Neural substrates of cognitive capacity limitations

A probabilistic palimpsest model of visual short-term memory

Working memory plays a key role in cognition, and yet its mechanisms remain much debated. Human performance on memory tasks is severely limited; however, the two major classes of theory explaining the limits leave open questions about key issues such as how multiple simultaneously-represented items can be distinguished. We propose a palimpsest model, with the occurrent activity of a single population of neurons coding for several multi-featured items. Using a probabilistic approach to storage and recall, we show how this model can account for many qualitative aspects of existing experimental data. In our account, the underlying nature of a memory item depends entirely on the characteristics of the population representation, and we provide analytical and numerical insights into critical issues such as multiplicity and binding. We consider representations in which information about individual feature values is partially separate from the information about binding that creates single items out of multiple features. An appropriate balance between these two types of information is required to capture fully the different types of error seen in human experimental data. Our model provides the first principled account of misbinding errors. We also suggest a specific set of stimuli designed to elucidate the representations that subjects actually employ.

Humans can remember several visual items for a few seconds and recall them; however, performance deteriorates surprisingly quickly with the number of items that must be stored. Along with increasingly inaccurate recollection, subjects make association errors, sometimes apparently recalling the wrong item altogether. No current model accounts for these data fully. We discuss a simple model that focuses attention on the population representations that are putatively involved, and thereby on limits to the amount of information that can be stored and recalled. We use theoretical and numerical methods to examine the characteristics and performance of our model.

Target templates: the precision of mental representations affects attentional guidance and decision-making in visual search

When people look for things in the environment, they use target templates-mental representations of the objects they are attempting to locate-to guide attention and to assess incoming visual input as potential targets. However, unlike laboratory participants, searchers in the real world rarely have perfect knowledge regarding the potential appearance of targets. In seven experiments, we examined how the precision of target templates affects the ability to conduct visual search. Specifically, we degraded template precision in two ways: 1) by contaminating searchers' templates with inaccurate features, and 2) by introducing extraneous features to the template that were unhelpful. We recorded eye movements to allow inferences regarding the relative extents to which attentional guidance and decision-making are hindered by template imprecision. Our findings support a dual-function theory of the target template and highlight the importance of examining template precision in visual search.

The frontoparietal control system: a central role in mental health

Recent findings suggest the existence of a frontoparietal control system consisting of flexible hubs that regulate distributed systems (e.g., visual, limbic, motor) according to current task goals. A growing number of studies are reporting alterations of this control system across a striking range of mental diseases. We suggest this may reflect a critical role for the control system in promoting and maintaining mental health. Specifically, we propose that this system implements feedback control to regulate symptoms as they arise (e.g., excessive anxiety reduced via regulation of amygdala), such that an intact control system is protective against a variety of mental illnesses. Consistent with this possibility, recent results indicate that several major mental illnesses involve altered brain-wide connectivity of the control system, likely altering its ability to regulate symptoms. These results suggest that this "immune system of the mind" may be an especially important target for future basic and clinical research.

Monkey visual short-term memory directly compared to humans

Two adult rhesus monkeys were trained to detect which item in an array of memory items had changed using the same stimuli, viewing times, and delays as used with humans. Although the monkeys were extensively trained, they were less accurate than humans with the same array sizes (2, 4, & 6 items), with both stimulus types (colored squares, clip art), and showed calculated memory capacities of about 1 item (or less). Nevertheless, the memory results from both monkeys and humans for both stimulus types were well characterized by the inverse power-law of display size. This characterization provides a simple and straightforward summary of a fundamental process of visual short-term memory (STM; how VSTM declines with memory load) that emphasizes species similarities based upon similar functional relationships. By more closely matching monkey testing parameters to those of humans, the similar functional relationships strengthen the evidence suggesting similar processes underlying monkey and human VSTM.

