Journal articles on the topic 'BRAIN COMMUNICATION'

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1

KIM, JeongTak. "Communication Philosophy in Taoism : Beyond “Brain-to-Brain” Communication." Asian Communication Research 14, no. 2 (December 31, 2017): 122–32. http://dx.doi.org/10.20879/acr.2017.14.2.122.

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2

Stower, Hannah. "Gut–brain communication." Nature Medicine 25, no. 12 (December 2019): 1799. http://dx.doi.org/10.1038/s41591-019-0685-y.

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3

Sakaguchi, Yutaka, Takeshi Aihara, Peter Ford Dominey, and Ichiro Tsuda. "Communication and Brain." Neural Networks 62 (February 2015): 1–2. http://dx.doi.org/10.1016/j.neunet.2014.12.005.

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4

Quan, Ning, and William A. Banks. "Brain-immune communication pathways." Brain, Behavior, and Immunity 21, no. 6 (August 2007): 727–35. http://dx.doi.org/10.1016/j.bbi.2007.05.005.

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5

Bara, Bruno G., and Maurizio Tirassa. "Neuropragmatics: Brain and Communication." Brain and Language 71, no. 1 (January 2000): 10–14. http://dx.doi.org/10.1006/brln.1999.2198.

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6

Powley, Terry L. "Brain-gut communication: vagovagal reflexes interconnect the two “brains”." American Journal of Physiology-Gastrointestinal and Liver Physiology 321, no. 5 (November 1, 2021): G576—G587. http://dx.doi.org/10.1152/ajpgi.00214.2021.

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The gastrointestinal tract has its own “brain,” the enteric nervous system or ENS, that executes routine housekeeping functions of digestion. The dorsal vagal complex in the central nervous system (CNS) brainstem, however, organizes vagovagal reflexes and establishes interconnections between the entire neuroaxis of the CNS and the gut. Thus, the dorsal vagal complex links the “CNS brain” to the “ENS brain.” This brain-gut connectome provides reflex adjustments that optimize digestion and assimilation of nutrients and fluid. Vagovagal circuitry also generates the plasticity and adaptability needed to maintain homeostasis to coordinate among organs and to react to environmental situations. Arguably, this dynamic flexibility provided by the vagal circuitry may, in some circumstances, lead to or complicate maladaptive disorders.
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7

De Massari, Daniele, Carolin A. Ruf, Adrian Furdea, Tamara Matuz, Linda van der Heiden, Sebastian Halder, Stefano Silvoni, and Niels Birbaumer. "Brain communication in the locked-in state." Brain 136, no. 6 (April 26, 2013): 1989–2000. http://dx.doi.org/10.1093/brain/awt102.

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8

Winek, Katarzyna, Daniel Cuervo Zanatta, and Marietta Zille. "Brain–body communication in stroke." Neuroforum 28, no. 1 (December 20, 2021): 31–39. http://dx.doi.org/10.1515/nf-2021-0030.

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Abstract Stroke is a leading cause of death and disability worldwide with limited therapeutic options available for selected groups of patients. The susceptibility to stroke depends also on systemic parameters, and some stroke risk factors are modifiable, such as atrial fibrillation (AF) or hypertension. When considering new treatment strategies, it is important to remember that the consequences of stroke are not limited to the central nervous system (CNS) injury, but reach beyond the boundaries of the brain. We provide here a brief overview of the mechanisms of how the brain communicates with the body, focusing on the heart, immune system, and gut microbiota (GM).
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9

Kübler, Andrea, Nicola Neumann, Barbara Wilhelm, Thilo Hinterberger, and Niels Birbaumer. "Predictability of Brain-Computer Communication." Journal of Psychophysiology 18, no. 2/3 (January 2004): 121–29. http://dx.doi.org/10.1027/0269-8803.18.23.121.

