Modeling within-session dynamics of categorical and item-memory mechanisms in pigeons

Past studies have shown that pigeons can learn complex categories and can also remember large numbers of individual objects. In recent work, Cook et al. Psychonomic Bulletin & Review, 28, 548-555, (2021) provided evidence that pigeons may use a dynamic combination of both category-based information and item-specific memorization to solve a categorical variation of the mid-session reversal (MSR) task, which is an influential task for exploring the nature of temporally organized behaviors in animals. To provide greater insight into these pigeons' behaviors, in this article we developed and investigated different computational models and their variations to account for these data. Of these, two models emerged as good candidates. One was a multinomial-processing-tree categorization/memory model, formalizing the two-process mechanism initially proposed by Cook et al. Psychonomic Bulletin & Review, 28, 548-555, (2021). The second was a new object/time-coding model, which posits the storage of object-specific memories with an additional within-session time code and assumes that a basic stimulus generalization process underlies the pigeons' choice behavior. Both provided high-quality fits to the published sets of training and transfer data collected in the categorical MSR task. These computational efforts give deeper insights into the theoretical mechanisms underlying the temporal and sequential structure of behavior in animals and stimulate future empirical research further revealing the organization of the pigeons' cognitive processes.

Estimating the human bottleneck for contact tracing

The SARS-CoV-2 pandemic has highlighted the importance of contact tracing for epidemiological mitigation. Contact tracing interviews (CTIs) typically rely on episodic memory, which is prone to decline over time. Here, we provide a quantitative estimate of reporting decline for age- and gender-representative samples from the United Kingdom and Germany, emulating >15,000 CTIs. We find that the number of reported contacts declines as a power function of recall delay and is significantly higher for younger subjects and for those who used memory aids, such as a scheduler. We further find that these factors interact with delay: Older subjects and those who made no use of memory aids have steeper decline functions. These findings can inform epidemiological modeling and policies in the context of infectious diseases.

Reconciling categorization and memory via environmental statistics

How people represent categories and how those representations change over time is a basic question about human cognition. Previous research has demonstrated that people categorize objects by comparing them to category prototypes in early stages of learning but consider the individual exemplars within each category in later stages. However, these results do not seem consistent with findings in the memory literature showing that it becomes increasingly easier to access representations of general knowledge than representations of specific items over time. Why would one rely more on exemplar-based representations in later stages of categorization when it is more difficult to access these exemplars in memory? To reconcile these incongruities, our study proposed that previous findings on categorization are a result of human participants adapting to a specific experimental environment, in which the probability of encountering an object stays uniform over time. In a more realistic environment, however, one would be less likely to encounter the same object if a long time has passed. Confirming our hypothesis, we demonstrated that under environmental statistics identical to typical categorization experiments the advantage of exemplar-based categorization over prototype-based categorization increases over time, replicating previous research in categorization. In contrast, under realistic environmental statistics simulated by our experiments the advantage of exemplar-based categorization over prototype-based categorization decreases over time. A second set of experiments replicated our results, while additionally demonstrating that human categorization is sensitive to the category structure presented to the participants. These results provide converging evidence that human categorization adapts appropriately to environmental statistics.

Recognition memory decisions made with short- and long-term retrieval

In the present research, we produce a coherent account of the storage and retrieval processes in short- and long-term event memory, and long-term knowledge, that produce response accuracy and response time in a wide variety of conditions in our studies of recognition memory. Two to nine pictures are studied sequentially followed by a target or foil test picture in four conditions used in Nosofsky et al. Journal of Experimental Psychology: Learning, Memory, and Cognition, 47, 316-342, (2021) and in our new paradigm: VM: target and foil responses to a given stimulus change from trial to trial; CM: the responses do not change from trial to trial; AN: every trial uses new stimuli; MIXED: combinations of VM, CN, and AN occur on each trial. In the new paradigm a given picture is equally often tested as old or new, but only in CM is the response key the same and learnable. Our model has components that have appeared in a variety of prior accounts, including learning and familiarity, but are given support by our demonstration that accuracy and response time data from a large variety of conditions can be predicted by these processes acting together, with parameter values that largely are unchanged. A longer version of this article, containing information not found here due to space, is available online  https://doi.org/10.31234/osf.io/h8msp .The avalibility of the data (supplement materials), info and link is attached at the end section ( https://psyarxiv.com/h8msp .).

