1. Degeneracy, multiple solutions, and predictive processing in affective science
McVeigh, K., Kleckner, I., Quigley, K., & Satpute, A. B. (2023). Fear-related psychophysiological patterns are situation and person dependent: A Bayesian model comparison approach. Emotion.
Khan, Z., Wang, Y., Sennesh, E. Z., Dy, J., Ostaddabas, S., van de Meent, J. W., Hutchinson, J. B., & Satpute, A. B. (2022). A computational neural model for mapping degenerative neural architectures. Neuroinformatics, 1-15.
Lee, K. M., Ferreira-Santos, F., & Satpute, A. B. (2021). Predictive models in affective neuroscience. Neuroscience and Biobehavioral Reviews 131, 211-228.
Azari, B., Westlin, C, Satpute, A.B., Hutchinson, J.B., Kragel P.A., Hoemann, K., Khan, Z., Wormwood, J.B., Quigley, K.S., Erdogmus, D., Dy, J., Brooks, D.H., & Barrett, L.F. (2020). Comparing supervised and unsupervised approaches to emotion categorization. Scientific Reports, 10, 1-17.
Sennesh, E., Khan, Z., Wang, Y., Farnoosh, A., Ostadabbas, S., Dy, J., Satpute, A. B., Hutchinson, J. B. & van de Meent, J. W. (2020). Neural Topographic Factor Analysis for fMRI Data. NeurIPS.
2. Affective experience: neuroscience and peripheral physiology
MacCormack, J. K., Stein, A. G., Giovanello, K. S., Kang, J., Satpute, A. B., & Lindquist, K. A. (2020). Affect in the aging brain: A neuroimaging meta-analysis of functional activation and coactivation differences in older vs. younger adult affective experience and perception. Affective Science, 1, 128-154. DOI: 10.1007/s42761-020-00016-8
Wake, S., Wormwood, J., & Satpute, A. B. (2020). The influence of fear on risk taking: A meta-analysis. Cognition and Emotion, 34, 1-17.
Satpute, A. B., Hanington, L., & Barrett, L. F. (2016). Novel response patterns during repeated presentation of affective and neutral stimuli. Soc Cogn Affect Neurosci, 11, 1919-1932.
Lindquist KA, Satpute AB, Wager TD, Weber J, Barrett LF (2016) The Brain Basis of Positive and Negative Affect: Evidence from a Meta-Analysis of the Human Neuroimaging Literature. Cereb Cortex 26:1910–1922.
Satpute, A. B., Kang, J., Bickart, K., Wager, T. D., & Feldman Barrett, L. (2015). Involvement of sensory regions in affective experience: A meta-analysis. Frontiers in Psychology, 6, 1860. Supplementary Materials
Satpute, A. B., Shu, J., Weber, J., Roy, M., & Ochsner, K. N. (2012). The Functional Neural Architecture of Self-Reports of Affective Experience. Biol Psychiatry, 73, 631-638. doi: 10.1016/j.biopsych.2012.10.001
3. Social cognitive neuroscience
Atzil, S., Satpute, A. B., Zhang, J., Parrish, M. H., Shablack, H., MacCormack, J. K., Leshin, J., Goel, S., Brooks, J. A., Kang, J., Xu, Y., Cohen, M., & Lindquist, K. A. (2023). The impact of sociality and affective valence on brain activation: A meta-analysis. NeuroImage, 119879
Satpute, A. B., Badre, D., & Ochsner, K. N. (2013). Distinct regions of prefrontal cortex are associated with the controlled retrieval and selection of social information. Cereb Cortex. doi: 10.1093/cercor/bhs408
Satpute, A. B., Badre, D., & Ochsner, K. N. (2012). The Neuroscience of Goal-Directed Behavior. In H. Aarts & A. Elliot (Eds.), Goal-directed Behavior (Frontiers of Social Psychology) (pp. 49-84). London, UK: Psychology Press.
Spunt, R. P., Satpute, A. B., & Lieberman, M. D. (2011). Identifying the what, why, and how of an observed action: an fMRI study of mentalizing and mechanizing during action observation. J Cogn Neurosci, 23(1), 63-74. doi: 10.1162/jocn.2010.21446
Rameson, L. T., Satpute, A. B., & Lieberman, M. D. (2010). The neural correlates of implicit and explicit self-relevant processing. Neuroimage, 50(2), 701-708. doi: 10.1016/j.neuroimage.2009.12.098
Satpute, A. B., & Lieberman, M. D. (2006). Integrating automatic and controlled processes into neurocognitive models of social cognition. Brain Res, 1079(1), 86-97. doi: 10.1016/j.brainres.2006.01.005
Lieberman, M. D., Jarcho, J. M., & Satpute, A. B. (2004). Evidence-based and intuition-based self-knowledge: an FMRI study. J Pers Soc Psychol, 87(4), 421-435. doi: 10.1037/0022-3514.87.4.421
4. Language, Concepts, and Emotion
Hegefeld, H. M., Satpute, A. B., Ochsner, K. N., Davidow, J. Y., & Nook, E. C. (2023). Fluency generating emotion words correlates with verbal measures but not emotion regulation, alexithymia, or depressive symptoms. Emotion.
