Prospective memory (PM), enabling execution of future intentions, underpins goal-directed behavior, such as medication compliance and remembering appointments, making it crucial to independent living. Its deterioration in neurocognitive disorders, including dementia and traumatic brain injury, renders it among the most common memory failure complaints. We investigated the impact of oscillatory power modulation during strategic monitoring on performance in an ongoing task to shed light on the neurocognitive mechanisms that underpin PM. Forty-four healthy adults performed a 2-back working memory (WM) task using colored letters, either with (with-PM) or without a PM component (no-PM), during EEG recording. The with-PM group responded to a particular color, assigned as the PM cue. Oscillatory spectral power in WM trials was contrasted between groups using cluster-based permutation testing, and partial least squares were calculated between power and WM performance measures. The with-PM group had lower accuracy and slower reaction times in the WM task. The performance costs align with strategic monitoring effects. Central-parietal alpha/beta oscillatory power was greater in the with-PM group. Early alpha/beta-band power was associated with slower responses in the no-PM condition, whereas oscillatory power was linked to improved accuracy/reaction times in the with-PM condition. Early alpha/beta power in the with-PM task fits with active PM maintenance during strategic monitoring. Alpha-/beta-band activity showed a context-dependent role, relating to reduced cognitive flexibility during WM alone but supporting goal maintenance under prospective monitoring. The findings shed new light on the neural mechanisms underpinning memory and attentional control.NEW & NOTEWORTHY Strategic monitoring impaired ongoing task performance and increased central-parietal alpha/beta power. Alpha- and beta-band activity showed a context-dependent role. In the no-PM condition, greater oscillatory power-particularly late alpha-was associated with slower responses, indicating reduced cognitive flexibility, whereas in the with-PM condition, increased alpha/beta power was linked to higher accuracy and faster responses, supporting goal maintenance during prospective monitoring.

Visual threshold estimation typically requires data from thousands of trials presented across extended periods of time. However, human attention fluctuates over time between focused and inattentive states, such as mind-wandering (MW). Failing to account for MW in perceptual research may produce systematically lower estimates of perceptual performance. We assessed how brief changes in brain state affect visual performance by investigating the impact of MW on visual target detection and discrimination in twelve behavioral tasks involving 239 subjects (156 female). In all tasks, subjects reported their task engagement (ON vs. OFF) in 20% of trials. We explored whether in the remaining 80% of unlabeled trials performance aligns with ON or OFF trials. MW led to threshold detection shifts and reduced perception in OFF compared to ON trials. MW primarily affected the perception of simple stimuli like gratings and curvature stimuli, with its influence diminishing as stimulus complexity increased. Importantly, visual performance in unlabeled trials aligned with the OFF-state. Our results show that mind wandering induces fluctuations in attentional capacity that render threshold measurements substantially less reliable without correction, underscoring the need to account for attentional state to obtain valid estimates of perceptual capacity.