Modeling the continuous recognition paradigm to determine how retrieval can impact subsequent retrievals

There are several ways in which retrieval during a memory test can harm memory: (a) retrieval can cause an increase in interference due to the storage of additional information (i.e., item-noise); (b) retrieval can decrease accessibility to studied items due to context drift; and (c) retrieval can result in a trade in accuracy for speed as testing progresses. While these mechanisms produce similar outcomes in a study-test paradigm, they are dissociated in the 'continuous' recognition paradigm, where items are presented continuously and a participant's task is to detect a repeat of an item. In this paradigm, context drift results in worse performance with increasing study-test lag (the lag effect), whereas increasing item-noise is evident in a decrease in performance for later test trials in the sequence (the test position effect [TPE]). In the present investigation, we measured the influences of item-noise, context drift, and decision-related factors in a novel continuous recognition dataset using variants of the Osth et al. (2018) global matching model. We fit both choice and response times at the single trial level using state-of-the-art hierarchical Bayesian methods while incorporating crucial amendments to the modeling framework, including multiple context scales and sequential effects. We found that item-noise was responsible for producing the TPE, context drift decreased the magnitude of the TPE (by diminishing the impact of item-noise), and speed-accuracy changes had some minor effects that varied across participants.

Mouse Behavior on the Trial-Unique Nonmatching-to-Location (TUNL) Touchscreen Task Reflects a Mixture of Distinct Working Memory Codes and Response Biases

The trial-unique nonmatching to location (TUNL) touchscreen task shows promise as a translational assay of working memory (WM) deficits in rodent models of autism, ADHD, and schizophrenia. However, the low-level neurocognitive processes that drive behavior in the TUNL task have not been fully elucidated. In particular, it is commonly assumed that the TUNL task predominantly measures spatial WM dependent on hippocampal pattern separation, but this proposition has not previously been tested. In this project, we tested this question using computational modeling of behavior from male and female mice performing the TUNL task (N = 163 across three datasets; 158,843 trials). Using this approach, we empirically tested whether TUNL behavior solely measured retrospective WM, or whether it was possible to deconstruct behavior into additional neurocognitive subprocesses. Overall, contrary to common assumptions, modeling analyses revealed that behavior on the TUNL task did not primarily reflect retrospective spatial WM. Instead, behavior was best explained as a mixture of response strategies, including both retrospective WM (remembering the spatial location of a previous stimulus) and prospective WM (remembering an anticipated future behavioral response) as well as animal-specific response biases. These results suggest that retrospective spatial WM is just one of a number of cognitive subprocesses that contribute to choice behavior on the TUNL task. We suggest that findings can be understood within a resource-rational framework, and use computational model simulations to propose several task-design principles that we predict will maximize spatial WM and minimize alternative behavioral strategies in the TUNL task.SIGNIFICANCE STATEMENT Touchscreen tasks represent a paradigm shift for assessment of cognition in nonhuman animals by automating large-scale behavioral data collection. Their main relevance, however, depends on the assumption of functional equivalence to cognitive domains in humans. The trial-unique, delayed nonmatching to location (TUNL) touchscreen task has revolutionized the study of rodent spatial working memory. However, its assumption of functional equivalence to human spatial working memory is untested. We leveraged previously untapped single-trial TUNL data to uncover a novel set of hierarchically ordered cognitive processes that underlie mouse behavior on this task. The strategies used demonstrate multiple cognitive approaches to a single behavioral outcome and the requirement for more precise task design and sophisticated data analysis in interpreting rodent spatial working memory.

