A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention

Working memory readout varies with frontal theta rhythms

Increasing evidence suggests that attention varies rhythmically, phase-locked to ongoing cortical oscillations. Here, we report that the phase of theta oscillations (3-6 Hz) in the frontal eye field (FEF) is associated with temporal and spatial variation of the read-out of information from working memory (WM). Non-human primates were briefly shown a sample array of colored squares. A short time later, they viewed a test array and were rewarded for identifying which square changed color (the target). Better performance (accuracy and reaction time) varied systematically with the phase of local field potential (LFP) theta at the time of test array onset as well as the target's location. This is consistent with theta "scanning" across the FEF and thus visual space from top to bottom. Theta was coupled, on opposing phases, to both spiking and beta (12-20 Hz). These results could be explained by a wave of activity that moves across the FEF, modulating the readout of information from WM.

Neural dynamics underlying the cue validity effect in target conflict resolution

Cue validity significantly influences attention guidance, either facilitating or hindering the ability for conflict resolution. Previous studies have demonstrated that the validity effect and conflict resolution are associated with better/worse behavioral performance and specific neural activations; however, the underlying neural mechanism of their interaction remains unclear. We hypothesized that the effect of cue validity might sustain specific sequences of neural activities until target occurrence and throughout the subsequent conflict resolution. In this study, we recorded the scalp electroencephalography during the Attention Network Test paradigm to investigate their interactions in neural dynamics. Specifically, we performed a cluster-level channel-time-frequency analysis to explore significant time-frequency neural activity patterns associated with these interactions, in scalp regions of interest determined by a data-driven strategy. Our results revealed a string of significant neural dynamics in the frontal and parietal regions, including initial broad-band (especially the gamma-band) activations and subsequent complex cognitive processes evoked/effected by the invalid cue, that were firstly elicited. Finally, the resolution of conflict was completed by the frontal behavior-related theta-band power reduction. In summary, our findings advanced the understanding of the temporal and spectral sequences of neural dynamics, with the key regions involved in the resolution of conflict after invalid cueing.

Top-down and bottom-up interactions rely on nested brain oscillations to shape rhythmic visual attention sampling

Adaptive visual processing is enabled through the dynamic interplay between top-down and bottom-up (feedback/feedforward) information exchange, presumably propagated through brain oscillations. Here, we causally tested for the oscillatory mechanisms governing this interaction in the human visual system. Using concurrent transcranial magnetic stimulation-electroencephalography (TMS-EEG), we emulated top-down signals by a single TMS pulse over the frontal eye field (right FEF), while manipulating the strength of sensory input through the presentation of moving concentric gratings (compared to a control-TMS site). FEF-TMS without sensory input led to a top-down modulated occipital phase realignment, alongside higher fronto-occipital phase connectivity, in the alpha/beta band. Sensory input in the absence of FEF-TMS increased occipital gamma activity. Crucially, testing the interaction between top-down and bottom-up processes (FEF-TMS during sensory input) revealed an increased nesting of the bottom-up gamma activity in the alpha/beta-band cycles. This establishes a causal link between phase-to-power coupling and top-down modulation of feedforward signals, providing novel mechanistic insights into how attention interacts with sensory input at the neural level, shaping rhythmic sampling.

Evidence for a constant occipital spotlight of attention using MVPA on EEG data

While traditional behavioural and electroencephalographic studies claim that visuospatial attention stays fixed at one location at a time, recent research has rather shown that attention rhythmically fluctuates between locations at different rates. However, little is known about the temporal dynamics of this fluctuation and whether it changes over time. We addressed this question by investigating how the neural pattern of visuospatial attention behaves over space and time by employing classification and conventional analysis of occipito-parietal EEG activity. Furthermore, we simulated data with the attentional electrophysiological correlates to control for the ground truth that would give rise to certain classification patterns. We analysed two visuospatial cueing tasks, with a peripheral and a central cue to control for sensory-driven processes, where attention was covertly oriented to the left or right hemifield. First, to decode the spatial locus of attention from neural activity, we trained and tested a classifier on every timepoint from the attentional cue to the stimulus onset. This resulted in one temporal generalization matrix per participant, which was time-frequency decomposed to identify the sampling rhythm. Independently, we calculated a lateralization index based on ERPs and alpha-band power and correlated these indices with classifier performance. Eventually, we simulated two dataset, with ERPs and alpha-band attentional modulations, and employed the same decoding approach. Our results show that attention settled on the cued hemifield in a late time window, but an early and rhythmic sampling of both hemifields exclusively after the peripheral cue. Only the ERP lateralization index correlated with classifier performance in the periperhal cue dataset, suggesting that the early rhythmic state did not reflect attentional sampling but instead was driven by the cue location, idea also supported by our simulations. Together, our results characterise the occipital attentional sampling as a constant process slightly delayed after the cue.

Distractor anticipation during working memory is associated with theta and beta oscillations across spatial scales

Introduction

Anticipating distractors during working memory maintenance is critical to reduce their disruptive effects. In this study, we aimed to identify the oscillatory correlates of this process across different spatial scales of neural activity.

Methods

We simultaneously recorded local field potentials (LFP) from the lateral prefrontal cortex (LPFC) and electroencephalograms (EEG) from the scalp of monkeys performing a modified memory-guided saccade (MGS) task. The monkeys were required to remember the location of a target visual stimulus while anticipating distracting visual stimulus, flashed at 50% probability during the delay period.

Results

We found significant theta-band activity across spatial scales during anticipation of a distractor, closely linked with underlying working memory dynamics, through decoding and cross-temporal generalization analyses. EEG particularly reflected reactivation of memory around the anticipated time of a distractor, even in the absence of stimuli. During this anticipated time, beta-band activity exhibited transiently enhanced intrahemispheric communication between the LPFC and occipitoparietal brain areas. These oscillatory phenomena were observed only when the monkeys successfully performed the task, implicating their possible functional role in mitigating anticipated distractors.

Discussion

Our results demonstrate that distractor anticipation recruits multiple oscillatory processes across the brain during working memory maintenance, with a key activity observed predominantly in the theta and beta bands.