The traditional notion of a sustained visual spotlight of attention has been challenged by behavioral and neural evidence showing that attention fluctuates rhythmically in the theta band (3-8 Hz). In rodents, locomotion drives hippocampal theta oscillations that support cue sampling during navigation, enhancing sensory encoding and decision-making. This raises the question of whether physical activity (PA) similarly modulates theta-based attentional sampling in humans. Using magnetoencephalography (MEG), we found that discrimination accuracy (DA) increased following PA, accompanied by stronger theta-band modulation of both DA and reaction times (RTs) in trial-by-trial spectral analyses. Critically, PA elevated frontal theta power after cue presentation and shifted the coupling of visual high-frequency activity (HFA; 80-150 Hz) toward an encoding-sensitive theta phase. Moreover, target-evoked HFA exhibited stronger theta-range fluctuations after PA. Together, these findings demonstrate that short bouts of movement can tune the brain's intrinsic theta-band sampling mechanism, thereby linking PA to enhanced visual attention.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by the loss of motor neurons in primary motor cortex, leading to muscle weakness, atrophy and death within a median of 3 years. Even though ALS is characterized by different disease subtypes affecting different body parts, individualized phenotyping of functional ALS pathology has so far not been achieved. We recorded 7 Tesla functional MRI data while ALS patients and matched controls moved affected and non-affected body parts in the MR scanner. We applied robust Shared Response Modelling for capturing ALS-specific shared responses for group classification, and Partial Least Squares regression for relating the latent variables to clinical subtypes and the degree of disease progression. We show that disease onset and severity can be best modelled by functional connectivity rather than local activation changes. We also show that functional disease-defining information in primary motor cortex is not the strongest in the area that is behaviourally first-affected, deviating from the behavioural phenotype of the patients. When computing the model's weight distribution of the King stage classification and projecting them back into voxel space, the highest mean weights are present in the foot and tongue/face regions. Our data highlight the importance of 7 Tesla functional MRI task-based functional connectivity measures for classifying ALS patients in addition to structural readouts and provides evidence that a 7 Tesla functional MRI can be used for identifying a disease signature of each individual ALS patient.

Fluctuations between attention and inattention shape sensory representation, yet the dynamics of these brain state transitions and whether inattention leads to a loss of sensory information remain unclear. We examined how focused wakefulness (ON state) and external inattention (OFF state) affect human perception and early visual responses. In two experiments, we investigated the temporal kinetics of brain state changes during stimulus processing and assessed fluctuations across extended periods of time. Using theta activity in MEG sensors, a classifier distinguished ON and OFF states on a single-trial level. Participants shifted from an ON to an OFF state as rapidly as two seconds. Visual target discrimination was comparable in both states, but reaction times were slower and more variable during the OFF state. Broad band high-frequency activity (BHA) recorded in MEG sensors covering the occipital cortex tracked target grating orientation. BHA was reduced during the OFF state but still tracked target grating orientation. Hence, participants were still able to distinguish sensory information highlighting the role of BHA in visual perception across cognitive brain states. Furthermore, BHA peak latency was longer than EEG-C1 latency, with the EEG-C1 component representing the initial visual feedforward sweep to V1. Taken together, these results suggest that BHA is involved in feedforward and feedback processing in the visual system.

Abstract The primary goal of a brain-computer interface (BCI) is to enable interactions with the environment by generating control signals directly from brain activity, independent of physical movement including gaze shifts. Attentional selection of peripheral objects has been used to control a BCI but requires sufficient visual acuity to reliably recognize the target stimulus. Here, we systematically investigated the effect of different stages of visual impairment on event-related potentials (ERPs) and BCI performance while healthy participants directed covert attention to peripheral visual stimuli. We hypothesized that the effect of visual impairments such as blurred or monocular vision might alter attention-related visual ERPs, but has only minor or no impact at all on BCI performance when color is the target feature. Early attention-sensitive visual components were altered in monocular vision compared to binocular vision. Simulated vision degradation resulted in reduction of ERPs in the P300 range. The differences in ERPs across vision conditions did not affect the decoding accuracy of the BCI. The study not only revealed differences of visual ERPs in different viewing conditions but primarily demonstrated that a BCI can be reliably controlled by focusing attention on a visual stimulus whose distinguishing features such as color, can be recognized even with visual impairments. This provides a promising approach to enable paralyzed persons to communicate using a non-invasive, gaze-independent BCI.

Ripples, representing the compressed reactivation of environmental information, provide a mechanism for retaining memory information in chronological order and are also crucial for working memory (WM) during wakefulness. Brief sessions of physical activity (PA) are proposed to boost WM. In concurrent EEG/MEG sessions, we investigated the role of PA in WM performance and high-frequency-ripple to wake spindle coupling. Ripples, identified in MEG sensors covering the medial temporal lobe (MTL) region, predicted individual WM performance. Ripples were locked to robust oscillatory patterns in the EEG defined spindle band. Wake spindle activity and ripples decrease during initial stimulus presentation and rebound after 1 sec. Behaviorally, PA enhanced WM performance. Neurophysiologically, PA scaled the ripple rate with the number of items to be kept in WM and strengthened the coupling between ripple events and wake spindle events. These findings reveal that PA modulates WM by coordinating ripple-spindle interaction.

