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Neuroscience of Cognitive Functions: From Theory to Applications

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Handbook of Neuroengineering

Abstract

Humans are working in increasingly complex environments that place high demands on mental resources. This has motivated strong interest in characterizing the cognitive functions that contribute to human performance and capitalizing on advances in the behavioral and brain sciences to engineer effective strategies for enhancing work safety and productivity. The current chapter presents contemporary theories and principles of these cognitive functions from the perspective of psychology and neuroscience, and discusses opportunities and limitations of their applications in practical settings. Emphasis will be on five key concepts: mental workload, vigilance, mental fatigue, error detection, and creativity. Issues concerning noninvasive brain stimulation for cognitive augmentation are also discussed. With a deeper appreciation of the mechanisms underlying these cognitive functions, researchers can better identify potential avenues for developing novel ergonomic solutions.

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Abbreviations

ACC::

Anterior cingulate cortex

ADHD::

Attention-deficit hyperactivity disorder

aMCC::

Anterior mid-cingulate cortex

AOC::

Attentional operating characteristics

AUT::

Alternative Uses task

CFS::

Chronic fatigue syndrome

cTBS::

Continuous TBS

DAN::

Dorsal attentional network

dlPFC::

Dorsal lateral prefrontal cortex

dmPFC::

Dorsomedial prefrontal cortex

EEG::

Electroencephalography

ERN::

Error-related negativity

ErrPs::

Error-related potentials

FEF::

Frontal eye field

fNIRS::

functional near-infrared spectroscopy

FRN::

Feedback-related negativity

IFG::

Inferior frontal gyrus

IPS::

Intraparietal sulcus

iTBS::

Intermittent theta-burst stimulation

LC-NE::

Locus-coeruleus noradrenergic

mPFC::

Medial prefrontal cortex

NE::

Noradrenaline

NIBS::

Noninvasive brain stimulation

PCC::

Posterior cingulate cortex

Pe::

Error positivity

PFC::

Prefrontal cortex

PPC::

Posterior parietal cortex

rTMS::

Repetitive TMS

SNR::

Signal-to-noise ratio

tACS::

Transcranial alternating current stimulation

TBS::

Theta-burst stimulation

tDCS::

Transcranial direct current stimulation

tES::

Transcranial electrical stimulation

Th::

Thalamus

TMS::

Transcranial magnetic stimulation

TPJ::

Temporoparietal junction

tRNS::

Transcranial random noise stimulation

VAN::

Ventral attentional network

vlPFC::

Ventral lateral prefrontal cortex

References

  1. Cinaz, B., Arnrich, B., Marca, R., Tröster, G.: Monitoring of mental workload levels during an everyday life office-work scenario. Pers. Ubiquit. Comput. 17(2), 229–239 (2013)

    Article  Google Scholar 

  2. Baddeley, A.: Working memory. Science. 255(5044), 556–559 (1992)

    Article  Google Scholar 

  3. Diamond, A.: Executive functions. Annu. Rev. Psychol. 64, 135–168 (2013)

    Article  Google Scholar 

  4. Seeley, W.W., Menon, V., Schatzberg, A.F., Keller, J., Glover, G.H., Kenna, H., Reiss, A.L., Greicius, M.D.: Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27(9), 2349–2356 (2007)

    Article  Google Scholar 

  5. Young, M.S., Brookhuis, K.A., Wickens, C.D., Hancock, P.A.: State of science: mental workload in ergonomics. Ergonomics. 58(1), 1–17 (2015)

    Article  Google Scholar 

  6. Kahneman, D.: Attention and Effort. Prentice-Hall, Inc, Englewood Cliffs (1973)

    Google Scholar 

  7. Wickens, C.D.: Multiple resources and performance prediction. Theor. Issues Ergon. Sci. 3(2), 159–177 (2002)

    Article  Google Scholar 

  8. Sperling, G., Melchner, M.: The attention operating characteristic: examples from visual search. Science. 202(4365), 315–318 (1978)

    Article  Google Scholar 

  9. Zurowski, B., Gostomzyk, J., Grön, G., Weller, R., Schirrmeister, H., Neumeier, B., Spitzer, M., Reske, S.N., Walter, H.: Dissociating a common working memory network from different neural substrates of phonological and spatial stimulus processing. NeuroImage. 15(1), 45–57 (2002)

