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DDG, an Electromagnetic Version of EEG Finds Evidence of a Self-operating Mathematical Universe (SOMU) When a Human Subject Converses with an Artificial Brain

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Emotion, Cognition and Silent Communication: Unsolved Mysteries

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Abstract

Mapping of 289 human brains, isolated and in groups and creating an organic artificial brain, the basic claims of a model Self-Operating Mathematical Universe, SOMU, have been verified where a fractal pattern of the density of primes runs an automaton for making decisions. So, to write natural events, the 6D space–time duplet is not used; rather, the 12D space–time-topology-prime quartet rewrites natural events as observation-free invariants. SOMU simulates nature and the brain as an assembly of electromagnetic resonators grown within and above from the smallest to the largest spatial scale as a fractal tape machine that synthesizes invariants. Electromagnetic radiation maps of 207 humans revealed the use of primes as symmetries of resonance chain, as predicted in 2014. Then by self-assembling organic resonators, an artificial brain is made that, if it vibrates like the resonance chain, derives 91 cognitive invariants. Human subjects interacted with the artificial brain to reveal that nature and the brain explore the resonance chain similarly. For both, the geometric arrangement of frequencies follows the prime number’s fractal pattern F(U) over integer space, an infinite source code that alleviates the need for programming. Hence, the brain does not compute; it evolves endlessly for a greater sync with nature's resonance chain, wherein mismatches become decisions. Cognitive responses with one-to-eight human subjects validate twelve dimensions (12D) in a space–time-topology-prime metric of SOMU. Live data streams using dodecanogram (DDG), an electromagnetic advancement of electroencephalogram (EEG), show that the brain's unit of information is a network of invariants encoded as polyatomic time crystal that evolves by decomposing 12D multinions (e.g., dodecanions), so, redefining the unit of information and integration rule is essential to learn brain. Unlike EEG, the DDG’s invariant bank reads 91 human perceptions live in both bio-n-synthetic brains, confirming that retrieving human-like cognitive responses require unforeseen technologies; its is a first and primitive step.

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References

  1. Acar AZ, Acar CE, Makeig S (2016) Simultaneous head tissue conductivity and EEG source location estimation. NeuroImage 1;124(Pt A):168–180. https://doi.org/10.1016/j.neuroimage.2015.08.032 (Epub 2015 Aug 22. PMID: 26302675; PMCID: PMC4651780)

  2. Agrawal L, Chhajed R, Ghosh S, Ghosh B, Ray K, Sahu S, Fujita D, Bandyopadhyay A (2018) Fractal information theory (FIT)-derived geometric musical language (GML) for brain-inspired hypercomputing. Soft Comput Theor Appl 548:343–372

    Google Scholar 

  3. Agrawal L, Ghosh S, Ghosh B, Ray K, Sahu S, Fujita D, Bandyopadhyay A (2016) Replacing Turing tape with a Fractal tape: a new information theory, associated mechanics and decision making without computing, consciousness (Chapter 6). Integrating Indian West Perspect 87–159

    Google Scholar 

  4. Atanasov V, Dandoloff R (2008) Curvature-induced quantum behaviour on a helical nanotube. Phys Lett A 372:6141–6144

    Article  Google Scholar 

  5. Agrawal L, Sahu S, Ghosh S, Shiga T, Fujita D, Bandyopadhyay A (2016) Inventing atomic resolution scanning dielectric microscopy to see a single protein complex operation live at resonance in a neuron without touching or adulterating the cell. J Integr Neurosci 15(04):435–462

    Article  Google Scholar 

  6. Bandyopadhyay A, Miki K, Wakayama Y (2006) Writing and erasing information in multilevel logic systems of a single molecule using scanning tunneling microscope. Appl Phys Lett 89(24)

    Google Scholar 

  7. Baars BJ, Demertzi A et al (2019) A cognitive theory of consciousness. Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci Adv 5:eaat7603