The high-frequency activity (HFA; 80-150 Hz) in human intracranial recordings shows a differential modulation to different degrees in contrast when stimuli are behaviorally relevant, indicating a feedforward process. However, the HFA is also significantly dominated by superficial layers and exhibits a peak before 200 ms, suggesting that it is more likely a feedback signal. Magnetoencephalographic (MEG) recordings are suited to reveal an HFA modulation similar to its modulation in intracranial recordings. This allows for noninvasive, direct comparison of HFA with the C1, an established measure for feedforward input to V1, to test whether HFA represents feedforward or rather feedback. In simultaneous recordings, we used the EEG-C1 event-related potential (ERP) component and MEG-HFA to define feedforward processing in visual cortices. C1 latency preceded the HFA peak modulation, which had a more sustained response. Furthermore, modulation parameters like onset, peak time, and peak amplitude were uncorrelated. Most importantly, the C1 but not HFA distinguished small task-irrelevant contrast differences in visual stimulation. These results highlight the differential roles for the C1 and HFA in visual processing with the C1 measuring feedforward discrimination ability and HFA indexing feedforward and feedback processing.NEW & NOTEWORTHY Whether the broadband high-frequency activity (HFA) represents exclusively feedforward or feedback processing remains unclear. In this study, we compared the response characteristics of the HFA-magnetoencephalographic (MEG) and the C1-EEG component to systematic contrast modulations of task-irrelevant visual stimulation. Our findings reveal that the more sustained HFA follows the C1 component and, unlike the C1, is not modulated by task-irrelevant contrast differences. This timing of the HFA modulation suggests that HFA encompasses both feedforward and feedback processing.

Covert attention to peripherally presented visual stimuli is an effective cognitive task that can be used to operate a brain-computer interface (BCI) even if the user is completely paralyzed. Brain responses to single visual search display onsets show attention-related components emerging between 180ms and 500ms. This poses a challenge when using fast visual stimuli that induce steady-state visual evoked potentials (SSVEP) for covert attention BCIs since a new stimulus is presented before the current stimulus is processed. Here we investigated brain activity during covert attention by presenting visual stimuli inducing SSVEPs in the left and right visual field. We decoded the attention shift to in-phase stimuli in the left and right visual field with an average accuracy of 72.5% across all channels. When left and right stimuli were presented with a phase shift but constant frequency, the average decoding accuracy increased to 84.6%. While with in-phase stimuli, top-down attention is decoded, decoding of attention to antiphase stimuli additionally takes advantage of stimulus-related processing.

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease characterized by the loss of motor neurons in primary motor cortex (MI), leading to muscle weakness, atrophy, and death within a median of three years. Even though ALS is characterized by different disease subtypes affecting different body parts, individiualized phenotyping of functional ALS pathology has so far not been achieved. We recorded 7 Tesla functional MRI (7T-fMRI) data while ALS patients and matched controls moved affected and non-affected body parts in the MR scanner. We applied robust Shared Response Modeling (rSRM) for capturing ALS-specific shared responses for group classification , and Partial Least Squares (PLS) regression for relating the latent variables to clinical subtypes and the degree of disease progression. We show that both functional connectivity and functional activation in MI are a predictor for disease onset site. However, disease severity could best be predicted by functional connectivity rather than pure activation changes. Critically, we show that functionally disease-defining information in MI is not strongest in the area that is behaviorally first-affected, deviating from the behavioral phenotype of the patients. When computing the model weight distribution of the King stage classification and projecting them back into voxel space, the highest mean weights are present in the foot and tongue/face regions that seem to drive disease progress. Our data highlight the importance of 7T-fMRI task-based functional connectivity measures for classifying ALS-patients, and provide evidence that a single 7T-MRI scan can be used for identifying a disease signature of each individual ALS patient. ### Competing Interest Statement The authors have declared no competing interest.

