Working memory enhancement using real-time phase-tuned transcranial alternating current stimulation

BACKGROUND

Prior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8-14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS has not been feasible so far due to stimulation artifacts preventing continuous phase tracking.

OBJECTIVES AND HYPOTHESIS

We aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag.

METHODS

We developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead.

RESULTS

WM accuracy improved in a phase lag dependent manner (p = 0.0350) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330° phase lag between tACS and ongoing alpha oscillations (p = 0.00273, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p = 0.0248) and phase (p = 0.0270) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation.

CONCLUSIONS

Our results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications.

Effective connectivity of working memory performance: a DCM study of MEG data

Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.

Neural alpha oscillations index context-driven perception of ambiguous vowel sequences

Perception of bistable stimuli is influenced by prior context. In some cases, the interpretation matches with how the preceding stimulus was perceived; in others, it tends to be the opposite of the previous stimulus percept. We measured high-density electroencephalography (EEG) while participants were presented with a sequence of vowels that varied in formant transition, promoting the perception of one or two auditory streams followed by an ambiguous bistable sequence. For the bistable sequence, participants were more likely to report hearing the opposite percept of the one heard immediately before. This auditory contrast effect coincided with changes in alpha power localized in the left angular gyrus and left sensorimotor and right sensorimotor/supramarginal areas. The latter correlated with participants' perception. These results suggest that the contrast effect for a bistable sequence of vowels may be related to neural adaptation in posterior auditory areas, which influences participants' perceptual construal level of ambiguous stimuli.

Alpha oscillatory activity is causally linked to working memory retention

Although previous studies have reported correlations between alpha oscillations and the "retention" subprocess of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain oscillations. Conventional transcranial alternating current stimulation (tACS) is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention subprocess). Here, we developed an online phase-corrected tACS system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits the modulation of brain oscillations at the target stimulation frequency within a short stimulation period and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to participants during the retention subprocess of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. These findings strongly support a causal link between alpha oscillations and WM retention and illustrate the broad application prospects of phase-corrected tACS.

Design Meets Neuroscience: An Electroencephalogram Study of Design Thinking in Concept Generation Phase

Extant research on design thinking is subjective and limited. This manuscript combines protocol analysis and electroencephalogram (EEG) to read design thoughts in the core design activities of concept generation phase. The results suggest that alpha band power had event related synchronization (ERS) in the scenario task and divergent thinking occupies a dominant position. However, it had event related desynchronization (ERD) in analogy and inference activities, etc., and it is stronger for mental pressure and exercised cognitive processing. In addition, the parietooccipital area differs significantly from other brain areas in most design activities. This study explores the relationship of different design thinking and EEG data, which is innovative and professional in the field of design, providing a more objective data basis and evaluation method for future applied research and diverse educational practices.

Cognitive and emotional regulation processes of spontaneous facial self-touch are activated in the first milliseconds of touch: Replication of previous EEG findings and further insights

Spontaneously touching one’s own face (sFST) is an everyday behavior that occurs in people of all ages, worldwide. It is—as opposed to actively touching the own face—performed without directing one’s attention to the action, and it serves neither instrumental (scratching, nose picking) nor communicative purposes. These sFST have been discussed in the context of self-regulation, emotional homeostasis, working memory processes, and attention focus. Even though self-touch research dates back decades, neuroimaging studies of this spontaneous behavior are basically nonexistent. To date, there is only one electroencephalography study that analyzed spectral power changes before and after sFST in 14 participants. The present study replicates the previous study on a larger sample. Sixty participants completed a delayed memory task of complex haptic relief stimuli while distracting sounds were played. During the retention interval 44 of the participants exhibited spontaneous face touch. Spectral power analyses corroborated the results of the replicated study. Decreased power shortly before sFST and increased power right after sFST indicated an involvement of regulation of attentional, emotional, and working memory processes. Additional analyses of spectral power changes during the skin contact phase of sFST revealed that significant neurophysiological changes do not occur while skin contact is in progress but at the beginning of sFST (movement toward face and initial skin contact). The present findings clearly illustrate the complexity of sFST and that the specific trigger mechanisms and functions of this spontaneous behavior need to be further investigated in controlled, experimental studies.