Sequential dynamics in visual short-term memory

Visual short-term memory (VSTM) is thought to help bridge across changes in visual input, and yet many studies of VSTM employ static displays. Here we investigate how VSTM copes with sequential input. In particular, we characterize the temporal dynamics of several different components of VSTM performance, including: storage probability, precision, variability in precision, guessing, and swapping. We used a variant of the continuous-report VSTM task developed for static displays, quantifying the contribution of each component with statistical likelihood estimation, as a function of serial position and set size. In Experiments 1 and 2, storage probability did not vary by serial position for small set sizes, but showed a small primacy effect and a robust recency effect for larger set sizes; precision did not vary by serial position or set size. In Experiment 3, the recency effect was shown to reflect an increased likelihood of swapping out items from earlier serial positions and swapping in later items, rather than an increased rate of guessing for earlier items. Indeed, a model that incorporated responding to non-targets provided a better fit to these data than alternative models that did not allow for swapping or that tried to account for variable precision. These findings suggest that VSTM is updated in a first-in-first-out manner, and they bring VSTM research into closer alignment with classical working memory research that focuses on sequential behavior and interference effects.

"Plateau"-related summary statistics are uninformative for comparing working memory models

Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.

Factorial comparison of working memory models

Three questions have been prominent in the study of visual working memory limitations: (a) What is the nature of mnemonic precision (e.g., quantized or continuous)? (b) How many items are remembered? (c) To what extent do spatial binding errors account for working memory failures? Modeling studies have typically focused on comparing possible answers to a single one of these questions, even though the result of such a comparison might depend on the assumed answers to both others. Here, we consider every possible combination of previously proposed answers to the individual questions. Each model is then a point in a 3-factor model space containing a total of 32 models, of which only 6 have been tested previously. We compare all models on data from 10 delayed-estimation experiments from 6 laboratories (for a total of 164 subjects and 131,452 trials). Consistently across experiments, we find that (a) mnemonic precision is not quantized but continuous and not equal but variable across items and trials; (b) the number of remembered items is likely to be variable across trials, with a mean of 6.4 in the best model (median across subjects); (c) spatial binding errors occur but explain only a small fraction of responses (16.5% at set size 8 in the best model). We find strong evidence against all 6 documented models. Our results demonstrate the value of factorial model comparison in working memory.

Differential neuronal representation of spatial attention dependent on relative target locations during multiple object tracking

Humans can simultaneously track multiple moving objects with attention. The number of objects that can be tracked is known to be larger when visual stimuli are presented bilaterally rather than presented unilaterally. To elucidate the underlying neuronal mechanism, we trained monkeys to covertly track a single or multiple object(s). We found that neurons in the lateral prefrontal cortex exhibited greater activity for the target passing through the receptive field (RF) than for distractors. During multiple-object tracking, response enhancement for one target presented in the RF was stronger when the other target was located in the opposite than the same visual hemifield. Because the neuronal modulation did not differ depending on relative target locations with respect to upper and lower visual hemifields, the distance between the targets does not explain the results. We propose that inherent, anatomical separation of visual processing for contralateral and ipsilateral visual fields might constrain cognitive capacity.

Different neuronal computations of spatial working memory for multiple locations within versus across visual hemifields

Spatial working memory is one of the most studied cognitive functions, serving as a model system to decipher computational principles of the brain. Although neuronal mechanisms for remembering a single location have been well elucidated, little is known about memory for multiple locations. Here, we examined the activities of prefrontal neurons during monkeys remembered positions of one or two visual cue(s). When the two cues were presented across the left and right visual fields, neurons exhibited a comparable response to the activity for the preferred cue presented alone. When the two cues were presented within the same hemifield, neurons exhibited an intermediate response between those to the individual cues. Subsequent computer simulations predicted a lower signal-to-noise ratio in the latter condition, which was further verified by behavioral experiments. Considering the separation of contralateral and ipsilateral visual processing, the lateral inhibition in local circuits might implicitly determine different neuronal computations and memory capacities for bilateral and unilateral displays.

Neural Substrates of Dopamine D2 Receptor Modulated Executive Functions in the Monkey Prefrontal Cortex

Dopamine D2 receptors (D2R) play a major role in cognition, mood and motor movements. Their blockade by antipsychotic drugs reduces hallucinatory and delusional behaviors in schizophrenia, but often fails to alleviate affective and cognitive dysfunctions. The prefrontal cortex (PFC) expresses D2R and is altered in schizophrenia. We investigated how D2R modulate behavior and PFC function in monkeys. Two monkeys learned new and performed highly familiar visuomotor associations, where each cue was associated with a saccade to a right or left target. We recorded neural spikes and local field potentials from multiple electrodes while injecting the D2R antagonist eticlopride in the lateral PFC. Blocking prefrontal D2R impaired associative learning and cognitive flexibility, reduced motivation, but left the performance of familiar associations intact. Eticlopride reduced saccade-direction selectivity of prefrontal neurons, leading to a decrease in neural information about the associations, and an increase in alpha oscillations. These results, together with our recent study using a D1R antagonist, suggest that D1R and D2R in the primate lateral PFC cooperate to modulate several executive functions. Our findings help to gain insight into why antipsychotic drugs, with strong antagonistic actions on D2R, fail to ameliorate cognitive and emotional deficits in schizophrenia.

