Relevant bibliographies by topics / Auditory Brain Responses

Academic literature on the topic 'Auditory Brain Responses'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Auditory Brain Responses"

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Kayed, Khalil, and Reidar Kloster. "Brain Stem Auditory Evoked Responses." Acta Neurologica Scandinavica 62, no. 1 (January 29, 2009): 64. http://dx.doi.org/10.1111/j.1600-0404.1980.tb03005.x.

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Busaba, Nicolas Y., and Steven D. Rauch. "Significance of Auditory Brain Stem Response and Gadolinium-Enhanced Magnetic Resonance Imaging for Idiopathic Sudden Sensorineural Hearing Loss." Otolaryngology–Head and Neck Surgery 113, no. 3 (September 1995): 271–75. http://dx.doi.org/10.1016/s0194-5998(95)70117-6.

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Previous studies tried to correlate prognosis and response to oral corticosteroids in patients with idiopathic sudden sensorineural hearing loss to such factors as the age of the patient, presence of vertigo, shape of the audiogram, or severity of the hearing loss. However, temporal bone histopathologic evidence shows that idiopathic sudden sensorineural hearing loss may be caused by cochleitis or cochlear nerve neuritis. Herein we report results of a retrospective study of 96 consecutive patients with idiopathic sudden sensorineural hearing loss who were evaluated with auditory brain stem responses and gadolinium-enhanced magnetic resonance imaging. Results of the auditory brain stem response and magnetic resonance imaging were correlated with hearing outcome. Follow-up was available for 65 patients: 14 with abnormal and 51 with normal auditory brain stem responses. The overall rate of hearing recovery or improvement was 65% in the normal auditory brain stem response group compared with 43% in the abnormal auditory brain stem response group ( p = 0.07). Among the 38 patients treated with a tapering course of oral corticosteroids, the recovery or improvement rate was 83% for those with normal auditory brain stem responses and 56% for those with abnormal auditory brain stem responses ( p < 0.05). Of the 27 patients who did not receive steroid therapy, the improvement rate was 41% in those with normal auditory brain stem responses and 20% in those with abnormal auditory brain stem responses ( p = 0.09). Magnetic resonance imaging with gadolinium was obtained on all 14 patients with abnormal auditory brain stem responses but on none with normal auditory brain stem responses. Only 1 magnetic resonance image of 14 demonstrated an abnormality, showing a high signal intensity in the distal internal auditory canal; this resolved 6 weeks later on a follow-up magnetic resonance image. We conclude that idiopathic sudden sensorineural hearing loss patients with abnormal auditory brain stem responses have poorer hearing prognoses compared with those patients with normal auditory brain stem responses, irrespective of treatment. Idiopathic sudden sensorineural hearing loss patients with abnormal auditory brain stem responses may have cochlear neuritis causing their hearing loss or may have a more extensive involvement of their auditory system, and this “lesion” may have a lower spontaneous recovery rate and less response to therapy. Magnetic resonance imaging with gadolinium may show abnormal signal intensities along the course of the eighth nerve in patients with idiopathic sudden sensorineural hearing loss, but this is infrequent, and its prognostic implications are not clear.
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Rosenhall, Ulf, Viviann Nordin, Krister Brantberg, and Christopher Gillberg. "Autism and Auditory Brain Stem Responses." Ear and Hearing 24, no. 3 (June 2003): 206–14. http://dx.doi.org/10.1097/01.aud.0000069326.11466.7e.

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Creel, Donnell J., John B. Holds, and Richard L. Anderson. "Auditory brain-stem responses in blepharospasm." Electroencephalography and Clinical Neurophysiology 86, no. 2 (February 1993): 138–40. http://dx.doi.org/10.1016/0013-4694(93)90086-b.

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ARAO, HARUMI, and HIDETO NIWA. "Auditory brain stem responses in Down's syndrome." Nippon Jibiinkoka Gakkai Kaiho 94, no. 11 (1991): 1673–82. http://dx.doi.org/10.3950/jibiinkoka.94.11_1673.

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Newman, Thomas B. "Neonatal jaundice and brain-stem auditory responses." Journal of Pediatrics 118, no. 4 (April 1991): 653. http://dx.doi.org/10.1016/s0022-3476(05)83398-0.

