What's magic about magic numbers? Chunking and data compression in short-term memory

Shared structure facilitates working memory of multiple sequences

Daily experiences often involve the processing of multiple sequences, yet storing them challenges the limited capacity of working memory (WM). To achieve efficient memory storage, relational structures shared by sequences would be leveraged to reorganize and compress information. Here, participants memorized a sequence of items with different colors and spatial locations and later reproduced the full color and location sequences one after another. Crucially, we manipulated the consistency between location and color sequence trajectories. First, sequences with consistent trajectories demonstrate improved memory performance and a trajectory correlation between reproduced color and location sequences. Second, sequences with consistent trajectories show neural reactivation of common trajectories, and display spontaneous replay of color sequences when recalling locations. Finally, neural reactivation correlates with WM behavior. Our findings suggest that a shared common structure is leveraged for the storage of multiple sequences through compressed encoding and neural replay, together facilitating efficient information organization in WM.

Spatial-positional associations in short-term memory can vanish in long-term memory

Studies on the SPoARC effect have shown that serial information is spatially processed in working memory. However, it remains unknown whether these spatial-positional associations are durable or only temporary. This study aimed at investigating whether spatialization would persist when a sequence presented repeatedly is expected to be chunked. If chunked, the items could be unified spatially and their spatialization could vanish. Thirty-seven participants performed a spatialization task which was remotely inspired by the Hebb repetition paradigm. A sequence of four stimuli presented individually in the middle of a computer screen was repeated throughout the task. After each sequence, participants had to decide whether a probe belonged to the series using two lateralized response keys. The results showed no spatialization for these repetitive sequences, on average. Moreover, further analysis revealed that the effect was detectable at the beginning of the task, suggesting that the more the sequence was repeated, the less participants spatialized information from left to right. These findings show that associations created in working memory between items and space can vanish in repeated sequences: we discuss the idea that working memory progressively saves on spatialization once a sequence is chunked in long-term memory.

Representation and computation in visual working memory

The ability to sustain internal representations of the sensory environment beyond immediate perception is a fundamental requirement of cognitive processing. In recent years, debates regarding the capacity and fidelity of the working memory (WM) system have advanced our understanding of the nature of these representations. In particular, there is growing recognition that WM representations are not merely imperfect copies of a perceived object or event. New experimental tools have revealed that observers possess richer information about the uncertainty in their memories and take advantage of environmental regularities to use limited memory resources optimally. Meanwhile, computational models of visuospatial WM formulated at different levels of implementation have converged on common principles relating capacity to variability and uncertainty. Here we review recent research on human WM from a computational perspective, including the neural mechanisms that support it.

Proactive interference of visual working memory chunks implicates long-term memory

Visual working memory (VWM) is a limited cognitive resource that can be functionally expanded through chunking (Miller, 1956). For example, participants can hold an increasing number of colours in mind as they learn to chunk reliably paired combinations (Brady et al., 2009). We investigated whether this benefit is mediated through the in situ compression of VWM representations (Brady et al., 2009) or the offloading of chunks to long-term memory (LTM; Huang & Awh, 2018; Ngiam et al., 2019) by asking if a vulnerability of LTM - proactive interference - influences VWM performance. We adapted previous designs using deterministic (Experiment 1, N = 60) and probabilistic pairings (Experiments 2 and 3, N = 64 and 80, respectively), to include colour pairings that swapped in sequence along with pairings that were consistent in sequence. Generally, participants reported colours from consistent pairs more accurately than from swapping pairs, which we designed to drive interference in LTM (Experiments 1 and 2). The error profiles also pointed to proactive interference between swapping pairs in all three experiments. Moreover, participants who had explicit awareness of frequent colour pairings had higher VWM accuracy, and their errors reflected more proactive interference than their unaware counterparts (Experiment 3). This pattern of long-term proactive interference in a VWM task lends support for accounts of VWM chunking that propose LTM offloading.

Chunking as a function of sequence length

Chunking mechanisms are central to several cognitive processes. During the acquisition of visuo-motor sequences, it is commonly reported that these sequences are segmented into chunks leading to more fluid, rapid, and accurate performances. The question of a chunk's storage capacity has been often investigated but little is known about the dynamics of chunk size evolution relative to sequence length. In two experiments, we studied the dynamics and the evolution of a sequence's chunking pattern as a function of sequence length in a non-human primate species (Guinea baboons, Papio papio). Using an operant conditioning device, baboons had to point on a touch screen to a moving target. In Experiment 1, they had to produce repeatedly the same sequence of 4 movements during 2000 trials. In Experiment 2, the sequence was composed of 5 movements and was repeated 4000 times. For both lengths, baboons initially produced small chunks that became fewer and longer with practice. Moreover, the dynamics and the evolution of the chunking pattern varied as a function of sequence length. Finally, with extended practice (i.e., more than 2000 trials), we observed that the mean chunk size reached a plateau indicating that there are fundamental limits to chunking processes that also depend on sequence length. These data therefore provide new empirical evidence for understanding the general properties of chunking mechanisms in sequence learning.

