Shared mechanisms underlie the control of working memory and attention

The Relation Between Attention and Memory

The relation between attention and memory has long been deemed important for understanding cognition, and it was heavily researched even in the first experimental psychology laboratory by Wilhelm Wundt and his colleagues. Since then, the importance of the relation between attention and memory has been explored in myriad subdisciplines of psychology, and we incorporate a wide range of these diverse fields. Here, we examine some of the practical consequences of this relation and summarize work with various methodologies relating attention to memory in the fields of working memory, long-term memory, individual differences, life-span development, typical brain function, and neuropsychological conditions. We point out strengths and unanswered questions for our own embedded processes view of information processing, which is used to organize a large body of evidence. Last, we briefly consider the relation of the evidence to a range of other theoretical views before drawing conclusions about the state of the field.

A neural substrate for short-term taste memories

Real-time decisions on what foods to select for consumption, particularly in the wild, require a sensitive sense of taste and an effective system to maintain short-term taste memories, also defined as working memory in the scale of seconds. Here, we used a behavioral memory assay, combined with recordings of neural activity, to identify the brain substrate for short-term taste memories. We demonstrate that persistent activity in taste cortex functions as an essential memory trace of a recent taste experience. Next, we manipulated the decay of this persistent activity and showed that early termination of the memory trace abolished the memory. Notably, extending the memory trace by transiently disinhibiting taste cortical activity dramatically extended the retention of a short-term taste memory. Together, our results uncover taste cortex as a neural substrate for working memory and substantiate the role of sensory cortex in memory-guided actions while imposing meaning to a sensory stimulus.

Attention influences the effects of the previous form orientation on the current motion direction estimation

Recent studies have found that the estimates of motion directions are biased toward the previous form orientations, showing serial dependence, and the serial dependence does not involve cognitive abilities. In the current study, we conducted two experiments to investigate whether and how attention-a cognitive ability-affected the serial dependence. The results showed that serial dependence was present in the current study, reproducing the previous findings. Importantly, when the attentional load reduced the reliability (i.e., estimation accuracy and precision) of previous form orientations (Experiment 1), the serial dependence decreased, meaning that the biases of motion direction estimates toward previous form orientations were reduced; in contrast, when the attentional load reduced the reliability of current motion directions (Experiment 2), the serial dependence increased, meaning that the biases of motion direction estimates toward previous form orientations were increased. These trends were well consistent with the prediction of the Bayesian inference theory. Therefore, the current study revealed the involvement of attention in the serial dependence of current motion direction estimation on the previous form orientation, demonstrating that the serial dependence was cognitive and the attentional effect can be a Bayesian inference process, initially revealing its computational mechanism.

Gamma Power as an Index of Sustained Attention in Simulated Vigilance Tasks

Performance on the psychomotor vigilance test (PVT; Dinges & Powell, 1985)-a common index of sustained attention-is affected by the opposing forces of fatigue and sustained effort, where reaction times and error rates typically increase across trials and are sometimes offset by additional efforts deployed toward the end of the task (i.e., an "end-spurt"; cf. Bergum & Klein, 1961). In ACT-R (Adaptive Control of Thought-Rational; Anderson et al., 2004), these influences on task performance have been modeled as latent variables that are inferred from performance (e.g., Jongman, 1998; Veksler & Gunzelmann, 2018) without connections to directly observable variables. We propose the use of frontal gamma (γ) spectral power as a direct measure of vigilant effort and demonstrate its efficacy in modeling performance on the PVT in both the aggregate and in individuals.

The Moderating Role of Cortisol and Negative Emotionality in the Effects of Classroom Size and Window View on Young Children's Executive Functions

This study probed how baseline cortisol (BC), negative emotionality (NE), and environmental facets-classroom size and window view-interact to affect executive function (EF) in preschoolers using virtual reality (VR). In a cohort of 144 children aged 61-85 months, BC levels were measured by saliva assays and NE by parental surveys. Participants completed computerized EF assessments both pre- and post-exposure to one of four VR conditions, which varied by classroom size (large vs. small) and window view (natural vs. built). Due to missing data and outlier responses, three children were removed from the analyses. Regression analyses, accounting for initial EFs, revealed that higher BC was significantly associated with better Digit-span task scores in the nature view, while lower BC correlated with improved performance in the built view. With regard to classroom size, children with varying levels of NE benefitted from the large classroom environment, as evidenced by marginally significant improvements on the Corsi block task. However, higher NE children outperformed their lower NE peers in the large classroom, while a trend inverted in the small classroom context. The findings illuminate how the physical components of preschool environments may interact with children's physiological reactivity, potentially influencing the development of working memory.

No obligatory trade-off between the use of space and time for working memory

Space and time can each act as scaffolds for the individuation and selection of visual objects in working memory. Here we ask whether there is a trade-off between the use of space and time for visual working memory: whether observers will rely less on space, when memoranda can additionally be individuated through time. We tracked the use of space through directional biases in microsaccades after attention was directed to memory contents that had been encoded simultaneously or sequentially to the left and right of fixation. We found that spatial gaze biases were preserved when participants could (Experiment 1) and even when they had to (Experiment 2) additionally rely on time for object individuation. Thus, space remains a profound organizing medium for working memory even when other organizing sources are available and utilized, with no evidence for an obligatory trade-off between the use of space and time.

Prefrontal Cortex Codes Representations of Target Identity and Feature Uncertainty

Many objects in the real world have features that vary over time, creating uncertainty in how they will look in the future. This uncertainty makes statistical knowledge about the likelihood of features critical to attention demanding processes such as visual search. However, little is known about how the uncertainty of visual features is integrated into predictions about search targets in the brain. In the current study, we test the idea that regions prefrontal cortex code statistical knowledge about search targets before the onset of search. Across 20 human participants (13 female; 7 male), we observe target identity in the multivariate pattern and uncertainty in the overall activation of dorsolateral prefrontal cortex (DLPFC) and inferior frontal junction (IFJ) in advance of the search display. This indicates that the target identity (mean) and uncertainty (variance) of the target distribution are coded independently within the same regions. Furthermore, once the search display appears the univariate IFJ signal scaled with the distance of the actual target from the expected mean, but more so when expected variability was low. These results inform neural theories of attention by showing how the prefrontal cortex represents both the identity and expected variability of features in service of top-down attentional control.SIGNIFICANCE STATEMENT Theories of attention and working memory posit that when we engage in complex cognitive tasks our performance is determined by how precisely we remember task-relevant information. However, in the real world the properties of objects change over time, creating uncertainty about many aspects of the task. There is currently a gap in our understanding of how neural systems represent this uncertainty and combine it with target identity information in anticipation of attention demanding cognitive tasks. In this study, we show that the prefrontal cortex represents identity and uncertainty as unique codes before task onset. These results advance theories of attention by showing that the prefrontal cortex codes both target identity and uncertainty to implement top-down attentional control.

