Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

Scene recognition is one of the hallmark tasks of computer vision, allowing definition of a context for object recognition. Whereas the tremendous recent progress in object recognition tasks is due to the availability of large datasets like ImageNet and the rise of Convolutional Neural Networks (CNNs) for learning high-level features, performance at scene recognition has not attained the same level of success. This may be because current deep features trained from ImageNet are not competitive enough for such tasks. Here, we introduce a new scene-centric database called Places with over 7 million labeled pictures of scenes. We propose new methods to compare the density and diversity of image datasets and show that Places is as dense as other scene datasets and has more diversity. Using CNN, we learn deep features for scene recognition tasks, and establish new state-of-the-art results on several scene-centric datasets. A visualization of the CNN layers' responses allows us to show differences in the internal representations of object-centric and scene-centric networks.

https://proceedings.neurips.cc/paper/2014/file/3fe94a002317b5f9259f82690aeea4cd-Paper.pdf

Learning Deep Features for Scene Recognition using Places Database

The concept of similarity, or a sense of 'sameness' among things, is pivotal to theories in the cognitive sciences and beyond. Similarity, however, is a difficult thing to measure. Multidimensional scaling (MDS) is a tool by which researchers can obtain quantitative estimates of similarity among groups of items. More formally, MDS refers to a set of statistical techniques that are used to reduce the complexity of a data set, permitting visual appreciation of the underlying relational structures contained therein. The current paper provides an overview of MDS. We discuss key aspects of performing this technique, such as methods that can be used to collect similarity estimates, analytic techniques for treating proximity data, and various concerns regarding interpretation of the MDS output. MDS analyses of two novel data sets are also included, highlighting in step-by-step fashion how MDS is performed, and key issues that may arise during analysis. WIREs Cogn Sci 2013, 4:93-103. doi: 10.1002/wcs.1203 This article is categorized under: Psychology > Perception and Psychophysics.

/pdf/multidimensional-scaling-multidimensional-scaling-1cctj0bnt0.pdf

Multidimensional scaling: Multidimensional scaling

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual \"filling in,\" visual stability despite eye movements, change blindness, sensory substitution, and color perception.

A sensorimotor account of vision and visual consciousness-Authors' Response-Acting out our sensory experience

Previous research has suggested that visual short-term memory has a fixed capacity of about four objects. However, we found that capacity varied substantially across the five stimulus classes we examined, ranging from 1.6 for shaded cubes to 4.4 for colors (estimated using a change detection task). We also estimated the information load per item in each class, using visual search rate. The changes we measured in memory capacity across classes were almost exactly mirrored by changes in the opposite direction in visual search rate (r2=.992 between search rate and the reciprocal of memory capacity). The greater the information load of each item in a stimulus class (as indicated by a slower search rate), the fewer items from that class one can hold in memory. Extrapolating this linear relationship reveals that there is also an upper bound on capacity of approximately four or five objects. Thus, both the visual information load and number of objects impose capacity limits on visual short-term memory.

/pdf/the-capacity-of-visual-short-term-memory-is-set-both-by-2fjit5cb6m.pdf

The capacity of visual short-term memory is set both by visual information load and by number of objects

One of the major lessons of memory research has been that human memory is fallible, imprecise, and subject to interference. Thus, although observers can remember thousands of images, it is widely assumed that these memories lack detail. Contrary to this assumption, here we show that long-term memory is capable of storing a massive number of objects with details from the image. Participants viewed pictures of 2,500 objects over the course of 5.5 h. Afterward, they were shown pairs of images and indicated which of the two they had seen. The previously viewed item could be paired with either an object from a novel category, an object of the same basic-level category, or the same object in a different state or pose. Performance in each of these conditions was remarkably high (92%, 88%, and 87%, respectively), suggesting that participants successfully maintained detailed representations of thousands of images. These results have implications for cognitive models, in which capacity limitations impose a primary computational constraint (e.g., models of object recognition), and pose a challenge to neural models of memory storage and retrieval, which must be able to account for such a large and detailed storage capacity.

