Preprint / Version 1

Anatomia Nova: The Evolution and Prospects of Anatomy in the Era of Human Augmentation Technology - An Integrative Review of Structure, Function, and Ethics

##article.authors##

  • Tetsuya Sasaki Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba https://orcid.org/0000-0002-7723-4417 https://researchmap.jp/tsasak
  • Sara Kamiya Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba
  • Kenyu Nakamura Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba
  • Koki Higuchi Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba
  • Sae Sanaka Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba
  • Asumi Kubo Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba

DOI:

https://doi.org/10.51094/jxiv.921

Keywords:

Anatomy, Brain-Machine Interface, Cognitive Enhancement, Human Augmentation Technology, Sensory Augmentation

Abstract

Recent technological advances have expanded the scope of medical interventions from treating diseases to enhancing human capabilities beyond normal levels. This field of "human augmentation" aims to enhance physical and cognitive functions in healthy individuals. The development of these technologies relies heavily on a detailed understanding of neuroanatomy. This review focuses on the neuroanatomical foundations underlying key areas of human augmentation technology. Brain-computer interfaces (BCIs) require thorough knowledge of cortical layer structure and functional localization, particularly in motor and somatosensory cortices. Neuromodulation technologies depend on understanding GABAergic interneuron distribution and connectivity for controlling cortical excitatory-inhibitory balance. Sensory augmentation technologies are based on the microstructure and function of sensory organs, including the retinal layers and visual cortices for vision, cochlear structure and auditory pathways for hearing, and skin layers and sensory receptors for touch. Understanding cortico-subcortical circuits and long-range projection pathways contributes to more precise neuromodulation techniques, such as those targeting higher cognitive functions through the prefrontal cortex-basal ganglia-thalamus circuit. The integration of insights from neuroscience, engineering, and materials science drives these developments. Future advancements in nanoscale neuroanatomy may lead to more effective augmentation technologies, such as more natural BCIs and sophisticated neuromodulation techniques. Understanding neural plasticity mechanisms is crucial for long-term stable augmentation. While these technologies promise to maximize human potential and improve quality of life, their development necessitates a comprehensive approach that considers ethical and social implications.

Conflicts of Interest Disclosure

There are no conflicts of interest to disclose.

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Author Biographies

Kenyu Nakamura, Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba

College of Medicine, School of Medicine and Health Sciences, University of Tsukuba

Koki Higuchi, Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba

College of Medicine, School of Medicine and Health Sciences, University of Tsukuba

Sae Sanaka, Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba

College of Medicine, School of Medicine and Health Sciences, University of Tsukuba

Asumi Kubo, Laboratory of Anatomy and Neuroscience, Department of Biomedical Sciences, Institute of Medicine, University of Tsukuba

College of Biology, School of Life and Environmental Sciences, University of Tsukuba

References

Steinert S, Friedrich O. Wired emotions: Ethical issues of affective brain-computer interfaces. Sci Eng Ethics. 2020 Feb;26(1):351–67.

Cinel C, Valeriani D, Poli R. Neurotechnologies for human cognitive augmentation: Current state of the art and future prospects. Front Hum Neurosci. 2019 Jan 31;13:13.

Shaw DB. Streets for cyborgs. Space Cult. 2015 Aug;18(3):230–42.

Kumar D. Evolution and terraformation in mars using cyborgs. In: AIAA SPACE 2009 Conference & Exposition [Internet]. Reston, Virigina: American Institute of Aeronautics and Astronautics; 2009. Available from: http://dx.doi.org/10.2514/6.2009-6576

Ogawa S, Lee TM, Nayak AS, Glynn P. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med. 1990 Apr;14(1):68–78.

Smith K. Brain imaging: fMRI 2.0. Nature. 2012 Apr 4;484(7392):24–6.

Human Augmentation: Past, Present, and Future. Human Augmentation: Past, Present, and Future International Journal of Environmental Research and Public Health.

Uehara A, Sankai Y. Basic study on cybernic interface for amyotrophic lateral sclerosis patients to perform daily living tasks by transiting seamlessly between cyberspace and physical space. In: 2024 IEEE/SICE International Symposium on System Integration (SII) [Internet]. IEEE; 2024. Available from: http://dx.doi.org/10.1109/sii58957.2024.10417447

Dresler M, Sandberg A, Ohla K, Bublitz C, Trenado C, Mroczko-Wąsowicz A, et al. Non-pharmacological cognitive enhancement. Neuropharmacology. 2013 Jan;64:529–43.