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HARELL, MOSHE, MOSHE ENGLENDER, ROBERT KIMHI, MYRIAM DEMER, and MOSHE ZOHAR. "AUDITORY BRAIN STEM RESPONSES IN SCHIZOPHRENIC PATIENTS." Laryngoscope 96, no. 8 (August 1986): 908???910. http://dx.doi.org/10.1288/00005537-198608000-00015.

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Wilson, Michael J., Denise Kelly-Ballweber, and Robert A. Dobie. "Binaural Interaction in Auditory Brain Stem Responses." Ear and Hearing 6, no. 2 (March 1985): 80–88. http://dx.doi.org/10.1097/00003446-198503000-00004.

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Schwartz, Daniel M., Robert E. Pratt, and Jamie A. Schwartz. "Auditory Brain Stem Responses in Preterm Infants." Ear and Hearing 10, no. 1 (February 1989): 14–22. http://dx.doi.org/10.1097/00003446-198902000-00003.

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Özdamar, Ö., and T. Kalayci. "Median Averaging of Auditory Brain Stem Responses." Ear and Hearing 20, no. 3 (June 1999): 253–64. http://dx.doi.org/10.1097/00003446-199906000-00007.

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Dissertations / Theses on the topic "Auditory Brain Responses"

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Harkrider, Ashley Whicker. "The acute effects of nicotine on physiological responses from the auditory systems of non-smokers /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Hart, Heledd. "Characterisation of responses of human auditory cortex to basic sound properties, as measured using fMRI." Thesis, University of Nottingham, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272359.

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Souto, Carlos Filipe da Silva [Verfasser], Birger [Akademischer Betreuer] Kollmeier, and Jesko L. [Akademischer Betreuer] Verhey. "Speech-related brain responses as a basis for auditory brain-computer interfaces / Carlos Filipe da Silva Souto ; Birger Kollmeier, Jesko L. Verhey." Oldenburg : BIS der Universität Oldenburg, 2019. http://d-nb.info/1201481325/34.

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Zhang, Yan. "The impact of midbrain cauterize size on auditory and visual responses' distribution." unrestricted, 2009. http://etd.gsu.edu/theses/available/etd-04202009-145923/.

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Thesis (M.S.)--Georgia State University, 2009.
Title from file title page. Yu-Sheng Hsu, committee chair; Xu Zhang, Sarah. L. Pallas, committee members. Description based on contents viewed June 12, 2009. Includes bibliographical references (p. 37). Appendix A: SAS code: p. 38-53.
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Sams, Mikko. "Electrical and magnetic responses of the humain brain to auditory pitch changes : reflections of automatic and controlled information processing /." Helsinki : Suomalainen tiedeakatemia, 1985. http://catalogue.bnf.fr/ark:/12148/cb34885954k.

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Sams, Mikko. "Electrical and magnetic responses of the human brain to auditory pitch changes reflections of automatic and controlled information processing /." Hki : Suomalainen tiedeakatemia : Akateeminen kirjakauppa [distr.], 1985. http://catalog.hathitrust.org/api/volumes/oclc/58505576.html.

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Lecaignard, Françoise. "Predictive coding in auditory processing : insights from advanced modeling of EEG and MEG mismatch responses." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1160/document.

