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Contribution of FEF to Attentional Periodicity during Visual Search: A TMS Study. eNeuro 2019; 6:ENEURO.0357-18.2019. [PMID: 31175148 PMCID: PMC6591533 DOI: 10.1523/eneuro.0357-18.2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 02/21/2019] [Accepted: 02/22/2019] [Indexed: 12/20/2022] Open
Abstract
Visual search, looking for a target embedded among distractors, has long been used to study attention. Current theories postulate a two-stage process in which early visual areas perform feature extraction, whereas higher-order regions perform attentional selection. Such a model implies iterative communication between low- and high-level regions to sequentially select candidate targets in the array, focus attention on these elements, and eventually permit target recognition. This leads to two independent predictions: (1) high-level, attentional regions and (2) early visual regions should both be involved periodically during the search. Here, we used transcranial magnetic stimulation (TMS) applied over the frontal eye field (FEF) in humans, known to be involved in attentional selection, at various delays while observers performed a difficult, attentional search task. We observed a periodic pattern of interference at ∼6 Hz (theta) suggesting that the FEF is periodically involved during this difficult search task. We further compared this result with two previous studies (Dugué et al., 2011, 2015a) in which a similar TMS procedure was applied over the early visual cortex (V1) while observers performed the same task. This analysis revealed the same pattern of interference, i.e., V1 is periodically involved during this difficult search task, at the theta frequency. Past V1 evidence reappraised for this paper, together with our current FEF results, confirm both of our independent predictions, and suggest that difficult search is supported by low- and high-level regions, each involved periodically at the theta frequency.
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Gardner JL, Liu T. Inverted Encoding Models Reconstruct an Arbitrary Model Response, Not the Stimulus. eNeuro 2019; 6:ENEURO.0363-18.2019. [PMID: 30923743 PMCID: PMC6437661 DOI: 10.1523/eneuro.0363-18.2019] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 02/25/2019] [Accepted: 03/03/2019] [Indexed: 01/24/2023] Open
Abstract
Probing how large populations of neurons represent stimuli is key to understanding sensory representations as many stimulus characteristics can only be discerned from population activity and not from individual single-units. Recently, inverted encoding models have been used to produce channel response functions from large spatial-scale measurements of human brain activity that are reminiscent of single-unit tuning functions and have been proposed to assay "population-level stimulus representations" (Sprague et al., 2018a). However, these channel response functions do not assay population tuning. We show by derivation that the channel response function is only determined up to an invertible linear transform. Thus, these channel response functions are arbitrary, one of an infinite family and therefore not a unique description of population representation. Indeed, simulations demonstrate that bimodal, even random, channel basis functions can account perfectly well for population responses without any underlying neural response units that are so tuned. However, the approach can be salvaged by extending it to reconstruct the stimulus, not the assumed model. We show that when this is done, even using bimodal and random channel basis functions, a unimodal function peaking at the appropriate value of the stimulus is recovered which can be interpreted as a measure of population selectivity. More precisely, the recovered function signifies how likely any value of the stimulus is, given the observed population response. Whether an analysis is recovering the hypothetical responses of an arbitrary model rather than assessing the selectivity of population representations is not an issue unique to the inverted encoding model and human neuroscience, but a general problem that must be confronted as more complex analyses intervene between measurement of population activity and presentation of data.
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Affiliation(s)
| | - Taosheng Liu
- Department of Psychology, Michigan State University, East Lansing, MI 48824
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53
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Foster JJ, Awh E. The role of alpha oscillations in spatial attention: limited evidence for a suppression account. Curr Opin Psychol 2018; 29:34-40. [PMID: 30472541 DOI: 10.1016/j.copsyc.2018.11.001] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 10/22/2018] [Accepted: 11/02/2018] [Indexed: 10/27/2022]
Abstract
Covert spatial attention allows us to prioritize visual processing at relevant locations. A fast growing literature suggests that alpha-band (8-12 Hz) oscillations play a key role in this core cognitive process. It is clear that alpha-band activity tracks both the locus and timing of covert spatial orienting. There is limited evidence, however, for the widely embraced view that alpha oscillations suppress irrelevant visual information during spatial selection. Extant evidence is equally compatible with an account in which alpha activity enables spatial selection through signal enhancement rather than distractor suppression. Thus, more work is needed to characterize the computational role of alpha activity in spatial attention.
