Summary

Inter-Brain Synchrony i Open-Ended Collaborative Learning: En fNIRS-Hyperscanning Study

Published: July 21, 2021
doi:

Summary

Protokollen for udførelse af fNIRS hyperscanning eksperimenter på kollaborative læring dyads i et naturalistisk læringsmiljø er skitseret. Desuden præsenteres en rørledning til analyse af Inter-Brain Synchrony (IBS) af iltede hæmoglobin (Oxy-Hb) signaler.

Abstract

fNIRS hyperscanning er meget udbredt til at opdage de neurobiologiske fundamenter af social interaktion. Med denne teknik kvalificerer forskere den samtidige hjerneaktivitet hos to eller flere interaktive personer med et nyt indeks kaldet inter-brain synkron (IBS) (dvs. fase og / eller amplitudjustering af de neuronale eller hæmodynamiske signaler over tid). En protokol til udførelse af fNIRS hyperscanning eksperimenter på kollaborative læring dyads i et naturalistisk læringsmiljø præsenteres her. Endvidere forklares en rørledning til analyse af IBS af iltet hæmoglobin (Oxy-Hb) signal. Specifikt diskuteres det eksperimentelle design, processen med NIRS-dataregistrering, dataanalysemetoder og fremtidige retninger. Samlet set er implementering af en standardiseret fNIRS hyperscanning pipeline en grundlæggende del af andenpersons neurovidenskab. Dette er også i overensstemmelse med opfordringen til åben videnskab for at støtte forskningens reproducerbarhed.

Introduction

For nylig, at afsløre den samtidige hjerneaktivitet på tværs af de interaktive dyads eller medlemmer af en gruppe, forskere anvender hyperscanning tilgang1,2. Specifikt anvendes elektroencefalogram (EEG), funktionel magnetisk resonansbilleddannelse (fMRI) og funktionel nær-infrarød spektroskopi (fNIRS) til at registrere neurale og hjerneaktiviteter fra to eller flere forsøgspersoner samtidigt3,4,5. Forskere udtrække en neural indeks indebærer samtidig hjerne kobling baseret på denne teknik, som refererer til inter-brain synkron (IBS) (dvs. fase og / eller amplitud tilpasning af neuronal eller hæmodynamiske signaler over tid). Et stort udvalg af hyperscanning forskning fundet IBS under social interaktion mellem flere personer (f.eks spiller-publikum, instruktør-elev, og leder-follower)6,7,8. Desuden har IBS specifikke konsekvenser af effektiv læring og instruktion9,10,11,12,13,14. Med bølgende hyperscanning forskning i naturalistiske læring scenarier, oprettelse af en standard protokol af hyperscanning eksperimenter og pipeline af dataanalyse på dette område er nødvendig.

Således giver dette papir en protokol til udførelse af fNIRS-baseret hyperscanning af kollaborative læringsdyader og en pipeline til analyse af IBS. fNIRS er et optisk billeddannelsesværktøj, som udstråler nær-infrarødt lys til at vurdere den spektrale absorption af hæmoglobin indirekte, og derefter måles hæmodynamisk / iltning aktivitet15,16,17. Sammenlignet med fMRI er fNIRS mindre tilbøjelig til at bevægelsesartefakter, hvilket giver målinger fra forsøg fra det virkelige liv (f.eks. efterligning, tale og ikke-verbal kommunikation)18,7,19. I sammenligning med EEG har fNIRS en højere rumlig opløsning, hvilket gør det muligt for forskere at registrere placeringen af hjerneaktivitet20. Således kvalificerer disse fordele i rumlig opløsning, logistik og gennemførlighed fNIRS til at udføre hyperscanning måling1. Ved hjælp af denne teknologi registrerer en ny forskningskrop et indeksudtryk som IBS-den neurale tilpasning af to (eller flere) menneskers hjerneaktivitet i forskellige former for naturalistiske sociale indstillinger9,10,11,12,13,14. I disse undersøgelser anvendes forskellige metoder (dvs. korrelationsanalyse og WTC-analyse (Wavelet Transform Coherence) til at beregne dette indeks. I mellemtiden er en standardpipeline til en sådan analyse afgørende, men mangler. Som følge heraf præsenteres en protokol til udførelse af fNIRS-baseret hyperscanning og en pipeline, der bruger WTC-analyse til at identificere IBS, i dette arbejde

