Whole-Brain fMRI Functional Connectivity Signatures Predict Sustained Emotional Experience in Naturalistic Contexts
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Linling Li | G. Huang | Zhiguo Zhang | Xiqin Liu | Li Zhang | Zhen Liang | Yongjie Zhou | B. Becker | Shuyue Xu | Danyi Lin
[1] Jonathan W. Kanen,et al. Angiotensin blockade enhances motivational reward learning via enhancing striatal prediction error signaling and frontostriatal communication , 2023, bioRxiv.
[2] F. Zhou,et al. Angiotensin II regulates the neural expression of subjective fear in humans - precision pharmaco-neuroimaging approach , 2022, bioRxiv.
[3] Philip A. Kragel,et al. Common and stimulus-type-specific brain representations of negative affect , 2022, Nature Neuroscience.
[4] E. Rolls,et al. The human orbitofrontal cortex, vmPFC, and anterior cingulate cortex effective connectome: emotion, memory, and action. , 2022, Cerebral cortex.
[5] Preston P. Thakral,et al. Representing the Good and Bad: fMRI signatures during the encoding of multisensory positive, negative, and neutral events , 2022, Cortex.
[6] M. Sams,et al. Classification of emotion categories based on functional connectivity patterns of the human brain , 2021, NeuroImage.
[7] U. Hasson,et al. Naturalistic imaging: The use of ecologically valid conditions to study brain function , 2021, NeuroImage.
[8] Pedro A. M. Mediano,et al. A synergistic core for human brain evolution and cognition , 2020, bioRxiv.
[9] T. Wager,et al. A distributed fMRI-based signature for the subjective experience of fear , 2021, Nature Communications.
[10] D. Brang,et al. Naturalistic Stimuli: A Paradigm for Multi-Scale Functional Characterization of the Human Brain. , 2021, Current opinion in biomedical engineering.
[11] N. Sousa,et al. Habitual coffee drinkers display a distinct pattern of brain functional connectivity , 2021, Molecular Psychiatry.
[12] K. Kendrick,et al. Segregating domain-general from emotional context-specific inhibitory control systems - ventral striatum and orbitofrontal cortex serve as emotion-cognition integration hubs , 2020, NeuroImage.
[13] M. Sams,et al. Movies and narratives as naturalistic stimuli in neuroimaging , 2020, NeuroImage.
[14] Emmanuel A Stamatakis,et al. Combining network topology and information theory to construct representative brain networks , 2020, Network Neuroscience.
[15] Affect Dynamics , 2021 .
[16] Luke J. Chang,et al. Movie viewing elicits rich and reliable brain state dynamics , 2020, Nature Communications.
[17] K. Kendrick,et al. Empathic pain evoked by sensory and emotional-communicative cues share common and process-specific neural representations , 2020, eLife.
[18] R. Ptak,et al. Discrete Patterns of Cross-Hemispheric Functional Connectivity Underlie Impairments of Spatial Cognition after Stroke , 2020, The Journal of Neuroscience.
[19] James A. Roberts,et al. Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain , 2020, NeuroImage.
[20] K. Kendrick,et al. Oxytocin Differentially Modulates Amygdala Responses during Top‐Down and Bottom‐Up Aversive Anticipation , 2020, Advanced science.
[21] Timo T. Heikkilä,et al. Decoding music-evoked emotions in the auditory and motor cortex , 2020, bioRxiv.
[22] K. Kendrick,et al. Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate Major Depressive from Generalized Anxiety Disorder , 2020, bioRxiv.
[23] J. Hajnal,et al. Emerging functional connectivity differences in newborn infants vulnerable to autism spectrum disorders , 2020, Translational Psychiatry.
[24] M. Milham,et al. Towards clinical applications of movie fMRI , 2020, NeuroImage.
[25] Christine E. Weber,et al. An fMRI Study of Affective Congruence across Visual and Auditory Modalities , 2020, Journal of Cognitive Neuroscience.
[26] Ale Smidts,et al. Decoding dynamic affective responses to naturalistic videos with shared neural patterns , 2020, NeuroImage.
[27] S. Sturgeon. The Bayesian Model , 2020 .
[28] Daniel S. Margulies,et al. Topographic organization of the human subcortex unveiled with functional connectivity gradients , 2020, Nature Neuroscience.
[29] Erez Simony,et al. Analysis of stimulus-induced brain dynamics during naturalistic paradigms , 2019, NeuroImage.
[30] X. Di,et al. Intersubject consistent dynamic connectivity during natural vision revealed by functional MRI , 2019, NeuroImage.
[31] J. Poline,et al. Nature abhors a paywall: How open science can realize the potential of naturalistic stimuli , 2019, NeuroImage.
[32] Alan S. Cowen,et al. The Neural Representation of Visually Evoked Emotion Is High-Dimensional, Categorical, and Distributed across Transmodal Brain Regions , 2019, bioRxiv.
[33] Ajay B. Satpute,et al. The Default Mode Network’s Role in Discrete Emotion , 2019, Trends in Cognitive Sciences.
