Wearable functional near infrared spectroscopy (fNIRS) and transcranial direct current stimulation (tDCS): expanding vistas for neurocognitive augmentation

Ryan McKendrick, Raja Parasuraman, Hasan Ayaz, Ryan McKendrick, Raja Parasuraman, Hasan Ayaz

Abstract

Contemporary studies with transcranial direct current stimulation (tDCS) provide a growing base of evidence for enhancing cognition through the non-invasive delivery of weak electric currents to the brain. The main effect of tDCS is to modulate cortical excitability depending on the polarity of the applied current. However, the underlying mechanism of neuromodulation is not well understood. A new generation of functional near infrared spectroscopy (fNIRS) systems is described that are miniaturized, portable, and include wearable sensors. These developments provide an opportunity to couple fNIRS with tDCS, consistent with a neuroergonomics approach for joint neuroimaging and neurostimulation investigations of cognition in complex tasks and in naturalistic conditions. The effects of tDCS on complex task performance and the use of fNIRS for monitoring cognitive workload during task performance are described. Also explained is how fNIRS + tDCS can be used simultaneously for assessing spatial working memory. Mobile optical brain imaging is a promising neuroimaging tool that has the potential to complement tDCS for realistic applications in natural settings.

Keywords: DLPFC; HDtDCS; fNIRS; neuroergonomics; spatial working memory.

Figures

Figure 1
Figure 1
Current flow model of tDCS montage (F10 anode, F2 cathode), field intensity of 0.44 V/m represented at white ring in coronal, sagittal and transverse views. Arrows represent direction of current flow.
Figure 2
Figure 2
Regions in which effects represent a correlation between increased activity and increased task performance. Legend represents the presence and direction of the effect, not p or t values.
Figure 3
Figure 3
Regions in which effects represent a decrease in activity during stimulation trials relative to the sham trials. Legend represents the presence and direction of the effect, not p or t values.
Figure 4
Figure 4
Regions in which effects represent a correlation between activity and increases in performance in stimulation trials relative to the sham trials. Legend represents the presence and direction of the effect, not p or t values.
Figure 5
Figure 5
Wireless fNIRS System. (left) Battery operated and wireless unit allows untethered outdoor measurement (right, up). Block diagram of the overall system (right, bottom), Building blocks and circuit representation (Ayaz et al., 2013).
Figure 6
Figure 6
Miniaturized and scalable fNIRS sensor pad with 2 optodes can be integrated with electrodes. (left) prototype sensor pad circuit board and covered with foam enclosure. A U.S. quarter is included for size. (right) The 2 optodes sensor pad parts.

References

    1. Abibullaev B., An J. (2012). Classification of frontal cortex haemodynamic responses during cognitive tasks using wavelet transforms and machine learning algorithms. Med. Eng. Phys. 34, 1394–1410. 10.1016/j.medengphy.2012.01.002
    1. Afergan D., Peck E. M., Solovey E. T., Jenkins A., Hincks S. W., Brown E. T., et al. (2014). “Dynamic difficulty using brain metrics of workload,” in Proc. ACM CHI 2014 Human Factors in Computing Systems Conference (Toronto, Canada: ACM Press).