/pdf/visual-long-term-memory-has-a-massive-storage-capacity-for-175nury4yu.pdf

Visual long-term memory has a massive storage capacity for object details

http://cns-classes.bu.edu/ennio/cnsftp/cn730-2007-pdf/Cavanagh%20%26%20Alvarez%20(2005).pdf

Tracking multiple targets with multifocal attention.

https://scholar.harvard.edu/alvarez/files/alvarez-2011-tics-ensemble.pdf

Representing multiple objects as an ensemble enhances visual cognition.

Tulving (2000) provided a concise, general definition of memory as the “neurocognitive capacity to encode, store, and retrieve information,” and suggested the possibility that there are many separate memory systems that fit this definition. Indeed, one of the primary aims of modern memory research has been to identify these different memory systems (Schacter & Tulving, 1994). This approach has lead to an extensive taxonomy of memory systems which are characterized by differences in timing, storage capacity, conscious access, active maintenance, and mechanisms of operation.

Early on, William James (1890) proposed the distinction between primary memory – the information held in the ‘conscious present’ – and secondary memory, which consists of information that is acquired, stored outside of conscious awareness, and then later remembered. This distinction maps directly onto the modern distinction between short-term memory (henceforth working memory) and long-term memory (Atkinson & Shiffrin, 1968; Scoville & Milner, 1957; Waugh & Norman, 1965). The most salient difference between these systems is their capacity: the active, working memory system has an extremely limited capacity of only a few items (Cowan, 2001; Cowan, 2005; Miller, 1956), whereas the passive, long-term memory system can store thousands of items (Brady et al. 2008; Standing, 1973; Voss, 2009) with remarkable fidelity (Brady et al., 2008; Konkle et al., 2010a).

The emphasis on memory systems and memory processes has been quite valuable in shaping cognitive and neural models of memory. In general, this approach aims to characterize memory systems in a way that generalizes over representational content (Schacter & Tulving, 1994). For example, working memory is characterized by a severely limited capacity regardless of whether items are remembered visually or verbally (e.g., Baddeley, 1986), and long-term memory has a very high capacity whether the items remembered are pictures (e.g., Standing, 1973), words (e.g., Shepard, 1967), or associations (e.g., Voss, 2009). However, generalization across content leaves many basic questions unanswered regarding the nature of stored representations: What is the structure and format of those representations?

Research on visual perception takes the opposite approach, attempting to determine what is being represented, and to generalize across processes. For example, early stages of visual representation consist of orientation and spatial frequency features. Vision research has measured the properties of these features, such as their tuning curves and sensitivity (e.g., Blakemore & Campbell, 1969), and shown that these tuning properties are constant across several domains of processing (e.g., from simple detection to visual search).

Thus, the intersection between memory and vision is a particularly interesting domain of research because it concerns both the processes of memory and the nature of the stored representations (Luck & Hollingworth, 2008). Recent research within the vision science community at this intersection between memory and vision has been quite fruitful. For example, working memory research has shown an important item/resolution tradeoff: as the number of items remembered increases, the precision with which each one is remembered decreases, possibly with an upper bound on the number of items that may be stored (Alvarez & Cavanagh, 2004; Zhang & Luck, 2008), or possibly without an upper bound (Bays, Catalao & Husain, 2009; Wilken & Ma, 2004). In long-term memory, it is possible to store thousands of detailed object representations (Brady et al. 2008; Konkle et al., 2010b) but only for meaningful items that connect with stored knowledge (Konkle et al., 2010b; Wiseman and Neisser, 1974).

Here we review recent research in the domains of visual working memory and visual long-term memory, focusing on how models of these memory systems are altered and refined by taking the contents of memory into account.

/pdf/a-review-of-visual-memory-capacity-beyond-individual-items-3rhnyd4un5.pdf

George A. Alvarez

Papers

The capacity of visual short-term memory is set both by visual information load and by number of objects

Visual long-term memory has a massive storage capacity for object details

Tracking multiple targets with multifocal attention.

Representing multiple objects as an ensemble enhances visual cognition.

A review of visual memory capacity: Beyond individual items and toward structured representations.