Biology subjects

Jensen, O.

Publications and source records attributed to Jensen, O..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Fast hierarchical processing of orthographic and semantic parafoveal information during natural reading

Readers extract orthographic and semantic information from parafoveal words before fixating on them. While this has to be achieved within an intersaccadic interval, the neuronal mechanisms supporting this fast parafoveal word processing within the language network remain unknown. We co-registered MEG and eye-tracking data in a natural reading paradigm to uncover the neuronal mechanisms supporting parafoveal processing. Representational similarity analysis (RSA) revealed that parafoveal orthographic neighbours (e.g., "writer" vs. "waiter") showed higher representational similarity than non-neighbours (e.g., "writer" vs. "police"), emerging [~]68 ms after fixation onset on the preceding word (e.g., "clever") in the visual word form area. Similarly, parafoveal semantic neighbours (e.g., "writer" vs. "author") exhibited increased representational similarity at [~]137 ms in the left inferior frontal gyrus. Importantly, the degree of orthographic and semantic parafoveal processing predicted individual reading speed. Our findings suggest fast hierarchical processing of parafoveal words across distinct brain regions, which enhances reading efficiency.

neuroscience↗

bioRxiv2024

Entorhinal grid-like codes for visual space during memory formation

Eye movements, such as saccades, allow us to gather information about the environment and, in this way, can shape memory. In non-human primates, saccades are associated with the activity of grid cells in the entorhinal cortex. Grid cells are essential for spatial navigation, but whether saccade-based grid-like signals play a role in human memory formation is currently unclear. Here, human participants underwent functional magnetic resonance imaging (fMRI) and continuous eye gaze monitoring while studying scene images. Recognition memory was probed immediately thereafter. Results revealed saccade-based grid-like codes in the left entorhinal cortex while participants studied the scene images, a finding that was replicated with an independent data set reported here. The grid-related effects were time-locked to activation increases in the frontal eye fields. Most importantly, saccade-based grid-like codes were associated with recognition memory, such that grid-like codes were lower the better participants performed in subsequently recognizing the scene images. Collectively, our findings suggest an entorhinal map of visual space that is timed with neural activity in oculomotor regions, supporting memory formation.

neuroscience↗

bioRxiv2024

Neocortical and hippocampal theta oscillations track audiovisual integration and replay of speech memories

"Are you talkin to me?!" If you ever watched the masterpiece "Taxi driver" directed by Martin Scorsese, you certainly recall the famous monologue during which Travis Bickle rehearses an imaginary confrontation in front of a mirror. While remembering this scene, you recollect a myriad of speech features across visual and auditory senses with a smooth sensation of unified memory. The aim of this study was to investigate how brain oscillations integrate the fine-grained synchrony between coinciding visual and auditory features when forming multisensory speech memories. We developed a memory task presenting participants with short synchronous or asynchronous movie clips focusing on the face of speakers engaged in real interviews. In the synchronous condition, the natural alignment between visual and auditory onsets was kept intact. In the asynchronous condition, auditory onsets were delayed to present lip movements and speech sounds in antiphase specifically with respect to the theta oscillation synchronising them in the original movie. We recorded magnetoencephalographic (MEG) activity to investigate brain oscillations in response to audiovisual asynchrony in the theta band. Our results first showed that theta oscillations in the neocortex and hippocampus were modulated by the level of synchrony between lip movements and syllables during audiovisual speech perception. Second, the accuracy of subsequent theta oscillation reinstatement during memory recollection was decreased when lip movements and the auditory envelope were encoded in asynchrony during speech perception. We demonstrate that neural theta oscillations in the neocortex and the hippocampus integrated lip movements and syllables during natural speech. We conclude that neural theta oscillations play a pivotal role in both aspects of audiovisual speech memories, i.e., encoding and retrieval.

neuroscience↗

bioRxiv2024

Fast feature- and category-related parafoveal previewing support natural visual exploration.