Attention with or without working memory: mnemonic reselection of attended information

Attention has been regarded as the 'gatekeeper' controlling what information gets selected into working memory. However, a new perspective has emerged with the discovery of attribute amnesia, a phenomenon revealing that people are frequently unable to report information they have just attended to moments ago. This report failure is thought to stem from a lack of consolidating the attended information into working memory, indicating a dissociation between attention and working memory. Building on these findings, a new concept called memory reselection is proposed to describe a secondary round of selection among the attended information. These discoveries challenge the conventional view of how attention and working memory are related and shed new light onto modeling attention and memory as dissociable processes.

What Is the Relationship between Metacognition and Mental Effort in Executive Functions? The Contribution of Neurophysiology

Prolonged cognitive effort can be considered one of the core determinants of mental fatigue and may negatively affect the efficacy and efficiency of cognitive performance. Metacognition-understood as a multi-componential set of skills concerning awareness and control of one's own cognition-might reduce such negative outcomes. This study aimed to explore the relation between metacognitive skills, neurocognitive performance, and the level of mental effort as mirrored by electrophysiological (EEG) markers of cognitive load and task demand. A challenging cognitive task was used to prompt and collect metacognition reports, performance data (accuracy and response times-RTs), and physiological markers of mental effort (task-related changes of spectral power for standard EEG frequency bands) via wearable EEG. Data analysis highlighted that different aspects of metacognitive skills are associated with performance as measured by, respectively, accuracy and RTs. Furthermore, specific aspects of metacognitive skills were found to be consistently correlated with EEG markers of cognitive effort, regardless of increasing task demands. Finally, behavioral metrics mirroring the efficiency of information processing were found to be associated with different EEG markers of cognitive effort depending on the low or high demand imposed by the task.

Functional alterations of the prefrontal circuit underlying cognitive aging in mice

Executive function is susceptible to aging. How aging impacts the circuit-level computations underlying executive function remains unclear. Using calcium imaging and optogenetic manipulation during memory-guided behavior, we show that working-memory coding and the relevant recurrent connectivity in the mouse medial prefrontal cortex (mPFC) are altered as early as middle age. Population activity in the young adult mPFC exhibits dissociable yet overlapping patterns between tactile and auditory modalities, enabling crossmodal memory coding concurrent with modality-dependent coding. In middle age, however, crossmodal coding remarkably diminishes while modality-dependent coding persists, and both types of coding decay in advanced age. Resting-state functional connectivity, especially among memory-coding neurons, decreases already in middle age, suggesting deteriorated recurrent circuits for memory maintenance. Optogenetic inactivation reveals that the middle-aged mPFC exhibits heightened vulnerability to perturbations. These findings elucidate functional alterations of the prefrontal circuit that unfold in middle age and deteriorate further as a hallmark of cognitive aging.

Working memory performance is tied to stimulus complexity

Working memory is the cognitive capability to maintain and process information over short periods. Behavioral and computational studies have shown that visual information is associated with working memory performance. However, the underlying neural correlates remain unknown. To identify how visual information affects working memory performance, we conducted behavioral experiments in pigeons (Columba livia) and single unit recordings in the avian prefrontal analog, the nidopallium caudolaterale (NCL). Complex pictures featuring luminance, spatial and color information, were associated with higher working memory performance compared to uniform gray pictures in conjunction with distinct neural coding patterns. For complex pictures, we found a multiplexed neuronal code displaying visual and value-related features that switched to a representation of the upcoming choice during a delay period. When processing gray stimuli, NCL neurons did not multiplex and exclusively represented the choice already during stimulus presentation and throughout the delay period. The prolonged representation possibly resulted in a decay of the memory trace ultimately leading to a decrease in performance. In conclusion, we found that high stimulus complexity is associated with neuronal multiplexing of the working memory representation possibly allowing a facilitated read-out of the neural code resulting in enhancement of working memory performance.

Early top-down control of internal selection induced by retrospective cues in visual working memory: advantage of peripheral over central cues

Attention can be deployed among external sensory stimuli or internal working memory (WM) representations, and recent primate studies have revealed that these external and internal selections share a common neural basis in the prefrontal cortex (PFC). However, it remains to be elucidated how PFC implements these selections, especially in humans. The present study aimed to further investigate whether PFC responded differentially to the peripheral and central retrospective cues (retro-cues) that induced attention selection among WM representations. To achieve this, we combined magnetoencephalography (MEG, Experiment 1) and transcranial magnetic stimulation (TMS, Experiment 2) with an orientation-recall paradigm. Experiment 1 found that a peripheral retro-cue with 100% reliability had a greater benefit on WM performance than a central retro-cue, while this advantage of peripheral over central cues vanished when the cue reliability dropped to 50% (non-informative). MEG source analysis indicated that the 100% peripheral retro-cue elicited earlier (∼125 ms) PFC responses than the central retro-cue (∼275 ms). Meanwhile, Granger causality analysis showed that PFC had earlier (0-200 ms) top-down signals projecting to the superior parietal lobule (SPL) and the lateral occipital cortex (LOC) after the onset of peripheral retro-cues, while these top-down signals appeared later (300-500 ms) after the onset of central retro-cues. Importantly, PFC activity within this period of 300-500 ms correlated with the peripheral advantage in behavior. Moreover, Experiment 2 applied TMS at different time points to test the causal influence of brain activity on behavior and found that stimulating PFC at 100 ms abolished the behavioral benefit of the peripheral retro-cue, as well as its advantage over the central retro-cue. Taken together, our results suggested that the advantage of peripheral over central retro-cues in the mnemonic domain is realized through faster top-down control from PFC, which challenged traditional opinions that the top-down control of attention on WM required at least 300 ms to appear. The present study highlighted that in addition to the causal role of PFC in attention selection of WM representations, timing was critical as well and faster was better.

