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(1981). Sensory specificity of apparent motion. Journal of Experimental Psychology, 7, 1318–1326.\nBeck, D. M., & Palmer, S. E. (2002). Top-down influences on perceptual grouping. Journal of Experimental Psychology: Human Perception & Performance, 28, 1071–1084.\nBertelson, P., & de Gelder, B. (2004). The psychology of multimodal perception. In C. Spence & J. Driver (Eds.), Crossmodal space and crossmodal attention (pp. 141–179). Oxford: Oxford University Press.\nCalvert, G. A., Spence, C., & Stein, B. E. (Eds.), (2004). The handbook of multisensory processes. Cambridge, MA: MIT Press.\nDriver, J., & Spence, C. (2000). Multisensory perception: Beyond modularity and convergence. Current Biology, 10, 311–331.\nEhrenstein, W. H., & Reinhardt-Rutland, A. H. (1996). A crossmodal aftereffect: Auditory displacement following adaptation to visual motion. Perceptual & Motor Skills, 82, 23–26.\nFrancis, G., & Grossberg, S. (1996). Cortical dynamics of form and motion integration: Persistence, apparent motion, and illusory contours. Vision Research, 36, 149–173.\nGeldard, F. A. (1976). The saltatory effect in vision. Sensory Processes, 1, 77–86.\nHagen, M. C., Franzen, O., McGlone, F., Essick, G., Dancer, C., & Pardo, J. V. (2002). Tactile motion activates the human middle temporal (MT\u002FV5) complex. European Journal of Neuroscience, 16, 957–964.\nHoward, L. P., & Templeton, W. B. (1966). Human spatial orientation. New York: Wiley.\nKilgard, M. P., & Merzenich, M. M. (1995). Anticipated stimuli across skin. Nature, 373, 663.\nKoffka, K. (1935). Principles of Gestalt psychology. New York: Harcourt Brace.\nKubovy, M., & Van Valkenburg, D. (2001). Auditory and visual objects. Cognition, 80, 97–126.\nLockhead, G. R., Johnson, R. C., & Gold, F. M. (1980). Saltation through the blind spot. Perception & Psychophysics, 27, 545–549.\nMateeff, S., Hohnsbein, J., & Noack, T. (1985). Dynamic visual capture: Apparent auditory motion induced by a moving visual target. Perception, 14, 721–727.\nNiemi, P., & Näätänen, R. (1981). Foreperiod and simple reaction time. Psychological Bulletin, 89, 133–162.\nPalmer, S. T. (2002). Perceptual grouping: It’s later than you think. Current Directions in Psychological Science, 11, 101–106.\nPalmer, S. T., Brooks, J. L., & Nelson, R. (2003). When does grouping happen? Acta Psychologica, 114, 311–330.\nPhillips, D. P., & Hall, S. E. (2001). Spatial and temporal factors in auditory saltation. Journal of the Acoustical Society of America, 110, 1539–1547.\nPosner, M. I. (1978). Chronometric explorations of mind. Hillsdale, NJ: Erlbaum.\nSanabria, D., Soto-Faraco, S, Chan, J., & Spence, C. (2003). Intramodal perceptual grouping modulates multisensory integration: Evidence from the crossmodal dynamic capture task. Manuscript submitted for publication.\nShore, D. I., Hall, S. E., & Klein, R. M. (1998). Auditory saltation: A new measure for an old illusion. Journal of the Acoustical Society of America, 103, 3730–3733.\nSoto-Faraco, S., & Kingstone, A. (2004). Multisensory integration of dynamic information. In G. Calvert, C. Spence & B. E. Stein (Eds.), The handbook of multisensory processes (pp. 49–69). Cambridge, MA: MIT Press.\nSoto-Faraco, S., Kingstone, A., & Spence, C. (2003). Multisensory contributions to the perception of motion. Neuropsychologia, 41, 1847–1862.\nSoto-Faraco, S., Lyons, J., Gazzaniga, M., Spence, C., & Kingstone, A. (2002). The ventriloquist in motion: Illusory capture of dynamic information across sensory modalities. Cognitive Brain Research, 14, 139–146.\nSoto-Faraco, S., Spence, C., & Kingstone, A. (2004). Cross-modal dynamic capture: Congruency effects of motion perception across sensory modalities. Journal of Experimental Psychology: Human Perception & Performance, 30, 330–345.\nSpence, C., & Driver, J. (1997). Audiovisual links in exogenous covert spatial orienting. Perception & Psychophysics, 59, 1–22.\nStaal, H. E., & Donderi, D. C. (1983). The effect of sound on visual apparent movement. American Journal of Psychology, 96, 95–105.\nStein, B. E., & Meredith, M. A. (1993). The merging of the senses. Cambridge, MA: MIT Press.\nVroomen. J., & de Gelder, B. (2000). Sound enhances visual perception: Cross-modal effects of auditory organization on vision. Journal of Experimental Psychology: Human Perception & Performance, 26, 1583–1590.\nWatanabe, K., & Shimojo, S. (2001). When sound affects vision: Effects of auditory grouping on visual perception. Psychological Science, 12, 109–116.\nWertheimer, M. (1950). Laws of organization in perceptual forms. In W. D. Ellis (Ed.), A sourcebook of Gestalt psychology (pp. 71–81). New York: Humanities Press. [Original work published 1923]\nWuerger, S. M., Hofbauer, M., & Meyer, G. F. (2003). The integration of auditory and visual motion signals at threshold. Perception & Psychophysics, 65, 1188–1196.\nZapparoli, G. C., & Reatto, L. L. (1969). The apparent movement between visual and acoustic stimulus and the problem of intermodal relations. Acta Psychologica, 29, 256–267.",{"EN":205},"Several studies have shown that the direction in which a visual apparent motion stream moves can influence the perceived direction of an auditory apparent motion stream (an effect known as crossmodal dynamic capture). However, little is known about the role that intramodal perceptual grouping processes play in the multisensory integration of motion information. The present study was designed to investigate the time course of any modulation of the cross-modal dynamic capture effect by the nature of the perceptual grouping taking place within vision. Participants were required to judge the direction of an auditory apparent motion stream while trying to ignore visual apparent motion streams presented in a variety of different configurations. Our results demonstrate that the cross-modal dynamic capture effect was influenced more by visual perceptual grouping when the conditions for intramodal perceptual grouping were set up prior to the presentation of the audiovisual apparent motion stimuli. However, no such modulation occurred when the visual perceptual grouping manipulation was established at the same time as or after the presentation of the audiovisual stimuli. These results highlight the importance of the unimodal perceptual organization of sensory information to the manifestation of multisensory integration.",{"EN":207},"When does visual perceptual grouping affect multisensory integration?",{"VOID":209},"10.3758\u002FCABN.4.2.218","PUBLICATION","VERIFIED","2025-02-20T23:55:07.089+00:00","Auto Verify","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002FCABN.4.2.218",[216,233,245,270],{"id":217,"sortIndex":218,"researcher":20,"roles":219,"affiliations":221,"properties":230},"aa537c9b-d07e-4159-9810-0d784dd39e32",2,[220],"AUTHOR",[222],{"id":20,"sortIndex":21,"affiliation":223,"properties":20},{"id":224,"createTime":225,"updateTime":225,"relativeEntities":226,"slug":20,"properties":227,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"3e23a0ef-08a7-4ecb-803a-d02c915f244c","2023-12-13T22:01:39.139+00:00",[],{"title":228},{"VI":229},"Department of Experimental Psychology, Oxford, England",{"title":231},{"VI":232},"Jason S. 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(2019). eyelinker: Import ASC Files from EyeLink Eye Trackers. from https:\u002F\u002Fcran.r-project.org\u002Fweb\u002Fpackages\u002Feyelinker\u002Findex.html\nBates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1–48. https:\u002F\u002Fdoi.org\u002F10.18637\u002Fjss.v067.i01\nBechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding Advantageously Before Knowing the Advantageous Strategy. Science, 275(5304), 1293. https:\u002F\u002Fdoi.org\u002F10.1126\u002Fscience.275.5304.1293\nBenjamini, Y., & Yekutieli, D. (2001). The Control of the False Discovery Rate in Multiple Testing under Dependency. The Annals of Statistics, 29(4), 1165–1188.\nBerlyne, D. E. (1966). Curiosity and exploration. Science, 153(3731), 25–33.\nBotvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. 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Journal of Experimental Psychology-General, 143(6), 2074–2081. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fa0038199\nZajkowski, W. K., Kossut, M., & Wilson, R. C. (2017). A causal role for right frontopolar cortex in directed, but not random, exploration. eLife, 6, e27430. https:\u002F\u002Fdoi.org\u002F10.7554\u002FeLife.27430\nZenon, A. (2019). Eye pupil signals information gain. Proceedings of the Royal Society B-Biological Sciences, 286(1911), Artn 20191593. https:\u002F\u002Fdoi.org\u002F10.1098\u002FRspb.2019.1593",{"EN":331},"\nThis study examined whether pupil size and response time would distinguish directed exploration from random exploration and exploitation. Eighty-nine participants performed the two-choice probabilistic learning task while their pupil size and response time were continuously recorded. Using LMM analysis, we estimated differences in the pupil size and response time between the advantageous and disadvantageous choices as a function of learning success, i.e., whether or not a participant has learned the probabilistic contingency between choices and their outcomes. We proposed that before a true value of each choice became known to a decision-maker, both advantageous and disadvantageous choices represented a random exploration of the two options with an equally uncertain outcome, whereas the same choices after learning manifested exploitation and direct exploration strategies, respectively. We found that disadvantageous choices were associated with increases both in response time and pupil size, but only after the participants had learned the choice-reward contingencies. For the pupil size, this effect was strongly amplified for those disadvantageous choices that immediately followed gains as compared to losses in the preceding choice. Pupil size modulations were evident during the behavioral choice rather than during the pretrial baseline. These findings suggest that occasional disadvantageous choices, which violate the acquired internal utility model, represent directed exploration. This exploratory strategy shifts choice priorities in favor of information seeking and its autonomic and behavioral concomitants are mainly driven by the conflict between the behavioral plan of the intended exploratory choice and its strong alternative, which has already proven to be more rewarding.",{"EN":333},"Pupil dilation and response slowing distinguish deliberate explorative choices in the probabilistic learning task",{"VOID":335},"10.3758\u002Fs13415-022-00996-z","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-022-00996-z",[338,354,367,379,391,404,416],{"id":339,"sortIndex":340,"researcher":20,"roles":341,"affiliations":342,"properties":351},"7cdf57c0-8650-49e7-a4a3-5939b0c44ec5",5,[220],[343],{"id":20,"sortIndex":21,"affiliation":344,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":347,"slug":20,"properties":348,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"1bc4e657-501d-46ea-8b22-d2c1712e7040","2024-01-05T09:04:08.067+00:00",[],{"title":349},{"VI":350},"Center for Neurocognitive Research (MEG-Center), Moscow State University of Psychology and Education, Moscow, Russia",{"title":352},{"VI":353},"Tatiana A. Stroganova",{"id":355,"sortIndex":356,"researcher":20,"roles":357,"affiliations":358,"properties":364},"1cf4cdd1-08ee-4375-9cc5-4d237b438089",4,[220],[359],{"id":20,"sortIndex":21,"affiliation":360,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":361,"slug":20,"properties":362,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":363},{"VI":350},{"title":365},{"VI":366},"Anna M. Rytikova",{"id":368,"sortIndex":21,"researcher":20,"roles":369,"affiliations":370,"properties":376},"78ba4e40-e516-4d72-9ab8-25d32faa0bd2",[220],[371],{"id":20,"sortIndex":21,"affiliation":372,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":373,"slug":20,"properties":374,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":375},{"VI":350},{"title":377},{"VI":378},"Galina L. Kozunova",{"id":380,"sortIndex":272,"researcher":20,"roles":381,"affiliations":382,"properties":388},"b3918ecb-994f-449d-bb01-8dd94ae95e83",[220],[383],{"id":20,"sortIndex":21,"affiliation":384,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":385,"slug":20,"properties":386,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":387},{"VI":350},{"title":389},{"VI":390},"Vladimir A. Medvedev",{"id":392,"sortIndex":393,"researcher":20,"roles":394,"affiliations":395,"properties":401},"0da278fd-867e-4e37-8d5a-f1d4b4ba85de",6,[220],[396],{"id":20,"sortIndex":21,"affiliation":397,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":398,"slug":20,"properties":399,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":400},{"VI":350},{"title":402},{"VI":403},"Boris V. Chernyshev",{"id":405,"sortIndex":218,"researcher":20,"roles":406,"affiliations":407,"properties":413},"8334f333-9e12-4d51-8150-c218df0e3c25",[220],[408],{"id":20,"sortIndex":21,"affiliation":409,"properties":20},{"id":345,"createTime":346,"updateTime":346,"relativeEntities":410,"slug":20,"properties":411,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":412},{"VI":350},{"title":414},{"VI":415},"Andrey O. 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The impact of deliberative strategy dissociates ERP components related to conflict processing vs. reinforcement learning. Frontiers in neuroscience, 6.\nWarren, C. M., Hyman, J. M., Seamans, J. K., & Holroyd, C. B. (2015). Reward processing in the rodent anterior cingulate cortex. Journal of Physiology, Paris, 109 (1), 87-94.\nWang, J., Chen, Z., Peng, X., Yang, T., Li, P., Cong, F., & Li, H. (2016). To know or not to know? theta and delta reflect complementary information about an advanced cue before feedback in decision-making. Frontiers in psychology, 7.",{"EN":472},"Although a growing number of studies have investigated the neural mechanisms of reinforcement learning, it remains unclear how the brain responds to feedback that is unreliable. A recent theory proposes that the reward positivity (RewP) component of the event-related brain potential (ERP) and frontal midline theta (FMT) power reflect separate feedback-related processing functions of anterior cingulate cortex (ACC). In the present study, the electroencephalogram (EEG) was recorded from participants as they engaged in a time estimation task in which feedback reliability was manipulated across conditions. After each response, they received a cue that indicated that the following feedback stimulus was 100%, 75%, or 50% reliable. The results showed that participants’ time estimates adjusted linearly according to the feedback reliability. Moreover, presentation of the cue indicating 100% reliability elicited a larger RewP-like ERP component than the other cues did, and feedback presentation elicited a RewP of approximately equal amplitude for all of the three reliability conditions. By contrast, FMT power elicited by negative feedback decreased linearly from the 100% condition to 75% and 50% condition, and only FMT power predicted behavioral adjustments on the following trials. In addition, an analysis of Beta power and cross-frequency coupling (CFC) of Beta power with FMT phase suggested that Beta-FMT communication modulated motor areas for the purpose of adjusting behavior. We interpreted these findings in terms of the hierarchical reinforcement learning account of ACC, in which the RewP and FMT are proposed to reflect reward processing and control functions of ACC, respectively.",{"EN":474},"Electrophysiological measures reveal the role of anterior cingulate cortex in learning from unreliable feedback",{"VOID":476},"10.3758\u002Fs13415-018-0615-3","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-018-0615-3",[479,504,533,545],{"id":480,"sortIndex":21,"researcher":20,"roles":481,"affiliations":482,"properties":501},"da64b1d8-60bc-4645-a539-8abbe1670500",[220],[483,491],{"id":20,"sortIndex":21,"affiliation":484,"properties":20},{"id":485,"createTime":486,"updateTime":486,"relativeEntities":487,"slug":20,"properties":488,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"2e5bfa4b-ee4a-4f96-a6c6-f8efc34f63eb","2023-12-27T07:20:46.254+00:00",[],{"title":489},{"VI":490},"Brain Function and Psychological Science Research Center, Shenzhen University, Shenzhen, China",{"id":492,"sortIndex":247,"affiliation":493,"properties":500},"ffbc2370-d7c5-4c0c-b47d-0c0b4309b093",{"id":494,"createTime":495,"updateTime":495,"relativeEntities":496,"slug":20,"properties":497,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"636e6987-07c9-4abc-afa0-5847e31c222f","2023-12-13T13:09:19.606+00:00",[],{"title":498},{"VI":499},"Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China",{},{"title":502},{"VI":503},"Peng Li",{"id":505,"sortIndex":218,"researcher":20,"roles":506,"affiliations":507,"properties":530},"c8c7d8b0-85b1-4289-90a8-b665a2071406",[220],[508,518,523],{"id":509,"sortIndex":218,"affiliation":510,"properties":517},"d2e779d8-8e0f-465e-804f-d29728e25ed1",{"id":511,"createTime":512,"updateTime":512,"relativeEntities":513,"slug":20,"properties":514,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"69c7a281-a2c6-44aa-baa8-db00e45c809f","2024-01-05T15:26:19.341+00:00",[],{"title":515},{"VI":516},"Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China",{},{"id":20,"sortIndex":21,"affiliation":519,"properties":20},{"id":485,"createTime":486,"updateTime":486,"relativeEntities":520,"slug":20,"properties":521,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":522},{"VI":490},{"id":524,"sortIndex":247,"affiliation":525,"properties":529},"9424b95e-808d-4485-9ac1-f1be85d1d003",{"id":494,"createTime":495,"updateTime":495,"relativeEntities":526,"slug":20,"properties":527,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":528},{"VI":499},{},{"title":531},{"VI":532},"Hong Li",{"id":534,"sortIndex":247,"researcher":20,"roles":535,"affiliations":536,"properties":542},"253b32d4-d15a-4999-ba33-059da795a860",[220],[537],{"id":20,"sortIndex":21,"affiliation":538,"properties":20},{"id":485,"createTime":486,"updateTime":486,"relativeEntities":539,"slug":20,"properties":540,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":541},{"VI":490},{"title":543},{"VI":544},"Weiwei Peng",{"id":546,"sortIndex":272,"researcher":20,"roles":547,"affiliations":548,"properties":557},"c5b2902e-6bad-4dfc-93e3-367e3e4475fc",[220],[549],{"id":20,"sortIndex":21,"affiliation":550,"properties":20},{"id":551,"createTime":552,"updateTime":552,"relativeEntities":553,"slug":20,"properties":554,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"491be97b-106a-4ec8-953c-0448d57b7e01","2023-12-24T03:53:50.329+00:00",[],{"title":555},{"VI":556},"Department of Psychology, University of Victoria, Victoria, Canada",{"title":558},{"VI":559},"Clay B. 