Heteroclinic networks for brain dynamics

Heteroclinic networks are a mathematical concept in dynamic systems theory that is suited to describe metastable states and switching events in brain dynamics. The framework is sensitive to external input and, at the same time, reproducible and robust against perturbations. Solutions of the corresponding differential equations are spatiotemporal patterns that are supposed to encode information both in space and time coordinates. We focus on the concept of winnerless competition as realized in generalized Lotka-Volterra equations and report on results for binding and chunking dynamics, synchronization on spatial grids, and entrainment to heteroclinic motion. We summarize proposals of how to design heteroclinic networks as desired in view of reproducing experimental observations from neuronal networks and discuss the subtle role of noise. The review is on a phenomenological level with possible applications to brain dynamics, while we refer to the literature for a rigorous mathematical treatment. We conclude with promising perspectives for future research.

Brain-imaging evidence for compression of binary sound sequences in human memory

According to the language-of-thought hypothesis, regular sequences are compressed in human memory using recursive loops akin to a mental program that predicts future items. We tested this theory by probing memory for 16-item sequences made of two sounds. We recorded brain activity with functional MRI and magneto-encephalography (MEG) while participants listened to a hierarchy of sequences of variable complexity, whose minimal description required transition probabilities, chunking, or nested structures. Occasional deviant sounds probed the participants' knowledge of the sequence. We predicted that task difficulty and brain activity would be proportional to the complexity derived from the minimal description length in our formal language. Furthermore, activity should increase with complexity for learned sequences, and decrease with complexity for deviants. These predictions were upheld in both fMRI and MEG, indicating that sequence predictions are highly dependent on sequence structure and become weaker and delayed as complexity increases. The proposed language recruited bilateral superior temporal, precentral, anterior intraparietal, and cerebellar cortices. These regions overlapped extensively with a localizer for mathematical calculation, and much less with spoken or written language processing. We propose that these areas collectively encode regular sequences as repetitions with variations and their recursive composition into nested structures.

Can compression take place in working memory without a central contribution of long-term memory?

Information is easier to remember when it is recognized as structured. One explanation for this benefit is that people represent structured information in a compressed form, thus reducing memory load. However, the contribution of long-term memory and working memory to compression are not yet disentangled. Previous work has mostly produced evidence that long-term memory is the main source of compression. In the present work, we reveal two signatures of compression in working memory using a large-scale naturalistic data set from a science museum. Analyzing data from more than 32,000 memory trials, in which people attempted to recall briefly displayed sequences of colors, we examined how the estimated compressibility of each sequence predicted memory performance. Besides finding that compressibility predicted memory performance, we found that greater compressibility of early subsections of sequences predicted better memory for later subsections, and that mis-recalled sequences were simpler than the originals. These findings suggest that (1) more compressibility reduces memory load, leaving space for additional information; (2) memory errors are not random and instead reflect compression gone awry. Together, these findings suggest that compression can take place in working memory. This may enable efficient storage on the spot without direct contributions from long-term memory. However, we also discuss ways long-term memory could explain our findings.

Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task

When exposed to perceptual and motor sequences, people are able to gradually identify patterns within and form a compact internal description of the sequence. One proposal of how sequences can be compressed is people's ability to form chunks. We study people's chunking behavior in a serial reaction time task. We relate chunk representation with sequence statistics and task demands, and propose a rational model of chunking that rearranges and concatenates its representation to jointly optimize for accuracy and speed. Our model predicts that participants should chunk more if chunks are indeed part of the generative model underlying a task and should, on average, learn longer chunks when optimizing for speed than optimizing for accuracy. We test these predictions in two experiments. In the first experiment, participants learn sequences with underlying chunks. In the second experiment, participants were instructed to act either as fast or as accurately as possible. The results of both experiments confirmed our model's predictions. Taken together, these results shed new light on the benefits of chunking and pave the way for future studies on step-wise representation learning in structured domains.

Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients

BACKGROUND

Two years into the COVID-19 pandemic and with more than five million deaths worldwide, the healthcare establishment continues to struggle with every new wave of the pandemic resulting from a new coronavirus variant. Research has demonstrated that there are variations in the symptoms, and even in the order of symptom presentations, in COVID-19 patients infected by different SARS-CoV-2 variants (e.g., Alpha and Omicron). Textual data in the form of admission notes and physician notes in the Electronic Health Records (EHRs) is rich in information regarding the symptoms and their orders of presentation. Unstructured EHR data is often underutilized in research due to the lack of annotations that enable automatic extraction of useful information from the available extensive volumes of textual data.

METHODS

We present the design of a COVID Interface Terminology (CIT), not just a generic COVID-19 terminology, but one serving a specific purpose of enabling automatic annotation of EHRs of COVID-19 patients. CIT was constructed by integrating existing COVID-related ontologies and mining additional fine granularity concepts from clinical notes. The iterative mining approach utilized the techniques of 'anchoring' and 'concatenation' to identify potential fine granularity concepts to be added to the CIT. We also tested the generalizability of our approach on a hold-out dataset and compared the annotation coverage to the coverage obtained for the dataset used to build the CIT.