Executive control processes underlying multi-item working memory

A dominant view of prefrontal cortex (PFC) function is that it stores task-relevant information in working memory. To examine this and determine how it applies when multiple pieces of information must be stored, we trained two macaque monkeys to perform a multi-item color change-detection task and recorded activity of neurons in PFC. Few neurons encoded the color of the items. Instead, the predominant encoding was spatial: a static signal reflecting the item's position and a dynamic signal reflecting the animal's covert attention. These findings challenge the notion that PFC stores task-relevant information. Instead, we suggest that the contribution of PFC is in controlling the allocation of resources to support working memory. In support of this, we found that increased power in the alpha and theta bands of PFC local field potentials, which are thought to reflect long-range communication with other brain areas, was correlated with more precise color representations.

How low can you go? Changing the resolution of novel complex objects in visual working memory according to task demands

In three experiments we manipulated the resolution of novel complex objects in visual working memory (WM) by changing task demands. Previous studies that investigated the trade-off between quantity and resolution in visual WM yielded mixed results for simple familiar stimuli. We used the contralateral delay activity as an electrophysiological marker to directly track the deployment of visual WM resources while participants preformed a change-detection task. Across three experiments we presented the same novel complex items but changed the task demands. In Experiment 1 we induced a medium resolution task by using change trials in which a random polygon changed to a different type of polygon and replicated previous findings showing that novel complex objects are represented with higher resolution relative to simple familiar objects. In Experiment 2 we induced a low resolution task that required distinguishing between polygons and other types of stimulus categories, but we failed in finding a corresponding decrease in the resolution of the represented item. Finally, in Experiment 3 we induced a high resolution task that required discriminating between highly similar polygons with somewhat different contours. This time, we observed an increase in the item’s resolution. Our findings indicate that the resolution for novel complex objects can be increased but not decreased according to task demands, suggesting that minimal resolution is required in order to maintain these items in visual WM. These findings support studies claiming that capacity and resolution in visual WM reflect different mechanisms.

Noise in neural populations accounts for errors in working memory

Errors in short-term memory increase with the quantity of information stored, limiting the complexity of cognition and behavior. In visual memory, attempts to account for errors in terms of allocation of a limited pool of working memory resources have met with some success, but the biological basis for this cognitive architecture is unclear. An alternative perspective attributes recall errors to noise in tuned populations of neurons that encode stimulus features in spiking activity. I show that errors associated with decreasing signal strength in probabilistically spiking neurons reproduce the pattern of failures in human recall under increasing memory load. In particular, deviations from the normal distribution that are characteristic of working memory errors and have been attributed previously to guesses or variability in precision are shown to arise as a natural consequence of decoding populations of tuned neurons. Observers possess fine control over memory representations and prioritize accurate storage of behaviorally relevant information, at a cost to lower priority stimuli. I show that changing the input drive to neurons encoding a prioritized stimulus biases population activity in a manner that reproduces this empirical tradeoff in memory precision. In a task in which predictive cues indicate stimuli most probable for test, human observers use the cues in an optimal manner to maximize performance, within the constraints imposed by neural noise.

Changing concepts of working memory

Working memory is widely considered to be limited in capacity, holding a fixed, small number of items, such as Miller's 'magical number' seven or Cowan's four. It has recently been proposed that working memory might better be conceptualized as a limited resource that is distributed flexibly among all items to be maintained in memory. According to this view, the quality rather than the quantity of working memory representations determines performance. Here we consider behavioral and emerging neural evidence for this proposal.

PFC neurons reflect categorical decisions about ambiguous stimuli

We examined whether PFC neuron activity reflects categorical decisions in monkeys categorizing ambiguous stimuli. A morphing system was used to systematically vary stimulus shape and precisely define category boundaries. Ambiguous stimuli were centered on a category boundary, that is, they were a mix of 50% of two prototypes and therefore had no category information, so monkeys guessed at their category membership. We found that the monkeys' trial-by-trial decision about the category membership of an ambiguous image was reflected in PFC activity. Activity to the same ambiguous image differed significantly, depending on which category the monkey had assigned it to. This effect only occurred when that scheme was behaviorally relevant. These indicate that PFC activity reflects categorical decisions.

