Rather than a natural product, a computational analysis leads us to characterize déjà vu as a failure of memory retrieval, linked to the activation in neocortex of familiar items from a compositional memory in the absence of hippocampal input, and to a misappropriation by the self of what is of others.

To fully embrace situations of radical uncertainty, we argue that the theory should abandon the requirements that narratives, in general, must lead toaffective evaluation, and that they have toexplain(and potentiallysimulate) all or even the bulk of the current decisional context. Evidence from studies of incidental learning show that narrative schemata can bias decisions while remaining fragmentary, insufficient for prediction, and devoid of utility values.

The target article demonstrates how neurocognitive modellers should not be intimidated by challenges such as Jackendoff's and should explore neurally plausible implementations of linguistic constructs. The next step is to take seriously insights offlered by neuroscience, including the robustness allowed by analogue computation with distributed representations and the power of attractor dynamics in turning analogue into nearly discrete operations.

The parallel distributed processing (PDP) perspective brings forward the important point that all semantic phenomena are based on analog underlying mechanisms, involving the weighted summation of multiple inputs by individual neurons. It falls short of indicating, however, how the essentially discrete nature of semantic processing may emerge at the cognitive level. Bridging this gap probably requires attractor networks.

Striedter's book offers precious insight into the comparative neuroanatomy of vertebrate brains, but it stops short of addressing what their evolution is all about: how effectively neural networks process information important for survival. To understand the principles of brain evolution, neuroanatomy needs to be combined not only with genetics, neurophysiology, and ethology, but also with quantitative network analyses.

We show that, given extensive exploration of a three-dimensional volume, grid units can form with the approximate periodicity of a face-centered cubic crystal, as the spontaneous product of a self-organizing process at the single unit level, driven solely by firing rate adaptation.

Where the isocortex comes from is an important question, but even more important is understanding what it leads to – that is, what advantage is afforded by its peculiar organization in layers of distinct neuronal types. A computational hypothesis accounts for granulation and for the differentiation between supra- and infragranular pyramidal layers, as quantitatively advantageous to support fine topography in sensory maps.

What exactly is going on via fornical connections? Aggleton & Brown's target article correctly stresses their importance, but a detailed understanding of their role in memory appears to require fresh research approaches.

A series of intriguing experiments has emphasized the need to understand synchronization effects. Information theory is proving to be an important tool for understanding the computations performed by cortical circuits. Nevertheless, Phillips & Singer's target article fails to provide a convincing correlation between synchronous firing and information transmission, which could well prove to be anticorrelated.