    1. Alon G., Roys S., Gullapalli R., Greenspan J. (2011). Non-invasive electrical stimulation of the brain (ESB) modifies the resting-state network connectivity of the primary motor cortex: a proof of concept fMRI study. Brain Res. 1403, 37–44. 10.1016/j.brainres.2011.06.013
    1. Angelakis E., Stathopoulou S., Frymiare J. L., Green D. L., Lubar J. F., Kounios J. (2007). EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Clin. Neuropsychol. 21, 110–129. 10.1080/13854040600744839
    1. Antal A., Bikson M., Datta A., Lafon B., Dechent P., Parra L. C., et al. . (2014). Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain. Neuroimage 85(Pt. 3), 1040–1047. 10.1016/j.neuroimage.2012.10.026
    1. Antal A., Polania R., Schmidt-Samoa C., Dechent P., Paulus W. (2011). Transcranial direct current stimulation over the primary motor cortex during fMRI. Neuroimage 55, 590–596. 10.1016/j.neuroimage.2010.11.085
    1. Attiah M. A., Farah M. J. (2014). Minds and motherboards and money: futurism and realism in the neuroethics of BCI technologies. Front. Syst. Neurosci. 8:86. 10.3389/fnsys.2014.00086
    1. Ayaz H., Ben Dor B., Solt D., Onaral B. (2011a). Infrascanner: cost effective, mobile medical imaging system for detecting hemotomas. J. Med. Device. 5:027540 10.1115/1.3591407
    1. Ayaz H., Izzetoglu M., Platek S. M., Bunce S., Izzetoglu K., Pourrezaei K., et al. . (2006). Registering fNIR data to brain surface image using MRI templates. Conf. Proc. IEEE Eng. Med. Biol. Soc. 1, 2671–2674. 10.1109/iembs.2006.260835
    1. Ayaz H., Onaral B., Izzetoglu K., Shewokis P. A., McKendrick R., Parasuraman R. (2013). Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development. Front. Hum. Neurosci. 7:871. 10.3389/fnhum.2013.00871
    1. Ayaz H., Shewokis P. A., Bunce S., Izzetoglu K., Willems B., Onaral B. (2012). Optical brain monitoring for operator training and mental workload assessment. Neuroimage 59, 36–47. 10.1016/j.neuroimage.2011.06.023
    1. Ayaz H., Shewokis P. A., Curtin A., Izzetoglu M., Izzetoglu K., Onaral B. (2011b). Using MazeSuite and functional near infrared spectroscopy to study learning in spatial navigation. J. Vis. Exp. 56:3443. 10.3791/3443
    1. Bikson M., Datta A., Elwassif M. (2009). Establishing safety limits for transcranial direct current stimulation. Clin. Neurophysiol. 120, 1033–1034. 10.1016/j.clinph.2009.03.018
    1. Bindman L. J., Lippold O., Redfearn J. (1964). The action of brief polarizing currents on the cerebral cortex of the rat (1) during current flow and (2) in the production of long-lasting after-effects. J. Physiol. 172, 369–382. 10.1113/jphysiol.1964.sp007425
    1. Bogler C., Mehnert J., Steinbrink J., Haynes J. D. (2014). Decoding vigilance with NIRS. PLoS One 9:e101729. 10.1371/journal.pone.0101729
    1. Browning M., Holmes E. A., Murphy S. E., Goodwin G. M., Harmer C. J. (2010). Lateral prefrontal cortex mediates the cognitive modification of attentional bias. Biol. Psychiatry 67, 919–925. 10.1016/j.biopsych.2009.10.031
    1. Byrne E. A., Parasuraman R. (1996). Psychophysiology and adaptive automation. Biol. Psychol. 42, 249–268. 10.1016/0301-0511(95)05161-9
    1. Chance B., Luo Q., Nioka S., Alsop D. C., Detre J. A. (1997). Optical investigations of physiology: a study of intrinsic and extrinsic biomedical contrast. Philos. Trans. R. Soc. Lond. B Biol. Sci. 352, 707–716. 10.1098/rstb.1997.0053
    1. Clark V. P., Coffman B. A., Mayer A. R., Weisend M. P., Lane T. D., Calhoun V. D., et al. . (2012). TDCS guided using fMRI significantly accelerates learning to identify concealed objects. Neuroimage 59, 117–128. 10.1016/j.neuroimage.2010.11.036