Bottlenecks of motion processing during a visual glance: the leaky flask model

Where do the bottlenecks for information and attention lie when our visual system processes incoming stimuli? The human visual system encodes the incoming stimulus and transfers its contents into three major memory systems with increasing time scales, viz., sensory (or iconic) memory, visual short-term memory (VSTM), and long-term memory (LTM). It is commonly believed that the major bottleneck of information processing resides in VSTM. In contrast to this view, we show major bottlenecks for motion processing prior to VSTM. In the first experiment, we examined bottlenecks at the stimulus encoding stage through a partial-report technique by delivering the cue immediately at the end of the stimulus presentation. In the second experiment, we varied the cue delay to investigate sensory memory and VSTM. Performance decayed exponentially as a function of cue delay and we used the time-constant of the exponential-decay to demarcate sensory memory from VSTM. We then decomposed performance in terms of quality and quantity measures to analyze bottlenecks along these dimensions. In terms of the quality of information, two thirds to three quarters of the motion-processing bottleneck occurs in stimulus encoding rather than memory stages. In terms of the quantity of information, the motion-processing bottleneck is distributed, with the stimulus-encoding stage accounting for one third of the bottleneck. The bottleneck for the stimulus-encoding stage is dominated by the selection compared to the filtering function of attention. We also found that the filtering function of attention is operating mainly at the sensory memory stage in a specific manner, i.e., influencing only quantity and sparing quality. These results provide a novel and more complete understanding of information processing and storage bottlenecks for motion processing.

Dynamic construction of a coherent attentional state in a prefrontal cell population

Prefrontal cortex has been proposed to show highly adaptive information coding, with neurons dynamically allocated to processing task-relevant information. To track this dynamic allocation in monkey prefrontal cortex, we used time-resolved measures of neural population activity in a simple case of competition between target (behaviorally critical) and nontarget objects in opposite visual hemifields. Early in processing, there were parallel responses to competing inputs, with neurons in each hemisphere dominated by the contralateral stimulus. Later, the nontarget lost control of neural activity, with emerging global control by the behaviorally critical target. The speed of transition reflected the competitive weights of different display elements, occurring most rapidly when relative behavioral significance was well established by training history. In line with adaptive coding, the results show widespread reallocation of prefrontal processing resources as an attentional focus is established.

Trade-off between capacity and precision in visuospatial working memory

Limitations in the performance of working memory (WM) tasks have been characterized in terms of the number of items retained (capacity) and in terms of the precision with which the information is retained. The neural mechanisms behind these limitations are still unclear. Here we used a biological constrained computational model to study the capacity and precision of visuospatial WM. The model consists of two connected networks of spiking neurons. One network is responsible for storage of information. The other provides a nonselective excitatory input to the storage network. Simulations showed that this excitation boost could temporarily increase storage capacity but also predicted that this would be associated with a decrease in precision of the memory. This prediction was subsequently tested in a behavioral (38 participants) and fMRI (22 participants) experiment. The behavioral results confirmed the trade-off effect, and the fMRI results suggest that a frontal region might be engaged in the trial-by-trial control of WM performance. The average effects were small, but individuals differed in the amount of trade-off, and these differences correlated with the frontal activation. These results support a two-module model of WM where performance is determined both by storage capacity and by top-down influence, which can vary on a trial-by-trial basis, affecting both the capacity and precision of WM.

Neural limits to representing objects still within view

Visual working memory is an online workspace for temporarily representing visual information from the environment. The two most prevalent empirical characteristics of working memory are that it is supported by sustained neural activity over a delay period and it has a severely limited capacity for representing multiple items simultaneously. Traditionally, such delay activity and capacity limits have been considered to be exclusive for maintaining information about objects that are no longer visible to the observers. Here, by contrast, we provide both neurophysiological and psychophysical evidence that the sustained neural activity and capacity limits for items that are continuously visible to the human observer are indistinguishable from those measured for items that are no longer visible. This holds true even when the observers know that the objects will not disappear from the visual field. These results demonstrate that our explicit representation of objects that are still "in view" is far more limited than previously assumed.