    Google Scholar 

  8. Baars B (2017) The global workspace theory of consciousness: predictions and results. In: Susan S, Velmans M (eds) The Blackwell companion to consciousness, 2nd edn. Wiley-Blackwell. https://doi.org/10.1002/9781119132363.ch16. ISBN 978-0-470-67406-2

  9. Bandyopadhyay A (2020) Nanobrain: the making of an artificial brain from a time crystal. CRC Press, Taylor and Francis. https://doi.org/10.1201/9780429107771

  10. Bandyopadhyay A, Fujita D (2021) Electromagnetic device, magnetic and electrical vortex synthesis device and magnetic and optical vortex synthesis device. Application no. 2021-172702

    Google Scholar 

  11. Boostani R, Karimzadeh F, Nami M (2017) A comparative review on sleep stage classification methods in patients and healthy individuals. Comput Methods Programs Biomed 140:77–91. https://doi.org/10.1016/j.cmpb.2016.12.004

    Article  Google Scholar 

  12. Borawski M, Biercewicz K, Duda J (2020) Determination of the inaccuracies of calculated EEG indices. Sensors 20(19):5715. https://doi.org/10.3390/s20195715

    Article  Google Scholar 

  13. Bandyopadhyay A, Fujita D, Pati R (2009) Architecture of a massive parallel processing nano brain operating 100 billion molecular neurons simultaneously. Int J Nanotech Mol Comp 1:50–80

    Article  Google Scholar 

  14. Barlow J (1983) Electroencephalography: basic principles, clinical applications and related fields. JAMA 250(22):3108. https://doi.org/10.1001/jama.1983.03340220076048

    Article  Google Scholar 

  15. Bandyopadhyay A, Ghosh S, Fujita D (2019) Universal Geometric-musical language for big data processing in an assembly of clocking resonators, JP-2017-150171, 8/2/2017. World patent received February 2019, WO 2019/026983

    Google Scholar 

  16. Barraza P, Pérez A, Rodríguez E (2020) Brain-to-brain coupling in the gamma-band as a marker of shared intentionality. Front Hum Neurosci 30;14:295. https://doi.org/10.3389/fnhum.2020.00295 (PMID: 32848670; PMCID: PMC7406570)

  17. Bayne T, Hohwy J, Owen AM (2016) Are there levels of consciousness? Trends Cogn Sci 20:405–413

    Article  Google Scholar 

  18. Boly M et al (2011) Preserved feedforward but impaired top-down processes in the vegetative state. Science 332:858–862

    Article  Google Scholar 

  19. Brea J, Gerstner W (2016) Does computational neuroscience need new synaptic learning paradigms? Curr Opin Behav Sci 11:61–66

    Article  Google Scholar 

  20. Breakspear M (2017) Dynamic models of large-scale brain activity. Nat Neurosci 20:340–352. https://doi.org/10.1038/nn.4497

    Article  Google Scholar 

  21. Buhlmann P (2018) Invariance in heterogeneous, large-scale and high-dimensional data. In: Proceedings of international congress of mathematicians. Rio de Janeiro, Brazil, pp 2785–2800

    Google Scholar 

  22. Christian D (2011) Maps of time: an introduction to big history. University of California Press. ISBN 978-0-520-95067-2

    Google Scholar 

  23. Criscione JC et al (2000) An invariant basis for natural strain which yields orthogonal stress response terms in isotropic hyperelasticity. J Mech Phys Sol 48:2445–2465

    Article  Google Scholar 

  24. Chanes L, Quentin R, Tallon-Baudry C, Valero-Cabré A (2013) Causal frequency-specific contributions of frontal spatiotemporal patterns induced by non-invasive neurostimulation to human visual performance. J Neurosci 33(11):5000–5005. https://doi.org/10.1523/jneurosci.4401-12.2013

    Article  Google Scholar 

  25. Coenen A, Fine E, Zayachkivska O (2014) Adolf Beck: a forgotten pioneer in electroencephalography. J Hist Neurosci 23(3):276–286

    Article  Google Scholar 

  26. Drisdelle B, Aubin S, Jolicœur P (2016) Dealing with ocular artifacts on lateralized ERPs in studies of visual-spatial attention and memory: ICA correction versus epoch rejection. Psychophysiology 54(1):83–99. https://doi.org/10.1111/psyp.12675

