The neural mechanisms underpinning the dynamic switching of a listener’s attention between speakers are not well understood. Here we addressed this issue in a natural conversation involving 21 triadic adult groups. Results showed that when the listener’s attention dynamically switched between speakers, neural synchronization with the to-be-attended speaker was significantly enhanced, whereas that with the to-be-ignored speaker was significantly suppressed. Along with attention switching, semantic distances between sentences significantly increased in the to-be-ignored speech. Moreover, neural synchronization negatively correlated with the increase in semantic distance but not with acoustic change of the to-be-ignored speech. However, no difference in neural synchronization was found between the listener and the two speakers during the phase of sustained attention. These findings support the attenuation model of attention, indicating that both speech signals are processed beyond the basic physical level. Additionally, shifting attention imposes a cognitive burden, as demonstrated by the opposite fluctuations of interpersonal neural synchronization.
BaldassanoC.ChenJ.ZadboodA.PillowJ. W.HassonU.NormanK. A. (2017). Discovering event structure in continuous narrative perception and memory. Neuron, 95(3), 709–721.e5. https://doi.org/10.1016/j.neuron.2017.06.041
2.
BertiS.SchrögerE. (2003). Working memory controls involuntary attention switching: Evidence from an auditory distraction paradigm. European Journal of Neuroscience, 17(5), 1119–1122. https://doi.org/10.1046/j.1460-9568.2003.02527.x
BögelsS.TorreiraF. (2021). Turn-end estimation in conversational turn-taking: The roles of context and prosody. Discourse Processes, 58(10), 903–924. https://doi.org/10.1080/0163853X.2021.1986664
5.
BroadbentD. E. (1958). Perception and communication. Pergamon Press.
6.
BrodbeckC.JiaoA.HongL. E.SimonJ. Z. (2020). Neural speech restoration at the cocktail party: Auditory cortex recovers masked speech of both attended and ignored speakers. PLOS Biology, 18(10), Article e3000883. https://doi.org/10.1371/journal.pbio.3000883
7.
ChoiH.KimJ.JoeS.GwonY. (2021). Evaluation of BERT and ALBERT sentence embedding performance on downstream NLP tasks. In 2020 25th International Conference on Pattern Recognition (ICPR), pp. 5482–5487. IEEE. https://doi.org/10.1109/ICPR48806.2021.9412102
8.
CuiX.BryantD. M.ReissA. L. (2012). NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation. NeuroImage, 59, 2430–2437. https://doi.org/10.1016/j.neuroimage.2011.09.003
9.
CuiY.CheW.LiuT.QinB.YangZ. (2021). Pre-training with whole word masking for Chinese BERT. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29, 3504–3514. https://doi.org/10.1109/TASLP.2021.3124365
10.
Da CostaS. D.van der ZwaagW.MillerL. M.ClarkeS.SaenzM. (2013). Tuning in to sound: Frequency-selective attentional filter in human primary auditory cortex. Journal of Neuroscience, 33(5), 1858–1863. https://doi.org/10.1523/JNEUROSCI.4405-12.2013
11.
DaiB.ChenC.LongY.ZhengL.ZhaoH.BaiX.LiuW.ZhangY.LiuL.GuoT.DingG.LuC. (2018). Neural mechanisms for selectively tuning in to the target speaker in a naturalistic noisy situation. Nature Communications, 9(1), Article 2405. https://doi.org/10.1038/s41467-018-04819-z
12.
DaiB.McQueenJ. M.HagoortP.KösemA. (2017). Pure linguistic interference during comprehension of competing speech signals. The Journal of the Acoustical Society of America, 141(3), EL249–EL254. https://doi.org/10.1121/1.4977590
13.
DaiB.McQueenJ. M.TerportenR.HagoortP.KösemA. (2022). Distracting linguistic information impairs neural tracking of attended speech. Current Research in Neurobiology, 3, Article 100043. https://doi.org/10.1016/j.crneur.2022.100043
14.