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Cette thèse porte sur le codage prédictif comme principe général pour la perception et vise à en étayer les mécanismes computationnels et neurophysiologiques dans la modalité auditive. Ce codage repose sur des erreurs de prédictions se propageant dans une hiérarchie, et qui pourraient se refléter dans des réponses cérébrales au changement (ou déviance) telles que la Négativité de discordance (mismatch negativity, MMN). Nous avons manipulé la prédictibilité de sons déviants et utilisé des approches de modélisation computationnelle et dynamique causale (DCM) appliquées à des enregistrements électrophysiologiques (EEG, MEG) simultanés.Une modulation des réponses à la déviance par la prédictibilité a été observée, permettant d'établir un lien avec les erreurs de prédictions. Cet effet implique un apprentissage implicite des régularités acoustiques, dont l'influence sur le traitement auditif a pu être caractérisée par notre approche de modélisation. Sur le plan computationnel, un apprentissage a été mis en évidence au cours de ce traitement auditif, reposant sur une fenêtre d'intégration temporelle dont la taille varie avec la prédictibilité des déviants. Cet effet pourrait également moduler la connectivité synaptique sous-tendant le traitement auditif, comme le suggère l'analyse DCM.Nos résultats mettent en évidence la mise en œuvre d'un apprentissage perceptif au sein d'une hiérarchie auditive soumis à une modulation par la prédictibilité du contexte acoustique, conformément aux prédictions du codage prédictif. Ils soulignent également l'intérêt de ce cadre théorique pour émettre et tester expérimentalement des hypothèses mécanistiques précises
This thesis aims at testing the predictive coding account of auditory perception. This framework rests on precision-weighted prediction errors elicited by unexpected sounds that propagate along a hierarchical organization in order to maintain the brain adapted to a varying acoustic environment. Using the mismatch negativity (MMN), a brain response to unexpected stimuli (deviants) that could reflect such errors, we could address the computational and neurophysiological underpinnings of predictive coding. Precisely, we manipulated the predictability of deviants and applied computational learning models and dynamic causal models (DCM) to electrophysiological responses (EEG, MEG) measured simultaneously. Deviant predictability was found to modulate deviance responses, a result supporting their interpretation as prediction errors. Such effect might involve the (high-level) implicit learning of sound sequence regularities that would in turn influence auditory processing in lower hierarchical levels. Computational modeling revealed the perceptual learning of sounds, resting on temporal integration exhibiting differences induced by our predictability manipulation. In addition, DCM analysis indicated predictability changes in the synaptic connectivity established by deviance processing. These results conform predictive coding predictions regarding both deviance processing and its modulation by deviant predictability and strongly support perceptual learning of auditory regularities achieved within an auditory hierarchy. Our findings also highlight the power of this mechanistic framework to elaborate and test new hypothesis enabling to improve our understanding of auditory processing
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Stephenson, Mark Ray. "Human auditory brainstem response to dichotic click stimuli /." The Ohio State University, 1986. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487267546983858.

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Sallinen, Mikael. "Event-related brain potentials to changes in the acoustic environment during sleep and sleepiness." Jyväskylä : University of Jyväskylä, 1997. http://catalog.hathitrust.org/api/volumes/oclc/39009942.html.

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Turkstra, Lyn Siobhan. "Autonomic response to auditory and visual stimulation in severely brain-injured adults." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186485.

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The clinical utility of electrodermal response measures as a predictor of outcome from traumatic vegetative state was investigated. Electrodermal potential data were obtained from five subjects in acute vegetative state at 1 to 3 months post-trauma (Acute group), five subjects in persistent vegetative state at more than 1 year post-trauma (PVS group), five subjects who were more than 1 year post-trauma and had recovered from vegetative state (RVS group), and 10 normal subjects (Control group). Measures included startle response amplitude, baseline lability, habituation and orientation to tones, responses to famous faces and written commands, and total number of skin potential responses. In addition, subjects in the Acute group were reassessed with respect to clinical outcome at 6 months post-trauma. Results revealed significant group differences between the Control group and each of the brain-injured groups in startle response amplitude, baseline lability, and total number of responses. The RVS group had significantly larger startle response amplitudes than the PVS group. Some subjects in the PVS group and all subjects in the Acute group exhibited no startle response on one or more days of testing. Significant group differences also were found for habituation and orientation. Habituation was present in 80% of the Control and RVS subjects, 20% of the Acute subjects and 0% of the PVS subjects, and orientation was present in 80% of the Control subjects, 20% of the Acute and RVS subjects and 0% of the PVS subjects. Group variance in startle response amplitude, baseline lability and total number of responses was significantly greater in the Control group compared with the brain-injured subject groups. In the Acute group, a larger startle response amplitude, greater baseline lability, a greater total number of electrodermal responses, and habituation and orientation were associated with a positive outcome at 6 months post-trauma. These results indicate electrodermal responsiveness is generally reduced following traumatic brain injury, even in subjects with a relatively good recovery from vegetative state. Greater electrodermal activity in early vegetative state may be associated with better potential for recovery.
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Books on the topic "Auditory Brain Responses"

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Sams, Mikko. Electrical and magnetic responses of the human brain to auditory pitch changes: Reflections of automatic and controlled processing. Helsinki: Suomalainen Tiedeakatemia, 1985.