When Normal is Not Normal: A Theory of the Non-Linear and Discontinuous Process of Desired Change and its Managerial Implications

Desirable change may appear chaotic, slow, or not sustainable. We may expect linear, continuous change, but it eludes us. Measurement and statistical analysis about behavior change often requires data showing continuity and having normal (i.e., Gaussian) distributions. When we encounter phenomenon that does not fit this expectation, we seek to transform the data to render it compatible with our method of analysis. We move from actual behavior to perception of it through surveys or transformations of the data. We believe this ignores “naturally” occurring data and what it says. Such techniques are convenient for statistics but may hide important features of the real phenomenon. Furthermore, desired behavior change is often nonlinear with a power curve distribution of the data. We explain why this occurs. We suggest how research and practice would be improved by using theories and methods that incorporate properties of non-normal distributions and discontinuous emergence.

How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach

Models of free recall describe free recall initiation as a decision-making process in which items compete to be retrieved. Recently, Osth and Farrell (Psychological Review, 126, 578–609, 2019) applied evidence accumulation models to complete RT distributions and serial positions of participants’ first recalls in free recall, which resulted in some novel conclusions about primacy and recency effects. Specifically, the results of the modeling favored an account in which primacy was due to reinstatement of the start-of-the-list, and recency was found to be exponential in shape. In this work, we examine what happens when participants are given alternative recall instructions. Prior work has demonstrated weaker primacy and greater recency when fewer items are required to report (Ward & Tan, Memory & Cognition, 2019), and a key question is whether this change in instructions qualitatively changes the nature of the recall process, or merely changes the parameters of the recall competition. We conducted an experiment where participants studied six- or 12-item lists and were post-cued as to whether to retrieve a single item, or as many items as possible. Subsequently, we applied LBA models with various assumptions about primacy and recency, implemented using hierarchical Bayesian techniques. While greater recency was observed when only one item was required for output, the model selection did not suggest that there were qualitative differences between the two conditions. Specifically, start-of-list reinstatement and exponential recency functions were favored in both conditions.

The warning stimulus as retrieval cue: The role of associative memory in temporal preparation

In a warned reaction time task, the warning stimulus (S1) initiates a process of temporal preparation, which promotes a speeded response to the impending target stimulus (S2). According to the multiple trace theory of temporal preparation (MTP), participants learn the timing of S2 by storing a memory trace on each trial, which contains a temporal profile of the events on that trial. On each new trial, S1 serves as a retrieval cue that implicitly and associatively activates memory traces created on earlier trials, which jointly drive temporal preparation for S2. The idea that S1 assumes this role as a retrieval cue was tested across eight experiments, in which two different S1s were associated with two different distributions of S1-S2 intervals: one with predominantly short and one with predominantly long intervals. Experiments differed regarding the S1 features that made up a pair, ranging from highly distinct (e.g., tone and flash) to more similar (e.g., red and green flash) and verbal (i.e., "short" vs "long"). Exclusively for pairs of highly distinct S1s, the results showed that the S1 cue modified temporal preparation, even in participants who showed no awareness of the contingency. This cueing effect persisted in a subsequent transfer phase, in which the contingency between S1 and the timing of S2 was broken - a fact participants were informed of in advance. Together, these findings support the role of S1 as an implicit retrieval cue, consistent with MTP.

Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons

Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. The diverse excitabilities of an individual neuron can be reproduced by a fractional-order biophysical model that preserves several previous memory effects. However, it is not completely clear to what extent the fractional-order dynamics changes the firing properties of excitable cells. In this article, we investigate the alternation of spiking and bursting phenomena of an uncoupled and coupled fractional leech-heart (L-H) neurons. We show that a complete graph of heterogeneous de-synchronized neurons in the backdrop of diverse memory settings (a mixture of integer and fractional exponents) can eventually lead to bursting with the formation of cluster synchronization over a certain threshold of coupling strength, however, the uncoupled L-H neurons cannot reveal bursting dynamics. Using the stability analysis in fractional domain, we demarcate the parameter space where the quiescent or steady-state emerges in uncoupled L-H neuron. Finally, a reduced-order model is introduced to capture the activities of the large network of fractional-order model neurons.

Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes

Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence classes. For this purpose, we first modify the PS model to accommodate imitating the emergence of equivalence relations. Later, we formulate the SE formation through the matching-to-sample (MTS) procedure. The proposed version of PS model, called the equivalence projective simulation (EPS) model, is able to act within a varying action set and derive new relations without receiving feedback from the environment. To the best of our knowledge, it is the first time that the field of equivalence theory in behavior analysis has been linked to an artificial agent in a machine learning context. This model has many advantages over existing neural network models. Briefly, our EPS model is not a black box model, but rather a model with the capability of easy interpretation and flexibility for further modifications. To validate the model, some experimental results performed by prominent behavior analysts are simulated. The results confirm that the EPS model is able to reliably simulate and replicate the same behavior as real experiments in various settings, including formation of equivalence relations in typical participants, nonformation of equivalence relations in language-disabled children, and nodal effect in a linear series with nodal distance five. Moreover, through a hypothetical experiment, we discuss the possibility of applying EPS in further equivalence theory research.

Time-conjunctive representations of future events

It is widely accepted that people can predict the relative imminence of future events. However, it is unknown whether the timing of future events is represented using only a "strength-like" estimate or if future events are represented conjunctively with their position on a mental timeline. We examined how people judge temporal relationships among anticipated future events using the novel Judgment of Anticipated Co-Occurrence (JACO) task. Participants were initially trained on a stream of letters sampled from a probabilistically repeating sequence. During test trials, the stream was interrupted with pairs of probe letters and the participants' task was to choose the probe letter they expected to appear in the stream during a lagged target window 4-6 items (4.3-8.5 s) in the future. Participants performed above chance as they gained experience with the task. Because the correct item was sometimes the more imminent probe letter and other times the less imminent probe letter, these results rule out the possibility that participants relied solely on thresholding a strength-like estimate of temporal imminence. Rather, these results suggest that participants held (1) temporally organized predictions of the future letters in the stream, (2) a temporal estimate of the lagged target window, and (3) some means to compare the two and evaluate their temporal alignment. Response time increased with the lag to the more imminent probe letter, suggesting that participants accessed the future sequentially in a manner that mirrors scanning processes previously proposed to operate on memory representations in the short-term judgment of recency task.

Firing activities of a fractional-order FitzHugh-Rinzel bursting neuron model and its coupled dynamics

Fractional-order dynamics of excitable systems can be physically described as a memory dependent phenomenon. It can produce diverse and fascinating oscillatory patterns for certain types of neuron models. To address these characteristics, we consider a nonlinear fast-slow FitzHugh-Rinzel (FH-R) model that exhibits elliptic bursting at a fixed set of parameters with a constant input current. The generalization of this classical order model provides a wide range of neuronal responses (regular spiking, fast-spiking, bursting, mixed-mode oscillations, etc.) in understanding the single neuron dynamics. So far, it is not completely understood to what extent the fractional-order dynamics may redesign the firing properties of excitable systems. We investigate how the classical order system changes its complex dynamics and how the bursting changes to different oscillations with stability and bifurcation analysis depending on the fractional exponent (0 < α ≤ 1). This occurs due to the memory trace of the fractional-order dynamics. The firing frequency of the fractional-order FH-R model is less than the classical order model, although the first spike latency exists there. Further, we investigate the responses of coupled FH-R neurons with small coupling strengths that synchronize at specific fractional-orders. The interesting dynamical characteristics suggest various neurocomputational features that can be induced in this fractional-order system which enriches the functional neuronal mechanisms.

Relation between centro-parietal positivity and diffusion model parameters in both perceptual and memory-based decision making

Several studies have suggested that the centro-parietal positivity (CPP), an EEG potential occurring approximately 500 ms post-stimulus, reflects the accumulation of evidence for making a decision. Yet, most previous studies of the CPP focused exclusively on perceptual decisions with very simple stimuli. In this study, we examined how the dynamics of the CPP depended on the type of decision being made, and whether its slope was related to parameters of an accumulator model of decision making. We show initial evidence that memory- and perceptual decisions about carefully-controlled face stimuli exhibit similar dynamics, but offset by a time difference in decision onset. Importantly, the individual-trial slopes of the CPP are related to the accumulator model's drift parameter. These findings help to further understand the role of the CPP across different kinds of decisions.