Prediction during language comprehension: what is next?

Prediction is often regarded as an integral aspect of incremental language comprehension, but little is known about the cognitive architectures and mechanisms that support it. We review studies showing that listeners and readers use all manner of contextual information to generate multifaceted predictions about upcoming input. The nature of these predictions may vary between individuals owing to differences in language experience, among other factors. We then turn to unresolved questions which may guide the search for the underlying mechanisms. (i) Is prediction essential to language processing or an optional strategy? (ii) Are predictions generated from within the language system or by domain-general processes? (iii) What is the relationship between prediction and memory? (iv) Does prediction in comprehension require simulation via the production system? We discuss promising directions for making progress in answering these questions and for developing a mechanistic understanding of prediction in language.

Early selection of task-relevant features through population gating

Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we propose that population gating, occurring within primary auditory cortex (A1) but controlled by top-down inputs from prelimbic region of medial prefrontal cortex (mPFC), can support across-area stimulus selection. Examining single-unit activity recorded while rats performed an auditory context-dependent task, we found that A1 encoded relevant and irrelevant stimuli along a common dimension of its neural space. Yet, the relevant stimulus encoding was enhanced along an extra dimension. In turn, mPFC encoded only the stimulus relevant to the ongoing context. To identify candidate mechanisms for stimulus selection within A1, we reverse-engineered low-rank RNNs trained on a similar task. Our analyses predicted that two context-modulated neural populations gated their preferred stimulus in opposite contexts, which we confirmed in further analyses of A1. Finally, we show in a two-region RNN how population gating within A1 could be controlled by top-down inputs from PFC, enabling flexible across-area communication despite fixed inter-areal connectivity.

The neural basis of swap errors in working memory

When making decisions in a cluttered world, humans and other animals often have to hold multiple items in memory at once - such as the different items on a shopping list. Psychophysical experiments in humans and other animals have shown remembered stimuli can sometimes become confused, with participants reporting chimeric stimuli composed of features from different stimuli. In particular, subjects will often make "swap errors" where they misattribute a feature from one object as belonging to another object. While swap errors have been described behaviorally, their neural mechanisms are unknown. Here, we elucidate these neural mechanisms through trial-by-trial analysis of neural population recordings from posterior and frontal brain regions while monkeys perform two multi-stimulus working memory tasks. In these tasks, monkeys were cued to report the color of an item that either was previously shown at a corresponding location (requiring selection from working memory) or will be shown at the corresponding location (requiring attention to a position). Animals made swap errors in both tasks. In the neural data, we find evidence that the neural correlates of swap errors emerged when correctly remembered information is selected incorrectly from working memory. This led to a representation of the distractor color as if it were the target color, underlying the eventual swap error. We did not find consistent evidence that swap errors arose from misinterpretation of the cue or errors during encoding or storage in working memory. These results suggest an alternative to established views on the neural origins of swap errors, and highlight selection from and manipulation in working memory as crucial - yet surprisingly brittle - neural processes.

Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, we trained two rhesus monkeys on a two-target, free-choice luminance-reward selection task. We demonstrate that visual-movement (VM) neurons and nonvisual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.

Bend but don't break: Prioritization protects working memory from displacement but leaves it vulnerable to distortion from distraction

Perceptual distraction distorts visual working memory representations. Previous research has shown that memory responses are systematically biased towards passively viewed visual distractors that are similar to the memoranda. However, it remains unclear whether the prioritization of one working memory representation over another reduces the impact of perceptual distractors. We designed a study with five different types of visual distraction that varied in engagement and found evidence for both subtle distortions and catastrophic failures of memory. Importantly, prioritization protected working memories from catastrophic loss (fewer "swap errors") but rendered them more vulnerable to distortion (greater attractive "biases" towards the distractor). Our findings demonstrate that prioritization does not simply protect working memory from any and all interference, but rather it reduces the likelihood of catastrophic disruption from perceptual distraction at the cost of an increased likelihood of distortion.

A recurrent neural network model of prefrontal brain activity during a working memory task

When multiple items are held in short-term memory, cues that retrospectively prioritise one item over another (retro-cues) can facilitate subsequent recall. However, the neural and computational underpinnings of this effect are poorly understood. One recent study recorded neural signals in the macaque lateral prefrontal cortex (LPFC) during a retro-cueing task, contrasting delay-period activity before (pre-cue) and after (post-cue) retrocue onset. They reported that in the pre-cue delay, the individual stimuli were maintained in independent subspaces of neural population activity, whereas in the post-cue delay, the prioritised items were rotated into a common subspace, potentially allowing a common readout mechanism. To understand how such representational transitions can be learnt through error minimisation, we trained recurrent neural networks (RNNs) with supervision to perform an equivalent cued-recall task. RNNs were presented with two inputs denoting conjunctive colour-location stimuli, followed by a pre-cue memory delay, a location retrocue, and a post-cue delay. We found that the orthogonal-to-parallel geometry transformation observed in the macaque LPFC emerged naturally in RNNs trained to perform the task. Interestingly, the parallel geometry only developed when the cued information was required to be maintained in short-term memory for several cycles before readout, suggesting that it might confer robustness during maintenance. We extend these findings by analysing the learning dynamics and connectivity patterns of the RNNs, as well as the behaviour of models trained with probabilistic cues, allowing us to make predictions for future studies. Overall, our findings are consistent with recent theoretical accounts which propose that retrocues transform the prioritised memory items into a prospective, action-oriented format.

Perisaccadic and Attentional Remapping of Receptive Fields in Lateral Intraparietal Area and Frontal Eye Fields

The nature and function of perisaccadic receptive-field (RF) remapping have been controversial. We used a delayed saccade task to reduce previous confounds and examined the remapping time course in areas LIP and FEF. In the delay period, the RF shift direction turned from the initial fixation to the saccade target. In the perisaccadic period, RFs first shifted toward the target (convergent remapping) but around the time of saccade onset/offset, the shifts became predominantly toward the post-saccadic RF locations (forward remapping). Thus, unlike forward remapping that depends on the corollary discharge (CD) of the saccade command, convergent remapping appeared to follow attention from the initial fixation to the target. We modelled the data with attention-modulated and CD-gated connections, and showed that both sets of connections emerged automatically in neural networks trained to update stimulus retinal locations across saccades. Our work thus unifies previous findings into a mechanism for transsaccadic visual stability.