RESULTS

Our experiments demonstrate that this approach results in higher annotation coverage compared to existing ontologies such as SNOMED CT and Coronavirus Infectious Disease Ontology (CIDO). The final version of CIT achieved about 20% more coverage than SNOMED CT and 50% more coverage than CIDO. In the future, the concepts mined and added into CIT could be used as training data for machine learning models for mining even more concepts into CIT and further increasing the annotation coverage.

CONCLUSION

In this paper, we demonstrated the construction of a COVID interface terminology that can be utilized for automatically annotating EHRs of COVID-19 patients. The techniques presented can identify frequently documented fine granularity concepts that are missing in other ontologies thereby increasing the annotation coverage.

Semantic-based memory-encoding strategy and cognitive stimulation in enhancing cognitive function and daily task performance for older adults with mild cognitive impairment: A pilot non-randomised cluster controlled trial

AIM

To investigate the effectiveness of a semantic-based memory-encoding strategy intervention and cognitive stimulation that enhances function for older adults with mild cognitive impairment.

METHODS

A two-armed single-blind non-randomised cluster controlled trial was conducted. Participants in two centres were allocated to the semantic-based memory-encoding experimental group and those in the other two centres received cognitive stimulation. In both groups, one centre- or community-based session and one home-based session were provided weekly for 10 weeks. Outcome measures included attention, memory and general cognitive function (Word List Memory and Word List Recall of the Consortium to Establish a Registry for the Alzheimer's disease, Digit Span Forwards and Backwards and the Cognistat), and daily task performance (Disability Assessment for Dementia and Lawton Instrumental Activities of Daily Living Scale). They were administered pre- and post-intervention.

RESULTS

Thirty-nine participants completed the study. No significant differences were revealed in the demographic or baseline data. The experimental group showed significant improvements in daily task performance (Disability Assessment for Dementia; p = 0.003), memory outcomes (Word List Recall; p < 0.001), general cognitive function (Cognistat subtests of Memory and Similarity; ps = 0.002 and < 0.001). The cognitive stimulation control group did not show any significant improvement in the measures. Between-group analysis showed significant differences in favour of the experimental group for the outcome measures of the Word List Recall and Cognistat Similarity subtest (ps < 0.001).

CONCLUSIONS

This study shows that the semantic-based memory-encoding strategy is more superior than cognitive stimulation with improvements in attention, memory, general cognitive function and daily task performance for people with a mild cognitive impairment.

TRIAL REGISTRATION

ClinicalTrials.gov Protocol Registration and Results System (NCT02953964).

A language of thought for the mental representation of geometric shapes

In various cultures and at all spatial scales, humans produce a rich complexity of geometric shapes such as lines, circles or spirals. Here, we propose that humans possess a language of thought for geometric shapes that can produce line drawings as recursive combinations of a minimal set of geometric primitives. We present a programming language, similar to Logo, that combines discrete numbers and continuous integration to form higher-level structures based on repetition, concatenation and embedding, and we show that the simplest programs in this language generate the fundamental geometric shapes observed in human cultures. On the perceptual side, we propose that shape perception in humans involves searching for the shortest program that correctly draws the image (program induction). A consequence of this framework is that the mental difficulty of remembering a shape should depend on its minimum description length (MDL) in the proposed language. In two experiments, we show that encoding and processing of geometric shapes is well predicted by MDL. Furthermore, our hypotheses predict additive laws for the psychological complexity of repeated, concatenated or embedded shapes, which we confirm experimentally.

Symbols and mental programs: a hypothesis about human singularity

Natural language is often seen as the single factor that explains the cognitive singularity of the human species. Instead, we propose that humans possess multiple internal languages of thought, akin to computer languages, which encode and compress structures in various domains (mathematics, music, shape…). These languages rely on cortical circuits distinct from classical language areas. Each is characterized by: (i) the discretization of a domain using a small set of symbols, and (ii) their recursive composition into mental programs that encode nested repetitions with variations. In various tasks of elementary shape or sequence perception, minimum description length in the proposed languages captures human behavior and brain activity, whereas non-human primate data are captured by simpler nonsymbolic models. Our research argues in favor of discrete symbolic models of human thought.

Syntactic chunking reveals a core syntactic representation of multi-digit numbers, which is generative and automatic

Representing the base-10 structure of numbers is a challenging cognitive ability, unique to humans, but it is yet unknown how precisely this is done. Here, we examined whether and how literate adults represent a number’s full syntactic structure. In 5 experiments, participants repeated number-word sequences and we systematically varied the order of words within each sequence. Repetition on grammatical sequences (e.g., two hundred ninety-seven) was better than on non-grammatical ones (hundred seven two ninety). We conclude that the participants represented the number’s full syntactic structure and used it to merge number words into chunks in short-term memory. Accuracy monotonously improved for sequences with increasingly longer grammatical segments, up to a limit of ~ 4 words per segment, irrespectively of the number of digits, and worsened thereafter. Namely, short chunks improved memorization, whereas oversized chunks disrupted memorization. This chunk size limit suggests that the chunks are not based on predefined structures, whose size limit is not expected to be so low, but are created ad hoc by a generative process, such as the hierarchical syntactic representation hypothesized in Michael McCloskey’s number-processing model. Chunking occurred even when it disrupted performance, as in the oversized chunks, and even when external cues for chunking were controlled for or were removed. We conclude that the above generative process operates automatically rather than voluntarily. To date, this is the most detailed account of the core representation of the syntactic structure of numbers—a critical aspect of numerical literacy and of the ability to read and write numbers.