Two distinct mechanisms of selection in working memory: Additive last-item and retro-cue benefits

In working memory research, individual items are sometimes said to be in the "focus of attention". According to one view, this occurs for the last item in a sequentially presented list (last-item benefit). According to a second view, this occurs when items are externally cued during the retention interval (retro-cue benefit). We investigated both phenomena at the same time to determine whether both result from the same cognitive mechanisms. If that were the case, retro-cue benefits should be reduced when the retro-cue is directed to the item that already benefits from being presented last. We measured speed-accuracy-tradeoff functions with the response-deadline paradigm to measure retrieval dynamics in a short-term recognition task. Across three experiments, we found that retro-cues benefited the last item and other items to the same extent. The additivity of the last-item benefit and the retro-cue benefit points towards the co-existence of at least two distinct forms of attentional prioritization in working memory.

Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making

A robust finding in recognition memory is that performance declines monotonically across test trials. Despite the prevalence of this decline, there is a lack of consensus on the mechanism responsible. Three hypotheses have been put forward: (1) interference is caused by learning of test items (2) the test items cause a shift in the context representation used to cue memory and (3) participants change their speed-accuracy thresholds through the course of testing. We implemented all three possibilities in a combined model of recognition memory and decision making, which inherits the memory retrieval elements of the Osth and Dennis (2015) model and uses the diffusion decision model (DDM: Ratcliff, 1978) to generate choice and response times. We applied the model to four datasets that represent three challenges, the findings that: (1) the number of test items plays a larger role in determining performance than the number of studied items, (2) performance decreases less for strong items than weak items in pure lists but not in mixed lists, and (3) lexical decision trials interspersed between recognition test trials do not increase the rate at which performance declines. Analysis of the model's parameter estimates suggests that item interference plays a weak role in explaining the effects of recognition testing, while context drift plays a very large role. These results are consistent with prior work showing a weak role for item noise in recognition memory and that retrieval is a strong cause of context change in episodic memory.

Memory as Perception of the Past: Compressed Time inMind and Brain

In the visual system retinal space is compressed such that acuity decreases further from the fovea. Different forms of memory may rely on a compressed representation of time, manifested as decreased accuracy for events that happened further in the past. Neurophysiologically, "time cells" show receptive fields in time. Analogous to the compression of visual space, time cells show less acuity for events further in the past. Behavioral evidence suggests memory can be accessed by scanning a compressed temporal representation, analogous to visual search. This suggests a common computational language for visual attention and memory retrieval. In this view, time functions like a scaffolding that organizes memories in much the same way that retinal space functions like a scaffolding for visual perception.

On stability of fixed points and chaos in fractional systems

In this paper, we propose a method to calculate asymptotically period two sinks and define the range of stability of fixed points for a variety of discrete fractional systems of the order 0<α<2. The method is tested on various forms of fractional generalizations of the standard and logistic maps. Based on our analysis, we make a conjecture that chaos is impossible in the corresponding continuous fractional systems.

Mimicking the brain functions of learning, forgetting and explicit/implicit memories with SrTiO3-based memristive devices

To implement the complex brain functions of learning, forgetting and memory in a single electronic device is very advantageous for realizing artificial intelligence. As a proof of concept, memristive devices with a simple structure of Ni/Nb-SrTiO₃/Ti were investigated in this work. The functions of learning, forgetting and memory were successfully mimicked using the memristive devices, and the "time-saving" effect of implicit memory was also demonstrated. The physics behind the brain functions is simply the modulation of the Schottky barrier at the Ni/SrTiO₃ interface. The realization of various psychological functions in a single device simplifies the construction of the artificial neural network and facilitates the advent of artificial intelligence.

