Treatment of 95 post-Covid patients with SSRIs.

After Covid-19 infection, 12.5% develops post-Covid-syndrome (PCS). Symptoms indicate numerous affected organ systems. After a year, chronic fatigue, dysautonomia and neurological and neuropsychiatric complaints predominate. In this study, 95 PCS patients were treated with selective serotonin reuptake inhibitors (SSRIs). This study used an exploratory questionnaire and found that two-thirds of patients had a reasonably good to strong response on SSRIs, over a quarter of patients had moderate response, while 10% reported no response. Overall, patients experienced substantial improved well-being. Brainfog and sensory overload decreased most, followed by chronic fatigue and dysautonomia. Outcomes were measured with three different measures that correlated strongly with each other. The response to SSRIs in PCS conditions was explained by seven possible neurobiological mechanisms based on recent literature on PCS integrated with already existing knowledge. Important for understanding these mechanisms is the underlying biochemical interaction between various neurotransmitter systems and parts of the immune system, and their dysregulation in PCS. The main link appears to be with the metabolic kynurenine pathway (KP) which interacts extensively with the immune system. The KP uses the same precursor as serotonin: tryptophan. The KP is overactive in PCS which maintains inflammation and which causes a lack of tryptophan. Finally, potential avenues for future research to advance this line of clinical research are discussed.

Predictive neural representations of naturalistic dynamic input.

Adaptive behavior such as social interaction requires our brain to predict unfolding external dynamics. While theories assume such dynamic prediction, empirical evidence is limited to static snapshots and indirect consequences of predictions. We present a dynamic extension to representational similarity analysis that uses temporally variable models to capture neural representations of unfolding events. We applied this approach to source-reconstructed magnetoencephalography (MEG) data of healthy human subjects and demonstrate both lagged and predictive neural representations of observed actions. Predictive representations exhibit a hierarchical pattern, such that high-level abstract stimulus features are predicted earlier in time, while low-level visual features are predicted closer in time to the actual sensory input. By quantifying the temporal forecast window of the brain, this approach allows investigating predictive processing of our dynamic world. It can be applied to other naturalistic stimuli (e.g., film, soundscapes, music, motor planning/execution, social interaction) and any biosignal with high temporal resolution.

Decoding Object-Based Auditory Attention from Source-Reconstructed MEG Alpha Oscillations.

How do we attend to relevant auditory information in complex naturalistic scenes? Much research has focused on detecting which information is attended, without regarding underlying top-down control mechanisms. Studies investigating attentional control generally manipulate and cue specific features in simple stimuli. However, in naturalistic scenes it is impossible to dissociate relevant from irrelevant information based on low-level features. Instead, the brain has to parse and select auditory objects of interest. The neural underpinnings of object-based auditory attention remain not well understood. Here we recorded MEG while 15 healthy human subjects (9 female) prepared for the repetition of an auditory object presented in one of two overlapping naturalistic auditory streams. The stream containing the repetition was prospectively cued with 70% validity. Crucially, this task could not be solved by attending low-level features, but only by processing the objects fully. We trained a linear classifier on the cortical distribution of source-reconstructed oscillatory activity to distinguish which auditory stream was attended. We could successfully classify the attended stream from alpha (8-14 Hz) activity in anticipation of repetition onset. Importantly, attention could only be classified from trials in which subjects subsequently detected the repetition, but not from miss trials. Behavioral relevance was further supported by a correlation between classification accuracy and detection performance. Decodability was not sustained throughout stimulus presentation, but peaked shortly before repetition onset, suggesting that attention acted transiently according to temporal expectations. We thus demonstrate anticipatory alpha oscillations to underlie top-down control of object-based auditory attention in complex naturalistic scenes.SIGNIFICANCE STATEMENT In everyday life, we often find ourselves bombarded with auditory information, from which we need to select what is relevant to our current goals. Previous research has highlighted how we attend to specific highly controlled aspects of the auditory input. Although invaluable, it is still unclear how this relates to attentional control in naturalistic auditory scenes. Here we used the high precision of magnetoencephalography in space and time to investigate the brain mechanisms underlying top-down control of object-based attention in ecologically valid sound scenes. We show that rhythmic activity in auditory association cortex at a frequency of ∼10 Hz (alpha waves) controls attention to currently relevant segments within the auditory scene and predicts whether these segments are subsequently detected.

