Solutions to the binding problem: progress through controversy and convergence.
By Anne Treisman. 1999
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- J. Urgen Schmidhuber
- Sjoerd van Steenkiste
- Klaus Greff
- Yoshua Bengio
- Sergey Levine
- Bo Li
- Quoc V. Le
- Mohit Bansal
Citations in the corpus
- On the Binding Problem in Artificial Neural Networks (2020, methodology): “Inspired by Treisman (1999), we organize our analysis along a functional division into three aspects pertaining to the role of binding for symbolic information processing in neural networks: 1) representation, 2) segregation, and 3) composition, each of which takes a different perspective on the…”
- Arousal-biased competition in perception and memory (2011, unknown): “Mather’s (2007) object-based framework proposed that arousal-enhanced memory binding for within-object features occurs because (a) as outlined by Treisman (1999), perceptually binding features such as color and location to an object requires focused attention; (b) emotionally arousing stimuli…”
- A Perspective on Objects and Systematic Generalization in Model-Based RL (2019, methodology): “Inspired by this literature (cf. Treisman (1999); von der Malsburg (1995)) we will focus on three main challenges in incorporating objects in connectionist models of the world: segregation, representation, and composing, which we discuss in the next sections.”
- The time dimension for scene analysis (2005, background): “way to prevent selective attention to individual stimuli [126],”
- Odor/taste integration and the perception of flavor (2005, result): “These data are therefore analogous to those showing the role of focused attention in binding visual features to form recognizable objects (Treisman 1999).”
- Binding in short-term visual memory. (2002, methodology): “In a pilot study performed in our lab (Wheeler & Treisman, 1999), we presented participants with squares divided into two differently colored halves.”
- On Ideal Binary Mask As the Computational Goal of Auditory Scene Analysis (2005, background): “A deeper issue with recognition as the goal is that perceiving is more than recognizing (Treisman, 1999).”
- Dynamic coordination in the brain : from neurons to mind (2010, background): “19 attention (Duncan 2006), and their more recent formulation as normalisation models (Reynolds and Heeger 2009), but how can that support be clarified and strengthened? Are competitions resolved by a single central executive controller, or locally as suggested by independence of their resolution ac”
- Distributed processing and temporal codes in neuronal networks (2009, background): “Psychophysical and electrophysiological evidence indicates that attentional mechanisms play an important role in grouping operations both at the level where scene segmentation is accomplished as well as at the higher levels where object identification is thought to occur (Treisman 1999).”
- Synchronization and pattern separation in spiking associative memories and visual cortical areas (2004, background): “, [154, 188, 191, 192, 51, 165, 150, 193, 168, 199, 187, 194, 148, 56, 163, 167, 59, 147, 205]) actually corresponds to a whole family of related problems.”
- Binding via Reconstruction Clustering (2015, background): “The binding problem and its possible solutions are a long standing debate in the neuroscience literature (see e.g. Milner (1974); von der Malsburg (1981); Gray (1999); Treisman (1999); Di Lollo (2012)).”