Item frequency in probe-recognition memory search: Converging evidence for a role of item-response learning

In short-term probe-recognition tasks, observers make speeded old-new recognition judgments for items that are members of short lists. However, long-term memory (LTM) for items from previous lists influences current-list performance. The current experiment pursued the nature of these long-term influences-in particular, whether they emerged from item-familiarity or item-response-learning mechanisms. Subjects engaged in varied-mapping (VM) and consistent-mapping (CM) short-term probe-recognition tasks (e.g., Schneider & Shiffrin, Psychological Review, 84, 1-66, 1977). The key manipulation was to vary the frequency with which individual items were presented across trials. We observed a striking dissociation: Whereas increased presentation frequency led to benefits in performance for both old and new test probes in CM search, it resulted in interference effects for both old and new test probes in VM search. Formal modeling suggested that a form of item-response learning took place in both conditions: Each presentation of a test probe led to the storage of that test probe-along with its associated "old" or "new" response-as an exemplar in LTM. These item-response pairs were retrieved along with current-list items in driving observers' old-- recognition judgments. We conclude that item-response learning is a core component of the LTM mechanisms that influence CM and VM memory search.

Asymmetric Compression of Representational Space for Object Animacy Categorization under Degraded Viewing Conditions

Animacy is a robust organizing principle among object category representations in the human brain. Using multivariate pattern analysis methods, it has been shown that distance to the decision boundary of a classifier trained to discriminate neural activation patterns for animate and inanimate objects correlates with observer RTs for the same animacy categorization task [Ritchie, J. B., Tovar, D. A., & Carlson, T. A. Emerging object representations in the visual system predict reaction times for categorization. PLoS Computational Biology, 11, e1004316, 2015; Carlson, T. A., Ritchie, J. B., Kriegeskorte, N., Durvasula, S., & Ma, J. Reaction time for object categorization is predicted by representational distance. Journal of Cognitive Neuroscience, 26, 132–142, 2014]. Using MEG decoding, we tested if the same relationship holds when a stimulus manipulation (degradation) increases task difficulty, which we predicted would systematically decrease the distance of activation patterns from the decision boundary and increase RTs. In addition, we tested whether distance to the classifier boundary correlates with drift rates in the linear ballistic accumulator [Brown, S. D., & Heathcote, A. The simplest complete model of choice response time: Linear ballistic accumulation. Cognitive Psychology, 57, 153–178, 2008]. We found that distance to the classifier boundary correlated with RT, accuracy, and drift rates in an animacy categorization task. Split by animacy, the correlations between brain and behavior were sustained longer over the time course for animate than for inanimate stimuli. Interestingly, when examining the distance to the classifier boundary during the peak correlation between brain and behavior, we found that only degraded versions of animate, but not inanimate, objects had systematically shifted toward the classifier decision boundary as predicted. Our results support an asymmetry in the representation of animate and inanimate object categories in the human brain.

Sequence-sensitive exemplar and decision-bound accounts of speeded-classification performance in a modified Garner-tasks paradigm

Among the most fundamental results in the area of perceptual classification are the "correlated facilitation" and "filtering interference" effects observed in Garner's (1974) speeded categorization tasks: In the case of integral-dimension stimuli, relative to a control task, single-dimension classification is faster when there is correlated variation along a second dimension, but slower when there is orthogonal variation that cannot be filtered out (e.g., by attention). These fundamental effects may result from participants' use of a trial-by-trial bypass strategy in the control and correlated tasks: The observer changes the previous category response whenever the stimulus changes, and maintains responses if the stimulus repeats. Here we conduct modified versions of the Garner tasks that eliminate the availability of a pure bypass strategy. The fundamental facilitation and interference effects remain, but are still largely explainable in terms of pronounced sequential effects in all tasks. We develop sequence-sensitive versions of exemplar-retrieval and decision-bound models aimed at capturing the detailed, trial-by-trial response-time distribution data. The models combine assumptions involving: (i) strengthened perceptual/memory representations of stimuli that repeat across consecutive trials, and (ii) a bias to change category responses on trials in which the stimulus changes. These models can predict our observed effects and provide a more complete account of the underlying bases of performance in our modified Garner tasks.