Studies on vision tend to prevent or control eye movements, while humans naturally saccade every [~]250 ms. As the oculomotor system takes [~]100 ms to initiate and execute a saccade, this leaves only [~]150 ms to identify the fixated object and select the next saccade goal. This is very little time, suggesting that vision relies on parafoveal processing before and after the eye movement. However, evidence of high-level parafoveal access is sparse. The purpose of our study was to use magnetoencephalography (MEG) combined with eye-tracking and multivariate pattern analysis to identify the neuronal dynamics of parafoveal processing which support natural visual exploration. We demonstrated that future saccade goals in the parafovea could be decoded at the feature and category level peaking at [~]90 ms and [~]160 ms respectively. Simultaneously, decoding of fixated objects at the feature and category level peaked at [~]70 ms and [~]145 ms respectively. Also decoding feature and category specific neuronal information related to past parafoveal objects were sustained for [~]230 ms after saccading away from them. The feature and category of objects in the parafovea could only be decoded if they were in the saccade goal. In sum, we provide insight on the neuronal mechanism of pre-saccadic attention by demonstrating that feature and category specific information of foveal and parafoveal objects can be extracted in succession within a [~]150 ms time-interval and may serve to plan the next saccade. This information is maintained also after fixations and may support integration across the full visual scene. Our study provides novel insight on the temporal dynamics of foveal and parafoveal processing at the feature and semantic levels during natural visual exploration.

neuroscience↗

bioRxiv2024

MAIT Cells Modulate Innate Immune Cells and Inhibit Colon Cancer Growth

Mucosal-associated invariant T (MAIT) cells are innate-like T cells that can be activated by microbial antigens and cytokines and are abundant in mucosal tissues including the colon. MAIT cells have cytotoxic and pro-inflammatory functions and have potentials for use as adoptive cell therapy. However, studies into their anti-cancer activity, including their role in colon cancer, are limited. Using an animal model of colon cancer, we show that peritumoral injection of in vivo-expanded MAIT cells into RAG1-/- mice with MC38-derived tumors inhibits tumor growth compared to control. Multiplex cytokine analyses show that tumors from the MAIT cell-treated group have higher expression of markers for eosinophil-activating cytokines, suggesting an association between eosinophil recruitment and tumor inhibition. In a human peripheral leukocyte co-culture model, we show that leukocytes stimulated with MAIT ligand show an increase in eotaxin-1 production and activation of eosinophils, associated with increased cancer cell killing. In conclusion, we show that MAIT cells have a protective role in a murine colon cancer model, associated with modulation of the immune response to cancer, potentially involving eosinophil-associated mechanisms. Our results highlight the potential of MAIT cells for non-donor restricted colon cancer immunotherapy. Brief summaryIn models of colon cancer, MAIT cells have anti-tumor activity, associated with increased production of proinflammatory and eosinophil-modulating cytokines.

cancer biology↗

bioRxiv2023

Oscillations in an Artificial Neural Network Convert Competing Inputs into a Temporal Code

Deep convolutional neural networks (CNNs) resemble the hierarchically organised neural representations in the primate visual ventral stream. However, these models typically disregard the temporal dynamics experimentally observed in these areas. For instance, alpha oscillations dominate the dynamics of the human visual cortex, yet the computational relevance of oscillations is rarely considered in artificial neural networks (ANNs). We propose an ANN that embraces oscillatory dynamics with the computational purpose of converting simultaneous inputs, presented at two different locations, into a temporal code. The network was trained to classify three individually presented letters. Post-training, we added semi-realistic temporal dynamics to the hidden layer, introducing relaxation dynamics in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, elucidating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activated sequentially, ordered along the phase of the inhibitory oscillations. Our model provides a novel approach for implementing multiplexing in ANNs. It further produces experimentally testable predictions of how the primate visual system handles competing stimuli.

neuroscience↗

bioRxiv2023

Spatiotemporal properties of common semantic categories for words and pictures

The timing of semantic processing during object recognition in the brain is a topic of ongoing discussion. One way of addressing this question is by applying multivariate pattern analysis (MVPA) to human electrophysiological responses to object images of different semantic categories. However, while MVPA can reveal whether neuronal activity patterns are distinct for different stimulus categories, concerns remain on whether low-level visual features also contribute to the classification results. To circumvent this issue, we applied a cross-decoding approach to magnetoencephalography (MEG) data from stimuli from two different modalities: images and their corresponding written words. We employed items for three categories and presented them in a randomized order. We show that If the classifier is trained on words, pictures are classified between 150 - 430 ms from after stimulus onset, and when training on pictures, words are classified between 225 - 430 ms. The topographical map identified using a searchlight approach for cross-modal activation in both directions showed left lateralization confirming the involvement of linguistics representations. These results point to semantic activation of pictorial stimuli occurring at {approx}150 ms whereas for words the semantic activation occurs at {approx}230 ms.

neuroscience↗

bioRxiv2023

Optimizing magnetometers arrays and pre-processing pipelines for multivariate pattern analysis