The dorsal attentional system in oculomotor learning of predictive information

The dorsal attentional network is known for its role in directing top-down visual attention toward task-relevant stimuli. This goal-directed nature of the dorsal network makes it a suitable candidate for processing and extracting predictive information from the visual environment. In this review we briefly summarize some of the findings that delineate the neural substrates that contribute to predictive learning at both levels within the dorsal attentional system: including the frontal eye field (FEF) and posterior parietal cortex (PPC). We also discuss the similarities and differences between these two regions when it comes to learning predictive information. The current findings from the literature suggest that the FEFs may be more involved in top-down spatial attention, whereas the parietal cortex is involved in processing task-relevant attentional influences driven by stimulus salience, both contribute to the processing of predictive cues at different time points.

Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.

Holding multiple items in short term memory: a neural mechanism

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.

The frontal eye fields limit the capacity of visual short-term memory in rhesus monkeys

The frontal eye fields (FEF) in rhesus monkeys have been implicated in visual short-term memory (VSTM) as well as control of visual attention. Here we examined the importance of the area in the VSTM capacity and the relationship between VSTM and attention, using the chemical inactivation technique and multi-target saccade tasks with or without the need of target-location memory. During FEF inactivation, serial saccades to targets defined by color contrast were unaffected, but saccades relying on short-term memory were impaired when the target count was at the capacity limit of VSTM. The memory impairment was specific to the FEF-coded retinotopic locations, and subject to competition among targets distributed across visual fields. These results together suggest that the FEF plays a crucial role during the entry of information into VSTM, by enabling attention deployment on targets to be remembered. In this view, the memory capacity results from the limited availability of attentional resources provided by FEF: The FEF can concurrently maintain only a limited number of activations to register the targets into memory. When lesions render part of the area unavailable for activation, the number would decrease, further reducing the capacity of VSTM.

Dynamic coding for cognitive control in prefrontal cortex

Cognitive flexibility is fundamental to adaptive intelligent behavior. Prefrontal cortex has long been associated with flexible cognitive function, but the neurophysiological principles that enable prefrontal cells to adapt their response properties according to context-dependent rules remain poorly understood. Here, we use time-resolved population-level neural pattern analyses to explore how context is encoded and maintained in primate prefrontal cortex and used in flexible decision making. We show that an instruction cue triggers a rapid series of state transitions before settling into a stable low-activity state. The postcue state is differentially tuned according to the current task-relevant rule. During decision making, the response to a choice stimulus is characterized by an initial stimulus-specific population response but evolves to different final decision-related states depending on the current rule. These results demonstrate how neural tuning profiles in prefrontal cortex adapt to accommodate changes in behavioral context. Highly flexible tuning could be mediated via short-term synaptic plasticity.

Visual working memory

Visual working memory (VWM), the system of storing, manipulating, and utilizing, visual information is fundamental to many cognitive acts. Exploring the limitations of this system is essential to understand the characteristics of higher-order cognition, since at a basic level, VWM is the interface through which we interact with our environment. Given its important function, this system has become a very active area of research in the recent years. Here, we examine current models of VWM, along with the proposed reasons for what limits its capacity. This is followed by a short description of recent neural findings that have helped constrain models of VWM. In closing, we focus on work exploring individual differences in working memory capacity, and what these findings reveal about the intimate relationship between VWM and attention. WIREs Cogn Sci 2013, 4:179-190. doi: 10.1002/wcs.1219 For further resources related to this article, please visit the WIREs website.

No evidence for an item limit in change detection

Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items (“item-limit models”). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size (“continuous-resource models”). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

Working memory is a fundamental aspect of human cognition. It allows us to remember bits of information over short periods of time and make split-second decisions about what to do next. Working memory is often tested using a change detection task: subjects report whether a change occurred between two subsequent visual images that both contain multiple objects (items). The more items are present in the images, the worse they do. The precise origin of this phenomenon is not agreed on. The classic theory asserts that working memory consists of a small number of slots, each of which can store one item; when there are more items than slots, the extra items are discarded. A modern model postulates that working memory is fundamentally limited in the quality rather than the quantity of memories. In a metaphor: instead of watering only a few plants in our garden, we water all of them, but the more plants we have, the less water each will receive on average. We show that this new model does much better in accounting for human change detection responses. This has consequences for the entire field of working memory research.

