Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations.

By Martin A. Giese, Giacomo Rizzolatti. 2015

81 citations recorded by the source corpus.

Action recognition has received enormous interest in the field of neuroscience over the last two decades. In spite of this interest, the knowledge in terms of fundamental neural mechanisms that provide constraints for underlying computations remains rather limited. This fact stands in contrast with a wide variety of speculative theories about how action recognition might work. This review focuses on new fundamental electrophysiological results in monkeys, which provide constraints for the detailed underlying computations. In addition, we review models for action recognition and processing that have concrete mathematical implementations, as opposed to conceptual models. We think that only such implemented models can be meaningfully linked quantitatively to physiological data and have a potential to narrow down the many possible computational explanations for action recognition. In addition, only concrete implementations allow judging whether postulated computational concepts have a feasible implementation in terms of realistic neural circuits.

Subfields: Cognitive Neuroscience, Social Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. German Ignacio Parisi
2. Stefan Wermter
3. Cornelius Weber
4. Jun Tani

In Social Psychology

1. German Ignacio Parisi
2. Stefan Wermter
3. Jun Tani
4. Cornelius Weber

Citations in the corpus

• Lifelong learning of human actions with deep neural network self-organization (2017, background): “terns of form and motion features with increasing complexity of representation (Giese and Rizzolatti, 2015).”