Spacetime in the brain: rapid brain network reorganization in visual processing and recovery

Functional connectivity networks (FCN) are the physiological basis of brain synchronization to integrating neural activity. They are not rigid but can reorganize under pathological conditions or during mental or behavioral states. However, because mental acts can be very fast, like the blink of an eye, we now used the visual system as a model to explore rapid FCN reorganization and its functional impact in normal, abnormal and post treatment vision. EEG-recordings were time-locked to visual stimulus presentation; graph analysis of neurophysiological oscillations were used to characterize millisecond FCN dynamics in healthy subjects and in patients with optic nerve damage before and after neuromodulation with alternating currents stimulation and were correlated with visual performance. We showed that rapid and transient FCN synchronization patterns in humans can evolve and dissolve in millisecond speed during visual processing. This rapid FCN reorganization is functionally relevant because disruption and recovery after treatment in optic nerve patients correlated with impaired and recovered visual performance, respectively. Because FCN hub and node interactions can evolve and dissolve in millisecond speed to manage spatial and temporal neural synchronization during visual processing and recovery, we propose “Brain Spacetime” as a fundamental principle of the human mind not only in visual cognition but also in vision restoration.

Decoding working memory task condition using magnetoencephalography source level long-range phase coupling patterns

OBJECTIVE

The objective of the study is to identify phase coupling patterns that are shared across subjects via a machine learning approach that utilises source space magnetoencephalography (MEG) phase coupling data from a working memory (WM) task. Indeed, phase coupling of neural oscillations is putatively a key factor for communication between distant brain areas and is therefore crucial in performing cognitive tasks, including WM. Previous studies investigating phase coupling during cognitive tasks have often focused on a few a priori selected brain areas or a specific frequency band, and the need for data-driven approaches has been recognised. Machine learning techniques have emerged as valuable tools for the analysis of neuroimaging data since they catch fine-grained differences in the multivariate signal distribution. Here, we expect that these techniques applied to MEG phase couplings can reveal WM-related processes that are shared across individuals.

APPROACH

We analysed WM data collected as part of the Human Connectome Project. The MEG data were collected while subjects (n = 83) performed N-back WM tasks in two different conditions, namely 2-back (WM condition) and 0-back (control condition). We estimated phase coupling patterns (multivariate phase slope index) for both conditions and for theta, alpha, beta, and gamma bands. The obtained phase coupling data were then used to train a linear support vector machine in order to classify which task condition the subject was performing with an across-subject cross-validation approach. The classification was performed separately based on the data from individual frequency bands and with all bands combined (multiband). Finally, we evaluated the relative importance of the different features (phase couplings) for classification by the means of feature selection probability.

MAIN RESULTS

The WM condition and control condition were successfully classified based on the phase coupling patterns in the theta (62% accuracy) and alpha bands (60% accuracy) separately. Importantly, the multiband classification showed that phase coupling patterns not only in the theta and alpha but also in the gamma bands are related to WM processing, as testified by improvement in classification performance (71%).

SIGNIFICANCE

Our study successfully decoded WM tasks using MEG source space functional connectivity. Our approach, combining across-subject classification and a multidimensional metric recently developed by our group, is able to detect patterns of connectivity that are shared across individuals. In other words, the results are generalisable to new individuals and allow meaningful interpretation of task-relevant phase coupling patterns.

Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review

Brain oscillations likely play a significant role in the storage of information in working memory (WM). Despite the wide popularity of the topic, current attempts to summarize the research in the field are narrative reviews. We address this gap by providing a descriptive systematic review, in which we investigated oscillatory correlates of maintenance of verbal and visual information in WM. The systematic approach enabled us to challenge some common views popularized by previous research. The identified literature (100 EEG/MEG studies) highlighted the importance of theta oscillations in verbal WM: frontal midline theta enhanced with load in most verbal studies, while more equivocal results have been obtained in visual studies. Increasing WM load affected alpha activity in most studies, but the direction of the effect was inconsistent: the ratio of studies that found alpha increase versus decrease with increasing load was 80/20% in the verbal WM domain and close to 60/40% in the visual domain. Alpha asymmetry (left < right) was a common finding in both verbal and visual WM studies. Beta and gamma activity studies yielded the least convincing data: a diversity in the spatial and frequency distribution of beta activity prevented us from making a coherent conclusion; gamma rhythm was virtually neglected in verbal WM studies with no systematic support for sustained gamma changes during the delay in EEG studies in general.