Kristjánsson Á, Moldoveanu A, Jóhannesson ÓI, Balan O, Spagnol S, Valgeirsdóttir VV, et al. Designing sensory-substitution devices: Principles, pitfalls and potential1. Restor Neurol Neurosci. 2016 Sep 21;34(5):769–87.

Judaš M, Cepanec M, Sedmak G. Brodmann’s map of the human cerebral cortex — or Brodmann’s maps? Transl Neurosci. 2012 Mar 1;3(1):67–74.

Zilles K. Brodmann: a pioneer of human brain mapping-his impact on concepts of cortical organization. Brain. 2018 Nov 1;141(11):3262–78.

Hikosaka O, Nakamura K, Nakahara H. Basal ganglia orient eyes to reward. J Neurophysiol. 2006 Feb;95(2):567–84.

Heimer L, Van Hoesen GW, Trimble M, Zahm DS. Anatomy of Neuropsychiatry: The New Anatomy of the Basal Forebrain and Its Implications for Neuropsychiatric Illness. Academic Press; 2007.

Grillner S, Robertson B. The basal ganglia over 500 million years. Curr Biol. 2016 Oct;26(20):R1088–100.

Lozano AM, Lipsman N, Bergman H, Brown P, Chabardes S, Chang JW, et al. Deep brain stimulation: current challenges and future directions. Nat Rev Neurol. 2019 Mar;15(3):148–60.

Ienca M, Andorno R. Towards new human rights in the age of neuroscience and neurotechnology. Life Sci Soc Policy [Internet]. 2017 Dec;13(1). Available from: http://dx.doi.org/10.1186/s40504-017-0050-1

Dayan E, Censor N, Buch ER, Sandrini M, Cohen LG. Noninvasive brain stimulation: from physiology to network dynamics and back. Nat Neurosci. 2013 Jul;16(7):838–44.

Spruston N, Johnston D. Out of control in the dendrites. Nat Neurosci. Springer Science and Business Media LLC; 2008 Jul;11(7):733–4.

Spruston N. Neuroscience: strength in numbers. Nature. Springer Science and Business Media LLC; 2008 Mar 27;452(7186):420–1.

Radman T, Ramos RL, Brumberg JC, Bikson M. Role of cortical cell type and morphology in subthreshold and suprathreshold uniform electric field stimulation in vitro. Brain Stimul. 2009 Oct;2(4):215–28, 228.e1-3.

Opitz A, Windhoff M, Heidemann RM, Turner R, Thielscher A. How the brain tissue shapes the electric field induced by transcranial magnetic stimulation. Neuroimage. 2011 Oct 1;58(3):849–59.

Thielscher A, Opitz A, Windhoff M. Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation. Neuroimage. 2011 Jan 1;54(1):234–43.

Alekseichuk I, Falchier AY, Linn G, Xu T, Milham MP, Schroeder CE, et al. Electric field dynamics in the brain during multi-electrode transcranial electric stimulation. Nat Commun. 2019 Jun 12;10(1):2573.

Huang Y, Liu AA, Lafon B, Friedman D, Dayan M, Wang X, et al. Correction: Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation. Elife [Internet]. 2018 Feb 15;7. Available from: http://dx.doi.org/10.7554/eLife.35178

Huang Y, Liu AA, Lafon B, Friedman D, Dayan M, Wang X, et al. Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation. Elife [Internet]. 2017 Feb 7;6. Available from: http://dx.doi.org/10.7554/elife.18834

Kubota Y, Kondo S, Nomura M, Hatada S, Yamaguchi N, Mohamed AA, et al. Functional effects of distinct innervation styles of pyramidal cells by fast spiking cortical interneurons. Elife [Internet]. 2015 Jul 4;4. Available from: http://dx.doi.org/10.7554/eLife.07919

Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. Interneurons of the neocortical inhibitory system. Nat Rev Neurosci. 2004 Oct;5(10):793–807.

Yizhar O, Fenno LE, Prigge M, Schneider F, Davidson TJ, O’Shea DJ, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011 Jul 27;477(7363):171–8.

Barker AT, Jalinous R, Freeston IL. Non-invasive magnetic stimulation of human motor cortex. Lancet. 1985 May;325(8437):1106–7.