Simplicity as a Cue to Probability: Multiple Roles for Simplicity in Evaluating Explanations

People often face the challenge of evaluating competing explanations. One approach is to assess the explanations' relative probabilities-for example, applying Bayesian inference to compute their posterior probabilities. Another approach is to consider an explanation's qualities or "virtues," such as its relative simplicity (i.e., the number of unexplained causes it invokes). The current work investigates how these two approaches are related. Study 1 found that simplicity is used to infer the inputs to Bayesian inference (explanations' priors and likelihoods). Studies 1 and 2 found that simplicity is also used as a direct cue to the outputs of Bayesian inference (the posterior probability of an explanation), such that simplicity affects estimates of posterior probability even after controlling for elicited (Study 1) or provided (Study 2) priors and likelihoods, with simplicity having a larger effect in Study 1, where posteriors are more uncertain and difficult to compute. Comparing Studies 1 and 2 also suggested that simplicity plays additional roles unrelated to approximating probabilities, as reflected in simplicity's effect on how "satisfying" (vs. probable) an explanation is, which remained largely unaffected by the difficulty of computing posteriors. Together, these results suggest that the virtue of simplicity is used in multiple ways to approximate probabilities (i.e., serving as a cue to priors, likelihoods, and posteriors) when these probabilities are otherwise uncertain or difficult to compute, but that the influence of simplicity also goes beyond these roles.

The Evolution of Chunks in Sequence Learning

Chunking mechanisms are central to several cognitive processes and notably to the acquisition of visuo-motor sequences. Individuals segment sequences into chunks of items to perform visuo-motor tasks more fluidly, rapidly, and accurately. However, the exact dynamics of chunking processes in the case of extended practice remain unclear. Using an operant conditioning device, 18 Guinea baboons (Papio papio) produced a fixed sequence of nine movements during 1000 trials by pointing to a moving target on a touch screen. Response times analyses revealed a specific chunking pattern of the sequence for each baboon. More importantly, we found that these patterns evolved during the course of the experiment, with chunks becoming progressively fewer and longer. We identified two chunk reorganization mechanisms: the recombination of preexisting chunks and the concatenation of two distinct chunks into a single one. These results provide new evidence on chunking mechanisms in sequence learning and challenge current models of associative and statistical learning.

Frontal Atrophy and Executive Dysfunction Relate to Complex Numbers Impairment in Progressive Supranuclear Palsy

BACKGROUND

Previous research finds a range of numbers impairments in Parkinsonian syndromes (PS), but has largely focused on how visuospatial impairments impact deficits in basic numerical processes (e.g., magnitude judgments, chunking). Differentiation between these basic functions and more complex numerical processes often utilized in everyday tasks may help elucidate neurocognitive and neuroanatomic bases of numbers deficits in PS.

OBJECTIVE

To test neurocognitive and neuroanatomic correlates of complex numerical processing in PS, we assessed number abilities, neuropsychological performance, and cortical thickness in progressive supranuclear palsy (PSP) and Lewy body spectrum disorders (LBSD).

METHODS

Fifty-six patients (LBSD = 35; PSP = 21) completed a Numbers Battery, including basic and complex numerical tasks. The Mini-Mental State Exam (MMSE), letter fluency (LF), and Judgment of Line Orientation (JOLO) assessed global, executive, and visuospatial functioning respectively. Mann-Whitney U tests compared neuropsychological testing and rank-transformed analysis of covariance (ANCOVA) compared numbers performance between groups while adjusting for demographic variables. Spearman's and partial correlations related numbers performance to neuropsychological tasks. Neuroimaging assessed cortical thickness in disease groups and demographically-matched healthy controls.

RESULTS

PSP had worse complex numbers performance than LBSD (F = 6.06, p = 0.02) but similar basic numbers performance (F = 0.38, p > 0.1), covarying for MMSE and sex. Across syndromes, impaired complex numbers performance was linked to poor LF (rho = 0.34, p = 0.01) but not JOLO (rho = 0.23, p > 0.05). Imaging revealed significant frontal atrophy in PSP compared to controls, which was associated with worse LF and complex numbers performance.

CONCLUSION

PSP demonstrated selective impairments in complex numbers processing compared to LBSD. This complex numerical deficit may relate to executive dysfunction and frontal atrophy.

The association of eye movements and performance accuracy in a novel sight-reading task

The present study investigated how eye movements were associated with performance accuracy during sight-reading. Participants performed a complex span task in which sequences of single quarter note symbols that either enabled chunking or did not enable chunking were presented for subsequent serial recall. In between the presentation of each note, participants sight-read a notated melody on an electric piano in the tempo of 70 bpm. All melodies were unique but contained four types of note pairs: eighth-eighth, eighthquarter, quarter-eighth, quarter-quarter. Analyses revealed that reading with fewer fixations was associated with a more accurate note onset. Fewer fixations might be advantageous for sight-reading as fewer saccades have to be planned and less information has to be integrated. Moreover, the quarter-quarter note pair was read with a larger number of fixations and the eighth-quarter note pair was read with a longer gaze duration. This suggests that when rhythm is processed, additional beats might trigger re-fixations and unconventional rhythmical patterns might trigger longer gazes. Neither recall accuracy nor chunking processes were found to explain additional variance in the eye movement data.

