectionism, symbolic artificial intelligence, theoretical linguistics and information-processing psychology. Tim Shallice (2006). From lesions to cognitive theory. Nature Neuroscience Vol 6, pp 215 (Book Review: Mark D’Esposito (2002). Neurological Foundations of Cognitive Neuroscience

13. Real Neuroscience Brains compute. This means that they process information, creating abstract representations of physical entities and performing operations on this information in order to execute tasks. One of the main goals of computational neuroscience is to describe these transformations as a sequence of simple elementary steps organized in an algorithmic way. The mechanistic substrate for these computations has long been debated. Traditionally, relatively simple computational properties have been attributed to the individual neuron, with the complex computations that are the hallmark of brains being performed by the network of these simple elements. London, Michael and Michael Häusser (2005). Dendritic Computation. Annual Review of Neuroscience. Vol. 28, pp 503–32

14. Real Neuroscience I compute, therefore I am (intelligent): I can converse in natural languages; I can analyse images, pictures (comprising images), and scenes (comprising pictures); I can reason, with facts available to me, to infer new facts and contradict what I had known to be true; I can plan (ahead); I can use symbols and analogies to represent what I know; I can learn on my own, through instruction and/or experimentation; I can compute trajectories of objects on the earth, in water and in the air; I have a sense of where I am physically (prio-perception) I can deal with instructions, commands, requests, pleas; I can ‘repair’ myself; I can understand the mood/sentiment/affect of people and groups I can debate the meaning(s) of life;

15. Real Neuroscience I cannot compute, therefore I am (not intelligent?): I cannot add/subtract/multiply/divide with consistent accuracy; I forget some of the patterns I had once memorised; I confuse facts; I cannot recall immediately what I know; I cannot solve complex equations; I am influenced by my environment when I make decisions, ask questions, pass comments; I will (eventually) loose my faculties and then die!!

16. Real Neuroscience I can and annot not compute because of my nervous system I use language, can see things, represent knowledge, learn, plan, reason …. Because of my nervous system? I cannot do arithmetic consistently, cannot recall and/or forget…. Because of my nervous system?

17. DEFINITIONS: Artificial Neural Networks Artificial Neural Networks (ANN) are computational systems, either hardware or software, which mimic animate neural systems comprising biological (real) neurons. An ANN is architecturally similar to a biological system in that the ANN also uses a number of simple, interconnected artificial neurons.

18. DEFINITIONS: Artificial Neural Networks Artificial neural networks emulate threshold behaviour, simulate co-operative phenomenon by a network of 'simple' switches and are used in a variety of applications, like banking, currency trading, robotics, and experimental and animal psychology studies. These information systems, neural networks or neuro-computing systems as they are popularly known, can be simulated by solving first-order difference or differential equations.

19. Multisensory Enhancement Cross-modal Suppression Cross-modal Facilitation Cross-modal Facilitation Inhibition- Dependent The real neurons are different! Real neurons co-operate, compete and inhinbit each other. In multi-modal information processing, convergence of modalities is critical. From Alex Meredith, Virginia Commonwealth University, Virginia, USA

20. Computation and its neural basis Much of the computing in the brain is on sporadic, multi-modal data streams Much of modern computing relies on the discrete serial processing of uni-modal data

21. Computation and its neural basis Neural computing emphasises the learning aspects of behaviour Analysis of neuroscience experiments is carried out with simple models without the capability of learning

22. Computation and its neural basis Learning to make decisions in noisy environments is something very human; key areas are image annotation, sentiment analysis Decision making invariably involves fusion of multi-modal data streams in the brain involving emotion and reasoning

23. Computation and its neural basis

24. What computers can do? Artificial Neural Networks In a restricted sense artificial neurons are simple emulations of biological neurons: the artificial neuron can, in principle, receive its input from all other artificial neurons in the ANN; simple operations are performed on the input data; and, the recipient neuron can, in principle, pass its output onto all other neurons. Intelligent behaviour can be simulated through computation in massively parallel networks of simple processors that store all their long-term knowledge in the connection strengths.

25. What computers can do? Artificial Neural Networks According to Igor Aleksander, Neural Computing is the study of cellular networks that have a natural propensity for storing experiential knowledge. Neural Computing Systems bear a resemblance to the brain in the sense that knowledge is acquired through training rather than programming and is retained due to changes in node functions. Functionally, the knowledge takes the form of stable states or cycles of states in the operation of the net. A central property of such states is to recall these states or cycles in response to the presentation of cues.