Characterizing brain network alterations in cervical spondylotic myelopathy using static and dynamic functional network connectivity and machine learning

BACKGROUND

Cervical spondylotic myelopathy (CSM) is a debilitating condition that affects the cervical spine, leading to neurological impairments. While the neural mechanisms underlying CSM remain poorly understood, changes in brain network connectivity, particularly within the context of static and dynamic functional network connectivity (sFNC and dFNC), may provide valuable insights into disease pathophysiology. This study investigates brain-wide connectivity alterations in CSM patients using both sFNC and dFNC, combined with machine learning approaches, to explore their potential as biomarkers for disease classification and progression.

METHODS

A total of 191 participants were included in this study, comprising 108 CSM patients and 83 healthy controls (HCs). Resting-state fMRI data were used to derive functional connectivity networks (FCNs), which were further analyzed to obtain sFNC and dFNC features. K-means clustering was applied to identify distinct dFNC states, and machine learning models, including support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), logistic regression (LR), and random forests (RF), were constructed to classify CSM patients and HCs based on FNC features.

RESULTS

The sFNC analysis revealed significant alterations in brain network connectivity in CSM patients, including enhanced connectivity between the posterior default mode network (pDMN) and ventral attention network (vAN), and between the right and left frontoparietal networks (rFPN and lFPN), alongside weakened connectivity in multiple other network pairs. K-means clustering of dFNC identified four distinct functional states, with CSM patients exhibiting altered connectivity in State 1 and State 3. Machine learning models based on sFNC demonstrated excellent classification performance, with the SVM model achieving an AUC of 0.92, accuracy of 85.86%, and sensitivity and specificity both exceeding 0.80. Models based on dFNC also performed well, with the State 3-based model yielding an AUC of 0.91 and accuracy of 84.97%.

CONCLUSIONS

Our findings highlight significant alterations in both sFNC and dFNC in CSM patients, suggesting that these connectivity changes may reflect underlying neural mechanisms of the disease. Machine learning models based on FNC features, particularly SVM, exhibit strong potential for classifying CSM patients and may serve as valuable neuroimaging biomarkers for diagnosis and monitoring disease progression. Future research should explore longitudinal studies and multimodal neuroimaging approaches to further validate these findings.

Attention Rhythmically Shapes Sensory Tuning

Attention is key to perception and human behavior, and evidence shows that it periodically samples sensory information (<20 Hz). However, this view has been recently challenged due to methodological concerns and gaps in our understanding of the function and mechanism of rhythmic attention. Here we used an intensive ∼22 h psychophysical protocol combined with reverse correlation analyses to infer the neural representation underlying these rhythms. Participants (male/female) performed a task in which covert spatial (sustained and exploratory) attention was manipulated and then probed at various delays. Our results show that sustained and exploratory attention periodically modulate perception via different neural computations. While sustained attention suppresses distracting stimulus features at the alpha (∼12 Hz) frequency, exploratory attention increases the gain around task-relevant stimulus feature at the theta (∼6 Hz) frequency. These findings reveal that both modes of rhythmic attention differentially shape sensory tuning, expanding the current understanding of the rhythmic sampling theory of attention.

Performance modulations phase-locked to action depend on internal state

Previous studies have shown that perceptual performance can be modulated at specific frequencies phase-locked to self-paced motor actions, but findings have been inconsistent. To investigate this effect at the population level, we tested 50 participants who performed a self-paced button press followed by a threshold-level detection task, using both fixed- and random-effects analyses. Contrary to expectations, the aggregated data showed no significant action-related modulation. However, when accounting for internal states, we found that trials during periods of low performance or following a missed detection exhibited significant modulation at approximately 17 Hz. Additionally, participants with no false alarms showed similar modulation. These effects were significant in random effects tests, suggesting that they generalize to the population. Our findings indicate that action-related perceptual modulations are not always detectable but may emerge under specific internal conditions, such as lower attentional engagement or higher decision criteria, particularly in the beta-frequency range.

Intermittent rate coding and cue-specific ensembles support working memory

Persistent, memorandum-specific neuronal spiking activity has long been hypothesized to underlie working memory1,2. However, emerging evidence suggests a potential role for 'activity-silent' synaptic mechanisms3-5. This issue remains controversial because evidence for either view has largely relied either on datasets that fail to capture single-trial population dynamics or on indirect measures of neuronal spiking. We addressed this controversy by examining the dynamics of mnemonic information on single trials obtained from large, local populations of lateral prefrontal neurons recorded simultaneously in monkeys performing a working memory task. Here we show that mnemonic information does not persist in the spiking activity of neuronal populations during memory delays, but instead alternates between coordinated 'On' and 'Off' states. At the level of single neurons, Off states are driven by both a loss of selectivity for memoranda and a return of firing rates to spontaneous levels. Further exploiting the large-scale recordings used here, we show that mnemonic information is available in the patterns of functional connections among neuronal ensembles during Off states. Our results suggest that intermittent periods of memorandum-specific spiking coexist with synaptic mechanisms to support working memory.

A domain-general process for theta-rhythmic sampling of either environmental information or internally stored information

Many everyday tasks, such as shopping for groceries, require the sampling of both environmental information and internally stored information. Selective attention involves the preferential processing and sampling of behaviorally important information from the external environment, while working memory involves the preferential processing and sampling of behaviorally important, internally stored information. These essential cognitive processes share neural resources within a large-scale network that includes frontal, parietal, and sensory cortices, and these shared neural resources can lead to between-domain interactions. Previous research has linked external sampling during selective attention and internal sampling during working memory to theta-rhythmic (3-8 Hz) neural activity in higher-order (e.g., frontal cortices) and sensory regions (e.g., visual cortices). Such theta-rhythmic neural activity might help to resolve the competition for shared neural resources by isolating neural activity associated with different functions over time. Here, we used EEG and a dual-task design (i.e., a task that required both external and internal sampling) to directly compare (i) theta-dependent fluctuations in behavioral performance during external sampling with (ii) theta-dependent fluctuations in behavioral performance during internal sampling. Our findings are consistent with a domain-general, theta-rhythmic process for sampling either external information or internal information. We further demonstrate that interactions between external and internal information-specifically, when to-be-detected information matches to-be-remembered information-are not dependent on theta-band activity (i.e., theta phase). Given that these theta-independent 'match effects' occur during early processing stages (peaking at 75 ms), we propose that theta-rhythmic sampling modulates external and internal information during later processing stages.