Patterns of Focal- and Large-Scale Synchronization in Cognitive Control and Inhibition: A Review

Neural synchronization patterns are involved in several complex cognitive functions and constitute a growing trend in neuroscience research. While synchrony patterns in working memory have been extensively discussed, a complete understanding of their role in cognitive control and inhibition is still elusive. Here, we provide an up-to-date review on synchronization patterns underlying behavioral inhibition, extrapolating common grounds, and dissociating features with other inhibitory functions. Moreover, we suggest a schematic conceptual framework and highlight existing gaps in the literature, current methodological challenges, and compelling research questions for future studies.

Neuropsychophysiological Measures of Alcohol Dependence: Can We Use EEG in the Clinical Assessment?

Addiction management is complex, and it requires a bio-psycho-social perspective, that ought to consider the multiple etiological and developmental factors. Because of this, a large amount of resources has been allocated to assess the vulnerability to dependence, i.e., to identify the processes underlying the transition from substance use to dependence, as well as its course, in order to determine the key points in its prevention, treatment, and recovery. Consequently, knowledge \from neuroscience must be taken into account, which is why different initiatives have emerged with this objective, such as the "Research Domain Criteria" (RDoC), and the "Addiction Neuroclinical Assessment" (ANA). Particularly, neuropsychophysiological measures could be used as markers of cognitive and behavioral attributes or traits in alcohol dependence, and even trace clinical change. In this way, the aim of this narrative review is to provide an overview following ANA clinical framework, to the most robust findings in neuropsychophysiological changes in alcohol dependence, that underlie the main cognitive domains implicated in addiction: incentive salience, negative emotionality, and executive functioning. The most consistent results have been found in event-related potential (ERP) analysis, especially in the P3 component, that could show a wide clinical utility, mainly for the executive functions. The review also shows the usefulness of other components, implicated in affective and substance-related processing (P1, N1, or the late positive potential LPP), as well as event-related oscillations, such as theta power, with a possible use as vulnerability or clinical marker in alcohol dependence. Finally, new tools emerging from psychophysiology research, based on functional connectivity or brain graph analysis could help toward a better understanding of altered circuits in alcohol dependence, as well as communication efficiency and effort during mental operations. This review concludes with an examination of these tools as possible markers in the clinical field and discusses methodological differences, the need for more replicability studies and incipient lines of work. It also uses consistent findings in psychophysiology to draw possible treatment targets and cognitive profiles in alcohol dependence.

Frontoparietal Network Connectivity During an N-Back Task in Adults With Autism Spectrum Disorder

BACKGROUND

Short-term and working memory (STM and WM) deficits have been demonstrated in individuals with autism spectrum disorder (ASD) and may emerge through atypical functional activity and connectivity of the frontoparietal network, which exerts top-down control necessary for successful STM and WM processes. Little is known regarding the spectral properties of the frontoparietal network during STM or WM processes in ASD, although certain neural frequencies have been linked to specific neural mechanisms.

METHODS

We analysed magnetoencephalographic data from 39 control adults (26 males; 27.15 ± 5.91 years old) and 40 adults with ASD (26 males; 27.17 ± 6.27 years old) during a 1-back condition (STM) of an n-back task, and from a subset of this sample during a 2-back condition (WM). We performed seed-based connectivity analyses using regions of the frontoparietal network. Interregional synchrony in theta, alpha, and beta bands was assessed with the phase difference derivative and compared between groups during periods of maintenance and recognition.

