Working Memory 2.0

Multiple-Timescale Representations of Space: Linking Memory to Navigation

When navigating through space, we must maintain a representation of our position in real time; when recalling a past episode, a memory can come back in a flash. Interestingly, the brain's spatial representation system, including the hippocampus, supports these two distinct timescale functions. How are neural representations of space used in the service of both real-world navigation and internal mnemonic processes? Recent progress has identified sequences of hippocampal place cells, evolving at multiple timescales in accordance with either navigational behaviors or internal oscillations, that underlie these functions. We review experimental findings on experience-dependent modulation of these sequential representations and consider how they link real-world navigation to time-compressed memories. We further discuss recent work suggesting the prevalence of these sequences beyond hippocampus and propose that these multiple-timescale mechanisms may represent a general algorithm for organizing cell assemblies, potentially unifying the dual roles of the spatial representation system in memory and navigation.

Theory of the Multiregional Neocortex: Large-Scale Neural Dynamics and Distributed Cognition

The neocortex is a complex neurobiological system with many interacting regions. How these regions work together to subserve flexible behavior and cognition has become increasingly amenable to rigorous research. Here, I review recent experimental and theoretical work on the modus operandi of a multiregional cortex. These studies revealed several general principles for the neocortical interareal connectivity, low-dimensional macroscopic gradients of biological properties across cortical areas, and a hierarchy of timescales for information processing. Theoretical work suggests testable predictions regarding differential excitation and inhibition along feedforward and feedback pathways in the cortical hierarchy. Furthermore, modeling of distributed working memory and simple decision-making has given rise to a novel mathematical concept, dubbed bifurcation in space, that potentially explains how different cortical areas, with a canonical circuit organization but gradients of biological heterogeneities, are able to subserve their respective (e.g., sensory coding versus executive control) functions in a modularly organized brain.

Where Actions Meet Outcomes: Medial Prefrontal Cortex, Central Thalamus, and the Basal Ganglia

Medial prefrontal cortex (mPFC) interacts with distributed networks that give rise to goal-directed behavior through afferent and efferent connections with multiple thalamic nuclei and recurrent basal ganglia-thalamocortical circuits. Recent studies have revealed individual roles for different thalamic nuclei: mediodorsal (MD) regulation of signaling properties in mPFC neurons, intralaminar control of cortico-basal ganglia networks, ventral medial facilitation of integrative motor function, and hippocampal functions supported by ventral midline and anterior nuclei. Large scale mapping studies have identified functionally distinct cortico-basal ganglia-thalamocortical subnetworks that provide a structural basis for understanding information processing and functional heterogeneity within the basal ganglia. Behavioral analyses comparing functional deficits produced by lesions or inactivation of specific thalamic nuclei or subregions of mPFC or the basal ganglia have elucidated the interdependent roles of these areas in adaptive goal-directed behavior. Electrophysiological recordings of mPFC neurons in rats performing delayed non-matching-to position (DNMTP) and other complex decision making tasks have revealed populations of neurons with activity related to actions and outcomes that underlie these behaviors. These include responses related to motor preparation, instrumental actions, movement, anticipation and delivery of action outcomes, memory delay, and spatial context. Comparison of results for mPFC, MD, and ventral pallidum (VP) suggest critical roles for mPFC in prospective processes that precede actions, MD for reinforcing task-relevant responses in mPFC, and VP for providing feedback about action outcomes. Synthesis of electrophysiological and behavioral results indicates that different networks connecting mPFC with thalamus and the basal ganglia are organized to support distinct functions that allow organisms to act efficiently to obtain intended outcomes.

Functional Significance of Human Resting-State Networks Hubs Identified Using MEG During the Transition From Childhood to Adulthood

Cortical hubs identified within resting-state networks (RSNs), areas of the cortex that have a higher-than-average number of connections, are known to be critical to typical cognitive functioning and are often implicated in disorders leading to abnormal cognitive functioning. Functionally defined cortical hubs are also known to change with age in the developing, maturing brain, mostly based on studies carried out using fMRI. We have recently used magnetoencephalography (MEG) to study the maturation trajectories of RSNs and their hubs from age 7 to 29 in 131 healthy participants with high temporal resolution. We found that maturation trajectories diverge as a function of the underlying cortical rhythm. Specifically, we found the beta band (13–30 Hz)-mediated RSNs became more locally efficient with maturation, i.e., more organized into clusters and connected with nearby regions, while gamma (31–80 Hz)-mediated RSNs became more globally efficient with maturation, i.e., prioritizing faster signal transmission between distant cortical regions. We also found that different sets of hubs were associated with each of these networks. To better understand the functional significance of this divergence, we wanted to examine the cortical functions associated with the identified hubs that grew or shrunk with maturation within each of these networks. To that end, we analyzed the results of the prior study using Neurosynth, a platform for large-scale, automated synthesis of fMRI data that links brain coordinates with their probabilistically associated terms. By mapping the Neurosynth terms associated with each of these hubs, we found that maturing hubs identified in the gamma band RSNs were more likely to be associated with bottom-up processes while maturing hubs identified in the beta band RSNs were more likely to be associated with top-down functions. The results were consistent with the idea that beta band-mediated networks preferentially support the maturation of top-down processing, while the gamma band-mediated networks preferentially support the maturation of bottom-up processing.

The Essential Role of Executive Attention in Unconscious Visuomotor Priming

Many reports have emphasized that unconscious processing demands attention. However, some studies were unable to observe a modulation of attentional load in subliminal visual processing. We proposed that the paradoxical phenomena could be explained based on whether the mental workload task was involved in central executive processes. In two experiments, by combining a masked shape discrimination task with an N-back task, executive attention availability for masked visuomotor processing decreased as the N-back task demand increased. We observed that unconscious visuomotor priming diminished with increasing executive attention load in Experiment 2; however, this pattern did not occur in Experiment 1. Further analysis verified that in Experiment 1, the role of the central executive in unconscious visuomotor priming was eliminated by the accuracy-speed trade-off since the higher load spatial N-back tasks with larger memory set sizes, compared with higher load verbal N-bask tasks, were quite difficult for the subjects to manage. Therefore, our results demonstrated that central executive load modulates unconscious visuomotor priming and that this modulation can be weakened by task difficulty. Collectively, by emphasizing the essential role of executive attention in subliminal visuomotor priming, the present work provides a powerful interpretation of prior debates and develops extant attention capacity limitations from the realm of consciousness to that of unconsciousness.

Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures

Time is of the essence in how neural codes, synchronies, and oscillations might function in encoding, representation, transmission, integration, storage, and retrieval of information in brains. This Hypothesis and Theory article examines observed and possible relations between codes, synchronies, oscillations, and types of neural networks they require. Toward reverse-engineering informational functions in brains, prospective, alternative neural architectures incorporating principles from radio modulation and demodulation, active reverberant circuits, distributed content-addressable memory, signal-signal time-domain correlation and convolution operations, spike-correlation-based holography, and self-organizing, autoencoding anticipatory systems are outlined. Synchronies and oscillations are thought to subserve many possible functions: sensation, perception, action, cognition, motivation, affect, memory, attention, anticipation, and imagination. These include direct involvement in coding attributes of events and objects through phase-locking as well as characteristic patterns of spike latency and oscillatory response. They are thought to be involved in segmentation and binding, working memory, attention, gating and routing of signals, temporal reset mechanisms, inter-regional coordination, time discretization, time-warping transformations, and support for temporal wave-interference based operations. A high level, partial taxonomy of neural codes consists of channel, temporal pattern, and spike latency codes. The functional roles of synchronies and oscillations in candidate neural codes, including oscillatory phase-offset codes, are outlined. Various forms of multiplexing neural signals are considered: time-division, frequency-division, code-division, oscillatory-phase, synchronized channels, oscillatory hierarchies, polychronous ensembles. An expandable, annotative neural spike train framework for encoding low- and high-level attributes of events and objects is proposed. Coding schemes require appropriate neural architectures for their interpretation. Time-delay, oscillatory, wave-interference, synfire chain, polychronous, and neural timing networks are discussed. Some novel concepts for formulating an alternative, more time-centric theory of brain function are discussed. As in radio communication systems, brains can be regarded as networks of dynamic, adaptive transceivers that broadcast and selectively receive multiplexed temporally-patterned pulse signals. These signals enable complex signal interactions that select, reinforce, and bind common subpatterns and create emergent lower dimensional signals that propagate through spreading activation interference networks. If memory traces share the same kind of temporal pattern forms as do active neuronal representations, then distributed, holograph-like content-addressable memories are made possible via temporal pattern resonances.

Does working memory activate the hippocampus during the late delay period?

The aim of the present discussion paper was to identify whether any fMRI studies have provided convincing evidence that the hippocampus is associated with working memory. The key outcome variable was the phase in which hippocampal activity was observed: study, early delay, late delay, and/or test. During working memory tasks, long-term memory processes can operate during the study phase, early delay phase (due to extended encoding), or test phase. Thus, working memory processes can be isolated from long-term memory processes during only the late delay period. Twenty-six working memory studies that reported hippocampal activity were systematically analyzed. Many experimental protocols and analysis parameters were considered including number of participants, stimulus type(s), number of items during the study phase, delay duration, task during the test phase, behavioral accuracy, relevant fMRI contrast(s), whether the information was novel or familiar, number of phases modeled, and whether activation timecourses were extracted. For studies that were able to identify activity in different phases, familiar information sometimes produced activity during the study phase and/or test phase, but never produced activity during the delay period. When early-delay phase and late-delay phase activity could be distinguished via modeling these phases separately or inspecting activation timecourses, novel information could additionally produce activity during the early delay phase. There was no convincing evidence of hippocampal activity during the late delay period. These results indicate that working memory does not activate the hippocampus and suggest a model of working memory where maintenance of novel information can foster long-term memory encoding.

Play Smart, Be Smart? Effect of Cognitively Engaging Physical Activity Interventions on Executive Function among Children 4~12 Years Old: A Systematic Review and Meta-Analysis

This paper aims to collect a compendium of randomized controlled trials (RCTs) exploring the effects of cognitively engaging physical activity (PA) interventions (basketball and floorball) on various domain-specific executive functions (EFs) in children aged 4 to 12. Following the PRISMA principle, 11 articles (total sample size: 2053) were analyzed for effect size and moderating impact with Stata 13.0 software. Overall EFs (SMD = 0.21, 95% CI 0.10 to 0.32, p < 0.05), updating (SMD = 0.17, 95% CI 0.03 to 0.30, p < 0.05) and shifting (SMD = 0.32, 95% CI 0.02 to 0.61, p < 0.05) were enhanced by cognitively engaging PA interventions. Age and BMI were found to have no effect on overall EFs performance in Meta regression. Overall EFs performance was improved by interventions with a session length (≥35 min) (SMD = 0.30, 95 % CI 0.10 to 0.49, p = 0.033). The review suggests that despite the moderate effect sizes, cognitively engaging PA may be an effective approach to improving EFs in children aged 4 to 12, especially updating and shifting.

Bipolar reasoning in feedback pathways

Instead of the conventional 0 and 1 values, bipolar reasoning uses -1, 0, +1 to describe double-sided judgements in which neutral elements are halfway between positive and negative evaluations (e.g., "uncertain" lies between "impossible" and "totally sure"). We discuss the state-of-the-art in bipolar logics and recall two medieval forerunners, i.e., William of Ockham and Nicholas of Autrecourt, who embodied a bipolar mode of thought that is eminently modern. Starting from the trivial observation that "once a wheat sheaf is sealed and tied up, the packed down straws display the same orientation", we work up a new theory of the bipolar nature of networks, suggesting that orthodromic (i.e., feedforward, bottom-up) projections might be functionally coupled with antidromic (i.e., feedback, top-down) projections via the mathematical apparatus of presheaves/globular sets. When an entrained oscillation such as a neuronal spike propagates from A to B, changes in B might lead to changes in A, providing unexpected antidromic effects. Our account points towards the methodological feasibility of novel neural networks in which message feedback is guaranteed by backpropagation mechanisms endowed in the same feedforward circuits. Bottom-up/top-down transmission at various coarse-grained network levels provides fresh insights in far-flung scientific fields such as object persistence, memory reinforcement, visual recognition, Bayesian inferential circuits and multidimensional activity of the brain. Implying that axonal stimulation by external sources might backpropagate and modify neuronal electric oscillations, our theory also suggests testable previsions concerning the optimal location of transcranial magnetic stimulation's coils in patients affected by drug-resistant epilepsy.

Spatio-temporal dynamics of large-scale electrophysiological networks during cognitive action control in healthy controls and Parkinson's disease patients

Among the cognitive symptoms that are associated with Parkinson's disease (PD), alterations in cognitive action control (CAC) are commonly reported in patients. CAC enables the suppression of an automatic action, in favor of a goal-directed one. The implementation of CAC is time-resolved and arguably associated with dynamic changes in functional brain networks. However, the electrophysiological functional networks involved, their dynamic changes, and how these changes are affected by PD, still remain unknown. In this study, to address this gap of knowledge, 10 PD patients and 10 healthy controls (HC) underwent a Simon task while high-density electroencephalography (HD-EEG) was recorded. Source-level dynamic connectivity matrices were estimated using the phase-locking value in the beta (12-25 Hz) and gamma (30-45 Hz) frequency bands. Temporal independent component analyses were used as a dimension reduction tool to isolate the task-related brain network states. Typical microstate metrics were quantified to investigate the presence of these states at the subject-level. Our results first confirmed that PD patients experienced difficulties in inhibiting automatic responses during the task. At the group-level, we found three functional network states in the beta band that involved fronto-temporal, temporo-cingulate and fronto-frontal connections with typical CAC-related prefrontal and cingulate nodes (e.g., inferior frontal cortex). The presence of these networks did not differ between PD patients and HC when analyzing microstates metrics, and no robust correlations with behavior were found. In the gamma band, five networks were found, including one fronto-temporal network that was identical to the one found in the beta band. These networks also included CAC-related nodes previously identified in different neuroimaging modalities. Similarly to the beta networks, no subject-level differences were found between PD patients and HC. Interestingly, in both frequency bands, the dominant network at the subject-level was never the one that was the most durably modulated by the task. Altogether, this study identified the dynamic functional brain networks observed during CAC, but did not highlight PD-related changes in these networks that might explain behavioral changes. Although other new methods might be needed to investigate the presence of task-related networks at the subject-level, this study still highlights that task-based dynamic functional connectivity is a promising approach in understanding the cognitive dysfunctions observed in PD and beyond.