Sensory History Drives Adaptive Neural Geometry in LP/Pulvinar-Prefrontal Cortex Circuits

Prior expectations guide attention and support perceptual filtering for efficient processing during decision-making. Here we show that during a visual discrimination task, mice adaptively use prior stimulus history to guide ongoing choices by estimating differences in evidence between consecutive trials (| Δ Dir |). The thalamic lateral posterior (LP)/pulvinar nucleus provides robust inputs to the Anterior Cingulate Cortex (ACC), which has been implicated in selective attention and predictive processing, but the function of the LP-ACC projection is unknown. We found that optogenetic manipulations of LP-ACC axons disrupted animals' ability to effectively estimate and use information across stimulus history, leading to | Δ Dir |-dependent ipsilateral biases. Two-photon calcium imaging of LP-ACC axons revealed an engagement-dependent low-dimensional organization of stimuli along a curved manifold. This representation was scaled by | Δ Dir | in a manner that emphasized greater deviations from prior evidence. Thus, our work identifies the LP-ACC pathway as essential for selecting and evaluating stimuli relative to prior evidence to guide decisions.

Peak alpha frequency is linked to visual temporal attention in 6-month-olds

The temporal resolution of adults' visual attention has been linked to the frequency of alpha-band oscillations in electroencephalogram (EEG) signal, with higher Peak Alpha Frequency (PAF) being associated with better visual temporal processing skills. However, relatively less is known about neural mechanisms underlying individual differences in the temporal resolution of visual attention in infancy. This study investigated the role of PAF in visual temporal processing in early infancy. In a sample of 6-month-old infants (n = 62) we examined the relationship between PAF extracted from resting-state EEG, and saccadic latencies in a predictive cueing task where the appearance of a reward was predicted by higher or lower frequency of two flickering objects. Results showed that higher PAF was associated with shorter saccadic latencies in a condition with higher differences between the two flickering frequencies, speaking for the involvement of PAF in visual temporal attention in early development. Additionally, we found that infants were generally faster to orient to the reward in trials where both peripheral stimuli were flickering at relatively lower frequencies, roughly corresponding to the theta frequency band. Our findings support theoretical accounts highlighting the role of PAF in visual attention processing and extend this framework to early infancy.

Hierarchical Organization of Visual Feature Attention Control

Attention can be deployed in anticipation of visual stimuli based on features such as their color or direction of motion. This anticipatory feature-based attention involves top-down neural control signals from the frontoparietal network that bias visual cortex to enhance the processing of attended information and suppress distraction. So, for example, anticipatory attention control can enable effective selection based on stimulus color while ignoring distracting information about stimulus motion. But as well, anticipatory attention can be focused more narrowly, for example, to select specific colors or motion directions that define task-relevant events and objects. One important question that remains open is whether anticipatory attention control first biases broad feature dimensions such as color versus motion before biasing the specific feature attributes (e.g., blue vs. green). To investigate this, we recorded EEG activity during a task where participants were cued to either attend to a color (blue or green) or a motion direction (up or down) on a trial-by-trial basis. Applying multivariate decoding approaches to the EEG alpha band (8-12 Hz) activity during the attention control period (cue-target interval), we observed significant decoding for both the attended dimensions (color vs. motion) and specific feature attributes (blue vs. green; up vs. down). Importantly, the temporal onset of the dimension-level biasing (color vs. motion) preceded that of the attribute-level biasing (e.g., blue vs. green). These findings demonstrate that the top-down control of feature-based attention proceeds in a hierarchical fashion, first biasing the broad feature dimension, and then narrowing to the specific feature attribute.

Significance Statement

During voluntary feature-based attention, electrophysiological and neuroimaging studies have highlighted the role of anticipatory (top-down) biasing of the sensory cortex in enhancing the selection of attended stimulus attributes, but little is known about how this is achieved. In particular, it is not clear whether attending to an attribute such as a color (blue vs. green) or motion direction (up vs. down) first biases all neural structures coding that dimension (color/motion) before biasing the specific attribute, or if the top-down signals directly bias only the attended attribute. Using EEG and multivariate decoding, we report that top-down attention control follows a hierarchical organization: first, the broader attended feature dimension is biased, which is followed by the biasing of the specific feature attribute.

Multimodal neuroimaging of hierarchical cognitive control

Cognitive control enables us to translate our knowledge into actions, allowing us to flexibly adjust our behavior, according to environmental contexts, our internal goals, and future plans. Multimodal neuroimaging and neurostimulation techniques have proven essential for advancing our understanding of how cognitive control emerges from the coordination of distributed neuronal activities in the brain. In this review, we examine the literature on multimodal studies of cognitive control. We explore how these studies provide converging evidence for a novel, multiplexed model of cognitive control, in which neural oscillations support different levels of control processing along a functionally hierarchical organization of distinct frontoparietal networks.

Dissociation of Attentional State and Behavioral Outcome Using Local Field Potentials

Successful behavior depends on the attentional state and other factors related to decision-making, which may modulate neuronal activity differently. Here, we investigated whether attentional state and behavioral outcome (i.e., whether a target is detected or missed) are distinguishable using the power and phase of local field potential recorded bilaterally from area V4 of two male rhesus monkeys performing a cued visual attention task. To link each trial's outcome to pairwise measures of attention that are typically averaged across trials, we used several methods to obtain single-trial estimates of spike count correlation and phase consistency. Surprisingly, while attentional location was best discriminated using gamma and high-gamma power, behavioral outcome was best discriminated by alpha power and steady-state visually evoked potential. Power outperformed absolute phase in attentional/behavioral discriminability, although single-trial gamma phase consistency provided reasonably high attentional discriminability. Our results suggest a dissociation between the neuronal mechanisms that regulate attentional focus and behavioral outcome.