    Article  Google Scholar 

  10. Metzger, U., Parasuraman, R.: Automation in future air traffic management: effects of decision aid reliability on controller performance and mental workload. Hum. Factors. 47(1), 35–49 (2005)

    Article  Google Scholar 

  11. Hancock, P.: The effect of performance failure and task demand on the perception of mental workload. Appl. Ergon. 20(3), 197–205 (1989)

    Article  Google Scholar 

  12. Venables, L., Fairclough, S.H.: The influence of performance feedback on goal-setting and mental effort regulation. Motiv. Emot. 33(1), 63–74 (2009)

    Article  Google Scholar 

  13. Ericsson, K.A., Lehmann, A.C.: Expert and exceptional performance: evidence of maximal adaptation to task constraints. Annu. Rev. Psychol. 47(1), 273–305 (1996)

    Article  Google Scholar 

  14. Fisherl, C.D.: Boredom at work: a neglected concept. Hum. Relat. 46(3), 395–417 (1993)

    Article  Google Scholar 

  15. Beilock, S.L., Carr, T.H.: On the fragility of skilled performance: what governs choking under pressure? J. Exp. Psychol. Gen. 130(4), 701–725 (2001)

    Article  Google Scholar 

  16. Borghini, G., Astolfi, L., Vecchiato, G., Mattia, D., Babiloni, F.: Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neurosci. Biobehav. Rev. 44, 58–75 (2014)

    Article  Google Scholar 

  17. Karbach, J., Verhaeghen, P.: Making working memory work:a meta-analysis of executive-control and working memory training in older adults. Psychol. Sci. 25(11), 2027–2037 (2014)

    Article  Google Scholar 

  18. Schwaighofer, M., Fischer, F., Bühner, M.: Does working memory training transfer? A meta-analysis including training conditions as moderators. Educ. Psychol. 50(2), 138–166 (2015)

    Article  Google Scholar 

  19. Kee, T., Weiyan, C., Blasiak, A., Wang, P., Chong, J.K., Chen, J., Yeo, B.T.T., Ho, D., Asplund, C.L.: Harnessing CURATE.AI as a digital therapeutics platform by identifying N-of-1 learning trajectory profiles. Adv. Ther. 2(9), 1900023 (2019)

    Article  Google Scholar 

  20. Walter, C., Rosenstiel, W., Bogdan, M., Gerjets, P., Spüler, M.: Online EEG-based workload adaptation of an arithmetic learning environment. Front. Hum. Neurosci. 11, 286 (2017)

    Article  Google Scholar 

  21. Elmasry, J., Loo, C., Martin, D.: A systematic review of transcranial electrical stimulation combined with cognitive training. Restor. Neurol. Neurosci. 33(3), 263–278 (2015)

    Google Scholar 

  22. Langner, R., Eickhoff, S.B.: Sustaining attention to simple tasks: a meta-analytic review of the neural mechanisms of vigilant attention. Psychol. Bull. 139(4), 870–900 (2013)

    Article  Google Scholar 

  23. Warm, J.S., Parasuraman, R., Matthews, G.: Vigilance requires hard mental work and is stressful. Hum. Factors. 50(3), 433–441 (2008)

    Article  Google Scholar 

  24. Vossel, S., Geng, J.J., Fink, G.R.: Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist. 20(2), 150–159 (2014)

    Article  Google Scholar 

  25. Dosenbach, N.U., Visscher, K.M., Palmer, E.D., Miezin, F.M., Wenger, K.K., Kang, H.C., Burgund, E.D., Grimes, A.L., Schlaggar, B.L., Petersen, S.E.: A core system for the implementation of task sets. Neuron. 50(5), 799–812 (2006)

    Article  Google Scholar 

  26. Corbetta, M., Shulman, G.L.: Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 3(3), 201–215 (2002)

    Article  Google Scholar 

  27. Xia, M., Wang, J., He, Y.: BrainNet viewer: a network visualization tool for human brain connectomics. PLoS One. 8(7), e68910 (2013)

    Article  Google Scholar 

  28. Esterman, M., Rothlein, D.: Models of sustained attention. Curr. Opin. Psychol. 29, 174–180 (2019)

    Article  Google Scholar 

  29. Samuels, E.R., Szabadi, E.: Functional neuroanatomy of the noradrenergic locus coeruleus: its roles in the regulation of arousal and autonomic function part I: principles of functional organisation. Curr. Neuropharmacol. 6(3), 235–253 (2008)