    1. Clark V. P., Coffman B. A., Trumbo M. C., Gasparovic C. (2011). Transcranial direct current stimulation (tDCS) produces localized and specific alterations in neurochemistry: A1 H magnetic resonance spectroscopy study. Neurosci. Lett. 500, 67–71. 10.1016/j.neulet.2011.05.244
    1. Clark V. P., Parasuraman R. (2014). Neuroenhancement: enhancing brain and mind in health and in disease. Neuroimage 85, 889–894. 10.1016/j.neuroimage.2013.08.071
    1. Clarke P. J., Browning M., Hammond G., Notebaert L., MacLeod C. (2014). The causal role of the dorsolateral prefrontal cortex in the modification of attentional bias: evidence from transcranial direct current stimulation. Biol. Psychiatry 76, 946–952. 10.1016/j.biopsych.2014.03.003
    1. Clausen J. (2011). Conceptual and ethical issues with brain-hardware interfaces. Curr. Opin. Psychiatry 24, 495–501. 10.1097/YCO.0b013e32834bb8ca
    1. Coffman B. A., Clark V. P., Parasuraman R. (2014). Battery powered thought: enhancement of attention, learning and memory in healthy adults using transcranial direct current stimulation. Neuroimage 85, 895–908. 10.1016/j.neuroimage.2013.07.083
    1. Coffman B. A., Trumbo M., Flores R., Garcia C. M., van der Merwe A., Wassermann E. M., et al. . (2012). Impact of tDCS on performance and learning of target detection: interaction with stimulus characteristics and experimental design. Neuropsychologia 50, 1594–1602. 10.1016/j.neuropsychologia.2012.03.012
    1. Cui X., Bray S., Bryant D. M., Glover G. H., Reiss A. L. (2011). A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. Neuroimage 54, 2808–2821. 10.1016/j.neuroimage.2010.10.069
    1. Datta A., Bansal V., Diaz J., Patel J., Reato D., Bikson M. (2009). Gyri-precise head model of transcranial direct current stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad. Brain Stimul. 2, 201–207.e1. 10.1016/j.brs.2009.03.005
    1. Deisseroth K. (2011). Optogenetics. Nat. Methods 8, 26–29. 10.1038/nmeth.f.324
    1. Derosière G., Dalhoumi S., Perrey S., Dray G., Ward T. (2014). Towards a near infrared spectroscopy-based estimation of operator attentional state. PLoS One 9:e92045. 10.1371/journal.pone.0092045
    1. De Vos M., Kroesen M., Emkes R., Debener S. (2014). P300 speller BCI with a mobile EEG system: comparison to a traditional amplifier. J. Neural Eng. 11:036008. 10.1088/1741-2560/11/3/036008
    1. Durantin G., Gagnon J.-F., Tremblay S., Dehais F. (2014). Using near infrared spectroscopy and heart rate variability to detect mental overload. Behav. Brain Res. 259, 16–23. 10.1016/j.bbr.2013.10.042
    1. Elbert T., Rockstroh B. (2004). Reorganization of human cerebral cortex: the range of changes following use and injury. Neuroscientist 10, 129–141. 10.1177/1073858403262111
    1. Fairclough S. (2014). Physiological data must remain confidential. Nature 505:263. 10.1038/505263a
    1. Falcone B., Coffman B. A., Clark V. P., Parasuraman R. (2012). Transcranial direct current stimulation augments perceptual sensitivity and 24-hour retention in a complex threat detection task. PLoS One 7:e34993. 10.1371/journal.pone.0034993
    1. Faria P., Fregni F., Sebastião F., Dias A. I., Leal A. (2012). Feasibility of focal transcranial DC polarization with simultaneous EEG recording: preliminary assessment in healthy subjects and human epilepsy. Epilepsy Behav. 25, 417–425. 10.1016/j.yebeh.2012.06.027
    1. Ferrari M., Quaresima V. (2012). A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage 63, 921–935. 10.1016/j.neuroimage.2012.03.049
    1. Filmer H. L., Dux P. E., Mattingley J. B. (2014). Applications of transcranial direct current stimulation for understanding brain function. Trends Neurosci. 37, 742–753. 10.1016/j.tins.2014.08.003