Visual Processing by Hierarchical and Dynamic Multiplexing

The complexity of natural environments requires highly flexible mechanisms for adaptive processing of single and multiple stimuli. Neuronal oscillations could be an ideal candidate for implementing such flexibility in neural systems. Here, we present a framework for structuring attention-guided processing of complex visual scenes in humans, based on multiplexing and phase coding schemes. Importantly, we suggest that the dynamic fluctuations of excitability vary rapidly in terms of magnitude, frequency and wave-form over time, i.e., they are not necessarily sinusoidal or sustained oscillations. Different elements of single objects would be processed within a single cycle (burst) of alpha activity (7-14 Hz), allowing for the formation of coherent object representations while separating multiple objects across multiple cycles. Each element of an object would be processed separately in time-expressed as different gamma band bursts (>30 Hz)-along the alpha phase. Since the processing capacity per alpha cycle is limited, an inverse relationship between object resolution and size of attentional spotlight ensures independence of the proposed mechanism from absolute object complexity. Frequency and wave-shape of those fluctuations would depend on the nature of the object that is processed and on cognitive demands. Multiple objects would further be organized along the phase of slower fluctuations (e.g., theta), potentially driven by saccades. Complex scene processing, involving covert attention and eye movements, would therefore be associated with multiple frequency changes in the alpha and lower frequency range. This framework embraces the idea of a hierarchical organization of visual processing, independent of environmental temporal dynamics.

Pre-stimulus EEG phase coherence predicts visual target detection failures in schizophrenia: A pilot study

Impaired visual target detection is a common finding in schizophrenia that is linked to poor functional outcomes. However, the neural mechanisms that contribute to this deficit remain unclear. Recent research in healthy samples has identified relationships between the phase of pre-stimulus electroencephalographic (EEG) activity in the alpha band (8-12 Hz) or theta band (4-7 Hz) and the likelihood of visual target detection with and without attentional cueing, but these effects have not yet been explored in schizophrenia. We performed a study to investigate such effects in schizophrenia (n = 19) and healthy participants (n = 14), using a visual target detection task with attentional cues. We found significant relationships between pre-stimulus EEG phase properties and visual target detection in both groups, but also clear differences in the effects as a function of frequency, group, and attentional cueing. Alpha-band phase effects were relatively uniform across groups and conditions. By contrast, theta-band phase effects showed differences by group and attentional condition which could be consistent with attentional hyperfocusing in the schizophrenia group. Thus, our results elucidate a novel neural mechanism that may help to explain known impairments affecting both visual target detection and attention in schizophrenia.

Spatial prediction modulates the rhythm of attentional sampling

Recent studies demonstrate that behavioral performance during visual spatial attention fluctuates at theta (4 to 8 Hz) and alpha (8 to 16 Hz) frequencies, linked to phase-amplitude coupling of neural oscillations within the visual and attentional system depending on task demands. To investigate the influence of prior spatial prediction, we employed an adaptive discrimination task with variable cue-target onset asynchronies (300 to 1,300 ms) and different cue validity (100% & 50%). We recorded electroencephalography concurrently and adopted adaptive electroencephalography data analytical methods, namely, Holo-Holo-Hilbert spectral analysis and Holo-Hilbert cross-frequency phase clustering. Our findings indicate that response precision for near-threshold Landolt rings fluctuates at the theta band (4 Hz) under certain predictions and at alpha & beta bands (15 & 19 Hz) with uncertain predictions. Furthermore, spatial prediction strengthens theta-alpha modulations at parietal-occipital areas, frontal theta/parietal-occipital alpha phase-amplitude coupling, and within frontal theta-alpha phase-amplitude coupling. Notably, during the pretarget period, beta-modulated gamma oscillations in parietal-occipital areas predict response precision under uncertain prediction, while frontal theta/parietal-occipital alpha phase-amplitude coupling predicts response precision in spatially certain conditions. In conclusion, our study highlights the critical role of spatial prediction in attentional sampling rhythms with both behavioral and electroencephalography evidence.

Procedure for extracting temporal structure embedded within psychophysical data

The idea that mental events unfold over time with an intrinsically paced regularity has a long history within experimental psychology, and it has gained traction from the actual measurement of brain rhythms evident in EEG signals recorded from the human brain and from direct recordings of action potentials and local field potentials within the nervous systems of nonhumans. The weak link in this idea, however, is the challenge of extracting signatures of this temporal structure from behavioral measures. Because there is nothing in the seamless stream of conscious awareness that belies rhythmic modulations in sensitivity or mental acuity, one must deploy inferential strategies for extracting evidence for the existence of temporal regularities in neural activity. We have devised a parametric procedure for analysis of temporal structure embedded in behaviorally measured data comprising durations. We confirm that this procedure, dubbed PATS, achieves comparable results to those obtained using spectral analysis, and that it outperforms conventional spectral analysis when analyzing human response time data containing just a few hundred data points per condition. PATS offers an efficient, sensitive means for bridging the gap between oscillations identified neurophysiologically and estimates of rhythmicity embedded within durations measured behaviorally.

Cortical dynamics of perception as trains of coherent gamma oscillations, with the pulvinar as central coordinator

Synchronization of spikes carried by the visual streams is strategic for the proper binding of cortical assemblies, hence for the perception of visual objects as coherent units. Perception of a complex visual scene involves multiple trains of gamma oscillations, coexisting at each stage in visual and associative cortex. Here, we analyze how this synchrony is managed, so that the perception of each visual object can emerge despite this complex interweaving of cortical activations. After a brief review of structural and temporal facts, we analyze the interactions which make the oscillations coherent for the visual elements related to the same object. We continue with the propagation of these gamma oscillations within the sensory chain. The dominant role of the pulvinar and associated reticular thalamic nucleus as cortical coordinator is the common thread running through this step-by-step description. Synchronization mechanisms are analyzed in the context of visual perception, although the present considerations are not limited to this sense. A simple experiment is described, with the aim of assessing the validity of the elements developed here. A first set of results is provided, together with a proposed method to go further in this investigation.