BackgroundMultivariate pattern analysis (MVPA) has proven an excellent tool in cognitive neuroscience used M/EEG, and MRI. It also holds a strong promise when applied to optically-pumped magnetometer-based magnetoencephalography. New methodTo optimize OPM-MEG systems for MVPA experiments this study examines data from a conventional MEG magnetometer array, focusing on appropriate noise reduction techniques for magnetometers. We also determined the least required number of sensors needed for robust MVPA for image categorization experiments. ResultsWe found that the use of signal space separation (SSS) significantly lowered the classification accuracy considering a sub-array of 102 magnetometers or a sub-array of 204 gradiometers. We also found that classification accuracy did not improve when going beyond 30 sensors irrespective of whether SSS has been applied. Comparison with existing methodsThe power spectra of data filtered with SSS has a substantially higher noise floor that data cleaned with SSP or HFC. Consequently, the MVPA decoding results obtained from the SSS-filtered data are significantly lower compared to all other methods employed. ConclusionsWhen designing an MEG system based on SQUID magnetometers optimized for multivariate analysis for image categorization experiments, about 30 magnetometers are sufficient. We advise against applying SSS filters to data from MEG and OPM systems prior to performing MVPA as this method, albeit reducing low-frequency external noise contributions, also introduces an increase in broadband noise. We recommend employing noise reduction techniques that either decrease or maintain the noise floor of the data like signal-space projection, homogeneous field correction and gradient noise reduction. HighlightsO_LIA sensor array of about 30 sensors is sufficient for multivariate pattern analysis using conventional MEG magnetometers for image classification. C_LIO_LIUsing signal space separation filter on magnetometer data prior to multivariate pattern analysis might reduce classification accuracy due to an increase in white noise in the data contributed by the algorithm. C_LIO_LIWhen performing multivariate data analysis, other noise reduction approaches that diminish the contribution of external noise sources and reduce the variance of the data are advisable such as synthetic gradiometers, signal space projection or homogeneous field correction. C_LI

neuroscience↗

bioRxiv2023

Differential neural mechanisms underlie cortical gating of visual spatial attention mediated by alpha-band oscillations

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information. SIGNIFICANCE STATEMENTSelective attention relies on neural mechanisms involved in target enhancement and distractor suppression to guide behavior. Using electrocorticographic data in humans, we show a spatiotemporal dissociation between cortical activities engaged in target facilitation and distractor inhibition during attentional deployment. We also found that, at attended locations, interareal interactions are enhanced through cross-frequency coupling along the visual hierarchy to potentially facilitate the processing of a spatially predictable target. In contrast, at unattended locations, intraareal interactions are enhanced through cross-frequency coupling, and interareal interactions are suppressed, together to potentially attenuate the processing of distractors. Our findings reveal that such a distributed cortical organization and complementary neural mechanisms enable efficient gating and filtering of sensory information in the anticipatory processing of spatial attention.

neuroscience↗

bioRxiv2023

Bioengineering of a human innervated cardiac muscle model

Cardiac autonomic neurons control cardiac contractility. Dysregulation of the autonomic nervous system can lead to sympathetic overdrive resulting in heart failure and an increased incidence of fatal arrhythmias. Here, we introduce innervated engineered human myocardium (iEHM), a novel model of neuro-cardiac junctions, constructed by fusion of a bioengineered neural organoid (BENO) patterned to autonomic nervous system and engineered human myocardium (EHM). Projections of sympathetic neurons into engineered human myocardium formed presynaptic terminals in close proximity to cardiomyocytes and an extensive vascular network co-developing in the tissues. Contractile responses to optogenetic stimulation of the accordingly engineered neuronal component demonstrated functionality of neuro-cardiac junctions in iEHM. This model will serve as a human surrogate system to delineate neuron and cardiac cell contribution to brain and heart diseases and is an important step towards engineering a human brain to heart axis in a dish.

bioengineering↗

bioRxiv2023

Alpha oscillations support the efficiency of guided visual search by inhibiting both target and distractor features in early visual cortex