Transient Oscillations of Neural Firing Rate Associated With Routing of Evidence in a Perceptual Decision

To form a perceptual decision, the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys of both sexes to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se Significance Statement It has often been suggested that oscillations in neural activity might serve a role in routing information appropriately. We observe an oscillation in neural firing rate in the lateral intraparietal area consistent with such a role. The oscillations are transient. They coincide with the establishment of routing, but they do not appear to play a role in the transmission (or conveyance) of the routed information itself.

Neural population dynamics of human working memory

The activity of neurons in macaque prefrontal cortex (PFC) persists during working memory (WM) delays, providing a mechanism for memory.1,2,3,4,5,6,7,8,9,10,11 Although theory,11,12 including formal network models,13,14 assumes that WM codes are stable over time, PFC neurons exhibit dynamics inconsistent with these assumptions.15,16,17,18,19 Recently, multivariate reanalyses revealed the coexistence of both stable and dynamic WM codes in macaque PFC.20,21,22,23 Human EEG studies also suggest that WM might contain dynamics.24,25 Nonetheless, how WM dynamics vary across the cortical hierarchy and which factors drive dynamics remain unknown. To elucidate WM dynamics in humans, we decoded WM content from fMRI responses across multiple cortical visual field maps.26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48 We found coexisting stable and dynamic neural representations of WM during a memory-guided saccade task. Geometric analyses of neural subspaces revealed that early visual cortex exhibited stronger dynamics than high-level visual and frontoparietal cortex. Leveraging models of population receptive fields, we visualized and made the neural dynamics interpretable. We found that during WM delays, V1 population initially encoded a narrowly tuned bump of activation centered on the peripheral memory target. Remarkably, this bump then spread inward toward foveal locations, forming a vector along the trajectory of the forthcoming memory-guided saccade. In other words, the neural code transformed into an abstraction of the stimulus more proximal to memory-guided behavior. Therefore, theories of WM must consider both sensory features and their task-relevant abstractions because changes in the format of memoranda naturally drive neural dynamics.

The Impact of Interpreting Training Experience on the Attentional Networks and Their Dynamics

Interpreting, a complicated and demanding bilingual task, depends heavily on attentional control. However, few studies have focused on the interpreters' advantages in attention, and the findings so far have been inconsistent. Meanwhile, the connection between attentional networks and other cognitive abilities, such as working memory (WM), has rarely been explored in interpreters. The present study investigated whether interpreting experience (IE) contributed to the attentional networks of bilinguals and explored the link between interpreters' attention and WM. Three groups of Chinese-English bilinguals, differing only in their duration of interpreting training (the More-IE group, the Less-IE group, and the No-IE group), completed the Attention Network Test (ANT). Results showed that only the alerting network was more efficient in the More-IE group than in the Less-IE and No-IE groups; moreover, the dynamics between the alerting and executive networks were significant only in the More-IE group. Furthermore, we found a negative correlation between the executive effect and the working memory capacity (WMC) in the More-IE group. Our study validated and provided empirical support for the Attentional Control Model, stimulating further research into neurocognitive mechanisms of advanced second language learning.

Sequential sparse autoencoder for dynamic heading representation in ventral intraparietal area

To navigate in space, it is important to predict headings in real-time from neural responses in the brain to vestibular and visual signals, and the ventral intraparietal area (VIP) is one of the critical brain areas. However, it remains unexplored in the population level how the heading perception is represented in VIP. And there are no commonly used methods suitable for decoding the headings from the population responses in VIP, given the large spatiotemporal dynamics and heterogeneity in the neural responses. Here, responses were recorded from 210 VIP neurons in three rhesus monkeys when they were performing a heading perception task. And by specifically and separately modelling the both dynamics with sparse representation, we built a sequential sparse autoencoder (SSAE) to do the population decoding on the recorded dataset and tried to maximize the decoding performance. The SSAE relies on a three-layer sparse autoencoder to extract temporal and spatial heading features in the dataset via unsupervised learning, and a softmax classifier to decode the headings. Compared with other population decoding methods, the SSAE achieves a leading accuracy of 96.8% ± 2.1%, and shows the advantages of robustness, low storage and computing burden for real-time prediction. Therefore, our SSAE model performs well in learning neurobiologically plausible features comprising dynamic navigational information.

Cycles of goal silencing and reactivation underlie complex problem-solving in primate frontal and parietal cortex

While classic views proposed that working memory (WM) is mediated by sustained firing, recent evidence suggests a contribution of activity-silent states. Within WM, human neuroimaging studies suggest a switch between attentional foreground and background, with only the foregrounded item represented in active neural firing. To address this process at the cellular level, we recorded prefrontal (PFC) and posterior parietal (PPC) neurons in a complex problem-solving task, with monkeys searching for one or two target locations in a first cycle of trials, and retaining them for memory-guided revisits on subsequent cycles. When target locations were discovered, neither frontal nor parietal neurons showed sustained goal-location codes continuing into subsequent trials and cycles. Instead there were sequences of timely goal silencing and reactivation, and following reactivation, sustained states until behavioral response. With two target locations, goal representations in both regions showed evidence of transitions between foreground and background, but the PFC representation was more complete, extending beyond the current trial to include both past and future selections. In the absence of unbroken sustained codes, different neuronal states interact to support maintenance and retrieval of WM representations across successive trials.

Action space restructures visual working memory in prefrontal cortex

Visual working memory enables flexible behavior by decoupling sensory stimuli from behavioral actions. While previous studies have predominantly focused on the storage component of working memory, the role of future actions in shaping working memory remains unknown. To answer this question, we used two working memory tasks that allowed the dissociation of sensory and action components of working memory. We measured behavioral performance and neuronal activity in the macaque prefrontal cortex area, frontal eye fields. We show that the action space reshapes working memory, as evidenced by distinct patterns of memory tuning and attentional orienting between the two tasks. Notably, neuronal activity during the working memory period predicted future behavior and exhibited mixed selectivity in relation to the sensory space but linear selectivity relative to the action space. This linear selectivity was achieved through the rapid transformation from sensory to action space and was subsequently maintained as a stable cross-temporal population activity pattern. Combined, we provide direct physiological evidence of the action-oriented nature of frontal eye field neurons during memory tasks and demonstrate that the anticipation of behavioral outcomes plays a significant role in transforming and maintaining the contents of visual working memory.