DevlinJ.ChangM. W.LeeK.ToutanovaK. (2019). BERT: Pre-training of deep bidirectional transformer for language understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1, 4171–4186. https://doi.org/10.18653/v1/N19-1423
15.
DingN.SimonJ. Z. (2012). Emergence of neural encoding of auditory objects while listening to competing speakers. Proceedings of the National Academy of Sciences, USA, 109(29), 11854–11859. https://doi.org/10.1073/pnas.1205381109
16.
DingN.SimonJ. Z. (2014). Cortical entrainment to continuous speech: Functional roles and interpretations. Frontiers in Human Neuroscience, 8, Article 311. https://doi.org/10.3389/fnhum.2014.00311
17.
DosenbachN. U. F.FairD. A.MiezinF. M.CohenA. L.WengerK. K.DosenbachR. A. T.FoxM. D.SnyderA. Z.VincentJ. L.RaichleM. E.SchlaggarB. L.PetersenS. E. (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, USA, 104(26), 11073–11078. https://doi.org/10.1073/pnas.0704320104
18.
EbenC.KochI.JolicoeurP.NoldenS. (2020). The persisting influence of unattended auditory information: Negative priming in intentional auditory attention switching. Attention, Perception, & Psychophysics, 82(4), 1835–1846. https://doi.org/10.3758/s13414-019-01909-y
19.
FiedlerL.WöstmannM.HerbstS. K.ObleserJ. (2019). Late cortical tracking of ignored speech facilitates neural selectivity in acoustically challenging conditions. NeuroImage, 186, 33–42. https://doi.org/10.1016/j.neuroimage.2018.10.057
20.
FreyJ. N.RuhnauP.WeiszN. (2015). Not so different after all: The same oscillatory processes support different types of attention. Brain Research, 1626, 183–197. https://doi.org/10.1016/j.brainres.2015.02.017
21.
GenoveseC. R.LazarN. A.NicholsT. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage, 15(4), 870–878. https://doi.org/10.1006/nimg.2001.1037
22.
GiraudA.-L.PoeppelD. (2012). Cortical oscillations and speech processing: Emerging computational principles and operations. Nature Neuroscience, 15(4), 511–517. https://doi.org/10.1038/nn.3063
23.
GrinstedA.MooreJ. C.JevrejevaS. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11, 561–566.
24.
Har-shai YahavP.Zion GolumbicE. (2021). Linguistic processing of task-irrelevant speech at a cocktail party. eLife, 10, Article e65096. https://doi.org/10.7554/eLife.65096
25.
HortonC.D’ZmuraM.SrinivasanR. (2013). Suppression of competing speech through entrainment of cortical oscillations. Journal of Neurophysiology, 109(12), 3082–3093. https://doi.org/10.1152/jn.01026.2012
26.
HoshiY. (2007). Functional near-infrared spectroscopy: Current status and future prospects. Journal of Biomedical Optics, 12(6), Article 062106. https://doi.org/10.1117/1.2804911
27.
JensenO.BonnefondM.VanRullenR. (2012). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences, 16(4), 200–206. https://doi.org/10.1016/j.tics.2012.03.002
28.
JiangJ.DaiB.PengD.ZhuC.LiuL.LuC. (2012). Neural synchronization during face-to-face communication. Journal of Neuroscience, 32, 16064–16069. https://doi.org/10.1523/JNEUROSCI.2926-12.2012
29.
KaufmanM.Zion GolumbicE. (2023). Listening to two speakers: Capacity and tradeoffs in neural speech tracking during selective and distributed attention. NeuroImage, 270, Article 119984. https://doi.org/10.1016/j.neuroimage.2023.119984
30.
KawashimaT.SatoT. (2015). Perceptual limits in a simulated “cocktail party.” Attention, Perception, & Psychophysics, 77(6), 2108–2120. https://doi.org/10.3758/s13414-015-0910-9
31.
KeshavarziM.VaranoE.ReichenbachT. (2021). Cortical tracking of a background speaker modulates the comprehension of a foreground speech signal. Journal of Neuroscience, 41(23), 5093–5101. https://doi.org/10.1523/JNEUROSCI.3200-20.2021
32.