Withdrawal StatementThe authors have withdrawn this manuscript owing to having received feedback that prompted a reconsideration of the findings in light of potential confounds associated with time-on-task effects, as highlighted by Benwell et al. (2019, NeuroImage). Subsequent in-depth analysis has led the authors to reassess the central assertions made in our original manuscript, and the main claims can no longer be supported. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

neuroscience↗

bioRxiv2023

Imperceptible gamma-band sensory stimulation enhances episodic memory retrieval

Enhanced gamma activity (30-100Hz) coincides with the successful recall of episodic memories, but it remains unknown whether this oscillatory activity is a cause or a consequence of the retrieval process. To address this question, we asked human participants to complete a paired associates memory task while undergoing sensory stimulation (at 65Hz, 43.3Hz and 32.5Hz). We observed that 65Hz and 32.5Hz sensory stimulation enhances recall compared to a baseline condition without stimulation. No similar effect was observed following 43.3Hz stimulation. Notably, while almost all participants could perceive 32.5Hz and 43.3Hz sensory stimulation, only a small proportion of participants ([~]10%) could perceive the 65Hz visual flicker, suggesting 65Hz sensory stimulation acts as an imperceptible intervention to enhance recall. To understand the dual action of 65Hz and 32.5Hz sensory stimulation on recall, we built three pyramidal-interneuronal network gamma (PING) models and drove them using the same stimulation protocols as in the behavioural task. The behavioural results could be reproduced by stimulating an endogenous [~]32Hz oscillation, but not by stimulating an endogenous [~]65Hz oscillation nor by stimulating a network without an endogenous oscillation. These results suggest that imperceptible 65Hz sensory stimulation enhances recall by harmonically entraining an endogenous [~]32.5Hz oscillation. Based on these findings, we propose that "slow" gamma oscillations play a causal role in episodic memory retrieval.

neuroscience↗

bioRxiv2023

Modulation of alpha oscillations by attention is predicted by hemispheric asymmetries of subcortical regions.

Evidence suggests that subcortical structures play a role in high-level cognitive functions such as the allocation of spatial attention. While there is abundant evidence in humans for posterior alpha band oscillations being modulated by spatial attention, little is known about how subcortical regions contribute to these oscillatory modulations, particularly under varying conditions of cognitive challenge. In this study, we combined MEG and structural MRI data to investigate the role of subcortical structures in controlling the allocation of attentional resources by employing a cued spatial attention paradigm with varying levels of perceptual load. We asked whether hemispheric lateralization of volumetric measures of the thalamus and basal ganglia predicted the hemispheric modulation of alpha-band power. Lateral asymmetry of the globus pallidus, caudate nucleus, and thalamus predicted attention-related modulations of posterior alpha oscillations. When the perceptual load was applied to the target and the distractor was salient caudate nucleus asymmetry predicted alpha-band modulations. Globus Pallidus was predictive of alpha-band modulations when either the target had a high load, or the distractor was salient, but not both. Finally, the asymmetry of the thalamus predicted alpha band modulation when neither component of the task was perceptually demanding. In addition to delivering new insight into the subcortical circuity controlling alpha oscillations with spatial attention, our finding might also have clinical applications. We provide a framework that could be followed for detecting how structural changes in subcortical regions that are associated with neurological disorders can be reflected in the modulation of oscillatory brain activity.

neuroscience↗

bioRxiv2023

An adversarial collaboration to critically evaluate theories of consciousness

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, yet, confirmation bias and dependence on design choices hamper progress in the field3. Here, we present an open science adversarial collaboration which directly juxtaposes Integrated Information Theory (IIT)4,5 and Global Neuronal Workspace Theory (GNWT)6-10, employing a theory-neutral consortium approach11,12. We investigate neural correlates of the content and duration of visual experience. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes, and their interpretation12. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography, and electrocorticography. We find information about conscious content in visual, ventro-temporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results confirm some predictions of IIT and GNWT, while substantially challenging both theories: for IIT, a lack of sustained synchronization within posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in prefrontal cortex. Beyond challenging the theories themselves, we present an alternative approach to advance cognitive neuroscience through a principled, theory-driven, collaborative effort. We highlight the challenges to change peoples mind 13 and the need for a quantitative framework integrating evidence for systematic theory testing and building.