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Affiliation(s)
- Joshua J Foster
- Department of Psychology and Institute for Mind and Biology, University of Chicago, 940 E. 57th Street, Chicago, IL 60637, United States.
| | - Edward Awh
- Department of Psychology and Institute for Mind and Biology, University of Chicago, 940 E. 57th Street, Chicago, IL 60637, United States.
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54
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Bocincova A, Johnson JS. The time course of encoding and maintenance of task-relevant versus irrelevant object features in working memory. Cortex 2018; 111:196-209. [PMID: 30508678 DOI: 10.1016/j.cortex.2018.10.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2018] [Revised: 09/06/2018] [Accepted: 10/10/2018] [Indexed: 11/27/2022]
Abstract
Access to WM can be restricted on the basis of goal-relevant properties such as spatial location. However, the extent of voluntary control over which features of an attended multi-feature object are encoded and maintained in WM is debated. Some evidence suggests that attending to an object leads to obligatory storage of all of its features, whereas other evidence suggests that access to WM can be restricted to only goal-relevant features. Another possibility is that all features are initially encoded, but irrelevant features are removed from WM over time. To address these various possibilities, we used pattern classification of EEG signals to track the temporal evolution of representations reflecting the encoding and storage of task-relevant and irrelevant features in WM. In different blocks, participants remembered the orientation, color or both orientation and color of a colored, oriented grating. The color and orientation of the grating was randomly drawn from two distinct feature bins on each trial. To examine trial-specific activity reflecting storage of the object's features, a support vector machine (SVM) classifier was trained to classify what bin the stimulus features came from. Importantly, for orientation, the classifier produced reliably above-chance classification across the delay when orientation was task-relevant but not when it was task-irrelevant. Interestingly, orientation could be accurately classified on trials for which both orientation and color were remembered. Moreover, a separate measure corresponding to the probability of a feature belonging to the correct bin was significantly higher when orientation was task-relevant compared to task-irrelevant during encoding. Above-chance classification for color was only present during the initial 500 msec across all conditions. Our results suggest that although information about all of an object's features is present in the initial stimulus-evoked neural response, information about the task-irrelevant features is attenuated during stimulus encoding and is largely absent throughout the delay.
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Affiliation(s)
- Andrea Bocincova
- Department of Psychology and Center for Visual and Cognitive Neuroscience, North Dakota State University, USA.
| | - Jeffrey S Johnson
- Department of Psychology and Center for Visual and Cognitive Neuroscience, North Dakota State University, USA.
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55
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Geometric classification of brain network dynamics via conic derivative discriminants. J Neurosci Methods 2018; 308:88-105. [PMID: 29966600 DOI: 10.1016/j.jneumeth.2018.06.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 06/22/2018] [Accepted: 06/25/2018] [Indexed: 11/21/2022]
Abstract
BACKGROUND Over the past decade, pattern decoding techniques have granted neuroscientists improved anatomical specificity in mapping neural representations associated with function and cognition. Dynamical patterns are of particular interest, as evidenced by the proliferation and success of frequency domain methods that reveal structured spatiotemporal rhythmic brain activity. One drawback of such approaches, however, is the need to estimate spectral power, which limits the temporal resolution of classification. NEW METHOD We propose an alternative method that enables classification of dynamical patterns with high temporal fidelity. The key feature of the method is a conversion of time-series data into temporal derivatives. By doing so, dynamically-coded information may be revealed in terms of geometric patterns in the phase space of the derivative signal. RESULTS We derive a geometric classifier for this problem which simplifies into a straightforward calculation in terms of covariances. We demonstrate the relative advantages and disadvantages of the technique with simulated data and benchmark its performance with an EEG dataset of covert spatial attention. We reveal the timecourse of covert spatial attention and, by mapping the classifier weights anatomically, its retinotopic organization. COMPARISON WITH EXISTING METHOD We especially highlight the ability of the method to provide strong group-level classification performance compared to existing benchmarks, while providing information that is complementary with classical spectral-based techniques. The robustness and sensitivity of the method to noise is also examined relative to spectral-based techniques. CONCLUSION The proposed classification technique enables decoding of dynamic patterns with high temporal resolution, performs favorably to benchmark methods, and facilitates anatomical inference.