KösemA.van WassenhoveV. (2017). Distinct contributions of low- and high-frequency neural oscillations to speech comprehension. Language, Cognition and Neuroscience, 32(5), 536–544. https://doi.org/10.1080/23273798.2016.1238495
MakovS.PintoD.Har-shai YahavP.MillerL. M.Zion GolumbicE. (2023). “Unattended, distracting or irrelevant”: Theoretical implications of terminological choices in auditory selective attention research. Cognition, 231, Article 105313. https://doi.org/10.1016/j.cognition.2022.105313
36.
MesgaraniN.ChangE. F. (2012). Selective cortical representation of attended speaker in multi-talker speech perception. Nature, 485, 233–236. https://doi.org/10.1038/nature11020
37.
O’SullivanJ. A.PowerA. J.MesgaraniN.RajaramS.FoxeJ. J.Shinn-CunninghamB. G.SlaneyM.ShammaS. A.LalorE. C. (2015). Attentional selection in a cocktail party environment can be decoded from single-trial EEG. Cerebral Cortex, 25(7), 1697–1706. https://doi.org/10.1093/cercor/bht355
PowerA. J.FoxeJ. J.FordeE. J.ReillyR. B.LalorE. C. (2012). At what time is the cocktail party? A late locus of selective attention to natural speech. European Journal of Neuroscience, 35, 1497–1503. https://doi.org/10.1111/j.1460-9568.2012.08060.x
40.
SongH.FinnE. S.RosenbergM. D. (2021). Neural signatures of attentional engagement during narratives and its consequences for event memory. Proceedings of the National Academy of Sciences, USA, 118(33), e2021905118. https://doi.org/10.1073/pnas.2021905118
41.
StephensG. J.SilbertL. J.HassonU. (2010). Speaker–listener neural coupling underlies successful communication. Proceedings of the National Academy of Sciences, USA, 107(32), 14425–14430. https://doi.org/10.1073/pnas.1008662107
UhrigS.PerkisA.MöllerS.SvenssonU. P.BehneD. M. (2022). Effects of spatial speech presentation on listener response strategy for talker-identification. Frontiers in Neuroscience, 15, Article 730744. https://www.frontiersin.org/articles/10.3389/fnins.2021.730744
44.
VachonF.MarshJ. E.LabontéK. (2020). The automaticity of semantic processing revisited: Auditory distraction by a categorical deviation. Journal of Experimental Psychology: General, 149(7), 1360–1397. https://doi.org/10.1037/xge0000714
45.
VeríssimoJ.VerhaeghenP.GoldmanN.WeinsteinM.UllmanM. T. (2022). Evidence that ageing yields improvements as well as declines across attention and executive functions. Nature Human Behaviour, 6(1), Article 1. https://doi.org/10.1038/s41562-021-01169-7
46.
XiaM.WangJ.HeY. (2013). BrainNet viewer: A network visualization tool for human brain connectomics. PLOS ONE, 8(7), Article e68910. https://doi.org/10.1371/journal.pone.0068910
47.
YonchevaY.MaurerU.ZevinJ. D.McCandlissB. D. (2014). Selective attention to phonology dynamically modulates initial encoding of auditory words within the left hemisphere. NeuroImage, 97, 262–270. https://doi.org/10.1016/j.neuroimage.2014.04.006
48.
Zion GolumbicE. M.DingN.BickelS.LakatosP.SchevonC. A.McKhannG. M.GoodmanR. R.EmersonR.MehtaA. D.SimonJ. Z.PoeppelD.SchroederC. E. (2013). Mechanisms underlying selective neuronal tracking of attended speech at a “cocktail party.” Neuron, 77, 980–991. https://doi.org/10.1016/j.neuron.2012.12.037
49.
ZoefelB.KösemA. (2024). Neural tracking of continuous acoustics: Properties, speech-specificity and open questions. European Journal of Neuroscience, 59(3), 394–414. https://doi.org/10.1111/ejn.16221
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