    Article  Google Scholar 

  27. Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1):9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009

    Article  Google Scholar 

  28. Delorme A et al (2007) Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. NeuroImage 34:1443–1449

    Google Scholar 

  29. Fingelkurts AA, Fingelkurts AA (2009) Brain and mind operational architectonics and man-made “machine” consciousness. Cogn Process 10(2):105–111

    Article  Google Scholar 

  30. Friston KJ (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 11:127–138

    Article  Google Scholar 

  31. Gao XC, Xu JB, Qian TZ (1991) Geometric phase and the generalized invariant formulation. Phys Rev A 44(11):7016–7021. https://doi.org/10.1103/physreva.44.7016

    Article  MathSciNet  Google Scholar 

  32. Gennaro RJ (ed) (2004) Higher-order theories of consciousness. John Benjamins Publishers, Amsterdam and Philadelphia

    Google Scholar 

  33. Ghosh S, Dutta M, Ray K, Fujita D, Bandyopadhyay A (2016) A simultaneous one pot synthesis of two fractal structures via swapping two fractal reaction kinetic states. Phys Chem Chem Phys 18:14772–14775

    Article  Google Scholar 

  34. Ghosh S, Dutta M, Sahu S, Fujita D, Bandyopadhyay A (2014) Nano molecular-platform: a protocol to write energy transmission program inside a molecule for bio-inspired supramolecular engineering. Adv Func Mater 24(10):1364–1371

    Article  Google Scholar 

  35. Ghosh S, Fujita D, Bandyopadhyay A (2015) An organic jelly made fractal logic gate with an infinite truth table. Sci Rep 5(1):1–8

    Article  Google Scholar 

  36. Ghosh S, Sahu S, Fujita D, Bandyopadhyay A (2014) Design and operation of a brain like computer: a new class of frequency-fractal computing using wireless communication in a supramolecular organic, inorganic systems. Information 5:28–99

    Article  Google Scholar 

  37. Grant A, Abdel-Baki S, Weedon J, Arnedo V, Chari G, Koziorynska E, Omurtag A et al (2014) EEG interpretation reliability and interpreter confidence: a large single-center study. Epilepsy Behav 32:102–107. https://doi.org/10.1016/j.yebeh.2014.01.011

  38. Ghosh S, Sahu S, Agrawal L, Shiga T, Bandyopadhyay A (2016) Inventing a co-axial atomic resolution patch clamp to study a single resonating protein complex and ultra-low power communication deep inside a living neuron cell. J Integr Neurosci 15(04):403–433

    Article  Google Scholar 

  39. Hameroff S, Penrose R (2014) Consciousness in the universe: a review of the ‘Orch OR’ theory. Phys Life Rev 11:39–78

    Article  Google Scholar 

  40. Hancock SW, Zahedpour S, Goffin A, Milchberg HM (2019) Free-space propagation of spatiotemporal optical vortices. Optica 6:1547–1553

    Article  Google Scholar 

  41. Harish R (2019) Nasadiya Shukta—the Hymm of creation in the Rig Veda. RV 10.154; RV 10.190. https://www.speakingtree.in/blog/nasadiya-suktam-the-hymn-of-creation-in-the-rig-veda-734806

  42. Herzberg G, Longuet-Higgins HC (1963) Intersection of potential energy surfaces in polyatomic molecules. Discuss Faraday Soc 35:77–82. https://doi.org/10.1039/DF9633500077

  43. Hinton GE (2007) Learning multiple layers of representation. Trends Cogn Sci 11(10):428–434

    Google Scholar 

  44. Huang C, Chen X, Oladipo A et al (2015) Generation of subwavelength plasmonic nanovortices via helically corrugated metallic nanowires. Sci Rep 5:13089. https://doi.org/10.1038/srep13089

