Biology subjects

Duncan, J.

Publications and source records attributed to Duncan, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Sperm development requires TMC5-dependent mechanoresponsive calcium entry

Spermiogenesis, the transformation of round spermatids into streamlined, fertilization-competent sperm, represents cellular morphogenesis at its most extreme. Despite decades of effort, spermiogenesis remains difficult to recapitulate outside the testis, highlighting the importance of cues within the native tissue environment. The nature of these cues, however, remains poorly understood. Here, we discover that mechanical stimulation elicits Ca2+ entry in spermatids and identify transmembrane channel-like protein 5 (TMC5) as a principal mediator of this response. In both mouse and human testes, TMC5 is selectively expressed in spermatids and localized to the plasma membrane. TMC5 associates with TMC7 and calcium- and integrin-binding (CIB) proteins, mirroring TMC-CIB mechanotransduction complexes in sensory organs. Mechanistically, loss of Tmc5 blocks mechanically evoked Ca2+ entry, leading to disruptions in cytoskeletal remodeling and failure of CREM [&tau] dependent transcriptional programs required for spermiogenesis. Thus, TMC5 is required to couple mechanical cues to sperm development, with direct implications for male infertility.

cell biology↗

bioRxiv2026

Aperiodic neural activity links electromagnetic and hemodynamic representations of domain-general cognitive demand across the cortical hierarchy

The human brain demonstrates remarkable flexibility and capacity for domain-general cognitive control, allowing us to perform diverse and complex tasks. Central to this ability is the multiple- demand (MD) network, a domain-general system that is robustly engaged during demanding tasks in fMRI studies. However, the electrophysiological signatures underlying these domain-general responses remain elusive. While recent research has implicated aperiodic neural activity as a promising candidate, the limited spatial resolution of non-invasive electrophysiology has left it unresolved how this aperiodic signal relates to demand-related activity within the MD network and whether this relationship reflects a broader organizational principle across the cortex. To address these questions, we used a multimodal fusion framework to integrate fMRI and magnetoencephalography (MEG) data acquired while participants performed a diverse set of cognitive control tasks. We found that raw MEG- fMRI correspondence was strongest in unimodal sensorimotor cortices and progressively decreased toward transmodal association cortex during cognitive control tasks, revealing a hierarchical decline in correspondence between the electromagnetic and hemodynamic signals measured by these technologies. However, the proportion of this variance that was attributable to cognitive demand and carried by aperiodic signals showed the reverse gradient, systematically increasing along the sensorimotor-association axis. In particular, in the MD network, aperiodic broadband power showed the strongest demand-specific cross-modal commonality, outperforming canonical oscillatory components. These findings reveal two opposing hierarchical gradients: overall MEG-fMRI correspondence across all electrophysiological signals decreased toward association cortex, whereas the proportion attributable to aperiodic signals associated with cognitive demand increased. Our results identify aperiodic neural activity as a key electrophysiological substrate of cognitive control and a bridge linking electromagnetic and hemodynamic representations across the cortical hierarchy.

neuroscience↗

bioRxiv2026

Attentional selection drives information convergence within macaque lateral prefrontal cortex

Attention is a coherent state, in which multiple brain regions converge to represent selected features of a focal object or event. Lateral prefrontal cortex (LPFC), with its flexible coding of multiple task features and their conjunctions, is widely believed to play a key role in this process. While much research has investigated biased competition between features within a brain region, and cofluctuations of activity between regions, less is known about the representational dynamics through which a coherent neural state emerges. Here, we examine directed mutual information concerning multiple feature-specific population codes, between dorsal and ventral LPFC, across three phases of an attentional selection task. We find bidirectional convergence of information regarding multiple task features, but specifically following the period of selection from the visual display. The results show that neural processes driving inter-region coherence are especially salient during a period of cued object selection, despite comparable local information representation during other task phases. Significance statementIn the primate brain, lateral prefrontal cortex (LPFC) is thought to play a key role in selective attention, which is fundamental to goal-directed behaviour, and implies inter-region convergence towards a coherent representational state. Combining neural recordings, multivariate decoding, and analysis of information dynamics, we find local representations of multiple task features during multiple task phases, in separate regions of LPFC, with strong inter-region representational coherence emerging when attention could be directed to a chosen target. Results show that information convergence between these regions is bidirectional, sustained, and reflects multiple features of a chosen object, but, unlike local information representation, is highly specific to the choice phase of the task.