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ERP correlates of source memory: Unitized source information increases familiarity-based retrieval. Brain Research, 1367, 278–286. doi:10.1016\u002Fj.brainres.2010.10.030\nDiana, R. A., Vilberg, K. L., & Reder, L. M. (2005). Identifying the ERP correlate of a recognition memory search attempt. Cognitive Brain Research, 24, 674–684. doi:10.1016\u002Fj.cogbrainres.2005.04.001\nDiana, R. A., Yonelinas, A. P., & Ranganath, C. (2008). The effects of unitization on familiarity-based source memory: Testing a behavioral prediction derived from neuroimaging data. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 730–740. doi:10.1037\u002F0278-7393.34.4.730\nDonaldson, D. I., & Rugg, M. D. (1998). Recognition memory for new associations: Electrophysiological evidence for the role of recollection. Neuropsychologia, 36, 377–395. doi:10.1016\u002FS0028-3932(97)00143-7\nDonaldson, D. I., & Rugg, M. D. (1999). 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Context effects on familiarity are familiarity effects of context — An electrophysiological study. International Journal of Psychophysiology, 64, 146–156. doi:10.1016\u002Fj.ijpsycho.2007.01.005\nFay, S., Isingrini, M., Ragot, R., & Pouthas, V. (2005). The effect of encoding manipulation on word-stem cued recall: An event-related potential study. Cognitive Brain Research, 24, 615–626. doi:10.1016\u002Fj.cogbrainres.2005.03.014\nFriedman, D., & Johnson, R. (2000). Event-related potential (ERP) studies of memory encoding and retrieval: A selective review. Microscopy Research and Technique, 51, 6–28. doi:10.1002\u002F1097-0029(20001001)51:1\u003C6::AID-JEMT2>3.3.CO;2-I\nGrunwald, T., Pezer, N., Münte, T., Kurthen, M., Lehnertz, K., Van Roost, D., ... Elger, C. E. (2003). Dissecting out conscious and unconscious memory (sub)processes within the human medial temporal lobe. NeuroImage, 20, S139–S145. doi:10.1016\u002Fj.neuroimage.2003.09.004\nHabib, R., & Nyberg, L. (2008). 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Kappenman (Eds.), The Oxford Handbook of ERP Components (pp. 373–396). Oxford: Oxford University Press. doi:10.1093\u002Foxfordhb\u002F9780195374148.013.0187\nWilding, E. L., & Rugg, M. D. (1996). An event-related potential study of recognition memory with and without retrieval of source. Brain, 119, 889–905. doi:10.1093\u002Fbrain\u002F119.3.889\nWoodruff, C. C., Hayama, H. R., & Rugg, M. D. (2006). Electrophysiological dissociation of the neural correlates of recollection and familiarity. Brain Research, 1100, 125–135. doi:10.1016\u002Fj.brainres.2006.05.019\nYonelinas, A. P. (2002). The nature of recollection and familiarity: A review of 30 years of research. Journal of Memory and Language, 46, 441–517. doi:10.1006\u002Fjmla.2002.2864\nYu, S. S., & Rugg, M. D. (2010). Dissociation of the electrophysiological correlates of familiarity strength and item repetition. Brain Research, 1320, 74–84. doi:10.1016\u002Fj.brainres.2009.12.071",{"EN":606},"Little is known about the time course of processes supporting episodic cued recall. To examine these processes, we recorded event-related scalp electrical potentials during episodic cued recall following pair-associate learning of unimodal object-picture pairs and crossmodal object-picture and sound pairs. Successful cued recall of unimodal associates was characterized by markedly early scalp potential differences over frontal areas, while cued recall of both unimodal and crossmodal associates were reflected by subsequent differences recorded over frontal and parietal areas. Notably, unimodal cued recall success divergences over frontal areas were apparent in a time window generally assumed to reflect the operation of familiarity but not recollection processes, raising the possibility that retrieval success effects in that temporal window may reflect additional mnemonic processes beyond familiarity. Furthermore, parietal scalp potential recall success differences, which did not distinguish between crossmodal and unimodal tasks, seemingly support attentional or buffer accounts of posterior parietal mnemonic function but appear to constrain signal accumulation, expectation, or representational accounts.",{"EN":608},"The time course of episodic associative retrieval: Electrophysiological correlates of cued recall of unimodal and crossmodal pair-associate learning",{"VOID":610},"10.3758\u002Fs13415-013-0199-x","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-013-0199-x",[613,628],{"id":614,"sortIndex":247,"researcher":20,"roles":615,"affiliations":616,"properties":625},"a96fb636-67cc-406e-8c7a-655bd5218f4c",[220],[617],{"id":20,"sortIndex":21,"affiliation":618,"properties":20},{"id":619,"createTime":620,"updateTime":620,"relativeEntities":621,"slug":20,"properties":622,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"e32b0d20-6e2d-4ff5-8274-deda6f526eb8","2024-01-09T16:20:12.573+00:00",[],{"title":623},{"VI":624},"School of Psychology and Unit for Applied Neuroscience, The Interdisciplinary Center, Herzliya, Israel",{"title":626},{"VI":627},"Daniel A. 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R., Poldrack, R. A., Ivry, R. B., & Diedrichsen, J. (2019). Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nature Neuroscience, 22(8), 1371–1378.\nLeggio, M., & Molinari, M. (2015). Cerebellar Sequencing: a Trick for Predicting the Future. Cerebellum, 14(1), 35–38. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12311-014-0616-x\nLi, M., Ma, Q., Baetens, K., Pu, M., Deroost, N., Baeken, C., & Van Overwalle, F. (2021). Social cerebellum in goal-directed navigation. Social Neuroscience, 16(5), 467–485. https:\u002F\u002Fdoi.org\u002F10.1080\u002F17470919.2021.1970017\nMa, Q., Pu, M., Haihambo, N. P., Baetens, K., Heleven, E., Deroost, N., & Van Overwalle, F. (2021a). The posterior cerebellum and temporoparietal junction support explicit learning of social belief sequences. Cognitive, Affective and Behavioral Neuroscience. https:\u002F\u002Fdoi.org\u002F10.3758\u002Fs13415-021-00966-x\nMa, Q., Pu, M., Heleven, E., Haihambo, N. 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Social Cognitive and Affective Neuroscience, 14(5), 549–558. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fscan\u002Fnsz032\nVan Overwalle, F., Manto, M., Leggio, M., & Delgado-García, J. M. J. M. (2019b). The sequencing process generated by the cerebellum crucially contributes to social interactions. Medical Hypotheses, 128, 33–42. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.mehy.2019.05.014\nVan Overwalle, F., Van de Steen, F., & Mariën, P. (2019c). Dynamic causal modeling of the effective connectivity between the cerebrum and cerebellum in social mentalizing across five studies. Cognitive, Affective and Behavioral Neuroscience, 19(1), 211–223. https:\u002F\u002Fdoi.org\u002F10.3758\u002Fs13415-018-00659-y\nVan Overwalle, F., Ma, Q., & Heleven, E. (2020a). The posterior crus II cerebellum is specialized for social mentalizing and emotional self-experiences: A meta-Analysis. Social Cognitive and Affective Neuroscience, 15(9), 905–928. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fscan\u002Fnsaa124\nVan Overwalle, F., Manto, M., Cattaneo, Z., Clausi, S., Ferrari, C., Gabrieli, J. D. E., & Leggio, M. (2020b). Consensus paper: Cerebellum and social cognition. Cerebellum, 19(6), 833–868. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12311-020-01155-1\nVan Overwalle, F., Van de Steen, F., van Dun, K., & Heleven, E. (2020c). Connectivity between the cerebrum and cerebellum during social and non-social sequencing using dynamic causal modelling. NeuroImage, 206, 116326. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.neuroimage.2019.116326\nVogeley, K., Bussfeld, P., Newen, A., Herrmann, S., Happé, F., Falkai, P., & Zilles, K. (2001). Mind reading: Neural mechanisms of theory of mind and self-perspective. NeuroImage, 14(1 I), 170–181. https:\u002F\u002Fdoi.org\u002F10.1006\u002Fnimg.2001.0789\nWalter, H., Adenzato, M., Ciaramidaro, A., Enrici, I., Pia, L., & Bara, B. G. (2004). Understanding intentions in social interaction: The mole of the anterior paracingulate cortex. Journal of Cognitive Neuroscience, 16(10), 1854–1863. https:\u002F\u002Fdoi.org\u002F10.1162\u002F0898929042947838\nYu, K. K., Cheung, C., Chua, S. E., & McAlonan, G. M. (2011). Can asperger syndrome be distinguished from autism? An anatomic likelihood meta-analysis of MRI studies. Journal of Psychiatry and Neuroscience, 36(6), 412–421. https:\u002F\u002Fdoi.org\u002F10.1503\u002Fjpn.100138",{"EN":686},"Humans read the minds of others to predict their actions and efficiently navigate social environments, a capacity called mentalizing. Accumulating evidence suggests that the cerebellum, especially Crus 1 and 2, and lobule IX are involved in identifying the sequence of others’ actions. In the current study, we investigated the neural correlates that underly predicting others’ intentions and how this plays out in the sequence of their actions. We developed a novel intention prediction task, which required participants to put protagonists’ behaviors in the correct chronological order based on the protagonists’ honest or deceitful intentions (i.e., inducing true or false beliefs in others). We found robust activation of cerebellar lobule IX