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56
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Retrospective Cues Mitigate Information Loss in Human Cortex during Working Memory Storage. J Neurosci 2018; 38:8538-8548. [PMID: 30126971 DOI: 10.1523/jneurosci.1566-18.2018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 08/06/2018] [Accepted: 08/16/2018] [Indexed: 12/29/2022] Open
Abstract
Working memory (WM) enables the flexible representation of information over short intervals. It is well established that WM performance can be enhanced by a retrospective cue presented during storage, yet the neural mechanisms responsible for this benefit are unclear. Here, we tested several explanations for retrospective cue benefits by quantifying changes in spatial WM representations reconstructed from alpha-band (8-12 Hz) EEG activity recorded from human participants (both sexes) before and after the presentation of a retrospective cue. This allowed us to track cue-related changes in WM representations with high temporal resolution (tens of milliseconds). Participants encoded the locations of two colored discs for subsequent report. During neutral trials, an uninformative cue instructed participants to remember the locations of both discs across a blank delay, and we observed a monotonic decrease in the fidelity of reconstructed spatial WM representations with time. During valid trials, a 100% reliable cue indicated that the color of the disc participants would be probed to report. Critically, valid cues were presented immediately after the termination of the encoding display ["valid early" (VE) trials] or midway through the delay period ["valid late" (VL) trials]. During VE trials, the gradual loss of location-specific information observed during neutral trials was eliminated, while during VL trials it was partially reversed. Our findings suggest that retrospective cues engage several different mechanisms that together serve to mitigate information loss during WM storage.SIGNIFICANCE STATEMENT Working memory (WM) performance can be improved by a cue presented during storage. This effect, termed a retrospective cue benefit, has been used to explore the limitations of attentional prioritization in WM. However, the mechanisms responsible for retrospective cue benefits are unclear. Here we tested several explanations for retrospective cue benefits by examining how they influence WM representations reconstructed from human EEG activity. This approach allowed us to visualize, quantify, and track the effects of retrospective cues with high temporal resolution (on the order of tens of milliseconds). We show that under different circumstances retrospective cues can both eliminate and even partially reverse information loss during WM storage, suggesting that retrospective cue benefits have manifold origins.
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57
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Harris AM, Dux PE, Mattingley JB. Awareness is related to reduced post‐stimulus alpha power: a no‐report inattentional blindness study. Eur J Neurosci 2018; 52:4411-4422. [DOI: 10.1111/ejn.13947] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 04/02/2018] [Accepted: 04/03/2018] [Indexed: 01/27/2023]
Affiliation(s)
- Anthony M. Harris
- Queensland Brain Institute The University of Queensland St Lucia Qld Australia
| | - Paul E. Dux
- School of Psychology The University of Queensland St Lucia Qld Australia
| | - Jason B. Mattingley
- Queensland Brain Institute The University of Queensland St Lucia Qld Australia
- School of Psychology The University of Queensland St Lucia Qld Australia
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58
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Dong Y, Raif KE, Determan SC, Gai Y. Decoding spatial attention with EEG and virtual acoustic space. Physiol Rep 2018; 5:5/22/e13512. [PMID: 29180483 PMCID: PMC5704085 DOI: 10.14814/phy2.13512] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 10/30/2017] [Indexed: 11/24/2022] Open
Abstract
Decoding spatial attention based on brain signals has wide applications in brain–computer interface (BCI). Previous BCI systems mostly relied on visual patterns or auditory stimulation (e.g., loudspeakers) to evoke synchronous brain signals. There would be difficulties to cover a large range of spatial locations with such a stimulation protocol. The present study explored the possibility of using virtual acoustic space and a visual‐auditory matching paradigm to overcome this issue. The technique has the flexibility of generating sound stimulation from virtually any spatial location. Brain signals of eight human subjects were obtained with a 32‐channel Electroencephalogram (EEG). Two amplitude‐modulated noise or speech sentences carrying distinct spatial information were presented concurrently. Each sound source was tagged with a unique modulation phase so that the phase of the recorded EEG signals indicated the sound being attended to. The phase‐tagged sound was further filtered with head‐related transfer functions to create the sense of virtual space. Subjects were required to pay attention to the sound source that best matched the location of a visual target. For all the subjects, the phase of a single sound could be accurately reflected over the majority of electrodes based on EEG responses of 90 s or less. The electrodes providing significant decoding performance on auditory attention were fewer and may require longer EEG responses. The reliability and efficiency of decoding with a single electrode varied with subjects. Overall, the virtual acoustic space protocol has the potential of being used in practical BCI systems.