    1. Fishburn F. A., Norr M. E., Medvedev A. V., Vaidya C. J. (2014). Sensitivity of fNIRS to cognitive state and load. Front. Hum. Neurosci. 8:76. 10.3389/fnhum.2014.00076
    1. Flöel A. (2014). tDCS-enhanced motor and cognitive function in neurological diseases. Neuroimage 85(Pt. 3), 934–947. 10.1016/j.neuroimage.2013.05.098
    1. Fregni F., Boggio P. S., Nitsche M., Bermpohl F., Antal A., Feredoes E., et al. . (2005). Anodal transcranial direct current stimulation of prefrontal cortex enhances working memory. Exp. Brain Res. 166, 23–30. 10.1007/s00221-005-2334-6
    1. Gramann K., Gwin J. T., Ferris D. P., Oie K., Jung T.-P., Lin C.-T., et al. . (2011). Cognition in action: imaging brain/body dynamics in mobile humans. Rev. Neurosci. 22, 593–608. 10.1515/RNS.2011.047
    1. Gramann K., Jung T. P., Ferris D. P., Lin C. T., Makeig S. (2014). Toward a new cognitive neuroscience: modeling natural brain dynamics. Front. Hum. Neurosci. 8:444. 10.3389/fnhum.2014.00444
    1. Grau C., Ginhoux R., Riera A., Nguyen T. L., Chauvat H., Berg M., et al. . (2014). Conscious brain-to-brain communication in humans using non-invasive technologies. PLoS One 9:e105225. 10.1371/journal.pone.0105225
    1. Gruzelier J. (2009). A theory of alpha/theta neurofeedback, creative performance enhancement, long distance functional connectivity and psychological integration. Cogn. Process. 10, S101–S109. 10.1007/s10339-008-0248-5
    1. Han C.-H., Song H., Kang Y.-G., Kim B.-M., Im C.-H. (2014). Hemodynamic responses in rat brain during transcranial direct current stimulation: a functional near-infrared spectroscopy study. Biomed. Opt. Express. 5, 1812–1821. 10.1364/BOE.5.001812
    1. Hanslmayr S., Sauseng P., Doppelmayr M., Schabus M., Klimesch W. (2005). Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Appl. Psychophysiol. Biofeedback 30, 1–10. 10.1007/s10484-005-2169-8
    1. Haselager P., Vlek R., Hill J., Nijboer F. (2009). A note on ethical aspects of BCI. Neural Netw. 22, 1352–1357. 10.1016/j.neunet.2009.06.046
    1. Heinrich H., Busch K., Studer P., Erbe K., Moll G. H., Kratz O. (2014). EEG spectral analysis of attention in ADHD: implications for neurofeedback training? Front. Hum. Neurosci. 8:611. 10.3389/fnhum.2014.00611
    1. Herff C., Heger D., Fortmann O., Hennrich J., Putze F., Schultz T. (2014). Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS. Front. Hum. Neurosci. 7:935. 10.3389/fnhum.2013.00935
    1. Hoffman D., Stockdale S., Van Egren L. (1996). EEG neurofeedback in the treatment of mild traumatic brain injury. Clin. Electroencephalogr. 27, 105.
    1. Holland R., Leff A. P., Josephs O., Galea J. M., Desikan M., Price C. J., et al. . (2011). Speech facilitation by left inferior frontal cortex stimulation. Curr. Biol. 21, 1403–1407. 10.1016/j.cub.2011.07.021
    1. Holper L., Muehlemann T., Scholkmann F., Eng K., Kiper D., Wolf M. (2010). Testing the potential of a virtual reality neurorehabilitation system during performance of observation, imagery and imitation of motor actions recorded by wireless functional near-infrared spectroscopy (fNIRS). J. Neuroeng. Rehabil. 7:57. 10.1186/1743-0003-7-57
    1. Hoshi Y. (2003). Functional near-infrared optical imaging: utility and limitations in human brain mapping. Psychophysiology 40, 511–520. 10.1111/1469-8986.00053
    1. Hunter M. A., Coffman B. A., Trumbo M. C., Clark V. P. (2013). Tracking the neuroplastic changes associated with transcranial direct current stimulation: a push for multimodal imaging. Front. Hum. Neurosci. 7:495. 10.3389/fnhum.2013.00495
    1. Illes J., Bird S. J. (2006). Neuroethics: a modern context for ethics in neuroscience. Trends Neurosci. 29, 511–517. 10.1016/j.tins.2006.07.002