and key mentalizing areas in the neocortex when participants ordered protagonists’ intentional behaviors compared with not ordering behaviors or to ordering object scenarios. Unlike a previous task that involved prediction based on personality traits that recruited cerebellar Crus 1 and 2, and lobule IX (Haihambo et al., 2021), the present task recruited only the cerebellar lobule IX. These results suggest that cerebellar lobule IX may be generally involved in social action sequence prediction, and that different areas of the cerebellum are specialized for distinct mentalizing functions.",{"EN":688},"To Do or Not to Do: The cerebellum and neocortex contribute to predicting sequences of social intentions",{"VOID":690},"10.3758\u002Fs13415-023-01071-x","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-023-01071-x",[693,740,752,764,776,788,800],{"id":694,"sortIndex":218,"researcher":20,"roles":695,"affiliations":696,"properties":737},"132c4263-baf5-4e9d-9db8-c8c0a6eccc82",[220],[697,707,715,727],{"id":698,"sortIndex":247,"affiliation":699,"properties":706},"54d6203d-f5ee-490e-b192-ed3895c12f7c",{"id":700,"createTime":701,"updateTime":701,"relativeEntities":702,"slug":20,"properties":703,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"bc98bd37-cd75-4930-8675-c742b6814342","2024-01-18T01:37:38.012+00:00",[],{"title":704},{"VI":705},"Department of Head and Skin (UZGent), Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium",{},{"id":20,"sortIndex":21,"affiliation":708,"properties":20},{"id":709,"createTime":710,"updateTime":710,"relativeEntities":711,"slug":20,"properties":712,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"ba80e401-68b6-4490-9252-7e2c29e8ae49","2023-12-07T12:02:00.881+00:00",[],{"title":713},{"VI":714},"Department of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium",{"id":716,"sortIndex":272,"affiliation":717,"properties":726},"f6f2b5b4-5aa8-488a-bacf-f8c40aa79a11",{"id":718,"createTime":719,"updateTime":720,"relativeEntities":721,"slug":722,"properties":723,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"6bf5d996-d688-40b6-9447-51b0b3b70db9","2023-12-12T17:40:58.051+00:00","2024-10-15T16:27:51.390+00:00",[],"Department-of-Electrical-Engineering-Eindhoven-University-of-Technology-Eindhoven-The-Netherlands",{"title":724},{"VI":725},"Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands",{},{"id":728,"sortIndex":218,"affiliation":729,"properties":736},"6d8f19b2-eb32-4122-babc-9d27c9db868a",{"id":730,"createTime":731,"updateTime":731,"relativeEntities":732,"slug":20,"properties":733,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"534c060f-c8d0-40f1-81a6-2739a7aac836","2023-12-13T23:20:46.097+00:00",[],{"title":734},{"VI":735},"Department of Psychiatry University Hospital (UZBrussel), Brussels, Belgium",{},{"title":738},{"VI":739},"Kris Baetens",{"id":741,"sortIndex":21,"researcher":20,"roles":742,"affiliations":743,"properties":749},"a94c407d-ad4e-437b-b837-52dd5af75a9a",[220],[744],{"id":20,"sortIndex":21,"affiliation":745,"properties":20},{"id":709,"createTime":710,"updateTime":710,"relativeEntities":746,"slug":20,"properties":747,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":748},{"VI":714},{"title":750},{"VI":751},"Naem Haihambo",{"id":753,"sortIndex":393,"researcher":20,"roles":754,"affiliations":755,"properties":761},"5dd4a558-4221-4d41-b57d-739f2c655795",[220],[756],{"id":20,"sortIndex":21,"affiliation":757,"properties":20},{"id":709,"createTime":710,"updateTime":710,"relativeEntities":758,"slug":20,"properties":759,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":760},{"VI":714},{"title":762},{"VI":763},"Frank 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T. J., & Patton, P. E. (2003). A two-stage unsupervised learning algorithm reproduces multisensory enhancement in a neural network model of the corticotectal system. Journal of Neuroscience, 23, 6713–6727.\nAnastasio, T. J., Patton, P. E., & Belkacem-Boussaid, K. (2000). Using Bayes’ rule to model multisensory enhancement in the superior colliculus. Neural Computation, 12, 1165–1187.\nBell, A. H., Corneil, B. D., Meredith, M. A., & Muñoz, D. P. (2001). The influence of stimulus properties on multisensory processing in the awake primate superior colliculus. Canadian Journal of Experimental Psychology, 55, 123–132.\nBurnett, L. R., Stein, B. E., Chaponis, D., & Wallace, M. T. (2004). Superior colliculus lesions preferentially disrupt multisensory orientation. Neuroscience, 124, 535–547.\nCarpenter, R. H., & Williams, M. L. (1995). Neural computation of log likelihood in control of saccadic eye movements. Nature, 377, 59–62.\nColonius, H., & Diederich, A. (2002). A maximum-likelihood approach to modeling multisensory enhancement. In T. G. Dietterich, S. Becker, & Z. Ghahramani (Eds.), Advances in neural information processing systems 14 (pp. 181–187). Cambridge, MA: MIT Press.\nColonius, H., & Diederich, A. (2004). Multisensory interaction in saccadic reaction time: A time-window-of-integration model. Journal of Cognitive Neuroscience, 16, 1000–1009.\nDiederich, A., & Colonius, H. (2004). Modeling the time course of multisensory interaction in manual and saccadic responses. In G. Calvert, C. Spence, & B. E. Stein (Eds.), Handbook of multisensory processes (pp. 395–408). Cambridge, MA: MIT Press.\nEgan, J. P. (1975). Signal detection theory and ROC analysis. New York: Academic Press.\nErnst, M. O., & Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature, 415, 429–433.\nFrens, M. A., & Van Opstal, A. J. (1998). Visual-auditory interactions modulate saccade-related activity in monkey superior colliculus. Brain Research Bulletin, 46, 211–224.\nFrens, M. A., Van Opstal, A. J., & Van der Willigen, R. F. (1995). Spatial and temporal factors determine auditory-visual interactions in human saccadic eye movements. Perception & Psychophysics, 57, 802–816.\nGlimcher, P. W. (2003). Decisions, uncertainty, and the brain: The science of neuroeconomics. Cambridge, MA: MIT Press.\nHorwitz, G. D., & Newsome, W. T. (2001). Target selection for saccadic eye movements: Prelude activity in the superior colliculus during a direction-discrimination task. Journal of Neurophysiology, 86, 2543–2558.\nJiang, W., Jiang, H., & Stein, B. E. (2002). Two corticotectal areas facilitate orientation behavior. Journal of Cognitive Neuroscience, 14, 1240–1255.\nJiang, W., Wallace, M. T., Jiang, H., Vaughan, J. W., & Stein, B. E. (2001). Two cortical areas mediate multisensory integration in superior colliculus neurons. Journal of Neurophysiology, 85, 506–522.\nKocherlakota, S., & Kocherlakota, K. (1992). Bivariate discrete distributions. New York: Dekker.\nKrauzlis, R. J., & Dill, N. (2002). Neural correlates of target choice for pursuit and saccades in the primate superior colliculus. Neuron, 35, 355–363.\nKrauzlis, R. J., Liston, D., & Carello, C. D. (2004). Target selection and the superior colliculus: Goals, choices and hypotheses. Vision Research, 44, 1445–1451.\nMeredith, M. A., & Stein, B. E. (1986a). Spatial factors determine the activity of multisensory neurons in cat superior colliculus. Brain Research, 365, 350–354.\nMeredith, M. A., & Stein, B. E. (1986b). Visual, auditory, and somatosensory convergence on cells in superior colliculus results in multisensory integration. Journal of Neurophysiology, 56, 640–662.\nMuñoz, D. P., & Schall, J. D. (2004). Concurrent, distributed control of saccade initiation in the frontal eye field and superior colliculus. In W. C. Hall & A. Moschovakis (Eds.), The superior colliculus: New approaches for studying sensorimotor integration (pp. 55–82). Boca Raton, FL: CRC Press.\nPatton, P., Belkacem-Boussaid, K., & Anastasio, T. J (2002). Multimodality in the superior colliculus: An information theoretic analysis. Cognitive Brain Research, 14, 10–19.\nRao, R. P. N. (2004). Bayesian computation in recurrent neural circuits. Neural Computation, 16, 1–38.\nRowe, D. B. (2003). Multivariate Bayesian statistics. Boca Raton, FL: CRC Press.\nStanford, T. R. (2004). Signal coding in the primate superior colliculus revealed through the use of artificial signals. In W. C. Hall & A. Moschovakis (Eds.), The superior colliculus: New approaches for studying sensorimotor integration (pp. 35-53). Boca Raton, FL: CRC Press.\nStein, B. E., Magalhães-Castro, B., & Kruger, L. (1976). Relationship between visual and tactile representations in cat superior colliculus. Journal of Neurophysiology, 39, 401–419.\nStein, B. E., & Meredith, M. A. (1993). The merging of the senses. Cambridge, MA: MIT Press.\nTuckwell, H. C. (1989). Stochastic processes in the neurosciences. Philadelphia: Society for Industrial and Applied Mathematics.\nWallace, M. T., Meredith, M. A., & Stein, B. E. (1993). Converging influences from visual, auditory, and somatosensory cortices onto output neurons of the superior colliculus. Journal of Neurophysiology, 69, 1797–1809.\nWallace, M. T., Meredith, M. A., & Stein, B. E (1998). Multisensory integration in the superior colliculus of the alert cat. Journal of Neurophysiology, 80, 1006–1010.\nWallace, M. T., & Stein, B. E. (1996). Sensory organization of the superior colliculus in cat and monkey. Progress in Brain Research, 112, 301–311.\nWallace, M. T., Wilkinson, L. K., & Stein, B. E. (1996). Representation and integration of multiple sensory inputs in primate superior colliculus. Journal of Neurophysiology, 76, 1246–1266.