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Affiliation(s)
- Yue Dong
- Biomedical Engineering Department, Parks College of Engineering, Aviation and Technology Saint Louis University, St Louis, Missouri
| | - Kaan E Raif
- Biomedical Engineering Department, Parks College of Engineering, Aviation and Technology Saint Louis University, St Louis, Missouri
| | - Sarah C Determan
- Biomedical Engineering Department, Parks College of Engineering, Aviation and Technology Saint Louis University, St Louis, Missouri
| | - Yan Gai
- Biomedical Engineering Department, Parks College of Engineering, Aviation and Technology Saint Louis University, St Louis, Missouri
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59
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Pesaran B, Vinck M, Einevoll GT, Sirota A, Fries P, Siegel M, Truccolo W, Schroeder CE, Srinivasan R. Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation. Nat Neurosci 2018; 21:903-919. [PMID: 29942039 DOI: 10.1038/s41593-018-0171-8] [Citation(s) in RCA: 203] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 05/01/2018] [Indexed: 11/09/2022]
Abstract
New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.
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Affiliation(s)
- Bijan Pesaran
- Center for Neural Science, New York University, New York, NY, USA. .,NYU Neuroscience Institute, New York University Langone Health, New York, NY, USA.
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Anton Sirota
- Bernstein Center for Computational Neuroscience Munich, Munich Cluster of Systems Neurology (SyNergy), Faculty of Medicine, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany.,Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Markus Siegel
- Centre for Integrative Neuroscience & MEG Center, University of Tübingen, Tübingen, Germany
| | - Wilson Truccolo
- Department of Neuroscience and Institute for Brain Science, Brown University, Providence, RI, USA.,Center for Neurorestoration and Neurotechnology, U.S. Department of Veterans Affairs, Providence, RI, USA
| | - Charles E Schroeder
- Translational Neuroscience Division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.,Department of Neurosurgery, Columbia College of Physicians and Surgeons, New York, NY, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, Department of Biomedical Engineering, University of California, Irvine, CA, USA
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60
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Proskovec AL, Wiesman AI, Heinrichs-Graham E, Wilson TW. Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance. Sci Rep 2018; 8:8488. [PMID: 29855522 PMCID: PMC5981644 DOI: 10.1038/s41598-018-26863-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 05/22/2018] [Indexed: 01/28/2023] Open
Abstract
The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.
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Affiliation(s)
- Amy L Proskovec
- Department of Psychology, University of Nebraska - Omaha, Omaha, NE, USA.,Center for Magnetoencephalography, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.,Department of Neurological Sciences, UNMC, Omaha, NE, USA
| | - Alex I Wiesman
- Center for Magnetoencephalography, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.,Department of Neurological Sciences, UNMC, Omaha, NE, USA
| | - Elizabeth Heinrichs-Graham
- Center for Magnetoencephalography, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.,Department of Neurological Sciences, UNMC, Omaha, NE, USA
| | - Tony W Wilson
- Department of Psychology, University of Nebraska - Omaha, Omaha, NE, USA. .,Center for Magnetoencephalography, University of Nebraska Medical Center (UNMC), Omaha, NE, USA. .,Department of Neurological Sciences, UNMC, Omaha, NE, USA.
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61
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Mensen A, Marshall W, Sasai S, Tononi G. Differentiation Analysis of Continuous Electroencephalographic Activity Triggered by Video Clip Contents. J Cogn Neurosci 2018; 30:1108-1118. [PMID: 29762103 DOI: 10.1162/jocn_a_01278] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
While viewing a video clip, we experience a wide variety of contents, from low-level features of the images to high-level ideas such as the storyline. Each change in our experience must be supported by some corresponding change in neurophysiological activity. Differentiation analysis, which quantifies the differences in brain activity by measuring the distances between observed brain states, was applied here to continuous high-density electroencephalographic data recorded while participants watched short video clips. These clips were manipulated in various ways to change the degree of meaningfulness of their contents. We found that neurophysiological differentiation mirrored that of phenomenal differentiation, being higher for meaningful clips and lower for phase-scrambled versions or random noise. The distinction between meaningful and meaningless clips was present even at the individual level, and moreover, differentiation values correlated with individual subjective reports of meaningfulness. Spatial and spectral breakdowns of the overall effect showed frontal and posterior ROIs and highlighted specific roles for different spectral bands. Comparing the results with a multivariate decoding approach reveals that the two methods are capturing different aspects of brain activity and highlights a crucial theoretical distinction between the level and pattern of activity. In future applications, differentiation analysis may be used to evaluate the subjective meaningfulness of stimuli when behavioral responses may be inadequate, as with disorders of consciousness.