    Article  Google Scholar 

  45. Jung TP, Makeig S, Humphries C, Lee TW, McKeown MJ, Iragui V, Sejnowski TJ (2000) Removing electroencephalographic artifacts by blind source separation. Psychophysiology 37(2):163–178 (PMID: 10731767)

    Google Scholar 

  46. Kent L, Wittmann M (2021) Special issue: consciousness science and its theories. Time consciousness: the missing link in theories of consciousness. Neurosci Conscious 2021:niab011

    Google Scholar 

  47. Laufs H, Krakow K, Sterzer P, Eger E, Beyerle A, Salek-Haddadi A, Birbaumer N (2003) EEG-correlated fMRI of human alpha activity: a new tool to study the neurophysiology of brain oscillations. Neuroimage 19(4):1463–1476

    Article  Google Scholar 

  48. Lehnertz K, Rings T, Bröhl T (2021) Time in brain: how biological rhythms impact on EEG signals and on EEG-derived brain networks. Front Netw Physiol 1. https://doi.org/10.3389/fnetp.2021.755016

  49. Lau H, Rosenthal D (2011) Empirical support for higher-order theories of conscious awareness. Trends Cogn Sci 15:365–373

    Article  Google Scholar 

  50. Lewis A, Claassen J, Illes J, Jox RJ, Kirschen M, Rohaut B, Trevick S, Young MJ, Fins JJ; and the Curing Coma Campaign and its contributing members. Ethics Priorities of the Curing Coma Campaign: An Empirical Survey. Neurocrit Care. 2022 Aug;37(1):12–21. https://doi.org/10.1007/s12028-022-01506-2. Epub 2022 May 4. PMID 35505222; PMCID PMC10034145.

  51. Liboff AR (2016) Magnetic correlates in electromagnetic consciousness. Electromagn Biol Med 35(3):228–236

    Article  Google Scholar 

  52. Liley DT, Walsh M. The Mesoscopic Modeling of Burst Suppression during Anesthesia. Front Comput Neurosci. 2013 Apr 30;7:46. https://doi.org/10.3389/fncom.2013.00046. PMID 23641211; PMCID PMC3639728.

  53. Luck SJ, Gaspelin N (2017) How to get statistically significant effects in any ERP experiment (and why you shouldn’t). Psychophysiology 54:146–157

    Article  Google Scholar 

  54. Markram H (2006) The blue brain project. Nature reviews. Neuroscience 7(2):153–160. https://doi.org/10.1038/nrn1848 (PMID 16429124. S2CID 15752137)

  55. Mannan M, Jeong M, Kamran M (2016) Hybrid ICA—regression: automatic identification and removal of ocular artifacts from electroencephalographic signals. Front Hum Neurosci 10. https://doi.org/10.3389/fnhum.2016.00193

  56. McCann H, Beltrachini L (2022) Impact of skull sutures, spongiform bone distribution, and aging skull conductivities on the EEG forward and inverse problems. J Neural Eng 19(1):016014. https://doi.org/10.1088/1741-2552/ac43f7

    Article  Google Scholar 

  57. Niso G, Krol LR, Combrisson E, Dubarry AS, Elliott MA, François C, Héjja-Brichard Y, Herbst SK, Jerbi K, Kovic V, Lehongre K, Luck SJ, Mercier M, Mosher JC, Pavlov YG, Puce A, Schettino A, Schön D, Sinnott-Armstrong W, Somon B, Šoškić A, Styles SJ, Tibon R, Vilas MG, van Vliet M, Chaumon M (2022) Good scientific practice in EEG and MEG research: progress and perspectives. Neuroimage 257:119056. https://doi.org/10.1016/j.neuroimage.2022.119056

    Article  Google Scholar 

  58. Picton TW, Bentin S, Berg P, Donchin E, Hillyard SA, Johnson R Jr, Mangun GR, Taylor MJ et al (2000) Guidelines for using human event-related potentials in studies of cognition: recording standards and publication criteria. Psychophysiology 37(2):127–152