Change detection for the study of object and location memory

Seven adult human participants were tested in change detection tasks for object and location memory with large and small sets of four different stimulus types. Blocked tests demonstrated that participants performed similarly in separate object and location tests with matched parameters and displays. In mixed tests, participants were informed that they would be tested with either object changes or location changes; surprisingly, they were nearly as accurate remembering both objects and locations as when either was tested alone. By contrast, in the large-set condition, performance was lower than baseline on surprise probe test trials in which participants were tested (on 13% of trials) with the change type opposite to the present block (e.g., location probe trials during the object change block). These probe-test results were further supported by the reduction in probe-baseline differences when tested with small sets (6) of these item types. Small sets required remembering locations and objects to resolve object-location confounds. Together these results show that humans can remember both objects and locations with little loss of accuracy when instructed to do so, but do not learn these contextual associations without instruction.

Effective visual working memory capacity: an emergent effect from the neural dynamics in an attractor network

The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items.

Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions.

The role of prefrontal dopamine D1 receptors in the neural mechanisms of associative learning

Dopamine is thought to play a major role in learning. However, while dopamine D1 receptors (D1Rs) in the prefrontal cortex (PFC) have been shown to modulate working memory-related neural activity, their role in the cellular basis of learning is unknown. We recorded activity from multiple electrodes while injecting the D1R antagonist SCH23390 in the lateral PFC as monkeys learned visuomotor associations. Blocking D1Rs impaired learning of novel associations and decreased cognitive flexibility but spared performance of already familiar associations. This suggests a greater role for prefrontal D1Rs in learning new, rather than performing familiar, associations. There was a corresponding greater decrease in neural selectivity and increase in alpha and beta oscillations in local field potentials for novel than for familiar associations. Our results suggest that weak stimulation of D1Rs observed in aging and psychiatric disorders may impair learning and PFC function by reducing neural selectivity and exacerbating neural oscillations associated with inattention and cognitive deficits.

From distributed resources to limited slots in multiple-item working memory: a spiking network model with normalization

Recent behavioral studies have given rise to two contrasting models for limited working memory capacity: a "discrete-slot" model in which memory items are stored in a limited number of slots, and a "shared-resource" model in which the neural representation of items is distributed across a limited pool of resources. To elucidate the underlying neural processes, we investigated a continuous network model for working memory of an analog feature. Our model network fundamentally operates with a shared resource mechanism, and stimuli in cue arrays are encoded by a distributed neural population. On the other hand, the network dynamics and performance are also consistent with the discrete-slot model, because multiple objects are maintained by distinct localized population persistent activity patterns (bump attractors). We identified two phenomena of recurrent circuit dynamics that give rise to limited working memory capacity. As the working memory load increases, a localized persistent activity bump may either fade out (so the memory of the corresponding item is lost) or merge with another nearby bump (hence the resolution of mnemonic representation for the merged items becomes blurred). We identified specific dependences of these two phenomena on the strength and tuning of recurrent synaptic excitation, as well as network normalization: the overall population activity is invariant to set size and delay duration; therefore, a constant neural resource is shared by and dynamically allocated to the memorized items. We demonstrate that the model reproduces salient observations predicted by both discrete-slot and shared-resource models, and propose testable predictions of the merging phenomenon.

A neurocomputational system for relational reasoning

The representation and manipulation of structured relations is central to human reasoning. Recent work in computational modeling and neuroscience has set the stage for developing more detailed neurocomputational models of these abilities. Several key neural findings appear to dovetail with computational constraints derived from a model of analogical processing, 'Learning and Inference with Schemas and Analogies' (LISA). These include evidence that (i) coherent oscillatory activity in the gamma and theta bands enables long-distance communication between the prefrontal cortex and posterior brain regions where information is stored; (ii) neurons in prefrontal cortex can rapidly learn to represent abstract concepts; (iii) a rostral-caudal abstraction gradient exists in the PFC; and (iv) the inferior frontal gyrus exerts inhibitory control over task-irrelevant information.

