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Haptics-mediated approaches for enhancing sustained attention: framework and challenges

Abstract

Sustained attention is essential in the daily human activities of perception, manipulation, and locomotion. An improvement in sustained attention exhibits potential impacts in several scenarios, including the treatment of mental disorders, such as the attention-deficit/hyperactivity disorder, and the training of certain professionals, such as aircraft pilots, who work under environments with heavy cognitive loads. In this study, we review the haptics-mediated sustained attention-training approaches from the afferent and efferent perspectives based on the bidirectional information flow in the haptic channel. Subsequently, the feasibility of modulating and enhancing attention via the haptic channel is analyzed based on the studies that have investigated the correlation between attention and the afferent/efferent pathways of the haptic channel. We identify several research questions, including how to design diverse haptic training tasks via the afferent and/or efferent pathways and which adaptive strategies can be used to adjust the difficulty levels of haptic training tasks to ensure user engagement. Furthermore, we examine the behavioral and biological evidence that can be used to validate the training efficacy, the manner in which the neural mechanisms underlying the attention-enhancing process can be understood, and the effective variables that can be attributed to the near- and far-transfer effects. In addition, we discuss the difficulties associated with the development of novel haptic technologies. In this study, we intend to investigate the potential impact of haptic stimuli on neuroplasticity and to promote the study of haptics-mediated sustained attention training.

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References

  1. 1

    Raz A, Buhle J. Typologies of attentional networks. Nat Rev Neurosci, 2006, 7: 367–379

  2. 2

    Medaglia J D, Zurn P, Sinnott-Armstrong W, et al. Mind control as a guide for the mind. Nat Hum Behav, 2017, 1: 0119

  3. 3

    Posner M I, Petersen S E. The attention system of the human brain. Annu Rev Neurosci, 1990, 13: 25–42

  4. 4

    Mirsky A F, Anthony B J, Duncan C C, et al. Analysis of the elements of attention: a neuropsychological approach. Neuropsychol Rev, 1991, 2: 109–145

  5. 5

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

  6. 6

    Fan J, McCandliss B D, Sommer T, et al. Testing the efficiency and independence of attentional networks. J Cogn Neurosci, 2002, 14: 340–347

  7. 7

    Killingsworth M A, Gilbert D T. A wandering mind is an unhappy mind. Science, 2010, 330: 932

  8. 8

    Tang Y Y, Posner M I. Attention training and attention state training. Trends Cogn Sci, 2009, 13: 222–227

  9. 9

    Anguera J A, Boccanfuso J, Rintoul J L, et al. Video game training enhances cognitive control in older adults. Nature, 2013, 501: 97–101

  10. 10

    Michel J A, Mateer C A. Attention rehabilitation following stroke and traumatic brain injury. Eura Medicophys, 2006, 42: 59–67

  11. 11

    Virk S, Williams T, Brunsdon R, et al. Cognitive remediation of attention deficits following acquired brain injury: a systematic review and meta-analysis. Neuro Rehabil, 2015, 36: 367–377

  12. 12

    Sohlberg M M, McLaughlin K A, Pavese A, et al. Evaluation of attention process training and brain injury education in persons with acquired brain injury. J Clin Exp Neuropsychol, 2000, 22: 656–676

  13. 13

    Edkins G D, Pollock C M. The influence of sustained attention on Railway accidents. Accid Anal Prev, 1997, 29: 533–539

  14. 14

    Petrilli R M, Roach G D, Dawson D, et al. The sleep, subjective fatigue, and sustained attention of commercial airline pilots during an international pattern. Chronobiol Int, 2006, 23: 1357–1362

  15. 15

    Roach G D, Petrilli R M A, Dawson D, et al. Impact of layover length on sleep, subjective fatigue levels, and sustained attention of long-haul airline pilots. Chronobiol Int, 2012, 29: 580–586

  16. 16

    Mackenzie A K, Harris J M. Visual attention and driving: how to measure it and how to train it. i-Perception, 2014, 5: 477

  17. 17

    Diamond A, Barnett W S, Thomas J, et al. Preschool program improves cognitive control. Science, 2007, 318: 1387–1388

  18. 18

    Tang Y Y. Exploring the Brain, Optimizing the Life. Beijing: Science Press, 2009

  19. 19

    Tang Y Y. Multi-intelligence and Unfolding the Full Potentials of Brain (in Chinese). Dalian: Dalian University of Technology Press, 2007