    Article  Google Scholar 

  30. Thomson, D.R., Besner, D., Smilek, D.: A resource-control account of sustained attention: evidence from mind-wandering and vigilance paradigms. Perspect. Psychol. Sci. 10(1), 82–96 (2015)

    Article  Google Scholar 

  31. Manly, T., Robertson, I.H., Galloway, M., Hawkins, K.: The absent mind:: further investigations of sustained attention to response. Neuropsychologia. 37(6), 661–670 (1999)

    Article  Google Scholar 

  32. Kurzban, R., Duckworth, A., Kable, J.W., Myers, J.: An opportunity cost model of subjective effort and task performance. Behav. Brain Sci. 36(6), 661–679 (2013)

    Article  Google Scholar 

  33. Lim, J., Dinges, D.F.: Sleep deprivation and vigilant attention. Ann. N. Y. Acad. Sci. 1129(1), 305–322 (2008)

    Article  Google Scholar 

  34. Castellanos, F.X., Proal, E.: Large-scale brain systems in ADHD: beyond the prefrontal-striatal model. Trends Cogn. Sci. 16(1), 17–26 (2012)

    Article  Google Scholar 

  35. Abbasi, N.I., Bodala, I.P., Bezerianos, A., Yu, S., Al-Nashash, H., Thakor, N.V.: Role of multisensory stimuli in vigilance enhancement- a single trial event related potential study. In: Paper presented at the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jul (2017)

    Google Scholar 

  36. Bodala, I.P., Li, J., Thakor, N.V., Al-Nashash, H.: EEG and eye tracking demonstrate vigilance enhancement with challenge integration. Front. Hum. Neurosci. 10, 273 (2016)

    Article  Google Scholar 

  37. Nelson, J.T., McKinley, R.A., Golob, E.J., Warm, J.S., Parasuraman, R.: Enhancing vigilance in operators with prefrontal cortex transcranial direct current stimulation (tDCS). NeuroImage. 85, 909–917 (2014)

    Article  Google Scholar 

  38. Mensen, A., Gorban, C., Niklaus, M., Kuske, E., Khatami, R.: The effects of theta-burst stimulation on sleep and vigilance in humans. Front. Hum. Neurosci. 8, 420 (2014)

    Article  Google Scholar 

  39. Boksem, M.A., Tops, M.: Mental fatigue: costs and benefits. Brain Res. Rev. 59(1), 125–139 (2008)

    Article  Google Scholar 

  40. Van Der Linden, D., Frese, M., Sonnentag, S.: The impact of mental fatigue on exploration in a complex computer task: rigidity and loss of systematic strategies. Hum. Factors. 45(3), 483–494 (2003)

    Article  Google Scholar 

  41. Grier, R.A., Warm, J.S., Dember, W.N., Matthews, G., Galinsky, T.L., Szalma, J.L., Parasuraman, R.: The vigilance decrement reflects limitations in effortful attention, not mindlessness. Human Fact. 45(3), 349–359 (2003)

    Article  Google Scholar 

  42. Ampel, B.C., Muraven, M., McNay, E.C.: Mental work requires physical energy: self-control is neither exception nor exceptional. Front. Psychol. 9, 1005 (2018)

    Article  Google Scholar 

  43. Xie, L., Kang, H., Xu, Q., Chen, M.J., Liao, Y., Thiyagarajan, M., O’Donnell, J., Christensen, D.J., Nicholson, C., Iliff, J.J., Takano, T., Deane, R., Nedergaard, M.: Sleep drives metabolite clearance from the adult brain. Science. 342(6156), 373–377 (2013)

    Article  Google Scholar 

  44. Boksem, M.A., Meijman, T.F., Lorist, M.M.: Mental fatigue, motivation and action monitoring. Biol. Psychol. 72(2), 123–132 (2006)

    Article  Google Scholar 

  45. Chaudhuri, A., Behan, P.O.: Fatigue and basal ganglia. J. Neurol. Sci. 179(1–2), 34–42 (2000)

    Article  Google Scholar 

  46. Kohl, A.D., Wylie, G.R., Genova, H., Hillary, F., Deluca, J.: The neural correlates of cognitive fatigue in traumatic brain injury using functional MRI. Brain Inj. 23(5), 420–432 (2009)