RESULTS

During maintenance of newly presented vs. repeated stimuli, the two groups did not differ significantly in theta, alpha, or beta phase synchrony for either condition. Adults with ASD showed alpha-band synchrony in a network containing the right dorsolateral prefrontal cortex, bilateral inferior parietal lobules (IPL), and precuneus in both 1- and 2-back tasks, whereas controls demonstrated alpha-band synchrony in a sparser set of regions, including the left insula and IPL, in only the 1-back task. During recognition of repeated vs. newly presented stimuli, adults with ASD exhibited decreased theta-band connectivity compared to controls in a network with hubs in the right inferior frontal gyrus and left IPL in the 1-back condition. Whilst there were no group differences in connectivity in the 2-back condition, adults with ASD showed no frontoparietal network recruitment during recognition, whilst controls activated networks in the theta and beta bands.

CONCLUSIONS

Our findings suggest that since adults with ASD performed well on the n-back task, their appropriate, but effortful recruitment of alpha-band mechanisms in the frontoparietal network to maintain items in STM and WM may compensate for atypical modulation of this network in the theta band to recognise previously presented items in STM.

Brain functional connectivity after cognitive-bias modification and behavioral changes in abstinent alcohol-use disorder patients

The use of the cognitive-bias modification (CBM) method has emerged as a therapeutic complement in the treatment of alcoholism, producing changes at behavioral and brain level. Nevertheless, the impact of the CBM procedure could be improved by the memory retrieval-extinction process (REP). Different studies have demonstrated that the retrieval of drug memories before extinction training later reduced the reinstatement of drug-seeking behavior. The main aim of this work was to study the effect of the CBM procedure itself, as well as in combination with the activation of alcohol-related memories, on the brain oscillatory activity of abstinent patients with alcohol-use disorder. The study sample comprised 33 patients divided into three groups: A-CBM (alcohol-related memory activation + CBM), N-CBM (neutral memory activation + CBM) and N-INT (no-intervention) groups. A resting-state EEG was obtained before and after each protocol, along with the assessment of the automatic action tendencies. A-CBM group showed a general alpha synchronization increase after the protocol, while the other groups did not show any significant change. Besides, A-CBM group showed significant intra and inter-group differences in the automatic action tendencies after the protocol, reflected in higher avoidance bias toward appetitive, aversive and without context alcohol-related stimuli. The alpha phase synchronization increase could be the neural manifestation of the conditioning produced between the alcohol-related stimuli and the automatic avoidance response. Moreover, the activation of the alcohol-related memories favors this conditioning with those alcohol-related stimuli associated with the activated memories, because it increases their threat level for the abstinence maintenance.

Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography

Magnetoencephalography has gained an increasing importance in systems neuroscience thanks to the possibility it offers of unraveling brain networks at time-scales relevant to behavior, i.e., frequencies in the 1-100 Hz range, with sufficient spatial resolution. In the first part of this review, we describe, in a unified mathematical framework, a large set of metrics used to estimate MEG functional connectivity at the same or at different frequencies. The different metrics are presented according to their characteristics: same-frequency or cross-frequency, univariate or multivariate, directed or undirected. We focus on phase coupling metrics given that phase coupling of neuronal oscillations is a putative mechanism for inter-areal communication, and that MEG is an ideal tool to non-invasively detect such coupling. In the second part of this review, we present examples of the use of specific phase methods on real MEG data in the context of resting state, visuospatial attention and working memory. Overall, the results of the studies provide evidence for frequency specific and/or cross-frequency brain circuits which partially overlap with brain networks as identified by hemodynamic-based imaging techniques, such as functional Magnetic Resonance (fMRI). Additionally, the relation of these functional brain circuits to anatomy and to behavior highlights the usefulness of MEG phase coupling in systems neuroscience studies. In conclusion, we believe that the field of MEG functional connectivity has made substantial steps forward in the recent years and is now ready for bringing the study of brain networks to a more mechanistic understanding.

Cognitive effort decreases beta, alpha, and theta coherence and ends afterdischarges in human brain

OBJECTIVE

Mental activation has been reported to modify the occurrence of epileptiform activity. We studied its effect on afterdischarges.

METHOD

In 15 patients with implanted electrodes we presented cognitive tasks when afterdischarges occurred. We developed a wavelet cross-coherence function to analyze the electrocorticography before and after the tasks and compared findings when cognitive tasks did or did not result in afterdischarge termination. Six patients returned for functional MRI (fMRI) testing, using similar tasks.