Denne undersøgelse har til formål at evaluere IBS i kollaborative læring dyads ved hjælp af fNIRS hyperscanning teknik. For det første registreres en hæmodynamisk respons samtidigt i hver dyads præfrontale og venstre temporoparietale regioner under en kollaborativ læringsopgave. Disse områder er blevet identificeret som forbundet med interaktiv undervisning og læring9,10,11,12,13,14. For det andet beregnes IBS på hver tilsvarende kanal. FNIRS-dataregistreringsprocessen består af to dele: hviletilstandssession og samarbejdssession. Hviletilstandssessionen varer i 5 minutter, hvor begge deltagere (siddende ansigt til ansigt, bortset fra hinanden ved et bord (0,8 m)) skal forblive stille og slappe af. Denne hviletilstandssession fungerer som udgangspunkt. Derefter bliver deltagerne i den kollaborative session bedt om at studere hele undervisningsmaterialerne sammen, fremkalde forståelse, opsummere reglerne og sørge for, at alle læringsmaterialer mestres. Her præsenteres de specifikke trin til at udføre eksperimentet og fNIRS-dataanalysen.

Protocol

Alle rekrutterede deltagere (40 dyads, gennemsnitsalder 22,1 ± 1,2 år; 100% højrehåndet, normal eller korrigeret til normal vision) var sunde. Før eksperimentet gav deltagerne informeret samtykke. Deltagerne blev økonomisk kompenseret for deres deltagelse. Undersøgelsen blev godkendt af University Committee of Human Research Protection (HR-0053-2021), East China Normal University. 1. Forberedelsestrin, før der vedtages data Hjemmelavede NIRS-hætter Vedtage elastisk …

Representative Results

Figur 1 illustrerer den eksperimentelle protokol og sonde placering. FNIRS-dataregistreringsprocessen består af to dele: hviletilstandssession (5 min) og samarbejdssession (15-20 min). De kollaborative læringsdyader er nødvendige for at slappe af og holde sig i ro i hviletilstandssessionen. Derefter bliver deltagerne bedt om at være med til at lære læringsmaterialet (figur 1A). Deres præfrontale og venstre temporoparietale regioner er omfattet af det tils…

Discussion

For det første, i den nuværende protokol, de specifikke trin til at gennemføre fNIRS hyperscanning eksperimenter i et samarbejde læring scenario er angivet. For det andet præsenteres også dataanalysepipelinen, der vurderer IBS af hæmodynamiske signaler i kollaborative læringsdyader. Den detaljerede operation om gennemførelse af fNIRS hyperscanning eksperimenter ville fremme udviklingen af åben videnskab. Desuden er analysen pipeline leveres her for at øge reproducerbarheden af hyperscanning forskning. I det f?…

Disclosures

The authors have nothing to disclose.

Acknowledgements

Dette arbejde er støttet af ECNU Academic Innovation Promotion Program for Excellent Ph.d.-studerende (YBNLTS2019-025) og National Natural Science Foundation of China (31872783 og 71942001).

Materials

EEG caps Compumedics Neuroscan,Charlotte,USA 64-channel Quik-Cap We choose two sizes of cap(i.e.medium and large).
NIRS measurement system with probe sets and probe holder grids Hitachi Medical Corporation, Tokyo, Japan ETG-7100 Optical Topography System The current study protocol requires an optional second adult probe set for 92 channels of measurement in total.
Numeric computing platform The MathWorks, Inc., Natick, MA MATLAB R2020a Serves as base for Psychophysics Toolbox extensions (stimulus presentation), Homer2  (fNIRS preprocess analysis), and "wtc" function(WTC computation).
Psychology software psychology software tools,Sharpsburg, PA,USA E-prime 2.0 we apply E-prime to start the fNIRS measurement system and send triggers which marking the rest phase and collaborative learning phase for fNIRS recording data
Swimming caps Zoke corporation,Shanghai,China 611503314 We first placed the standard 10-20 EEG cap on the head mold, and placed the swimming cap on the EEG cap. Second, we marked (inion, Cz, T3, T4, PFC and P5) with chalk.
Three-dimensional (3-D) digitizer Polhemus, Colchester, VT, USA; Three-dimensional (3-D) digitizer Anatomical locations of optodes in relation to standard head landmarks were determined for each participant using a Patriot 3D Digitizer