3T vs. 7T fMRI: capturing early human memory consolidation after motor task utilizing the observed higher functional specificity of 7T

Objective

Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the blood oxygen level dependent (BOLD) response to distinct neuronal processes continues to be challenging. Here, we investigated the characteristics of 7 T-fMRI compared to 3 T-fMRI in the human brain beyond the effect of increased SNR and verified the benefits of 7 T-fMRI in the detection of tiny, highly specific modulations of functional connectivity in the resting state following a motor task.

Methods

18 healthy volunteers underwent two resting state and a stimulus driven measurement using a finger tapping motor task at 3 and 7 T, respectively. The SNR for each field strength was adjusted by targeted voxel size variation to minimize the effect of SNR on the field strength specific outcome. Spatial and temporal characteristics of resting state ICA, network graphs, and motor task related activated areas were compared. Finally, a graph theoretical approach was used to detect resting state modulation subsequent to a simple motor task.

Results

Spatial extensions of resting state ICA and motor task related activated areas were consistent between field strengths, but temporal characteristics varied, indicating that 7 T achieved a higher functional specificity of the BOLD response than 3 T-fMRI. Following the motor task, only 7 T-fMRI enabled the detection of highly specific connectivity modulations representing an "offline replay" of previous motor activation. Modulated connections of the motor cortex were directly linked to brain regions associated with memory consolidation.

Conclusion

These findings reveal how memory processing is initiated even after simple motor tasks, and that it begins earlier than previously shown. Thus, the superior capability of 7 T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases.

Selection within working memory impairs perceptual detection

There is broad consensus supporting the reciprocal influence of working memory (WM) and attention. Top-down mechanisms operate to cope with either environmental or internal demands. In that sense, it is possible to select an item within the contents of WM to endow it with prioritized access. Although evidence supports that maintaining an item in this privileged state does not rely on sustained visual attention, it is unknown whether selection within WM depends on perceptual attention. To answer this question, we recorded electrophysiological neural activity while participants performed a retro-cue task in which we inserted a detection task in the delay period after retro-cue presentation. Critically, the onset of to-be-detected near threshold stimuli was unpredictable, and thus, sustained perceptual spatial attention was needed to accomplish the detection task from the offset of the retro-cue. At a behavioral level, we found decreased visual detection when a WM representation was retro-cued. At a neural level, alpha oscillatory activity confirmed a spatial shift of attention to the retro-cued representation. We interpret the convergence of neural oscillations and behavioral data to point towards the theory that selection within WM could be accomplished through a perceptual attentional mechanism.

Redundant representations are required to disambiguate simultaneously presented complex stimuli

A pedestrian crossing a street during rush hour often looks and listens for potential danger. When they hear several different horns, they localize the cars that are honking and decide whether or not they need to modify their motor plan. How does the pedestrian use this auditory information to pick out the corresponding cars in visual space? The integration of distributed representations like these is called the assignment problem, and it must be solved to integrate distinct representations across but also within sensory modalities. Here, we identify and analyze a solution to the assignment problem: the representation of one or more common stimulus features in pairs of relevant brain regions-for example, estimates of the spatial position of cars are represented in both the visual and auditory systems. We characterize how the reliability of this solution depends on different features of the stimulus set (e.g., the size of the set and the complexity of the stimuli) and the details of the split representations (e.g., the precision of each stimulus representation and the amount of overlapping information). Next, we implement this solution in a biologically plausible receptive field code and show how constraints on the number of neurons and spikes used by the code force the brain to navigate a tradeoff between local and catastrophic errors. We show that, when many spikes and neurons are available, representing stimuli from a single sensory modality can be done more reliably across multiple brain regions, despite the risk of assignment errors. Finally, we show that a feedforward neural network can learn the optimal solution to the assignment problem, even when it receives inputs in two distinct representational formats. We also discuss relevant results on assignment errors from the human working memory literature and show that several key predictions of our theory already have support.

Effects of Experiencing CS-US Pairings on Instructed Fear Reversal

Fear learning allows us to identify and anticipate aversive events and adapt our behavior accordingly. This is often thought to rely on associative learning mechanisms where an initially neutral conditioned stimulus (CS) is repeatedly paired with an aversive unconditioned stimulus (US), eventually leading to the CS also being perceived as aversive and threatening. Importantly, however, humans also show verbal fear learning. Namely, they have the ability to change their responses to stimuli rapidly through verbal instructions about CS-US pairings. Past research on the link between experience-based and verbal fear learning indicated that verbal instructions about a reversal of CS-US pairings can fully override the effects of previously experienced CS-US pairings, as measured through fear ratings, skin conductance, and fear-potentiated startle. However, it remains an open question whether such instructions can also annul learned CS representations in the brain. Here, we used a fear reversal paradigm (female and male participants) in conjunction with representational similarity analysis of fMRI data to test whether verbal instructions fully override the effects of experienced CS-US pairings in fear-related brain regions or not. Previous research suggests that only the right amygdala should show lingering representations of previously experienced threat ("pavlovian trace"). Unexpectedly, we found evidence for the residual effect of prior CS-US experience to be much more widespread than anticipated, in the amygdala but also cortical regions like the dorsal anterior cingulate or dorsolateral prefrontal cortex. This finding shines a new light on the interaction of different fear learning mechanisms, at times with unexpected consequences.SIGNIFICANCE STATEMENT Humans are able to learn about aversive stimuli both from experience (i.e., repeated pairings of conditioned stimulus (CS) and unconditioned stimulus (US; pavlovian conditioning), and from verbal instructions about stimulus pairings. Understanding how experience-based and verbal learning processes interact is key for understanding the cognitive and neural underpinnings of fear learning. We tested whether prior aversive experiences (CS-US pairings) affected subsequent verbal learning, searching for lingering threat signals after verbal instructions reversed a CS from being threatening to being safe. While past research suggested such threat signals can only be found in the amygdala, we found evidence to be much more widespread, including the medial and lateral PFC. This highlights how experience-based and verbal learning processes interact to support adaptive behavior.