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Affiliation(s)
- Armand Mensen
- University of Liège.,University of Wisconsin at Madison
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62
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Effects of meaningfulness on perception: Alpha-band oscillations carry perceptual expectations and influence early visual responses. Sci Rep 2018; 8:6606. [PMID: 29700428 PMCID: PMC5920106 DOI: 10.1038/s41598-018-25093-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 04/09/2018] [Indexed: 12/03/2022] Open
Abstract
Perceptual experience results from a complex interplay of bottom-up input and prior knowledge about the world, yet the extent to which knowledge affects perception, the neural mechanisms underlying these effects, and the stages of processing at which these two sources of information converge, are still unclear. In several experiments we show that language, in the form of verbal labels, both aids recognition of ambiguous “Mooney” images and improves objective visual discrimination performance in a match/non-match task. We then used electroencephalography (EEG) to better understand the mechanisms of this effect. The improved discrimination of images previously labeled was accompanied by a larger occipital-parietal P1 evoked response to the meaningful versus meaningless target stimuli. Time-frequency analysis of the interval between the cue and the target stimulus revealed increases in the power of posterior alpha-band (8–14 Hz) oscillations when the meaning of the stimuli to be compared was trained. The magnitude of the pre-target alpha difference and the P1 amplitude difference were positively correlated across individuals. These results suggest that prior knowledge prepares the brain for upcoming perception via the modulation of alpha-band oscillations, and that this preparatory state influences early (~120 ms) stages of visual processing.
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63
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Brüers S, VanRullen R. Alpha Power Modulates Perception Independently of Endogenous Factors. Front Neurosci 2018; 12:279. [PMID: 29743869 PMCID: PMC5930164 DOI: 10.3389/fnins.2018.00279] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 04/10/2018] [Indexed: 11/24/2022] Open
Abstract
Oscillations are ubiquitous in the brain. Alpha oscillations in particular have been proposed to play an important role in sensory perception. Past studies have shown that the power of ongoing EEG oscillations in the alpha band is negatively correlated with visual outcome. Moreover, it also co-varies with other endogenous factors such as attention, vigilance, or alertness. In turn, these endogenous factors influence visual perception. Therefore, it remains unclear how much of the relation between alpha and perception is indirectly mediated by such endogenous factors, and how much reflects a direct causal influence of alpha rhythms on sensory neural processing. We propose to disentangle the direct from the indirect causal routes by introducing modulations of alpha power, independently of any fluctuations in endogenous factors. To this end, we use white-noise sequences to constrain the brain activity of 20 participants. The cross-correlation between the white-noise sequences and the concurrently recorded EEG reveals the impulse response function (IRF), a model of the systematic relationship between stimulation and brain response. These IRFs are then used to reconstruct rather than record the brain activity linked with new random sequences (by convolution). Interestingly, this reconstructed EEG only contains information about oscillations directly linked to the white-noise stimulation; fluctuations in attention and other endogenous factors may still modulate brain alpha rhythms during the task, but our reconstructed EEG is immune to these factors. We found that the detection of near-perceptual threshold targets embedded within these new white-noise sequences depended on the power of the ~10 Hz reconstructed EEG over parieto-occipital channels. Around the time of presentation, higher power led to poorer performance. Thus, fluctuations in alpha power, induced here by random luminance sequences, can directly influence perception: the relation between alpha power and perception is not a mere consequence of fluctuations in endogenous factors.