Cardin JA, Carlén M, Meletis K, Knoblich U, Zhang F, Deisseroth K, et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature. 2009 Jun 4;459(7247):663–7.

Alexander G. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu Rev Neurosci. 1986 Jan 1;9(1):357–81.

Lozano AM, Lipsman N. Probing and regulating dysfunctional circuits using deep brain stimulation. Neuron. 2013 Feb 6;77(3):406–24.

Ahmari SE, Spellman T, Douglass NL, Kheirbek MA, Simpson HB, Deisseroth K, et al. Repeated cortico-striatal stimulation generates persistent OCD-like behavior. Science. 2013 Jun 7;340(6137):1234–9.

Hornung J-P. The human raphe nuclei and the serotonergic system. J Chem Neuroanat. 2003 Dec;26(4):331–43.

Sara SJ, Bouret S. Orienting and reorienting: the locus coeruleus mediates cognition through arousal. Neuron. 2012 Oct 4;76(1):130–41.

Roth BL. DREADDs for neuroscientists. Neuron. 2016 Feb 17;89(4):683–94.

Herr H. Exoskeletons and orthoses: classification, design challenges and future directions. J Neuroeng Rehabil. 2009 Jun 18;6(1):21.

Pons JL. Wearable Robots. 1st ed. Nashville, TN: John Wiley & Sons; 2008. 358 p.

Dollar AM, Herr H. Lower extremity exoskeletons and active orthoses: Challenges and state-of-the-art. IEEE Trans Robot. 2008 Feb;24(1):144–58.

Perry JC, Rosen J, Burns S. Upper-limb powered exoskeleton design. IEEE ASME Trans Mechatron. 2007 Aug;12(4):408–17.

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences.

Zajac FE. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng. 1989;17(4):359–411.

Prochazka A, Yakovenko S. Predictive and reactive tuning of the locomotor CPG. Integr Comp Biol. 2007 Oct;47(4):474–81.

Farina D, Jiang N, Rehbaum H, Holobar A, Graimann B, Dietl H, et al. The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges. IEEE Trans Neural Syst Rehabil Eng. 2014 Jul;22(4):797–809.

Kuiken TA, Li G, Lock BA, Lipschutz RD, Miller LA, Stubblefield KA, et al. Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. JAMA. 2009 Feb 11;301(6):619–28.

Tagliamonte NL, Sergi F, Carpino G, Accoto D, Guglielmelli E. Design of a variable impedance differential actuator for wearable robotics applications. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems [Internet]. IEEE; 2010. Available from: http://dx.doi.org/10.1109/iros.2010.5649982

Reinkensmeyer DJ, Boninger ML. Technologies and combination therapies for enhancing movement training for people with a disability. J Neuroeng Rehabil. 2012 Mar 30;9(1):17.

Zhao H, O’Brien K, Li S, Shepherd RF. Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides. Sci Robot. 2016 Dec 6;1(1):eaai7529.

Merabet LB, Pascual-Leone A. Neural reorganization following sensory loss: the opportunity of change. Nat Rev Neurosci. 2010 Jan;11(1):44–52.

Weiland JD, Humayun MS. Retinal prosthesis. IEEE Trans Biomed Eng. 2014 May;61(5):1412–24.

Wilson BS, Dorman MF. Cochlear implants: a remarkable past and a brilliant future. Hear Res. 2008 Aug;242(1–2):3–21.

Beyond sensory substitution-learning the sixth sense. Journal of Neural Engineering.

Maidenbaum S, Abboud S, Amedi A. Sensory substitution: closing the gap between basic research and widespread practical visual rehabilitation. Neurosci Biobehav Rev. 2014 Apr;41:3–15.

Bach-y-Rita P, W Kercel S. Sensory substitution and the human-machine interface. Trends Cogn Sci. 2003 Dec;7(12):541–6.

Clark A. Natural-born cyborgs. New York, NY: Oxford University Press; 2004. 240 p.

D’Esposito M, Postle BR. The cognitive neuroscience of working memory. Annu Rev Psychol. 2015 Jan 3;66(1):115–42.

Brunoni AR, Vanderhasselt M-A. Working memory improvement with non-invasive brain stimulation of the dorsolateral prefrontal cortex: a systematic review and meta-analysis. Brain Cogn. 2014 Apr;86:1–9.

Rolls ET. The orbitofrontal cortex and emotion in health and disease, including depression. Neuropsychologia. 2019 May;128:14–43.