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I, Berlin Charles, ed. Auditory evoked potentials. Austin, Tex: PRO-ED, 1986.

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Alho, Kimmo. Mechanisms of selective listening reflected by event-related brain potentials in humans. Helsinki: Suomalainen Tiedeakatemia, 1987.

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Irvine, D. R. F. The auditory brainstem: A review of the structure and function of auditory brainstem processing mechanisms. Berlin: Springer-Verlag, 1986.

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1943-, Jacobson John T., ed. The Auditory brainstem response. San Diego, Calif: College-Hill Press, 1985.

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Gary, Jackson C., Josey Anne Forrest, and Glasscock Michael E. 1933-, eds. The ABR handbook: Auditory brainstem response. 2nd ed. New York: Thieme Medical Publishers, 1987.

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Clinical applications of the auditory brainstem response. San Diego: Singular Pub. Group, 1998.

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Schroeder, Linda L. The very basics of ABR: An introduction to auditory brainstem response. Danville, Ill: Interstate, 1989.

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J, Kramer Steven, ed. The very basics of ABR: An introduction to auditory brainstem response. Danville, Ill: Interstate Printers & Publishers, 1989.

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Eggermont, Jos J. Brain Responses to Auditory Mismatch and Novelty Detection: Predictive Coding from Cocktail Parties to Auditory-Related Disorders. Elsevier Science & Technology Books, 2024.

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Book chapters on the topic "Auditory Brain Responses"

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Nagao, S., H. Kuyama, Y. Honma, F. Momma, T. Nishiura, M. Suga, T. Murota, T. Tanimoto, M. Kawauchi, and A. Nishimoto. "Auditory Brain Stem Responses in Uncal Herniation." In Intracranial Pressure VI, 331–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-70971-5_61.

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Csépe, Valéria, Georg Juckel, Márk Molnár, and George Karmos. "Stimulus-Related Oscillatory Responses in the Auditory Cortex of Cats." In Oscillatory Event-Related Brain Dynamics, 383–88. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1307-4_27.

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Ikawa, Nobuko, Akira Morimoto, and Ryuichi Ashino. "Application of Complex Continuous Wavelet Analysis to Auditory Evoked Brain Responses." In Trends in Mathematics, 543–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04459-6_52.

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Stone, J. L., R. F. Ghaly, K. S. Subramanian, and P. Roccaforte. "Transtentorial Brain Herniation in the Monkey: Predictive Value of Brain-Stem Auditory and Somatosensory Evoked Responses." In Intracranial Pressure VII, 623–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-73987-3_161.

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Regan, D., and M. P. Regan. "Ultra-High Resolution Analysis of Auditory and Visual Brain Responses Using Zoom-FFT." In Advances in Biomagnetism, 205–7. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0581-1_38.

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Bertrand, Olivier, and Christo Pantev. "Stimulus Frequency Dependence of the Transient Oscillatory Auditory Evoked Responses (40 Hz) Studied by Electric and Magnetic Recordings in Human." In Oscillatory Event-Related Brain Dynamics, 231–42. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1307-4_17.

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Tsutsui, T., M. Nitta, A. Ladds, and L. Symon. "The Effects of an Expanding Supratentorial Mass on Auditory Brain Stem Responses in Baboons." In Intracranial Pressure VI, 335–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-70971-5_62.

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Li, Songhai, Paul E. Nachtigall, and Marlee Breese. "Auditory Brain Stem Responses Associated with Echolocation in an Atlantic Bottlenose Dolphin (Tursiops truncatus)." In Advances in Experimental Medicine and Biology, 45–47. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-7311-5_9.

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Talacchi, A., L. Cristofori, D. Garozzo, L. Deotto, and A. Bricolo. "Auditory Evoked Responses and Blink Reflex in Brain-Stem Cavernous Angiomas. Report of 7 Cases." In New Trends in Management of Cerebro-Vascular Malformations, 546–49. Vienna: Springer Vienna, 1994. http://dx.doi.org/10.1007/978-3-7091-9330-3_93.

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Perrin, F., O. Bertrand, and J. Pernier. "Early Cortical Somatosensory and N1 Auditory Evoked Responses: Analysis with Potential Maps, Scalp Current Density Maps and Three-Concentric-Shell Head Models." In Topographic Brain Mapping of EEG and Evoked Potentials, 390–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-72658-3_44.

