This is the list of article you can choose from. You also can present any other paper, just tell us in advance what paper it is, so that we can check it suits well.
- TAKEN Miller & Cohen, 2001 An Integrative Theory on Prefrontal Cortex Function, an easy to read and follow review about the prefrontal cortex. Important, because PFC is what makes us human, several diseases are related to PFC malfunction, and there are many computational models that try to capture this. (Cognitive science, neuroscience)
- TAKEN Clark, 2013, Whatever next? Predictive brains, situated agents, and the future of cognitive science, smoothly written overview about how brains predict future. No differential equations. A good paper about predictive coding. (Cognitive science, neuroscience)
- Desimone & Duncan, 1995, Neural Mechanisms of Selective Visual Attention, review that has influenced the systems neuroscience community. Here they clearly explain the biased competition idea and lay the foundation for understanding how attention works in the brain (Cognitive science, neuroscience).
- McClelland et al., 1995, Why There Are Complementary Learning Systems in the Hippocampus and Neocortex: Insights From the Successes and Failures of Connectionist Models of Learning and Memory, a classic paper about the dual process approach to memory (hippocampus, cortex, their different computations and different time-courses for memory processing). Is a bit more complex and maybe not so easy to read but it is one of the foundations for current neuroscientific and computational thinking about memory (Cognitive science, neuroscience, computational neuroscience).
- Olshausen & Field, 2005, How Close Are We to Understanding V1?, Primary visual cortex (V1) is the mostly studied and understood brain area. This paper shows the gaps in our understanding of V1. One of the best critical papers on neuroscience. (Neuroscience)
- TAKEN Tononi & Cirelli, 2006, Sleep function and synaptic homeostasis, well readable, tries to answer one of the sweetest questions in biology - what's the function of sleep? Nice paper, a good read. (Neuroscience)
- Di Carlo et al., 2012, How Does the Brain Solve Visual Object Recognition? this review merges many (new) computational ideas about vision. A bit technical! (Neuroscience, computational neuroscience)
- Quiroga et al. 2005, Invariant visual representation by single neurons in the human brain. An experimental paper showing that individual neurons in hippocampus respond to abstract concepts (for example neurons selectively respond to the concept of Halle Berry). Try to make computer vision systems of today to do similar things! (Neuroscience)
- Nirenberg et al., 2009, Ruling out and ruling in neural codes, Also an experimental paper, where the group of Nirenberg studies the neural code with a very clever method - they measure all the input the brain gets from the retina and then use different codes for decoding, which are all compared to the behavior of the animal. They can for example show that at this stage, on retina, the rate code cannot work - it performs much worse than the animal. Easy to understand, great paper. (Computational neuroscience)
- Eliasmith et al., 2012 A large-scale model of the functioning brain, nice paper showing the emergence of human-like cognitive functions in a computational model of the brain. (Computational neuroscience)
- TAKEN Shadlen & Gold, 2007, The Neural Basis of Decision Making, a review about decision making based on findings from single cell recordings in monkey. (Neuroscience)
- Körding & Wolpert, 2004, Bayesian Integration in Sensorimotor Learning, empirical paper showing how people do implicitly Bayesian statistics by movement control. (Computational neuroscience)
- Berkes et al., 2011 - Spontaneous Cortical Activity Reveals Hallmarks of an Optimal Internal Model of the Environment, empirical paper showing that spontaneous activity of the visual cortex might reflect the internal model of the environment. (Neuroscience)
- Wei Ji Ma, 2012, Organizing probabilistic models of perception, overview paper which clarifies many misconceptions about Bayesian inference in systems neuroscience (Cognitive neuroscience)
- TAKEN Soon et al., 2008, Unconscious determinants of free decisions in the human brain, empirical paper that uses machine learning and fMRI to show that it is possible to predict the free choices from brain activity 10 seconds before subjects become aware of their choices. (Cognitive neuroscience, computational neuroscience)
- TAKEN Buanomano and Maass, 2009, State-dependent computations: spatiotemporal processing in cortical networks, overview paper on a new approach for neural computations beyond the attractor-based framework. Liquid state machines are shown to outperform many machine learning algorithms. (Computational neuroscience)
- Gerstner et al, 1996, A neuronal learning rule for sub-millisecond temporal coding, modeling paper that anticipated the spike-timing dependent rule of neuronal plasticity. (Computational neuroscience)