Using Neural Networks to Uncover the Relationship between Highly Variable Behavior and EEG during a Working Memory Task with Distractors

Value-driven attention capture (VDAC) occurs when previously rewarded stimuli capture attention and impair goal-directed behavior. In a working memory (WM) task with VDAC-related distractors, we observe behavioral variability both within and across individuals. Individuals differ in their ability to maintain relevant information and ignore distractions. These cognitive components shift over time with changes in motivation and attention, making it difficult to identify underlying neural mechanisms of individual differences. In this study, we develop the first participant-specific feedforward neural network models of reaction time from neural data during a VDAC WM task. We used short epochs of electroencephalography (EEG) data from 16 participants to develop the feedforward neural network (NN) models of RT aimed at understanding both WM and VDAC. Using general linear models (GLM), we identified 20 EEG features to predict RT across participants (r=0.53±0.08). The linear model was compared to the NN model, which improved the predicted trial-by-trial RT for all participants (r=0.87±0.04). We found that right frontal gamma-band activity and fronto-posterior functional connectivity in the alpha, beta, and gamma bands explain individual differences. Our study shows that NN models can link neural activity to highly variable behavior and can identify potential new targets for neuromodulation interventions.

M/EEG Dynamics Underlying Reserve, Resilience, and Maintenance in Aging: A Review

Cognitive reserve and resilience refer to the set of processes allowing the preservation of cognitive performance in the presence of structural and functional brain changes. Investigations of these concepts have provided unique insights into the heterogeneity of cognitive and brain changes associated with aging. Previous work mainly relied on methods benefiting from a high spatial precision but a low temporal resolution, and thus the temporal brain dynamics underlying these concepts remains poorly known. Moreover, while spontaneous fluctuations of neural activity have long been considered as noise, recent work highlights its critical contribution to brain functions. In this study, we synthesized the current state of knowledge from magnetoencephalography (MEG) and electroencephalography (EEG) studies that investigated the contribution of maintenance of neural synchrony, and variability of brain dynamics, to cognitive changes associated with healthy aging and the progression of neurodegenerative disease (such as Alzheimer's disease). The reviewed findings highlight that compensations could be associated with increased synchrony of higher (>10 Hz) frequency bands. Maintenance of young-like synchrony patterns was also observed in healthy older individuals. Both maintenance and compensation appear to be highly related to preserved structural integrity (brain reserve). However, increased synchrony was also found to be deleterious in some cases and reflects neurodegenerative processes. These results provide major elements on the stability or variability of functional networks as well as maintenance of neural synchrony over time, and their association with individual cognitive changes with aging. These findings could provide new and interesting considerations about cognitive reserve, maintenance, and resilience of brain functions and cognition.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Proximal CA1 20-40 Hz power dynamics reflect trial-specific information processing supporting nonspatial sequence memory

The hippocampus is known to play a critical role in processing information about temporal context. However, it remains unclear how hippocampal oscillations are involved, and how their functional organization is influenced by connectivity gradients. We examined local field potential activity in CA1 as rats performed a nonspatial odor sequence memory task. We found that odor sequence processing epochs were characterized by distinct spectral profiles and proximodistal CA1 gradients of theta and 20-40 Hz power than track running epochs. We also discovered that 20-40 Hz power was predictive of sequence memory performance, particularly in proximal CA1 and during the plateau of high power observed in trials in which animals had to maintain their decision until instructed to respond. Altogether, these results provide evidence that dynamics of 20-40 Hz power along the CA1 axis are linked to trial-specific processing of nonspatial information critical to order judgments and are consistent with a role for 20-40 Hz power in gating information processing.

Boosting working memory: Uncovering the differential effects of tDCS and tACS

Working memory (WM) is essential for reasoning, decision making and problem solving. Recently, there has been an increasing effort in improving WM through non-invasive brain stimulation, especially transcranial direct and alternating current stimulation (tDCS/tACS). Studies suggest that tDCS and tACS can modulate WM performance, but large variability in research approaches hinders identification of optimal stimulation protocols and interpretation of study results. Moreover, it is unclear whether tDCS and tACS differentially affect WM. Here, we summarize and compare studies examining the effects of tDCS and tACS on WM performance in healthy adults. Following PRISMA-selection criteria, our systematic review resulted in 43 studies (29 tDCS, 11 tACS, 3 both) with a total of 1826 adult participants. For tDCS, only 4 out of 23 single-session studies reported effects on WM, while 7 out of 9 multi-session experiments showed positive effects on WM training. For tACS, 10 out of 14 studies demonstrated effects on WM, which were frequency dependent and robust for frontoparietal stimulation. Our review revealed no reliable effect of single-session tDCS on WM, but moderate effects of multi-session tDCS and single-session tACS. We discuss implications of these findings and future directions in the emerging research field of non-invasive brain stimulation and WM.

Distinct neural codes in primate hippocampus and lateral prefrontal cortex during associative learning in virtual environments

The hippocampus (HPC) and the lateral prefrontal cortex (LPFC) are two cortical areas of the primate brain deemed essential to cognition. Here, we hypothesized that the codes mediating neuronal communication in the HPC and LPFC microcircuits have distinctively evolved to serve plasticity and memory function at different spatiotemporal scales. We used a virtual reality task in which animals selected one of the two targets in the arms of the maze, according to a learned context-color rule. Our results show that during associative learning, HPC principal cells concentrate spikes in bursts, enabling temporal summation and fast synaptic plasticity in small populations of neurons and ultimately facilitating rapid encoding of associative memories. On the other hand, layer II/III LPFC pyramidal cells fire spikes more sparsely distributed over time. The latter would facilitate broadcasting of signals loaded in short-term memory across neuronal populations without necessarily triggering fast synaptic plasticity.

Intermittent theta burst stimulation improved visual-spatial working memory in treatment-resistant schizophrenia: A pilot study

BACKGROUND

Visual-spatial working memory (vsWM) impairment in treatment-resistant schizophrenia (TRS) currently has no satisfactory treatment. Our study aimed to improve vsWM function in TRS through intermittent theta burst stimulation (iTBS) using neuronavigation equipment to target the left dorsolateral prefrontal cortex.