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Affiliation(s)
- Sasskia Brüers
- UMR 5549, Faculté de Médecine Purpan, Centre National de la Recherche Scientifique, Toulouse, France
- Centre de Recherche Cerveau et Cognition, Université de Toulouse, Université Paul Sabatier, Toulouse, France
| | - Rufin VanRullen
- UMR 5549, Faculté de Médecine Purpan, Centre National de la Recherche Scientifique, Toulouse, France
- Centre de Recherche Cerveau et Cognition, Université de Toulouse, Université Paul Sabatier, Toulouse, France
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64
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Cao D, Li Y, Niznikiewicz MA, Tang Y, Wang J. The theta burst transcranial magnetic stimulation over the right PFC affects electroencephalogram oscillation during emotional processing. Prog Neuropsychopharmacol Biol Psychiatry 2018; 82:21-30. [PMID: 29241839 DOI: 10.1016/j.pnpbp.2017.12.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 12/08/2017] [Accepted: 12/08/2017] [Indexed: 10/18/2022]
Abstract
Prefrontal cortex (PFC) plays an important role in emotional processing and therefore is one of the most frequently targeted regions for non-invasive brain stimulation such as repetitive transcranial magnetic stimulation (rTMS) in clinical trials, especially in the treatment of emotional disorders. As an approach to enhance the effectiveness of rTMS, continuous theta burst stimulation (cTBS) has been demonstrated to be efficient and safe. However, it is unclear how cTBS affects brain processes related to emotion. In particular, psychophysiological studies on the underlying neural mechanisms are sparse. In the current study, we investigated how the cTBS influences emotional processing when applied over the right PFC. Participants performed an emotion recognition Go/NoGo task, which asked them to select a GO response to either happy or fearful faces after the cTBS or after sham stimulation, while 64-channel electroencephalogram (EEG) was recorded. EEG oscillation was examined using event-related spectral perturbation (ERSP) in a time-interval between 170 and 310ms after face stimuli onset. In the sham group, we found a significant difference in the alpha band between response to happy and fearful stimuli but that effect did not exist in the cTBS group. The alpha band activity at the scalp was reduced suggesting the excitatory effect at the brain level. The beta and gamma band activity was not sensitive to cTBS intervention. The results of the current study demonstrate that cTBS does affect emotion processing and the effect is reflected in changes in EEG oscillations in the alpha band specifically. The results confirm the role of prefrontal cortex in emotion processing. We also suggest that this pattern of cTBS results elucidates mechanisms by which mood improvement in depressive disorders is achieved using cTBS intervention.
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Affiliation(s)
- Dan Cao
- School of Communication and Information Engineering, Qianweichang College, Shanghai University, Shanghai 200444, China
| | - Yingjie Li
- School of Communication and Information Engineering, Qianweichang College, Shanghai University, Shanghai 200444, China.
| | - Margaret A Niznikiewicz
- Laboratory of Cognitive Neuroscience, Boston VA Healthcare System, Brockton Division and Department of Psychiatry, Harvard Medical School, Boston, MA 02301, United States.
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200030, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiaotong University, Shanghai 200030, China.
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65
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Sprague TC, Itthipuripat S, Vo VA, Serences JT. Dissociable signatures of visual salience and behavioral relevance across attentional priority maps in human cortex. J Neurophysiol 2018; 119:2153-2165. [PMID: 29488841 DOI: 10.1152/jn.00059.2018] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Computational models posit that visual attention is guided by activity within spatial maps that index the image-computable salience and the behavioral relevance of objects in the scene. These spatial maps are theorized to be instantiated as activation patterns across a series of retinotopic visual regions in occipital, parietal, and frontal cortex. Whereas previous research has identified sensitivity to either the behavioral relevance or the image-computable salience of different scene elements, the simultaneous influence of these factors on neural "attentional priority maps" in human cortex is not well understood. We tested the hypothesis that visual salience and behavioral relevance independently impact the activation profile across retinotopically organized cortical regions by quantifying attentional priority maps measured in human brains using functional MRI while participants attended one of two differentially salient stimuli. We found that the topography of activation in priority maps, as reflected in the modulation of region-level patterns of population activity, independently indexed the physical salience and behavioral relevance of each scene element. Moreover, salience strongly impacted activation patterns in early visual areas, whereas later visual areas were dominated by relevance. This suggests that prioritizing spatial locations relies on distributed neural codes containing graded representations of salience and relevance across the visual hierarchy. NEW & NOTEWORTHY We tested a theory which supposes that neural systems represent scene elements according to both their salience and their relevance in a series of "priority maps" by measuring functional MRI activation patterns across human brains and reconstructing spatial maps of the visual scene. We found that different regions indexed either the salience or the relevance of scene items, but not their interaction, suggesting an evolving representation of salience and relevance across different visual areas.