26. DEFINITIONS: Artificial Neural Networks

27. What can computers do? Computers help you in visualising the un-built environment http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

28. What can computers do? Computers help you in visualising the un-built environment http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

29. What can computers do? Computers help you in visualising the un-built environment http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

30. What can computers do? Robots, containing sophisticated computers, can perform a variety of tasks in an automated factory, in bomb disposal and other applications. Robots need to be looked after – be energized, helped to navigate, tasks to be assigned, but, but ………. http://www.nytimes.com/2009/07/26/science/26robot.html

31. What can computers do? Robots, containing sophisticated computers, can perform a variety of tasks in an automated factory, in bomb disposal and other applications. Robots need to be looked after – be energized, helped to navigate, tasks to be assigned, but, but ………. http://www.nytimes.com/2009/07/26/science/26robot.html & http://www.imdb.com/media/rm969447936/tt0062622

32. What can computers do?

33. What can computers do?

34. What can computers do? Tera RoadRunner = 100,000 Laptops (running simultaneously and exchanging information pico second by pico second) Giga http://www.ibm.com/ibm/ideasfromibm/us/roadrunner/20080609/index.shtml

35. Computers dealing with problems in neuroscience Dealing with idiosyncratic behaviour: Letting the autistic child/adult have feedback on self http://affect.media.mit.edu/pdfs/07.Teeters-sm.pdf

36. Computers dealing with problems in neuroscience Dealing with idiosyncratic behaviour http://affect.media.mit.edu/pdfs/07.Teeters-sm.pdf

37. How do computers do what computers do? The number of chips on the same area has doubled every 18-24 months; and has increased exponentially. However, the R&D costs and manufacturing costs for building ultra-small, high-precision circuitry and controls has had an impact on the prices http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

38. The ever growing computer systems (1997) http://www.transhumanist.com/volume1/moravec.htm

39. The ever growing computer systems (1997) http://www.transhumanist.com/volume1/moravec.htm

40. The ever growing computer systems (1997) http://www.transhumanist.com/volume1/moravec.htm

41. The ever growing computer systems Tera The industry took 35 years to reach 1GB (in 1991), 14 years more to reach 500GB (in 2005), and just two more years to reach 1TB (2007) Library of Congress Minerva Web Presence Giga http://en.wikipedia.org/wiki/File:Cmos-chip_structure_in_2000s_(en).svg http://www.transhumanist.com/volume1/moravec.htm & http://www.loc.gov/webarchiving/faq.html

42. The ever growing computer systems The cost of computation is falling dramatically – an exponential decay in what we can get by spending $1000 (calculations per second): In 1940: 0.01 In 1950: 1 In 1960: 100 In 1970: 500-1000 In 1980: 10,000 In 1990: 100,000 In 2000: 1,000,000 http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

43. The ever growing computer systems The cost of data storage is falling dramatically – an exponential decay in what we can get by spending the same amount of money: In 1980: 0.001 GB In 1985: 0.01 In 1990: 0.1 In 1995: 1 In 2000: 10 In 2005: 100 In 2010: 1000 http://search.eb.com.elib.tcd.ie/eb/art-68188/Moores-law-In-1965-Gordon-E-Moore-observed-that-the

44. The ever growing computer systems:Supercomputers of today 300 to 1400 Trillion Floating Point Operations per Second http://www.transhumanist.com/volume1/moravec.htm

45. The intelligent computer:Turing Test http://en.wikipedia.org/wiki/File:Cmos-chip_structure_in_2000s_(en).svg

46. What humans think about what computers will do? http://www.longbets.org/1

47. What can computers do?

48. What can computers do? Aaron, an expert system that can ‘paint’ has had ITS exhibition in major galleries  Here is Aaron’s Liberty & Freinds based on the Statute of Liberty http://crca.ucsd.edu/~hcohen/cohenpdf/furtherexploits.pdf

49. What can computers do? Aaron, an expert system that can ‘paint’ has had ITS exhibition in major galleries  Here is Aaron’s Theo http://crca.ucsd.edu/~hcohen/cohenpdf/furtherexploits.pdf

50. What can computers do? http://crca.ucsd.edu/~hcohen/cohenpdf/furtherexploits.pdf