neuroscience↗

bioRxiv2026

HeteroRC: Decoding latent information from dynamic neural responses with interpretable heterogeneous reservoir computing

Time-resolved neural decoding is widely used to track information represented in neural activity, but conventional linear decoders primarily capture phase-locked evoked responses and often fail to recover representations embedded in nonlinear or non-phase-locked dynamics, potentially limiting the interpretation of neural coding. Here, we introduce HeteroRC, a biologically inspired and interpretable decoding framework based on heterogeneous reservoir computing. HeteroRC projects neural signals into a high-dimensional recurrent state space with heterogeneous time constants, enabling nonlinear feature expansion and multiscale temporal integration directly from raw neural time series. Simulations demonstrate that HeteroRC significantly outperforms linear decoders and a suite of artificial neural networks (including RNNs, LSTMs, Transformers and EEGNet) on evoked responses while robustly capturing induced oscillatory power, phase synchrony, and aperiodic modulations--dynamics that are largely latent to conventional linear methods. We further validate HeteroRC on two empirical EEG datasets. In a motor imagery task, it substantially improves decoding accuracy and exhibits superior cross-temporal generalisation, revealing dynamic representational transformations. In an attentional priority task, HeteroRC uncovers statistically learned spatial priority information that remains hidden from conventional methods, successfully decoding these latent states previously thought to be activity-silent. Furthermore, we develop a dual-level interpretability framework linking reservoir dynamics to virtual sources and sensor space, revealing the temporal, spectral, and spatial signatures underlying decoding performance at both the individual and group levels. Together, HeteroRC offers an interpretable approach to decode information from dynamic neural responses, broadening the analytical scope of neural decoding while remaining computationally efficient and free from manual feature engineering, making it particularly suitable for small-sample electrophysiological studies.

neuroscience↗

bioRxiv2026

Cognitive control networks in human and macaque

A much-replicated finding in human brain imaging is a distributed 'multiple-demand' or MD system, increasing in activity for many kinds of cognitive demand, and centrally involved in cognitive control. MD regions are proposed to encode a distributed mental model of critical task events, bound together in the roles and relationships needed to direct action selection. Though previous data hint at a corresponding network in the macaque, there has been no direct comparison to human data. Here we used functional magnetic resonance imaging to measure whole brain activation in a multi-step saccadic maze task, compared to a control requiring similar moves but without goal-based decisions. Human data were a close match to the canonical MD network, extended to include adjacent regions and in particular much of the canonical dorsal attention network. Data from two monkeys suggested correspondences in dorsomedial frontal, insula/orbitofrontal and posterior temporal cortex. In lateral frontal cortex there was just a single, largely dorsal activation patch, in contrast to multiple distinct human patches. In one animal, as in human, there was accompanying activation of dorsal and medial parietal cortex. In macaque as in human, together with previous data, our findings suggest an extended and strongly interconnected brain network recruited by increased cognitive challenge.

neuroscience↗

bioRxiv2025

Neural dynamics in ventrolateral prefrontal cortex underlie learning from feedback

Learning often depends on feedback, yet how positive and negative outcomes reorganize target representations to support later memory retrieval remains poorly understood. Accumulating evidence suggests that the ventrolateral prefrontal cortex (vlPFC) acts as a central hub linking learning and retrieval, raising the possibility that it plays a critical role in this process. Here we analysed spiking activity and local field potentials (LFPs) recorded from vlPFC while monkeys performed a multi-cycle object-learning task. During the initial learning cycle, correct and incorrect feedback elicited distinct vlPFC neural responses in both spiking and LFPs. In particular, positive feedback produced elevated theta power and enhanced phase-amplitude coupling (PAC) between theta phase and high-frequency amplitude, associated with sustained suppression of neural spiking. Incorrect feedback induced stronger beta power. Despite comparable levels of object information under both feedback conditions, decoders trained and tested within the same feedback state outperformed those tested across states, revealing feedback-dependent coding formats. State-space and cross-period generalisation analyses further showed that object representations following positive feedback were geometrically closer to and shared a common coding format with those reinstated during later retrieval, indicating that feedback reshapes neural geometry toward retrieval-compatible states. Moreover, these geometric and generalisation effects were selectively expressed on electrodes showing stronger PAC or beta power, suggesting that oscillatory coordination may regulate how feedback signals are transformed into stable target codes. Together, our results reveal how vlPFC serves as a critical bridge between learning and memory retrieval, with feedback-driven dynamics reorganizing population geometry through rhythmic coordination and bringing successful outcome states closer to future retrieval representations.

