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==Research==
==Research==
Prof. Howard is well known for his Theory of Intention Awareness (IA),<ref>{{Cite book|title = Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions|last = Howard|first = Newton|publisher = Author House First Books Library|year = 2002|isbn = |location = Bloomington, IN|pages = }}</ref> which provides a possible model for explaining volition in human intelligence, recursively throughout all layers of biological organization. IA is both the process and product of planning and serves as an intelligent architecture to which we can credit purposeful action. This work on Intention Awareness led him to develop the Mood State Indicator (MSI)<ref name=":1">{{Cite journal|url = |title = LXIO: The Mood Detection Robopsych|last = Howard|first = Newton|date = January 2012|journal = Brain Sciences Journal|doi = |pmid = |access-date = |last2 = Guidere|first2 = Mathieu}}</ref> a machine learning system capable of predicting emotional states by modeling the mental processes involved in human speech and writing. Upon this MSI architecture, he next developed the Language Axiological Input/Output system (LXIO),<ref name=":1" /> algorithms capable of detecting both sentiment and mood states based on the analysis of written or verbal discourse, representing mood state by the sum of values generated by a given sentence or word string. LXIO evaluates cognitive states by parsing sentences into words, which are then processed through time orientation, contextual-prediction and subsequent modules with each word's contextual and grammatical function computed with a Mind Default Axiology (MDA). The key significance of LXIO was its ability to incorporate conscious thought and bodily expression (linguistic or otherwise) into a uniform code schema<ref name=":1" />.
Prof. Howard is known for his Theory of Intention Awareness (IA),<ref>{{Cite book|title = Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions|last = Howard|first = Newton|publisher = Author House First Books Library|year = 2002|isbn = |location = Bloomington, IN|pages = }}</ref> which provides a possible model for explaining volition in human intelligence, recursively throughout all layers of biological organization. IA is both the process and product of planning and serves as an intelligent architecture to which we can credit purposeful action. This work on Intention Awareness led him to develop the Mood State Indicator (MSI)<ref name=":1">{{Cite journal|url = |title = LXIO: The Mood Detection Robopsych|last = Howard|first = Newton|date = January 2012|journal = Brain Sciences Journal|doi = |pmid = |access-date = |last2 = Guidere|first2 = Mathieu}}</ref> a machine learning system capable of predicting emotional states by modeling the mental processes involved in human speech and writing. Upon this MSI architecture, he next developed the Language Axiological Input/Output system (LXIO),<ref name=":1" /> algorithms capable of detecting both sentiment and mood states based on the analysis of written or verbal discourse, representing mood state by the sum of values generated by a given sentence or word string. LXIO evaluates cognitive states by parsing sentences into words, which are then processed through time orientation, contextual-prediction and subsequent modules with each word's contextual and grammatical function computed with a Mind Default Axiology (MDA). The key significance of LXIO was its ability to incorporate conscious thought and bodily expression (linguistic or otherwise) into a uniform code schema<ref name=":1" />.


In 2012, Prof. Howard published and patented<ref>{{Cite web|url = http://www.google.com/patents/US20130338526|title = Patent US20130338526-A1|date = |accessdate = |website = Google Patent DB|publisher = US Patent & Trademark Office|last = Howard|first = Newton}}</ref> the Fundamental Code Unit (FCU)<ref name=":2">{{Cite web|url = http://www.brainsciencesjournal.org/brain-language.pdf|title = Brain Language: The Fundamental Code Unit|date = 2012|accessdate = |website = Brain Sciences Journal|publisher = Brain Sciences Foundation|last = Howard|first = Newton}}</ref> theory, which uses [[Unary coding|unitary mathematics]] (ON/OFF +/-) to correlate networks of [[Neurophysiology|neurophysiological]] processes and map them to higher order function. In 2013, he proposed the Brain Code (BC) theory, a methodology for using the FCU to map entire circuits of neurological activity to behavior and response, effectively decoding the language of the brain<ref name=":3">{{Cite book|title = The Brain Language|last = Howard|first = Newton|publisher = Cambridge Scientific Publishing|year = 2015|isbn = 978-1-908106-50-6|location = London, UK|pages = }}</ref>.
In 2012, Prof. Howard published and patented<ref>{{Cite web|url = http://www.google.com/patents/US20130338526|title = Patent US20130338526-A1|date = |accessdate = |website = Google Patent DB|publisher = US Patent & Trademark Office|last = Howard|first = Newton}}</ref> the Fundamental Code Unit (FCU)<ref name=":2">{{Cite web|url = http://www.brainsciencesjournal.org/brain-language.pdf|title = Brain Language: The Fundamental Code Unit|date = 2012|accessdate = |website = Brain Sciences Journal|publisher = Brain Sciences Foundation|last = Howard|first = Newton}}</ref> theory, which uses [[Unary coding|unitary mathematics]] (ON/OFF +/-) to correlate networks of [[Neurophysiology|neurophysiological]] processes and map them to higher order function. In 2013, he proposed the Brain Code (BC) theory, a methodology for using the FCU to map entire circuits of neurological activity to behavior and response, effectively decoding the language of the brain<ref name=":3">{{Cite book|title = The Brain Language|last = Howard|first = Newton|publisher = Cambridge Scientific Publishing|year = 2015|isbn = 978-1-908106-50-6|location = London, UK|pages = }}</ref>.