The intersection of the retrieval state and internal attention

Large-scale brain states or distributed patterns of brain activity modulate downstream processing and behavior. Sustained attention and memory retrieval states impact subsequent memory, yet how these states relate to one another is unclear. I hypothesize that internal attention is a central process of the retrieval state. The alternative is that the retrieval state specifically reflects a controlled, episodic retrieval mode, engaged only when intentionally accessing events situated within a spatiotemporal context. To test my hypothesis, I developed a mnemonic state classifier independently trained to measure retrieval state evidence and applied this classifier to a spatial attention task. I find that retrieval state evidence increases during delay and response intervals when participants are maintaining spatial information. Critically, retrieval state evidence is positively related to the amount of maintained spatial location information and predicts target detection reaction times. Together, these findings support the hypothesis that internal attention is a central process of the retrieval state.

Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular-Structural-Functional Co-alterations

Human cognition is usually underpinned by intrinsic structure and functional neural co-activation in spatially distributed brain regions. Owing to lacking an effective approach to quantifying the covarying of structure and functional responses, how the structural-functional circuits interact and how genes encode the relationships, to deepen our knowledge of human cognition and disease, are still unclear. Here, we propose a multimodal covariance network (MCN) construction approach to capture interregional covarying of the structural skeleton and transient functional activities for a single individual. We further explored the potential association between brain-wide gene expression patterns and structural-functional covarying in individuals involved in a gambling task and individuals with major depression disorder (MDD), adopting multimodal data from a publicly available human brain transcriptomic atlas and 2 independent cohorts. MCN analysis showed a replicable cortical structural-functional fine map in healthy individuals, and the expression of cognition- and disease phenotype-related genes was found to be spatially correlated with the corresponding MCN differences. Further analysis of cell type-specific signature genes suggests that the excitatory and inhibitory neuron transcriptomic changes could account for most of the observed correlation with task-evoked MCN differences. In contrast, changes in MCN of MDD patients were enriched for biological processes related to synapse function and neuroinflammation in astrocytes, microglia, and neurons, suggesting its promising application in developing targeted therapies for MDD patients. Collectively, these findings confirmed the correlations of MCN-related differences with brain-wide gene expression patterns, which captured genetically validated structural-functional differences at the cellular level in specific cognitive processes and psychiatric patients.

A rapid theta network mechanism for flexible information encoding

Flexible behavior requires gating mechanisms that encode only task-relevant information in working memory. Extant literature supports a theoretical division of labor whereby lateral frontoparietal interactions underlie information maintenance and the striatum enacts the gate. Here, we reveal neocortical gating mechanisms in intracranial EEG patients by identifying rapid, within-trial changes in regional and inter-regional activities that predict subsequent behavioral outputs. Results first demonstrate information accumulation mechanisms that extend prior fMRI (i.e., regional high-frequency activity) and EEG evidence (inter-regional theta synchrony) of distributed neocortical networks in working memory. Second, results demonstrate that rapid changes in theta synchrony, reflected in changing patterns of default mode network connectivity, support filtering. Graph theoretical analyses further linked filtering in task-relevant information and filtering out irrelevant information to dorsal and ventral attention networks, respectively. Results establish a rapid neocortical theta network mechanism for flexible information encoding, a role previously attributed to the striatum.

Rhythmic temporal coordination of neural activity prevents representational conflict during working memory

Selective attention¹ is characterized by alternating states associated with either attentional sampling or attentional shifting, helping to prevent functional conflicts by isolating function-specific neural activity in time.^2,3,4,5 We hypothesized that such rhythmic temporal coordination might also help to prevent representational conflicts during working memory.⁶ Multiple items can be simultaneously held in working memory, and these items can be represented by overlapping neural populations.^7,8,9 Traditional theories propose that the short-term storage of to-be-remembered items occurs through persistent neural activity,^10,11,12 but when neurons are simultaneously representing multiple items, persistent activity creates a potential for representational conflicts. In comparison, more recent, "activity-silent" theories of working memory propose that synaptic changes also contribute to short-term storage of to-be-remembered items.^13,14,15,16 Transient bursts in neural activity,¹⁷ rather than persistent activity, could serve to occasionally refresh these synaptic changes. Here, we used EEG and response times to test whether rhythmic temporal coordination helps to isolate neural activity associated with different to-be-remembered items, thereby helping to prevent representational conflicts. Consistent with this hypothesis, we report that the relative strength of different item representations alternates over time as a function of the frequency-specific phase. Although RTs were linked to theta (∼6 Hz) and beta (∼25 Hz) phases during a memory delay, the relative strength of item representations only alternated as a function of the beta phase. The present findings (1) are consistent with rhythmic temporal coordination being a general mechanism for preventing functional or representational conflicts during cognitive processes and (2) inform models describing the role of oscillatory dynamics in organizing working memory.^{13,18,19,20,21}.

Shared Neural Activity But Distinct Neural Dynamics for Cognitive Control in Monkey Prefrontal and Parietal Cortex

To better understand how prefrontal networks mediate forms of cognitive control disrupted in schizophrenia, we translated a variant of the AX continuous performance task that measures specific deficits in the human disease to 2 male monkeys and recorded neurons in PFC and parietal cortex during task performance. In the task, contextual information instructed by cue stimuli determines the response required to a subsequent probe stimulus. We found parietal neurons encoding the behavioral context instructed by cues that exhibited nearly identical activity to their prefrontal counterparts (Blackman et al., 2016). This neural population switched their preference for stimuli over the course of the trial depending on whether the stimuli signaled the need to engage cognitive control to override a prepotent response. Cues evoked visual responses that appeared in parietal neurons first, whereas population activity encoding contextual information instructed by cues was stronger and more persistent in PFC. Increasing cognitive control demand biased the representation of contextual information toward the PFC and augmented the temporal correlation of task-defined information encoded by neurons in the two areas. Oscillatory dynamics in local field potentials differed between cortical areas and carried as much information about task conditions as spike rates. We found that, at the single-neuron level, patterns of activity evoked by the task were nearly identical between the two cortical areas. Nonetheless, distinct population dynamics in PFC and parietal cortex were evident. suggesting differential contributions to cognitive control.SIGNIFICANCE STATEMENT We recorded neural activity in PFC and parietal cortex of monkeys performing a task that measures cognitive control deficits in schizophrenia. This allowed us to characterize computations performed by neurons in the two areas to support forms of cognitive control disrupted in the disease. Subpopulations of neurons in the two areas exhibited parallel modulations in firing rate; and as a result, all patterns of task-evoked activity were distributed between PFC and parietal cortex. This included the presence in both cortical areas of neurons reflecting proactive and reactive cognitive control dissociated from stimuli or responses in the task. However, differences in the timing, strength, synchrony, and correlation of information encoded by neural activity were evident, indicating differential contributions to cognitive control.

