650 Biological Cybernetics (2021) 115:643-653 0 2 4 6 8 10 12 14 16 18 20 Time (sec)00. 050. 10. 150. 20. 250. 30. 350. 40. 450. 5Response Fig. 5 Example of binocular rivalry generated by the Wilson-Cowan model with adaptation. Following a brief transient, a limit cycle resultswith left monocular activity (red) alternating with right monocular activ-ity (blue) about once every two seconds. Model responses are in unitsof relative contrast. The stochastic component has been omitted here to emphasize the limit cycle produced by H current adaptation and recip-rocal inhibition showed that, with appropriate parameters, local oscillations would lead to travelling waves and then to synchronous sus-tained activity. The results were comparable to data recordedfrom cortical surface electrodes during passage of epileptic seizures. The explanations of cortical travelling waves in focal epilepsy have also led to a suggested modiﬁcation of the Wilson-Cowan equations. To describe an epileptiform cortex, an effect was incorporated that does not occurunder healthy physiological conditions. The Hodgkin-Hux-ley equations show that if extracellular K +builds up in the extracellular space too much, there is a bifurcation in whichall spiking vanishes. This was simulated in Wilson-Cowanby replacing the sigmoid function in Eq. ( 3) by a Gaussian so that excessive activity could actually drive the ﬁring rate down to zero. Introduction of this physiologically importantclinical observation produced an accurate simulation of focal epilepsy and its spread (Meijer et al. 2015 ). 7 Decisions Contemporary philosophy of mind has been strongly inﬂu-enced by neuroscience. For example, Dennett ( 1996 ) has proposed that conscious decisions are the result of compe-tition among a range of possibilities. Similarly, Dehaene, aneuroscientist who has studied brain function in domains such a mathematics (Dehaene 1997 ), argued in a recent book on consciousness (Dehaene 2014 ): “Rivalry is, indeed, an apt metaphor for the constant ﬁght for conscious access. ” These opinions suggest that decision making by the brain might be usefully interpreted as a form of generalized rivalry amongcompeting neural representations reﬂecting ideas based on past memories. A candidate network for decisions, presumably mimick-ing areas in the prefrontal lobe, has been proposed related to the Wilson-Cowan network for rivalry (Wilson 2009 ; Wil-son2013 ). It can be argued that decisions among alternative interpretations or courses of action require reﬂection andthe expenditure of neural energy in the cases where there is almost equal evidence in favour of several alternative courses of action. In this instance one typically considers each alter-native in turn, seeking new evidence for or against it, and ultimately deciding on one alternative. The small network in Fig. 6can be used to illustrate this. Imagine that each column of neural populations represents a category, perhaps the ﬁrst as subject, second as verb, and so forth. The neural populations in each row are the particular possibilities foreach category, such as I, you, he/she for subject; came, went,gave for verb, etc. Then a particular idea or possibility would be represented by a learned pattern association including one member of each column. With correlation learning (Hopﬁeld 123