[34] Amy M. Belfi,et al. The default-mode network represents aesthetic appeal that generalizes across visual domains , 2019, Proceedings of the National Academy of Sciences.
[35] Richard F. Betzel,et al. Temporal fluctuations in the brain's modular architecture during movie-watching , 2019, NeuroImage.
[36] Michael Breakspear,et al. Naturalistic Stimuli in Neuroscience: Critically Acclaimed , 2019, Trends in Cognitive Sciences.
[37] Ling Zou,et al. The Cortical Network of Emotion Regulation: Insights From Advanced EEG-fMRI Integration Analysis , 2019, IEEE Transactions on Medical Imaging.
[38] Catherine Perrodin,et al. Are We Ready for Real-world Neuroscience? , 2019, Journal of Cognitive Neuroscience.
[39] Tor D. Wager,et al. Emotion schemas are embedded in the human visual system , 2018, Science Advances.
[40] Emiliano Ricciardi,et al. Emotionotopy in the human right temporo-parietal cortex , 2019, Nature Communications.
[41] Matthieu Gilson,et al. Distinct modes of functional connectivity induced by movie-watching , 2019, NeuroImage.
[42] Marianne C. Reddan,et al. Attenuating Neural Threat Expression with Imagination , 2018, Neuron.
[43] M. Breakspear,et al. Effective connectivity of the anterior hippocampus predicts recollection confidence during natural memory retrieval , 2018, Nature Communications.
[44] C. Kilts,et al. Common Functional Brain States Encode both Perceived Emotion and the Psychophysiological Response to Affective Stimuli , 2018, Scientific Reports.
[45] Simon B Eickhoff,et al. Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results , 2018, Network Neuroscience.
[46] K. Kendrick,et al. Shifted balance of dorsal versus ventral striatal communication with frontal reward and regulatory regions in cannabis‐dependent males , 2018, Human brain mapping.
[47] Maurizio Corbetta,et al. A New Modular Brain Organization of the BOLD Signal during Natural Vision , 2018, Cerebral cortex.
[48] Vince D. Calhoun,et al. Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging , 2018, Front. Neurosci..
[49] Nathan M. Petro,et al. Individual differences in valence bias: fMRI evidence of the initial negativity hypothesis , 2018, Social cognitive and affective neuroscience.
[50] M. Sams,et al. Distributed affective space represents multiple emotion categories across the human brain , 2018, Social cognitive and affective neuroscience.
[51] Anthony R. McIntosh,et al. Unique Mapping of Structural and Functional Connectivity on Cognition , 2018, The Journal of Neuroscience.
[52] Luiz Pessoa,et al. Understanding emotion with brain networks , 2018, Current Opinion in Behavioral Sciences.
[53] Matthieu Gilson,et al. Effective connectivity inferred from fMRI transition dynamics during movie viewing points to a balanced reconfiguration of cortical interactions , 2017, NeuroImage.
[54] B. Weber,et al. Altered orbitofrontal activity and dorsal striatal connectivity during emotion processing in dependent marijuana users after 28 days of abstinence , 2018, Psychopharmacology.
[55] Yuanqing Li,et al. An MVPA method based on sparse representation for pattern localization in fMRI data analysis , 2017, Neurocomputing.
[56] David K. Menon,et al. Default mode contributions to automated information processing , 2017, Proceedings of the National Academy of Sciences.
[57] Alan S. Cowen,et al. Self-report captures 27 distinct categories of emotion bridged by continuous gradients , 2017, Proceedings of the National Academy of Sciences.
[58] Evan M. Gordon,et al. Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI , 2017, bioRxiv.
[59] L. Pessoa. A Network Model of the Emotional Brain , 2017, Trends in Cognitive Sciences.
[60] Peter Kuppens,et al. The neural basis of emotions varies over time: different regions go with onset- and offset-bound processes underlying emotion intensity , 2017, Social cognitive and affective neuroscience.
[61] Xintao Hu,et al. Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms , 2016, bioRxiv.
[62] R. Cameron Craddock,et al. Individual differences in functional connectivity during naturalistic viewing conditions , 2016, NeuroImage.
[63] Alzheimer's Disease Neuroimaging Initiative,et al. Altered functional brain networks in amnestic mild cognitive impairment: a resting-state fMRI study , 2016, Brain Imaging and Behavior.
[64] Jessica R. Cohen,et al. The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition , 2016, The Journal of Neuroscience.
[65] Yufeng Zang,et al. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging , 2016, Neuroinformatics.
[66] R. Hari,et al. Discrete Neural Signatures of Basic Emotions. , 2016, Cerebral cortex.
[67] Philip A. Kragel,et al. Multivariate neural biomarkers of emotional states are categorically distinct. , 2015, Social cognitive and affective neuroscience.
[68] N. Jaworska,et al. A review of fMRI studies during visual emotive processing in major depressive disorder , 2015, The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry.
[69] J. P. Hamilton,et al. Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience , 2015, Biological Psychiatry.
[70] Karim Jerbi,et al. Exceeding chance level by chance: The caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy , 2015, Journal of Neuroscience Methods.