Attention in flux

Selective attention comprises essential infrastructural functions supporting cognition-anticipating, prioritizing, selecting, routing, integrating, and preparing signals to guide adaptive behavior. Most studies have examined its consequences, systems, and mechanisms in a static way, but attention is at the confluence of multiple sources of flux. The world advances, we operate within it, our minds change, and all resulting signals progress through multiple pathways within the dynamic networks of our brains. Our aim in this review is to raise awareness of and interest in three important facets of how timing impacts our understanding of attention. These include the challenges posed to attention by the timing of neural processing and psychological functions, the opportunities conferred to attention by various temporal structures in the environment, and how tracking the time courses of neural and behavioral modulations with continuous measures yields surprising insights into the workings and principles of attention.

Good-enough attentional guidance

Theories of attention posit that attentional guidance operates on information held in a target template within memory. The template is often thought to contain veridical target features, akin to a photograph, and to guide attention to objects that match the exact target features. However, recent evidence suggests that attentional guidance is highly flexible and often guided by non-veridical features, a subset of features, or only associated features. We integrate these findings and propose that attentional guidance maximizes search efficiency based on a 'good-enough' principle to rapidly localize candidate target objects. Candidates are then serially interrogated to make target-match decisions using more precise information. We suggest that good-enough guidance optimizes the speed-accuracy-effort trade-offs inherent in each stage of visual search.

The medial temporal lobe supports the quality of visual short-term memory representation

The quality of short-term memory (STM) underlies our ability to recall the exact details of a recent event, yet how the human brain enables this core cognitive function remains poorly understood. Here we use multiple experimental approaches to test the hypothesis that the quality of STM, such as its precision or fidelity, relies on the medial temporal lobe (MTL), a region commonly associated with the ability to distinguish similar information remembered in long-term memory. First, with intracranial recordings, we find that delay-period MTL activity retains item-specific STM content that is predictive of subsequent recall precision. Second, STM recall precision is associated with an increase in the strength of intrinsic MTL-to-neocortical functional connections during a brief retention interval. Finally, perturbing the MTL through electrical stimulation or surgical removal can selectively reduce STM precision. Collectively, these findings provide converging evidence that the MTL is critically involved in the quality of STM representation.

Prioritizing flexible working memory representations through retrospective attentional strengthening

Previous work has proposed two potential benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation is vital to high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude coupling was increased by valid retrospective attention and predicted the reduced random guessing rates. This long-range connection supported top-down information flow in the engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision by enhancing flexible target representation and emphasize the critical role of the frontoparietal attentional network in the control of WM representations.

Working memory control dynamics follow principles of spatial computing

Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts of beta and gamma oscillations. However, it is not clear how oscillations, reflecting coherent activity of millions of neurons, can selectively control individual WM items. Here we propose the novel concept of spatial computing where beta and gamma interactions cause item-specific activity to flow spatially across the network during a task. This way, control-related information such as item order is stored in the spatial activity independent of the detailed recurrent connectivity supporting the item-specific activity itself. The spatial flow is in turn reflected in low-dimensional activity shared by many neurons. We verify these predictions by analyzing local field potentials and neuronal spiking. We hypothesize that spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension.

The entorhinal-DG/CA3 pathway in the medial temporal lobe retains visual working memory of a simple surface feature

Classic models consider working memory (WM) and long-term memory as distinct mental faculties that are supported by different neural mechanisms. Yet, there are significant parallels in the computation that both types of memory require. For instance, the representation of precise item-specific memory requires the separation of overlapping neural representations of similar information. This computation has been referred to as pattern separation, which can be mediated by the entorhinal-DG/CA3 pathway of the medial temporal lobe (MTL) in service of long-term episodic memory. However, although recent evidence has suggested that the MTL is involved in WM, the extent to which the entorhinal-DG/CA3 pathway supports precise item-specific WM has remained elusive. Here, we combine an established orientation WM task with high-resolution fMRI to test the hypothesis that the entorhinal-DG/CA3 pathway retains visual WM of a simple surface feature. Participants were retrospectively cued to retain one of the two studied orientation gratings during a brief delay period and then tried to reproduce the cued orientation as precisely as possible. By modeling the delay-period activity to reconstruct the retained WM content, we found that the anterior-lateral entorhinal cortex (aLEC) and the hippocampal DG/CA3 subfield both contain item-specific WM information that is associated with subsequent recall fidelity. Together, these results highlight the contribution of MTL circuitry to item-specific WM representation.

Changes in behavioral priority influence the accessibility of working memory content

Evolving behavioral goals require the existence of selection mechanisms that prioritize task-relevant working memory (WM) content for action. Selecting an item stored in WM is known to blunt and/or reverse information loss in stimulus-specific representations of that item reconstructed from human brain activity, but extant studies have focused on all-or-none circumstances that allow or disallow an agent to select one of several items stored in WM. Conversely, behavioral studies suggest that humans can flexibly assign different levels of priority to different items stored in WM, but how doing so influences neural representations of WM content is unclear. One possibility is that assigning different levels of priority to items in WM influences the quality of those representations, resulting in more robust neural representations of high- vs. low-priority WM content. A second - and non-exclusive - possibility is that asymmetries in behavioral priority influence how rapidly neural representations of high- vs. low-priority WM content can be selected and reported. We tested these possibilities in two experiments by decoding high- and low-priority WM content from EEG recordings obtained while human volunteers performed a retrospectively cued WM task. Probabilistic changes in the behavioral relevance of a remembered item had no effect on our ability to decode it from EEG signals; instead, these changes influenced the latency at which above-chance decoding performance was reached. Thus, our results indicate that probabilistic changes in the behavioral relevance of WM content influence the ease with which memories can be selected independently of their strength.

