Publications

Ramus, F. (2013). A neurological model of dyslexia and other domain-specific developmental disorders with an associated sensorimotor syndrome. (pp. 75-102). doi:10.4324/9780203774915

Ramus, F., Peperkamp, S., Christophe, A., Jacquemot, C., Kouider, S. & Dupoux, E. (2010). A Psycholinguistic Perspective on the Acquisition of Phonology. In C. Fougeron (Eds.), Laboratory Phonology (Vol. 10 ).De Gruyter Mouton

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

Pressnitzer, D., Agus, T., Kang, H. , Graves, J. & Andrillon, T. (2021). Apprentissage de motifs sonores. In S. Samson, B. Tillmann, C. Jourdan, V. Brun (Eds.), Audition et Cognition Montpellier: Sauramps Medical

Ramus, F. (2005). Aux origines cognitives, neurobiologiques et génétiques de la dyslexie. ANAE - Approche Neuropsychologique des Apprentissages chez l'Enfant, 17, 247-253

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Kouider, S. (2018). Devenir scientifique pour comprendre qui nous sommes. In Michel Dugnat (Eds.), Bébé attentif cherche adulte(s) attentionné(s) (pp. 45-48). Toulouse, France: ERES

Ramus, F. (2018). Do gifted people have a qualitatively different brain?,Les surdoués ont-ils un cerveau qualitativement différent ? ANAE - Approche Neuropsychologique des Apprentissages chez l'Enfant, 30(154), 281-287

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

Ramus, F., Di Folco , C. , Guez, A. & Peyre, H. (2021). Epidémiologie des troubles de la lecture en France : une comparaison du DSM-5 et de la CIM-11. Approche neuropsychologique des apprentissages chez l'enfant, 175, 639-649

Ramus, F. (2008). Génétique de la dyslexie développementale. ANAE - Approche Neuropsychologique des Apprentissages chez l'Enfant, 20, 9-14

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

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

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. Advances in Intelligent Systems and Computing (Vol. 1252, pp. 241-255). doi:10.1007/978-3-030-55190-2_19

Ramus, F. (2012). Les troubles spécifiques de la lecture. Information Grammaticale, 133, 34-40

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Ramus, F. (2011). Quel pouvoir prédictif de la génétique et des neurosciences, et quels problmes? Medecine et Droit, 2011(106), 51-58. doi:10.1016/j.meddro.2010.10.010

Varnet, L., Meunier, F. & Hoen, M. (2016). Speech reductions cause a de-weighting of secondary acoustic cues. In Interspeech. doi:10.21437/Interspeech.2016-343

Caze, R., Humphries, M. & Gutkin, B. (2012). Spiking and saturating dendrites differentially expand single neuron computation capacity. , Vol. 13: In Twenty First Annual Computational Neuroscience Meeting: CNS*2012, Decatur, GA, USA.

Shamma, S. (2020). Temporal Coherence Principle in Scene Analysis. The Senses: A Comprehensive Reference (Second Edition) (Vol. 2, pp. 777-790).Elsevier. doi:10.1016/B978-0-12-809324-5.24252-1

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

Ripley, D., Verheyen, S. & Egré, P. (2019). The Sorites Paradox in Psychology. In S. Oms and E. Zardini (Eds.), The Sorites Paradox (pp. 263-286). Cambridge: Cambridge University Press

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Ramus, F. & Szenkovits, G. (2011). Understanding the nature of the phonological deficit. (pp. 153-169). doi:10.4324/9780203838006