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Abstract Since 1996 we have been teaching more than 18 severely or totally paralyzed patients to successfully control the movements of a cursor on a computer screen by means of systematic changes in the amplitudes of their slow cortical potentials (SCPs; Birbaumer, Ghanayim, Hinterberger, Iversen, Kotchoubey et al., 1999 ). Patients learned regulation of their SCP amplitudes by means of a brain-computer interface (BCI) and on-line feedback about the time course of SCP amplitude shifts, represented by cursor movements on a computer screen. When patients were able to successfully regulate their SCP amplitude, they were trained to use this ability to communicate with friends and caregivers by means of a Language Support Program ( Perelmouter, Kotchoubey, Kübler, Taub, & Birbaumer, 1999 ). Having a reliable predictor of progress in training would be particularly helpful because training patients at their homes requires substantial effort and a positive outcome is desirable given limited personal and financial resources. In this study we present data from healthy participants (n = 10) and a sample of patients (n = 10), diagnosed with amyotrophic lateral sclerosis, who participated in six BCI training sessions; six patients continued training for another six sessions. All participants except one achieved stable significant cursor control. The number of sessions needed to achieve significant cursor control (initial training phase) correlated moderately with the number of sessions needed to achieve a correct response rate of 70% (advanced training phase). Individual differences in performance remained stable within the six training sessions. After six sessions both groups had achieved significant cursor control, but patients' performance was poorer than that of healthy participants. The patients, however, were trained once a week only, and for some patients longer breaks in training occurred. We conclude that learning during the initial training phase indicates the duration of training that will be necessary to achieve 70% correct responses. A higher frequency of training sessions per week seems necessary to achieve faster progress.
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10

Sagara, K. "Special Section on Brain Communication." IEICE Transactions on Communications E91-B, no. 7 (July 1, 2008): 2101. http://dx.doi.org/10.1093/ietcom/e91-b.7.2101.

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11

Souček, Branko, and Albert D. Carlson. "Brain windows in firefly communication." Journal of Theoretical Biology 119, no. 1 (March 1986): 47–65. http://dx.doi.org/10.1016/s0022-5193(86)80050-9.

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12

Agnati, L. F., K. Fuxe, and F. Mora. "Intercellular communication in the brain." Brain Research Reviews 55, no. 1 (August 2007): 1–2. http://dx.doi.org/10.1016/j.brainresrev.2007.07.004.

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13

Fujiki, Nobuya, and Yasushi Naito. "Auditory Communication and Brain Function." Japan Journal of Logopedics and Phoniatrics 48, no. 3 (2007): 277–83. http://dx.doi.org/10.5112/jjlp.48.277.

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14

Monje, Michelle. "Synaptic Communication in Brain Cancer." Cancer Research 80, no. 14 (May 7, 2020): 2979–82. http://dx.doi.org/10.1158/0008-5472.can-20-0646.

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15

Brown, Jason W. "Language, Communication and the Brain." Journal of Nervous and Mental Disease 176, no. 9 (September 1988): 576–77. http://dx.doi.org/10.1097/00005053-198809000-00014.

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16

Janić, Milan, Marko Ćirović, Nikolaos Dimitriadis, Neda Jovanović Dimitriadis, and Panayiota Alevizou. "Neuroscience and CSR: Using EEG for Assessing the Effectiveness of Branded Videos Related to Environmental Issues." Sustainability 14, no. 3 (January 25, 2022): 1347. http://dx.doi.org/10.3390/su14031347.

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The majority of studies evaluating the effectiveness of branded CSR campaigns are concentrated and base their conclusions on data collection through self-reporting questionnaires. Although such studies provide insights for evaluating the effectiveness of CSR communication methods, analysing the message that is communicated, the communication channel used and the explicit brain responses of those for whom the message is intended, they lack the ability to fully encapsulate the problem of communicating environmental messages by not taking into consideration what the recipients’ implicit brain reactions are presenting. Therefore, this study aims to investigate the effectiveness of CSR video communications relating to environmental issues through the lens of the recipients’ implicit self, by employing neuroscience-based assessments. For the examination of implicit brain perception, an electroencephalogram (EEG) was used, and the collected data was analysed through three indicators identified as the most influential indicators on human behaviour. These three indicators are emotional valence, the level of brain engagement and cognitive load. The study is conducted on individuals from the millennial generation in Thessaloniki, Greece, whose implicit brain responses to seven branded commercial videos are recorded. The seven videos were a part of CSR campaigns addressing environmental issues. Simultaneously, the self-reporting results from the participants were gathered for a comparison between the explicit and implicit brain responses. One of the key findings of the study is that the explicit and implicit brain responses differ to the extent that the CSR video communications’ brain friendliness has to be taken into account in the future, to ensure success. The results of the study provide an insight for the future creation process, conceptualisation, design and content of the effective CSR communication, in regard to environmental issues.
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17

Tuor, Paula, and Jenkins Zhao. "Pathogenesis of Brain: Autism Spectrum Disorders." Neuroscience and Neurological Surgery 2, no. 2 (April 20, 2018): 01–02. http://dx.doi.org/10.31579/2578-8868/029.

