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15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
15 Trends In Neurotechnologies That Will Change The World
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15 Trends In Neurotechnologies That Will Change The World

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Below are technologies related to neuro and cognitive under three key areas of accelerating change: Machine Learning & Neural Network Computing, Extended Cognition and Neural Interfaces. Neural …

Below are technologies related to neuro and cognitive under three key areas of accelerating change: Machine Learning & Neural Network Computing, Extended Cognition and Neural Interfaces. Neural network computing will lead to improvements in computer vision and analysis, such as detecting emotions and moods, which may have safety and security applications. Extended cognition involves more direct connection to people's brains, allowing mood, thought patterns and information to be altered in the brain. Neural interfaces get information out of people's brains more efficiently, ultimately allowing a machine-enabled form of telepathy. This presentation covers Michell Zappa research from Policy Horizons Canada

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  • 1. NEURO TECHNOLOGIES That Will Change The World 15
  • 2. Machine Learning & Neural NetworkComputing6 SECTION 1
  • 3. EMOTION TRACKING Using sensors, computer vision and algorithms to correctly identify the likely emotions displayed by individuals in a crowd. Useful in airports and other high-risk facilities. 2015 2020 2025 Machine Learning & Neural NetworkComputing6 1.1 Technology Viability
  • 4. GROUP BEHAVIOR PREDICTION Predicting the likely behavior of large groups of people based on sociometricinput variables like social tension, weather variation, pedestrian flows and degree of agitation is becoming increasingly possible. Machine Learning & Neural NetworkComputing6 1.2 Technology Viability 2015 2020 2025
  • 5. PREDICTIVE CRIME PREVENTION The use of sociometricsensors coupled with neural networked computers to statistically determine the probability of crime (or other anti-social behavior) taking place before it happens. Machine Learning & Neural NetworkComputing6 1.3 Technology Viability 2015 2020 2025
  • 6. IMAGE RECOGNITION Using hundreds of thousands of processor cores programmed to algorithmically determine the content of a given image. Different from reverse image search, neural network image recognition has the capacity to successfully understand the photo of, for example, a cat, based on thousands of cat pictures. Machine Learning & Neural NetworkComputing6 1.4 Technology Viability 2015 2020 2025
  • 7. PROACTIVE APPS Software applications with the capacity of discerning and predicting likely future needs for whomever is being served. Intelligently scheduling meetings, sorting email and selectively notifying the user are potential usages. Machine Learning & Neural NetworkComputing6 1.5 Technology Viability 2015 2020 2025
  • 8. Neural interfaces SECTION 2
  • 9. EEG BRAIN-COMPUTER INTERFACES Electroencephalography remains the most feasible practice of executing and implementing brain to brain interfaces. It represents the best temporal-resolution tool for getting a picture of the brain in action, is portable, non-invasive and extremely affordable compared to other methods. Neural interfaces 2.1 Technology Viability 2015 2020 2025
  • 10. HIGH-RESOLUTION FMRI The next generation of functional Magnetic Resonance Imaging involves increasing the spatial and temporal resolution of the imagery. We are likely to see a 14- tesla machines becoming common (as opposed to today's 3-tesla). Neural interfaces 2.2 Technology Viability 2015 2020 2025
  • 11. TRANSCRANIAL MAGNETIC STIMULATION TMS is a noninvasive method to cause depolarization or hyperpolarization in the neurons of the brain using electromagnetic induction to induce weak electric currents using a rapidly changing magnetic field. This can cause activity in specific or general parts of the brain with minimal discomfort, allowing the functioning and interconnections of the brain to be studied. Neural interfaces 2.3 Technology Viability 2015 2020 2025
  • 12. OPTOGENETIC IMPLANTS IN HUMANS The combination of genetic and optical methods to control specific events in targeted cells of living tissue, even within freely moving mammals and other animals, with the temporal precision (millisecond timescale) needed to keep pace with functioning intact biological systems. Neural interfaces 2.4 Technology Viability 2015 2020 2025
  • 13. AUGMENTED COGNITIVE DEVICES Hypothetical interfaces to be used for assisting, augmenting, or repairing human cognitive or sensory-motor functions and communicate thoughts and intentions to the Internet. Neural interfaces 2.5 Technology Viability 2015 2020 2025
  • 14. BRAIN-TO-BRAIN INTERFACES The hypothetical implementation of brain interfaces that translate thoughts, sensations or impulses into digital signal, converting the data back into the recipient's brain to enable a certain response from both ends. Loosely interpreted as telepathy, brain interfaces would be able to transmit information from one person so another without any mediation other than the internet, allowing the brain on the receiving end to perform behaviouraltasks without training. Neural interfaces 2.6 Technology Viability 2015 2020 2025
  • 15. Extended Cognition SECTION 3
  • 16. NEURAL BIOFEEDBACK Biofeedback using real-time EEG or fMRI to illustrate brain activity, often with a goal of controlling the central nervous actions. Extended Cognition 3.1 Technology Viability 2015 2020 2025
  • 17. CAPACITIVE ULTRASONIC TRANSDUCERS A relatively new concept in the field of ultrasonic transducers where the energy transduction is due to change in capacitance. Can be used to remotely improve alertness, awareness in soldiers, etc. Extended Cognition 3.2 Technology Viability 2015 2020 2025
  • 18. NEXT-GEN NEUROPHARMACOLOGY Both behavioral and molecular neuropharmacology are benefitting from rapidly accelerating change. With an increase in technology and improved understanding of the nervous system, the development of drugs will continue to rise with an increase in drug sensitivity and specificity. (Such as neuropharmacologicalenhancements that work better than caffeine). Extended Cognition 3.3 Technology Viability 2015 2020 2025
  • 19. NEUROPROSTHESIS Neural devices capable of substituting motor, sensory or cognitive modalities that might have been damaged as a result of an injury or a disease. Applications include neural enhancements, advanced cognitive featurandextended physiological senses. Extended Cognition 3.4 Technology Viability 2015 2020 2025
  • 20. THE CONTENT CREDITS Policy Horizons Canadaworked with futurist and data visualizerMichellZappaofEnvisioningto produce a report calledMetaScan3: Emerging Technologiesandaccompanying infographics. I am reproducing the summary foremergingneuro and cognitive technologies. ABOUT Nikita Lukianets is a PhD candidate in Computational Neuroscience within a LabExSIGNALIFE consortium at University of Nice Sophia-Antipolis. Nikita is also a co- founder and a CEO of LimeJam. For a long time, Nikita focused on User Experience side of product (worked as UI designer, System Analyst, Product Manager). From 2010 Nikita has been managing developer marketing in Microsoft and was responsible for BizSparkstart-up program. He has a strong research & academic background specialized in applied analysis and biotech. Nikita has MBA degree in design & innovation management from MIP, Politecnicodi Milano and technical education in the field of Applied Physics(M.Sc.) from Kyiv Polytechnic Institute.

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