    1. Ishikuro K., Urakawa S., Takamoto K., Ishikawa A., Ono T., Nishijo H. (2014). Cerebral functional imaging using near-infrared spectroscopy during repeated performances of motor rehabilitation tasks tested on healthy subjects. Front. Hum. Neurosci. 8:292. 10.3389/fnhum.2014.00292
    1. Jacobson L., Koslowsky M., Lavidor M. (2012). tDCS polarity effects in motor and cognitive domains: a meta-analytical review. Exp. Brain Res. 216, 1–10. 10.1007/s00221-011-2891-9
    1. James D. R. C., Orihuela-Espina F., Leff D. R., Sodergren M. H., Athanasiou T., Darzi A. W., et al. . (2011). The ergonomics of natural orifice translumenal endoscopic surgery (NOTES) navigation in terms of performance, stress and cognitive behavior. Surgery 149, 525–533. 10.1016/j.surg.2010.11.019
    1. Jones K. T., Gözenman F., Berryhill M. E. (2015). The strategy and motivational influences on the beneficial effect of neurostimulation: a tDCS and fNIRS study. Neuroimage 105, 238–247. 10.1016/j.neuroimage.2014.11.012
    1. Khan B., Hodics T., Hervey N., Kondraske G., Stowe A. M., Alexandrakis G. (2013). Functional near-infrared spectroscopy maps cortical plasticity underlying altered motor performance induced by transcranial direct current stimulation. J. Biomed. Opt. 18:116003. 10.1117/1.JBO.18.11.116003
    1. Kopton I. M., Kenning P. (2014). Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research. Front. Hum. Neurosci. 8:549. 10.3389/fnhum.2014.00549
    1. Kouijzer M. E. J., de Moor J. M. H., Gerrits B. J. L., Congedo M., van Schie H. T. (2009). Neurofeedback improves executive functioning in children with autism spectrum disorders. Res. Autism Spectr. Disord. 3, 145–162 10.1016/j.rasd.2008.05.001
    1. Kwon Y. H., Jang S. H. (2011). The enhanced cortical activation induced by transcranial direct current stimulation during hand movements. Neurosci. Lett. 492, 105–108. 10.1016/j.neulet.2011.01.066
    1. Lareau E., Lesage F., Pouliot P., Nguyen D., Le Lan J., Sawan M. (2011). Multichannel wearable system dedicated for simultaneous electroencephalography/near-infrared spectroscopy real-time data acquisitions. J. Biomed. Opt. 16:096014. 10.1117/1.3625575
    1. Leamy D., Collins R., Ward T. (2011). “Combining fNIRS and EEG to improve motor cortex activity classification during an imagined movement-based task,” in Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, eds Schmorrow D. D., Fidopiastis C. M. (Berlin Heidelberg: Springer; ), 177–185.
    1. Lebedev M. (2014). Brain-machine interfaces: an overview. Transl. Neurosci. 5, 99–110 10.2478/s13380-014-0212-z
    1. Lewis C. M., Baldassarre A., Committeri G., Romani G. L., Corbetta M. (2009). Learning sculpts the spontaneous activity of the resting human brain. Proc. Natl. Acad. Sci. U S A 106, 17558–17563. 10.1073/pnas.0902455106
    1. Liao L.-D., Lin C.-T., McDowell K., Wickenden A. E., Gramann K., Jung T.-P., et al. (2012). Biosensor technologies for augmented brain-computer interfaces in the next decades. Proc. IEEE 100, 1553–1566 10.1109/jproc.2012.2184829
    1. Liebetanz D., Nitsche M. A., Tergau F., Paulus W. (2002). Pharmacological approach to the mechanisms of transcranial DC-stimulation-induced after-effects of human motor cortex excitability. Brain 125, 2238–2247. 10.1093/brain/awf238
    1. Lim C. G., Lee T. S., Guan C., Fung D. S., Zhao Y., Teng S. S., et al. . (2012). A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder. PLoS One 7:e46692. 10.1371/journal.pone.0046692
    1. Lövdén M., Bodammer N. C., Kühn S., Kaufmann J., Schütze H., Tempelmann C., et al. . (2010). Experience-dependent plasticity of white-matter microstructure extends into old age. Neuropsychologia 48, 3878–3883. 10.1016/j.neuropsychologia.2010.08.026