    Article  Google Scholar 

  47. Walton, M.E., Rudebeck, P.H., Bannerman, D.M., Rushworth, M.F.: Calculating the cost of acting in frontal cortex. Ann. N. Y. Acad. Sci. 1104(1), 340–356 (2007)

    Article  Google Scholar 

  48. Sara, S.J., Bouret, S.: Orienting and reorienting: the locus coeruleus mediates cognition through arousal. Neuron. 76(1), 130–141 (2012)

    Article  Google Scholar 

  49. Aston-Jones, G., Cohen, J.D.: An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403–450 (2005)

    Article  Google Scholar 

  50. Joshi, S., Li, Y., Kalwani, R.M., Gold, J.I.: Relationships between pupil diameter and neuronal activity in the locus coeruleus, colliculi, and cingulate cortex. Neuron. 89(1), 221–234 (2016)

    Article  Google Scholar 

  51. Suda, M., Fukuda, M., Sato, T., Iwata, S., Song, M., Kameyama, M., Mikuni, M.: Subjective feeling of psychological fatigue is related to decreased reactivity in ventrolateral prefrontal cortex. Brain Res. 1252, 152–160 (2009)

    Article  Google Scholar 

  52. Sun, Y., Lim, J., Kwok, K., Bezerianos, A.: Functional cortical connectivity analysis of mental fatigue unmasks hemispheric asymmetry and changes in small-world networks. Brain Cogn. 85, 220–230 (2014)

    Article  Google Scholar 

  53. Harvy, J., Thakor, N., Bezerianos, A., Li, J.: Between-frequency topographical and dynamic high-order functional connectivity for driving drowsiness assessment. IEEE Trans. Neural Syst. Rehabil. Eng. 27(3), 358–367 (2019)

    Article  Google Scholar 

  54. Surawy, C., Hackmann, A., Hawton, K., Sharpe, M.: Chronic fatigue syndrome: a cognitive approach. Behav. Res. Ther. 33(5), 535–544 (1995)

    Article  Google Scholar 

  55. Wang, H., Dragomir, A., Abbasi, N.I., Li, J., Thakor, N.V., Bezerianos, A.: A novel real-time driving fatigue detection system based on wireless dry EEG. Cogn. Neurodyn. 12(4), 365–376 (2018)

    Article  Google Scholar 

  56. Wang, H., Wu, C., Li, T., He, Y., Chen, P., Bezerianos, A.: Driving fatigue classification based on fusion entropy analysis combining EOG and EEG. IEEE Access. 7, 61975–61986 (2019)

    Article  Google Scholar 

  57. Bose, R., Wang, H., Dragomir, A., Thakor, N.: Regression based continuous driving fatigue estimation: towards practical implementation. IEEE Trans. Cogn. Develop. Sys. 12(2), 323–331 (2020)

    Article  Google Scholar 

  58. Dimitrakopoulos, G.N., Kakkos, I., Dai, Z., Wang, H., Sgarbas, K., Thakor, N., Bezerianos, A., Sun, Y.: Functional connectivity analysis of mental fatigue reveals different network topological alterations between driving and vigilance tasks. IEEE Trans. Neural Syst. Rehabil. Eng. 26(4), 740–749 (2018)

    Article  Google Scholar 

  59. Hopstaken, J.F., van der Linden, D., Bakker, A.B., Kompier, M.A.: The window of my eyes: task disengagement and mental fatigue covary with pupil dynamics. Biol. Psychol. 110, 100–106 (2015)

    Article  Google Scholar 

  60. Laeng, B., Endestad, T.: Bright illusions reduce the eye’s pupil. Proc. Natl. Acad. Sci. U. S. A. 109(6), 2162–2167 (2012)

    Article  Google Scholar 

  61. Sikander, G., Anwar, S.: Driver fatigue detection systems: a review. IEEE Trans. Intell. Transp. Syst. 20(6), 2339–2352 (2018)

    Article  Google Scholar 

  62. Carter, C.S., Braver, T.S., Barch, D.M., Botvinick, M.M., Noll, D., Cohen, J.D.: Anterior cingulate cortex, error detection, and the online monitoring of performance. Science. 280(5364), 747–749 (1998)