  20. 20

    Hasenkamp W, Wilson-Mendenhall C D, Duncan E, et al. Mind wandering and attention during focused meditation: a fine-grained temporal analysis of fluctuating cognitive states. Neuro Image, 2012, 59: 750–760

  21. 21

    Mrazek M D, Franklin M S, Phillips D T, et al. Mindfulness training improves working memory capacity and GRE performance while reducing mind wandering. Psychol Sci, 2013, 24: 776–781

  22. 22

    Fu M, Zuo Y. Experience-dependent structural plasticity in the cortex. Trends Neurosci, 2011, 34: 177–187

  23. 23

    University of Oregon. Body-mind meditation boosts performance, reduces stress. ScienceDaily. 2007, October 9. www.sciencedaily.com/releases/2007/10/071008193437.htm

  24. 24

    Ospina M B, Bond K, Karkhaneh M, et al. Meditation practices for health: state of the research. Evidence Report/Technol Assessment, 2007, 155: 1–263

  25. 25

    Tang Y Y, Ma Y H, Wang J, et al. Short-term meditation training improves attention and self-regulation. Proc Natl Acad Sci USA, 2007, 104: 17152–17156

  26. 26

    Tang Y Y. Mechanism of integrative body-mind training. Neurosci Bull, 2011, 27: 383–388

  27. 27

    Kerr C E, Sacchet M D, Lazar S W, et al. Mindfulness starts with the body: somatosensory attention and top-down modulation of cortical alpha rhythms in mindfulness meditation. Front Hum Neurosci, 2013, 7: 12

  28. 28

    Tang Y Y, Hölzel B K, Posner M I. The neuroscience of mindfulness meditation. Nat Rev Neurosci, 2015, 16: 213–225

  29. 29

    Lutz A, Slagter H A, Rawlings N B, et al. Mental training enhances attentional stability: neural and behavioral evidence. J Neurosci, 2009, 29: 13418–13427

  30. 30

    Khoury B, Lecomte T, Fortin G, et al. Mindfulness-based therapy: a comprehensive meta-analysis. Clin Psychol Rev, 2013, 33: 763–771

  31. 31

    Bavelier D, Green C S, Davidson R J, et al. A National Science Foundation Report. Workshop on Interactive Media, Attention, and Well-Being, 2012

  32. 32

    Green C S, Bavelier D. Learning, attentional control, and action video games. Curr Biol, 2012, 22: R197–R206

  33. 33

    Latham A J, Patston L L M, Tippett L J. The virtual brain: 30 years of video-game play and cognitive abilities. Front Psychol, 2013, 4: 1–10

  34. 34

    Montani V, de Filippo de Grazia M, Zorzi M. A new adaptive videogame for training attention and executive functions: design principles and initial validation. Front Psychol, 2014, 5: 409

  35. 35

    Green C S, Bavelier D. Action video game modifies visual selective attention. Nature, 2003, 423: 534–537

  36. 36

    Franceschini S, Gori S, Ruffino M, et al. Action video games make dyslexic children read better. Curr Biol, 2013, 23: 462–466

  37. 37

    Taya F, Sun Y, Babiloni F, et al. Brain enhancement through cognitive training: a new insight from brain connectome. Front Syst Neurosci, 2015, 9: 1–19

  38. 38

    Rizzo A A, Buckwalter J G, Bowerly T, et al. The virtual classroom: a virtual reality environment for the assessment and rehabilitation of attention deficits. Cyber Psychol Behav, 2000, 3: 483–499

  39. 39

    Cho B H, Ku J, Jang D P, et al. The effect of virtual reality cognitive training for attention enhancement. Cyber Psychol Behav, 2002, 5: 129–137

  40. 40

    Sherlin L H, Arns M, Lubar J, et al. Neurofeedback and basic learning theory: implications for research and practice. J Neurother, 2011, 15: 292–304

  41. 41

    Sitaram R, Ros T, Stoeckel L, et al. Closed-loop brain training: the science of neurofeedback. Nat Rev Neurosci, 2017, 18: 86–100

  42. 42

    Sulzer J, Haller S, Scharnowski F, et al. Real-time fMRI neurofeedback: progress and challenges. Neuroimage, 2013, 76: 386–399