    1. Lubar J. F., Swartwood M. O., Swartwood J. N., O’Donnell P. H. (1995). Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in TOVA scores, behavioral ratings and WISC-R performance. Biofeedback Self Regul. 20, 83–99. 10.1007/bf01712768
    1. Makeig S., Gramann K., Jung T.-P., Sejnowski T. J., Poizner H. (2009). Linking brain, mind and behavior. Int. J. Psychophysiol. 73, 95–100. 10.1016/j.ijpsycho.2008.11.008
    1. Mandrick K., Derosiere G., Dray G., Coulon D., Micallef J.-P., Perrey S. (2013). Prefrontal cortex activity during motor tasks with additional mental load requiring attentional demand: a near-infrared spectroscopy study. Neurosci. Res. 76, 156–162. 10.1016/j.neures.2013.04.006
    1. Mangia A. L., Pirini M., Cappello A. (2014). Transcranial direct current stimulation and power spectral parameters: a tDCS/EEG co-registration study. Front. Hum. Neurosci. 8:601. 10.3389/fnhum.2014.00601
    1. McKendrick R., Ayaz H., Olmstead R., Parasuraman R. (2014). Enhancing dual-task performance with verbal and spatial working memory training: continuous monitoring of cerebral hemodynamics with NIRS. Neuroimage 85(Pt. 3), 1014–1026. 10.1016/j.neuroimage.2013.05.103
    1. McKinley R. A., McIntire L., Bridges N., Goodyear C., Weisend M. P. (2013). Acceleration of image analyst training with transcranial direct current stimulation. Behav. Neurosci. 127, 936–946. 10.1037/a0034975
    1. Mehta R. K., Parasuraman R. (2013). Neuroergonomics: a review of applications to physical and cognitive work. Front. Hum. Neurosci. 7:889. 10.3389/fnhum.2013.00889
    1. Mehta R. K., Parasuraman R. (2014). Effects of mental fatigue on the development of physical fatigue: a neuroergonomic approach. Hum. Factors 56, 645–656. 10.1177/0018720813507279
    1. Merzagora A. C., Foffani G., Panyavin I., Mordillo-Mateos L., Aguilar J., Onaral B., et al. . (2010). Prefrontal hemodynamic changes produced by anodal direct current stimulation. Neuroimage 49, 2304–2310. 10.1016/j.neuroimage.2009.10.044
    1. Mihajlovic V., Grundlehner B., Vullers R., Penders J. (2015). Wearable, wireless EEG Solutions in daily life applications: what are we missing? IEEE J. Biomed. Health Inform. 19, 6–21. 10.1109/JBHI.2014.2328317
    1. Miller K., Schalk G., Fetz E., den Nijs M., Ojemann J., Rao R. (2010). Cortical activity during motor execution, motor imagery and imagery-based online feedback. Proc. Natl. Acad. Sci. U S A 107, 4430–4435. 10.1073/pnas.0913697107
    1. Muehlemann T., Haensse D., Wolf M. (2008). Wireless miniaturized in-vivo near infrared imaging. Opt. Express 16, 10323–10330. 10.1364/oe.16.010323
    1. Muthalib M., Dutta A., Besson P., Rothwell J., Ward T., Perrey S. (2014). “Comparison of online vs offline effects of HD-tDCS induced modulation of cortical sensorimotor networks using a combined fNIRS-EEG setup,” in Poster presented at the International Society on Oxygen Transport to Tissues (ISOTT) Conference (London).
    1. Muthalib M., Kan B., Nosaka K., Perrey S. (2013). “Effects of transcranial direct current stimulation of the motor cortex on prefrontal cortex activation during a neuromuscular fatigue task: an fNIRS study,” in Oxygen Transport to Tissue XXXV, eds Van Huffel S., Naulaers G., Caicedo A., Bruley D. F., Harrison D. K. (New York: Springer; ), 73–79.
    1. Naseer N., Keum-Shik H. (2013). “Functional near-infrared spectroscopy based discrimination of mental counting and no-control state for development of a brain-computer interface,” in Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE, 1780–1783.