RESULTS

Cognitive tasks often could terminate afterdischarges when direct abortive stimulation could not. Wavelet cross-coherence analysis showed that, when afterdischarges stopped, there was decreased coherence throughout the brain in the 7.13-22.53 Hz frequency ranges (p values 0.008-0.034). This occurred a) regardless of whether an area activated on fMRI and b) regardless of whether there were afterdischarges in the area.

CONCLUSIONS

It is known that cognitive tasks can alter localized or network synchronization. Our results show that they can change activity throughout the brain. These changes in turn can terminate localized epileptiform activity.

SIGNIFICANCE

Cognitive tasks result in diffuse brain changes that can modify focal brain activity. Combined with a seizure detection device, cognitive activation might provide a non-invasive method of terminating or modifying seizures.

Altered Static and Temporal Dynamic Amplitude of Low-Frequency Fluctuations in the Background Network During Working Memory States in Mild Cognitive Impairment

Previous studies investigating working memory performance in patients with mild cognitive impairment (MCI) have mainly focused on the neural mechanisms of alterations in activation. To date, very few studies have investigated background network alterations in the working memory state. Therefore, the present study investigated the static and temporal dynamic changes in the background network in MCI patients during a working memory task. A hybrid delayed-match-to-sample task was used to examine working memory performance in MCI patients. Functional magnetic resonance imaging (fMRI) data were collected and the marker of amplitude of low-frequency fluctuations (ALFF) was used to investigate alterations in the background network. The present study demonstrated static and dynamic alterations of ALFF in MCI patients during working memory tasks, relative to the resting state. Traditional static analysis revealed that ALFF decreased in the right ventrolateral prefrontal cortex (VLPFC), right dorsolateral PFC (DLPFC), and left supplementary motor area for normal controls (NCs) in the working memory state. However, the same regions showed increased ALFF in MCI patients. Furthermore, relative to NCs, MCI patients demonstrated altered performance-related functional connectivity (FC) patterns, with the right VLPFC and right DLPFC as ROIs. In terms of temporal dynamic analysis, the present study found that in the working memory state dynamic ALFF of bilateral thalamus regions was increased in NCs but decreased in MCI patients. Additionally, MCI patients demonstrated altered performance-related coefficient of variation patterns; the regions in MCI patients were larger and more widely distributed in the parietal and temporal lobes, relative to NCs. This is the first study to examine static and temporal dynamic alterations of ALFF in the background network of MCI patients in working memory states. The results extend previous studies by providing a new perspective on the neural mechanisms of working memory deficits in MCI patients.

Load effects on spatial working memory performance are linked to distributed alpha and beta oscillations

Increasing spatial working memory (SWM) load is generally associated with declines in behavioral performance, but the neural correlates of load-related behavioral effects remain poorly understood. Herein, we examine the alterations in oscillatory activity that accompany such performance changes in 22 healthy adults who performed a two- and four-load SWM task during magnetoencephalography (MEG). All MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged separately per load using a beamformer. Whole-brain correlation maps were computed using the load-related beamformer difference images and load-related accuracy effects on the SWM task. The results indicated that load-related differences in left inferior frontal alpha activity during encoding and maintenance were negatively correlated with load-related accuracy differences on the SWM task. That is, individuals who had more substantial decreases in prefrontal alpha during high-relative to low-load SWM trials tended to have smaller performance decrements on the high-load condition (i.e., they performed more accurately). The same pattern of neurobehavioral correlations was observed during the maintenance period for right superior temporal alpha activity and right superior parietal beta activity. Importantly, this is the first study to employ a voxel-wise whole-brain approach to significantly link load-related oscillatory differences and load-related SWM performance differences.

