Publications

Caucheteux, C. , Gramfort, A. & King, J. (2022). Deep language algorithms predict semantic comprehension from brain activity. , 1é(16327). doi:10.1038/s41598-022-20460-9

Garcia, B., Cerrotti, F. & Palminteri, S. (2021). The description–experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Phil. Trans. R. Soc. B, 376, 20190665. doi:10.1098/rstb.2019.0665

Vandendriessche, H., Demmou, A. , Bavard, S., Yadak, J. , Lemogne, C. , Mauras, T. & Palminteri, S. (2022). Contextual influence of reinforcement learning performance of depression: evidence for a negativity bias? Psychological Medicine, ., 1-11. doi:10.1017/S0033291722001593

Bavard, S. & Palminteri, S. (2021). Why unchosen options linger in our minds. Communications Biology , 4, 1271. doi:10.1038/s42003-021-02803-w

Anlló, H., Katsumi, W., Sackur, J. & de Gardelle, V. (2022). Effects of false statements on visual perception hinge on social suggestibility. J Exp Psychol Hum Percept Perform, 48(8), 889–900. doi:10.1037/xhp0001024

Lussange, J., Vrizzi, S., Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2022). Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model. Comput Econ. doi:10.1007/s10614-022-10249-3

Jurado, C., Chow, P., Leung, L., Larrea, M., Vizuete, J., de Cheveigné, A. & Marquart, T. (2022). The Spectral Extent of Phasic Suppression of Loudness and Distortion-Product Otoacoustic Emissions by Infrasound and Low-Frequency Tones. Journal of the Association for Research in Otolaryngology (JARO), 23(2), 167-181. doi:10.1007/s10162-021-00830-2

Casati, R. (2021). Drawing problems: thought in action. Adaptive Behavior, 29(5), 441-448. doi:10.1177/1059712319861551

Cavanagh, P., Casati, R. & Elder , J. (2022). Scaling depth from shadow offset. Journal of Vision, 21(12), 15. doi:10.1167/jov.21.12.15

Casati, R. (2021). Im Moment des Schattens. Liddy Scheffknecht – Points in Time,De Gruyter,. doi:10.1515/9783110769562-005

Casati, R. (2021). Shadows in the Moment. Liddy Scheffknecht – Points in Time (pp. 161-164).De Gruyter. doi:10.1515/9783110769562-010

Casati, R. (2022). The Sailing Mind. Springer Nature. doi:10.1007/978-3-030-89639-3

Casati, R., Kulvicki, J. & Zeimbekis, J. (2022). Borgesian Maps . Analytic Philosophy, 63(2), 90–98. doi:10.1111/phib.12204

Arcangeli, M. & Dokic, J. (2021). At the Limits: What Drives Experiences of the Sublime. British Journal of Aesthetics, 61(2), 145-161. doi:10.1093/aesthj/ayaa030

Arcangeli, M. (2021). The conceptual nature of imaginative content. Synthese, 199(1-2), 3189-3205. doi:10.1007/s11229-020-02930-7

Atkinson-Clement, C. , Maël, L., Patsalides, L. , De Liege, A. , Klein, Y. , Roze, E. , Deniau, E. , Andreas, H., Palminteri, S. & Yulia, W. (2022). Decision-making under risk and ambiguity in adults with Tourette syndrome. Psychological Medicine, 1-11. doi:10.1017/S0033291722002318

Grinfeder, E., Lorenzi, C., Haupert, S. & Sueur, J. (2022). What Do We Mean by “Soundscape”? A Functional Description. Front. Ecol. Evol, 10, 894232. doi:10.3389/fevo.2022.894232

Li, K., Rajendran, V., Mishra, A. , Chan, C. & Schnupp, J. (2021). Interaural time difference tuning in the rat inferior colliculus is predictive of behavioral sensitivity. Hearing Research, 409, 108331. doi:10.1016/j.heares.2021.108331

Di Liberto, G., Hjortkjær, J. & Nima, M. (2022). Neural Tracking: Closing the Gap Between Neurophysiology and Translational Medicine. Front. Neurosci. doi:10.3389/fnins.2022.872600

Attaheri, A. , Choisdealbha, Á. , Di Liberto, G., Rocha, S. , Brusini, P. , Mead, N. , Olawole-Scott, H. , Boutris, P., Gibbon, S. , Williams, I. , Grey, C. , Flanagan, S. & Goswami, U. (2022). Delta- and theta-band cortical tracking and phase-amplitude coupling to sung speech by infants. NeuroImage, 247, 118698. doi:10.1016/j.neuroimage.2021.118698

Osses , A. , Varnet, L., Carney, L. , Dau, T. , Bruce, I. , Verhulst, S. & Majdak, P. (2022). A comparative study of eight human auditory models of monaural processing. Acta Acustica, 6(17), 24. doi:10.1051/aacus/2022008

M Siriwardena, Y., Marion, G. & Shamma, S. (2022). The Mirrornet: Learning Audio Synthesizer Controls Inspired by Sensorimotor Interaction. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 946-950. doi:10.1109/ICASSP43922.2022.9747358

Parikh, R. , Kavalerov, I. , Espy-Wilson, C. & Shamma, S. (2022). Harmonicity Plays a Critical Role in DNN Based Versus in Biologically-Inspired Monaural Speech Segregation Systems. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 536-540. doi:10.1109/ICASSP43922.2022.9747314

Agus, T. & Pressnitzer, D. (2021). Repetition detection and rapid auditory learning for stochastic tone clouds. The Journal of the Acoustical Society of America, 150, 1735. doi:10.1121/10.0005935

Graves, J., Egré, P., Pressnitzer, D. & de Gardelle, V. (2021). An implicit representation of stimulus ambiguity in pupil size. , Vol. 18: In Proceedings of the National Academy of Sciences, e2107997118. doi:10.1073/pnas.2107997118

Berthommier, F. & Lorenzi, C. (2021). Implications of Physiological Mechanisms of Amplitude Modulation Processing for Modeling Complex Sounds Analysis and Separation. (pp. 12). doi:10.1201/9781003064183

Varnet, L. & Lorenzi, C. (2022). Probing temporal modulation detection in white noise using intrinsic envelope fluctuations: A reverse-correlation study. Journal of the Acoustical Society of America, 151(2), 1353-1366. doi:10.1121/10.0009629

Caucheteux, C. & King, J. (2022). Brains and algorithms partially converge in natural language processing. Nature Communications Biology , 5, 134. doi:10.1038/s42003-022-03036-1

Lemi, L. , Gwilliams, L., Samaha, J., Auksztulewicz, R., M Cycowicz, Y. , King, J. , Nikulin, V., Thesen, T. , Doyle, W. , Devinsky, O. , E Schroeder, C. , Melloni, L. & Haegens, S. (2022). Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability. NeuroImage , 247, 118746. doi:10.1016/j.neuroimage.2021.118746

Palminteri, S. & Maël, L. (2022). The computational roots of positivity and confirmation biases in reinforcement-learning. Trends in Cognitive Sciences, 26(7), 607-621. doi:10.1016/j.tics.2022.04.005