\nWickens, T. D. (2002). Elementary signal detection theory. New York: Oxford University Press.",{"EN":879},"Multisensory neurons in the deep superior colliculus (SC) show response enhancement to cross-modal stimuli that coincide in time and space. However, multisensory SC neurons respond to unimodal input as well. It is thus legitimate to ask why not all deep SC neurons are multisensory or, at least, develop multisensory behavior during an organism’s maturation. The novel answer given here derives from a signal detection theory perspective. A Bayes’ ratio model of multisensory enhancement is suggested. It holds that deep SC neurons operate under the Bayes’ ratio rule, which guarantees optimal performance—that is, it maximizes the probability of target detection while minimizing the false alarm rate. It is shown that optimal performance of multisensory neurons vis-à-vis cross-modal stimuli implies, at the same time, that modality-specific neurons will outperform multisensory neurons in processing unimodal targets. Thus, only the existence of both multisensory and modality-specific neurons allows optimal performance when targets of one or several modalities may occur.",{"EN":881},"Why aren’t all deep superior colliculus neurons multisensory? A Bayes’ ratio analysis",{"VOID":883},"10.3758\u002FCABN.4.3.344","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002FCABN.4.3.344",[886,903],{"id":887,"sortIndex":247,"researcher":20,"roles":888,"affiliations":889,"properties":900},"99db1212-6dc9-4a6a-aae6-7028a4745af2",[220],[890],{"id":20,"sortIndex":21,"affiliation":891,"properties":20},{"id":892,"createTime":893,"updateTime":894,"relativeEntities":895,"slug":896,"properties":897,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"1e7072ea-308b-447f-99af-7f27280d6b40","2023-12-07T20:11:20.257+00:00","2024-12-21T09:15:10.894+00:00",[],"International-University-Bremen-Bremen-Germany",{"title":898},{"VI":899},"International University Bremen, Bremen, Germany",{"title":901},{"VI":902},"Adele Diederich",{"id":904,"sortIndex":21,"researcher":20,"roles":905,"affiliations":906,"properties":915},"b5831865-ca59-4e2b-9efd-2e5a504bdb8a",[220],[907],{"id":20,"sortIndex":21,"affiliation":908,"properties":20},{"id":909,"createTime":910,"updateTime":910,"relativeEntities":911,"slug":20,"properties":912,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"a5feb3bd-e001-49b0-b2a2-b7097437600c","2023-12-23T03:18:21.118+00:00",[],{"title":913},{"VI":914},"Department of Psychology, Universität Oldenburg, Oldenburg, Germany",{"title":916},{"VI":917},"Hans Colonius",{"url":884,"publisher":919,"properties":947},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":920,"slug":10,"properties":921,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":925,"manageAffiliations":926,"indexDatabases":927,"url":20,"thumbnailPath":20,"statistic":942,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":922,"eissn":923,"title":924},{"VOID":13},{"VOID":15},{"EN":17},[],[],[928,935],{"id":84,"indexDatabase":929,"url":99,"indexYears":20,"academicFieldIds":934,"indexDatabaseRanking":20},{"id":86,"createTime":87,"updateTime":88,"relativeEntities":930,"label":931,"description":932,"key":95,"publicationTags":933,"standard":20},[],{"EN":91,"VI":91},{"VI":93,"EN":94},[97,98],[101,102],{"id":64,"indexDatabase":936,"url":77,"indexYears":78,"academicFieldIds":941,"indexDatabaseRanking":82},{"id":66,"createTime":67,"updateTime":68,"relativeEntities":937,"label":938,"description":939,"key":74,"publicationTags":940,"standard":20},[],{"EN":71,"VI":71},{"EN":71,"VI":73},[76],[80,81],{"impactFactor":21,"impactFactorByYear":943,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":944,"totalCitation":142,"totalCitationByYear":945,"totalCitationPerPublication":166,"totalCitationPerPublicationByYear":946,"hindexLast5Year":133,"hindex":133},{"2012":105,"2013":106,"2014":107,"2015":108,"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2001":121,"2002":122,"2003":123,"2004":124,"2005":118,"2006":125,"2007":125,"2008":126,"2009":127,"2010":128,"2011":129,"2012":130,"2013":131,"2014":132,"2015":133,"2016":134,"2017":135,"2018":136,"2019":137,"2020":131,"2021":138,"2022":139,"2023":140,"2024":141},{"2001":144,"2002":145,"2003":146,"2004":147,"2005":148,"2006":149,"2007":150,"2008":151,"2009":152,"2010":153,"2011":154,"2012":155,"2013":156,"2014":157,"2015":158,"2016":159,"2017":160,"2018":161,"2019":162,"2020":163,"2021":164,"2022":140,"2023":165},{"2001":168,"2002":169,"2003":170,"2004":171,"2005":172,"2006":173,"2007":174,"2008":175,"2009":176,"2010":177,"2011":178,"2012":179,"2013":180,"2014":181,"2015":182,"2016":183,"2017":184,"2018":185,"2019":186,"2020":187,"2021":188,"2022":189,"2023":190},{"volume":948,"pages":949},{"VOID":315},{"VOID":950},"344-353","2004-09-01",{"id":953,"createTime":954,"updateTime":955,"relativeEntities":956,"slug":957,"properties":958,"entityType":210,"verifyStatus":211,"verifyTime":955,"verifyNote":213,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":218,"primaryUrl":967,"fullTextUrl":20,"authors":968,"publicationType":283,"publisherRelationship":1004,"citationCount":20,"citationInfo":20,"publishDate":1038,"publishYear":1039,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":320},"65327305-6c31-4be9-b1a2-8b8d8160a52a","2023-12-24T18:12:47.140+00:00","2025-02-20T23:51:57.602+00:00",[],"Neural-response-to-evaluating-depression-predicts-perceivers-mental-health-treatment-recommendations",{"references":959,"abstract":961,"title":963,"doi":965},{"VOID":960},"Altamura, A. 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O., Copeland, V. C., Grote, N., Beach, S., Battista, D., & Reynolds, C. F. (2010). Depression stigma, race, and treatment seeking behavior and attitudes. Journal of Community Psychology, 38(3), 350–368.\nCassidy, B. S., & Gutchess, A. H. (2012). Social relevance enhances memory for impressions in older adults. Memory, 20(4), 332–345.\nCassidy, B. S., & Krendl, A. C. (2016). Dynamic neural mechanisms underlie race disparities in social cognition. NeuroImage, 132, 238–246.\nCehajic, S., Brown, R., & Gonzalez, R. (2009). What do I care? Perceive ingroup responsibility and dehumanization as predictors of empathy felt for the victim group. Group Processes and Intergroup Relations, 12, 715–729.\nCenters for Disease Control and Prevention (2013). Ten Leading Causes of Death by Age Group, United States -2013. Retrieved from: http:\u002F\u002Fwww.cdc.gov\u002Finjury\u002Fwisqars\u002Fpdf\u002Fleading_causes_of_death_by_age_group_2013-a.pdf\nCloutier, J., Gabrieli, J. 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Cerebral Cortex. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fcercor\u002Fbhu186\nFerrari, C., Vecchi, T., Todorov, A., & Cattaneo, Z. (2016). Interfering with activity in the dorsomedial prefrontal cortex via TMS affects social impressions updating. Cognitive, Affective, & Behavioral Neuroscience, 16(4), 626–634.\nFincher, K., & Tetlock, P. (2016). Dehumanization of faces is activated by norm violations and facilitates norm enforcement. Journal of Experimental Psychology: General, 145(2), 131–146.\nFiske, S. T., Cuddy, A. J., Glick, P., & Xu, J. (2002). A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition. Journal of Personality and Social Psychology, 82(6), 878.\nFiske, S. T., & Neuberg, S. L. (1990). A continuum of impression formation, from category- based to individuating processes: Influences of information and motivation on attention and interpretation. Advances in Experimental Social Psychology, 23, 1–74.\nGeorg Hsu, L. K., Wan, Y. M., Chang, H., Summergrad, P., Tsang, B. Y., & Chen, H. (2008). Stigma of depression is more severe in Chinese Americans than Caucasian Americans. Psychiatry: Interpersonal and Biological Processes, 71(3), 210–218.\nGivens, J. L., Katz, I. R., Bellamy, S., & Holmes, W. C. (2007). Stigma and the acceptability of depression treatments among African Americans and whites. Journal of General Internal Medicine, 22(9), 1292–1297.\nGoffman, E. (1963). Stigma: Notes on the management of spoiled identity. New York: Simon and Schuster.\nGreenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464.\nGreenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197.\nHarris, L. T., & Fiske, S. T. (2006). Dehumanizing the lowest of the low neuroimaging responses to extreme out-groups. Psychological Science, 17(10), 847–853.\nHayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling [White paper]. Retrieved from Retrieved from http:\u002F\u002Fwww.afhayes.com\u002Fpublic\u002Fprocess2012.pdf\nHinshaw, S. P. (2006). The mark of shame: Stigma of mental illness and an agenda for change. Oxford: Oxford University Press.\nJanz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health Education & Behavior, 11(1), 1–47.\nKrendl, A. C., Heatherton, T. F., & Kensinger, E. A. (2009). Aging minds and twisting attitudes: An fMRI investigation of age differences in inhibiting prejudice. Psychology and Aging, 24(3), 530.\nKrendl, A.C., Kensinger, E.A., & Ambady, N. (2012). How does the brain regulate negative bias to stigma? Social Cognitive & Affective Neuroscience. Advance online publication. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fscan\u002Fnsr046\nKrendl, A. C., Macrae, C. N., Kelley, W. M., Fugelsang, J. A., & Heatherton, T. F. (2006). The good, the bad, and the ugly: An fMRI investigation of the functional anatomic correlates of stigma. Social Neuroscience, 1(1), 5–15.