METHOD

TRS patients (n = 59) were randomly allocated to receive iTBS (n = 33) or a sham treatment (n = 26) over 2 weeks. The participants including TRS patients and healthy controls (HCs) performed the vsWM n-back task, and TRS patients' neuroimaging data were acquired before and after treatment. All patients also underwent a battery of symptom measures to assess the severity of illness. The main outcome measure was the accuracy (ACC) of n-back target responses, particularly 3-back ACC.

RESULTS

The iTBS group showed considerable improvement in n-back ACC compared to the sham group, especially 3-back ACC. After iTBS, performance on the n-back task was comparable to that of HCs. The interaction (group × time) results showed increased fractional amplitude of low frequency fluctuations (fALFF) in the right occipital areas and decreased fALFF in the right precuneus. However, there was a negative correlation between the 3-back ACC and improved clinical symptoms scores. Improvements in 3-back ACC were positively correlated with activity in the right visual cortex.

CONCLUSIONS

Our study suggested that 2 weeks of iTBS intervention may be a novel, efficacious treatment for vsWM deficits in TRS, which can modulate the activity of local brain regions. iTBS can provide a solution for clinical treatment of TRS and may help patients approach normalcy.

[Phase amplitude coupling analysis of local field potentials in working memory of rats affected by transcranial magneto-acoustic-electrical stimulation]

Transcranial magneto-acoustic-electrical stimulation is a new non-invasive neuromodulation technology, in which the induced electric field generated by the coupling effect of ultrasound and static magnetic field are used to regulate the neural rhythm oscillation activity in the corresponding brain region. The purpose of this paper is to investigate the effects of transcranial magneto-acoustic-electrical stimulation on the information transfer and communication in neuronal clusters during memory. In the experiment, twenty healthy adult Wistar rats were randomly divided into a control group (five rats) and stimulation groups (fifteen rats). Transcranial magneto-acoustic-electrical stimulation of 0.05~0.15 T and 2.66~13.33 W/cm 2 was applied to the rats in stimulation groups, and no stimulation was applied to the rats in the control group. The local field potentials signals in the prefrontal cortex of rats during the T-maze working memory tasks were acquired. Then the coupling differences between delta rhythm phase, theta rhythm phase and gamma rhythm amplitude of rats in different parameter stimulation groups and control group were compared. The experimental results showed that the coupling intensity of delta and gamma rhythm in stimulation groups was significantly lower than that in the control group ( P<0.05), while the coupling intensity of theta and gamma rhythm was significantly higher than that in the control group ( P<0.05). With the increase of stimulation parameters, the degree of coupling between delta and gamma rhythm showed a decreasing trend, while the degree of coupling between theta and gamma rhythm tended to increase. The preliminary results of this paper indicated that transcranial magneto-acoustic-electrical stimulation inhibited delta rhythmic neuronal activity and enhanced the oscillation of theta and gamma rhythm in the prefrontal cortex, thus promoted the exchange and transmission of information between neuronal clusters in different spatial scales. This lays the foundation for further exploring the mechanism of transcranial magneto-acoustic-electrical stimulation in regulating brain memory function.

Unconscious priming shares a common resource pool with the manipulation subsystem

Background

Working memory can be subdivided into two relatively independent subordinate systems, the maintenance subsystem and the manipulation subsystem. Although the two subsystems are quite heterogeneous, research thus far has not adequately distinguished the resource pools of the two subsystems. Additionally, previous research on the relationship between working memory and unconscious priming is paradoxical. Different subsystems leading to different effects on unconscious priming might be the reason for the paradoxical research. Therefore, the current article aimed to distinguish the resource pools among two working-memory subsystems and to investigate the relationship between the two subsystems and unconscious priming.

Methods

To address these issues, a maintenance dual-task and a manipulation dual-task program were developed. Each participant had to separately perform the two dual tasks in a balanced order. In each dual task, participants first completed a masked priming task accompanied by working-memory load. As a control, participants completed a prime identification test to confirm that the processing of the masked prime was at the unconscious level. The maintenance dual task comprised sandwich masking trials accompanied by Sternberg trials, while the manipulation dual task comprised sandwich masking trials accompanied by N-back trials.

Results

The results of the prime identification test indicated that the participants could not consciously perceive the masked prime of both dual tasks. The results of the working-memory task of both dual tasks indicated that the load manipulation was successful for both dual tasks. Most importantly, the results of the masking task of both dual tasks showed that an increase in working-memory load decreased the magnitude of unconscious priming in the manipulation dual task, whereas an increase in working-memory load did not decrease unconscious priming in the maintenance dual task. These observations demonstrate that the manipulation subsystem, rather than the maintenance subsystem, interferes with unconscious priming. Together with previous research, we propose a two-pool attention resource model to explain the modulation of working memory on unconscious priming by dissociating the executive resource pool of the manipulation system from the retention resource pool of the maintenance system. Thus, the current work confirms and extends the extant literature about the dependence of unconscious processing on attention resources by suggesting that unconscious priming shares a common resource pool with the manipulation subsystem.

Elevated Gamma Connectivity in Nidopallium Caudolaterale of Pigeons during Spatial Path Adjustment

Simple Summary

Imagine that you need to reach a designated destination, but the familiar path you most often choose suddenly becomes impassable. Then, what will you do? Of course, you will try to adjust the path according to your cognition of the current environment and the goal. During this, how will be the spatial environment, especially the path adjustment process, be represented in your brain? That is a very interesting research topic. In this study, we attempted to explore the internal neural patterns within the brain, especially within the higher-order cognitive brain areas, by taking pigeons, a species with excellent navigation ability, as a model animal. The most classical detour paradigm was used to train pigeons in a task of spatial path adjustment, and the neural signals in pigeons’ nidopallium caudolaterale ((NCL) functionally similar to mammalian “prefrontal cortex”) were recorded. We found that the spatial path adjustment process is accompanied by modifications of the changes in spectral and connectivity properties of the neural activities in the NCL. The elevated gamma connectivity in the NCL found in this study supports the role of the NCL in spatial cognition and contributes to explaining the potential neural mechanism of path adjustment.

Abstract

Previous studies showed that spatial navigation depends on a local network including multiple brain regions with strong interactions. However, it is still not fully understood whether and how the neural patterns in avian nidopallium caudolaterale (NCL), which is suggested to play a key role in navigation as a higher cognitive structure, are modulated by the behaviors during spatial navigation, especially involved path adjustment needs. Hence, we examined neural activity in the NCL of pigeons and explored the local field potentials’ (LFPs) spectral and functional connectivity patterns in a goal-directed spatial cognitive task with the detour paradigm. We found the pigeons progressively learned to solve the path adjustment task when the learned path was blocked suddenly. Importantly, the behavioral changes during the adjustment were accompanied by the modifications in neural patterns in the NCL. Specifically, the spectral power in lower bands (1–4 Hz and 5–12 Hz) decreased as the pigeons were tested during the adjustment. Meanwhile, an elevated gamma (31–45 Hz and 55–80 Hz) connectivity in the NCL was also detected. These results and the partial least square discriminant analysis (PLS-DA) modeling analysis provide insights into the neural activities in the avian NCL during the spatial path adjustment, contributing to understanding the potential mechanism of avian spatial encoding. This study suggests the important role of the NCL in spatial learning, especially path adjustment in avian navigation.