Revision as of 09:46, 2 January 2016

  • Comment: Previous draft has been deleted as abandoned. Please add references and resubmit. Robert McClenon (talk) 21:00, 26 December 2015 (UTC)
  • Comment: On further review, the existing draft in draft space, which is mostly an autobiography, has been abandoned for more than six months. The author of this draft is advised to add proper references, because this draft is unreferenced, and otherwise to wait until the existing draft is speedy-deleted as abandoned. Robert McClenon (talk) 18:15, 26 December 2015 (UTC)
  • Comment: The author may have accidentally created two copies of this draft. The one in draft space is a good start but is unreferenced and should be the basis for more work (entry of references). I suggest that this one be deleted or blanked so that edits do not get split between the two drafts. Robert McClenon (talk) 18:12, 26 December 2015 (UTC)

{AFC submission|d|dup|Newton Howard|u=Bbrink8|ns=2|decliner=Robert McClenon|declinets=20151226181205|ts=20151226174845}}

Prof. Newton Howard is a brain and cognitive scientist and former Director of the MIT Mind Machine Project[1][2] at the Massachusetts Institute of Technology (MIT). He is a Professor of Computational Neuroscience and Functional Neurosurgery[3] at the University of Oxford, where he directs the Oxford Computational Neuroscience Laboratory[4]. He is also the Director of the Synthetic Intelligence Lab at MIT[5], the founder of the Center for Advanced Defense Studies[6] and the Chairman of the Brain Sciences Foundation[7]. Professor Howard is also a Senior Fellow at the John Radcliffe Hospital at Oxford, a Senior Scientist at INSERM in Paris and a P.A.H. at the CHU Hospital in Martinique.

His research areas include Cognition, Memory, Trauma, Machine Learning, Comprehensive Brain Modeling, Natural Language Processing, Nanotech, Medical Devices and Artificial Intelligence.

Education and Career

Dr. Howard earned his B.A. from Concordia University, then obtained an M.A. in Technology from Eastern Michigan University. He went on to study at MIT and at the University of Oxford where he proposed the Theory of Intention Awareness (IA)[8] as a graduate member of the Faculty of Mathematical Sciences. He also received a Doctorate in Cognitive Informatics and Mathematics while at the University of Paris-Sorbonne, where hewas aalso warded a Habilitation a Diriger des Recherches for his work on the Physics of Cognition (PoC)[9].

Professor Howard is an author and national security advisor[10][11] to several U.S. Government organizations[12] and his work has contributed to more than 30 U.S. patents and over 90 publications. In 2009, he founded the Brain Sciences Foundation (BSF)[7], a nonprofit 501(c)3 organization with the goal of improving the quality of life for those suffering from neurological disorders. The Foundation includes fellows from various research institutions, including Oxford University, Massachusetts Institute of Technology, La Sorbonne University of Paris and INSERM.