    Article  Google Scholar 

  63. Ullsperger, M., Harsay, H.A., Wessel, J.R., Ridderinkhof, K.R.: Conscious perception of errors and its relation to the anterior insula. Brain Struct. Funct. 214(5–6), 629–643 (2010)

    Article  Google Scholar 

  64. Ham, T., Leff, A., de Boissezon, X., Joffe, A., Sharp, D.J.: Cognitive control and the salience network: an investigation of error processing and effective connectivity. J. Neurosci. 33(16), 7091–7098 (2013)

    Article  Google Scholar 

  65. Chavarriaga, R., Sobolewski, A., Millán, J.R.: Errare machinale Est: the use of error-related potentials in brain-machine interfaces. Front. Neurosci. 8, 208 (2014)

    Article  Google Scholar 

  66. Botvinick, M.M., Cohen, J.D., Carter, C.S.: Conflict monitoring and anterior cingulate cortex: an update. Trends Cogn. Sci. 8(12), 539–546 (2004)

    Article  Google Scholar 

  67. Sawyer, B.D., Karwowski, W., Xanthopoulos, P., Hancock, P.: Detection of error-related negativity in complex visual stimuli: a new neuroergonomic arrow in the practitioner’s quiver. Ergonomics. 60(2), 234–240 (2017)

    Article  Google Scholar 

  68. Loft, S., Bolland, S., Humphreys, M.S., Neal, A.: A theory and model of conflict detection in air traffic control: incorporating environmental constraints. J. Exp. Psychol. Appl. 15(2), 106–124 (2009)

    Article  Google Scholar 

  69. Pailing, P.E., Segalowitz, S.J.: The effects of uncertainty in error monitoring on associated ERPs. Brain Cogn. 56(2), 215–233 (2004)

    Article  Google Scholar 

  70. Hajcak, G., Moser, J.S., Yeung, N., Simons, R.F.: On the ERN and the significance of errors. Psychophysiology. 42(2), 151–160 (2005)

    Article  Google Scholar 

  71. Jackson, F., Nelson, B.D., Hajcak, G.: The uncertainty of errors: intolerance of uncertainty is associated with error-related brain activity. Biol. Psychol. 113, 52–58 (2016)

    Article  Google Scholar 

  72. Salazar-Gomez, A.F., DelPreto, J., Gil, S., Guenther, F.H., Rus, D.: Correcting robot mistakes in real time using EEG signals. In: Paper presented at the 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore (2017)

    Google Scholar 

  73. Zhang, H., Chavarriaga, R., Khaliliardali, Z., Gheorghe, L., Iturrate, I., d R Millán, J.: EEG-based decoding of error-related brain activity in a real-world driving task. J. Neural Eng. 12(6), 066028 (2015)

    Article  Google Scholar 

  74. Abu-Alqumsan, M., Kapeller, C., Hintermüller, C., Guger, C., Peer, A.: Invariance and variability in interaction error-related potentials and their consequences for classification. J. Neural Eng. 14(6), 066015 (2017)

    Article  Google Scholar 

  75. Jarrahi, M.H.: Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making. Bus. Horiz. 61(4), 577–586 (2018)

    Article  Google Scholar 

  76. Runco, M.A., Jaeger, G.J.: The standard definition of creativity. Creat. Res. J. 24(1), 92–96 (2012)

    Article  Google Scholar 

  77. Runco, M.A., Acar, S.: Divergent thinking as an indicator of creative potential. Creat. Res. J. 24(1), 66–75 (2012)

    Article  Google Scholar 

  78. Bose, R., Dragomir, A., Taya, F., Thakor, N., Bezerianos, A.: Role of Cross-Frequency Coupling in the Frontal and Parieto-Occipital Subnetwork during Creative Ideation. In: Paper presented at the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), San Francisco (2019)

    Google Scholar 

  79. Guilford, J.P.: Creativity: yesterday, today and tomorrow. J. Creat. Behav. 1(1), 3–14 (1967)

    Article  Google Scholar 

  80. Gilhooly, K., Fioratou, E., Anthony, S., Wynn, V.: Divergent thinking: strategies and executive involvement in generating novel uses for familiar objects. Br. J. Psychol. 98(4), 611–625 (2007)