Bartsch T, Wulff P. The hippocampus in aging and disease: From plasticity to vulnerability. Neuroscience. 2015 Nov 19;309:1–16.

Ranganath C, Ritchey M. Two cortical systems for memory-guided behaviour. Nat Rev Neurosci. 2012 Oct;13(10):713–26.

Hikosaka O, Kim HF, Amita H, Yasuda M, Isoda M, Tachibana Y, et al. Direct and indirect pathways for choosing objects and actions. Eur J Neurosci. 2019 Mar;49(5):637–45.

Haber SN. Corticostriatal circuitry. Dialogues Clin Neurosci. 2016 Mar;18(1):7–21.

Schultz W. Dopamine reward prediction error coding. Dialogues Clin Neurosci. 2016 Mar;18(1):23–32.

Helfrich RF, Schneider TR, Rach S, Trautmann-Lengsfeld SA, Engel AK, Herrmann CS. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr Biol. 2014 Feb 3;24(3):333–9.

Ros T, Enriquez-Geppert S, Zotev V, Young KD, Wood G, Whitfield-Gabrieli S, et al. Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain. 2020 Jun 1;143(6):1674–85.

Chi RP, Snyder AW. Brain stimulation enables the solution of an inherently difficult problem. Neurosci Lett. 2012 May 2;515(2):121–4.

Zmigrod S, Colzato LS, Hommel B. Stimulating creativity: Modulation of convergent and divergent thinking by transcranial direct current stimulation (tDCS). Creat Res J. 2015 Oct 2;27(4):353–60.

Fecteau S, Knoch D, Fregni F, Sultani N, Boggio P, Pascual-Leone A. Diminishing risk-taking behavior by modulating activity in the prefrontal cortex: a direct current stimulation study. J Neurosci. 2007 Nov 14;27(46):12500–5.

Pessoa L. A network model of the emotional brain. Trends Cogn Sci. 2017 May;21(5):357–71.

Farah MJ, Smith ME, Ilieva I, Hamilton RH. Cognitive enhancement. Wiley Interdiscip Rev Cogn Sci. 2014 Jan;5(1):95–103.

Farah MJ. NEUROSCIENCE. The unknowns of cognitive enhancement. Science. 2015 Oct 23;350(6259):379–80.

Craddock RC, Jbabdi S, Yan C-G, Vogelstein JT, Castellanos FX, Di Martino A, et al. Imaging human connectomes at the macroscale. Nat Methods. 2013 Jun;10(6):524–39.

Alivisatos AP, Andrews AM, Boyden ES, Chun M, Church GM, Deisseroth K, et al. Nanotools for neuroscience and brain activity mapping. ACS Nano. 2013 Mar 26;7(3):1850–66.

Helmstaedter M. Cellular-resolution connectomics: challenges of dense neural circuit reconstruction. Nat Methods. 2013 Jun;10(6):501–7.

Moro C, Štromberga Z, Raikos A, Stirling A. The effectiveness of virtual and augmented reality in health sciences and medical anatomy. Anat Sci Educ. 2017 Nov;10(6):549–59.

Deisseroth K. Optogenetics: 10 years of microbial opsins in neuroscience. Nat Neurosci. 2015 Sep;18(9):1213–25.

Toga AW, Thompson PM, Mori S, Amunts K, Zilles K. Towards multimodal atlases of the human brain. Nat Rev Neurosci. 2006 Dec;7(12):952–66.

Pascual-Leone A, Freitas C, Oberman L, Horvath JC, Halko M, Eldaief M, et al. Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI. Brain Topogr. 2011 Oct;24(3–4):302–15.

Herr H, Dennis RG. A swimming robot actuated by living muscle tissue. J Neuroeng Rehabil. 2004 Oct 28;1(1):6.

Egan MF, Kojima M, Callicott JH, Goldberg TE, Kolachana BS, Bertolino A, et al. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell. 2003 Jan 24;112(2):257–69.

Amunts K, Hawrylycz MJ, Van Essen DC, Van Horn JD, Harel N, Poline J-B, et al. Interoperable atlases of the human brain. Neuroimage. 2014 Oct 1;99:525–32.

Posted


Submitted: 2024-10-01 00:53:19 UTC

Published: 2024-10-07 05:29:21 UTC
Section
Biology, Life Sciences & Basic Medicine