Massive visual long-term memory is largely dependent on meaning.

Previous research demonstrated a massive capacity of visual long-term memory (VLTM) for meaningful images. However, the capacity and limits of a "pure" VLTM that is independent of conceptual information still need to be determined. In the encoding phase of three experiments, participants viewed hundreds of images depicting real-world objects, along with visually similar images that were stripped of their semantic meaning. VLTM was evaluated using a four-alternative-forced-choice test including old and new images and their counterpart mirror transformations. The results revealed superior memory for meaningful than for meaningless stimuli and importantly, there was no hint of a massive VLTM for the meaningless items. Furthermore, when examining memory recognition of visual properties per-se (i.e., original/mirror state), memory was overall poor, and practically negligible for the meaningless items. Taken together, our findings suggest that meaning is critical for massive VLTM and for the ability to store visual properties.

Meaningful stimuli inflate the role of proactive interference in visual working memory.

The use of meaningful daily objects in visual working memory (VWM) tasks revealed two uncharacteristic findings: enlarged memory capacity, and strong proactive interference (PI), which was previously believed to play only a modest role in VWM. To disassociate the roles of meaning and visual complexity in these effects, a set of stimuli composed of meaningful daily objects was compared to visually similar meaningless sets. These sets were included in a Repeated (PI-prone) condition in which stimuli were repeatedly drawn from a limited set of items, and in a Unique (PI-free) condition in which each stimulus appeared only once. In line with past findings, the results consistently showed superior memory for meaningful stimuli. Importantly, they also showed a stronger PI-effect for meaningful stimuli as the difference between the Repeated and Unique conditions was greatly reduced (Experiment 1) or eliminated (Experiment 2) for meaningless stimuli. Together, these results strongly imply that meaning, and not visual complexity, plays a key role not only in boosting memory capacity but also in inflating the role of PI in VWM.

The locus of proactive interference in visual working memory.

Recent studies showed that proactive interference (PI) impairs visual working memory (WM), as performance is better when the memory items are unique rather than repeated throughout the experiment. To scrutinize the mechanisms driving this effect, we tested how it affects the stages of encoding, retention, and testing. Experiment 1 instructed participants to make speeded responses and found that reaction time was slower in the repeated than in the unique condition, suggesting memory source confusion during testing. Experiment 2 showed that a retention interval manipulation did not affect the magnitude of the PI effect. Finally, Experiment 3 found that the PI effect did not increase when the encoding interval was short. Instead, the difference between the repeated and unique conditions was reduced, probably because the increased familiarity with the memory items in the repeated condition facilitated consolidation. Taken together, these results suggest that the main locus of PI in visual WM is during testing and that encoding and retaining information in visual WM are hardly affected by no longer needed information. Consequently, these data support the involvement of long-term memory in the effect. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Bridging the gap between visual temporary memory and working memory: The role of stimuli distinctiveness.

Visual working memory (VWM) is traditionally assumed to be immune to proactive interference (PI). However, in a recent study (Endress & Potter, 2014), performance in a visual memory task was superior when all items were unique and hence interference from previous trials was impossible, compared to a standard condition in which a limited set of repeating items was used and stimuli from previous trials could interfere with the current trial. Furthermore, when all the items were unique, the estimated memory capacity far exceeded typical capacity estimates. Consequently, the researchers suggested the existence of a separate memory buffer, the "temporary memory," which has an unbounded capacity for meaningful items. However, before accepting this conclusion, methodological differences between the repeated-unique procedure and typical estimates of VWM should be considered. Here, we tested the extent to which the exceptional set of heterogeneous, complex, meaningful real-world objects contributed to the large PI in the repeated-unique procedure. Thus, the same paradigm was employed with a set of real-world objects and with homogenous sets (e.g., houses, faces) in which the items were meaningful, yet less visually distinct, and participants had to rely on subtle visual details to perform the task. The results revealed a large PI effect for real-world heterogeneous objects, but substantially smaller effects for the homogenous sets. These findings suggest that there is no need to postulate a new memory buffer. Instead, we suggest that VWM capacity and vulnerability to PI are highly influenced by task characteristics, and specifically, by the stimuli distinctiveness. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Seeing without knowing: task relevance dissociates between visual awareness and recognition.

We demonstrate that task relevance dissociates between visual awareness and knowledge activation to create a state of seeing without knowing-visual awareness of familiar stimuli without recognizing them. We rely on the fact that in order to experience a Kanizsa illusion, participants must be aware of its inducers. While people can indicate the orientation of the illusory rectangle with great ease (signifying that they have consciously experienced the illusion's inducers), almost 30% of them could not report the inducers' color. Thus, people can see, in the sense of phenomenally experiencing, but not know, in the sense of recognizing what the object is or activating appropriate knowledge about it. Experiment 2 tests whether relevance-based selection operates within objects and shows that, contrary to the pattern of results found with features of different objects in our previous studies and replicated in Experiment 1, selection does not occur when both relevant and irrelevant features belong to the same object. We discuss these findings in relation to the existing theories of consciousness and to attention and inattentional blindness, and the role of cognitive load, object-based attention, and the use of self-reports as measures of awareness.

Are task irrelevant faces unintentionally processed? Implicit learning as a test case.

Faces are one of the most important signals for reading people's mental states. In sync with their apparent "chronic" (cross-situational) relevance, faces have been argued to be processed independently of the task one is currently performing. Many of these demonstrations have involved "capture of attention" or increased interference by faces functioning as distractors. Here we ask whether multiple repetitions of task irrelevant faces leave a trace in the system. Specifically, we tested whether repeating structures instantiated by task irrelevant faces are unintentionally or implicitly learned. Our findings indicate that although faces are indeed unique in that they are the only stimulus found to lead to implicit learning of complex rules when irrelevant, such learning is small in magnitude. Although these results support the conjecture that task irrelevant faces are processed, the functional significance of this learning needs to be assessed.

Relevance-based selectivity: the case of implicit learning.

Learning the structure of the environment (e.g., what usually follows what) enables animals to behave in an effective manner and prepare for future events. Unintentional learning is capable of efficiently producing such knowledge as has been demonstrated with the Artificial Grammar Learning paradigm (AGL), among others. It has been argued that selective attention is a necessary and sufficient condition for visual implicit learning. Experiment 1 shows that spatial attention is not sufficient for implicit learning. Learning does not occur if the stimuli instantiating the structure are task irrelevant. In a second experiment, we demonstrate that this holds even with abundance of available attentional resources. Together, these results challenge the current view of the relations between attention, resources, and implicit learning.