Prefrontal pyramidal neurons are critical for all phases of working memory

The prefrontal cortex (PFC) is essential for working memory (WM) and has primarily been viewed as being responsible for maintaining information over a delay, but it is unclear whether it also plays a more general role during WM. Using task phase-specific optogenetic silencing of pyramidal neurons in the medial PFC (mPFC) of mice performing a spatial WM task, we find that the mPFC is required not only during the delay phase of the task but also during other phases requiring the encoding and retrieval of spatial information. Imaging of mPFC pyramidal neurons reveals that they are most strongly influenced by the animals' position and running direction, indicating a fundamental role in spatial navigation. Pyramidal neuron ensembles also represent to-be-remembered goal locations in a dynamic manner. Taken together, these results delineate the functional contribution of mPFC pyramidal neurons to WM, extending their role beyond the maintenance of information.

Decoding distributed oscillatory signals driven by memory and perception in the prefrontal cortex

Sensory perception and memory recall generate different conscious experiences. Although externally and internally driven neural activities signifying the same perceptual content overlap in the sensory cortex, their distribution in the prefrontal cortex (PFC), an area implicated in both perception and memory, remains elusive. Here, we test whether the local spatial configurations and frequencies of neural oscillations driven by perception and memory recall overlap in the macaque PFC using high-density electrocorticography and multivariate pattern analysis. We find that dynamically changing oscillatory signals distributed across the PFC in the delta-, theta-, alpha-, and beta-band ranges carry significant, but mutually different, information predicting the same feature of memory-recalled internal targets and passively perceived external objects. These findings suggest that the frequency-specific distribution of oscillatory neural signals in the PFC serves cortical signatures responsible for distinguishing between different types of cognition driven by external perception and internal memory.

Synaptic Variability and Cortical Gamma Oscillation Power in Schizophrenia

OBJECTIVE

Cognitive impairments in schizophrenia are associated with lower gamma oscillation power in the prefrontal cortex (PFC). Gamma power depends in part on excitatory drive to fast-spiking parvalbumin interneurons (PVIs). Excitatory drive to cortical neurons varies in strength, which could affect how these neurons regulate network oscillations. The authors investigated whether variability in excitatory synaptic strength across PVIs could contribute to lower prefrontal gamma power in schizophrenia.

METHODS

In postmortem PFC from 20 matched pairs of comparison and schizophrenia subjects, levels of vesicular glutamate transporter 1 (VGlut1) and postsynaptic density 95 (PSD95) proteins were quantified to assess variability in excitatory synaptic strength across PVIs. A computational model network was then used to simulate how variability in excitatory synaptic strength across fast-spiking (a defining feature of PVIs) interneurons (FSIs) regulates gamma power.

RESULTS

The variability of VGlut1 and PSD95 levels at excitatory inputs across PVIs was larger in schizophrenia relative to comparison subjects. This alteration was not influenced by schizophrenia-associated comorbid factors, was not present in monkeys chronically exposed to antipsychotic medications, and was not present in calretinin interneurons. In the model network, variability in excitatory synaptic strength across FSIs regulated gamma power by affecting network synchrony. Finally, greater synaptic variability interacted synergistically with other synaptic alterations in schizophrenia (i.e., fewer excitatory inputs to FSIs and lower inhibitory strength from FSIs) to robustly reduce gamma power.

CONCLUSIONS

The study findings suggest that greater variability in excitatory synaptic strength across PVIs, in combination with other modest synaptic alterations in these neurons, can markedly lower PFC gamma power in schizophrenia.

Aging-Related Alterations to Persistent Firing in the Lateral Entorhinal Cortex Contribute to Deficits in Temporal Associative Memory

With aging comes a myriad of different disorders, and cognitive decline is one of them. Studies have consistently shown a decline amongst aged subjects in their ability to acquire and maintain temporal associative memory. Defined as the memory of the association between two objects that are separated in time, temporal associative memory is dependent on neocortical structures such as the prefrontal cortex and temporal lobe structures. For this memory to be acquired, a mental trace of the first stimulus is necessary to bridge the temporal gap so the two stimuli can be properly associated. Persistent firing, the ability of the neuron to continue to fire action potentials even after the termination of a triggering stimulus, is one mechanism that is posited to support this mental trace. A recent study demonstrated a decline in persistent firing ability in pyramidal neurons of layer III of the lateral entorhinal cortex with aging, contributing to learning impairments in temporal associative memory acquisition. In this work, we explore the potential ways persistent firing in lateral entorhinal cortex (LEC) III supports temporal associative memory, and how aging may disrupt this mechanism within the temporal lobe system, resulting in impairment in this crucial behavior.

Mechanisms of distributed working memory in a large-scale network of macaque neocortex

Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating self-sustained activity. The mnemonic activity pattern along the cortical hierarchy indicates a transition in space, separating areas engaged in working memory and those which do not. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions, including the idea of counterstream inhibitory bias, the role of prefrontal areas in controlling distributed attractors, and the resilience of distributed activity to lesions or inactivation. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.

Neural Mechanisms of Working Memory Accuracy Revealed by Recurrent Neural Networks

Understanding the neural mechanisms of working memory has been a long-standing Neuroscience goal. Bump attractor models have been used to simulate persistent activity generated in the prefrontal cortex during working memory tasks and to study the relationship between activity and behavior. How realistic the assumptions of these models are has been a matter of debate. Here, we relied on an alternative strategy to gain insights into the computational principles behind the generation of persistent activity and on whether current models capture some universal computational principles. We trained Recurrent Neural Networks (RNNs) to perform spatial working memory tasks and examined what aspects of RNN activity accounted for working memory performance. Furthermore, we compared activity in fully trained networks and immature networks, achieving only imperfect performance. We thus examined the relationship between the trial-to-trial variability of responses simulated by the network and different aspects of unit activity as a way of identifying the critical parameters of memory maintenance. Properties that spontaneously emerged in the artificial network strongly resembled persistent activity of prefrontal neurons. Most importantly, these included drift of network activity during the course of a trial that was causal to the behavior of the network. As a consequence, delay period firing rate and behavior were positively correlated, in strong analogy to experimental results from the prefrontal cortex. These findings reveal that delay period activity is computationally efficient in maintaining working memory, as evidenced by unbiased optimization of parameters in artificial neural networks, oblivious to the properties of prefrontal neurons.