Semantic influence on visual working memory of object identity and location

Does semantic information-in particular, regularities in category membership across objects-influence visual working memory (VWM) processing? We predict that the answer is "yes". Four experiments evaluating this prediction are reported. Experimental stimuli were images of real-world objects arranged in either one or two spatial clusters. On coherent trials, all objects belonging to a cluster also belonged to the same category. On incoherent trials, at least one cluster contained objects from different categories. Experiments using a change-detection paradigm (Experiments 1-3) and an experiment in which participants recalled the locations of objects in a scene (Experiment 4) yielded the same result: participants showed better memory performance on coherent trials than on incoherent trials. Taken as a whole, these experiments provide the best (perhaps only) data to date demonstrating that statistical regularities in semantic category membership improve VWM performance. Because a conventional perspective in cognitive science regards VWM as being sensitive solely to bottom-up visual properties of objects (e.g., shape, color, orientation), our results indicate that cognitive science may need to modify its conceptualization of VWM so that it is closer to "conceptual short-term memory", a short-term memory store representing current stimuli and their associated concepts (Potter, 1993, 2012).

Scaling Laws for Phonotactic Complexity in Spoken English Language Data

Two prominent statistical laws in language and other complex systems are Zipf's law and Heaps' law. We investigate the extent to which these two laws apply to the linguistic domain of phonotactics-that is, to sequences of sounds. We analyze phonotactic sequences with different lengths within words and across word boundaries taken from a corpus of spoken English (Buckeye). We demonstrate that the expected relationship between the two scaling laws can only be attested when boundary spanning phonotactic sequences are also taken into account. Furthermore, it is shown that Zipf's law exhibits both high goodness-of-fit and a high scaling coefficient if sequences of more than two sounds are considered. Our results support the notion that phonotactic cognition employs information about boundary spanning phonotactic sequences.

Mental compression of spatial sequences in human working memory using numerical and geometrical primitives

How does the human brain store sequences of spatial locations? We propose that each sequence is internally compressed using an abstract, language-like code that captures its numerical and geometrical regularities. We exposed participants to spatial sequences of fixed length but variable regularity while their brain activity was recorded using magneto-encephalography. Using multivariate decoders, each successive location could be decoded from brain signals, and upcoming locations were anticipated prior to their actual onset. Crucially, sequences with lower complexity, defined as the minimal description length provided by the formal language, led to lower error rates and to increased anticipations. Furthermore, neural codes specific to the numerical and geometrical primitives of the postulated language could be detected, both in isolation and within the sequences. These results suggest that the human brain detects sequence regularities at multiple nested levels and uses them to compress long sequences in working memory.

Immediate recall of serial numbers with or without multiple item repetitions

Immediate recall of lists of items in random serial order has been examined in thousands of studies throughout the history of experimental psychology. In most studies, though, there have been no repetitions of items within a list, or occasionally a single repetition. These stimuli differ from the common uses of item series, which often include multiple repetitions (e.g., identification numbers; orders of people at a restaurant table). To begin to understand such cases we presented lists that, in some trial blocks, were constructed with no restrictions on repetitions. Specifically, we examined immediate serial recall of visually-presented, nine-digit lists, either spatially separated into three separate groups of three digits (Experiment 1) or undivided (Experiment 2). Many of the lists included single or multiple repetitions of digits, with repeated digits either adjacent or non-adjacent in an unpredictable manner. We assessed theoretical expectations derived from prior research. Effects of repetition were often helpful but, when repetitions favoured a grouping that conflicted with the presented grouping into threes in Experiment 1, repetition was disadvantageous. We suggest a theoretical analysis in which participants can use presented grouping cues or, when those cues are absent, create their own groupings to exploit repetitions among the stimuli.

Benefits and pitfalls of data compression in visual working memory

Data compression in memory is a cognitive process allowing participants to cope with complexity to reduce information load. However, previous studies have not yet considered the hypothesis that this process could also lead to over-simplifying information due to haphazard amplification of the compression process itself. For instance, we could expect that the over-regularized features of a visual scene could produce false recognition of patterns, not because of storage capacity limits but because of an errant compression process. To prompt memory compression in our participants, we used multielement visual displays for which the underlying information varied in compressibility. The compressibility of our material could vary depending on the number of common features between the multi-dimensional objects in the displays. We measured both accuracy and response times by probing memory representations with probes that we hypothesized could modify the participants' representations. We confirm that more compressible information facilitates performance, but a more novel finding is that compression can produce both typical memory errors and lengthened response times. Our findings provide clearer evidence of the forms of compression that participants carry out.