Coupled oscillations orchestrate selective information transmission in visual cortex

Performing visually guided behavior involves flexible routing of sensory information towards associative areas. We hypothesize that in visual cortical areas, this routing is shaped by a gating influence of the local neuronal population on the activity of the same population's single neurons. We analyzed beta frequencies (representing local population activity), high-gamma frequencies (representative of the activity of local clusters of neurons), and the firing of single neurons in the medial temporal (MT) area of behaving rhesus monkeys. Our results show an influence of beta activity on single neurons, predictive of behavioral performance. Similarly, the temporal dependence of high-gamma on beta predicts behavioral performance. These demonstrate a unidirectional influence of network-level neural dynamics on single-neuron activity, preferentially routing relevant information. This demonstration of a local top-down influence unveils a previously unexplored perspective onto a core feature of cortical information processing: the selective transmission of sensory information to downstream areas based on behavioral relevance.

Fluctuation in cortical excitation/inhibition modulates capability of attention across time scales ranging from hours to seconds

Sustained attention, as the basis of general cognitive ability, naturally varies across different time scales, spanning from hours, e.g. from wakefulness to drowsiness state, to seconds, e.g. trial-by-trail fluctuation in a task session. Whether there is a unified mechanism underneath such trans-scale variability remains unclear. Here we show that fluctuation of cortical excitation/inhibition (E/I) is a strong modulator to sustained attention in humans across time scales. First, we observed the ability to attend varied across different brain states (wakefulness, postprandial somnolence, sleep deprived), as well as within any single state with larger swings. Second, regardless of the time scale involved, we found highly attentive state was always linked to more balanced cortical E/I characterized by electroencephalography (EEG) features, while deviations from the balanced state led to temporal decline in attention, suggesting the fluctuation of cortical E/I as a common mechanism underneath trans-scale attentional variability. Furthermore, we found the variations of both sustained attention and cortical E/I indices exhibited fractal structure in the temporal domain, exhibiting features of self-similarity. Taken together, these results demonstrate that sustained attention naturally varies across different time scales in a more complex way than previously appreciated, with the cortical E/I as a shared neurophysiological modulator.

Signal switching may enhance processing power of the brain

Our ability to perceive multiple objects is mysterious. Sensory neurons are broadly tuned, producing potential overlap in the populations of neurons activated by each object in a scene. This overlap raises questions about how distinct information is retained about each item. We present a novel signal switching theory of neural representation, which posits that neural signals may interleave representations of individual items across time. Evidence for this theory comes from new statistical tools that overcome the limitations inherent to standard time-and-trial-pooled assessments of neural signals. Our theory has implications for diverse domains of neuroscience, including attention, figure binding/scene segregation, oscillations, and divisive normalization. The general concept of switching between functions could also lend explanatory power to theories of grounded cognition.

Beta: bursts of cognition

Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.

Multiband task related components enhance rapid cognition decoding for both small and similar objects

The cortically-coupled target recognition system based on rapid serial visual presentation (RSVP) has a wide range of applications in brain computer interface (BCI) fields such as medical and military. However, in the complex natural environment backgrounds, the identification of event-related potentials (ERP) of both small and similar objects that are quickly presented is a research challenge. Therefore, we designed corresponding experimental paradigms and proposed a multi-band task related components matching (MTRCM) method to improve the rapid cognitive decoding of both small and similar objects. We compared the areas under the receiver operating characteristic curve (AUC) between MTRCM and other 9 methods under different numbers of training sample using RSVP-ERP data from 50 subjects. The results showed that MTRCM maintained an overall superiority and achieved the highest average AUC (0.6562 ± 0.0091). We also optimized the frequency band and the time parameters of the method. The verification on public data sets further showed the necessity of designing MTRCM method. The MTRCM method provides a new approach for neural decoding of both small and similar RSVP objects, which is conducive to promote the further development of RSVP-BCI.

Dissociation of attentional state and behavioral outcome using local field potentials

Successful behavior depends on attentional state and other factors related to decision-making, which may modulate neuronal activity differently. Here, we investigated whether attentional state and behavioral outcome (i.e., whether a target is detected or missed) are distinguishable using the power and phase of local field potential (LFP) recorded bilaterally from area V4 of monkeys performing a cued visual attention task. To link each trial's outcome to pairwise measures of attention that are typically averaged across trials, we used several methods to obtain single-trial estimates of spike count correlation and phase consistency. Surprisingly, while attentional location was best discriminated using gamma and high-gamma power, behavioral outcome was best discriminated by alpha power and steady-state visually evoked potential. Power outperformed absolute phase in attentional/behavioral discriminability, although single-trial gamma phase consistency provided reasonably high attentional discriminability. Our results suggest a dissociation between the neuronal mechanisms that regulate attentional focus and behavioral outcome.

Brain-state mediated modulation of inter-laminar dependencies in visual cortex

Spatial attention is critical for recognizing behaviorally relevant objects in a cluttered environment. How the deployment of spatial attention aids the hierarchical computations of object recognition remains unclear. We investigated this in the laminar cortical network of visual area V4, an area strongly modulated by attention. We found that deployment of attention strengthened unique dependencies in neural activity across cortical layers. On the other hand, shared dependencies were reduced within the excitatory population of a layer. Surprisingly, attention strengthened unique dependencies within a laminar population. Crucially, these modulation patterns were also observed during successful behavioral outcomes that are thought to be mediated by internal brain state fluctuations. Successful behavioral outcomes were also associated with phases of reduced neural excitability, suggesting a mechanism for enhanced information transfer during optimal states. Our results suggest common computation goals of optimal sensory states that are attained by either task demands or internal fluctuations.