\nKrendl, A. C., Moran, J. M., & Ambady, N. (2012). Does context matter in evaluations of stigmatized individuals? An fMRI study. Social Cognitive and Affective Neuroscience. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fscan\u002Fnss037\nKrendl, A. C., Zucker, H. R., & Kensinger, E. A. (2016). Identifying social stigma in 340 ms: Examining the effects of emotion regulation on the ERP response to negative social stimuli. Social Neuroscience, 12(3), 1–12.\nKroenke, K., Spitzer, R. L., & Williams, J. B. (2003). 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Annual Review of Psychology, 56, 393–421.\nMende-Siedlecki, P., Cai, Y., & Todorov, A. (2012). The neural dynamics of updating person impressions. Social Cognitive and Affective Neuroscience. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fscan\u002Fnss040\nMinear, M., & Park, D. C. (2004). A lifespan database of adult facial stimuli. Behavior Research Methods, Instruments, & Computers, 36(4), 630–633.\nMitchell, J. P. (2009). Social psychology as a natural kind. Trends in Cognitive Sciences, 13(6), 246–251.\nMitchell, J. P., Macrae, C. N., & Banaji, M. R. (2006). Dissociable medial prefrontal contributions to judgments of similar and dissimilar others. Neuron, 50(4), 655–663.\nMojtabai, R., Olfson, M., & Mechanic, D. (2002). Perceived need and help-seeking in adults with mood, anxiety, or substance use disorders. Archives of General Psychiatry, 59, 77–84.\nMoses, T. (2010). Being treated differently: Stigma experiences with family, peers, and school staff among adolescents with mental health disorders. Social Science & Medicine, 70(7), 985–993.\nNational Institute of Mental Health. (2012). Substance abuse and mental health services administration. Results from the 2009 National Survey on Drug Use and Health: Mental health findings. Rockville: Center for Behavioral Health Statistics and Quality.\nOchsner, K. N., Silvers, J. A., & Buhle, J. T. (2012). Functional imaging studies of emotion regulation: a synthetic review and evolving model of the cognitive control of emotion. Annals of the New York Academy of Sciences (New York, NY), 1251(1), E1–E24.\nPereira, C., Vala, J., & Leyens, J. P. (2009). From infra-humanization to discrimination: The mediation of symbolic threat needs egalitarian norms. Journal of Experimental Social Psychology, 45(2), 336–344.\nPescosolido, B. A., Martin, J. K., Lang, A., & Olafsdottir, S. (2008). Rethinking theoretical approaches to stigma: A framework integrating normative influences on stigma (FINIS). Social Science & Medicine, 67(3), 431–440.\nRao, D., Feinglass, J., & Corrigan, P. (2007). Racial and ethnic disparities in mental illness stigma. The Journal of nervous and mental disease, 195(12), 1020–1023.\nRicheson, J. A., Baird, A. A., Gordon, H. L., Heatherton, T. F., Wyland, C. L., Trawalter, S., & Shelton, J. N. (2003). An fMRI investigation of the impact of interracial contact on executive function. Nature Neuroscience, 6(12), 1323–1328.\nRitsher, J. B., Otilingam, P. G., & Grajales, M. (2003). Internalized stigma of mental illness: Psychometric properties of a new measure. Psychiatry Research, 121(1), 31–49.\nSchiller, D., Freeman, J. B., Mitchell, J. P., Uleman, J. S., & Phelps, E. A. (2009). A neural mechanism of first impressions. Nature Neuroscience, 12(4), 508–514.\nTeachman, B. A., Wilson, J. G., & Komarovskaya, I. (2006). Implicit and explicit stigma of mental illness in diagnosed and healthy samples. Journal of Social and Clinical Psychology, 25(1), 75–95.\nUleman, J. S., Newman, L. S., & Moskowitz, G. B. (1996). People as flexible interpreters: Evidence and issues from spontaneous trait inference. Advances in experimental social psychology, 28, 211-279.\nVan Overwalle, F. (2009). Social cognition and the brain: A meta-analysis. Human Brain Mapping, 30(3), 829–858.\nViki, G., Osgood, D., & Phillips, S. (2013). Dehumanization and self-reported proclivity to torture prisoners of war. Journal of Experimental Social Psychology, 49(3), 325–328.\nWakabayashi, A., Baron-Cohen, S., Wheelwright, S., Goldenfeld, N., Delaney, J., Fine, D., … & Weil, L. (2006). Development of short forms of the Empathy Quotient (EQ-Short) and the Systemizing Quotient (SQ-Short). Personality and Individual Differences, 41(5), 929–940.",{"EN":962},"Nonstigmatized perceivers’ initial evaluations of stigmatized individuals have profound consequences for the well-being of those stigmatized individuals. However, the mechanism by which this occurs remains underexplored. Specifically, what beliefs about the stigmatized condition (stigma-related beliefs) shape how nonstigmatized perceivers evaluate and behave toward stigmatized individuals? We examined these questions with respect to depression-related stigmatization because depression is highly stigmatized and nondepressed individuals’ behavior (e.g., willingness to recommend treatment) directly relates to removing stigma and increasing well-being. In Study 1, we identified common stigma-related beliefs associated with depression (e.g., not a serious illness, controllable, threatening), and found that only perceptions that depression is a serious condition predicted nondepressed perceivers’ willingness to recommend mental health treatment. Moreover, perceivers’ beliefs that depression is a distressing condition mediated the relationship between perceived seriousness and treatment recommendations (Study 1). In Study 2, we used fMRI to disentangle the potential processes connecting distress to nondepressed perceivers’ self-reported treatment intentions. Heightened activity in the dorsomedial prefrontal cortex (dmPFC)—a region widely implicated in evaluating others—and the ventrolateral prefrontal cortex (vlPFC)—a region widely implicated in regulating negative emotions—emerged when nondepressed perceivers evaluated individuals who were ostensibly depressed. Beliefs that depression is a distressing condition mediated the relationship between dmPFC (but not vlPFC) activity and nondepressed individuals’ self-reported treatment recommendations.",{"EN":964},"Neural response to evaluating depression predicts perceivers’ mental health treatment recommendations",{"VOID":966},"10.3758\u002Fs13415-017-0534-8","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-017-0534-8",[969,989],{"id":970,"sortIndex":247,"researcher":20,"roles":971,"affiliations":972,"properties":986},"89149abd-e035-4739-a31f-cea538a16272",[220],[973],{"id":974,"sortIndex":21,"affiliation":975,"properties":983},"e6331fc0-a7c7-4b3b-8b83-0ec3532c2269",{"id":976,"createTime":977,"updateTime":977,"relativeEntities":978,"slug":979,"properties":980,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"a00f68ea-5b19-4913-97cf-0c6188bb5a49","2024-12-10T21:26:54.591+00:00",[],"Department-of-Psychological-and-Brain-Sciences-Indiana-University-Bloomington-United-States",{"title":981},{"EN":982},"Department of Psychological and Brain Sciences, Indiana University, Bloomington, United States",{"title":984},{"VI":985},"Department of Psychological and Brain Sciences, Indiana University, Bloomington, USA",{"title":987},{"VI":988},"Brittany S. 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Advance online publication. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fjopy.12587\nWolff, M., Krönke, K.-M., Venz, J., Kräplin, A., Bühringer, G., Smolka, M. N., & Goschke, T. (2016). Action versus state orientation moderates the impact of executive functioning on real-life self-control. Journal of Experimental Psychology: General, 145(12), 1635–1653. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fxge0000229\nXu, X., Yuan, H., & Lei, X. (2016). Activation and Connectivity within the Default Mode Network Contribute Independently to Future-Oriented Thought. Scientific Reports, 6, 21001. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsrep21001\nZwosta, K., Ruge, H., Goschke, T., & Wolfensteller, U. (2018). Habit strength is predicted by activity dynamics in goal-directed brain systems during training. NeuroImage, 165, 125–137. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.neuroimage.2017.09.062\nZwosta, K., Ruge, H., & Wolfensteller, U. (2015). Neural mechanisms of goal-directed behavior: Outcome-based response selection is associated with increased functional coupling of the angular gyrus. Frontiers in Human Neuroscience, 9, 180. https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffnhum.2015.00180",{"EN":1050},"Despite its relevance for health and education, the neurocognitive mechanism of real-life self-control is largely unknown. While recent research revealed a prominent role of the ventromedial prefrontal cortex in the computation of an integrative value signal, the contribution and relevance of other brain regions for real-life self-control remains unclear. To investigate neural correlates of decisions in line with long-term consequences and to assess the potential of brain decoding methods for the individual prediction of real-life self-control, we combined functional magnetic resonance imaging during preference decision making with ecological momentary assessment of daily self-control in a large community sample (N = 266). Decisions in line with long-term consequences were associated with increased activity in bilateral angular gyrus and precuneus, regions involved in different forms of perspective taking, such as imagining one’s own future and the perspective of others. Applying multivariate pattern analysis to the same clusters revealed that individual patterns of activity predicted the probability of real-life self-control. Brain activations are discussed in relation to episodic future thinking and mentalizing as potential mechanisms mediating real-life self-control.",{"EN":1052},"Real-Life Self-Control is Predicted by Parietal Activity During Preference Decision Making: A Brain Decoding Analysis",{"VOID":1054},"10.3758\u002Fs13415-021-00913-w","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-021-00913-w",[1057,1072,1084,1113,1132,1154,1173,1185],{"id":1058,"sortIndex":21,"researcher":20,"roles":1059,"affiliations":1060,"properties":1069},"09e78461-7246-4240-995f-31402f062406",[220],[1061],{"id":20,"sortIndex":21,"affiliation":1062,"properties":20},{"id":1063,"createTime":1064,"updateTime":1064,"relativeEntities":1065,"slug":20,"properties":1066,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"127b3e28-181c-4623-86f5-402f6fa2eb90","2024-01-12T20:27:09.156+00:00",[],{"title":1067},{"VI":1068},"Faculty of Psychology, Technische Universität Dresden, Dresden, Germany",{"title":1070},{"VI":1071},"Klaus-Martin Krönke",{"id":1073,"sortIndex":272,"researcher":20,"roles":1074,"affiliations":1075,"properties":1081},"fc43ca4e-a45e-4c98-b668-764a5c7ef9d8",[220],[1076],{"id":20,"sortIndex":21,"affiliation":1077,"properties":20},{"id":1063,"createTime":1064,"updateTime":1064,"relativeEntities":1078,"slug":20,"properties":1079,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1080},{"VI":1068},{"title":1082},{"VI":1083},"Anja Kräplin",{"id":1085,"sortIndex":356,"researcher":20,"roles":1086,"affiliations":1087,"properties":1110},"19bdd354-a4b0-4db3-bf08-20c0bbd2e7e0",[220],[1088,1098],{"id":20,"sortIndex":21,"affiliation":1089,"properties":20},{"id":1090,"createTime":1091,"updateTime":1092,"relativeEntities":1093,"slug":1094,"properties":1095,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"9c074bbe-f8a9-4381-b787-517a1cbe3f83","2023-12-27T03:12:21.766+00:00","2024-09-04T13:22:53.643+00:00",[],"Department-of-Psychiatry-and-Psychotherapy-Technische-Universit%C3%A4t-Dresden-Dresden-Germany",{"title":1096},{"VI":1097},"Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany",{"id":1099,"sortIndex":247,"affiliation":1100,"properties":1109},"1410fae7-a27b-4c5b-9097-33648db2fc0d",{"id":1101,"createTime":1102,"updateTime":1103,"relativeEntities":1104,"slug":1105,"properties":1106,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"b0a67914-ca00-41ef-856a-3598065be17f","2023-12-06T05:23:41.074+00:00","2024-09-04T13:22:53.645+00:00",[],"Neuroimaging-Center-Technische-Universit%C3%A4t-Dresden-Dresden-Germany",{"title":1107},{"VI":1108},"Neuroimaging Center, Technische Universität Dresden, Dresden, Germany",{},{"title":1111},{"VI":1112},"Michael N. Smolka",{"id":1114,"sortIndex":247,"researcher":20,"roles":1115,"affiliations":1116,"properties":1129},"8901f703-6c8a-4075-9624-8822893508b3",[220],[1117,1122],{"id":20,"sortIndex":21,"affiliation":1118,"properties":20},{"id":1063,"createTime":1064,"updateTime":1064,"relativeEntities":1119,"slug":20,"properties":1120,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1121},{"VI":1068},{"id":1123,"sortIndex":247,"affiliation":1124,"properties":1128},"2bc3a8eb-cdfa-4ab6-83fa-bb0e6bcef728",{"id":1101,"createTime":1102,"updateTime":1103,"relativeEntities":1125,"slug":1105,"properties":1126,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1127},{"VI":1108},{},{"title":1130},{"VI":1131},"Holger Mohr",{"id":1133,"sortIndex":340,"researcher":20,"roles":1134,"affiliations":1135,"properties":1151},"bb2e7d70-8f5b-42bc-877a-04363f440c61",[220],[1136,1146],{"id":1137,"sortIndex":247,"affiliation":1138,"properties":1145},"22c3a6d3-16fa-42b8-b7b9-d3fdad9c9eb4",{"id":1139,"createTime":1140,"updateTime":1140,"relativeEntities":1141,"slug":20,"properties":1142,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"759233a1-e56e-4213-b82f-6b3d33d4878c","2024-01-25T04:22:04.755+00:00",[],{"title":1143},{"VI":1144},"Department of Clinical Research, Faculty of Health, University of Southern Denmark, Odense, 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K. C., Machado-de-Sousa, J. P., Trzesniak, C., Santos Filho, A., Ferrari, M. C. F., Osório, F. L., … Crippa, J. A. S. (2010). Social anxiety disorder women easily recognize fearfull, sad and happy faces: The influence of gender. Journal of Psychiatric Research, 44, 535–540. doi:10.1016\u002Fj.jpsychires.2009.11.003\nBar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study. Psychological Bulletin, 133, 1–24. doi:10.1037\u002F0033-2909.133.1.1\nBarlow, D. H. (2004). Anxiety and its disorders: The nature and treatment of anxiety and panic. New York: Guilford Press.\nBechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15.\nBechara, A., Tranel, D., & Damasio, H. (2000). Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain, 123, 2189–2202. doi:10.1093\u002Fbrain\u002F123.11.2189\nBlair, K., Marsh, A. A., Morton, J., Vythilingam, M., Jones, M., Mondillo, K., & Blair, J. R. (2006). Choosing the lesser of two evils, the better of two goods: Specifying the roles of ventromedial prefrontal cortex and dorsal anterior cingulate in object choice. Journal of Neuroscience, 26, 11379–11386. doi:10.1523\u002FJNEUROSCI.1640-06.2006\nBlasi, G., Hariri, A. R., Alce, G., Taurisano, P., Sambataro, F., Das, S., & Mattay, V. S. (2009). Preferential amygdala reactivity to the negative assessment of neutral faces. Biological Psychiatry, 66, 847–853. doi:10.1016\u002Fj.biopsych.2009.06.017\nBradley, B. P., Mogg, K., White, J., Groom, C., & de Bono, J. (1999). Attentional bias for emotional faces in generalized anxiety disorder. British Journal of Clinical Psychology, 38, 267–278.\nBreiter, H. C., Etcoff, N. L., Whalen, P. J., Kennedy, W. A., Rauch, S. L., Buckner, R. L., & Rosen, B. R. (1996). Response and habituation of the human amygdala during visual processing of facial expression. Neuron, 17, 875–887.\nCarmichael, S. T., & Price, J. L. (1995). Limbic connections of the orbital and medial prefrontal cortex in macaque monkeys. Journal of Comparative Neurology, 363, 615–641. doi:10.1002\u002Fcne.903630408\nCarmichael, S. T., & Price, J. L. (1996). Connectional networks within the orbital and medial prefrontal cortex of macaque monkeys. Journal of Comparative Neurology, 371, 179–207.\nCaseras, X., Àvila, C., & Torrubia, R. (2003). The measurement of individual differences in Behavioural Inhibition and Behavioural Activation Systems: A comparison of personality scales. Personality and Individual Differences, 34, 999–1013. doi:10.1016\u002FS0191-8869(02)00084-3\nChawla, D., Rees, G., & Friston, K. J. (1999). The physiological basis of attentional modulation in extrastriate visual areas. 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Neural activity relating to generation and representation of galvanic skin conductance responses: A functional magnetic resonance imaging study. Journal of Neuroscience, 20, 3033–3040.\nDale, A. M. (1999). Optimal experimental design for event-related fMRI. Human Brain Mapping, 8, 109–114.\nDavidson, R. J., Maxwell, J. S., & Shackman, A. J. (2004). The privileged status of emotion in the brain. Proceedings of the National Academy of Sciences, 101, 11915–11916. doi:10.1073\u002Fpnas.0404264101\nDeane, G. E. (1969). Cardiac activity during experimentally induced anxiety. Psychophysiology, 6, 17–30.\nDi Martino, A., Scheres, A., Margulies, D. S., Kelly, A. M. C., Uddin, L. Q., Shehzad, Z., … Milham, M. P. (2008). Functional connectivity of human striatum: A resting state FMRI study. Cerebral Cortex, 18, 2735–2747. doi:10.1093\u002Fcercor\u002Fbhn041\nDoty, T. J., Japee, S., Ingvar, M., & Ungerleider, L. G. (2013). 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Cognition and Emotion, 14, 61–92. doi:10.1080\u002F026999300378996\nFurmark, T., Tillfors, M., Marteinsdottir, I., Fischer, H., Pissiota, A., Långström, B., & Fredrikson, M. (2002). Common changes in cerebral blood flow in patients with social phobia treated with citalopram or cognitive–behavioral therapy. Archives of General Psychiatry, 59, 425–433.\nHaber, S. N., Kunishio, K., Mizobuchi, M., & Lynd-Balta, E. (1995). The orbital and medial prefrontal circuit through the primate basal ganglia. Journal of Neuroscience, 15, 4851–4867.\nHansen, C. H., & Hansen, R. D. (1988). Finding the face in the crowd: An anger superiority effect. Journal of Personality and Social Psychology, 54, 917–924.\nHikosaka, O., Sakamoto, M., & Usui, S. (1989). Functional properties of monkey caudate neurons: III. Activities related to expectation of target and reward. Journal of Neurophysiology, 61, 814–832.\nIshai, A., Pessoa, L., Bikle, P. C., & Ungerleider, L. G. (2004). Repetition suppression of faces is modulated by emotion. Proceedings of the National Academy of Sciences, 101, 9827–9832. doi:10.1073\u002Fpnas.0403559101\nJapee, S., Crocker, L., Carver, F., Pessoa, L., & Ungerleider, L. G. (2009). Individual differences in valence modulation of face-selective M170 response. Emotion, 9, 59–69. doi:10.1037\u002Fa0014487\nJohansen-Berg, H., Gutman, D. A., Behrens, T. E. J., Matthews, P. M., Rushworth, M. F. S., Katz, E., … Mayberg, H. S. (2008). Anatomical connectivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression. Cerebral Cortex, 18, 1374–1383. doi:10.1093\u002Fcercor\u002Fbhm167\nKastner, S., Pinsk, M. A., De Weerd, P., Desimone, R., & Ungerleider, L. G. (1999). Increased activity in human visual cortex during directed attention in the absence of visual stimulation. Neuron, 22, 751–761.