Sensitivity to geometric shape regularity in humans and baboons: A putative signature of human singularity

Among primates, humans are special in their ability to create and manipulate highly elaborate structures of language, mathematics, and music. Here we show that this sensitivity to abstract structure is already present in a much simpler domain: the visual perception of regular geometric shapes such as squares, rectangles, and parallelograms. We asked human subjects to detect an intruder shape among six quadrilaterals. Although the intruder was always defined by an identical amount of displacement of a single vertex, the results revealed a geometric regularity effect: detection was considerably easier when either the base shape or the intruder was a regular figure comprising right angles, parallelism, or symmetry rather than a more irregular shape. This effect was replicated in several tasks and in all human populations tested, including uneducated Himba adults and French kindergartners. Baboons, however, showed no such geometric regularity effect, even after extensive training. Baboon behavior was captured by convolutional neural networks (CNNs), but neither CNNs nor a variational autoencoder captured the human geometric regularity effect. However, a symbolic model, based on exact properties of Euclidean geometry, closely fitted human behavior. Our results indicate that the human propensity for symbolic abstraction permeates even elementary shape perception. They suggest a putative signature of human singularity and provide a challenge for nonsymbolic models of human shape perception.

A compressibility account of the color-sharing bonus in working memory

It has been established that objects sharing color in a visual display can boost working memory. The capacity to encode singletons particularly benefits from the repetition of colors encoded as perceptual groups. We manipulated the algorithmic complexity of visual displays to test whether compressibility of information could account for the color-sharing bonus. This study used a free recall working memory task in which the participants were shown displays of 2 to 8 color items. We examined the influence of set size, complexity, number of same-color clusters and amount of color redundancy. The results showed that the probability of correct recall of the pattern and the proportion of similarity between the pattern and the response decreased with an increase of each manipulated variable, except for color redundancy in terms of probability of correct recall. The model performance of complexity did not differ from that of clusters, but complexity was found more accurate than either set size or color redundancy. The results also showed that similar items were more often recalled adjacently, and complexity correlated strongly with the number of extra color repetitions in the response, suggesting that more complex patterns encouraged the use of information compression. Moreover, color repetitions were more often recalled first and the probability of correct recall for singletons and sub-patterns could be predicted by the compressibility measure. We discuss the potential advantage of using compressibility measures to capture the effects of regularities in visual patterns, in particular to refine analysis of the color-sharing bonus.

Chunking and data compression in verbal short-term memory

Short-term verbal memory is improved when words can be chunked into larger units. Miller (1956) suggested that the capacity of verbal short-term memory is determined by the number of chunks that can be stored in memory, rather than by the number of items or the amount of information. But how does the improvement due to chunking come about, and is memory really determined by the number of chunks? One possibility is that chunking is a form of data compression. It allows more information to be stored in the available capacity. An alternative is that chunking operates primarily by redintegration. Chunks exist only in long-term memory, and enable the corresponding items in short-term memory to be reconstructed more reliably from a degraded trace. We review the data favoring each of these views and discuss the implications of treating chunking as data compression. Contrary to Miller, we suggest that memory capacity is primarily determined both by the amount of information that can be stored but also by the underlying representational vocabulary of the memory system. Given the limitations on the representations that can be stored in verbal short-term memory, chunking can sometimes allow the information capacity of short-term memory to be exploited more efficiently. (202 words).

A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

Working memory capacity can be improved by recoding the memorized information in a condensed form. Here, we tested the theory that human adults encode binary sequences of stimuli in memory using an abstract internal language and a recursive compression algorithm. The theory predicts that the psychological complexity of a given sequence should be proportional to the length of its shortest description in the proposed language, which can capture any nested pattern of repetitions and alternations using a limited number of instructions. Five experiments examine the capacity of the theory to predict human adults' memory for a variety of auditory and visual sequences. We probed memory using a sequence violation paradigm in which participants attempted to detect occasional violations in an otherwise fixed sequence. Both subjective complexity ratings and objective violation detection performance were well predicted by our theoretical measure of complexity, which simply reflects a weighted sum of the number of elementary instructions and digits in the shortest formula that captures the sequence in our language. While a simpler transition probability model, when tested as a single predictor in the statistical analyses, accounted for significant variance in the data, the goodness-of-fit with the data significantly improved when the language-based complexity measure was included in the statistical model, while the variance explained by the transition probability model largely decreased. Model comparison also showed that shortest description length in a recursive language provides a better fit than six alternative previously proposed models of sequence encoding. The data support the hypothesis that, beyond the extraction of statistical knowledge, human sequence coding relies on an internal compression using language-like nested structures.

Individually distinctive features facilitate numerical discrimination of sets of objects in domestic chicks

Day-old domestic chicks approach the larger of two groups of identical objects, but in a 3 vs 4 comparison, their performance is random. Here we investigated whether adding individually distinctive features to each object would facilitate such discrimination. Chicks reared with 7 objects were presented with the operation 1 + 1 + 1 vs 1 + 1 + 1 + 1. When objects were all identical, chicks performed randomly, as expected (Experiment 1). In the remaining experiments, objects differed from one another due to additional features. Chicks succeeded when those features were differently oriented segments (Experiment 2) but failed when the features were arranged to depict individually different face-like displays (Experiment 3). Discrimination was restored if the face-like stimuli were presented upside-down, disrupting global processing (Experiment 4). Our results support the claim that numerical discrimination in 3 vs 4 comparison benefits from the presence of distinctive features that enhance object individuation due to individual processing. Interestingly, when the distinctive features are arranged into upright face-like displays, the process is susceptible to global over local interference due to configural processing. This study was aimed at assessing whether individual object processing affects numerical discrimination. We hypothesise that in humans similar strategies aimed at improving performance at the non-symbolic level may have positive effects on symbolic mathematical abilities.