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Autism spectrum disorders (ASDs) affect as many as 1 in 45 children and are characterized by deficits in sociability and communication, as well as stereotypic movements. Many children also show severe anxiety.
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18

Vasile, Aurelia Ana. "Formal, Non-formal, and Informal Approaches in Prosocial Crisis Communication while Dealing with Refugees from Conflict Areas." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 14, no. 1 (March 9, 2023): 157–74. http://dx.doi.org/10.18662/brain/14.1/412.

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The way formal organisations (governmental), non-formal (non-governmental) organisations, and informal citizen communication deal with social crisis pro-socially, that is, to the benefit of others, accounts for some characteristics that are worth fathoming in order to create the framework for the development of better communication strategies and better and faster prosocial reaction within socially challenging crisis contexts. Crisis communication has been tackled in public relations mostly with regard to governmental and nongovernmental organisations, whilst citizen informal communication has not been a matter of PR scientific focus so far, and neither has a comparison between these ways to communicate been approached for that matter. As speed is key in communication, and mostly within a refugee crisis, a double fold quantitative and qualitative analysis of the communication content and strategies used by key social actors in a hub-country of refugee reception like Romania in the emergency context created by Russia’s invasion of Ukraine may provide useful scientific information to generate consequent strategic improvements. This content analysis methodological approach on communication in the social media and on websites of such various outlets (the Facebook pages and groups of the Romanian Red Cross, UNICEF, Romanian Government, the “Uniţi pentru Ucraina” group, the Romanian government, UNICEF and Red Cross websites) from 24th February 2022, the beginning of the conflict in Ukraine, to the moment, allows intriguing conclusions about the effectiveness, timeliness, and constancy in communicating support in times of social crisis within a prosocial approach in Romania to receiving refugees from the conflict areas in Ukraine.
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19

Chin, F. C. J., M. L. Ooi, and M. W. Yip. "The Effects of Colored Brain Communication and Brain Processing Interpretation on the Academic Performance of Students: A Literature Review." International Journal of Information and Education Technology 6, no. 12 (2016): 945–48. http://dx.doi.org/10.7763/ijiet.2016.v6.822.

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20

Dahal, Prawesh, Naureen Ghani, Adeen Flinker, Patricia Dugan, Daniel Friedman, Werner Doyle, Orrin Devinsky, Dion Khodagholy, and Jennifer N. Gelinas. "Interictal epileptiform discharges shape large-scale intercortical communication." Brain 142, no. 11 (September 9, 2019): 3502–13. http://dx.doi.org/10.1093/brain/awz269.

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Focal epilepsy is associated with large-scale brain dysfunction. Dahal et al. reveal that interictal epileptiform discharges modulate normal brain rhythms in regions beyond the epileptic network, potentially impairing processes that rely heavily upon intercortical communication, such as cognition and memory.
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21

Graham, Daniel, Andrea Avena-Koenigsberger, and Bratislav Mišić. "Editorial: Network Communication in the Brain." Network Neuroscience 4, no. 4 (January 2020): 976–79. http://dx.doi.org/10.1162/netn_e_00167.

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Communication models describe the flow of signals among nodes of a network. In neural systems, communication models are increasingly applied to investigate network dynamics across the whole brain, with the ultimate aim to understand how signal flow gives rise to brain function. Communication models range from diffusion-like processes to those related to infectious disease transmission and those inspired by engineered communication systems like the internet. This Focus Feature brings together novel investigations of a diverse range of mechanisms and strategies that could shape communication in mammal whole-brain networks.
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22

TANEMURA, Jun, and Akio TSUBAHARA. "Communication Disorders following Traumatic Brain Injury." Japanese Journal of Rehabilitation Medicine 43, no. 2 (2006): 110–19. http://dx.doi.org/10.2490/jjrm1963.43.110.

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23

Avena-Koenigsberger, Andrea, Bratislav Misic, and Olaf Sporns. "Communication dynamics in complex brain networks." Nature Reviews Neuroscience 19, no. 1 (December 14, 2017): 17–33. http://dx.doi.org/10.1038/nrn.2017.149.

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24

Xiaomei Pei, J. Hill, and G. Schalk. "Silent Communication: Toward Using Brain Signals." IEEE Pulse 3, no. 1 (January 2012): 43–46. http://dx.doi.org/10.1109/mpul.2011.2175637.