References

  1. Babiloni, F., Astolfi, L. Social neuroscience and hyperscanning techniques: past, present and future. Neuroscience & Biobehavioral Reviews. 44, 76-93 (2014).
  2. Schilbach, L., et al. Toward a second-person neuroscience. Behavior Brain Science. 36, 393-414 (2013).
  3. Montague, P. Hyperscanning: simultaneous fMRI during linked social interactions. NeuroImage. 16, 1159-1164 (2002).
  4. Cui, X., Bryant, D. M., Reiss, A. L. NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation. NeuroImage. 59 (3), 2430-2437 (2012).
  5. Dikker, S., et al. Brain-to-brain synchrony tracks real-world dynamic group interactions in the classroom. Current Biology. 27 (9), 1375-1380 (2017).
  6. Abrams, D. A., et al. Inter-subject synchronization of brain responses during natural music listening. European Journal of Neuroscience. 37 (9), 1458-1469 (2013).
  7. Pan, Y., et al. Instructor-learner brain coupling discriminates between instructional approaches and predicts learning. NeuroImage. 211, 116657 (2020).
  8. Jiang, J., et al. Leader emergence through interpersonal neural synchronization. Proceedings of the National Academy of Sciences of the United States of America. 112 (14), 4274-4279 (2015).
  9. Bevilacqua, D., et al. Brain-to-brain synchrony and learning outcomes vary by student-teacher dynamics: Evidence from a real-world classroom electroencephalography study. Journal of Cognitive Neuroscience. 31 (3), 401-411 (2019).
  10. Dikker, S., et al. Morning brain: real-world neural evidence that high school class times matter. Social Cognitive and Affective Neuroscience. 15 (11), 1193-1202 (2020).
  11. Pan, Y., Guyon, C., Borragán, G., Hu, Y., Peigneux, P. Interpersonal brain synchronization with instructor compensates for learner’s sleep deprivation in interactive learning. Biochemical Pharmacology. , 114111 (2020).
  12. Pan, Y., Novembre, G., Song, B., Li, X., Hu, Y. Interpersonal synchronization of inferior frontal cortices tracks social interactive learning of a song. NeuroImage. 183, 280-290 (2018).
  13. Zheng, L., et al. Enhancement of teaching outcome through neural prediction of the students’ knowledge state. Human Brain Mapping. 39 (7), 3046-3057 (2018).
  14. Zheng, L., et al. Affiliative bonding between teachers and students through interpersonal synchronisation in brain activity. Social Cognitive and Affective Neuroscience. 15 (1), 97-109 (2020).
  15. Kleinschmidt, A., et al. Simultaneous recording of cerebral blood oxygenation changes during human brain activation by magnetic resonance imaging and near-infrared spectroscopy. Journal of Cerebral Blood Flow & Metabolism. 16 (5), 817-826 (1996).
  16. Strangman, G., Culver, J. P., Thompson, J. H., Boas, D. A. A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. NeuroImage. 17 (2), 719-731 (2002).
  17. Huppert, T. J., Hoge, R. D., Diamond, S. G., Franceschini, M. A., Boas, D. A. A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. NeuroImage. 29 (2), 368-382 (2006).
  18. Holper, L., Scholkmann, F., Wolf, M. Between-brain connectivity during imitation measured by fNIRS. NeuroImage. 63, 212-222 (2012).
  19. Hirsch, J., Zhang, X., Noah, J. A., Ono, Y. Frontal temporal and parietal systems synchronize within and across brains during live eye-to-eye contact. NeuroImage. 157, 314-330 (2017).
  20. Wilcox, T., Biondi, M. fNIRS in the developmental sciences. Wiley Interdisciplinary Reviews: Cognitive Science. 6 (3), 263-283 (2015).
  21. Ye, J. C., Tak, S., Jang, K. E., Jung, J., Jang, J. NIRS-SPM: statistical parametric mapping for nearinfrared spectroscopy. NeuroImage. 44 (2), 428-447 (2009).
  22. Huppert, T. J., Diamond, S. G., Franceschini, M. A., Boas, D. A. HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain. Applied Optics. 48 (10), 280-298 (2009).
  23. Santosa, H., Zhai, X., Fishburn, F., Huppert, T. The NIRS Brain AnalyzIR toolbox. Algorithms. 11 (5), 73 (2018).
  24. Xu, Y., Graber, H. L., Barbour, R. L. nirsLAB: a computing environment for fNIRS neuroimaging data analysis. Biomedical Optics. , (2014).
  25. Cope, M., Delpy, D. T. System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination. Medical and Biological Engineering and Computing. 26 (3), 289-294 (1988).
  26. Hoshi, Y. Functional near-infrared spectroscopy: current status and future prospects. Journal of Biomedical Optics. 12 (6), 062106 (2007).
  27. Molavi, B., Dumont, G. A. Wavelet-based motion artifact removal for functional near-infrared spectroscopy. Physiological Measurement. 33 (2), 259 (2012).