Examining the limits of Memory-Guided Planning in 3- and 4-year olds

Stored memories may be drawn upon when accomplishing goals. In two experiments, we investigated limits on the ability to use episodic memories to support planning in 3- and 4-year-old children. We designed a new memory-guided planning task that required children to both retrieve memories and apply those memories to accomplish multiple, nested goals. We manipulated the difficulty of the task by varying the number of steps required to achieve the goals, and examined the impact of this manipulation on both memory retrieval and planning. We found that, overall, 4-year-olds outperformed 3-year-olds, but as task difficulty increased, all children made more errors. Analysis of these errors suggested that retrieval and planning processes might impose separate limits on memory-guided planning in early childhood, but that these limits may ease across early childhood.

Working Memory as an Indicator for Comparative Cognition - Detecting Qualitative and Quantitative Differences

Working memory (WM), the representation of information held accessible for manipulation over time, is an essential component of all higher cognitive abilities. It allows for complex behaviors that go beyond simple stimulus-response associations and inflexible behavioral patterns. WM capacity determines how many different pieces of information (items) can be used for these cognitive processes, and in humans, it correlates with fluid intelligence. As such, WM might be a useful tool for comparison of cognition across species. WM can be tested using comparatively simple behavioral protocols, based on operant conditioning, in a multitude of different species. Species-specific contextual variables that influence an animal’s performance on a non-cognitive level are controlled by adapting the WM paradigm. The neuronal mechanisms by which WM emerges in the brain, as sustained neuronal activity, are comparable between the different species studied (mammals and birds), as are the areas of the brain in which WM activity can be measured. Thus WM is comparable between vastly different species within their respective niches, accounting for specific contextual variables and unique adaptations. By approaching the question of “general cognitive abilities” or “intelligence” within the animal kingdom from the perspective of WM, the complexity of the core question at hand is reduced to a fundamental memory system required to allow for complex cognitive abilities. This article argues that measuring WM can be a suitable addition to the toolkit of comparative cognition. By measuring WM on a behavioral level and going beyond behavior to the underlying physiological processes, qualitative and quantitative differences in cognition between different animal species can be identified, free of contextual restraints.

The development of working memory spatialization revealed by using the cave paradigm in a two-alternative spatial choice

When Western participants are asked to keep in mind a sequence of verbal items, they tend to associate the first items to the left and the last items to the right. This phenomenon, known as the spatial-positional association response codes effect, has been interpreted as showing that individuals spatialize the memoranda by creating a left-to-right mental line with them. One important gap in our knowledge concerns the development of this phenomenon: when do Western individuals start organizing their thought from left to right? To answer this question, 274 participants in seven age groups were tested (kindergarten, Grades 1, 2, 3, 4, and 5, and adults). We used a new protocol meant to be child-friendly, which involves associating two caves with two animals using a two-alternative spatial forced choice. Participants had to guess in which cave a specific animal could be hidden. Results showed that it is from Grade 3 on that participants spatialize information in working memory in a left-to-right fashion like adults.

How Do People Code Information in Working Memory When Items Share Features?

Abstract. A large literature suggests that the way we process information is influenced by the categories that we have learned. We examined whether, when we try to uniquely encode items in working memory, the information encoded depends on the other stimuli being simultaneously learned. Participants were required to memorize unknown aliens, presented one at the time, for immediate recognition of their features. Some aliens, called twins, were organized into pairs that shared every feature (nondiscriminative feature) except one (discriminative feature), while some other aliens, called hermits, did not share feature. We reasoned that if people develop unsupervised categories by creating a category for a pair of aliens, we should observe better feature identification performance for nondiscriminative features compared to hermit features, but not compared to discriminative features. On the contrary, if distinguishing features draw attention, we should observe better performance when a discriminative rather than nondiscriminative feature was probed. Overall, our results suggest that when items share features, people code items in working memory by focusing on similarities between items, establishing clusters of items in an unsupervised fashion not requiring feedback on cluster membership.

Chunking and redintegration in verbal short-term memory

Memory for verbal material improves when words form familiar chunks. But how does the improvement due to chunking come about? Two possible explanations are that the input might be actively recoded into chunks, each of which takes up less memory capacity than items not forming part of a chunk (a form of data compression), or that chunking is based on redintegration. If chunking is achieved by redintegration, representations of chunks exist only in long-term memory (LTM) and help to reconstructing degraded traces in short-term memory (STM). In 6 experiments using 2-alternative forced choice recognition and immediate serial recall we find that when chunks are small (2 words) they display a pattern suggestive of redintegration, whereas larger chunks (3 words), show a pattern consistent with data compression. This concurs with previous data showing that there is a cost involved in recoding material into chunks in STM. With smaller chunks this cost seems to outweigh the benefits of recoding words into chunks. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

