Translations: effects of viewpoint, feature, naming and context on identifying repeatedly copied drawings

We explored the tension between bottom – up and top – down contributions to object recognition in a collaboration between a visual artist and a cognitive psychologist. Initial pictorial renderings of objects and animals from various viewpoints were iteratively copied, and a series of drawings that changed from highly concrete images into highly abstract images was produced. In drawing identification in which sets were shown in reverse order, participants were more accurate, more confident, and quicker to correctly identify the evolving image when it was originally displayed from a canonical viewpoint with all salient features present. In drawing identification in which images were shown in random order, more abstract images could be resolved as a result of previously identifying a more concrete iteration of the same drawing. The results raise issues about the influence of viewpoint and feature on the preservation of pictorial images and about the role of labelling in the interpretation of ambiguous stimuli. In addition, the study highlights a procedure in which visual stimuli can degrade without necessitating a substantial loss of complexity

Promoting Inclusivity in the Archive: A literature review reassessing tradition through theory and practice

The call for social justice and rise of postmodernism in the second half of the 20th century forced the critical re-evaluation of the traditional archive and its presumed neutral role in the collection and creation of history. Reappraisal of traditional archive theory and practice was forced by heightened critical conscious among the field and its constituents. This literature review examines contemporary methodologies and methods influenced by the postmodern movement and call for social justice in the archive. Affect theory, radical empathy, and queer/ed methodology provide new frameworks for the thinking about the archive space and work towards the creation of a more diverse and inclusive archive. The collection of oral histories and participatory, community archiving practices provide concrete methods for employing the aforementioned theories. This paper purports that these ideas may be better framed within the context of the post-postmodern movement of metamodernism and calls for the continual evaluation of archival theory and practice within this vein

An Overdensity of Extremely Red Objects Around Faint Mid-IR galaxies

We have searched for Extremely Red Objects (EROs) around faint mid-IR selected galaxies in ELAIS fields. We find a significant overdensity, by factors of 2 to 5, of these EROs compared to field EROs in the same region and literature random field ERO counts. The excess is similar to that found previously in the fields of known high redshift quasars and AGN. While with the present data it cannot be definitely shown whether the overdensity is physically connected to the mid-IR source, a derived radial distribution does suggest this. The fraction of EROs among K-selected galaxies is high in the mid-IR fields in agreement with the picture that the EROs responsible for the overdensity are members of high redshift clusters of galaxies. We find R-K>5 selected EROs to be more clustered around the mid-IR galaxies than I-K>4 EROs, though statistics are weak because of small numbers. However, this would be consistent with a cluster/galaxy group scenario if, as we argue, the former colour selection finds preferentially more strongly clustered early type galaxies, whereas the latter selection includes a larger fraction of dusty EROs. Finally, using the mid-IR data, we are able to limit the fraction of ULIRG type very dusty EROs at K<18 magnitude to less than 10% of the total ERO population.Comment: A&A, accepted, 13 pages and 5 ps-fig

Short term synaptic depression improves information transfer in perceptual multistability

Competitive neural networks are often used to model the dynamics of perceptual bistability. Switching between percepts can occur through fluctuations and/or a slow adaptive process. Here, we analyze switching statistics in competitive networks with short term synaptic depression and noise. We start by analyzing a ring model that yields spatially structured solutions and complement this with a study of a space-free network whose populations are coupled with mutual inhibition. Dominance times arising from depression driven switching can be approximated using a separation of timescales in the ring and space-free model. For purely noise-driven switching, we use energy arguments to justify how dominance times are exponentially related to input strength. We also show that a combination of depression and noise generates realistic distributions of dominance times. Unimodal functions of dominance times are more easily differentiated from one another using Bayesian sampling, suggesting synaptic depression induced switching transfers more information about stimuli than noise-driven switching. Finally, we analyze a competitive network model of perceptual tristability, showing depression generates a memory of previous percepts based on the ordering of percepts.Comment: 26 pages, 15 figure

How active perception and attractor dynamics shape perceptual categorization: A computational model

We propose a computational model of perceptual categorization that fuses elements of grounded and sensorimotor theories of cognition with dynamic models of decision-making. We assume that category information consists in anticipated patterns of agent–environment interactions that can be elicited through overt or covert (simulated) eye movements, object manipulation, etc. This information is firstly encoded when category information is acquired, and then re-enacted during perceptual categorization. The perceptual categorization consists in a dynamic competition between attractors that encode the sensorimotor patterns typical of each category; action prediction success counts as ‘‘evidence’’ for a given category and contributes to falling into the corresponding attractor. The evidence accumulation process is guided by an active perception loop, and the active exploration of objects (e.g., visual exploration) aims at eliciting expected sensorimotor patterns that count as evidence for the object category. We present a computational model incorporating these elements and describing action prediction, active perception, and attractor dynamics as key elements of perceptual categorizations. We test the model in three simulated perceptual categorization tasks, and we discuss its relevance for grounded and sensorimotor theories of cognition.Peer reviewe