neuroscience↗

bioRxiv2022

Optimal parameters for Rapid invisible Frequency Tagging using MEG

Frequency tagging has been demonstrated to be a useful tool for identifying representational-specific neuronal activity in the auditory and visual domains. However, the slow flicker (<30Hz) applied in conventional frequency tagging studies is highly visible and might entrain endogenous neuronal oscillations. Hence, stimulation at faster frequencies that is much less visible and does not interfere with endogenous brain oscillatory activity is a promising new tool. In this study, we set out to examine the optimal stimulation parameters of rapid invisible frequency tagging (RFT/RIFT) with magnetoencephalography (MEG) by quantifying the effects of stimulation frequency, size and position of the flickering patch. Rapid frequency tagging (RFT) using flickers above 50 Hz results in almost invisible stimulation which does not interfere with slower endogenous oscillations; however, the signal is weaker as compared to tagging at slower frequencies so the optimal parameters of stimulation delivery are crucial. The here presented results examining the frequency range between 60Hz and 96Hz suggest that RFT induces brain responses with decreasing strength up to about 84Hz. In addition, even at the smallest flicker patch (2{degrees}) focally presented RFT induces a significant oscillatory brain signal at the stimulation frequency (66Hz); however, the elicited response increases with patch size. While focal RFT presentation elicits the strongest response, off-centre presentations do generally mainly elicit a measureable response if presented below the horizontal midline. The results also revealed considerable individual differences in the neuronal responses of to RFT stimulation. Finally, we discuss the comparison of oscillatory measures (coherence and power) and sensor types (planar gradiometers and magnetometers) in order to achieve optimal outcomes. Based on our extensive findings we set forward concrete recommendations for using rapid frequency tagging in human cognitive neuroscience investigations.

neuroscience↗

bioRxiv2022

Travelling waves observed in MEG data can be explained by two discrete sources

Growing evidence suggests that travelling waves are functionally relevant for cognitive operations in the brain. Several electroencephalography (EEG) studies report on a perceptual alpha-echo, representing the brain response to a random visual flicker, propagating as a travelling wave across the cortical surface. In this study, we ask if the propagating activity of the alpha-echo is best explained by a set of discrete sources mixing at the sensor level rather than a cortical travelling wave. To this end, we presented participants with gratings modulated by random noise and simultaneously acquired the ongoing MEG. The perceptual alpha-echo was estimated using the temporal response function linking the visual input to the brain response. At the group level, we observed a spatial decay of the amplitude of the alpha-echo with respect to the sensor where the alpha-echo was the largest. Importantly, the propagation latencies consistently increased with the distance. Interestingly, the propagation of the alpha-echoes was predominantly centro-lateral, while EEG studies reported mainly posterior-frontal propagation. Moreover, the propagation speed of the alpha-echoes derived from the MEG data was around 10 m/s, which is higher compared to the 2 m/s reported in EEG studies. Using source modelling, we found an early component in the primary visual cortex and a phase-lagged late component in the parietal cortex, which may underlie the travelling alpha-echoes at the sensor level. We then simulated the alpha-echoes using realistic EEG and MEG forward models by placing two sources in the parietal and occipital cortices in accordance with our empirical findings. The two-source model could account for both the direction and speed of the observed alpha-echoes in the EEG and MEG data. Our results demonstrate that the propagation of the perceptual echoes observed in EEG and MEG data can be explained by two sources mixing at the scalp level equally well as by a cortical travelling wave. This conclusion however does not put into question continuous travelling waves reported in intracranial recordings.

neuroscience↗

bioRxiv2022

Parafoveal semantic integration in natural reading

Humans can read and comprehend text rapidly, implying that readers might process multiple words per fixation. However, the extent to which parafoveal words are previewed and integrated into the evolving sentence context remains disputed. We investigated parafoveal processing during natural reading by recording brain activity and eye movements using MEG and an eye tracker while participants silently read one-line sentences. The sentences contained an unpredictable target word that was either congruent or incongruent with the sentence context. To measure parafoveal processing, we flickered the target words at 60 Hz and measured the resulting brain responses (i.e., Rapid Invisible Frequency Tagging, RIFT) during fixations on the pre-target words. Our results revealed a significantly weaker tagging response for target words that were incongruent with the previous context compared to congruent ones, even within 100 ms of fixating the word immediately preceding the target. This reduction in the RIFT response was also found to be predictive of individual reading speed. We conclude that semantic information is not only extracted from the parafovea but can also be integrated with the previous context before the word is fixated. This early and extensive parafoveal processing supports the rapid word processing required for natural reading. Our study suggests that theoretical frameworks of natural reading should incorporate the concept of deep parafoveal processing.

neuroscience↗

bioRxiv2022

Statistical Learning of Distractor Suppression Down-regulates Pre-Stimulus Neural Excitability in Early Visual Cortex

Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning. Here we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression, while concurrently investigating the modulation of posterior alpha-band activity (8-12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the pre-stimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha-band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha-band activity might subtend different and possibly independent attentional mechanisms.

neuroscience↗