    Article  Google Scholar 

  81. Beaty, R.E., Benedek, M., Silvia, P.J., Schacter, D.L.: Creative cognition and brain network dynamics. Trends Cogn. Sci. 20(2), 87–95 (2016)

    Article  Google Scholar 

  82. Anticevic, A., Cole, M.W., Murray, J.D., Corlett, P.R., Wang, X.-J., Krystal, J.H.: The role of default network deactivation in cognition and disease. Trends Cogn. Sci. 16(12), 584–592 (2012)

    Article  Google Scholar 

  83. Ellamil, M., Dobson, C., Beeman, M., Christoff, K.: Evaluative and generative modes of thought during the creative process. NeuroImage. 59(2), 1783–1794 (2012)

    Article  Google Scholar 

  84. Ottemiller, D.D., Elliott, C.S., Giovannetti, T.: Creativity, overinclusion, and everyday tasks. Creat. Res. J. 26(3), 289–296 (2014)

    Article  Google Scholar 

  85. Whitfield-Gabrieli, S., Thermenos, H.W., Milanovic, S., Tsuang, M.T., Faraone, S.V., McCarley, R.W., Shenton, M.E., Green, A.I., Nieto-Castanon, A., LaViolette, P.: Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc. Natl. Acad. Sci. 106(4), 1279–1284 (2009)

    Article  Google Scholar 

  86. Woodward, N.D., Rogers, B., Heckers, S.: Functional resting-state networks are differentially affected in schizophrenia. Schizophr. Res. 130(1–3), 86–93 (2011)

    Article  Google Scholar 

  87. Atchley, R.A., Strayer, D.L., Atchley, P.: Creativity in the wild: improving creative reasoning through immersion in natural settings. PLoS One. 7(12), e51474 (2012)

    Article  Google Scholar 

  88. Ritter, S.M., Dijksterhuis, A.: Creativity—the unconscious foundations of the incubation period. Front. Hum. Neurosci. 8, 215 (2014)

    Article  Google Scholar 

  89. Sio, U., Ormerod, T.: Does incubation enhance problem solving? A meta-analytic review. Psychol. Bull. 135(1), 94–120 (2009)

    Article  Google Scholar 

  90. Lebuda, I., Zabelina, D.L., Karwowski, M.: Mind full of ideas: a meta-analysis of the mindfulness–creativity link. Personal. Individ. Differ. 93, 22–26 (2016)

    Article  Google Scholar 

  91. Hasenkamp, W., Barsalou, L.: Effects of meditation experience on functional connectivity of distributed brain networks. Front. Hum. Neurosci. 6, 38 (2012)

    Article  Google Scholar 

  92. Ivancovsky, T., Kurman, J., Morio, H., Shamay-Tsoory, S.: Transcranial direct current stimulation (tDCS) targeting the left inferior frontal gyrus: effects on creativity across cultures. Soc. Neurosci. 14(3), 277–285 (2019)

    Article  Google Scholar 

  93. Fertonani, A., Miniussi, C.: Transcranial electrical stimulation: what we know and do not know about mechanisms. Neuroscientist. 23(2), 109–123 (2017)

    Article  Google Scholar 

  94. Miniussi, C., Harris, J.A., Ruzzoli, M.: Modelling non-invasive brain stimulation in cognitive neuroscience. Neurosci. Biobehav. Rev. 37(8), 1702–1712 (2013)

    Article  Google Scholar 

  95. Fitzgerald, P.B., Fountain, S., Daskalakis, Z.J.: A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition. Clin. Neurophysiol. 117(12), 2584–2596 (2006)

    Article  Google Scholar 

  96. Touge, T., Gerschlager, W., Brown, P., Rothwell, J.C.: Are the after-effects of low-frequency rTMS on motor cortex excitability due to changes in the efficacy of cortical synapses? Clin. Neurophysiol. 112(11), 2138–2145 (2001)

    Article  Google Scholar 

  97. Huang, Y.-Z., Edwards, M.J., Rounis, E., Bhatia, K.P., Rothwell, J.C.: Theta burst stimulation of the human motor cortex. Neuron. 45(2), 201–206 (2005)

    Article  Google Scholar 

  98. Wischnewski, M., Schutter, D.J.: Efficacy and time course of theta burst stimulation in healthy humans. Brain Stimul. 8(4), 685–692 (2015)