  43. 43

    Reiner M, Gruzelier J, Bamidis P D, et al. The science of neurofeedback: learnability and effects. Neuroscience, 2018, 378: 1–10

  44. 44

    Gruzelier J H. EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci Biobehaval Rev, 2014, 44: 124–141

  45. 45

    Khong A, Lin J, Thomas K P, et al. BCI based multi-player 3-D game control using EEG for enhancing attention and memory. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, 2014. 1847–1852

  46. 46

    de Bettencourt M T, Cohen J D, Lee R F, et al. Closed-loop training of attention with real-time brain imaging. Nat Neurosci, 2015, 18: 470–475

  47. 47

    Shibata K, Watanabe T, Sasaki Y, et al. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science, 2011, 334: 1413–1415

  48. 48

    Sohlberg M M, Mateer C A. Introduction to Cognitive Rehabilitation: Theory and Practice. New York: Guilford Press, 1989. 414

  49. 49

    Dvorkin A Y, Ramaiya M, Larson E B, et al. A “virtually minimal” visuo-haptic training of attention in severe traumatic brain injury. J Neuroeng Rehabil, 2013, 10: 92

  50. 50

    Sohlberg M M, Avery J, Kennedy M, et al. Practice guidelines for direct attention training. J Med Speech Lang Pathol, 2003, 11: XIX–XLII

  51. 51

    Barker-Collo S L, Feigin V L, Lawes C M M, et al. Reducing attention deficits after stroke using attention process training: a randomized controlled trial. Stroke, 2009, 40: 3293–3298

  52. 52

    Huang T L, Charyton C. A comprehensive review of the psychological effects of brainwave entrainment. Altern Ther Health Med, 2008, 14: 38–50

  53. 53

    Jiang L J, Guan C T, Zhang H H, et al. Brain computer interface based 3D game for attention training and rehabilitation. In: Proceedings of the 6th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2011. 124–127

  54. 54

    Cover T M, Thomas J A. Elements of Information Theory. New York: Wiley, 2006

  55. 55

    Utz K S, Dimova V, Oppenländer K, et al. Electrified minds: transcranial direct current stimulation (tDCS) and galvanic vestibular stimulation (GVS) as methods of non-invasive brain stimulation in neuropsychology-a review of current data and future implications. Neuropsychologia, 2010, 48: 2789–2810

  56. 56

    Hamilton R, Messing S, Chatterjee A. Rethinking the thinking cap: ethics of neural enhancement using noninvasive brain stimulation. Neurology, 2011, 76: 187–193

  57. 57

    Grunwald M. Human Haptic Perception: Basics and Applications. Basel: Birkhauser, 2008

  58. 58

    Körding K P, Wolpert D M. Bayesian integration in sensorimotor learning. Nature, 2004, 427: 244–247

  59. 59

    Andersen P A. Haptic perception in the human foetus. In: Human Haptic Perception: Basics and Applications. Basel: Birkhäuser, 2008. 149–154

  60. 60

    Pispa J, Thesleff I. Mechanisms of ectodermal organogenesis. Dev Biol, 2003, 262: 195–205

  61. 61

    van Erp J B F, Brouwer A M. Touch-based brain computer interfaces: state of the art. In: Proceedings of IEEE Haptics Symposium, 2014. 397–401

  62. 62

    Meng F, Spence C. Tactile warning signals for in-vehicle systems. Accident Anal Prev, 2015, 75: 333–346

  63. 63

    Locher P J. Use of haptic training to modify impulse and attention control deficits of learning disabled children. J Learn Disabil, 1985, 18: 89–93

  64. 64

    Young J J, Tan H Z, Gray R. Validity of haptic cues and Its effect on priming visual spatial attention. In: Proceedings of the 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. 166–170

  65. 65

    Halperin J M, Marks D J, Bedard A C V, et al. Training executive, attention, and motor skills: a proof-of-concept study in preschool children with ADHD. J Atten Disord, 2013, 17: 711–721

  66. 66

    Yang X X, Wang D X, Zhang Y R. An adaptive strategy for an immersive visuo-haptic attention training game. In: Proceedings of the 10th International Conference on Haptics: Perception, Devices, Control, and Applications, London, 2016. 441–451

  67. 67

    Lederman S J, Klatzky R L. Haptic identification of common objects: effects of constraining the manual exploration process. Percept Psychophys, 2004, 66: 618–628