Differential gene expression in layer 3 pyramidal neurons across 3 regions of the human cortical visual spatial working memory network

Visual spatial working memory (vsWM) is mediated by a distributed cortical network composed of multiple nodes, including primary visual (V1), posterior parietal (PPC), and dorsolateral prefrontal (DLPFC) cortices. Feedforward and feedback information is transferred among these nodes via projections furnished by pyramidal neurons (PNs) located primarily in cortical layer 3. Morphological and electrophysiological differences among layer 3 PNs across these nodes have been reported; however, the transcriptional signatures underlying these differences have not been examined in the human brain. Here we interrogated the transcriptomes of layer 3 PNs from 39 neurotypical human subjects across 3 critical nodes of the vsWM network. Over 8,000 differentially expressed genes were detected, with more than 6,000 transcriptional differences present between layer 3 PNs in V1 and those in PPC and DLPFC. Additionally, over 600 other genes differed in expression along the rostral-to-caudal hierarchy formed by these 3 nodes. Moreover, pathway analysis revealed enrichment of genes in V1 related to circadian rhythms and in DLPFC of genes involved in synaptic plasticity. Overall, these results show robust regional differences in the transcriptome of layer 3 PNs, which likely contribute to regional specialization in their morphological and physiological features and thus in their functional contributions to vsWM.

Dependence of Working Memory on Coordinated Activity Across Brain Areas

Neural signatures of working memory (WM) have been reported in numerous brain areas, suggesting a distributed neural substrate for memory maintenance. In the current manuscript we provide an updated review of the literature focusing on intracranial neurophysiological recordings during WM in primates. Such signatures of WM include changes in firing rate or local oscillatory power within an area, along with measures of coordinated activity between areas based on synchronization between oscillations. In comparing the ability of various neural signatures in any brain area to predict behavioral performance, we observe that synchrony between areas is more frequently and robustly correlated with WM performance than any of the within-area neural signatures. We further review the evidence for alteration of inter-areal synchrony in brain disorders, consistent with an important role for such synchrony during behavior. Additionally, results of causal studies indicate that manipulating synchrony across areas is especially effective at influencing WM task performance. Each of these lines of research supports the critical role of inter-areal synchrony in WM. Finally, we propose a framework for interactions between prefrontal and sensory areas during WM, incorporating a range of experimental findings and offering an explanation for the observed link between intra-areal measures and WM performance.

Serendipitous Stimulation of Nucleus Basalis of Meynert-The Effect of Unintentional, Long-Term High-Frequency Stimulation on Cognition in Parkinson's Disease

There is a growing interest in deep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) as a potential therapeutic modality for Parkinson’s disease dementia (PDD). Low-frequency stimulation has yielded encouraging results in individual patients; however, these are not yet sustained in larger studies. With the aim to expand the understanding of NBM-DBS, we share our experience with serendipitous NBM-DBS in patients treated with DBS of the internal Globus pallidus (GPi) for Parkinson’s disease. Since NBM is anatomically located ventral to GPi, several GPi-treated patients appeared to have the distal contact of DBS-electrode(s) positioned in the NBM. We hypothesized that unintentional high-frequency NBM-DBS over a period of one year would result in the opposite effect of low-frequency NBM-stimulation and cause cognitive decline. We studied a cohort of 33 patients with bilateral high-frequency DBS in the GPi for Parkinson’s disease, of which twelve were unintentionally co-stimulated in NBM. The subgroups of unintentional unilateral (N = 7) and bilateral NBM-DBS (N = 5) were compared to the control group of bilateral GPi-DBS (N = 11). Here, we show that unintentional high-frequency NBM-DBS did not cause a significantly faster decline in cognitive function. Further research is warranted for characterizing the therapeutic role of NBM-DBS.

Exercise types and working memory components during development

Working memory is crucial to learning and academic success. Exercise has been found to benefit working memory in late life, but its effects during cognitive development are less clear. Building on findings that working memory is supported by the motor system, we highlight the sensitivity of different working memory components to acute and long-term exercise in children and adolescents. We also consider how the specific skill demands of endurance and coordinative exercise influence this sensitivity. Distinct effects of these exercise types are further linked with neurocognitive and neuroendocrine pathways. Our review suggests long-term rather than acute benefits of exercise for children and adolescents' working memory, which are more pronounced and specific for exercise with high coordinative demands.

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

Rhythmicity of Prefrontal Local Field Potentials after Nucleus Basalis Stimulation

The action of acetylcholine in the cortex is critical for cognitive functions and cholinergic drugs can improve functions such as attention and working memory. An alternative means of enhancing cholinergic neuromodulation in primates is the intermittent electrical stimulation of the cortical source of acetylcholine, the nucleus basalis (NB) of Meynert. NB stimulation generally increases firing rate of neurons in the prefrontal cortex, however its effects on single neurons are diverse and complex. We sought to understand how NB stimulation affects global measures of neural activity by recording and analyzing local field potentials (LFPs) in monkeys as they performed working memory tasks. NB stimulation primarily decreased power in the alpha frequency range during the delay interval of working memory tasks. The effect was consistent across variants of the task. No consistent modulation in the delay interval of the task was observed in the gamma frequency range, which has previously been implicated in the maintenance of working memory. Our results reveal global effects of cholinergic neuromodulation via deep brain stimulation, an emerging intervention for the improvement of cognitive function.

Spatial and Temporal Distribution of Information Processing in the Human Dorsal Anterior Cingulate Cortex

The dorsal anterior cingulate cortex (dACC) is a key node in the human salience network. It has been ascribed motor, pain-processing and affective functions. However, the dynamics of information flow in this complex region and how it responds to inputs remain unclear and are difficult to study using non-invasive electrophysiology. The area is targeted by neurosurgery to treat neuropathic pain. During deep brain stimulation surgery, we recorded local field potentials from this region in humans during a decision-making task requiring motor output. We investigated the spatial and temporal distribution of information flow within the dACC. We demonstrate the existence of a distributed network within the anterior cingulate cortex where discrete nodes demonstrate directed communication following inputs. We show that this network anticipates and responds to the valence of feedback to actions. We further show that these network dynamics adapt following learning. Our results provide evidence for the integration of learning and the response to feedback in a key cognitive region.

Breaking Down a Rhythm: Dissecting the Mechanisms Underlying Task-Related Neural Oscillations

A century worth of research has linked multiple cognitive, perceptual and behavioral states to various brain oscillations. However, the mechanistic roles and circuit underpinnings of these oscillations remain an area of active study. In this review, we argue that the advent of optogenetic and related systems neuroscience techniques has shifted the field from correlational to causal observations regarding the role of oscillations in brain function. As a result, studying brain rhythms associated with behavior can provide insight at different levels, such as decoding task-relevant information, mapping relevant circuits or determining key proteins involved in rhythmicity. We summarize recent advances in this field, highlighting the methods that are being used for this purpose, and discussing their relative strengths and limitations. We conclude with promising future approaches that will help unravel the functional role of brain rhythms in orchestrating the repertoire of complex behavior.

