This paper addresses the issue of integrating top-down and bottom-up processing of information in modular hybrid systems. Backed by computational and neurological evidence, we show that there are important advantages to be gained from supporting bi-directional flow of information, especially in the context of intelligent information processing in real-world applications. We consider modular hyb...

We present a modelling framework for cortical processing aimed at understanding how, maintaining biological plausibility, neural network models can: (a) approximate general inference algorithms like belief propagation, combining bottom-up and top-down information, (b) solve Rosenblatt’s classical superposition problem, which we link to the binding problem, and (c) do so based on an unsupervised...

In response to Kobele et al. (2012), we evaluate four ways of linking the processing difficulty of sentences to the behavior of the top-down parser for Minimalist grammars developed in Stabler (2012). We investigate the predictions these four metrics make for a number of relative clause constructions, and we conclude that at this point, none of them capture the full range of attested patterns.

One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothes...

During tactile perception, long-range intracortical top-down axonal projections are essential for processing sensory information. Whether these projections regulate sleep-dependent long-term memory consolidation is unknown. We altered top-down inputs from higher-order cortex to sensory cortex during sleep and examined the consolidation of memories acquired earlier during awake texture perceptio...