IP Library Granted Patent US 10,624,578
Granted Patent B2
US 10,624,578 · App. 16/000,783 · Granted Apr 21, 2020

Fundamental code unit of the brain: towards a new model for cognitive geometry

Inventor: Newton Howard (Providence, RI)
A61B5/4839A61B5/04A61B5/04004A61B5/04008A61B5/0476A61B5/055A61B5/112A61B5/407A61B5/4082A61B5/4088A61B5/4803A61B5/4824A61B5/7282A61M21/02A61N1/00A61N2/006A61N5/0618A61N5/0622A61N7/00A61B5/4076A61B2576/026A61M2021/0027A61M2021/0044A61N1/36014A61N1/36071A61N2005/0661A61N2005/1087A61N2007/0026A61N2007/0073A61N2007/0082
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Quick Facts
Patent No.
US 10,624,578
App. No.
16/000,783
Granted
Apr 21, 2020
Kind
B2
Abstract

In embodiments, devices, methods and systems to analyze the different mediums of brain function in a mathematically uniform manner may be provided. These devices, methods and systems may manifest at several levels and ways relating to brain physiology, including neuronal activity, molecular chirality and frequency oscillations. For example, in an embodiment, a computer-implemented method for determining structure of living neural tissue may comprise receiving at least one signal from at least one read modality, the signal representing at least one physical condition of the living neural tissue, determining action potentials based on the signals received from the read modalities, determining frequency oscillations based on the signals received from the read modalities and the action potentials, and determining neuron network structures based on the signals received from the read modalities, the action potentials, and the frequency oscillations.

Claims (26)

1. A computer-implemented method for determining structure of living neural tissue comprising:

receiving at least one signal from at least one read modality, the signal representing at least one physical condition of the living neural tissue;

determining action potentials based on the signals received from the read modalities;

determining frequency oscillations based on the signals received from the read modalities and the action potentials; and

determining neuron network structures based on the signals received from the read modalities, the action potentials, and the frequency oscillations.

2. The method of claim 1 , wherein the neuron network structures are determined using a Maximum Entropy model.

3. The method of claim 2 , further comprising determining axiological structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, and the determined neuron network structures.

4. The method of claim 3 , wherein the axiological structures are determined using a Unitary System in which preconceptual image schemata include axiological parameters with bipolar properties having positive and negative associations.

5. The method of claim 4 , further comprising determining linguistic structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, the determined neuron network structures, and the determined axiological structures.

6. The method of claim 5 , wherein the linguistic structures are determined by assessing linguistic symbolic units on an axiological scale.

7. A system for determining structure of living neural tissue, the system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor to perform:

receiving at least one signal from at least one read modality, the signal representing at least one physical condition of the living neural tissue;

determining action potentials based on the signals received from the read modalities;

determining frequency oscillations based on the signals received from the read modalities and the action potentials; and

determining neuron network structures based on the signals received from the read modalities, the action potentials, and the frequency oscillations.

8. The system of claim 7 , wherein the neuron network structures are determined using a Maximum Entropy model.

9. The system of claim 8 , further comprising determining axiological structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, and the determined neuron network structures.

10. The system of claim 9 , wherein the axiological structures are determined using a Unitary System in which preconceptual image schemata include axiological parameters with bipolar properties having positive and negative associations.

11. The system of claim 10 , further comprising determining linguistic structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, the determined neuron network structures, and the determined axiological structures.

12. The system of claim 11 , wherein the linguistic structures are determined by assessing linguistic symbolic units on an axiological scale.

13. A non-transitory computer program product for determining structure of living neural tissue, the computer program product comprising a non-transitory computer readable storage having program instructions embodied therewith, the program instructions executable by a computer, to cause the computer to perform a method comprising: receiving at least one signal from at least one read modality, the signal representing at least one physical condition of the living neural tissue; determining action potentials based on the signals received from the read modalities; determining frequency oscillations based on the signals received from the read modalities and the action potentials; and determining neuron network structures based on the signals received from the read modalities, the action potentials, and the frequency oscillations.

14. The non-transitory computer program product of claim 13 , wherein the neuron network structures are determined using a Maximum Entropy model.

15. The non-transitory computer program product of claim 14 , further comprising determining axiological structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, and the determined neuron network structures.

16. The non-transitory computer program product of claim 15 , wherein the axiological structures are determined using a Unitary System in which preconceptual image schemata include axiological parameters with bipolar properties having positive and negative associations.

17. The non-transitory computer program product of claim 16 , further comprising determining linguistic structures based on the signals received from the read modalities, the action potentials, the frequency oscillations, the determined neuron network structures, and the determined axiological structures.

18. The non-transitory computer program product of claim 17 , wherein the linguistic structures are determined by assessing linguistic symbolic units on an axiological scale.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 28, 2025
From: HOWARD, NEWTON
To: GENESIS INTELLIGENCE, LLC
Reel/Frame 072702/0249 →
Continuity (11)
Continuation In Part 15988292 · May 24, 2018
Continuation In Part 15219255 · Jul 25, 2016
Continuation 13747448 · Jan 22, 2013
Continuation In Part 13083352 · Apr 8, 2011
Continuation In Part 12880042 · Sep 10, 2010
Provisional Application 62515133 · Jun 5, 2017
Provisional Application 62510519 · May 24, 2017
Provisional Application 61588666 · Jan 20, 2012
Provisional Application 61322158 · Apr 8, 2010
Provisional Application 61241314 · Sep 10, 2009
Related Publication 20180289319A1 · Oct 11, 2018