Dorsal pulvinar inactivation leads to spatial selection bias without perceptual deficit

The dorsal pulvinar has been implicated in visuospatial attentional and perceptual confidence processing. Pulvinar lesions in humans and monkeys lead to spatial neglect symptoms, including an overt spatial saccade bias during free choices. However, it remains unclear whether disrupting the dorsal pulvinar during target selection that relies on a perceptual decision leads to a perceptual impairment or a more general spatial orienting and choice deficit. To address this question, we reversibly inactivated the unilateral dorsal pulvinar by injecting GABA-A agonist THIP while two macaque monkeys performed a color discrimination saccade task with varying perceptual difficulty. We used Signal Detection Theory and simulations to dissociate perceptual sensitivity (d-prime) and spatial selection bias (response criterion) effects. We expected a decrease in d-prime if dorsal pulvinar affects perceptual discrimination and a shift in response criterion if dorsal pulvinar is mainly involved in spatial orienting. After the inactivation, we observed response criterion shifts away from contralesional stimuli, especially when two competing stimuli in opposite hemifields were present. Notably, the d-prime and overall accuracy remained largely unaffected. Our results underline the critical contribution of the dorsal pulvinar to spatial orienting and action selection while showing it to be less important for visual perceptual discrimination.

Common and distinct neural mechanisms of attention

Despite a constant deluge of sensory stimulation, only a fraction of it is used to guide behavior. This selective processing is generally referred to as attention, and much research has focused on the neural mechanisms controlling it. Recently, research has broadened to include more ways by which different species selectively process sensory information, whether due to the sensory input itself or to different behavioral and brain states. This work has produced a complex and disjointed body of evidence across different species and forms of attention. However, it has also provided opportunities to better understand the breadth of attentional mechanisms. Here, we summarize the evidence that suggests that different forms of selective processing are supported by mechanisms both common and distinct.

Same, Same but Different? A Multi-Method Review of the Processes Underlying Executive Control

Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions.

Concurrent attention to hetero-depth surfaces in 3-D visual space is governed by theta rhythm

When simultaneously confronted with multiple attentional targets, visual system employs a time-multiplexing approach in which each target alternates for prioritized access, a mechanism broadly known as rhythmic attentional sampling. For the past decade, rhythmic attentional sampling has received mounting support from converging behavioral and neural findings. However, so compelling are these findings that a critical test ground has been long overshadowed, namely the 3-D visual space where attention is complicated by extraction of the spatial layout of surfaces extending beyond 2-D planes. It remains unknown how attentional deployment to multiple targets is accomplished in the 3-D space. Here, we provided a time-resolved portrait of the behavioral and neural dynamics when participants concurrently attended to two surfaces defined by motion-depth conjunctions. To characterize the moment-to-moment attentional modulation effects, we measured perceptual sensitivity to the hetero-depth surface motions on a fine temporal scale and reconstructed their neural representations using a time-resolved multivariate inverted encoding model. We found that the perceptual sensitivity to the two surface motions rhythmically fluctuated over time at ~4 Hz, with one's enhancement closely tracked by the other's diminishment. Moreover, the behavioral pattern was coupled with an ongoing periodic alternation in strength between the two surface motion representations in the same frequency. Together, our findings provide the first converging evidence of an attentional "pendulum" that rhythmically traverses different stereoscopic depth planes and are indicative of a ubiquitous attentional time multiplexor based on theta rhythm in the 3-D visual space.

Functional organization of posterior parietal cortex circuitry based on inferred information flow

Many studies infer the role of neurons by asking what information can be decoded from their activity or by observing the consequences of perturbing their activity. An alternative approach is to consider information flow between neurons. We applied this approach to the parietal reach region (PRR) and the lateral intraparietal area (LIP) in posterior parietal cortex. Two complementary methods imply that across a range of reaching tasks, information flows primarily from PRR to LIP. This indicates that during a coordinated reach task, LIP has minimal influence on PRR and rules out the idea that LIP forms a general purpose spatial processing hub for action and cognition. Instead, we conclude that PRR and LIP operate in parallel to plan arm and eye movements, respectively, with asymmetric interactions that likely support eye-hand coordination. Similar methods can be applied to other areas to infer their functional relationships based on inferred information flow.

Hierarchical consciousness: the Nested Observer Windows model

Foremost in our experience is the intuition that we possess a unified conscious experience. However, many observations run counter to this intuition: we experience paralyzing indecision when faced with two appealing behavioral choices, we simultaneously hold contradictory beliefs, and the content of our thought is often characterized by an internal debate. Here, we propose the Nested Observer Windows (NOW) Model, a framework for hierarchical consciousness wherein information processed across many spatiotemporal scales of the brain feeds into subjective experience. The model likens the mind to a hierarchy of nested mosaic tiles-where an image is composed of mosaic tiles, and each of these tiles is itself an image composed of mosaic tiles. Unitary consciousness exists at the apex of this nested hierarchy where perceptual constructs become fully integrated and complex behaviors are initiated via abstract commands. We define an observer window as a spatially and temporally constrained system within which information is integrated, e.g. in functional brain regions and neurons. Three principles from the signal analysis of electrical activity describe the nested hierarchy and generate testable predictions. First, nested observer windows disseminate information across spatiotemporal scales with cross-frequency coupling. Second, observer windows are characterized by a high degree of internal synchrony (with zero phase lag). Third, observer windows at the same spatiotemporal level share information with each other through coherence (with non-zero phase lag). The theoretical framework of the NOW Model accounts for a wide range of subjective experiences and a novel approach for integrating prominent theories of consciousness.

Multiple objects evoke fluctuating responses in several regions of the visual pathway

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (e.g., visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time (Jun et al., 2022). However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here, we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action.

Walking modulates visual detection performance according to stride cycle phase

Walking is among our most frequent and natural of voluntary behaviours, yet the consequences of locomotion upon perceptual and cognitive function remain largely unknown. Recent work has highlighted that although walking feels smooth and continuous, critical phases exist within each step for the successful coordination of perceptual and motor function. Here, we test whether these phasic demands impact upon visual perception, by assessing performance in a visual detection task during natural unencumbered walking. We finely sample visual performance over the stride cycle as participants walk along a smooth linear path at a comfortable speed in a wireless virtual reality environment. At the group-level, accuracy, reaction times, and response likelihood show strong oscillations, modulating at approximately 2 cycles per stride (~2 Hz) with a marked phase of optimal performance aligned with the swing phase of each step. At the participant level, Bayesian inference of population prevalence reveals highly prevalent oscillations in visual detection performance that cluster in two idiosyncratic frequency ranges (2 or 4 cycles per stride), with a strong phase alignment across participants.

