The experiment is fascinating. It looks like they developed a model (DORA) for learning relational reasoning. It turns out that model showed similar oscillatory

The experiment is fascinating. It looks like they developed a model (DORA) for learning relational reasoning. It turns out that model showed similar oscillatory activation patterns to observed cortical signals. As a comparison, they also looked at a fully connected RNN with a which did not produce oscillations. So the key research finding is that time-binding is a requisite to produce oscillations in neural networks. The paper's conclusions: "In sum, we remain relatively agnostic about the specific details of the required representational hierarchy because we do not yet know how to link the predicate calculus representations we use to natural language mental and cortical representations. What we are not agnostic about is the need for asynchronous time-based binding in order to produce oscillations in a neural network, as well as the need for representational hierarchy to produce the particular pattern of oscillations observed here and in" The paper on evaluating if NLP parsers with representational hierarchies reflect what the cortical functionality: "Our results naturally beg the converse question, as to whether any system with representational hierarchy could produce the oscillatory pattern of activation that [6] and DORA show. For example, could natural language processing (NLP) parsers, which feature representational hierarchy and were developed to specifically parse natural language in a machine, produce oscillations and the pattern seen in [6] and in our simulations? In principle, any system of hierarchy that is (de)compositional has the representational ingredients to encode units that could be fired in a sequence. However, we would argue that any given representational hierarchy could only produce oscillations if it were combined with time-based binding, which, as far as we know, no NLP system features. In DORA, time-based binding is the oscillation of activity throughout the network, which is part of the reason why the RNN did not show oscillatory activity nor the specific pattern from [6]. The representational structure of DORA (a (de)compositional role-filler binding predicate logic) is what makes the oscillations take the form that the data from [6] have. In terms of the specifics of the observed 1-2-4 Hz pattern, both [6] and our simulations are highly shaped by the word presentation rate of 250 ms/4 Hz. But without time-based binding, there is no mechanism to produce oscillations in a network, even in a NLP parser or other system with representational hierarchy."