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25

Ylvisaker, Mark. "Communication Outcome Following Traumatic Brain Injury." Seminars in Speech and Language 13, no. 04 (November 1992): 239–51. http://dx.doi.org/10.1055/s-2008-1064200.

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26

Herzog, Jean. "Communication Disorders Following Traumatic Brain Injury." Journal of Head Trauma Rehabilitation 16, no. 6 (December 2001): 612–13. http://dx.doi.org/10.1097/00001199-200112000-00010.

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27

Berthoud, Hans-Rudolf, Andrew C. Shin, and Huiyuan Zheng. "Obesity surgery and gut–brain communication." Physiology & Behavior 105, no. 1 (November 2011): 106–19. http://dx.doi.org/10.1016/j.physbeh.2011.01.023.

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28

Newman, John D. "Vocal communication and the triune brain." Physiology & Behavior 79, no. 3 (August 2003): 495–502. http://dx.doi.org/10.1016/s0031-9384(03)00155-0.

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29

Morley, John E. "Bidirectional Communication Between Brain and Muscle." Journal of nutrition, health & aging 22, no. 10 (November 26, 2018): 1144–45. http://dx.doi.org/10.1007/s12603-018-1141-2.

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30

Sauma, Sami, and Patrizia Casaccia. "Gut-brain communication in demyelinating disorders." Current Opinion in Neurobiology 62 (June 2020): 92–101. http://dx.doi.org/10.1016/j.conb.2020.01.005.

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31

Ebrahimi, T., J. M. Vesin, and G. Garcia. "Brain-computer interface in multimedia communication." IEEE Signal Processing Magazine 20, no. 1 (January 2003): 14–24. http://dx.doi.org/10.1109/msp.2003.1166626.

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32

Wolpaw, Jonathan R., and Dennis J. McFarland. "Multichannel EEG-based brain-computer communication." Electroencephalography and Clinical Neurophysiology 90, no. 6 (June 1994): 444–49. http://dx.doi.org/10.1016/0013-4694(94)90135-x.

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33

Brumberg, Jonathan S., Alfonso Nieto-Castanon, Philip R. Kennedy, and Frank H. Guenther. "Brain–computer interfaces for speech communication." Speech Communication 52, no. 4 (April 2010): 367–79. http://dx.doi.org/10.1016/j.specom.2010.01.001.

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34

Aroniadis, Olga C., Douglas A. Drossman, and Magnus Simrén. "A Perspective on Brain–Gut Communication." Psychosomatic Medicine 79, no. 8 (October 2017): 847–56. http://dx.doi.org/10.1097/psy.0000000000000431.

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35

Johnson, Pamela R., and Claudia Rawlins Daumer. "Intuitive Development: Communication in the Nineties." Public Personnel Management 22, no. 2 (June 1993): 257–68. http://dx.doi.org/10.1177/009102609302200206.

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Communication is an intuitive as well as cognitive process. In order to develop the brain skill of intuition, it is sometimes necessary to shut down cognitive (left-brain analyses and pay special attention to intuitive (right-brain) ways of knowing. The brain hemispheres work differently and yet in conjunction. This article suggests techniques for developing intuitive brain skills. Mandalas, “other” hand writing, and positive affirmations can be used to improve intuitive skills.
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36

Birbaumer, N. "Brain–machine interfaces (BMI) for brain communication and chronic stroke." Annals of Physical and Rehabilitation Medicine 56 (October 2013): e373. http://dx.doi.org/10.1016/j.rehab.2013.07.961.

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37

BLONDER, L. X., D. BOWERS, and K. M. HEILMAN. "THE ROLE OF THE RIGHT HEMISPHERE IN EMOTIONAL COMMUNICATION." Brain 114, no. 3 (June 1, 1991): 1115–27. http://dx.doi.org/10.1093/brain/114.3.1115.

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38

BLONDER, LEE XENAKIS, DAWN BOWERS, and KENNETH M. HELLMAN. "THE ROLE OF THE RIGHT HEMISPHERE IN EMOTIONAL COMMUNICATION." Brain 115, no. 2 (1992): 645. http://dx.doi.org/10.1093/brain/115.2.645.

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39

Wang, Zhuo, Niting Wang, Zehua Li, Fangyan Xiao, and Jiapei Dai. "Human high intelligence is involved in spectral redshift of biophotonic activities in the brain." Proceedings of the National Academy of Sciences 113, no. 31 (July 18, 2016): 8753–58. http://dx.doi.org/10.1073/pnas.1604855113.