Lindquist, K. A., Jackson, J. C., Leshin, J., Satpute, A. B., & Gendron, M. (2022). The cultural evolution of emotion. Nature Reviews Psychology, 1-13.
Lee, A. S., McVeigh, K., Garcia, M. S., Carrillo, V., Kim, J., & Satpute, A. B. (2024). Disentangling valence in emotion knowledge: The good, the pleasant, and the desirable. Emotion.
Lee, K. M., Lee, S., & Satpute, A. B. (2022). Sinful pleasures and pious woes? Using fMRI to examine evaluative and hedonic emotion knowledge. Social, Cognitive, and Affective Neuroscience.
Nook, E. C., Satpute, A. B., Ochsner, K. N. (2021). Emotion naming impedes emotion regulation. Affective Science, 2, 187-198.
Satpute, A. B., & Lindquist, K. A. (2021). At the neural intersection between language and emotion. Affective Science, 2, 207–220. DOI: 10.1007/s42761-021-00032-2
Satpute, A. B., & Lindquist, K. A. (2019) “The Default Mode Network’s Role in Discrete Emotion.” Trends in cognitive sciences.
Brooks JA, Shablack H, Gendron M, Satpute AB, Parrish MH, Lindquist KA (2017) The role of language in the experience and perception of emotion: a neuroimaging meta-analysis. Soc Cogn Affect Neurosci 12:169–183.
Satpute AB, Nook EC, Narayanan S, Shu J, Weber J, Ochsner KN (2016) Emotions in “Black and White” or Shades of Gray? How We Think About Emotion Shapes Our Perception and Neural Representation of Emotion. Psychol Sci 27:1428–1442.
Wager, T. D., Kang, J., Johnson, T. D., Nichols, T. E., Satpute, A. B., & Barrett, L. F. (2015). A Bayesian model of category-specific emotional brain responses. PLOS One: Computational Biology.
Lindquist, K., Satpute, A. B., Gendron, M. (2015). Does language do more than communicate emotion? Current Directions in Psychological Science
5. 7T fMRI and human brainstem nuclei
Fischbach, A. K., Satpute, A. B., Quigley, K., Kragel, P. A., Chen, D., Bianciardi, M., Wald, L. L., Wager, T. D., Choi, J.-K., Zhang, J., Barrett, L. F., & Theriault, J. E. (2024). 7-Tesla evidence for columnar and rostral–caudal organization of the human periaqueductal gray response in the absence of threat: a working memory study. Journal of Neuroscience.
Kragel, P. A., Bianciardi, M., Hartley, L., Matthewson, G., Choi, J. K., Quigley, K. S., Wald, L. L., Wager, T. D., Barrett, L. F., & Satpute, A. B. (2019). Functional involvement of human periaqueductal gray and other midbrain nuclei in cognitive control. Journal of Neuroscience, 2043-18.
Wang, Y.C., Bianciardi, M., Chanes, L., & Satpute, A. B. (2020). Ultra High Field fMRI of Human Superior Colliculi Activity during Affective Visual Processing. Scientific Reports 10:1331.
Satpute, A. B., Kragel, P. A., Barrett, L. F., Wager, T. D., & Bianciardi, M. (2018). Deconstructing arousal into wakeful, autonomic and affective varieties. Neuroscience Letters
Satpute A.B., Wager T.D., Cohen-Adad J., Bianciardi M., Choi J-K., Buhle J.T., Wald L.L., Barrett L.F. (2013) Identification of discrete functional subregions of the human periaqueductal gray. Proc Natl Acad Sci USA 110:17101–17106.
6. Large-scale networks
Ciric R, Nomi JS, Uddin LQ, Satpute AB (2017) Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks. Scientific Reports 7:6537.
Barrett, L. F., & Satpute, A. B. (2013). Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain. Curr Opin Neurobiol, 23, 361-372. doi: 10.1016/j.conb.2012.12.012
7. Bibliometrics and citation network analysis
Iancarelli, A., Denson, T. F., Chou, C. A., & Satpute, A. B. (2022). Using citation network analysis to enhance scholarship in psychological science: A case study of the human aggression literature. PloS one, 17(4), e0266513.