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Affiliation(s)
- Thomas C Sprague
- Department of Psychology, New York University , New York, New York.,Neurosciences Graduate Program, University of California, San Diego, La Jolla, California
| | - Sirawaj Itthipuripat
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California.,Learning Institute, King Mongkut's University of Technology Thonburi, Bangmod, Thung Kru, Bangkok , Thailand.,Department of Psychology, Vanderbilt University , Nashville, Tennessee
| | - Vy A Vo
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California
| | - John T Serences
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California.,Department of Psychology, University of California, San Diego, La Jolla, California.,Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, California
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66
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Wutz A, Melcher D, Samaha J. Frequency modulation of neural oscillations according to visual task demands. Proc Natl Acad Sci U S A 2018; 115:1346-1351. [PMID: 29358390 PMCID: PMC5819398 DOI: 10.1073/pnas.1713318115] [Citation(s) in RCA: 118] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Temporal integration in visual perception is thought to occur within cycles of occipital alpha-band (8-12 Hz) oscillations. Successive stimuli may be integrated when they fall within the same alpha cycle and segregated for different alpha cycles. Consequently, the speed of alpha oscillations correlates with the temporal resolution of perception, such that lower alpha frequencies provide longer time windows for perceptual integration and higher alpha frequencies correspond to faster sampling and segregation. Can the brain's rhythmic activity be dynamically controlled to adjust its processing speed according to different visual task demands? We recorded magnetoencephalography (MEG) while participants switched between task instructions for temporal integration and segregation, holding stimuli and task difficulty constant. We found that the peak frequency of alpha oscillations decreased when visual task demands required temporal integration compared with segregation. Alpha frequency was strategically modulated immediately before and during stimulus processing, suggesting a preparatory top-down source of modulation. Its neural generators were located in occipital and inferotemporal cortex. The frequency modulation was specific to alpha oscillations and did not occur in the delta (1-3 Hz), theta (3-7 Hz), beta (15-30 Hz), or gamma (30-50 Hz) frequency range. These results show that alpha frequency is under top-down control to increase or decrease the temporal resolution of visual perception.
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Affiliation(s)
- Andreas Wutz
- Center for Mind and Brain Sciences, University of Trento, I-38068 Rovereto, Italy;
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - David Melcher
- Center for Mind and Brain Sciences, University of Trento, I-38068 Rovereto, Italy
| | - Jason Samaha
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53706
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67
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Clayton MS, Yeung N, Cohen Kadosh R. The many characters of visual alpha oscillations. Eur J Neurosci 2017; 48:2498-2508. [DOI: 10.1111/ejn.13747] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 09/27/2017] [Accepted: 10/09/2017] [Indexed: 11/26/2022]
Affiliation(s)
| | - Nick Yeung
- Department of Experimental Psychology; University of Oxford; Oxford UK
| | - Roi Cohen Kadosh
- Department of Experimental Psychology; University of Oxford; Oxford UK
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68
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Gulbinaite R, van Viegen T, Wieling M, Cohen MX, VanRullen R. Individual Alpha Peak Frequency Predicts 10 Hz Flicker Effects on Selective Attention. J Neurosci 2017; 37:10173-10184. [PMID: 28931569 PMCID: PMC6596538 DOI: 10.1523/jneurosci.1163-17.2017] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 09/05/2017] [Indexed: 11/21/2022] Open
Abstract
Rhythmic visual stimulation ("flicker") is primarily used to "tag" processing of low-level visual and high-level cognitive phenomena. However, preliminary evidence suggests that flicker may also entrain endogenous brain oscillations, thereby modulating cognitive processes supported by those brain rhythms. Here we tested the interaction between 10 Hz flicker and endogenous alpha-band (∼10 Hz) oscillations during a selective visuospatial attention task. We recorded EEG from human participants (both genders) while they performed a modified Eriksen flanker task in which distractors and targets flickered within (10 Hz) or outside (7.5 or 15 Hz) the alpha band. By using a combination of EEG source separation, time-frequency, and single-trial linear mixed-effects modeling, we demonstrate that 10 Hz flicker interfered with stimulus processing more on incongruent than congruent trials (high vs low selective attention demands). Crucially, the effect of 10 Hz flicker on task performance was predicted