Publications

Schaffer, E., Ostojic, S. & Abbott, L. (2013). A complex-valued firing-rate model that approximates the dynamics of spiking networks. PLoS computational biology, 9(10), e1003301. doi:10.1371/journal.pcbi.1003301

Mastrogiuseppe, F. & Ostojic, S. (2019). A geometrical description of global dynamics in trained feedback networks. Neural Computation, 31(6), 1139-1182. doi:10.1162/neco_a_01187

Barbosa, J., Stein, H., Zorowitz, S. , Niv, Y. , Summerfield, C., Soto-Faraco, S. & Hyafil, A. (2022). A practical guide for studying human behavior in the lab. Behavior Research Methods. doi:10.3758/s13428-022-01793-9

Saez, A., Rigotti, M., Ostojic, S., Fusi, S. & Salzman, C. (2015). Abstract Context Representations in Primate Amygdala and Prefrontal Cortex. Neuron, 87(4), 869-81. doi:10.1016/j.neuron.2015.07.024

Barbosa, J., Babushkin, V. , Temudo, A. , Sreenivasan, K. & Compte, A. (2021). Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory. Front. Neural Circuits. doi:10.3389/fncir.2021.716965

Claidière, N., Trouche, E. & Mercier, H. (2017). Argumentation and the diffusion of counter-intuitive beliefs. Journal of experimental psychology. General, 146(7), 1052-1066. doi:10.1037/xge0000323

V Kuchibhotla, K. , Hindmarsh Sten, T., C. Papadoyannis, E. , Elnozahy, S. , Fogelson, K. , Chillale, R. , Boubenec, Y., C. Holland, P. , Ostojic, S. & C. Froemke, R. (2020). Author Correction: Dissociating task acquisition from expression during learning reveals latent knowledge. Nat Commun, 11(3176). doi:10.1038/s41467-020-17023-9

Kriegel, U. (2018). Brentano’s Dual-Framing Theory of Consciousness. Philosophy and Phenomenological Research, 97(1), 79-98. doi:10.1111/phpr.12327

Kriegel, U. (2017). Brentano’s Evaluative-Attitudinal Account of Will and Emotion. Revue Philosophique de la France Et de l'Etranger , 142(4), 529-558

Ostojic, S., Panja, D. & Nienhuis, B. (2004). Clustering in a one-dimensional inelastic lattice gas. Physical Review E, 69(4 Pt 1), 041301. doi:10.1103/PhysRevE.69.041301

Bondanelli, G. & Ostojic, S. (2020). Coding with transient trajectories in recurrent neural networks. PLoS Computational Biology, 16 (2), e1007655. doi:10.1371/journal.pcbi.1007655

Dokic, J. (2018). Comments on “Postures of listening” by Victor A. Stoichita and Bernd Brabec de Mori. Terrain. Anthropologie et sciences humaines

Giustina, A. (2017). Conscious Unity From the Top Down: A Brentanian Approach. The Monist, 100(1 ), 16–37

Beiran, M. & Ostojic, S. (2019). Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks . PLoS Computational Biology, 15(3), e1006893. doi:10.1371/journal.pcbi.1006893

Oswald, A. & Ostojic, S. (2020). Curating more diverse scientific conferences. Nat Rev Neurosci, 21, 589-590. doi:10.1038/s41583-020-0373-4

Kriegel, U. (2019). Dignāga’s Argument for the Awareness Principle: An Analytic Refinement. Philosophy East & West , 69, 144-156

V Kuchibhotla, K. , Hindmarsh Sten, T., C. Papadoyannis, E. , Elnozahy, S. , Fogelson, K. , Chillale, R. , Boubenec, Y., C. Holland, P. , Ostojic, S. & C. Froemke, R. (2019). Dissociating task acquisition from expression during learning reveals latent knowledge. Nature Communications, 10, 2151. doi:10.1038/s41467-019-10089-0

Kuchibhotla, K., Hindmarsh Sten, T., Papadoyannis, E., Elnozahy, S. , Fogelson, K. , Kumar, R., Boubenec, Y., Holland, P., Ostojic, S. & Froemke, R. (2020). Dissociating task acquisition from expression during learning reveals latent knowledge. Nature communications, 10(1), 2151. doi:10.1038/s41467-019-10089-0

K Chillale, R., Shamma, S., Ostojic, S. & Boubenec, Y. (2023). Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement. eLife, 12(e85706). doi:10.7554/eLife.85706

Schuessler, F. , Dubreuil, A., Mastrogiuseppe, F., Ostojic, S. & Barak, O. (2020). Dynamics of random recurrent networks with correlated low-rank structure. Phys. Rev. Research, 2(1), 013111. doi:10.1103/PhysRevResearch.2.013111

Ostojic, S. & Panja, D. (2006). Elasticity from the force network ensemble in granular media. Physical Review Letters, 97(20), 208001. doi:10.1103/PhysRevLett.97.208001

Kovarski, K., Mennella, R., Wong, S., Dunkley, B., Taylor, M. & Batty, M. (2019). Enhanced Early Visual Responses During Implicit Emotional Faces Processing in Autism Spectrum Disorder. Journal of autism and developmental disorders, 49(3), 871-886. doi:10.1007/s10803-018-3787-3

Giustina, A. & Kriegel, U. (2017). Fact-Introspection, Thing-Introspection, and Inner Awareness. Review of Philosophy and Psychology, 8(1 ), 143–164

Ostojic, S. & Brunel, N. (2011). From spiking neuron models to linear-nonlinear models. PLoS Computational Biology, 7(1), e1001056. doi:10.1371/journal.pcbi.1001056

Cimesa, L., Ciric, L. & Ostojic, S. (2023). Geometry of population activity in spiking networks with low-rank structure. PLoS computational biology, 19(8), e1011315. doi:10.1371/journal.pcbi.1011315

Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Boubenec, Y. & Ostojic, S. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Communications, 9, 2529 . doi:10.1038/s41467-018-04839-9

Udden, J. , Martins, M. , Zuidema, W. & Tecumseh Fitch, W. (2019). Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation. Topics in Cognitive Science . doi:10.1111/tops.12442

Ostojic, S., Brunel, N. & Hakim, V. (2009). How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains. The Journal of Neuroscience, 29(33), 10234-53. doi:10.1523/JNEUROSCI.1275-09.2009

Bernard, A., Bredeche, N. & Andre, J. (2020). Indirect genetic effects allow escape from the inefficient equilibrium in a coordination game. Evolution Letters, 4(3), 257-265. doi:10.1002/evl3.155

Ladenbauer, J., McKenzie , S., English , D., Hagens , O. & Ostojic, S. (2019). Inferring and validating mechanistic models of neural microcircuits based on spike-train data. Nature Communications, 10(4933). doi:10.1038/s41467-019-12572-0