    Article  Google Scholar 

  99. Thut, G., Veniero, D., Romei, V., Miniussi, C., Schyns, P., Gross, J.: Rhythmic TMS causes local entrainment of natural oscillatory signatures. Curr. Biol. 21(14), 1176–1185 (2011)

    Article  Google Scholar 

  100. Iturrate, I., Pereira, M., Millán, J.R.: Closed-loop electrical neurostimulation: challenges and opportunities. Curr. Opin. Biomed. Eng. 8, 28–37 (2018)

    Article  Google Scholar 

  101. Filmer, H.L., Dux, P.E., Mattingley, J.B.: Applications of transcranial direct current stimulation for understanding brain function. Trends Neurosci. 37(12), 742–753 (2014)

    Article  Google Scholar 

  102. Helfrich, R.F., Schneider, T.R., Rach, S., Trautmann-Lengsfeld, S.A., Engel, A.K., Herrmann, C.S.: Entrainment of brain oscillations by transcranial alternating current stimulation. Curr. Biol. 24(3), 333–339 (2014)

    Article  Google Scholar 

  103. Thut, G., Miniussi, C., Gross, J.: The functional importance of rhythmic activity in the brain. Curr. Biol. 22, 658–663 (2012)

    Article  Google Scholar 

  104. Fröhlich, F., McCormick, D.A.: Endogenous electric fields may guide neocortical network activity. Neuron. 67(1), 129–143 (2010)

    Article  Google Scholar 

  105. Moliadze, V., Antal, A., Paulus, W.: Boosting brain excitability by transcranial high frequency stimulation in the ripple range. J. Physiol. 588(24), 4891–4904 (2010)

    Article  Google Scholar 

  106. Moliadze, V., Atalay, D., Antal, A., Paulus, W.: Close to threshold transcranial electrical stimulation preferentially activates inhibitory networks before switching to excitation with higher intensities. Brain Stimul. 5(4), 505–511 (2012)

    Article  Google Scholar 

  107. Inukai, Y., Saito, K., Sasaki, R., Tsuiki, S., Miyaguchi, S., Kojima, S., Masaki, M., Otsuru, N., Onishi, H.: Comparison of three non-invasive transcranial electrical stimulation methods for increasing cortical excitability. Front. Hum. Neurosci. 10, 668 (2016)

    Google Scholar 

  108. Terney, D., Chaieb, L., Moliadze, V., Antal, A., Paulus, W.: Increasing human brain excitability by transcranial high-frequency random noise stimulation. J. Neurosci. 28(52), 14147–14155 (2008)

    Article  Google Scholar 

  109. van der Groen, O., Wenderoth, N.: Transcranial random noise stimulation of visual cortex: stochastic resonance enhances central mechanisms of perception. J. Neurosci. 36(19), 5289–5298 (2016)

    Article  Google Scholar 

  110. Fertonani, A., Pirulli, C., Miniussi, C.: Random noise stimulation improves neuroplasticity in perceptual learning. J. Neurosci. 31(43), 15416–15423 (2011)

    Article  Google Scholar 

  111. López-Alonso, V., Cheeran, B., Río-Rodríguez, D., Fernández-del-Olmo, M.: Inter-individual variability in response to non-invasive brain stimulation paradigms. Brain Stimul. 7(3), 372–380 (2014)

    Article  Google Scholar 

  112. Sparing, R., Buelte, D., Meister, I.G., Pauš, T., Fink, G.R.: Transcranial magnetic stimulation and the challenge of coil placement: a comparison of conventional and stereotaxic neuronavigational strategies. Hum. Brain Mapp. 29(1), 82–96 (2008)

    Article  Google Scholar 

  113. Datta, A.: Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models. Front. Psych. 3, 91 (2012)

    Google Scholar 

  114. Helfrich, R.F., Knepper, H., Nolte, G., Strüber, D., Rach, S., Herrmann, C.S., Schneider, T.R., Engel, A.K.: Selective modulation of interhemispheric functional connectivity by HD-tACS shapes perception. PLoS Biol. 12(12), e1002031 (2015)

    Article  Google Scholar 

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Correspondence to Anastasios Bezerianos .

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Seet, M.S., Bezerianos, A. (2022). Neuroscience of Cognitive Functions: From Theory to Applications. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_73-2

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