  68. 68

    Klatzky R L, Loomis J M, Lederman S J, et al. Haptic identification of objects and their depictions. Percept Psychophys, 1993, 54: 170–178

  69. 69

    Hannaford B, Okamura A M. Haptics. In: Springer Handbook of Robotics. Berlin: Springer, 2008. 719–739

  70. 70

    Will U, Berg E. Brain wave synchronization and entrainment to periodic acoustic stimuli. Neurosci Lett, 2007, 424: 55–60

  71. 71

    Patrick G J. Improved neuronal regulation in ADHD. J Neurother, 1996, 1: 27–36

  72. 72

    Lane J D, Kasian S J, Owens J E, et al. Binaural auditory beats affect vigilance performance and mood. Physiol Behav, 1998, 63: 249–252

  73. 73

    Nam Y, Cichocki A, Choi S. Common spatial patterns for steady-state somatosensory evoked potentials. In: Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013. 2255–2258

  74. 74

    Ahn S, Kim K, Jun S C. Steady-state somatosensory evoked potential for brain-computer interface-present and future. Front Hum Neurosci, 2016, 9: 1–6

  75. 75

    Snyder A Z. Steady-state vibration evoked potentials: description of technique and characterization of responses. Electroencephal Clin Neurophysiol/Evoked Potentials Sect, 1992, 84: 257–268

  76. 76

    Kelly E F, Folger S E. EEG evidence of stimulus-directed response dynamics in human somatosensory cortex. Brain Res, 1999, 815: 326–336

  77. 77

    Wang D X, Xu M, Zhang Y R, et al. Preliminary study on haptic-stimulation based brainwave entrainment. In: Proceedings of 2013 IEEE World Haptics Conference (WHC), 2013. 565–570

  78. 78

    Zhang S S, Wang D X, Afzal N, et al. Rhythmic haptic stimuli improve short-term attention. IEEE Trans Haptics, 2016, 9: 437–442

  79. 79

    Neuper C, Wortz M, Pfurtscheller G. ERD/ERS patterns reflecting sensorimotor activation and deactivation. Prog Brain Res, 2006, 159: 211–222

  80. 80

    Anderson J R. Cognitive Psychology and Its Implications. New York: Worth Publishers, 2013

  81. 81

    Ganesan S. Sensory Motor Rhythm Neurofeedback Training. Lambert Academic Publishing, 2012

  82. 82

    Choi S, Kuchenbecker K J. Vibrotactile display: perception, technology, and applications. Proc IEEE, 2013, 101: 2093–2104

  83. 83

    Pacchierotti C, Sinclair S, Solazzi M, et al. Wearable haptic systems for the fingertip and the hand: taxonomy, review, and perspectives. IEEE Trans Haptics, 2017, 10: 580–600

  84. 84

    Bark K, Wheeler J, Shull P, et al. Rotational skin stretch feedback: a wearable haptic display for motion. IEEE Trans Haptics, 2010, 3: 166–176

  85. 85

    Manasrah A, Crane N, Guldiken R, et al. Perceived cooling using asymmetrically-applied hot and cold stimuli. IEEE Trans Haptics, 2017, 10: 75–83

  86. 86

    Salzer Y, Oron-Gilad T, Henik A. Evaluation of the attention network test using vibrotactile stimulations. Behav Res, 2015, 47: 395–408

  87. 87

    Spence C, Gallace A. Recent developments in the study of tactile attention. Canadian J Exp Psychol/Revue Canadienne de Psychol Exp, 2007, 61: 196–207

  88. 88

    Zheng Y, Morrell J B. Haptic actuator design parameters that influence affect and attention. In: Proceedings of IEEE Haptics Symposium, 2012. 463–470

  89. 89

    Lakatos S, Shepard R N. Time-distance relations in shifting attention between locations on one’s body. Percept Psychophys, 1997, 59: 557–566

  90. 90

    Spence C, Ho C. Tactile and multisensory spatial warning signals for drivers. IEEE Trans Haptics, 2008, 1: 121–129

  91. 91

    Ho C, Reed N, Spence C. Assessing the effectiveness of “intuitive” vibrotactile warning signals in preventing front-to-rear-end collisions in a driving simulator. Accident Anal Prevent, 2006, 38: 988–996