neuroscience↗

bioRxiv2025

Stimulus effects dwarf task effects in human visual cortex

Task context affects stimulus representations in human visual cortex, suggesting that visual representations are flexible. However, this interpretation is at odds with a major computational goal of the human visual system: creating a perceptually stable representation of the external visual environment. How does the visual system balance stability and flexibility? Here, human participants (71 percent females) categorized object images and written words according to different task rules, while brain responses were measured with fMRI. Using an ANOVA-based modeling strategy, we precisely quantified the relative contributions of stimulus, task, and their interaction in explaining representational variance across the cortical hierarchy. Our results show that stimulus effects account for the overwhelming majority of explainable representational variance across the ventral visual system: > 95 percent in V1 and V2, and > 90 percent in higher-level visual cortex. In prefrontal cortex, the relative contributions reverse: task effects dominate stimulus effects, accounting for 80 percent of explainable representational variance. In parietal cortex, contributions of stimulus and task are approximately equal. Our findings suggest that population coding in sensory cortex is optimized for representational stability to allow a consistent interpretation of the external environment. Population coding in parietal and frontal multiple-demand cortex, by contrast, is optimized for representational flexibility to accommodate changing behavioral goals and support flexible cognition and action. Significance statementStimulus representations in human visual cortex are affected by behavioral goals and are therefore thought to be flexible. However, this view is inconsistent with a major computational goal of the human visual system: creating a perceptually stable representation of the external environment. Here, we show that modulatory effects of behavioral goals on stimulus representations in visual cortex are surprisingly small. In contrast, behavioral goals strongly affect representations in parietal and frontal multiple-demand cortex. Our findings suggest that population coding in sensory cortex is optimized for stable perception, while population coding in parietal and frontal multiple-demand cortex is optimized for flexible cognition.

neuroscience↗

bioRxiv2025

Neural dynamics of an extended frontal lobe network in goal-subgoal problem solving

In goal-directed behavior, cognitive control calls for representation of current state, goal state, and current move, often with hierarchical organization into a series of steps or subgoals. In the human brain, a network of multiple-demand or MD regions underpins cognitive control, and core task features are likely encoded and integrated across this distributed network. Here we recorded from four putative homologs to human MD regions in the frontal cortex -- ventrolateral (vlPFC), dorsomedial (dmPFC), dorsal premotor (dPM) and anterior insula/orbitofrontal (I/O) cortex -- as two male monkeys solved a multi-step, on-screen spatial maze. Across regions there was substantial overlap but also wide quantitative variation in encoding task variables. Sensory input and current state were strongly coded in vlPFC, goal most stably in dmPFC, and move most rapidly in vlPFC and dPM. I/O responded during revision of a prepared route. In all regions, an abstract code of problem structure marked progress from problem start to end, with hierarchical separation of progress within and between successive steps. Partial specialisations, we suggest, arise from distinct connectivity, while broad co-recruitment reflects strong information exchange. Our results show how core components of goal-directed behavior are encoded across a distributed network of partial frontal lobe specialists, putatively homologous to frontal components of the human MD system.

neuroscience↗

bioRxiv2025

Category-biased patches encircle core domain-general regions in the human lateral prefrontal cortex

The fine-grained functional organization of the human lateral prefrontal cortex (PFC) remains poorly understood. Previous fMRI studies delineated focal domain-general, or multiple-demand (MD), PFC areas that co-activate during diverse cognitively demanding tasks. While there is some evidence for category-selective (face and scene) patches, in human and non-human primate PFC, these have not been systematically assessed. Recent precision fMRI studies have also revealed sensory-biased PFC patches adjacent to MD regions. To investigate if this topographic arrangement extends to other domains, we analysed two independent fMRI datasets (n=449 and n=37) utilizing the high-resolution multimodal MRI approaches of the Human Connectome Project (HCP). Both datasets included cognitive control tasks and stimuli spanning different categories: faces, places, tools and body parts. Contrasting each stimulus category against the remaining ones revealed focal interdigitated patches of activity located adjacent to core MD regions. The face and place results were robust, replicating across different executive tasks, experimental designs (block and event-related) and at the single subject level. In one dataset, where participants performed both category and sensory tasks, place patches overlapped with visually biased regions, while face patches were positioned between visual and auditory biases. Our results paint a refined view of the fine-grained functional organization of the PFC, revealing a recurring motif of interdigitated domain-specific and domain-general circuits. This organization offers new constraints for models of cognitive control, cortical specialization and development.