Coupling Between Brain Structures During Visual and Auditory Working Memory Tasks

Transmission of EEG activity during a visual and auditory version of the working memory task based on the paradigm of linear syllogism was investigated. Our aim was to find possible similarities and differences in the synchronization patterns between brain structures during the same mental activity performed on different modality stimuli. The EEG activity transmission was evaluated by means of full frequency Directed Transfer Function (ffDTF) and short-time Directed Transfer Function (SDTF). SDTF provided information on dynamical propagation of EEG activity. The assortative mixing approach was applied to quantify coupling between regions of interest encompassing frontal, central and two posterior modules. The results showed similar schemes of coupling for both modalities with stronger coupling within the regions of interests than between them, which is concordant with the theories concerning efficient wiring and metabolic energy saving. The patterns of transmission showed main sources of activity in the anterior and posterior regions communicating intermittently in a broad frequency range. The differences between the patterns of transmission between the visual and auditory versions of working memory tasks were subtle and involved bigger propagation from the posterior electrodes towards the frontal ones during the visual task as well as from the temporal sites to the frontal ones during the auditory task.

Differences in the synchronization of alpha oscillations between anterior and posterior brain regions

Alpha oscillations generated in the human brain have long been investigated in neuroscience. Synchronized oscillatory activities of numerous neural oscillators are thought to underlie alpha oscillations. The amplitude of alpha oscillations reflects the degree of synchronization, which is often modulated through alpha activation and inactivation, for example, in event-related synchronization and desynchronization. The range of synchronization can be estimated using the similarity between neighboring alpha oscillations. Yet, little is known about how the synchronization range of alpha oscillations varies with alpha activation/inactivation over different brain regions. To examine this, we recorded human electroencephalography (EEG) during different tasks used to modulate alpha oscillations. We found that the synchronization range of posterior alpha oscillations was reduced in the activation phase compared to that in the inactivation phase. In contrast, the synchronization range of anterior alpha oscillations was enhanced in the activation phase compared to that in the inactivation phase. The results imply that the mechanisms generating anterior and posterior alpha oscillations may be different.

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

Task modulates functional connectivity networks in free viewing behavior

In free visual exploration, eye-movement is immediately followed by dynamic reconfiguration of brain functional connectivity. We studied the task-dependency of this process in a combined visual search-change detection experiment. Participants viewed two (nearly) same displays in succession. First time they had to find and remember multiple targets among distractors, so the ongoing task involved memory encoding. Second time they had to determine if a target had changed in orientation, so the ongoing task involved memory retrieval. From multichannel EEG recorded during 200 ms intervals time-locked to fixation onsets, we estimated the functional connectivity using a weighted phase lag index at the frequencies of theta, alpha, and beta bands, and derived global and local measures of the functional connectivity graphs. We found differences between both memory task conditions for several network measures, such as mean path length, radius, diameter, closeness and eccentricity, mainly in the alpha band. Both the local and the global measures indicated that encoding involved a more segregated mode of operation than retrieval. These differences arose immediately after fixation onset and persisted for the entire duration of the lambda complex, an evoked potential commonly associated with early visual perception. We concluded that encoding and retrieval differentially shape network configurations involved in early visual perception, affecting the way the visual input is processed at each fixation. These findings demonstrate that task requirements dynamically control the functional connectivity networks involved in early visual perception.

EEG oscillations: how are they modulated during different phases of repetitive movements?

Voluntary movements are planned through the relative timing between submovements of movement sequences as part of the motor program. Different movement phases are characterized by specific amplitude modulation of cortical oscillations. The latter represent neurophysiological correlates of specific synchronization or desynchronization of different neuronal groups. In this Neuro Forum, we review recent evidence regarding the temporal relation between neurophysiological correlates of different phases of a repetitive motor task using electroencephalography and source localization using individualized MRI.

