Temporal cortex neurons encode articulated actions as slow sequences of integrated poses

By Jedediah M. Singer, David L. Sheinberg. 2010

74 citations recorded by the source corpus.

Form and motion processing pathways of the primate visual system are known to be interconnected, but there has been surprisingly little investigation of how they interact at the cellular level. Here we explore this issue with a series of three electrophysiology experiments designed to reveal the sources of action selectivity in monkey temporal cortex neurons. Monkeys discriminated between actions performed by complex, richly textured, rendered bipedal figures and hands. The firing patterns of neurons contained enough information to discriminate the identity of the character, the action performed, and the particular conjunction of action and character. This suggests convergence of motion and form information within single cells. Form and motion information in isolation were both sufficient to drive action discrimination within these neurons, but removing form information caused a greater disruption to the original response. Finally, we investigated the temporal window across which visual information is integrated into a single pose (or, equivalently, the timing with which poses are differentiated). Temporal cortex neurons under normal conditions represent actions as sequences of poses integrated over ∼120 ms. They receive both motion and form information, however, and can use either if the other is absent.

Subfields: Cognitive Neuroscience, Social Psychology

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Citations in the corpus

A self-organizing neural network architecture for learning human-object interactions (2017, methodology): “ encodings through the snapshot neurons found in the STS area of the brain [10]. There is also neurophysiological evidence that actions are represented by sequences of poses over xed temporal windows [58]. From the computational perspective, the sliding window technique allows for the extrapolation ”
Self-organizing neural integration of pose-motion features for human action recognition (2015, methodology): “This scheme is in accordance with neurophysiological evidence that actions are represented by sequences of integrated poses over ﬁxed windows of around 120 ms (Singer et al., 2010).”
Physiologically Inspired Model for the Visual Recognition of Transitive Hand Actions (2013, unknown): “Suchtemporalsequenceselectivityiscompatible with neural data, e.g., from the superior temporal sulcus (Jellema and Perrett, 2003; Vangeneugden et al., 2009; Singer and Sheinberg, 2010), and it can be accounted for by recurrent connections between shape-selective neurons (Giese and Poggio, 2003).”
Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations. (2015, background): “In addition, individual neurons can show different degrees of invariance with respect to these parameters (see also Singer and Sheinberg, 2010).”