[71] M. Raichle. The brain's default mode network. , 2015, Annual review of neuroscience.
[72] Thomas E. Nichols,et al. A Bayesian Model of Category-Specific Emotional Brain Responses , 2015, PLoS Comput. Biol..
[73] Mikko Sams,et al. Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks , 2014, NeuroImage.
[74] Moors Pieter,et al. Test-retest reliability. , 2014 .
[75] Rebecca Saxe,et al. Contributions of episodic retrieval and mentalizing to autobiographical thought: Evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses , 2014, NeuroImage.
[76] Dewen Hu,et al. Unsupervised classification of major depression using functional connectivity MRI , 2014, Human brain mapping.
[77] Kevin S. LaBar,et al. Advancing Emotion Theory with Multivariate Pattern Classification , 2014, Emotion review : journal of the International Society for Research on Emotion.
[78] G. Glover,et al. Causal interactions between fronto-parietal central executive and default-mode networks in humans , 2013, Proceedings of the National Academy of Sciences.
[79] Viviana Betti,et al. Natural Scenes Viewing Alters the Dynamics of Functional Connectivity in the Human Brain , 2013, Neuron.
[80] M. Maroun,et al. Medial Prefrontal Cortex , 2013, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[81] M. Just,et al. Identifying Emotions on the Basis of Neural Activation , 2013, PloS one.
[82] Florin Dolcos,et al. Neural Correlates of Opposing Effects of Emotional Distraction on Working Memory and Episodic Memory: An Event-Related fMRI Investigation , 2013, Front. Psychol..
[83] Antonio Rangel,et al. Stimulus Value Signals in Ventromedial PFC Reflect the Integration of Attribute Value Signals Computed in Fusiform Gyrus and Posterior Superior Temporal Gyrus , 2013, The Journal of Neuroscience.
[84] Steffen Katzner,et al. Visual cortical networks: of mice and men , 2013, Current Opinion in Neurobiology.
[85] A. Damasio,et al. The nature of feelings: evolutionary and neurobiological origins , 2013, Nature Reviews Neuroscience.
[86] Kristen A. Lindquist,et al. A functional architecture of the human brain: emerging insights from the science of emotion , 2012, Trends in Cognitive Sciences.
[87] Christian E. Waugh,et al. Timing: A missing key ingredient in typical fMRI studies of emotion , 2012, Behavioral and Brain Sciences.
[88] Kristen A. Lindquist,et al. The brain basis of emotion: A meta-analytic review , 2012, Behavioral and Brain Sciences.
[89] D. Hu,et al. Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. , 2012, Brain : a journal of neurology.
[90] Feng Liu,et al. Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatment-response depression: A resting-state fMRI study , 2012, Progress in Neuro-Psychopharmacology and Biological Psychiatry.
[91] J. Ford,et al. Default mode network activity and connectivity in psychopathology. , 2012, Annual review of clinical psychology.
[92] Jing Wang,et al. Decoding the neural representation of affective states , 2012, NeuroImage.
[93] Ilya M. Veer,et al. Beyond acute social stress: Increased functional connectivity between amygdala and cortical midline structures , 2011, NeuroImage.
[94] S. Hamann,et al. Neuroimaging Support for Discrete Neural Correlates of Basic Emotions: A Voxel-based Meta-analysis , 2010, Journal of Cognitive Neuroscience.
[95] J. Yiend. The effects of emotion on attention: A review of attentional processing of emotional information , 2010 .
[96] 劉 健勤,et al. 複雑系に見たDefault Mode Network , 2009, ICS 2009.
[97] F. Van Overwalle. Social cognition and the brain: A meta‐analysis , 2009, Human brain mapping.
[98] R. Nathan Spreng,et al. The Common Neural Basis of Autobiographical Memory, Prospection, Navigation, Theory of Mind, and the Default Mode: A Quantitative Meta-analysis , 2009, Journal of Cognitive Neuroscience.
[99] J. Andrews-Hanna,et al. The brain's default network: Anatomy, function, and consequence of disruption , 2009 .
[100] A. Craig,et al. How do you feel — now? The anterior insula and human awareness , 2009, Nature Reviews Neuroscience.
[101] Lisa Feldman Barrett,et al. Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies , 2008, NeuroImage.
[102] E. Kensinger,et al. Emotional valence influences the neural correlates associated with remembering and knowing , 2008, Cognitive, affective & behavioral neuroscience.
[103] D. Schacter,et al. The cognitive neuroscience of constructive memory: remembering the past and imagining the future , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.
[104] O. Pollatos,et al. Neural systems connecting interoceptive awareness and feelings , 2007, Human brain mapping.
[105] Janaina Mourão Miranda,et al. Contributions of stimulus valence and arousal to visual activation during emotional perception , 2003, NeuroImage.
[106] K. Luan Phan,et al. Functional Neuroanatomy of Emotion: A Meta-Analysis of Emotion Activation Studies in PET and fMRI , 2002, NeuroImage.
[107] Thomas E. Nichols,et al. Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.
[108] G. Shulman,et al. Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function , 2001, Proceedings of the National Academy of Sciences of the United States of America.