Traveling waves in the prefrontal cortex during working memory

Neural oscillations are evident across cortex but their spatial structure is not well- explored. Are oscillations stationary or do they form "traveling waves", i.e., spatially organized patterns whose peaks and troughs move sequentially across cortex? Here, we show that oscillations in the prefrontal cortex (PFC) organized as traveling waves in the theta (4-8Hz), alpha (8-12Hz) and beta (12-30Hz) bands. Some traveling waves were planar but most rotated. The waves were modulated during performance of a working memory task. During baseline conditions, waves flowed bidirectionally along a specific axis of orientation. Waves in different frequency bands could travel in different directions. During task performance, there was an increase in waves in one direction over the other, especially in the beta band.

Executive function during typing on computer

In recent decades, computer typing has become one of the fundamental tools for personal communication in everyday life. Typing is a multi-level hierarchical process that involves a large number of cognitive and physiological functions. Executive functions (EF), such as working memory and executive control, actively influence the inhibitory and activation processes during typing. Using the example of the work of the IF, one can observe the hierarchical organization of the central and peripheral parts of the nervous system during typing. However, there are not so many studies aimed at studying the neurophysiology of typing, and there were no works devoted to the study of EF in typing. In this regard, this article discusses the potential possibilities of studying EF by typing on a computer and provides examples of experiments and models that can be used in such studies. The article also describes the main psychophysiological studies in which typing was involved and a review of methods for studying and analyzing typing was conducted.

Working Memory and Language Contribution to Verbal Learning and Memory in Drug-Resistant Unilateral Focal Temporal Lobe Epilepsy

We aimed to investigate the working memory (WM) and language separate contributions to verbal learning and memory in patients with unilateral drug-resistant temporal lobe epilepsy (drTLE); additionally, we explored the mediating role of WM on the relationship between the number of antiepileptic drugs (AEDs) and short-term verbal memory. We retrospectively enrolled 70 patients with left (LTLE; n = 44) and right (RTLE; n = 26) drTLE. About 40 similar (age and education) healthy controls were used to determine impairments of groups at WM, language (naming and verbal fluency), and verbal learning and memory (five trials list-learning, story memory-immediate recall). To disentangle the effect of learning from the short-term memory, we separately analyzed performances at the first trial, last trial, and delayed-recall list-learning measures, in addition to the total learning capacity (the sum of the five trials). Correlation and regression analyses were used to assess the contribution of potential predictors while controlling for main clinical and demographic variables, and ascertain the mediating role of WM. All patients were impaired at WM and story memory, whereas only LTLE showed language and verbal learning deficits. In RTLE, language was the unique predictor for the most verbal learning performances, whereas WM predicted the results at story memory. In LTLE, WM was the sole predictor for short-term verbal learning (list-learning capacity; trial 1) and mediated the interaction between AED number and the performance at these measures, whereas language predicted the delayed-recall. Finally, WM confounded the performance at short-term memory in both groups, although at different measures. WM is impaired in drTLE and contributes to verbal memory and learning deficits in addition to language, mediating the relationship between AED number and short-term verbal memory in LTLE. Clinicians should consider this overlap when interpreting poor performance at verbal learning and memory in drTLE.

Personalizing Dual-Target Cortical Stimulation with Bayesian Parameter Optimization Successfully Treats Central Post-Stroke Pain: A Case Report

Central pain disorders, such as central post-stroke pain, remain clinically challenging to treat, despite many decades of pharmacological advances and the evolution of neuromodulation. For treatment refractory cases, previous studies have highlighted some benefits of cortical stimulation. Recent advances in new targets for pain and the optimization of neuromodulation encouraged our group to develop a dual cortical target approach paired with Bayesian optimization to provide a personalized treatment. Here, we present a case report of a woman who developed left-sided facial pain after multiple thalamic strokes. All previous pharmacologic and interventional treatments failed to mitigate the pain, leaving her incapacitated due to pain and medication side effects. She subsequently underwent a single burr hole for placement of motor cortex (M1) and dorsolateral prefrontal cortex (dlPFC) paddles for stimulation with externalization. By using Bayesian optimization to find optimal stimulation parameters and stimulation sites, we were able to reduce pain from an 8.5/10 to a 0/10 during a 5-day inpatient stay, with pain staying at or below a 2/10 one-month post-procedure. We found optimal treatment to be simultaneous stimulation of M1 and dlPFC without any evidence of seizure induction. In addition, we found no worsening in cognitive performance during a working memory task with dlPFC stimulation. This personalized approach using Bayesian optimization may provide a new foundation for treating central pain and other functional disorders through systematic evaluation of stimulation parameters.

Gamma Oscillations in Alzheimer’s Disease and Their Potential Therapeutic Role

Despite decades of research, Alzheimer’s Disease (AD) remains a lethal neurodegenerative disorder for which there are no effective treatments. This review examines the latest evidence of a novel and newly introduced perspective, which focuses on the restoration of gamma oscillations and investigates their potential role in the treatment of AD. Gamma brain activity (∼25–100 Hz) has been well-known for its role in cognitive function, including memory, and it is fundamental for healthy brain activity and intra-brain communication. Aberrant gamma oscillations have been observed in both mice AD models and human AD patients. A recent line of work demonstrated that gamma entrainment, through auditory and visual sensory stimulation, can effectively attenuate AD pathology and improve cognitive function in mice models of the disease. The first evidence from AD patients indicate that gamma entrainment therapy can reduce loss of functional connectivity and brain atrophy, improve cognitive function, and ameliorate several pathological markers of the disease. Even though research is still in its infancy, evidence suggests that gamma-based therapy may have a disease-modifying effect and has signified a new and promising era in AD research.

Decoding Color Visual Working Memory from EEG Signals Using Graph Convolutional Neural Networks

Color has an important role in object recognition and visual working memory (VWM). Decoding color VWM in the human brain is helpful to understand the mechanism of visual cognitive process and evaluate memory ability. Recently, several studies showed that color could be decoded from scalp electroencephalogram (EEG) signals during the encoding stage of VWM, which process visible information with strong neural coding. Whether color could be decoded from other VWM processing stages, especially the maintaining stage which processes invisible information, is still unknown. Here, we constructed an EEG color graph convolutional network model (ECo-GCN) to decode colors during different VWM stages. Based on graph convolutional networks, ECo-GCN considers the graph structure of EEG signals and may be more efficient in color decoding. We found that (1) decoding accuracies for colors during the encoding, early, and late maintaining stages were 81.58%, 79.36%, and 77.06%, respectively, exceeding those during the pre-stimuli stage (67.34%), and (2) the decoding accuracy during maintaining stage could predict participants' memory performance. The results suggest that EEG signals during the maintaining stage may be more sensitive than behavioral measurement to predict the VWM performance of human, and ECo-GCN provides an effective approach to explore human cognitive function.