    1. Nijboer F., Clausen J., Allison B. Z., Haselager P. (2011). The asilomar survey: stakeholders’ opinions on ethical issues related to brain-computer interfacing. Neuroethics 6, 541–578. 10.1007/s12152-011-9132-6
    1. Ninaus M., Kober S. E., Witte M., Koschutnig K., Stangl M., Neuper C., et al. . (2013). Neural substrates of cognitive control under the belief of getting neurofeedback training. Front. Hum. Neurosci. 7:914. 10.3389/fnhum.2013.00914
    1. Nitsche M., Paulus W. (2000). Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J. Physiol. 527, 633–639. 10.1111/j.1469-7793.2000.t01-1-00633.x
    1. O’Doherty J. E., Lebedev M. A., Ifft P. J., Zhuang K. Z., Shokur S., Bleuler H., et al. . (2011). Active tactile exploration using a brain-machine-brain interface. Nature 479, 228–231. 10.1038/nature10489
    1. Pais-Vieira M., Lebedev M., Kunicki C., Wang J., Nicolelis M. A. L. (2013). A brain-to-brain interface for real-time sharing of sensorimotor information. Sci. Rep. 3:1319. 10.1038/srep01319
    1. Parasuraman R. (2003). Neuroergonomics: research and practice. Theor. Issues Ergon. Sci. 4, 5–20 10.1080/14639220210199753
    1. Parasuraman R. (2011). Neuroergonomics brain, cognition and performance at work. Curr. Dir. Psychol. Sci. 20, 181–186 10.1177/0963721411409176
    1. Parasuraman R., Galster S. (2013). Sensing, assessing and augmenting threat detection: behavioral, neuroimaging and brain stimulation evidence for the critical role of attention. Front. Hum. Neurosci. 7:273. 10.3389/fnhum.2013.00273
    1. Parasuraman R., Mckinley R. A. (2014). Using noninvasive brain stimulation to accelerate learning and enhance human performance. Hum. Factors 56, 816–824. 10.1177/0018720814538815
    1. Parasuraman R., Rizzo M. (2007). Neuroergonomics: The Brain at Work. New York, NY: Oxford University Press.
    1. Rahman A., Reato D., Arlotti M., Gasca F., Datta A., Parra L. C., et al. . (2013). Cellular effects of acute direct current stimulation: somatic and synaptic terminal effects. J. Physiol. 591, 2563–2578. 10.1113/jphysiol.2012.247171
    1. Raymond J., Varney C., Parkinson L. A., Gruzelier J. H. (2005). The effects of alpha/theta neurofeedback on personality and mood. Brain Res. Cogn. Brain Res. 23, 287–292. 10.1016/j.cogbrainres.2004.10.023
    1. Rodriguez M., Pourrezaei K. (2011). Development of a Versatile Wireless fNIR System. Philadelphia, PA: Masters Degree, Drexel University.
    1. Safaie J., Grebe R., Abrishami Moghaddam H., Wallois F. (2013). Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system. J. Neural Eng. 10:056001. 10.1088/1741-2560/10/5/056001
    1. Saiote C., Turi Z., Paulus W., Antal A. (2013). Combining functional magnetic resonance imaging with transcranial electrical stimulation. Front. Hum. Neurosci. 7:435. 10.3389/fnhum.2013.00435
    1. Sao V., Pourrezaei K., Akin A., Ayaz H. (2003). “Breast tumor imaging using NIR LED based handheld continuous-wave imager,” in Bioengineering Conference, IEEE 29th Annual, Proceedings of (IEEE).
    1. Sato H., Yahata N., Funane T., Takizawa R., Katura T., Atsumori H., et al. . (2013). A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task. Neuroimage 83, 158–173. 10.1016/j.neuroimage.2013.06.043
    1. Schermer M. (2009). The mind and the machine. On the conceptual and moral implications of brain-machine interaction. Nanoethics 3, 217–230. 10.1007/s11569-009-0076-9
    1. Schestatsky P., Morales-Quezada L., Fregni F. (2013). Simultaneous EEG monitoring during transcranial direct current stimulation. J. Vis. Exp. 76:e50426. 10.3791/50426
    1. Schudlo L. C., Chau T. (2014). Dynamic topographical pattern classification of multichannel prefrontal NIRS signals: II. Online differentiation of mental arithmetic and rest. J. Neural Eng. 11:016003. 10.1088/1741-2560/11/1/016003
    1. Shapiro M. G., Homma K., Villarreal S., Richter C.-P., Bezanilla F. (2012). Infrared light excites cells by changing their electrical capacitance. Nat. Commun. 3:736. 10.1038/ncomms1742