Resources masquerading as slots: Flexible allocation of visual working memory

Whether the capacity of visual working memory is better characterized by an item-based or a resource-based account continues to be keenly debated. Here, we propose that visual working memory is a flexible resource that is sometimes deployed in a slot-like manner. We develop a computational model that can either encode all items in a memory set, or encode only a subset of those items. A fixed-capacity mnemonic resource is divided among the items in memory. When fewer items are encoded, they are each remembered with higher fidelity, but at the cost of having to rely on an explicit guessing process when probed about an item that is not in memory. We use the new model to test the prediction that participants will more often encode the entire set of items when the demands on memory are predictable.

Memory strength versus memory variability in visual change detection

Observers made change-detection judgments for colored squares in a paradigm that manipulated the retention interval, the magnitude of change, and objective change probability. The probability of change judgments increased across the retention interval for “same” and “small-change” test items but stayed the same or decreased for “large-change” and “far” test items. A variety of formal models were fitted to the individual-subject data. The modeling results provided evidence that, beyond changes in visual-memory precision, there were decreases in memory strength of individual study items across the retention interval. In addition, the modeling results provided evidence of a zero-information, absence-of-memory state that required guessing. The data were not sufficiently strong to sharply distinguish whether the losses in memory strength across the retention interval were continuous in nature or all-or-none. The authors argue that the construct of memory strength as distinct from memory variability is an important component of the nature of forgetting from visual working memory.

Subdiffusive dynamics of bump attractors: mechanisms and functional roles

Bump attractors are localized activity patterns that can self-sustain after stimulus presentation, and they are regarded as the neural substrate for a host of perceptual and cognitive processes. One of the characteristic features of bump attractors is that they are neutrally stable, so that noisy inputs cause them to drift away from their initial locations, severely impairing the accuracy of bump location-dependent neural coding. Previous modeling studies of such noise-induced drifting activity of bump attractors have focused on normal diffusive dynamics, often with an assumption that noisy inputs are uncorrelated. Here we show that long-range temporal correlations and spatial correlations in neural inputs generated by multiple interacting bumps cause them to drift in an anomalous subdiffusive way. This mechanism for generating subdiffusive dynamics of bump attractors is further analyzed based on a generalized Langevin equation. We demonstrate that subdiffusive dynamics can significantly improve the coding accuracy of bump attractors, since the variance of the bump displacement increases sublinearly over time and is much smaller than that of normal diffusion. Furthermore, we reanalyze existing psychophysical data concerning the spread of recalled cue position in spatial working memory tasks and show that its variance increases sublinearly with time, consistent with subdiffusive dynamics of bump attractors. Based on the probability density function of bump position, we also show that the subdiffusive dynamics result in a long-tailed decay of firing rate, greatly extending the duration of persistent activity.

Familiarity and categorization processes in memory search

A fundamental distinction in tasks of memory search is whether items receive varied mappings (targets and distractors switch roles across trials) or consistent mappings (targets and distractors never switch roles). The type of mapping often produces markedly different performance patterns, but formal memory-based models that account quantitatively for detailed aspects of the results have not yet been developed and evaluated. Experiments were conducted to test a modern exemplar-retrieval model on its ability to account for memory-search performance involving a wide range of memory-set sizes in both varied-mapping (VM) and consistent-mapping (CM) probe-recognition tasks. The model formalized the idea that both familiarity-based and categorization-based processes operate. The model was required to fit detailed response-time (RT) distributions of individual, highly practiced subjects. A key manipulation involved the repetition of negative probes across trials. This manipulation produced a dramatic dissociation: False-alarm rates increased and correct-rejection RTs got longer in VM, but not in CM. The qualitative pattern of results and modeling analyses provided evidence for a strong form of categorization-based processing in CM, in which observers made use of the membership of negative probes in the "new" category to make old-new recognition decisions.

Working memory retrieval as a decision process

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.