    Google Scholar 

  59. Pascual-Marqui RD, Michel CM, Lehmann D (1994) Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49–65

    Article  Google Scholar 

  60. Pattanayak A, Dutta T, Pranjal P, Singh P, Sahoo P et al (2022) Meta-analysis of fMRI for emotional and cognitive states shows hierarchical invariant optimization in brain. In: Kaiser MS, Bandyopadhyay A, Ray K, Singh R, Nagar V (eds) Proceedings of trends in electronics and health informatics. Lecture notes in networks and systems, vol 376. Springer, Singapore, pp 255–265

    Google Scholar 

  61. Poldrack RA (2006) Can cognitive processes be inferred from neuroimaging data? Trends Cogn Sci 10(2):59–63

    Article  Google Scholar 

  62. Pradhan B, Bandyopadhyay A, Pal AJ (2004) Molecular level control of donor/acceptor heterostructures in organic photovoltaic devices. Appl Phys Lett 85(4):663–665

    Article  Google Scholar 

  63. Pramanik S, Singh P, Sahoo P, Ray K, Bandyopadhyay A (2022) 1D to 20D tensors like dodecanions and icosanions to model human cognition as morphogenesis in the density of primes. In: 4th international conference on trends in computational and cognitive engineering, TCCE-2022 (under press)

    Google Scholar 

  64. Pockett S (2000). The nature of consciousness. ISBN 978-0-595-12215-8

    Google Scholar 

  65. Quentin R, Frankston S, Vernet M, Toba M, Bartolomeo P, Chanes L, Valero-Cabré A et al (2015) Visual contrast sensitivity improvement by right frontal high-beta activity is mediated by contrast gain mechanisms and influenced by fronto-parietal white matter microstructure. Cereb Cortex 26(6):2381–2390. https://doi.org/10.1093/cercor/bhv060

  66. Reddy S, Sonker D, Singh P, Saxena K, Singh S, Chhajed R, Tiwari S, Karthik KV, Ghosh S, Ray K, Bandyopadhyay A (2018) A brain-like computer made of time crystal: could a metric of prime alone replace a user and alleviate programming forever? Soft Comput Appl 761:1–43

    Google Scholar 

  67. Ruofan W, Wang J, Li S, Yu H, Deng B, Wei X (2015) Multiple feature extraction and classification of electroencephalograph signal for alzheimers’ with spectrum and bispectrum. Chaos Interdisc J Nonlinear Sci 25(1). https://doi.org/10.1063/1.4906038

  68. Robbins KA et al (2021) Capturing the nature of events and event context using hierarchical event descriptors (HED). NeuroImage 245:118766–118766

    Google Scholar 

  69. Sahoo P, Singh P, Manna J, Singh RP, Hill JP, Nakayama T, Ghosh S, Bandyopadhyay A (2023a) A Third Angular Momentum of Photons. Symmetry, 15, 158. https://doi.org/10.3390/sym15010158

  70. Sahoo P, Singh P, Saxena K, Ghosh S, Singh RP, Benosman R, Hill JP, Nakayama T, Bandyopadhyay A (2023b). A general-purpose organic gel computer that learns by itself. Neuromorph. Comput. Eng. 3 044007

    Google Scholar 

  71. Stengel C, Quentin R, Amengual J, Valero-Cabré A (2019) Entrainment of local synchrony reveals a causal role for high-beta right frontal oscillations in human visual consciousness. Sci Rep 9(1). https://doi.org/10.1038/s41598-019-49673-1

  72. Sahu S, Fujita D, Bandyopadhyay A (2010) An inductor made of arrayed capacitors. JP-511630; US 9019685B2, 2015. European patent EP2562776B1 https://patents.google.com/patent/EP2562776A1/de

  73. Saxena K, Singh P, Sahoo P, Ghosh S, Krishnanda D, Ray K, Fujita D, Bandyopadhyay A (2022) All basics that are wrong with the current concept of time crystal: learning from the polyatomic time crystals of protein, microtubule, and neuron. Proc Trends Electron Health Inform 376:243–254