"Memory compression" effects in visual working memory are contingent on explicit long-term memory

Brady, Konkle, and Alvarez (2009) argued that statistical learning boosts the number of colors that can be held online in visual working memory (WM). They showed that when specific colors are consistently paired together in a WM task, subjects can take optimal advantage of these regularities to recall more colors, an effect they labeled memory compression. They proposed that memory compression is a product of visual statistical learning, an automatic apprehension of statistical regularities that has been shown in prior work to be disconnected from explicit learning. If statistical learning enables an expansion of the number of individuated representations in visual WM, it would require revision of virtually all models of capacity in this online memory system. That said, this provocative claim is inconsistent with multiple studies that have found no improvement in WM performance following numerous repetitions of specific sample displays (e.g., Logie, Brockmole, & Vandenbroucke, 2009; Olson & Jiang, 2004). Here, we replicate the Brady et al. (2009) findings but show that memory compression effects were restricted to subjects who had perfect explicit recall of the color pairs at the end of the study, suggesting that statistical regularities boosted performance by enabling contributions from long-term memory. Thus, while memory compression effects provide an interesting example of the tight collaboration between online and offline memory representations, they do not provide evidence that statistical regularities can augment the number of individuated representations that can be concurrently stored in visual WM. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Complexity can facilitate visual and auditory perception

Visual and auditory inputs vary in complexity. For example, driving in a city versus the country or listening to the radio versus not are experiences that differ in complexity. How does such complexity impact perception? One possibility is that complex stimuli demand resources that exceed attentional or working memory capacities, reducing sensitivity to perceptual changes. Alternatively, complexity may allow for richer and more distinctive representations, increasing such sensitivity. We performed five experiments to test the nature of the relationship between complexity and perceptual sensitivity during movie clip viewing. Experiment 1 revealed higher sensitivity to global changes in audio or video streams for clips with greater complexity, defined both subjectively (judgments by independent coders) and objectively (information-theoretic redundancy). Experiment 2 replicated this finding but found no evidence that it resulted from complexity drawing attention. Experiment 3 provided a boundary condition by showing that change detection was unaffected by complexity when the changes were superimposed on, rather than dispersed throughout, the clips. Experiment 4 suggested that the effect of complexity, at least when defined objectively, was present without the working memory demands of the preceding experiments. Experiment 5 suggested that complexity led to richer representations of the clips, as reflected in enhanced long-term memory. Collectively, these findings show that, despite increasing informational load, complexity can serve to ground and facilitate perceptual sensitivity. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis

Brains exhibit plasticity, multi-scale integration of information, computation and memory, having evolved by specialization of non-neural cells that already possessed many of the same molecular components and functions. The emerging field of basal cognition provides many examples of decision-making throughout a wide range of non-neural systems. How can biological information processing across scales of size and complexity be quantitatively characterized and exploited in biomedical settings? We use pattern regulation as a context in which to introduce the Cognitive Lens-a strategy using well-established concepts from cognitive and computer science to complement mechanistic investigation in biology. To facilitate the assimilation and application of these approaches across biology, we review tools from various quantitative disciplines, including dynamical systems, information theory and least-action principles. We propose that these tools can be extended beyond neural settings to predict and control systems-level outcomes, and to understand biological patterning as a form of primitive cognition. We hypothesize that a cognitive-level information-processing view of the functions of living systems can complement reductive perspectives, improving efficient top-down control of organism-level outcomes. Exploration of the deep parallels across diverse quantitative paradigms will drive integrative advances in evolutionary biology, regenerative medicine, synthetic bioengineering, cognitive neuroscience and artificial intelligence. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

Simulation Training in Medical Education-an Exploration Through Different Theoretical Lenses

Different theoretical frameworks offer specific, but separate, understandings of the same phenomenon. With the increasing use of simulation for training and assessment in medical education, it is vital to consider how different frameworks grant various insights into the pedagogical value of simulation. In this article, the author evaluated three exemplar theoretical frameworks, cultural-historical activity theory, cognitive load theory, and grounded theory, considering their ontological and epistemological stances, their limitations, and their application to simulation training. The greater understanding offered by this article will inform research design and interpretation of results, enabling a more theoretically poised construction of pedagogical techniques.

High-Tempo and Stinky: High Arousal Sound-Odor Congruence Affects Product Memory

The tendency to match different sensory modalities together can be beneficial for marketing. Here we assessed the effect of sound-odor congruence on people's attitude and memory for products of a familiar and unfamiliar brand. Participants smelled high- and low-arousal odors and then saw an advertisement for a product of a familiar or unfamiliar brand, paired with a high- or low-arousal jingle. Participants' attitude towards the advertisement, the advertised product, and the product's brand was measured, as well as memory for the product. In general, no sound-odor congruence effect was found on attitude, irrespective of brand familiarity. However, congruence was found to affect recognition: when a high-arousal odor and a high-arousal sound were combined, participants recognized products faster than in the other conditions. In addition, familiar brands were recognized faster than unfamiliar brands, but only when sound or odor arousal was high. This study provides insight into the possible applications of sound-odor congruence for marketing by demonstrating its potential to influence product memory.