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Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain.
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40

Ramírez-Moreno, Mauricio A., Jesús G. Cruz-Garza, Akanksha Acharya, Girija Chatufale, Woody Witt, Dan Gelok, Guillermo Reza, and José L. Contreras-Vidal. "Brain-to-brain communication during musical improvisation: a performance case study." F1000Research 11 (September 1, 2022): 989. http://dx.doi.org/10.12688/f1000research.123515.1.

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Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the synchronization of scalp electroencephalographic (EEG) signals from three expert musicians during a three-part 45 minute jazz performance, during which a new musician joined every five minutes. The bispectrum was estimated for all musician dyads, electrode combinations, and five frequency bands. The results showed higher bispectrum in the beta and gamma frequency bands (13-50 Hz) when more musicians performed together, and when they played a musical phrase synchronously. Positive bispectrum amplitude changes were found approximately three seconds prior to the identified synchronized performance events suggesting preparatory cortical activity predictive of concerted behavioral action. Moreover, a higher amount of synchronized EEG activity, across electrode regions, was observed as more musicians performed, with inter-brain synchronization between the temporal, parietal, and occipital regions the most frequent. Increased synchrony between the musicians' brain activity reflects shared multi-sensory processing and movement intention in a musical improvisation task.
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41

Grau, Carles, Romuald Ginhoux, Alejandro Riera, Thanh Lam Nguyen, Hubert Chauvat, Michel Berg, Julià L. Amengual, Alvaro Pascual-Leone, and Giulio Ruffini. "Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies." PLoS ONE 9, no. 8 (August 19, 2014): e105225. http://dx.doi.org/10.1371/journal.pone.0105225.

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42

Hurley, Dan. "Report Describes First Instance of Direct, Noninvasive Brain-to-Brain Communication." Neurology Today 14, no. 21 (November 2014): 33–37. http://dx.doi.org/10.1097/01.nt.0000457149.60646.22.

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43

Neumann, Nicola, Andrea Kübler, Jochen Kaiser, Thilo Hinterberger, and Niels Birbaumer. "Conscious perception of brain states: mental strategies for brain–computer communication." Neuropsychologia 41, no. 8 (January 2003): 1028–36. http://dx.doi.org/10.1016/s0028-3932(02)00298-1.

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44

Sutter, Erich E. "The brain response interface: communication through visually-induced electrical brain responses." Journal of Microcomputer Applications 15, no. 1 (January 1992): 31–45. http://dx.doi.org/10.1016/0745-7138(92)90045-7.

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45

Grau, Carles, Romuald Ginhoux, Alejandro Riera, Thanh Lam Nguyen, Hubert Chauvat, Michel Berg, Julià L. Amengual, Alvaro Pascual-Leone, and Giulio Ruffini. "Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies." Brain Stimulation 8, no. 2 (March 2015): 323. http://dx.doi.org/10.1016/j.brs.2015.01.047.

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46

Liu, Wei, Xinying Zhang, Zifeng Wu, Kai Huang, Chun Yang, and Ling Yang. "Brain–heart communication in health and diseases." Brain Research Bulletin 183 (June 2022): 27–37. http://dx.doi.org/10.1016/j.brainresbull.2022.02.012.

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47

Kitada, Ryo. "Cognitive Brain Mechanisms Underlying Haptic Social Communication." Journal of the Robotics Society of Japan 30, no. 5 (2012): 466–68. http://dx.doi.org/10.7210/jrsj.30.466.

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48

Bosone, Camilla, Abraham Andreu, and Diego Echevarria. "GAP junctional communication in brain secondary organizers." Development, Growth & Differentiation 58, no. 5 (June 2016): 446–55. http://dx.doi.org/10.1111/dgd.12297.

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49

Mingui Sun, M. Mickle, Wei Liang, Qiang Liu, and R. J. Sclabassi. "Data communication between brain implants and computer." IEEE Transactions on Neural Systems and Rehabilitation Engineering 11, no. 2 (June 2003): 189–92. http://dx.doi.org/10.1109/tnsre.2003.814421.

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50

McEwen, Bruce S. "Epigenetic Interactions and the Brain-Body Communication." Psychotherapy and Psychosomatics 86, no. 1 (November 25, 2016): 1–4. http://dx.doi.org/10.1159/000449150.

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