neuroscience↗

bioRxiv2025

Specialized response of default mode subnetworks and multiple-demand regions to transitions of person, place and time

This study used functional MRI data from the StudyForrest dataset to investigate the role of subnetworks of the default mode network (DMN) during naturalistic stimulus transitions of different types and magnitudes. We found distinct activation profiles within the DMN: the dmPFC subnetwork was specifically associated with character and location transitions, the MTL subnetwork preferred location and temporal transitions, while the Core DMN subnetwork responded to all three transition types. The multiple-demand network instead responded selectively to temporal transitions. These distinct response profiles appeared largely invariant to the semantic distance implied by the transitions. All subnetworks also responded significantly, and in a graded manner, to subjective event boundaries. Results suggest specific roles of the DMN subnetworks in perceiving and segmenting naturalistic events, supporting the view that DMN subnetworks cooperate in interpreting continuous external events and maintaining an updated contextual model of the world.

neuroscience↗

bioRxiv2024

Genomic Discovery of EF-24 Targets Unveils Antitumorigenic Mechanisms in Leukemia Cells

Curcumin, a polyphenolic compound derived from the plant Curcuma longa L., has demonstrated a wide range of therapeutic properties, including potential anticancer effects. However, its clinical efficacy is limited due to poor bioavailability and stability. To overcome these challenges, curcumin analogs like EF-24 have been developed with improved pharmacological properties. In this study, we used whole-transcriptome profiling to identify the genome-wide functional impacts of EF-24 treatment in leukemia cells to improve our understanding of its potential mechanisms of action. This approach allowed us to establish a model system for associating druggable genes with clinical disease targets. We used the chronic myeloid leukemia (CML) cell line K-562 and acute myeloid leukemia (AML) cell lines HL-60, Kasumi-1, and THP-1 to conduct EF-24 treatment studies. Cell viability was significantly decreased in the EF-24-treated cells as compared to the untreated controls. We discovered that the genes ATF3, CLU, HSPA6, OSGIN1, ZFAND2A, and CXCL8, which are associated with reduced cell viability and proliferation, were consistently upregulated in all EF-24-treated cell lines. Further analysis of the tested cell lines revealed the activation of various signaling pathways, including the STAT1 regulated S100 family signaling pathway, that controlled downstream gene expression in response to EF-24 treatment. Our results elucidate the molecular mechanisms underlying EF-24s antitumor efficacy against leukemia, highlighting its multifaceted impact on signaling pathways and gene networks that regulate cell survival, proliferation, and immune responses in myeloid leukemia cells. SignificanceThis study reveals how EF-24, a curcumin analog, disrupts key signaling pathways in chronic and acute myeloid leukemia cell lines, offering insights to enhance targeted therapies and provide new targets for investigation. Conflict of Interest StatementThe authors declare no potential conflicts of interest.

cancer biology↗

bioRxiv2024

Aperiodic and oscillatory systems underpinning human domain-general cognition

Domain-general cognitive systems are essential for adaptive human behaviour, supporting various cognitive tasks through flexible neural mechanisms. While fMRI studies link the frontoparietal network activation to increasing demands across various tasks, the electrophysiological mechanisms underlying this domain-general response to demand remain unclear. Here, we used MEG/EEG, with aperiodic and oscillatory components separated, to examine their roles in domain-general cognition across three cognitive tasks using multivariate analysis. We found that both aperiodic (broadband power, slope, and intercept) and oscillatory (theta, alpha, and beta power) components coded task demand and content across all subtasks. Aperiodic broadband power in particular strongly coded task demand, in a manner that generalised across all subtasks. Source estimation suggested that increasing cognitive demand decreased aperiodic broadband power across the brain, with the strongest modulations overlapping with the frontoparietal network. In contrast, oscillatory activity showed more localised patterns of modulation, primarily in frontal or occipital regions. These results provide insights into the electrophysiological underpinnings of human domain-general cognition, highlighting the critical role of aperiodic broadband power.

