Introducción a la Neurociencia Computacional y Teórica

Bibliografía

• Strogatz, S. H. (2018). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (2nd ed.). CRC Press.
• Izhikevich, E. M. (2004). Which Model to Use for Cortical Spiking Neurons? IEEE Transactions on Neural Networks, 15(5), 1063–1070.
• Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning. MIT Press.
• Nielsen, M. A. (2015). Neural Networks and Deep Learning. Determination Press.
• Seth, A. K. (2021). Being You: A New Science of Consciousness. Faber & Faber.
• Rolls, E. T. (2014). Emotion and Decision-Making Explained. Oxford University Press.
• Pessoa, L. (2022). The Entangled Brain: How Perception, Cognition, and Emotion Are Woven Together. MIT Press.
• Sejnowski, T. J. (2020). The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence. Proceedings of the National Academy of Sciences, 117(48), 30033–30038.
• Dayan, P., & Abbott, L. F. (2001). Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press.