Objective. Brain-computer interfaces (BCI) that are aimed at supporting completely locked-in patients require independence from eye movements. Since visual spatial attention (VSA) shifts precede eye movements, they can be used for non-invasive, gaze-independent BCI control. In VSA tasks, stimuli locations and presentation onsets are commonly unpredictable. In this study we investigated the impact of predictability of potential target stimuli on the decoding accuracy of a BCI.Approach. We presented visual stimuli simultaneously to the left and right visual fields while participants shifted attention to a target stimulus. Using canonical correlation analysis, we decoded the direction of attention under different combinations of temporal and spatial predictability and compared the performance.Main results. We found no variation in decoding accuracies with spatial predictability. In addition, jittered timing did not alter the decoding accuracy compared to a constant stimulus onset asynchrony (SOA). Finally, reducing the SOA enabled faster BCI communication without accuracy loss. Using time-resolved decoding and interpretable models, we show that a later positive difference wave (between 300 ms and 350 ms post-stimulus onset) at occipital sites, rather than the N2pc, primarily contributes to decoding the target receiving attention.Significance. Our results demonstrate that stimulus predictability has no beneficial impact on decoding accuracy, but the paradigm proved robust to alterations in various stimulus parameters, making VSA a promising cognitive process for use in non-invasive, gaze-independent BCI-based communication.

Prospective memory (PM) is the ability to remember to execute future intentions. PM requires engagement of attentional networks, in which oscillatory activity in the alpha frequency range has been implicated. The left dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex are assumed to be engaged during PM tasks. We hypothesized that the selective application of transcranial alternating current stimulation (tACS) at alpha frequency to these areas can modulate PM-associated event-related potentials. Participants were assigned to alpha-tACS, theta-tACS, or Sham stimulation. They performed a working memory task (OGT), with a PM component, pre-, during, and post-stimulation. EEG was recorded post-stimulation. Accuracy and reaction times (RTs) were computed. Following EEG source reconstruction of mean amplitude, source activity was contrasted between conditions in which performance was modulated by tACS using cluster-based permutation tests. RTs were slower on introducing the PM task, consistent with strategic monitoring. PM accuracy improved in the alpha-tACS group only. During PM trials, source activity in the posterior cingulate cortex (PCC) was lower following alpha-tACS than after Sham stimulation. Source activity in the DLPFC following alpha-tACS was lower during PM than in OGT trials following alpha-tACS. Performance modulation through alpha-tACS, and the lower DLPFC activity in PM than in OGT trials provide evidence of a role for alpha oscillations during strategic monitoring for a PM cue. Lower PCC activity in the alpha-tACS than Sham group is consistent with facilitation of disengagement of the default mode network, supporting re-direction of attention from the OGT to the PM task and task-switching.