The role of brain oscillations in feature integration

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well-known. However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration. Alpha and beta power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top-down expectancies.

Errors elicit frontoparietal theta-gamma coupling that is modulated by endogenous estradiol levels

Cognitive control-related error monitoring is intimately involved in behavioral adaptation, learning, and individual differences in a variety of psychological traits and disorders. Accumulating evidence suggests that a focus on women's health and ovarian hormones is critical to the study of such cognitive brain functions. Here we sought to identify a novel index of error monitoring using a time-frequency based phase amplitude coupling (t-f PAC) measure and examine its modulation by endogenous levels of estradiol in females. Forty-three healthy, naturally cycling young adult females completed a flanker task while continuous electroencephalogram was recorded on four occasions across the menstrual cycle. Results revealed significant error-related t-f PAC between theta phase generated in fronto-central areas and gamma amplitude generated in parietal-occipital areas. Moreover, this error-related theta-gamma coupling was enhanced by endogenous levels of estradiol both within females across the cycle as well as between females with higher levels of average circulating estradiol. While the role of frontal midline theta in error processing is well documented, this paper extends the extant literature by illustrating that error monitoring involves the coordination between multiple distributed systems with the slow midline theta activity modulating the power of gamma-band oscillatory activity in parietal regions. They further show enhancement of inter-regional coupling by endogenous estradiol levels, consistent with research indicating modulation of cognitive control neural functions by the endocrine system in females. Together, this work identifies a novel neurophysiological marker of cognitive control-related error monitoring in females that has implications for neuroscience and women's health.

The theta-gamma code in predictive processing and mnemonic updating

Predictive processing has become a leading theory about how the brain works. Yet, it remains an open question how predictive processes are realized in the brain. Here I discuss theta-gamma coupling as one potential neural mechanism for prediction and model updating. Building on Lisman and colleagues SOCRATIC model, theta-gamma coupling has been associated with phase precession and learning phenomena in medio-temporal lobe of rodents, where it completes and retains a sequence of places or items (i.e., predictive models). These sequences may be updated upon prediction errors (i.e., model updating), signaled by dopaminergic inputs from prefrontal networks. This framework, spanning the molecular to the network level, matches excitingly well with recent findings on predictive processing, mnemonic updating, and perceptual foraging for the theta-gamma code in human cognition. In sum, I use the case of theta-gamma coupling to link the predictive processing account, a very general concept of how the brain works, to specific neural processes which may implement predictive processing and model updating at the cognitive, network, cellular and molecular level.

Brain-state mediated modulation of inter-laminar dependencies in visual cortex

Spatial attention is a quintessential example of adaptive information processing in the brain and is critical for recognizing behaviorally relevant objects in a cluttered environment. Object recognition is mediated by neural encoding along the ventral visual hierarchy. How the deployment of spatial attention aids these hierarchical computations is unclear. Prior studies point to two distinct mechanisms: an improvement in the efficacy of information directed from one encoding stage to another, and/or a suppression of shared information within encoding stages. To test these proposals, it is crucial to estimate the attentional modulation of unique information flow across and shared information within the encoding stages of the visual hierarchy. We investigated this in the multi-stage laminar network of visual area V4, an area strongly modulated by attention. Using network-based dependency estimation from multivariate data, we quantified the modulation of inter-layer information flow during a change detection task and found that deployment of attention indeed strengthened unique dependencies between the input and superficial layers. Using the partial information decomposition framework, we estimated the modulation of shared dependencies and found that they are reduced specifically in the putative excitatory subpopulations within a layer. Surprisingly, we found a strengthening of unique dependencies within the laminar populations, a finding not previously predicted. Crucially, these modulation patterns were also observed during successful behavioral outcomes (hits) that are thought to be mediated by endogenous brain state fluctuations, and not by experimentally imposed attentive states. Finally, phases of endogenous fluctuations that were optimal for 'hits' were associated with reduced neural excitability. A reduction in neural excitability, potentially mediated by diminished shared inputs, suggests a novel mechanism for enhancing unique information transmission during optimal states. By decomposing the modulation of multivariate information, and combined with prior theoretical work, our results suggest common computations of optimal sensory states that are attained by either task demands or endogenous fluctuations.

Phase of neural oscillations as a reference frame for attention-based routing in visual cortex

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.

Pathway-selective optogenetics reveals the functional anatomy of top-down attentional modulation in the macaque visual cortex

Spatial attention represents a powerful top-down influence on sensory responses in primate visual cortical areas. The frontal eye field (FEF) has emerged as a key candidate area for the source of this modulation. However, it is unclear whether the FEF exerts its effects via its direct axonal projections to visual areas or indirectly through other brain areas and whether the FEF affects both the enhancement of attended and the suppression of unattended sensory responses. We used pathway-selective optogenetics in rhesus macaques performing a spatial attention task to inhibit the direct input from the FEF to area MT, an area along the dorsal visual pathway specialized for the processing of visual motion information. Our results show that the optogenetic inhibition of the FEF input specifically reduces attentional modulation in MT by about a third without affecting the neurons' sensory response component. We find that the direct FEF-to-MT pathway contributes to both the enhanced processing of target stimuli and the suppression of distractors. The FEF, thus, selectively modulates firing rates in visual area MT, and it does so via its direct axonal projections.

Serial attentional resource allocation during parallel feature value tracking

The visual system has evolved the ability to track features like color and orientation in parallel. This property aligns with the specialization of processing these feature dimensions in the visual cortex. But what if we ask to track changing feature-values within the same feature dimension? Parallel tracking would then have to share the same cortical representation, which would set strong limitations on tracking performance. We address this question by measuring the precision of color representations when human observers track the color of two superimposed dot clouds that simultaneously change color along independent trajectories in color-space. We find that tracking precision is highly imbalanced between streams and that tracking precision changes over time by alternating between streams at a rate of ~1 Hz. These observations suggest that, while parallel color tracking is possible, it is highly limited, essentially allowing for only one color-stream to be tracked with precision at a given time.