Working memory capacity of crows and monkeys arises from similar neuronal computations

Complex cognition relies on flexible working memory, which is severely limited in its capacity. The neuronal computations underlying these capacity limits have been extensively studied in humans and in monkeys, resulting in competing theoretical models. We probed the working memory capacity of crows (Corvus corone) in a change detection task, developed for monkeys (Macaca mulatta), while we performed extracellular recordings of the prefrontal-like area nidopallium caudolaterale. We found that neuronal encoding and maintenance of information were affected by item load, in a way that is virtually identical to results obtained from monkey prefrontal cortex. Contemporary neurophysiological models of working memory employ divisive normalization as an important mechanism that may result in the capacity limitation. As these models are usually conceptualized and tested in an exclusively mammalian context, it remains unclear if they fully capture a general concept of working memory or if they are restricted to the mammalian neocortex. Here, we report that carrion crows and macaque monkeys share divisive normalization as a neuronal computation that is in line with mammalian models. This indicates that computational models of working memory developed in the mammalian cortex can also apply to non-cortical associative brain regions of birds.

Determinants of bilingualism predict dynamic changes in resting state EEG oscillations

This study uses resting state EEG data from 103 bilinguals to understand how determinants of bilingualism may reshape the mind/brain. Participants completed the LSBQ, which quantifies language use and crucially the division of labor of dual-language use in diverse activities and settings over the lifespan. We hypothesized correlations between the degree of active bilingualism with power of neural oscillations in specific frequency bands. Moreover, we anticipated levels of mean coherence (connectivity between brain regions) to vary by degree of bilingual language experience. Results demonstrated effects of Age of L2/2L1 onset on high beta and gamma powers. Higher usage of the non-societal language at home and society modulated indices of functional connectivity in theta, alpha and gamma frequencies. Results add to the emerging literature on the neuromodulatory effects of bilingualism for rs-EEG, and are in line with claims that bilingualism effects are modulated by degree of engagement with dual-language experiential factors.

Brain rhythms define distinct interaction networks with differential dependence on anatomy

Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent. Thus, the rhythms defined distinct interaction networks. Importantly, networks of coherence and GC were not explained by the spatial distributions of the strengths of the rhythms. Those networks, particularly the GC networks, contained clear modules, with typically one dominant rhythm per module. To understand how this distinctiveness and modularity arises on a common anatomical backbone, we correlated, across 91 area pairs, the metrics of functional interaction with those of anatomical projection strength. Anatomy was primarily related to coherence and GC, with the largest effect sizes for GC. The correlation differed markedly between rhythms, being less pronounced for the beta and strongest for the gamma rhythm.

Theta Dynamics Contribute to Retrieving Motor Plans after Interruptions in the Primate Premotor Area

To achieve a behavioral goal, we often need to maintain an internal action plan against external interruption and thereafter retrieve the action plan. We recently found that the maintenance and updating of motor plans are reflected by reciprocal changes in the beta and gamma power of the local field potential (LFP) of the primate medial motor areas. In particular, the maintenance of the immediate motor plan is supported by enhanced beta oscillations. However, it is unclear how the brain manages to maintain and retrieve the internal action plan against interruptions. Here, we show that dynamic theta changes contribute to the maintenance of the action plan. Specifically, the power of the theta frequency band (4-10 Hz) of LFPs increased before and during the interruption in the dorsal premotor areas in two monkeys. Without theta enhancement before the interruption, retrieval of the internal action plan was impaired. Theta and beta oscillations showed distinct changes depending on the behavioral context. Our results demonstrate that immediate and suspended motor plans are supported by the beta and theta oscillatory components of LFPs. Motor cortical theta oscillations may contribute to bridging motor plans across behavioral interruptions in a prospective manner.

Age-Related Differences in Resting-State EEG and Allocentric Spatial Working Memory Performance

During normal aging resting-state brain activity changes and working memory performance declines as compared to young adulthood. Interestingly, previous studies reported that different electroencephalographic (EEG) measures of resting-state brain activity may correlate with working memory performance at different ages. Here, we recorded resting-state EEG activity and tested allocentric spatial working memory in healthy young (20-30 years) and older (65-75 years) adults. We adapted standard EEG methods to record brain activity in mobile participants in a non-shielded environment, in both eyes closed and eyes open conditions. Our study revealed some age-group differences in resting-state brain activity that were consistent with previous results obtained in different recording conditions. We confirmed that age-group differences in resting-state EEG activity depend on the recording conditions and the specific parameters considered. Nevertheless, lower theta-band and alpha-band frequencies and absolute powers, and higher beta-band and gamma-band relative powers were overall observed in healthy older adults, as compared to healthy young adults. In addition, using principal component and regression analyses, we found that the first extracted EEG component, which represented mainly theta, alpha and beta powers, correlated with spatial working memory performance in older adults, but not in young adults. These findings are consistent with the theory that the neurobiological bases of working memory performance may differ between young and older adults. However, individual measures of resting-state EEG activity could not be used as reliable biomarkers to predict individual allocentric spatial working memory performance in young or older adults.

Neural circuits and symbolic processing

The ability to use symbols is a defining feature of human intelligence. However, neuroscience has yet to explain the fundamental neural circuit mechanisms for flexibly representing and manipulating abstract concepts. This article will review the research on neural models for symbolic processing. The review first focuses on the question of how symbols could possibly be represented in neural circuits. The review then addresses how neural symbolic representations could be flexibly combined to meet a wide range of reasoning demands. Finally, the review assesses the research on program synthesis and proposes that the most flexible neural representation of symbolic processing would involve the capacity to rapidly synthesize neural operations analogous to lambda calculus to solve complex cognitive tasks.

Multichannel anodal tDCS over the left dorsolateral prefrontal cortex in a paediatric population

Methodological studies investigating transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (lDLPFC) in paediatric populations are limited. Therefore, we investigated in a paediatric population whether stimulation success of multichannel tDCS over the lDLPFC depends on concurrent task performance and individual head anatomy. In a randomised, sham-controlled, double-blind crossover study 22 healthy participants (10–17 years) received 2 mA multichannel anodal tDCS (atDCS) over the lDLPFC with and without a 2-back working memory (WM) task. After stimulation, the 2-back task and a Flanker task were performed. Resting state and task-related EEG were recorded. In 16 participants we calculated the individual electric field (E-field) distribution. Performance and neurophysiological activity in the 2-back task were not affected by atDCS. atDCS reduced reaction times in the Flanker task, independent of whether atDCS had been combined with the 2-back task. Flanker task related beta oscillation increased following stimulation without 2-back task performance. atDCS effects were not correlated with the E-field. We found no effect of multichannel atDCS over the lDLPFC on WM in children/adolescents but a transfer effect on interference control. While this effect on behaviour was independent of concurrent task performance, neurophysiological activity might be more sensitive to cognitive activation during stimulation. However, our results are limited by the small sample size, the lack of an active control group and variations in WM performance.