Real and implied motion at the center of gaze

Even though the dynamicity of our environment is a given, much of what we know on fixation selection comes from studies of static scene viewing. We performed a direct comparison of fixation selection on static and dynamic visual stimuli and investigated how far identical mechanisms drive these. We recorded eye movements while participants viewed movie clips of natural scenery and static frames taken from the same movies. Both were presented in the same high spatial resolution (1080 × 1920 pixels). The static condition allowed us to check whether local movement features computed from movies are salient even when presented as single frames. We observed that during the first second of viewing, movement and static features are equally salient in both conditions. Furthermore, predictability of fixations based on movement features decreased faster when viewing static frames as compared with viewing movie clips. Yet even during the later portion of static-frame viewing, the predictive value of movement features was still high above chance. Moreover, we demonstrated that, whereas the sets of movement and static features were statistically dependent within these sets, respectively, no dependence was observed between the two sets. Based on these results, we argue that implied motion is predictive of fixation similarly to real movement and that the onset of motion in natural stimuli is more salient than ongoing movement is. The present results allow us to address to what extent and when static image viewing is similar to the perception of a dynamic environment.

Working memory retrieval differences between medial temporal lobe epilepsy patients and controls: a three memory layer approach

Multi-store models of working memory (WM) have given way to more dynamic approaches that conceive WM as an activated subset of long-term memory (LTM). The resulting framework considers that memory representations are governed by a hierarchy of accessibility. The activated part of LTM holds representations in a heightened state of activation, some of which can reach a state of immediate accessibility according to task demands. Recent neuroimaging studies have studied the neural basis of retrieval information with different states of accessibility. It was found that the medial temporal lobe (MTL) was involved in retrieving information within immediate access store and outside this privileged zone. In the current study we further explored the contribution of MTL to WM retrieval by analyzing the consequences of MTL damage to this process considering the state of accessibility of memory representations. The performance of a group of epilepsy patients with left hippocampal sclerosis in a 12-item recognition task was compared with that of a healthy control group. We adopted an embedded model of WM that distinguishes three components: the activated LTM, the region of direct access, and a single-item focus of attention. Groups did not differ when retrieving information from single-item focus, but patients were less accurate retrieving information outside focal attention, either items from LTM or items expected to be in the WM range. Analyses focused on items held in the direct access buffer showed that consequences of MTL damage were modulated by the level of accessibility of memory representations, producing a reduced capacity.

Discrete-slots models of visual working-memory response times

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for "slots plus resources" when memory set size is very small.

Quantitative linking hypotheses for infant eye movements

The study of cognitive development hinges, largely, on the analysis of infant looking. But analyses of eye gaze data require the adoption of linking hypotheses: assumptions about the relationship between observed eye movements and underlying cognitive processes. We develop a general framework for constructing, testing, and comparing these hypotheses, and thus for producing new insights into early cognitive development. We first introduce the general framework--applicable to any infant gaze experiment--and then demonstrate its utility by analyzing data from a set of experiments investigating the role of attentional cues in infant learning. The new analysis uncovers significantly more structure in these data, finding evidence of learning that was not found in standard analyses and showing an unexpected relationship between cue use and learning rate. Finally, we discuss general implications for the construction and testing of quantitative linking hypotheses. MATLAB code for sample linking hypotheses can be found on the first author's website.

The structure of short-term memory scanning: an investigation using response time distribution models

A classic question in cognitive psychology concerns the nature of memory search in short-term recognition. Despite its long history of investigation, however, there is still no consensus on whether memory search takes place serially or in parallel or is based on global access. In the present investigation, we formalize a variety of models designed to account for detailed response time distribution data in the classic Sternberg (Science 153: 652-654, 1966) memory-scanning task. The models vary in their mental architectures (serial exhaustive, parallel self-terminating, and global access). Furthermore, the component processes within the architectures that make match/mismatch decisions are formalized as linear ballistic accumulators (LBAs). In fast presentation rate conditions, the parallel and global access models provide far better accounts of the data than does the serial model. LBA drift rates are found to depend almost solely on the lag between study items and test probes, whereas response thresholds change with memory set size. Under slow presentation rate conditions, even simple versions of the serial-exhaustive model provide accounts of the data that are as good as those of the parallel and global access models. We provide alternative interpretations of the results in our General Discussion.