    1. Slagter H. A., Davidson R. J., Lutz A. (2011). Mental training as a tool in the neuroscientific study of brain and cognitive plasticity. Front. Hum. Neurosci. 5:17. 10.3389/fnhum.2011.00017
    1. Solovey E. T., Afergan D., Peck E. M., Hincks S. W., Jacob R. J. K. (2015). Designing implicit interfaces for physiological computing: guidelines and lessons learned using fNIRS. ACM Trans. Comput. Hum. Interact. 21, 1–27 10.1145/2687926
    1. Stopczynski A., Stahlhut C., Petersen M. K., Larsen J. E., Jensen C. F., Ivanova M. G., et al. . (2014). Smartphones as pocketable labs: visions for mobile brain imaging and neurofeedback. Int. J. Psychophysiol. 91, 54–66. 10.1016/j.ijpsycho.2013.08.007
    1. Strenziok M., Parasuraman R., Clarke E., Cisler D. S., Thompson J. C., Greenwood P. M. (2014). Neurocognitive enhancement in older adults: comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity. Neuroimage 85, 1027–1039. 10.1016/j.neuroimage.2013.07.069
    1. Villamar M. F., Volz M. S., Bikson M., Datta A., Dasilva A. F., Fregni F. (2013). Technique and considerations in the use of 4x1 ring high-definition transcranial direct current stimulation (HD-tDCS). J. Vis. Exp. e50309. 10.3791/50309
    1. Villringer A., Chance B. (1997). Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci. 20, 435–442. 10.1016/s0166-2236(97)01132-6
    1. Vlek R. J., Steines D., Szibbo D., Kubler A., Schneider M. J., Haselager P., et al. . (2012). Ethical issues in brain-computer interface research, development and dissemination. J. Neurol. Phys. Ther. 36, 94–99. 10.1097/npt.0b013e31825064cc
    1. Voss M. W., Prakash R. S., Erickson K. I., Boot W. R., Basak C., Neider M. B., et al. . (2012). Effects of training strategies implemented in a complex videogame on functional connectivity of attentional networks. Neuroimage 59, 138–148. 10.1016/j.neuroimage.2011.03.052
    1. Walsh V., Pascual-Leone A. (2005). Transcranial Magnetic Stimulation: A Neurochronometrics of Mind. Cambridge, MA: Bradford.
    1. Weingarten M. S., Papazoglou E. S., Zubkov L., Zhu L., Neidrauer M., Savir G., et al. . (2008). Correlation of near infrared absorption and diffuse reflectance spectroscopy scattering with tissue neovascularization and collagen concentration in a diabetic rat wound healing model. Wound Repair Regen. 16, 234–242. 10.1111/j.1524-475x.2008.00364.x
    1. Wells J., Kao C., Jansen E. D., Konrad P., Mahadevan-Jansen A. (2005a). Application of infrared light for in vivo neural stimulation. J. Biomed. Opt. 10:064003. 10.1117/1.2121772
    1. Wells J., Kao C., Mariappan K., Albea J., Jansen E. D., Konrad P., et al. . (2005b). Optical stimulation of neural tissue in vivo. Opt. Lett. 30, 504–506. 10.1364/ol.30.000504
    1. Wolpaw J. R., Birbaumer N., Mcfarland D. J., Pfurtscheller G., Vaughan T. M. (2002). Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791. 10.1016/S1388-2457(02)00057-3
    1. Yamauchi Y., Kikuchi S., Miwakeichi F., Matsumoto K., Nishida M., Ishiguro M., et al. . (2013). Relation between parametric change of the workload and prefrontal cortex activity during a modified version of the ‘rock, paper, scissors’ task. Neuropsychobiology 68, 24–33. 10.1159/000350948
    1. Yerkes R. M., Dodson J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. J. Comp. Neurol. Psychol. 18, 459–482 10.1002/cne.920180503
    1. Yoshino K., Oka N., Yamamoto K., Takahashi H., Kato T. (2013a). Correlation of prefrontal cortical activation with changing vehicle speeds in actual driving: a vector-based functional near-infrared spectroscopy study. Front. Hum. Neurosci. 7:895. 10.3389/fnhum.2013.00895
    1. Yoshino K., Oka N., Yamamoto K., Takahashi H., Kato T. (2013b). Functional brain imaging using near-infrared spectroscopy during actual driving on an expressway. Front. Hum. Neurosci. 7:882. 10.3389/fnhum.2013.00882
    1. Yurtsever G., Ayaz H., Kepics F., Onaral B., Pourrezaei K. (2006). Wireless, Continuous Wave Near Infrared Spectroscopy System for Monitoring Brain Activity. Philadelphia, PA: Drexel University.

Source: PubMed

3
订阅