Beta oscillations in vision: a (preconscious) neural mechanism for the dorsal visual stream?

Neural oscillations in alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are thought to reflect feedback/reentrant loops and large-scale cortical interactions. In the last decades a main effort has been made in linking perception with alpha-band oscillations, with converging evidence showing that alpha oscillations have a key role in the temporal and featural binding of visual input, configuring the alpha rhythm a key determinant of conscious visual experience. Less attention has been historically dedicated to link beta oscillations and visual processing. Nonetheless, increasing studies report that task conditions that require to segregate/integrate stimuli in space, to disentangle local/global shapes, to spatially reorganize visual inputs, and to achieve motion perception or form-motion integration, rely on the activity of beta oscillations, with a main hub in parietal areas. In the present review, we summarize the evidence linking oscillations within the beta band and visual perception. We propose that beta oscillations represent a neural code that supports the functionality of the magnocellular-dorsal (M-D) visual pathway, serving as a fast primary neural code to exert top-down influences on the slower parvocellular-ventral visual pathway activity. Such M-D-related beta activity is proposed to act mainly pre-consciously, providing the spatial coordinates of vision and guiding the conscious extraction of objects identity that are achieved with slower alpha rhythms in ventral areas. Finally, within this new theoretical framework, we discuss the potential role of M-D-related beta oscillations in visuo-spatial attention, oculo-motor behavior and reading (dis)abilities.

From neural noise to co-adaptability: Rethinking the multifaceted architecture of motor variability

In the last decade, the source and the functional meaning of motor variability have attracted considerable attention in behavioral and brain sciences. This construct classically combined different levels of description, variable internal robustness or coherence, and multifaceted operational meanings. We provide here a comprehensive review of the literature with the primary aim of building a precise lexicon that goes beyond the generic and monolithic use of motor variability. In the pars destruens of the work, we model three domains of motor variability related to peculiar computational elements that influence fluctuations in motor outputs. Each domain is in turn characterized by multiple sub-domains. We begin with the domains of noise and differentiation. However, the main contribution of our model concerns the domain of adaptability, which refers to variation within the same exact motor representation. In particular, we use the terms learning and (social)fitting to specify the portions of motor variability that depend on our propensity to learn and on our largely constitutive propensity to be influenced by external factors. A particular focus is on motor variability in the context of the sub-domain named co-adaptability. Further groundbreaking challenges arise in the modeling of motor variability. Therefore, in a separate pars construens, we attempt to characterize these challenges, addressing both theoretical and experimental aspects as well as potential clinical implications for neurorehabilitation. All in all, our work suggests that motor variability is neither simply detrimental nor beneficial, and that studying its fluctuations can provide meaningful insights for future research.

Periodic attention deficits after frontoparietal lesions provide causal evidence for rhythmic attentional sampling

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time, even in states of presumed "sustained" attention. Recent evidence has suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results revealed that frontoparietal lesions introduce periodic attention deficits, i.e., temporally specific behavioral deficits that are aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with that of healthy controls during optimal phases but was attenuated during the less excitable sub-cycles. Theta-dependent sampling (3-8 Hz) was causally dependent on the prefrontal cortex, while high-alpha/low-beta sampling (8-14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high-amplitude, low-frequency brain activity is not epiphenomenal but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

Different Methods to Estimate the Phase of Neural Rhythms Agree But Only During Times of Low Uncertainty

Rhythms are a common feature of brain activity. Across different types of rhythms, the phase has been proposed to have functional consequences, thus requiring its accurate specification from noisy data. Phase is conventionally specified using techniques that presume a frequency band-limited rhythm. However, in practice, observed brain rhythms are typically nonsinusoidal and amplitude modulated. How these features impact methods to estimate phase remains unclear. To address this, we consider three phase estimation methods, each with different underlying assumptions about the rhythm. We apply these methods to rhythms simulated with different generative mechanisms and demonstrate inconsistency in phase estimates across the different methods. We propose two improvements to the practice of phase estimation: (1) estimating confidence in the phase estimate, and (2) examining the consistency of phase estimates between two (or more) methods.

"Leader-Follower" Dynamic Perturbation Manipulates Multi-Item Working Memory in Humans

Manipulating working memory (WM) is a central yet challenging notion. Previous studies suggest that WM items with varied memory strengths reactivate at different latencies, supporting a time-based mechanism. Motivated by this view, here we developed a purely bottom-up "Leader-Follower" behavioral approach to manipulate WM in humans. Specifically, task-irrelevant flickering color disks that are bound to each of the memorized items are presented during the delay period, and the ongoing luminance sequences of the color disks follow a Leader-Follower relationship, that is, a hundreds of milliseconds temporal lag. We show that this dynamic behavioral approach leads to better memory performance for the item associated with the temporally advanced luminance sequence (Leader) than the item with the temporally lagged luminance sequence (Follower), yet with limited effectiveness. Together, our findings constitute evidence for the essential role of temporal dynamics in WM operation and offer a promising, noninvasive WM manipulation approach.

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

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

Routing states transition during oscillatory bursts and attentional selection

Brain-wide information routing relies on the spatio-temporal dynamics of neural activity, but it remains unclear how routing states emerge at fast spiking timescales and relate to slower activity dynamics during cognitive processes. Here, we show that localized spiking events participate in directional routing states with spiking activity in distant brain areas that dynamically switch or amplify states during oscillatory bursts, attentional selection, and decision-making. Modeling and neural recordings from lateral prefrontal cortex (LPFC), anterior cingulate cortex (ACC), and striatum of nonhuman primates revealed that cross-regional routing states arise within 20 ms following individual neuron spikes, with LPFC spikes leading the activity in ACC and striatum. The baseline routing state amplified during LPFC beta bursts between LPFC and striatum and switched direction during ACC theta/alpha bursts between ACC and LPFC. Selective attention amplified theta-/alpha-band-specific lead ensembles in ACC, while decision-making increased the lead of ACC and LPFC spikes to the striatum.

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

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