You can’t “count” how many items people remember in working memory: The importance of signal detection-based measures for understanding change detection performance

Change detection tasks are commonly used to measure and understand the nature of visual working memory capacity. Across two experiments, we examine whether the nature of the latent memory signals used to perform change detection are continuous or all-or-none, and consider the implications for proper measurement of performance. In Experiment 1, we find evidence from confidence reports that visual working memory is continuous in strength, with strong support for equal variance signal detection models. We then tested a critical implication of this result without relying on model comparison or confidence reports in Experiment 2 by asking whether a simple instruction change would improve performance when measured with K, an all-or-none-measure, compared to d’, a measure based on continuous strength signals. We found strong evidence that K values increased by roughly 30% despite no change in the underlying memory signals. By contrast, we found that d’ is fixed across these same instructions, demonstrating that it correctly separates response criterion from memory performance. Overall, our data call into question a large body of work using threshold measures, like K, to analyze change detection data since this metric confounds response bias with memory performance in standard change detection tasks.

A smartphone intervention that enhances real-world memory and promotes differentiation of hippocampal activity in older adults

The act of remembering an everyday experience influences how we interpret the world, how we think about the future, and how we perceive ourselves. It also enhances long-term retention of the recalled content, increasing the likelihood that it will be recalled again. Unfortunately, the ability to recollect event-specific details tends to decline with age, resulting in an impoverished ability to mentally re-experience the past. This shift has been linked to a corresponding decline in the distinctiveness of hippocampal memory representations. Despite these well-established changes, there are few effective cognitive behavioral interventions that target real-world episodic memory. We addressed this gap by developing a smartphone-based application called HippoCamera that allows participants to record labelled videos of everyday events and subsequently replay standardized, high-fidelity autobiographical memory cues. In two experiments, we found that older adults were able to easily integrate this non-invasive intervention into their daily lives. Using HippoCamera to repeatedly reactivate memories for real-world events improved episodic recollection and it evoked more positive autobiographical sentiment at the time of retrieval. In both experiments, these benefits were observed shortly after the intervention and again after a 3-month delay. Moreover, more detailed recollection was associated with more differentiated memory signals in the hippocampus. We conclude that using this smartphone application to systematically reactivate memories for recent real-world experiences can help to maintain a bridge between the present and past self in older adults.

Benchmarking GE-BOLD, SE-BOLD, and SS-SI-VASO sequences for depth-dependent separation of feedforward and feedback signals in high-field MRI

Recent advances in high-field fMRI have allowed differentiating feedforward and feedback information in the grey matter of the human brain. For continued progress in this endeavor, it is critical to understand how MRI data acquisition parameters impact the read-out of information from laminar response profiles. Here, we benchmarked three different MR-sequences at 7T - gradient-echo (GE), spin-echo (SE) and vascular space occupancy imaging (VASO) - in differentiating feedforward and feedback signals in human early visual cortex (V1). The experiment (N=4) consisted of two complementary tasks: a perception task that predominantly evokes feedforward signals and a working memory task that relies on feedback signals. In the perception task, participants saw flickering oriented gratings while detecting orthogonal color-changes. In the working memory task, participants memorized the precise orientation of a grating. We used multivariate pattern analysis to read out the perceived (feedforward) and memorized (feedback) grating orientation from neural signals across cortical depth. Analyses across all the MR-sequences revealed perception signals predominantly in the middle cortical compartment of area V1 and working memory signals in the deep compartment. Despite an overall consistency across sequences, SE-EPI was the only sequence where both feedforward and feedback information were differently pronounced across cortical depth in a statistically robust way. We therefore suggest that in the context of a typical cognitive neuroscience experiment as the one benchmarked here, SE-EPI may provide a favorable trade-off between spatial specificity and signal sensitivity.

Neural Substrates of Visual Perception and Working Memory: Two Sides of the Same Coin or Two Different Coins?

Visual perception occurs when a set of physical signals emanating from the environment enter the visual system and the brain interprets such signals as a percept. Visual working memory occurs when the brain produces and maintains a mental representation of a percept while the physical signals corresponding to that percept are not available. Early studies in humans and non-human primates demonstrated that lesions of the prefrontal cortex impair performance during visual working memory tasks but not during perceptual tasks. These studies attributed a fundamental role in working memory and a lesser role in visual perception to the prefrontal cortex. Indeed, single cell recording studies have found that neurons in the lateral prefrontal cortex of macaques encode working memory representations via persistent firing, validating the results of lesion studies. However, other studies have reported that neurons in some areas of the parietal and temporal lobe—classically associated with visual perception—similarly encode working memory representations via persistent firing. This prompted a line of enquiry about the role of the prefrontal and other associative cortices in working memory and perception. Here, we review evidence from single neuron studies in macaque monkeys examining working memory representations across different areas of the visual hierarchy and link them to studies examining the role of the same areas in visual perception. We conclude that neurons in early visual areas of both ventral (V1-V2-V4) and dorsal (V1-V3-MT) visual pathways of macaques mainly encode perceptual signals. On the other hand, areas downstream from V4 and MT contain subpopulations of neurons that encode both perceptual and/or working memory signals. Differences in cortical architecture (neuronal types, layer composition, and synaptic density and distribution) may be linked to the differential encoding of perceptual and working memory signals between early visual areas and higher association areas.