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Conference papers on the topic "Auditory Brain Responses"

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Matsumoto, Yoshihiro, Shoji Makino, Koichi Mori, and Tomasz M. Rutkowski. "Classifying P300 responses to vowel stimuli for auditory brain-computer interface." In 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, 2013. http://dx.doi.org/10.1109/apsipa.2013.6694341.

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Chikara, Rupesh Kumar, Ramesh Perumal, Li-Wei Ko, and Hsin Chen. "EEG dynamics in inhibition of left-hand and right-hand responses during auditory stop-signal task." In 2014 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB). IEEE, 2014. http://dx.doi.org/10.1109/ccmb.2014.7020703.

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Hu, Min, and GuoZhong Liu. "Research of brain activation regions of "yes" and "no" responses by auditory stimulations in human EEG." In International Conference on Optical Instruments and Technology (OIT2011). SPIE, 2011. http://dx.doi.org/10.1117/12.905015.

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Li, Guoshi, Stacy Cheng, Frank Ko, Scott L. Raunch, Gregory Quirk, and Satish S. Nair. "Computational Modeling of Lateral Amygdala Neurons During Acquisition and Extinction of Conditioned Fear, Using Hebbian Learning." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15078.

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The amygdaloid complex located within the medial temporal lobe plays an important role in the acquisition and expression of learned fear associations (Quirk et al. 2003) and contains three main components: the lateral nucleus (LA), the basal nucleus (BLA), and the central nucleus (CE) (Faber and Sah, 2002). The lateral nucleus of the amygdala (LA) is widely accepted to be a key site of plastic synaptic events that contributes to fear learning (Pare, Quirk, LeDoux, 2004). There are two main types of neurons within the LA and the BLA: principal pyramidal-like cells which form projection neurons and are glutamatergic and local circuit GABAergic interneurons (Faber and Sah, 2002). In auditory fear conditioning, convergence of tone [conditioned stimulus (CS)] and foot-shock [unconditioned stimulus (US)] inputs potentiates the synaptic transmission containing CS information from the thalamus and cortex to LA, which leads to larger responses in LA in the presentation of subsequent tones only. The increasing LA responses disinhibit the CE neurons via the intercalated (ITC) cells, eliciting fear responses via excessive projections to brain stem and hypothalamic sites (Pare, Quirk, LeDoux, 2004). As a result, rats learn to freeze to a tone that predicts a foot-shock. Once acquired, conditioned fear associations are not always expressed and repeated presentation of the tone CS in the absence of US causes conditioned fear responses to rapidly diminish, a phenomenon termed fear extinction (Quirk et al. 2003). Extinction does not erase the CS-US association, instead it forms a new memory that inhibits conditioned response (Quirk et al. 2003)
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Animashaun, Aisha, and Gilberto Bernardes. "Noise promotes disengagement in dementia patients during non-invasive neurorehabilitation treatment." In 4th Symposium on Occupational Safety and Health. FEUP, 2021. http://dx.doi.org/10.24840/978-972-752-279-8_0009-0014.