Prospective memory, or memory for future intentions, engages particular cortical regions. Lesion studies also implicate the thalamus, with prospective memory deterioration following thalamic stroke. Neuroimaging, anatomical and lesion studies suggest the anterior nuclei of the thalamus (ANT), in particular, are involved in episodic memory, with electrophysiological studies suggesting an active role in selecting neural assemblies underlying particular memory traces. Here, we hypothesized that the ANT are engaged in realizing prospectively-encoded intentions, detectable using ultra-high-field strength functional MRI. Using a within-subject design, participants (N = 14; age 20-35 years) performed an ongoing n-back working memory task with two cognitive loads, each with and without a prospective memory component, during 7-Tesla functional MRI. Seed-to-voxel whole brain functional connectivity analyses were performed to establish whether including a prospective memory component in an ongoing task results in greater connectivity between ANT and cortical regions engaged in prospective memory. Repeated measures ANOVAs were applied to behavioral and connectivity measures, with the factors Task Type (with prospective memory or not) and N-Back (2-back or 3-back). Response accuracy was greater and reaction times faster without the prospective memory component, and accuracy was higher in the 2- than 3-back condition. Task Type had a main effect on connectivity with an ANT seed, with greater ANT-DLPFC and ANT-STG connectivity when including a prospective memory component. Post hoc testing based on a significant interaction showed greater ANT-DLPFC connectivity (p-FWE = 0.007) when prospective memory was included with the low cognitive load and ANT-STG connectivity (p-FWE = 0.019) with the high cognitive load ongoing task. Direct comparison showed greater functional connectivity between these areas and the ANT than dorsomedial nucleus of the thalamus (DMNT) during prospective remembering. Enhanced ANT-DLPFC connectivity, a brain region with an established role in strategic monitoring for prospective memory cues, arose with a low cognitive load ongoing task that enabled monitoring. This connectivity was significantly less on direct comparison with increasing the cognitive load of the ongoing task without prospective memory, suggesting specificity for prospective memory. Greater ANT-STG connectivity on prospective memory inclusion in the higher cognitive load ongoing task fits with reported STG activation on prospective memory through spontaneous retrieval. Lower connectivity on direct comparison with a DMNT seed suggests ANT specificity. The findings fit with a coordinating role for the ANT in prospective remembering. Given the small sample, these findings should be considered preliminary, with replication required.

Selective attention requires fast and accurate distractor suppression. We investigated if broadband high-frequency activity (BHA; 80-150 Hz), indicative of local neuronal population dynamics in early sensory cortices, indexes rapid processing of distracting information. In a first experiment we tested whether BHA distinguishes targets from distracting information in a visual search paradigm using tilted gratings as targets and distractors. In a second experiment, we examined whether BHA distractor processing can be trained by statistical regularities. In both experiments, BHA preceded the target enhancement (NT) and distractor suppression (PD; 1-40 Hz) event-related field (ERF) components and distinguished between targets and distractors. Only the BHA but not ERF component amplitude correlated with participants' performance and was higher for lateral distractors versus lateral targets. Furthermore, BHA predicted the strength of the PD. These results indicate that BHA initiates stimulus discrimination via distractor suppression.

We investigated the effects of brain states on human perception and early visual response comparing focused wakefulness (ON state) to external inattention (OFF state). In two experiments, we investigated the temporal kinetics of brain states changes during stimulus processing and assessed fluctuations across extended periods of time. We used a classifier to distinguish between these states on a single trial level using theta activity in MEG sensors. We found that participants shifted from an ON to an OFF state as rapidly as two seconds. Visual target discrimination was comparable in both states, but reaction times were slower and more variable during the OFF state. Broad band high-frequency activity (BHA) recorded in MEG sensors covering the occipital cortex tracked target grating orientation. BHA was reduced during the OFF state but participants were still able to distinguish sensory information highlighting the role of BHA in visual perception across cognitive brain states. ### Competing Interest Statement The authors have declared no competing interest.

