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22282415 1 apa 50 creator asc year 1 1 13 https://inctneurocomp.com/wp-content/plugins/zotpress/
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Abreu, E., Vazquez, P. F., & Castellano, G. (2026). Decoding inner speech with functional connectivity. Biomedical Physics & Engineering Express, 12(2), 025019. https://doi.org/10.1088/2057-1976/ae451b
Brandão, D. S., Scott, R. N. B., Soares, E. S., Mota, N. B., & Ribeiro, S. (2026). Dream content and slow waves benefit prey against predator in a video game confrontation. Scientific Reports, 16(1), 9331. https://doi.org/10.1038/s41598-026-42759-7
Bussotti Reyes, M., Da Rosa Ferreira, F., Gobbo, G., Salvador Caetano, M., & Machado, A. (2026). Evidence for timing in the midsession reversal task with rats. Journal of Experimental Psychology: Animal Learning and Cognition. https://doi.org/10.1037/xan0000442
Cambraia, E. B. S. A., Prado, T. L., Viana, R. L., & Lopes, S. R. (2026). Unstable dimension variability as a key dynamical factor shaping neural network synchronization mechanisms. Chaos, Solitons & Fractals, 209, 118540. https://doi.org/10.1016/j.chaos.2026.118540
Cambrainha, G. G., Castro, D. M., De Vasconcelos, N. A. P., Carelli, P. V., & Copelli, M. (2025). Criticality at Work: Scaling in the Mouse Cortex Enhances Performance. PRX Life, 3(3), 033026. https://doi.org/10.1103/w49n-2vz8
Castro, D. M., Raposo, E. P., Copelli, M., & Santos, F. A. N. (2025). Interdependent Scaling Exponents in the Human Brain. Physical Review Letters, 135(19), 198401. https://doi.org/10.1103/lvwj-hjr3
De Paula, E. V., Jungmann, R. M., Fontenele, A. J., Aguiar, L. A. A., Carelli, P. V., Matias, F. S., Copelli, M., & De Vasconcelos, N. A. P. (2026). Revealing Stimulus-Dependent Dynamics Through Statistical Complexity. PRX Life, 4(2), 023018. https://doi.org/10.1103/wndc-k654
Ferreira, G. V., Lopes Da Cruz, F. E., Marghoti, G., De Lima Prado, T., Lopes, S. R., Marwan, N., & Kurths, J. (2026). An optimized Python library for analyzing dynamical systems with recurrence microstates. The European Physical Journal Special Topics. https://doi.org/10.1140/epjs/s11734-026-02389-6
Moreira Maia, C., B. V. De Amorim, L., M. O. Cruz, R., & D. C. Cavalcanti, G. (2027). Multi-label Meta-learning for Pipeline Recommendation: The Importance of Pipeline Diversity. In M. Recamonde-Mendoza & R. C. Barros (Eds.), Intelligent Systems (Vol. 17107, pp. 248–262). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-39895-6_17
Nascimento, K. F. R., Castro, D. M., Cambrainha, G. G., & Copelli, M. (2026). Phenomenological renormalization group in neuronal models near criticality. Physical Review E, 114(1), 014310. https://doi.org/10.1103/3lsz-87dd
Ohno Bezerra, T., & C. Roque, A. (2026). Context-Dependent modulation of astrocytic Ca2+ signals by mitochondria: a computational study. Journal of Computational Neuroscience. https://doi.org/10.1007/s10827-026-00956-3
Patroclo, C. B., Ramalho, B. L., Maia, J. S., Torres, F. F., Braghetto, K. R., & Vargas, C. D. (2026). A public database on traumatic brachial plexus injury: data collection and sharing. BMC Research Notes, 19(1), 263. https://doi.org/10.1186/s13104-026-07780-z
Prado, T. L., Santos-Silva, R. J., Spezzatto, G. S., Milani, L. C., Da Cruz, F. E. L., & Lopes, S. R. (2026). Using recurrence microstates to improve learning of multi-layer perceptrons. The European Physical Journal Special Topics. https://doi.org/10.1140/epjs/s11734-026-02256-4
Prado, T. L., Santos-Silva, R. J., Marghoti, G., Lopes, S. R., & Sanjuán, M. A. F. (2026). Time localized trigger for phase synchronization transition in complex neuronal networks. Communications in Nonlinear Science and Numerical Simulation, 162, 110381. https://doi.org/10.1016/j.cnsns.2026.110381
Prodocimo Lopes, G., Da Silveira, R. V., Idalgo Carnielli, I. C., & Castellano, G. (2026). Comparison between healthy young and elderly individuals using MRI texture analysis. Revista Brasileira de Física Médica, 20, 888. https://doi.org/10.29384/rbfm.2026.v20.19849001888
Santos Bonadia, M., Da Silveira, R. V., & Castellano, G. (2026). MRI texture changes in young adults undergoing a moderate-intensity running training program. Revista Brasileira de Física Médica, 20, 894. https://doi.org/10.29384/rbfm.2026.v20.19849001894
Schmaedeke, A. C., Erthal, F. S., Vargas, C. D., & Ramalho, B. L. (2026). Somatosensory Misalignment: Persistent Referred Sensation After Intercostal‐to‐Musculocutaneous Nerve Transfer. Neural Plasticity, 2026(1), 3079894. https://doi.org/10.1155/np/3079894
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