This paper sets forward a novel theory of temporal binding, a mechanism that integrates the temporal properties of sensory features into coherent perceptual experiences. Specifying a theory of temporal binding remains a widespread problem. The popular ‘brain time theory’ suggests that the temporal content of perceptual experiences is determined by when sensory features complete processing. However, this theory struggles to explain how perceptual experiences can accurately reflect the relative timing of sensory features processed at discrepant times. In contrast, ‘event time (...) theories’ suggest that the temporal content of perceptual experiences reflects the relative event time of external sensory features and that the brain accommodates differential processing times. We can formulate retrodictive and predictive versions of this theory. Retrodictive event time theories propose that we accommodate desynchronised processing retrodictively. Predictive event time theories propose that we accommodate desynchronised processing by predictively modelling the event time of sensory features. I argue that both views have strengths and weaknesses. This paper proposes a new hybrid theory that integrates these theories to accommodate these weaknesses. Firstly, I argue how retrodictions and predictions can interact in mutually beneficial ways to ensure speedy and accurate temporal binding. Secondly, I propose how attention plays a central role in flexibly selecting which contents get to be temporally bound. This theory can explain how prediction and retrodiction differentially affect temporal binding and, in turn, proposes a new way to understand temporal binding and has implications for how we should understand conscious experiences. (shrink)

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory, as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed—a motor command. This paper aims (...) to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference—behavioral modeling frameworks that descend, but are distinct, from OMCT—and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference. (shrink)

Volume 2, Issue 2, June 2018, Page 234-245.