Oscillatory Control over Representational States in Working Memory.

In the visual world, attention is guided by perceptual goals activated in visual working memory (VWM). However, planning multiple-task sequences also requires VWM to store representations for future goals. These future goals need to be prevented from interfering with the current perceptual task. Recent findings have implicated neural oscillations as a control mechanism serving the implementation and switching of different states of prioritization of VWM representations. We review recent evidence that posterior alpha-band oscillations underlie the flexible activation and deactivation of VWM representations and that frontal delta-to-theta-band oscillations play a role in the executive control of this process. That is, frontal delta-to-theta appears to orchestrate posterior alpha through long-range oscillatory networks to flexibly set up and change VWM states during multitask sequences.

Oscillatory Mechanisms of Preparing for Visual Distraction.

Evidence shows that observers preactivate a target representation in preparation of a visual selection task. In this study, we addressed the question if and how preparing to ignore an anticipated distractor differs from preparing for an anticipated target. We measured EEG while participants memorized a laterally presented color, which was cued to be either a target or a distractor in two subsequent visual search tasks. Decoding the location of items in the search display from EOG channels revealed that, initially, the anticipated distractor attracted attention and could only be ignored later during the trial. This suggests that distractors could not be suppressed in advance but were represented in an active, attention-guiding format. Consistent with this, lateralized posterior alpha power did not dissociate between target and distractor templates during the delay periods, suggesting similar encoding and maintenance. However, distractor preparation did lead to relatively enhanced nonlateralized posterior alpha power, which appeared to gate sensory processing at search display onset to prevent attentional capture in general. Finally, anticipating distractors also led to enhanced midfrontal theta power during the delay period, a signal that was predictive of how strongly both target and distractor were represented in the search display. Together, our results speak against a distractor-specific advance inhibitory template, thus contrary to the preactivation of specific target templates. Rather, we demonstrate a general selection suppression mechanism, which serves to prevent initial involuntary capture by anticipated distracting input.

Decoding the status of working memory representations in preparation of visual selection.

Daily life is filled with sequences of multiple tasks, each with their own relevant perceptual input. Working memory needs to dissociate representations that drive attention towards currently relevant information from prospective representations that are needed for future tasks, but that until then should be prevented from guiding attention. Yet, little is known about how the brain initiates and controls such sequential prioritization of selection. In the current study we recorded EEG while subjects remembered a color as the target template for one of two sequential search tasks, thus making it either currently relevant (when it was the target for the first search) or prospectively relevant (when it was the target for the second search) prior to the task sequence. Using time-frequency specific linear classifiers, we were able to predict the priority status (current versus prospective) of the memory representation from multivariate patterns of delta (2-4 Hz) and non-lateralized alpha power (8-14 Hz) during both delay periods. The delta band was only transiently involved when initializing the priority status at the start of the first delay, or when switching priority during the second delay, which we interpret as reflecting the momentary top-down control over prioritization. In contrast, alpha power decoding was based on a more stable pattern of activity that generalized across time both within and between delay periods, which we interpret as reflecting a difference in the prioritized memory representations themselves. Taken together, we reveal the involvement of a complex, distributed and dynamic spatiotemporal landscape of frequency-specific oscillatory activity in controlling prioritization of information within working memory.

Priority Switches in Visual Working Memory are Supported by Frontal Delta and Posterior Alpha Interactions.