    Article  Google Scholar 

  74. Saxena K, Singh P, Sarkar J, Sahoo P, Ghosh S, Bandyopadhyay A (2022) Polyatomic time crystals of the brain neuron extracted microtubule are projected like a hologram meters away. J Appl Phys 132:194401. https://doi.org/10.1063/5.0130618

    Article  Google Scholar 

  75. Saxena K, Singh P, Sahoo P, Sahu S, Ghosh S, Ray K, Fujita D, Bandyopadhyay A (2020) Fractal, scale free electromagnetic resonance of a single brain extracted microtubule nanowire, a single tubulin protein and a single neuron. Fractal Fractional 4(2):11

    Article  Google Scholar 

  76. Singh P, Doti R, Lugo JE, Faubert J, Rawat S, Ghosh S, Ray K (2018) DNA as an electromagnetic fractal cavity resonator: its universal sensing and fractal antenna behavior. Soft Comput Theor Appl 584:213–223

    Google Scholar 

  77. Singh P, Doti R, Lugo JE, Faubert J, Rawat S, Ghosh S, Ray K, Bandyopadhyay A (2018) Frequency fractal behavior in the retina nano-center-fed dipole antenna network of a human eye. Soft Comput Theor Appl 548:201–211

    Google Scholar 

  78. Shi L, Tashiro S (2018) Estimation of the effects of medical diagnostic radiation exposure based on DNA damage. J Radiat Res 59(suppl_2):ii121–ii129. https://doi.org/10.1093/jrr/rry006

  79. Singer W (1993) Synchronization of cortical activity and its putative role in information processing and learning. Annu Rev Physiol 55(1):349–374. https://doi.org/10.1146/annurev.physiol.55.1.349

    Article  Google Scholar 

  80. Singh P, Ocampo M, Lugo JE, Doti R, Faubert J, Rawat S, Ghosh S, Ray K, Bandyopadhyay A (2018) Fractal and periodical biological antennas: hidden topologies in DNA, wasps and retina in the eye. Soft Comput Appl 761:113–130

    Google Scholar 

  81. Singh P, Ray K, Bandyopadhyay A (2022) The making of a humanoid bot using electromagnetic antenna and sensors: biological antenna to the humanoid bot. Stud Rhythm Eng 153–195. https://doi.org/10.1007/978-981-16-9677-0_5153

  82. Singh P, Ray K, Fujita D, Bandyopadhyay A (2019) Complete dielectric resonator model of human brain from MRI data: a journey from connectome neural branching to single protein. Eng Vibr Commun Inform Process 478:717–733

    Google Scholar 

  83. Singh P, Sahoo P, Ray K, Ghosh S, Bandyopadhyay A (2021) Building a non-ionic, non-electronic, non-algorithmic artificial brain: cortex and connectome interaction in a humanoid bot Subject (HBS). In: Proceedings of international conference on trends in computational and cognitive engineering, vol 1309, pp 245–278

    Google Scholar 

  84. Singh P, Sahoo P, Saxena K, Ghosh S, Sahu S, Ray K, Fujita D, Bandyopadhyay A (2021) A space-time-topology-prime, stTS metric for a self-operating mathematical universe uses Dodecanion geometric algebra of 2-20 D complex vectors. In: Proceedings of international conference on data science and applications, vol 148, pp 1–31

    Google Scholar 

  85. Singh P, Sahoo P, Saxena K, Ghosh S, Sahu S, Ray K, Fujita D, Bandyopadhyay A (2021) Quaternion, octonion to dodecanion manifold: stereographic projections from infinity lead to a self-operating mathematical universe. In: Proceedings of international conference on trends in computational and cognitive engineering, vol 1169, pp 55–77

    Google Scholar 

  86. Singh P, Saxena K, Sahoo P, Sarkar J, Ghosh S, Ray K, Bandyopadhyay A (2022) Instantaneous communication between cerebellum, hypothalamus, and hippocampus (C–H–H) during decision-making process in human brain-III. In: Proceedings of the third international conference on trends in computational and cognitive engineering, vol 348, pp 93–110