  92. 92

    Cavina-Pratesi C, Valyear K F, Culham J C, et al. Dissociating arbitrary stimulus-response mapping from movement planning during preparatory period: evidence from event-related functional magnetic resonance imaging. J Neurosci, 2006, 26: 2704–2713

  93. 93

    Bennike I H, Wieghorst A, Kirk U. Online-based mindfulness training reduces behavioral markers of mind wandering. J Cogn Enhanc, 2017, 1: 172–181

  94. 94

    Petersen S E, Posner M I. The attention system of the human brain: 20 years after. Annu Rev Neurosci, 2012, 35: 73–89

  95. 95

    Arnell K M, Joliceur P. The attentional blink across stimulus modalities: evidence for central processing limitations. J Exp Psychol-Human Percept Perform, 1999, 25: 630–648

  96. 96

    Sathian K. Visual cortical activity during tactile perception in the sighted and the visually deprived. Dev Psychobiol, 2005, 46: 279–286

  97. 97

    Costantini M, Urgesi C, Galati G, et al. Haptic perception and body representation in lateral and medial occipito-temporal cortices. Neuropsychologia, 2011, 49: 821–829

  98. 98

    Johnsson M, Balkenius C. Neural network models of haptic shape perception. Robot Autonom Syst, 2007, 55: 720–727

  99. 99

    Wang D, Zhang Y, Yang X, et al. Force control tasks with pure haptic feedback promote short-term focused attention. IEEE Trans Haptics, 2014, 7: 467–476

  100. 100

    Spence C, Pavani F, Driver J. Crossmodal links between vision and touch in covert endogenous spatial attention. J Exp Psychol-Human Percept Perform, 2000, 26: 1298–1319

  101. 101

    Chica A B, Sanabria D, Lupiáñez J, et al. Comparing intramodal and crossmodal cuing in the endogenous orienting of spatial attention. Exp Brain Res, 2007, 179: 353–364

  102. 102

    Gerber L H, Narber C G, Vishnoi N, et al. The feasibility of using haptic devices to engage people with chronic traumatic brain injury in virtual 3D functional tasks. J Neuroeng Rehabil, 2014, 11: 15

  103. 103

    Larson E B, Ramaiya M, Zollman F S, et al. Tolerance of a virtual reality intervention for attention remediation in persons with severe TBI. Brain Injury, 2011, 25: 274–281

  104. 104

    Lohse K R. The influence of attention on learning and performance: pre-movement time and accuracy in an isometric force production task. Human Movement Sci, 2012, 31: 12–25

  105. 105

    Chen Y Y, Liaw L J, Liang J M, et al. A pilot study: force control on ball throwing in children with attention deficit hyperactivity disorder. Procedia Eng, 2011, 13: 328–333

  106. 106

    Barkley R A. Attention Deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment. New York: Guilford Press, 1990

  107. 107

    Peng C, Wang D, Zhang Y, et al. A visuo-haptic attention training game with dynamic adjustment of difficulty. IEEE Access, 2019, 7: 68878–68891

  108. 108

    Lohse K R, Jones M, Healy A F, et al. The role of attention in motor control. J Exp Psychol-General, 2014, 143: 930–948

  109. 109

    Niksirat K S, Silpasuwanchai C, Ahmed M M H, et al. A framework for interactive mindfulness meditation using attention-regulation process. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017. 2672–2684

  110. 110

    Majorek M, Tüchelmann T, Heusser P. Therapeutic eurythmy-movement therapy for children with attention deficit hyperactivity disorder (ADHD): a pilot study. Complement Therapies Nursing Midwifery, 2004, 10: 46–53

  111. 111

    Ozbay E A, Cansu I, Senyer S, et al. An ERP study on effects of complex motor movement training on football players’ sustained attention performance. In: Proceedings of 2015 Medical Technologies National Conference (TIPTEKNO), Bodrum, 2015

  112. 112

    Klimkeit E I, Sheppard D M, Lee P, et al. Bimanual coordination deficits in attention deficit/hyperactivity disorder (ADHD). J Clin Exp Neuropsychol, 2004, 26: 999–1010

  113. 113

    Monno A, Temprado J J, Zanone P G, et al. The interplay of attention and bimanual coordination dynamics. Acta Psychol, 2002, 110: 187–211