Visual working memory (VWM) distinguishes between representations relevant for imminent versus future perceptual goals. We investigated how the brain sequentially prioritizes visual working memory representations that serve consecutive tasks. Observers remembered two targets for a sequence of two visual search tasks, thus making one target currently relevant, and the other prospectively relevant. We show that during the retention interval prior to the first search, lateralized parieto-occipital EEG alpha (8-14 Hz) suppression is stronger for current compared with prospective search targets. Crucially, between the first and second search task, this difference in posterior alpha lateralization reverses, reflecting the change in priority states of the two target representations. Connectivity analyses indicate that this switch in posterior alpha lateralization is driven by frontal delta/low-theta (2-6 Hz) activity. Moreover, this frontal low-frequency signal also predicts task performance after the switch. We thus obtained evidence for large-scale network interactions underlying the flexible shifting between the priority states of multiple memory representations in VWM.

Posterior α EEG Dynamics Dissociate Current from Future Goals in Working Memory-Guided Visual Search.

Current models of visual search assume that search is guided by an active visual working memory representation of what we are currently looking for. This attentional template for currently relevant stimuli can be dissociated from accessory memory representations that are only needed prospectively, for a future task, and that should be prevented from guiding current attention. However, it remains unclear what electrophysiological mechanisms dissociate currently relevant (serving upcoming selection) from prospectively relevant memories (serving future selection). We measured EEG of 20 human subjects while they performed two consecutive visual search tasks. Before the search tasks, a cue instructed observers which item to look for first (current template) and which second (prospective template). During the delay leading up to the first search display, we found clear suppression of α band (8-14 Hz) activity in regions contralateral to remembered items, comprising both local power and interregional phase synchronization within a posterior parietal network. Importantly, these lateralization effects were stronger when the memory item was currently relevant (i.e., for the first search) compared with when it was prospectively relevant (i.e., for the second search), consistent with current templates being prioritized over future templates. In contrast, event-related potential analysis revealed that the contralateral delay activity was similar for all conditions, suggesting no difference in storage. Together, these findings support the idea that posterior α oscillations represent a state of increased processing or excitability in task-relevant cortical regions, and reflect enhanced cortical prioritization of memory representations that serve as a current selection filter.SIGNIFICANCE STATEMENT Our days are filled with looking for relevant objects while ignoring irrelevant visual information. Such visual search activity is thought to be driven by current goals activated in working memory. However, working memory not only serves current goals, but also future goals, with differential impact upon visual selection. Little is known about how the brain differentiates between current and future goals. Here we show, for the first time, that modulations of brain oscillations in the EEG α frequency band in posterior cortex can dissociate current from future search goals in working memory. Moreover, the dynamics of these oscillations uncover how we flexibly switch focus between memory representations. Together, we reveal how the brain assigns priority for selection.

Functional connectivity in the neuromuscular system underlying bimanual coordination.

Neural synchrony has been suggested as a mechanism for integrating distributed sensorimotor systems involved in coordinated movement. To test the role of corticomuscular and intermuscular coherence in bimanual coordination, we experimentally manipulated the degree of coordination between hand muscles by varying the sensitivity of the visual feedback to differences in bilateral force. In 16 healthy participants, cortical activity was measured using EEG and muscle activity of the flexor pollicis brevis of both hands using high-density electromyography (HDsEMG). Using the uncontrolled manifold framework, coordination between bilateral forces was quantified by the synergy index RV in the time and frequency domain. Functional connectivity was assessed using corticomuscular coherence between muscle activity and cortical source activity and intermuscular coherence between bilateral EMG activity. The synergy index increased in the high coordination condition. RV was higher in the high coordination condition in frequencies between 0 and 0.5 Hz; for the 0.5- to 2-Hz frequency band, this pattern was inverted. Corticomuscular coherence in the beta band (16-30 Hz) was maximal in the contralateral motor cortex and was reduced in the high coordination condition. In contrast, intermuscular coherence was observed at 5-12 Hz and increased with bimanual coordination. Within-subject comparisons revealed a negative correlation between RV and corticomuscular coherence and a positive correlation between RV and intermuscular coherence. Our findings suggest two distinct neural pathways: 1) corticomuscular coherence reflects direct corticospinal projections involved in controlling individual muscles; and 2) intermuscular coherence reflects diverging pathways involved in the coordination of multiple muscles.