The locus of recognition memory signals in human cortex depends on the complexity of the memory representations

Representational theories predict that brain regions contribute to cognition according to the information they represent (e.g., simple versus complex), contradicting the traditional notion that brain regions are specialized for cognitive functions (e.g., perception versus memory). In support of representational accounts, substantial evidence now attests that the Medial Temporal Lobe (MTL) is not specialized solely for long-term declarative memory, but underpins other functions including perception and future-imagining for complex stimuli and events. However, a complementary prediction has been less well explored, namely that the cortical locus of declarative memory may fall outside the MTL if the to-be-remembered content is sufficiently simple. Specifically, the locus should coincide with the optimal neural code for the representations being retrieved. To test this prediction, we manipulated the complexity of the to-be-remembered representations in a recognition memory task. First, participants in the scanner viewed novel 3D objects and scenes, and we used multivariate analyses to identify regions in the ventral visual-MTL pathway that preferentially coded for either simple features of the stimuli, or complex conjunctions of those features. Next, in a separate scan, we tested recognition memory for these stimuli and performed neuroimaging contrasts that revealed two memory signals ‒ feature memory and conjunction memory. Feature memory signals were found in visual cortex, while conjunction memory signals emerged in MTL. Further, the regions optimally representing features via preferential feature-coding coincided with those exhibiting feature memory signals. These findings suggest that representational content, rather than cognitive function, is the primary organizing principle in the ventral visual-MTL pathway.

Two kinds of memory signals in neurons of the human hippocampus

Some studies of the neural representation of memory in the human hippocampus have identified memory signals reflecting the categorical status of test items (novel vs. repeated). Others have identified pattern-separated, episodic memory signals reflecting recognition of particular test items. Here, we report that both kinds of memory signals can be found in the hippocampus, and we consider their possible functions. We recorded single-unit activity from four brain regions (hippocampus, amygdala, anterior cingulate, and prefrontal cortex) of epilepsy patients as they performed a continuous recognition task. The generic signal was found in all four regions, whereas the sparse, pattern-separated signal was limited to the hippocampus, as predicted by longstanding computational models.

Measuring memory is harder than you think: A crisis of measurement in memory research

There is a crisis of measurement in memory research, with major implications for theory and practice. This crisis arises because of a critical complication present when measuring memory using the recognition memory task that dominates the study of working memory and long-term memory (“did you see this item? yes/no” or “did this item change? yes/no”). Such tasks give two measures of performance, the “hit rate” (how often you say you previously saw an item you actually did previously see) and the “false alarm rate” (how often you say you saw something you never saw). Yet what researchers want is one single, integrated measure of memory performance. Integrating the hit and false alarm rate into a single measure, however, requires a complex problem of counterfactual reasoning that depends on the (unknowable) distribution of underlying memory signals: when faced with two people differing in both hit rate and false alarm rate, the question of who had the better memory is really “who would have had more hits if they each had the same number of false alarms”. As a result of this difficulty, different literatures in memory research (e.g., visual working memory, eyewitness identification, picture memory, etc) have settled on a variety of distinct metrics to combine hit rates and false alarm rates (e.g., A’, corrected hit rate, percent correct, d’, diagnosticity ratios, K values, etc.). These metrics make different, contradictory assumptions about the distribution of latent memory signals, and all of their assumptions are frequently incorrect. Despite a large literature on how to properly measure memory performance, spanning decades, real-life decisions are often made using these metrics, even when they subsequently turn out to be wrong when memory is studied with better measures. We suggest that in order for the psychology and neuroscience of memory to become a cumulative, theory-driven science, more attention must be given to measurement issues. We make a concrete suggestion: the default memory task should change from old/new (“did you see this item’?”) to forced-choice (“which of these two items did you see?”). In situations where old/new variants are preferred (e.g., eyewitness identification; theoretical investigations of the nature of memory decisions), receiver operating characteristic (ROC) analysis should always be performed.

Web Revisitation using Content and Context Tokens

Right now, the Internet is the most common medium people use to obtain access to knowledge. One's requirements vary from a single word sense to specialized papers and self-education. Revisiting previously visited web pages is one of the most common and unpleasant activities a person does. In fact, a significant primary feedback technique is included in tailoring the individual's memory of vigor and re-examination patterns. Our successful control of environment and object recollections, including decay and reinforcing techniques, may imitate device retention and retention mechanisms. This proposed solution takes into consideration the normal human retrieval method of utilizing episodic and textual memory signals for fast retrieval and includes a different site revisitation mechanism known as the "Web Page Preview" via meaning and information gained through user discovery and web page visits. The underlying methods for the collection, preservation, degradation and usage of meaning and quality of consumer memories for page re-discovery are addressed. Our 3 month user study says that of the time, location, and activity context factors in Web Page Prep, activity is the best recall guide, and context + content based re-discovery provides the highest results relative to context and content individual rediscovery. This concept, if completed, can be used to improve web surfing functionality by providing users a variety of apps with a rather simple UI.