Neural population dynamics of computing with synaptic modulations

In addition to long-timescale rewiring, synapses in the brain are subject to significant modulation that occurs at faster timescales that endow the brain with additional means of processing information. Despite this, models of the brain like recurrent neural networks (RNNs) often have their weights frozen after training, relying on an internal state stored in neuronal activity to hold task-relevant information. In this work, we study the computational potential and resulting dynamics of a network that relies solely on synapse modulation during inference to process task-relevant information, the multi-plasticity network (MPN). Since the MPN has no recurrent connections, this allows us to study the computational capabilities and dynamical behavior contributed by synapses modulations alone. The generality of the MPN allows for our results to apply to synaptic modulation mechanisms ranging from short-term synaptic plasticity (STSP) to slower modulations such as spike-time dependent plasticity (STDP). We thoroughly examine the neural population dynamics of the MPN trained on integration-based tasks and compare it to known RNN dynamics, finding the two to have fundamentally different attractor structure. We find said differences in dynamics allow the MPN to outperform its RNN counterparts on several neuroscience-relevant tests. Training the MPN across a battery of neuroscience tasks, we find its computational capabilities in such settings is comparable to networks that compute with recurrent connections. Altogether, we believe this work demonstrates the computational possibilities of computing with synaptic modulations and highlights important motifs of these computations so that they can be identified in brain-like systems.

Multiplexed Subspaces Route Neural Activity Across Brain-wide Networks

Cognition is flexible. Behaviors can change on a moment-by-moment basis. Such flexibility is thought to rely on the brain's ability to route information through different networks of brain regions in order to support different cognitive computations. However, the mechanisms that determine which network of brain regions is engaged are unknown. To address this, we combined cortex-wide calcium imaging with high-density electrophysiological recordings in eight cortical and subcortical regions of mice. Different dimensions within the population activity of each brain region were functionally connected with different cortex-wide 'subspace networks' of regions. These subspace networks were multiplexed, allowing a brain region to simultaneously interact with multiple independent, yet overlapping, networks. Alignment of neural activity within a region to a specific subspace network dimension predicted how neural activity propagated between regions. Thus, changing the geometry of the neural representation within a brain region could be a mechanism to selectively engage different brain-wide networks to support cognitive flexibility.

The geometry of cortical representations of touch in rodents

Neurons often encode highly heterogeneous non-linear functions of multiple task variables, a signature of a high-dimensional geometry. We studied the representational geometry in the somatosensory cortex of mice trained to report the curvature of objects touched by their whiskers. High-speed videos of the whiskers revealed that the task can be solved by linearly integrating multiple whisker contacts over time. However, the neural activity in somatosensory cortex reflects non-linear integration of spatio-temporal features of the sensory inputs. Although the responses at first appeared disorganized, we identified an interesting structure in the representational geometry: different whisker contacts are disentangled variables represented in approximately, but not fully, orthogonal subspaces of the neural activity space. This geometry allows linear readouts to perform a broad class of tasks of different complexities without compromising the ability to generalize to novel situations.

Turning Attention Inside Out: How Working Memory Serves Behavior

Flexible behavior requires guidance not only by sensations that are available immediately but also by relevant mental contents carried forward through working memory. Therefore, selective-attention functions that modulate the contents of working memory to guide behavior (inside-out) are just as important as those operating on sensory signals to generate internal contents (outside-in). We review the burgeoning literature on selective attention in the inside-out direction and underscore its functional, flexible, and future-focused nature. We discuss in turn the purpose (why), targets (what), sources (when), and mechanisms (how) of selective attention inside working memory, using visual working memory as a model. We show how the study of internal selective attention brings new insights concerning the core cognitive processes of attention and working memory and how considering selective attention and working memory together paves the way for a rich and integrated understanding of how mind serves behavior.

Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. During conflict i.e, when salience and goal each favor the selection of different targets, endogenous selection of the task-relevant target relies on top-down control. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, using a two-target free-choice luminance-reward selection task, we demonstrate that visual-movement neurons and not visual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent-beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.

Dynamics Are the Only Constant in Working Memory

In this short perspective, we reflect upon our tendency to use oversimplified and idiosyncratic tasks in a quest to discover general mechanisms of working memory. We discuss how the work of Mark Stokes and collaborators has looked beyond localized, temporally persistent neural activity and shifted focus toward the importance of distributed, dynamic neural codes for working memory. A critical lesson from this work is that using simplified tasks does not automatically simplify the neural computations supporting behavior (even if we wish it were so). Moreover, Stokes' insights about multidimensional dynamics highlight the flexibility of the neural codes underlying cognition and have pushed the field to look beyond static measures of working memory.

Defining attention from an auditory perspective

Attention prioritizes certain information at the expense of other information in ways that are similar across vision, audition, and other sensory modalities. It influences how-and even what-information is represented and processed, affecting brain activity at every level. Much of the core research into cognitive and neural mechanisms of attention has used visual tasks. However, the same top-down, object-based, and bottom-up attentional processes shape auditory perception, largely through the same underlying, cognitive networks. This article is categorized under: Psychology > Attention.

Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals

Humans can learn several tasks in succession with minimal mutual interference but perform more poorly when trained on multiple tasks at once. The opposite is true for standard deep neural networks. Here, we propose novel computational constraints for artificial neural networks, inspired by earlier work on gating in the primate prefrontal cortex, that capture the cost of interleaved training and allow the network to learn two tasks in sequence without forgetting. We augment standard stochastic gradient descent with two algorithmic motifs, so-called "sluggish" task units and a Hebbian training step that strengthens connections between task units and hidden units that encode task-relevant information. We found that the "sluggish" units introduce a switch-cost during training, which biases representations under interleaved training towards a joint representation that ignores the contextual cue, while the Hebbian step promotes the formation of a gating scheme from task units to the hidden layer that produces orthogonal representations which are perfectly guarded against interference. Validating the model on previously published human behavioural data revealed that it matches performance of participants who had been trained on blocked or interleaved curricula, and that these performance differences were driven by misestimation of the true category boundary.

Goals, usefulness and abstraction in value-based choice

Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our values on-the-fly. Studies in decision-making and neuroeconomics have often implicitly equated value to reward, emphasising the hedonic and automatic aspect of the value computation, while overlooking its functional (concept-like) nature. Here we outline the computational and biological principles that enable the brain to compute the usefulness of an option or action by creating abstractions that flexibly adapt to changing goals. We present different algorithmic architectures, comparing ideas from artificial intelligence (AI) and cognitive neuroscience with psychological theories and, when possible, drawing parallels.