  114. 114

    Sherwood D E, Rios V. Divided attention in bimanual aiming movements: effects on movement accuracy. Res Q Exercise Sport, 2001, 72: 210–218

  115. 115

    Sherwood D E, Buchanan J J. The effect of the focus of attention on bimanual circle drawing. J Sport Exerc Psychol, 2011, 33: S113

  116. 116

    Johansen-Berg H, Della-Maggiore V, Behrens T E J, et al. Integrity of white matter in the corpus callosum correlates with bimanual co-ordination skills. Neuroimage, 2007, 36: T16–T21

  117. 117

    Gooijers J, Swinnen S P. Interactions between brain structure and behavior: the corpus callosum and bimanual coordination. Neurosci Biobehaval Rev, 2014, 43: 1–19

  118. 118

    Draganski B, Gaser C, Busch V, et al. Neuroplasticity: changes in grey matter induced by training. Nature, 2004, 427: 311–312

  119. 119

    Hebb D. The Organization of Behavior: A Neuropsycho-logical Theory. New York: John Wiley and Sons, 1949

  120. 120

    Willis S L, Tennstedt S L, Marsiske M, et al. Long-term effects of cognitive training on everyday functional outcomes in older adults. J Am Med Assoc, 2006, 296: 2805–2814

  121. 121

    Rebok G W, Ball K, Guey L T, et al. Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. J Am Geriatr Soc, 2014, 62: 16–24

  122. 122

    Tan H Z, Srinivasan M A, Eberman B, et al. Human factors for the design of force-reflecting haptic interfaces. Dynam Syst Control, 1994, 55: 353–359

  123. 123

    Keller J M. Development and use of the ARCS model of instructional design. J Instructional Dev, 1987, 10: 2–10

  124. 124

    Csikszentmihalyi M. Flow and the Psychology of Discovery and Invention. New York: Harper Collins, 1996

  125. 125

    Cahn B R, Polich J. Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychol Bull, 2006, 132: 180–211

  126. 126

    Beauregard M, Lévesque J. Functional magnetic resonance imaging investigation of the effects of neurofeedback training on the neural bases of selective attention and response inhibition in children with attention-deficit/hyperactivity disorder. Appl Psychophys Biofeedback, 2006, 31: 3–20

  127. 127

    Baniqued P L, Kranz M B, Voss M W, et al. Cognitive training with casual video games: points to consider. Front Psychol, 2014, 4: 19

  128. 128

    Greenberg L M, Waldmant I D. Developmental normative data on the test of variables of attention (T.O.V.A.?). J Child Psychol Psychiat, 1993, 34: 1019–1030

  129. 129

    Nuechterlein K H, Green M F, Kern R S, et al. The MATRICS consensus cognitive battery, part 1: test selection, reliability, and validity. Am J Psychiat, 2008, 165: 203–213

  130. 130

    Robertson I H, Manly T, Andrade J, et al. ‘Oops!’: performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 1997, 35: 747–758

  131. 131

    Maruff P, Thomas E, Cysique L, et al. Validity of the CogState brief battery: relationship to standardized tests and sensitivity to cognitive impairment in mild traumatic brain injury, schizophrenia, and AIDS dementia complex. Arch Clin Neuropsychol, 2009, 24: 165–178

  132. 132

    Yeo B T T, Krienen F M, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol, 2011, 106: 1125–1165

  133. 133

    Clayton M S, Yeung N, Kadosh R C. The roles of cortical oscillations in sustained attention. Trends Cogn Sci, 2015, 19: 188–195

  134. 134

    Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci, 2009, 10: 186–198

  135. 135

    Sporns O. Contributions and challenges for network models in cognitive neuroscience. Nat Neurosci, 2014, 17: 652–660

  136. 136

    Buschman T J, Miller E K. Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 2007, 315: 1860–1862

  137. 137

    Green C S, Pouget A, Bavelier D. Improved probabilistic inference as a general learning mechanism with action video games. Curr Biol, 2010, 20: 1573–1579

  138. 138

    Byers A, Serences J T. Exploring the relationship between perceptual learning and top-down attentional control. Vision Res, 2012, 74: 30–39

  139. 139

    Lutz A, Greischar L L, Rawlings N B, et al. Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proc Natl Acad Sci USA, 2004, 101: 16369–16373