    Google Scholar 

  87. Singh P, Saxena K, Singhania A, Sahoo P, Ghosh S, Chhajed R, Ray K, Fujita D, Bandyopadhyay A (2020) A self-operating time crystal model of the human brain: can we replace entire brain hardware with a 3D fractal architecture of clocks alone? Information 11(5):238

    Article  Google Scholar 

  88. Taheri B, Knight R, Smith R (1994) A dry electrode for EEG recording. Electroencephalogr Clin Neurophysiol 90(5):376–383

    Article  Google Scholar 

  89. Tam W, Wu T, Zhao Q, Keefer E, Yang Z (2019) Human motor decoding from neural signals: a review. BMC Biomed Eng 1(1). https://doi.org/10.1186/s42490-019-0022-z

  90. Tamburro G, Stone D, Comani S (2019) Automatic removal of cardiac interference (ARCI): a new approach for EEG data. Front Neurosci 13. https://doi.org/10.3389/fnins.2019.00441

  91. Tononi G (2008) Consciousness as integrated information: a provisional manifesto. Biol Bull 215:216–242

    Article  Google Scholar 

  92. Thut G, Veniero D, Romei V, Miniussi C, Schyns P, Groß J (2011) Rhythmic TMS causes local entrainment of natural oscillatory signatures. Curr Biol 21(14):1176–1185. https://doi.org/10.1016/j.cub.2011.05.049

    Article  Google Scholar 

  93. Vishwa R et al (2020) Current research and future prospects of neuromorphic computing in artificial intelligence. IOP Conf Ser Mater Sci Eng 912:062029. https://doi.org/10.1088/1757-899X/912/6/062029

  94. Veis L, Pittner J (2014) Adiabatic state preparation study of methylene. J Chem Phys 140(21):214111. https://doi.org/10.1063/1.4880755

    Article  Google Scholar 

  95. Van Veen BD, Buckley KM (1988) Beamforming: a versatile approach to spatial filtering. IEEE Trans Biomed Eng 35(4):432–447

    Google Scholar 

  96. Vikshu V (1928) Sankhya Darshana. In: Shastri D (ed) Kashi Sanskrit Series 67. Chaukhambha Prakashan, Varanasi, India

    Google Scholar 

  97. Vicente R, Rizzuto M, Sarica C, Yamamoto K, Sadr M, Khajuria T, Fatehi M, Moien-Afshari F, Haw CS, Llinas RR, Lozano AM, Neimat JS, Zemmar A (2022) Enhanced interplay of neuronal coherence and coupling in the dying human brain. Front Aging Neurosci 14:813531. https://doi.org/10.3389/fnagi.2022.813531 (PMID: 35273490; PMCID: PMC8902637)

  98. Veluw S, Shih A, Smith E, Chen C, Schneider J, Wardlaw J, Biessels G et al (2017) Detection, risk factors, and functional consequences of cerebral microinfarcts. Lancet Neurol 16(9):730–740. https://doi.org/10.1016/s1474-4422(17)30196-5

  99. Worrell G, Gotman J (2011) High-frequency oscillations and other electrophysiological biomarkers of epilepsy: clinical studies. Biomark Med 5(5):557–566. https://doi.org/10.2217/bmm.11.74 (PMID: 22003904; PMCID: PMC3254091)

  100. Wiese W (2020) The science of consciousness does not need another theory, it needs a minimal unifying model. Neurosci Conscious 2020:niaa013

    Google Scholar 

  101. Williford K, Bennequin D, Friston K, Rudrauf D (2018) The projective consciousness model and phenomenal selfhood. Front Psychol 9:2571

    Article  Google Scholar 

  102. Winfree A (1977) Biological rhythm research: the geometry of biological time, 2nd edn. Springer, p 2001

    Google Scholar 

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Dutta, T., Bandyopadhyay, A. (2024). DDG, an Electromagnetic Version of EEG Finds Evidence of a Self-operating Mathematical Universe (SOMU) When a Human Subject Converses with an Artificial Brain. In: Emotion, Cognition and Silent Communication: Unsolved Mysteries. Studies in Rhythm Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-9334-5_5

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