The well-known decrease in finger dexterity during healthy aging leads to a significant reduction in quality of life. Still, the exact patterns of altered finger kinematics of older adults in daily life are fairly unexplored. Finger interdependence is the unintentional comovement of fingers that are not intended to move, and it is known to vary across the lifespan. Nevertheless, the magnitude and direction of age-related differences in finger interdependence are ambiguous across studies and tasks and have not been explored in the context of daily life finger movements. We investigated five different free and daily-life-inspired finger movements of the right, dominant hand as well as a sequential finger tapping task of the thumb against the other fingers, in 17 younger (22-37 yr) and 17 older (62-80 yr) adults using an exoskeleton data glove for data recording. Using inferential statistics, we found that the unintentional comovement of fingers generally decreases with age in all performed daily-life-inspired movements. Finger tapping, however, showed a trend towards higher finger interdependence for older compared with younger adults. Using machine learning, we predicted the age group of a person from finger interdependence features of single movement trials significantly better than chance level for the daily-life-inspired movements, but not for finger tapping. Taken together, we show that for specific tasks, decreased finger interdependence (i.e., less comovement) could potentially act as a marker of human aging that specifically characterizes older adults' complex finger movements in daily life. NEW & NOTEWORTHY Kinematic finger movement data were analyzed with regard to age-related differences. Extensive analyses of complex and daily-life-inspired movements reveal that the direction of age effects is not uniform but task-dependent: Although older adults generally show more finger interdependence than younger adults in a simple finger tapping task, this effect is reversed for daily-life-inspired movement tasks. For these tasks, finger interdependence indices offer potential new markers to predict the age group of an individual using machine learning approaches.

Brain state changes affect visual perception by altering spatial resolution. Attention enhances the spatial resolution decorrelating neuronal activity in early nonhuman primate (NHP) visual cortex. Physical activity (PA) amplifies these attentional effects in rodents but impact of PA on visual perception in humans remains uncertain. We investigated the relationship between broadband high-frequency activity (BHA: 80-150 Hz) recorded with magnetoencephalography (MEG) and visual detection performance. We found that PA enhanced visual target detection predicted by a reduction of early BHA responses (<90 msec). This effect may be due to reduced interneuronal correlation to improve spatial resolution. Moreover, PA improved spatial integration time, as indicated by a linear relationship between reaction times and BHA variation with target eccentricity. These findings provide evidence that PA influences neuronal activity critical for early visual perception, optimizing visual processing at the initial stages of the visual hierarchy. ### Competing Interest Statement The authors have declared no competing interest.

Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain-computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.

Spindle-ripple coupling enhances memory consolidation during sleep. Ripples, representing the compressed reactivation of environmental information, provide a mechanism for retaining memory information in chronological order and are also crucial for working memory (WM) during wakefulness. Brief sessions of physical exercise (PE) are proposed to boost WM. In concurrent EEG/MEG sessions, we investigated the role of PE in WM performance and high-frequency-ripple to spindle coupling. Ripples, identified in MEG sensors covering the medial temporal lobe (MTL) region, predicted individual WM performance. Ripples were locked to robust oscillatory patterns in the EEG defined spindle band. Spindle activity and ripples decrease during initial stimulus presentation and rebound after 1 sec. Behaviorally, PE enhanced WM performance. Neurophysiologically, PE scaled the ripple rate with the number of items to be kept in WM and strengthened the coupling between ripple events and spindle oscillations. These findings reveal that PE enhances WM by coordinating ripple-spindle interaction. ### Competing Interest Statement The authors have declared no competing interest.

Commands in brain-computer interface (BCI) applications often rely on the decoding of event-related potentials (ERP). For instance, the P300 potential is frequently used as a marker of attention to an oddball event. Error-related potentials and the N2pc signal are further examples of ERPs used for BCI control. One challenge in decoding brain activity from the electroencephalogram (EEG) is the selection of the most suitable channels and appropriate features for a particular classification approach. Here we introduce a toolbox that enables ERP-based decoding using the full set of channels, while automatically extracting informative components from relevant channels. The strength of our approach is that it handles sequences of stimuli that encode multiple items using binary classification, such as target vs. nontarget events typically used in ERP-based spellers. We demonstrate examples of application scenarios and evaluate the performance of four openly available datasets: a P300-based matrix speller, a P300-based rapid serial visual presentation (RSVP) speller, a binary BCI based on the N2pc, and a dataset capturing error potentials. We show that our approach achieves performances comparable to those in the original papers, with the advantage that only conventional preprocessing is required by the user, while channel weighting and decoding algorithms are internally performed. Thus, we provide a tool to reliably decode ERPs for BCI use with minimal programming requirements.