  140. 140

    Wells R E, Yeh G Y, Kerr C E, et al. Meditation’s impact on default mode network and hippocampus in mild cognitive impairment: a pilot study. Neurosci Lett, 2013, 556: 15–19

  141. 141

    Oei A C, Patterson M D. Are videogame training gains specific or general? Front Syst Neurosci, 2014, 8: 54

  142. 142

    Oei A C, Patterson M D. Enhancing cognition with video games: a multiple game training study. PLoS One, 2013, 8: e58546

  143. 143

    Klingberg T, Forssberg H, Westerberg H. Training of working memory in children with ADHD. J Clin Exp Neuropsychol, 2002, 24: 781–791

  144. 144

    Colom R, Quiroga M A, Shih P C, et al. Improvement in working memory is not related to increased intelligence scores. Intelligence, 2010, 38: 497–505

  145. 145

    Jaeggi S M, Buschkuehl M, Jonides J, et al. From the cover: improving fluid intelligence with training on working memory. Proc Natl Acad Sci USA, 2008, 105: 6829–6833

  146. 146

    Arns M, Heinrich H, Strehl U. Evaluation of neurofeedback in ADHD: the long and winding road. Biol Psychol, 2014, 95: 108–115

  147. 147

    Hayward V, Astley O R, Cruz-Hernandez M, et al. Haptic interfaces and devices. Sens Rev, 2004, 24: 16–29

  148. 148

    Schmidt H, Werner C, Bernhardt R, et al. Gait rehabilitation machines based on programmable footplates. J Neuroeng Rehabil, 2007, 4: 2

  149. 149

    Visell Y, Law A, Cooperstock J R. Touch is everywhere: floor surfaces as ambient haptic interfaces. IEEE Trans Haptics, 2009, 2: 148–159

  150. 150

    Schmidt H, Hesse S, Bernhardt R, et al. HapticWalker—a novel haptic foot device. ACM Trans Appl Percept, 2005, 2: 166–180

  151. 151

    Visell Y, Cooperstock J R, Giordano B L, et al. A vibrotactile device for display of virtual ground materials in walking. In: Proceedings of International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, 2008. 420–426

  152. 152

    Wang D, Zhang X, Zhang Y, et al. Configuration-based optimization for six degree-of-freedom haptic rendering for fine manipulation. IEEE Trans Haptics, 2013, 6: 167–180

  153. 153

    Wang D, Shi Y, Liu S, et al. Haptic simulation of organ deformation and hybrid contacts in dental operations. IEEE Trans Haptics, 2014, 7: 48–60

  154. 154

    Diedrichsen J, Hashambhoy Y, Rane T, et al. Neural correlates of reach errors. J Neuroscience, 2005, 25: 9919–9931

  155. 155

    Menon S, Stanley A A, Zhu J, et al. Mapping stiffness perception in the brain with an fMRI-compatible particle-jamming haptic interface. In: Proceedings of the 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), 2014. 2051–2056

  156. 156

    Gassert R, Dovat L, Lambercy O, et al. A 2-DOF fMRI compatible haptic interface to investigate the neural control of arm movements. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2006. 3825–3831

  157. 157

    Imamizu H, Miyauchi S, Tamada T, et al. Human cerebellar activity reflecting an acquired internal model of a new tool. Nature, 2000, 403: 192–195

  158. 158

    Menon S, Brantner G, Aholt C, et al. Haptic fMRI: combining functional neuroimaging with haptics for studying the brain’s motor control representation. In: Proceedings of the 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), 2013. 4137–4142

  159. 159

    Menon S, Yu M, Kay K, et al. Haptic fMRI: accurately estimating neural responses in motor, pre-motor, and somatosensory cortex during complex motor tasks. In: Proceedings of the 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), 2014. 2040–2045

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61572055), and also partially supported by National Key R&D Program of China (Grant No. 2017YFB1002803), and Academic Excellence Foundation of BUAA for Ph.D. Students.

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Correspondence to Dangxiao Wang.

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Wang, D., Li, T., Afzal, N. et al. Haptics-mediated approaches for enhancing sustained attention: framework and challenges. Sci. China Inf. Sci. 62, 211101 (2019). https://doi.org/10.1007/s11432-018-9931-1

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Keywords

  • sustained attention
  • attention enhancement
  • haptic interaction
  • robotics
  • electroencephalogram
  • virtual reality
  • human-computer interaction