Insights from neuropsychology: pinpointing the role of the posterior parietal cortex in episodic and working memory

The role of posterior parietal cortex (PPC) in various forms of memory is a current topic of interest in the broader field of cognitive neuroscience. This large cortical region has been linked with a wide range of mnemonic functions affecting each stage of memory processing: encoding, maintenance, and retrieval. Yet, the precise role of the PPC in memory remains mysterious and controversial. Progress in understanding PPC function will require researchers to incorporate findings in a convergent manner from multiple experimental techniques rather than emphasizing a particular type of data. To facilitate this process, here, we review findings from the human neuropsychological research and examine the consequences to memory following PPC damage. Recent patient-based research findings have investigated two typically disconnected fields: working memory (WM) and episodic memory. The findings from patient participants with unilateral and bilateral PPC lesions performing diverse experimental paradigms are summarized. These findings are then related to findings from other techniques including neurostimulation (TMS and tDCS) and the influential and more abundant functional neuroimaging literature. We then review the strengths and weaknesses of hypotheses proposed to account for PPC function in these forms of memory. Finally, we address what missing evidence is needed to clarify the role(s) of the PPC in memory.

Variability in encoding precision accounts for visual short-term memory limitations

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

Unique and shared roles of the posterior parietal and dorsolateral prefrontal cortex in cognitive functions

The dorsolateral prefrontal cortex (PFC) and posterior parietal cortex (PPC) are two parts of a broader brain network involved in the control of cognitive functions such as working-memory, spatial attention, and decision-making. The two areas share many functional properties and exhibit similar patterns of activation during the execution of mental operations. However, neurophysiological experiments in non-human primates have also documented subtle differences, revealing functional specialization within the fronto-parietal network. These differences include the ability of the PFC to influence memory performance, attention allocation, and motor responses to a greater extent, and to resist interference by distracting stimuli. In recent years, distinct cellular and anatomical differences have been identified, offering insights into how functional specialization is achieved. This article reviews the common functions and functional differences between the PFC and PPC, and their underlying mechanisms.

Human visual short-term memory precision can be varied at will when the number of retained items is low

It has been debated whether human visual working memory is limited by the number of items or the precision with which they are represented. In the research reported here, we show that the precision of working memory can be flexibly and willfully controlled, but only if the number of retained items is low. Electroencephalographic recordings revealed that a neural marker for visual working memory (contralateral delay activity, or CDA) that is known to increase in amplitude with the number of retained items was also affected by the precision with which items were retained. However, willfully enhanced precision increased CDA amplitude only when the number of retained items was low. These results show that both the number and the (willfully controlled) precision of retained items constrain visual working memory: People can enhance the precision of their visual working memory, but only for a few items.

Capacity and precision in an animal model of visual short-term memory

Temporary storage of information in visual short-term memory (VSTM) is a key component of many complex cognitive abilities. However, it is highly limited in capacity. Understanding the neurophysiological nature of this capacity limit will require a valid animal model of VSTM. We used a multiple-item color change detection task to measure macaque monkeys' VSTM capacity. Subjects' performance deteriorated and reaction times increased as a function of the number of items in memory. Additionally, we measured the precision of the memory representations by varying the distance between sample and test colors. In trials with similar sample and test colors, subjects made more errors compared to trials with highly discriminable colors. We modeled the error distribution as a Gaussian function and used this to estimate the precision of VSTM representations. We found that as the number of items in memory increases the precision of the representations decreases dramatically. Additionally, we found that focusing attention on one of the objects increases the precision with which that object is stored and degrades the precision of the remaining. These results are in line with recent findings in human psychophysics and provide a solid foundation for understanding the neurophysiological nature of the capacity limit of VSTM.

Polymorphisms in the 5-HTTLPR gene mediate storage capacity of visual working memory

Working memory (WM) is a limited capacity system that permeates nearly all levels of cognition, ranging from perceptual awareness to intelligence. Through behavioral, electrophysiological, and neuroimaging work, substantial gains have been made in understanding this capacity-limited system. In the current work, we examined genetic contributions to the storage capacity of WM. Multiple studies have demonstrated a link between the serotonin transporter-linked polymorphic region (5-HTTLPR) and cognition, where better performance is observed in individuals possessing a copy of the short (s) variant of the polymorphism compared with individuals homozygous for the long (l) variant. We predicted the same profile in WM performance, such that estimated capacities of l/l carriers should be smaller than s/s and s/l carriers. To measure WM capacity, we implemented a change detection task, which requires observers to actively maintain the color and spatial location of briefly presented squares over a short retention interval. In line with our prediction, we observed similar WM performance between s/s and s/l groups, and these individuals performed better than the l/l group. We then discuss the distribution of the serotonin transporter system and parallels between WM and attention to provide insight into how variation in the 5-HTT polymorphism could lead to individual differences in the storage capacity of WM.