\nKim, M. J., Gee, D. G., Loucks, R. A., Davis, F. C., & Whalen, P. J. (2011). Anxiety dissociates dorsal and ventral medial prefrontal cortex functional connectivity with the amygdala at rest. Cerebral Cortex, 21, 1667–1673. doi:10.1093\u002Fcercor\u002Fbhq237\nKim, M. J., & Whalen, P. J. (2009). The structural integrity of an amygdala–prefrontal pathway predicts trait anxiety. Journal of Neuroscience, 29, 11614–11618. doi:10.1523\u002FJNEUROSCI.2335-09.2009\nKnutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience, 21, RC159.\nKoenigs, M., Young, L., Adolphs, R., Tranel, D., Cushman, F., Hauser, M., & Damasio, A. (2007). Damage to the prefrontal cortex increases utilitarian moral judgements. Nature, 446, 908–911. doi:10.1038\u002Fnature05631\nKunishio, K., & Haber, S. N. (1994). Primate cingulostriatal projection: Limbic striatal versus sensorimotor striatal input. Journal of Comparative Neurology, 350, 337–356. doi:10.1002\u002Fcne.903500302\nLeh, S. 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Some methodological issues in assessing attentional biases for threatening faces in anxiety: A replication study using a modified version of the probe detection task. Behaviour Research and Therapy, 37, 595–604.\nMorris, J. S., Friston, K. J., Büchel, C., Frith, C. D., Young, A. W., Calder, A. J., & Dolan, R. J. (1998). A neuromodulatory role for the human amygdala in processing emotional facial expressions. Brain, 121, 47–57.\nMorris, J. S., Frith, C. D., Perrett, D. I., Rowland, D., Young, A. W., Calder, A. J., & Dolan, R. J. (1996). A differential neural response in the human amygdala to fearful and happy facial expressions. Nature, 383, 812–815. doi:10.1038\u002F383812a0\nÖhman, A., & Mineka, S. (2001). Fears, phobias, and preparedness: Toward an evolved module of fear and fear learning. Psychological Review, 108, 483–522. doi:10.1037\u002F0033-295X.108.3.483\nPessoa, L., Japee, S., Sturman, D., & Ungerleider, L. G. (2006). Target visibility and visual awareness modulate amygdala responses to fearful faces. Cerebral Cortex, 16, 366–375. doi:10.1093\u002Fcercor\u002Fbhi115\nPessoa, L., Japee, S., & Ungerleider, L. G. (2005). Visual awareness and the detection of fearful faces. Emotion, 5, 243–247. doi:10.1037\u002F1528-3542.5.2.243\nPessoa, L., McKenna, M., Gutierrez, E., & Ungerleider, L. G. (2002). Neural processing of emotional faces requires attention. Proceedings of the National Academy of Sciences, 99, 11458–11463. doi:10.1073\u002Fpnas.172403899\nPhelps, E. A., Delgado, M. R., Nearing, K. I., & LeDoux, J. E. (2004). Extinction learning in humans: Role of the amygdala and vmPFC. Neuron, 43, 897–905. doi:10.1016\u002Fj.neuron.2004.08.042\nPorrino, L. J., Crane, A. M., & Goldman-Rakic, P. S. (1981). Direct and indirect pathways from the amygdala to the frontal lobe in rhesus monkeys. Journal of Comparative Neurology, 198, 121–136. doi:10.1002\u002Fcne.901980111\nRichards, A., French, C. C., Calder, A. J., Webb, B., Fox, R., & Young, A. W. (2002). Anxiety-related bias in the classification of emotionally ambiguous facial expressions. Emotion, 2, 273–287.\nRusschen, F. T., Bakst, I., Amaral, D. G., & Price, J. L. (1985). The amygdalostriatal projections in the monkey: An anterograde tracing study. Brain Research, 329, 241–257.\nSamejima, K., Ueda, Y., Doya, K., & Kimura, M. (2005). Representation of action-specific reward values in the striatum. Science, 310, 1337–1340. doi:10.1126\u002Fscience.1115270\nSchoenbaum, G., & Roesch, M. (2005). Orbitofrontal cortex, associative learning, and expectancies. Neuron, 47, 633–636. doi:10.1016\u002Fj.neuron.2005.07.018\nSchultz, W., & Dickinson, A. (2000). Neuronal coding of prediction errors. Annual Review of Neuroscience, 23, 473–500. doi:10.1146\u002Fannurev.neuro.23.1.473\nSpielberger, C. D. (1983). Manual for the State–Trait Anxiety Inventory (Form Y). Palo Alto: Consulting Psychologists Press.\nStewart, M. E., Ebmeier, K. P., & Deary, I. J. (2005). Personality correlates of happiness and sadness: EPQ-R and TPQ compared. Personality and Individual Differences, 38, 1085–1096. doi:10.1016\u002Fj.paid.2004.07.007\nSurcinelli, P., Codispoti, M., Montebarocci, O., Rossi, N., & Baldaro, B. (2006). Facial emotion recognition in trait anxiety. Journal of Anxiety Disorders, 20, 110–117. doi:10.1016\u002Fj.janxdis.2004.11.010\nTalairach, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain: 3-D proportional system: An approach to cerebral imaging. New York: Thieme.\nTobler, P. N., O’Doherty, J. P., Dolan, R. J., & Schultz, W. (2006). Human neural learning depends on reward prediction errors in the blocking paradigm. Journal of Neurophysiology, 95, 301–310. doi:10.1152\u002Fjn.00762.2005\nVogt, B. A., & Pandya, D. N. (1987). Cingulate cortex of the rhesus monkey: II. Cortical afferents. Journal of Comparative Neurology, 262, 271–289. doi:10.1002\u002Fcne.902620208\nWhalen, P. J., Rauch, S. L., Etcoff, N. L., McInerney, S. C., Lee, M. B., & Jenike, M. A. (1998). Masked presentations of emotional facial expressions modulate amygdala activity without explicit knowledge. Journal of Neuroscience, 18, 411–418.\nWilson, E., & MacLeod, C. (2003). Contrasting two accounts of anxiety-linked attentional bias: Selective attention to varying levels of stimulus threat intensity. Journal of Abnormal Psychology, 112, 212–218.\nWinecoff, A., Clithero, J. A., Carter, R. M., Bergman, S. R., Wang, L., & Huettel, S. A. (2013). Ventromedial prefrontal cortex encodes emotional value. Journal of Neuroscience, 33, 11032–11039. doi:10.1523\u002FJNEUROSCI.4317-12.2013\nWinton, E. C., Clark, D. M., & Edelmann, R. J. (1995). Social anxiety, fear of negative evaluation and the detection of negative emotion in others. Behaviour Research and Therapy, 33, 193–196.\nYoung, L., Bechara, A., Tranel, D., Damasio, H., Hauser, M., & Damasio, A. (2010). Damage to ventromedial prefrontal cortex impairs judgment of harmful intent. Neuron, 65, 845–851. doi:10.1016\u002Fj.neuron.2010.03.003",{"EN":1251},"Stimuli that signal threat show considerable variability in the extents to which they enhance behavior, even among healthy individuals. However, the neural underpinning of this behavioral variability is not well understood. By manipulating expectation of threat in an fMRI study of fearful versus neutral face categorization, we uncovered a network of areas underlying variability in threat processing in healthy adults. We explicitly altered expectations by presenting face images at three different expectation levels: 80 %, 50 %, and 20 %. Subjects were instructed to report as quickly and accurately as possible whether the face was fearful (signaled threat) or not. An uninformative cue preceded each face by 4 s. By taking the difference between reaction times (RTs) to fearful and neutral faces, we quantified an overall fear RT bias (i.e., faster to fearful than to neutral faces) for each subject. This bias correlated positively with late-trial fMRI activation (8 s after the face) during unexpected-fearful-face trials in bilateral ventromedial prefrontal cortex, the left subgenual cingulate cortex, and the right caudate nucleus, and correlated negatively with early-trial fMRI activation (4 s after the cue) during expected-neutral-face trials in bilateral dorsal striatum and the right ventral striatum. These results demonstrate that the variability in threat processing among healthy adults is reflected not only in behavior, but also in the magnitude of activation in medial prefrontal and striatal regions that appear to encode affective value.",{"EN":1253},"Intersubject variability in fearful face processing: the linkbetween behavior and neural activation",{"VOID":1255},"10.3758\u002Fs13415-014-0290-y","2025-01-14T23:50:17.072+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.3758\u002Fs13415-014-0290-y",[1259,1276,1291,1303],{"id":1260,"sortIndex":218,"researcher":20,"roles":1261,"affiliations":1262,"properties":1273},"3adf8d55-c1e2-4d2e-93d4-d9095b46cd7c",[220],[1263],{"id":20,"sortIndex":21,"affiliation":1264,"properties":20},{"id":1265,"createTime":1266,"updateTime":1267,"relativeEntities":1268,"slug":1269,"properties":1270,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"16f53dd4-b2d7-4417-b7c0-f7eedc0c7392","2024-01-05T13:00:45.663+00:00","2024-11-30T14:24:20.234+00:00",[],"Department-of-Clinical-Neuroscience-Karolinska-Institutet-Stockholm-Sweden",{"title":1271},{"VI":1272},"Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden",{"title":1274},{"VI":1275},"Martin Ingvar",{"id":1277,"sortIndex":272,"researcher":20,"roles":1278,"affiliations":1279,"properties":1288},"0a4c6926-10a3-44f1-81b0-873a9be6b4a3",[220],[1280],{"id":20,"sortIndex":21,"affiliation":1281,"properties":20},{"id":1282,"createTime":1283,"updateTime":1283,"relativeEntities":1284,"slug":20,"properties":1285,"entityType":48,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"28fc381a-12b9-4406-84d7-348dafb4524c","2024-01-15T11:05:22.740+00:00",[],{"title":1286},{"VI":1287},"Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA",{"title":1289},{"VI":1290},"Leslie G. 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