Research

Prof. Howard is known for his Theory of Intention Awareness (IA),[13] which provides a possible model for explaining volition in human intelligence, recursively throughout all layers of biological organization. IA is both the process and product of planning and serves as an intelligent architecture to which we can credit purposeful action. This work on Intention Awareness led him to develop the Mood State Indicator (MSI)[14] a machine learning system capable of predicting emotional states by modeling the mental processes involved in human speech and writing. Upon this MSI architecture, he next developed the Language Axiological Input/Output system (LXIO),[14] algorithms capable of detecting both sentiment and mood states based on the analysis of written or verbal discourse, representing mood state by the sum of values generated by a given sentence or word string. LXIO evaluates cognitive states by parsing sentences into words, which are then processed through time orientation, contextual-prediction and subsequent modules with each word's contextual and grammatical function computed with a Mind Default Axiology (MDA). The key significance of LXIO was its ability to incorporate conscious thought and bodily expression (linguistic or otherwise) into a uniform code schema[14].

In 2012, Prof. Howard published and patented[15] the Fundamental Code Unit (FCU)[16] theory, which uses unitary mathematics (ON/OFF +/-) to correlate networks of neurophysiological processes and map them to higher order function. In 2013, he proposed the Brain Code (BC) theory, a methodology for using the FCU to map entire circuits of neurological activity to behavior and response, effectively decoding the language of the brain[17].

In 2014, Prof. Howard discovered a functional endogenous optical network within the brain, mediated by neuropsin (OPN5). This self-regulating cycle of photon-mediated events in the neocortex involves sequential interactions among 3 mitochondrial sources of endogenously-generated photons during periods of increased neural spiking activity: (a) near-UV photons (~380 nm), a free radical reaction byproduct; (b) blue photons (~470 nm) emitted by NAD(P)H upon absorption of near-UV photons; and (c) green photons (~530 nm) generated by NAD(P)H oxidases, upon NAD(P)H-generated blue photon absorption.  The bistable nature of this nanoscale quantum process provides evidence for an on/off (UNARY +/-) coding system existing at the most fundamental level of brain operation and provides a solid neurophysiological basis for Dr. Howard's FCU[16] thesis to build from.

Selected Works

Patents (US)

Patents (International)

References

  1. ^ "MIT Mind Machine Project". Mind Machine Project. Massachusetts Institute of Technology.
  2. ^ Chandler, David (December 7, 2009). "Rethinking artificial intelligence". MIT News. Massachusetts Institute of Technology.
  3. ^ "Nuffield Department of Surgical Sciences". Nuffield Department of Surgical Sciences. University of Oxford.
  4. ^ "Oxford Computational Neuroscience Laboratory". Oxford Computational Neuroscience Laboratory. University of Oxford.
  5. ^ "Synthetic Intelligence Lab". Synthetic Intelligence Lab. Massachusetts Institute of Technology.
  6. ^ "Center for Advanced Defense Studies". Center for Advanced Defense Studies. Center for Advanced Defense Studies.
  7. ^ a b "Brain Sciences Foundation". Brain Sciences Foundation. Brain Sciences Foundation.
  8. ^ Newton Howard, “Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions", Author House First Books Library, Bloomington, Indiana. 2002.
  9. ^ Howard, Newton (1999). "The Logic of Uncertainty and Situational Understanding". Center for Advanced Defense Studies (CADS)/Institute for the Mathematical Complexity & Cognition (MC) Centre de Recherche en Informatique, Université Paris Sorbonne.
  10. ^ JMO, CWID (2007). "CWID - Coalition Warrior Interoperability Demonstration" (PDF). CWID JMO.
  11. ^ NATO, MIP (2007). "Joint C3 Information Exchange Data Model Overview" (PDF). MIP-NATO Management Board.
  12. ^ Howard, Newton (2013). "Development of a Diplomatic, Information, Military, Health, and Economic Effects Modeling System" (PDF). Massachusetts Institute of Technology.
  13. ^ Howard, Newton (2002). Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions. Bloomington, IN: Author House First Books Library.
  14. ^ a b c Howard, Newton; Guidere, Mathieu (January 2012). "LXIO: The Mood Detection Robopsych". Brain Sciences Journal.
  15. ^ Howard, Newton. "Patent US20130338526-A1". Google Patent DB. US Patent & Trademark Office.
  16. ^ a b Howard, Newton (2012). "Brain Language: The Fundamental Code Unit" (PDF). Brain Sciences Journal. Brain Sciences Foundation.
  17. ^ Howard, Newton (2015). The Brain Language. London, UK: Cambridge Scientific Publishing. ISBN 978-1-908106-50-6.
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