  28. Cooper, R., et al. A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy. Frontiers in Neuroscience. 6, 147 (2012).
  29. Zhang, X., Noah, J. A., Hirsch, J. Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering. Neurophotonics. 3 (1), 015004 (2016).
  30. Grinsted, A., Moore, J. C., Jevrejeva, S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics. 11, 561-566 (2004).
  31. Maris, E., Oostenveld, R. Nonparametric statistical testing of EEG-and MEG-data. Journal of Neuroscience Methods. 164 (1), 177-190 (2007).
  32. Nozawa, T., Sasaki, Y., Sakaki, K., Yokoyama, R., Kawashima, R. Interpersonal frontopolar neural synchronization in group communication: an exploration toward fNIRS hyperscanning of natural interactions. NeuroImage. 133, 484-497 (2016).
  33. Reindl, V., Gerloff, C., Scharke, W., Konrad, K. Brain-to-brain synchrony in parent-child dyads and the relationship with emotion regulation revealed by fNIRS-based hyperscanning. NeuroImage. 178, 493-502 (2018).
  34. Theiler, J., Eubank, S., Longtin, A., Galdrikian, B., Farmer, J. D. Testing for nonlinearity in time series: the method of surrogate data. Physica D: Nonlinear Phenomena. 58 (1-4), 77-94 (1992).
  35. Genovese, C. R., Lazar, N. A., Nichols, T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage. 15 (4), 870-878 (2002).
  36. Nichols, T., Hayasaka, S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Statistical Methods in Medical Research. 12 (5), 419-446 (2003).
  37. Tsuzuki, D., et al. Virtual spatial registration of stand-alone fNIRS data to MNI space. NeuroImage. 34 (4), 1506-1518 (2007).
  38. Singh, A. K., Okamoto, M., Dan, H., Jurcak, V., Dan, I. Spatial registration of multi-channel multi-subject fNIRS data to MNI space without MRI. NeuroImage. 27 (4), 842-851 (2005).
  39. Noah, J. A., et al. Comparison of short-channel separation and spatial domain filtering for removal of non-neural components in functional near-infrared spectroscopy signals. Neurophotonics. 8 (1), 015004 (2021).
  40. Noah, J. A., et al. Real-time eye-to-eye contact is associated with cross-brain neural coupling in angular gyrus. Frontiers in Human Neuroscience. 14 (19), (2020).
  41. Torrence, C., Compo, G. P. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society. 79 (1), 61-78 (1998).
  42. Osaka, N., Minamoto, T., Yaoi, K., Azuma, M., Osaka, M. Neural synchronization during cooperated humming: a hyperscanning study using fNIRS. Procedia-Social and Behavioral Sciences. 126, 241-243 (2014).
  43. Dommer, L., Jäger, N., Scholkmann, F., Wolf, M., Holper, L. Between-brain coherence during joint n-back task performance: a two-person functional near-infrared spectroscopy study. Behavioural Brain Research. 234 (2), 212-222 (2012).
  44. Holper, L., Scholkmann, F., Wolf, M. Between-brain connectivity during imitation measured by fNIRS. Neuroimage. 63, 212-222 (2012).
  45. Nguyen, T., et al. The effects of interaction quality on neural synchrony during mother-child problem solving. Cortex. 124, 235-249 (2020).
  46. Seth, A. K., Barrett, A. B., Barnett, L. Granger causality analysis in neuroscience and neuroimaging. Journal of Neuroscience. 35 (8), 3293-3297 (2015).
  47. Funane, T., et al. Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy. Journal of Biomedical Optics. 16 (7), 077011 (2011).
  48. Liu, T., Saito, H., Oi, M. Role of the right inferior frontal gyrus in turn-based cooperation and competition: a near-infrared spectroscopy study. Brain and Cognition. 99, 17-23 (2015).
  49. Lachaux, J. P., Rodriguez, E., Martinerie, J., Varela, F. J. Measuring phase synchrony in brain signals. Human Brain Mapping. 8 (4), 194-208 (1999).
  50. Burgess, A. P. On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note. Frontiers in Human Neuroscience. 7, 881 (2013).
  51. Burgos-Robles, A., et al. Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment. Nature Neuroscience. 20 (6), 824-835 (2017).
  52. Mende, S., Proske, A., Narciss, S. Individual preparation for collaborative learning: Systematic review and synthesis. Educational Psychologist. , 1-25 (2020).
  53. Hamilton, A. F. D. C. Hyperscanning: Beyond the hype. Neuron. 109 (3), 404-407 (2021).
  54. Novembre, G., Iannetti, G. D. Hyperscanning alone cannot prove causality. Multibrain stimulation can. Trends in Cognitive Sciences. 25 (2), 96-99 (2021).
check_url/kr/62777?article_type=t

Play Video

Cite This Article
Zhao, N., Zhu, Y., Hu, Y. Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study. J. Vis. Exp. (173), e62777, doi:10.3791/62777 (2021).

View Video