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In this opinion piece, the authors, from the fields of artificial intelligence (AI) and psychology, reflect on how the foundational discoveries of Nobel laureates Hopfield and Hinton have influenced their research. They also discuss emerging directions in AI and the challenges that lie ahead for neural networks and machine learning. 

Visual learning often occurs in a specific context, where an agent acquires skills through exploration and tracking of its location in a consistent environment. The historical spatial context of the agent provides a similarity signal for self-supervised contrastive learning. We present a unique approach, termed Environmental Spatial Similarity (ESS), that complements existing contrastive learning methods. Using images from simulated, photorealistic environments as an experimental setting, we demonstrate that ESS outperforms traditional instance discrimination approaches. Moreover, sampling additional data from the same environment substantially improves accuracy and provides new augmentations. ESS allows remarkable proficiency in room classification and spatial prediction tasks, especially in unfamiliar environments. This learning paradigm has the potential to enable rapid visual learning in agents operating in new environments with unique visual characteristics. Potentially transformative applications span from robotics to space exploration. Our proof of concept demonstrates improved efficiency over methods that rely on extensive, disconnected datasets. 

There have been conflicting findings on the degree to which rapidly deployed visual attention is selective for depth, and this issue has important implications for attention models. Previous findings have attempted to find depth-based cueing effects on such attention using reaction time (RT) measures for stimuli presented in stereo goggles with a display screen. Results stemming from such approaches have been mixed, depending on whether target/distractor discrimination was required. To help clarify the existence of such depth effects, we have developed a paradigm that measures accuracy rather than RT in an immersive virtual-reality environment, providing a more appropriate context of depth. Three modified Posner Cueing paradigms were run to test for depth-specific rapid attentional selectivity. Participants fixated a cross while attempting to identify a rapidly masked black letter preceded by a red cue that could be valid in depth, side, or both. In Experiment 1a, a potent cueing effect was found for lateral cueing validity, but a weak effect was found for depth despite an extreme difference in virtual depth (1 vs. 300 m). In Experiment 1b, a near-replication of 1a, the lateral effect replicated while the depth effect did not. Finally, in Experiment 2, to increase the depth cue’s effectiveness, the letter matched the cue’s color, and the presentation duration was increased; however, again only a minimal depth-based cueing effect – no greater than that of Experiment 1a – was observed. Thus, we conclude that rapidly deployed attention is driven largely by spatiotopic rather than depth-based information. 

Abstract It has been debated whether salient distractors in visual search can be proactively suppressed to completely prevent attentional capture, as the occurrence of proactive suppression implies that the initial shift of attention is not entirely driven by physical salience. While the presence of a Pd component in the EEG (associated with suppression) without a preceding N2pc component (associated with selection) has been used as evidence for proactive suppression, the link between these ERPs and the underlying mechanisms is not always clear. This is exemplified in two recent articles that observed the same waveform pattern, where an early Pd-like component flipped to a N2pc-like component, but provided vastly different interpretations (Drisdelle, B. L., & Eimer, E. PD components and distractor inhibition in visual search: New evidence for the signal suppression hypothesis. Psychophysiology, 58, e13898, 2021; Kerzel, D., & Burra, N. Capture by context elements, not attentional suppression of distractors, explains the PD with small search displays. Journal of Cognitive Neuroscience, 32, 1170–1183, 2020). Using RAGNAROC (Wyble et al., Understanding visual attention with RAGNAROC: A Reflexive Attention Gradient through Neural AttRactOr Competition. Psychological Review, 127, 1163–1198, 2020), a computational model of reflexive attention, we successfully simulated this ERP pattern with minimal changes to its existing architecture, providing a parsimonious and mechanistic explanation for this flip in the EEG that is unique from both of the previous interpretations. Our account supports the occurrence of proactive suppression and demonstrates the benefits of incorporating computational modeling into theory building. 

Previous evidence demonstrated that individuals can recall a target’s location in a search display even if location information is completely task-irrelevant. This finding raises the question: does this ability to automatically encode a single item’s location into a reportable memory trace extend to other aspects of spatial information as well? We tested this question using a paradigm designed to elicit attribute amnesia (Chen & Wyble, 2015a). Participants were initially asked to report the location of a target letter among digits with stimuli arranged to form one of two or four spatial configurations varying randomly across trials. After completing numerous trials that matched their expectations, participants were surprised with a series of unexpected questions probing their memory for various aspects of the display they had just viewed. Participants had a profound inability to report which spatial configuration they had just perceived when the target’s location was not unique to a specific configuration (i.e., orthogonal). Despite being unable to report the most recent configuration, answer choices on the surprise trial were focused around previously seen configurations, rather than novel configurations. Thus, there were clear memories of the set of configurations that had been viewed during the experiment but not of the specific configuration from the most recent trial. This finding helps to set boundary conditions on previous findings regarding the automatic encoding of location information into memory.