neuroscience↗

bioRxiv2024

Default Mode Network activation at task switches reflects mental task-set structure

Recent findings challenge traditional views of the Default Mode Network (DMN) as purely task-negative or self-oriented, showing increased DMN activity during demanding switches between externally-focused tasks (Crittenden et al., 2015; Smith et al., 2018; Zhou et al., 2024). However, it is unclear what modulates the DMN at switches, with transitions within a stimulus domain activating DMN regions in some studies but not others. Differences in the number of tasks suggest that complexity or structure of the set of tasks may be important. In this fMRI study, we examined whether the DMNs response to task switches depends on the complexity of the active set of tasks, manipulated by the number of tasks in a run, or abstract task groupings based on instructional order. Core DMN activation at task switches was unaffected by the number of currently relevant tasks. Instead, it depended on the order in which groups of tasks had been learnt. Multivariate decoding revealed that Core DMN hierarchically represents individual tasks, task domains, and higher-order task groupings based on instruction order. We suggest that, as the complexity of instructions increases, rules are increasingly organized into higher-level chunks, and Core DMN activity is highest at switches between chunks.

neuroscience↗

bioRxiv2024

Domain general frontoparietal regions show modality-dependent coding of auditory and visual rules

A defining feature of human cognition is our ability to respond flexibly to what we see and hear, changing how we respond depending on our current goals. In fact, we can rapidly associate almost any input stimulus with any arbitrary behavioural response. This remarkable ability is thought to depend on a frontoparietal "multiple demand" circuit which is engaged by many types of cognitive demand and widely referred to as domain general. However, it is not clear how responses to multiple input modalities are structured within this system. Domain generality could be achieved by holding information in an abstract form that generalises over input modality, or in a modality-tagged form, which uses similar resources but produces unique codes to represent the information in each modality. We used a stimulus-response task, with conceptually identical rules in two sensory modalities (visual and auditory), to distinguish between these possibilities. Multivariate decoding of functional magnetic resonance imaging data showed that representations of visual and auditory rules recruited overlapping neural resources but were expressed in modality-tagged non-generalisable neural codes. Our data suggest that this frontoparietal system may draw on the same or similar resources to solve multiple tasks, but does not create modality-general representations of task rules, even when those rules are conceptually identical between domains.

neuroscience↗

bioRxiv2024

External task switches activate default mode regions without enhanced processing of the surrounding scene

Default mode network (DMN) activity, measured with fMRI, typically increases during internally directed thought, and decreases during tasks that demand externally focused attention. However, Crittenden et al. (2015) and Smith et al. (2018) reported increased DMN activity during demanding external task switches between different cognitive domains, compared to within-domain switches and task repeats. This finding is hard to reconcile with many dominant views of DMN function. Here, we aimed to replicate this DMN task-switch effect in a similar paradigm and test whether it reflects increased representation of broader context, specifically of a scene presented behind the focal task. In Core DMN, we found significant activity for all task switches, compared to task repeats, and stronger activity for switches between rest and task. Although the content of the background scene was attended, recalled, and neurally decodable, there was no evidence that this differed by switch type. Therefore, external task switches activated DMN without enhanced processing of the surrounding scene. Surprisingly, DMN activity at within-domain switches was no less than at between-domain switches. We suggest that modulation of DMN activity by task switches reflects a shift in the current cognitive model and depends on the overall complexity of that model.

neuroscience↗

bioRxiv2024

The dimensionality of neural coding for cognitive control is gradually transformed within the lateral prefrontal cortex