Local and interregional alpha EEG dynamics dissociate between memory for search and memory for recognition

Attention during visual search is thought to be guided by an active visual working memory (VWM) representation of the search target. We tested the hypothesis that a VWM representation used for searching a target among competing information (a "search template") is distinct from VWM representations used for simple recognition tasks, without competition. We analyzed EEG from 20 human participants while they performed three different VWM-based visual detection tasks. All tasks started with identical lateralized VWM cues, but differed with respect to the presence and nature of competing distractors during the target display at test, where participants performed a simple recognition task without distractors, or visual search in pop-out (distinct) and serial (non-distinct) search displays. Performance was worst for non-distinct search, and best for simple recognition. During the one second delay period between cue and test, we observed robust suppression of EEG dynamics in the alpha (8-14Hz) band over parieto-occipital sites contralateral to the relevant VWM item, both in terms of local power as well as interregional phase synchrony within a posterior-parietal network. Importantly, these lateralization dynamics were more strongly expressed prior to search compared to simple recognition. Furthermore, before the VWM cue, alpha phase synchrony between prefrontal and mid-posterior-parietal sites was strongest for non-distinct search, reflecting enhanced anticipatory control prior to VWM encoding. Directional connectivity analyses confirmed this effect to be in an anterior-to-posterior direction. Together, these results provide evidence for frontally mediated top-down control of VWM in preparation of visual search.

Information maintenance in working memory: an integrated presentation of cognitive and neural concepts

Working memory (WM) maintains information in a state that it is available for processing. A host of various concepts exist which define this core function at different levels of abstraction. The present article intended to bring together existing cognitive and neural explanatory approaches about the architecture and neural mechanisms of information maintenance in WM. For this, we highlight how existing WM concepts define information retention and present different methodological approaches which led to the assumption that information can exist in various components and states. This view is broadened by neural concepts focussing on various forms of phase synchronization and molecular biological mechanisms relevant for retaining information in an active state. An integrated presentation of different concepts and methodological approaches can deepen our understanding of this central WM function.

The cognitive neuroscience of working memory

For more than 50 years, psychologists and neuroscientists have recognized the importance of a working memory to coordinate processing when multiple goals are active and to guide behavior with information that is not present in the immediate environment. In recent years, psychological theory and cognitive neuroscience data have converged on the idea that information is encoded into working memory by allocating attention to internal representations, whether semantic long-term memory (e.g., letters, digits, words), sensory, or motoric. Thus, information-based multivariate analyses of human functional MRI data typically find evidence for the temporary representation of stimuli in regions that also process this information in nonworking memory contexts. The prefrontal cortex (PFC), on the other hand, exerts control over behavior by biasing the salience of mnemonic representations and adjudicating among competing, context-dependent rules. The "control of the controller" emerges from a complex interplay between PFC and striatal circuits and ascending dopaminergic neuromodulatory signals.

Brain Activity During Resting State in Relation to Academic Performance

EEG coherence has been widely used to investigate brain activity and learning. However, relatively little is known about the relationship between resting-state EEG coherence and academic performance. The present study investigated this relationship with 140 healthy, normal participants. EEG was recorded during resting periods, with eyes open for 3 min, and the recordings were analyzed for 64 electrode positions in the theta (4–8 Hz), alpha (8–12 Hz), and beta (12–25 Hz) frequency bands. Coherence, defined as the spectral cross-correlation between two signals normalized by their power spectra, was calculated. Short- and long-range intrahemispheric coherence within each hemisphere and interhemispheric coherence across the left and right hemispheres were then computed and compared for each of the theta, alpha, and beta bands. The results showed that academic performance, as measured by grade point average (GPA), was negatively correlated with short-range intrahemispheric alpha and beta coherences in both hemispheres and with interhemispheric alpha and beta coherences in the temporal cortical regions. Therefore, better academic performers demonstrated more decoupling of brain areas when resting with eyes open. This is consistent with a model that relates decreased coherence to neural efficiency.

Working memory and neural oscillations: α-γ versus θ-γ codes for distinct WM information?

Neural oscillations at different frequencies have recently been related to a wide range of basic and higher cognitive processes. One possible role of oscillatory activity is to assure the maintenance of information in working memory (WM). Here we review the possibility that rhythmic activity at theta, alpha, and gamma frequencies serve distinct functional roles during WM maintenance. Specifically, we propose that gamma-band oscillations are generically involved in the maintenance of WM information. By contrast, alpha-band activity reflects the active inhibition of task-irrelevant information, whereas theta-band oscillations underlie the organization of sequentially ordered WM items. Finally, we address the role of cross-frequency coupling (CFC) in enabling alpha-gamma and theta-gamma codes for distinct WM information.