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Introduction:The lack of engagement and the shortage of motivation and drive, also referred to as apathy, negatively impacts the effectiveness and adherence to treatment and the general well-being of people with neurocognitive disorders (NCDs), such as dementia. Methodology:The hypothesis raised states that the engagement of people with dementia during their non-invasive treatments for NCDs is affected by the noisy source levels and negative auditory stimuli present within environmental treatment settings. An online survey was conducted with the study objectives to assess 1) the engagement levels of dementia patients while interacting with others at home versus in therapy facilities, 2) the emotions perceived when interacting with people at home compared to therapy sessions, 3) the perceived loudness of the environment at home versus in therapy facilities, and 4) which source sounds negatively impact the patients at home and during therapy sessions. A purposive sampling (n=62) targeting relatives, friends, and caregivers of dementia patients was conducted via online community forums in the DACH region. Moreover, a recording session was conducted in a psychotherapist’s office to verify the answer tothe questionnaire on the noise sources perceived in therapy facilities. Results and Discussion:The raised hypothesis that disruptive auditory stimuli and noise levels influence the engagement levels of demented individuals during treatment is confirmed as the engagement is affected by the perceived noise disruptions when comparing perceived noise levels and engagement at home to those in treatment facilities.Significant statistical results were found between the lower engagement of demented individuals when interacting with people during therapy sessions compared to higher engagement in-home interactions. Furthermore, negatively perceived sound sources can be found in both therapy facilities and home settings. The noise sound sources identified, such as human voices, household appliances and household noises, while recording inthe psychotherapist’s office align with the questionnaire responses received on this topic. The findings indicate that the perceived heightened noise levels in therapy facilities stand in correlation with the lowered engagement rate perceived during the therapy session compared to the lower noise level and higher engagement encountered when demented individuals interact at home. Conclusion:If the identified noise elements are masked or replaced by other auditory stimuli that promote a soothing soundscape, the original disturbances encountered during therapy and the lack of engagement can possibly be minimized. Further studies need to be conducted in the prototyping of a noise intervention tool to analyze the impact on lack of engagement through noise disturbances.Keywords. Noise, Engagement, Dementia, Therapy, Apathy.INTRODUCTIONNeurocognitive disorders (NCDs) are a steadily rising global public health concern. In 2020, around 50 million people worldwide lived with major NCDs, specifically dementia, with nearly 10 million new cases per year1NCDs can be found in many diseases, including Alzheimer, Parkinson, Huntington, and Creutzfeldt-Jakob (Reith, 2018). The causes of NCDs are typically associated with advanced age. Still, it can occur from incidents such as traumatic brain injuries, infections, thyroid problems, damage to the blood vessels, and other causes (Kane et al., 2017), increasingly affecting a wide range of people and age groups. Successful treatment methods are limited and can be split into two main categories, invasive and non-invasive methods.Invasive treatment methods are surgical procedures, such as Deep Brain Stimulation (DBS), a neurosurgical procedure in which a neurotransmitter is placed in the brain to send electrical 1World Health Organization, Dementia [website] https://www.who.int/news-room/fact-sheets/detail/dementia(accessed 12 April 2021)
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Miles, Thimothy, Eva Ignatious, Sami Azam, Mirjam Jonkman, and Friso De Boer. "Mathematically Modelling the Brain Response to Auditory Stimulus." In TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON). IEEE, 2021. http://dx.doi.org/10.1109/tencon54134.2021.9707290.

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Beauchene, Christine, Alexander Leonessa, Subhradeep Roy, James Simon, and Nicole Abaid. "Closed-Loop Control of the Frequency Response of the Virtual Brain Model." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5117.

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The brain is a highly complex network and analyzing brain connectivity is a nontrivial task. Consequently, the neuroscience community created a large-scale, customizable, mathematical model which simulates brain activity called The Virtual Brain (TVB). Using TVB, we seek to control electroencephalography (EEG) measured brain states using auditory inputs, through TVB. A safe non-invasive brain stimulation method is binaural beats (BB) which arise from the brain’s interpretation of two pure tones, with a small frequency mismatch, delivered independently to each ear. A third phantom BB, whose frequency is equal to the difference of the two presented tones, is produced. This paper details the development and proof-of-concept testing of a simulation environment for an EEG-based closed-loop control of TVB using BB. Results suggest that the connectivity networks, constructed from simulated EEG, may change with certain BB stimulation frequency. In this work, we demonstrate that a linear controller can successfully modulate TVB connectivity.
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Madhale Jadav, Guruprasad, Luka Batistic, Sasa Vlahinic, and Miroslav Vrankic. "Brain computer interface communicator: A response to auditory stimuli experiment." In 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2017. http://dx.doi.org/10.23919/mipro.2017.7973461.

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Nakaizumi, Chisaki, Shoji Makino, and Tomasz M. Rutkowski. "Head-related impulse response cues for spatial auditory brain-computer interface." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7318550.

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Neklyudova, Anastasia, Anna Rebreikina, Victoria Voinova, Kirill Smirnov, Daria Kostanyan, Daria Kleeva, Gurgen Soghoyan, and Olga Sysoeva. "CHARACTERISTIC OF BRAIN RESPONSE TO 40-Hz AUDITORY STIMULATION IN RETT SYNDROME." In XVII INTERNATIONAL INTERDISCIPLINARY CONGRESS NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY. LCC MAKS Press, 2021. http://dx.doi.org/10.29003/m2251.sudak.ns2021-17/278-279.

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