Implementing cognitive control relies on neural representations that are inherently high-dimensional and distribute across multiple subregions in the prefrontal cortex (PFC). Traditional approaches tackle prefrontal representations by reducing them into a unidimensional measure (univariate amplitude) or using them to distinguish a limited number of alternatives (pattern classification). By contrast, representational similarity analysis (RSA) enables flexibly formulating various hypotheses about informational contents underlying the neural codes, explicitly comparing hypotheses, and examining the representational alignment between brain regions. Here, we used a multifaceted paradigm wherein the difficulty of cognitive control was manipulated separately for five cognitive tasks. We used RSA to unveil representational contents, measure the representational alignment between regions, and quantify representational generality vs. specificity. We found a graded transition in the lateral PFC: The dorsocaudal PFC was tuned to the information about behavioural effort, preferentially connected with the parietal cortex, and representationally generalisable across domains. The ventrorostral PFC was tuned to the abstract structure of tasks, preferentially connected with the temporal cortex, and representationally specific. The middle PFC (interposed between dorsocaudal and ventrorostral PFC) was tuned to individual task-sets, ranked in the middle in terms of connectivity and generalisability. Furthermore, whether a region was dimensionally rich or thin co-varied with its functional profile: Low dimensionality (only gist) in the dorsocaudal PFC dovetailed with better generality, whereas high dimensionality (gist plus details) in the ventrorostral PFC corresponded with better ability to encode subtleties. Our findings, collectively, demonstrate how cognitive control is decomposed into distinct facets that transition steadily along prefrontal subregions. SignificanceCognitive control is known to be a high-dimensional construct, implemented along the dorsocaudal-ventrorostral subregions of PFC. However, it remains unclear how prefrontal representations could be dissected in a multivariate fashion to reveal (1) what information is encoded in each subregion, (2) whether information systematically transforms across contiguous PFC subregions as a gradient, (3) how this transformation is affected by functional connectivity. Here we shed light on these issues by using RSA to decode informational composition in the PFC while using participant-specific localisers to facilitate individually-tailored precision. Our findings elucidate the functional organisation of PFC by revealing how a trade-off between dimensionality and generalisability unfolds in the PFC and highlight the strength of RSA in deciphering the coding of cognitive control.

neuroscience↗

bioRxiv2023

RAPID RESISTANCE TO BET INHIBITORS IS MEDIATED BY FGFR1 IN GLIOBLASTOMA

Bromodomain and extra-terminal domain (BET) proteins are therapeutic targets in several cancers including the most common malignant adult brain tumor glioblastoma (GBM). Multiple small molecule inhibitors of BET proteins have been utilized in preclinical and clinical studies. Unfortunately, BET inhibitors have not shown efficacy in clinical trials enrolling GBM patients. One possible reason for this may stem from resistance mechanisms that arise after prolonged treatment within a clinical setting. However, the mechanisms and timeframe of resistance to BET inhibitors in GBM is not known. To identify the temporal order of resistance mechanisms in GBM we performed quantitative proteomics using multiplex-inhibitor bead mass spectrometry and demonstrated that intrinsic resistance to BET inhibitors in GBM treatment occurs rapidly within hours and involves the fibroblast growth factor receptor 1 (FGFR1) protein. Additionally, small molecule inhibition of BET proteins and FGFR1 simultaneously induces synergy in reducing GBM tumor growth in vitro and in vivo. Further, FGFR1 knockdown synergizes with BET inhibitor mediated reduction of GBM cell proliferation. Collectively, our studies suggest that co-targeting BET and FGFR1 may dampen resistance mechanisms to yield a clinical response in GBM.

cancer biology↗

bioRxiv2023

The causal roles of parietal alpha oscillations and evoked potentials in coding task-relevant information during selective attention

Selective attention is a fundamental cognitive mechanism that allows people to prioritise task-relevant information while ignoring irrelevant information. Previous research has suggested key roles of parietal evoked potentials and alpha oscillatory responses in spatial attention tasks. However, the informational content of these signals is less clear, and their causal effects on the coding of multiple task elements are yet unresolved. Here, we used concurrent TMS-EEG to causally manipulate parietal alpha power and evoked potentials and investigate their roles in coding multiple task features (where to attend, what to attend to, and visual stimulus) in a selective attention task. First, using EEG-only data, we found that evoked potentials coded all three types of task-relevant information with distinct temporal dynamics, and alpha oscillations carried information regarding both where to attend and what to attend to. Then, we applied rhythmic-TMS (rTMS) at individual alpha frequency over the right intraparietal sulcus (IPS), while concurrently measuring EEG. Compared with control arrhythmic-TMS, alpha rTMS increased alpha power and inter-trial phase coherence and yielded more negative posterior-contralateral evoked potentials. Moreover, alpha rTMS causally and specifically improved multivariate decoding of the information about where to attend (but not what to attend to or feature information) during task performance, with decoding improvements predicting changes in behavioural performance. These findings illuminate the dynamics with which the complementary aspects of a selective attention task are encoded in evoked and oscillatory brain activity. Moreover, they reveal a specific and causal role of IPS-controlled evoked and oscillatory activity in carrying behaviour-driving information about where to focus attention.

neuroscience↗