Representing multiple objects as an ensemble enhances visual cognition

Abstract

The visual system can only accurately represent a handful of objects at once. How do we cope with this severe capacity limitation? One possibility is to use selective attention to process only the most relevant incoming information. A complementary strategy is to represent sets of objects as a group or ensemble (e.g. represent the average size of items). Recent studies have established that the visual system computes accurate ensemble representations across a variety of feature domains and current research aims to determine how these representations are computed, why they are computed and where they are coded in the brain. Ensemble representations enhance visual cognition in many ways, making ensemble coding a crucial mechanism for coping with the limitations on visual processing.

Social norm perception in groups with outliers.

“…The mean is the most sensitive to outlier presence and thus the most conservative benchmark to test for overweighting because it already gives the most weight to the outlier (see Study 1 stimuli). encode accurately and rapidly sets (ensembles) of stimuli (Alvarez, 2011;Whitney, Haberman & Sweeny, 2014). This is true of basic visual stimuli such as item size (Ariely, 2001;Chong & Treisman, 2003), orientation (Alvarez & Oliva, 2009;Dakin & Watt, 1997), speed (Watamaniuk & Duchon, 1992), and location (Alvarez & Oliva, 2008).…”

Distinctive signatures of recursion

“…Here, it is important to note two points: (i) if there are no priors regarding which rules are possible or likely to represent the output of a given system, then it may be impossible to generalize and predict its future behaviour [28,48]; (ii) although real objects deviate from abstractions (such as apples deviate from spheres), it seems that, at least in visual processing, abstract prototypes and the amount of deviation from those prototypes can be simultaneously represented in a mutually informative way [46]: the amount of deviation allowed before a shift from the initial abstraction is dependent on the suitability of the resulting behaviours [14,49]. Although recursive prototypes can be the initial priors, the representational schema may evolve owing to functional constraints.…”

Gestalt Effects in Visual Working Memory

“…One theoretical consequence of the previous studies as well as the current study is that most probably representtation of information in VWM does not consist of isolated representations of objects in a memorized scene, but it also includes the pattern of their mutual relations (see Clevenger & Hummel, 2014), the overall layout (see Rensink, 2000), and general statistical properties encoded into some ensemble representation of the visual pattern (see Alvarez, 2011;. Although early research on VWM was primarily focused on uncovering VWM representation of the single visual objects, as well as their maximal number that can be simultaneously processed by humans (leading to estimates of VWM capacity of about three or four objects; see Cowan, 2001;Vogel et al, 2001), currently an increasing evidence implicates that representation of visual information in WM is highly hierarchical, encompassing the binding of elementary features into composite objects, as well as binding of objects into groups and ensembles (for a seminal model of such binding see Hummel & Biederman, 1992).…”

“…It seems that only such hierarchical representations allow holistic and meaningful interpretation of perceptual data . Moreover, such representations more efficiently compress visual data, which often include a lot of structured organization and redundancy (Alvarez, 2011). Overall, encoding (in perception) and actively maintaining (in VWM) visual information seem to be more complex processes than they were initially considered.…”

“…Context also influences how we recall individual items, as recall of items that possessed an extreme value of a particular visual feature (e.g., size) is often biased toward an average value of that feature in a display . In total, all these context effects suggest that people encode in VWM not only particular items, but also (oreven -primarily) encode their ensemble in a way that is able to compress redundant and structured information from a display into concise but very informative higher-level representation of ensemble, which then can be used to predict features of individual items (Alvarez, 2011).…”