by the distance between 10 Hz and individual alpha peak frequency (estimated during the task). Finally, the flicker effect on task performance was more strongly predicted by EEG flicker responses during stimulus processing than during preparation for the upcoming stimulus, suggesting that 10 Hz flicker interfered more with reactive than proactive selective attention. These findings are consistent with our hypothesis that visual flicker entrained endogenous alpha-band networks, which in turn impaired task performance. Our findings also provide novel evidence for frequency-dependent exogenous modulation of cognition that is determined by the correspondence between the exogenous flicker frequency and the endogenous brain rhythms.SIGNIFICANCE STATEMENT Here we provide novel evidence that the interaction between exogenous rhythmic visual stimulation and endogenous brain rhythms can have frequency-specific behavioral effects. We show that alpha-band (10 Hz) flicker impairs stimulus processing in a selective attention task when the stimulus flicker rate matches individual alpha peak frequency. The effect of sensory flicker on task performance was stronger when selective attention demands were high, and was stronger during stimulus processing and response selection compared with the prestimulus anticipatory period. These findings provide novel evidence that frequency-specific sensory flicker affects online attentional processing, and also demonstrate that the correspondence between exogenous and endogenous rhythms is an overlooked prerequisite when testing for frequency-specific cognitive effects of flicker.
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Affiliation(s)
- Rasa Gulbinaite
- Centre National de la Recherche Scientifique, Faculté de Médecine Purpan, Toulouse 31000, France,
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Université Paul Sabatier, Toulouse 31052, France
| | - Tara van Viegen
- School of Psychology, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Martijn Wieling
- Department of Information Science, Faculty of Arts, University of Groningen, Groningen 9712 EK, The Netherlands, and
| | - Michael X Cohen
- Faculty of Science, Donders Center for Neuroscience, Radboud University, Nijmegen 6525 EN, The Netherlands
| | - Rufin VanRullen
- Centre National de la Recherche Scientifique, Faculté de Médecine Purpan, Toulouse 31000, France
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Université Paul Sabatier, Toulouse 31052, France
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69
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van Moorselaar D, Foster JJ, Sutterer DW, Theeuwes J, Olivers CNL, Awh E. Spatially Selective Alpha Oscillations Reveal Moment-by-Moment Trade-offs between Working Memory and Attention. J Cogn Neurosci 2017; 30:256-266. [PMID: 29040014 DOI: 10.1162/jocn_a_01198] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Current theories assume a functional role for covert attention in the maintenance of spatial information in working memory. Consistent with this view, both the locus of attention and positions stored in working memory can be decoded based on the topography of oscillatory alpha-band (8-12 Hz) activity on the scalp. Thus far, however, alpha modulation has been studied in isolation for covert attention and working memory tasks. Here, we applied an inverted spatial encoding model in combination with EEG to study the temporal dynamics of spatially specific alpha activity during a task that required observers to visually select a target location while maintaining another independently varying location in working memory. During the memory delay period, alpha-based spatial tuning functions shifted from the position stored in working memory to the covertly attended position and back again after the attention task was completed. The findings provide further evidence for a common oscillatory mechanism in both the selection and the maintenance of relevant spatial visual information and demonstrate the dynamic trade-off in prioritization between two spatial tasks.
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70
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Simon DM, Damiano CR, Woynaroski TG, Ibañez LV, Murias M, Stone WL, Wallace MT, Cascio CJ. Neural Correlates of Sensory Hyporesponsiveness in Toddlers at High Risk for Autism Spectrum Disorder. J Autism Dev Disord 2017; 47:2710-2722. [PMID: 28597185 PMCID: PMC5880549 DOI: 10.1007/s10803-017-3191-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Altered patterns of sensory responsiveness are a frequently reported feature of Autism Spectrum Disorder (ASD). Younger siblings of individuals with ASD are at a greatly elevated risk of a future diagnosis of ASD, but little is known about the neural basis of sensory responsiveness patterns in this population. Younger siblings (n = 20) of children diagnosed with ASD participated in resting electroencephalography (EEG) at an age of 18 months. Data on toddlers' sensory responsiveness were obtained using the Sensory Experiences Questionnaire. Correlations were present between hyporesponsiveness and patterns of oscillatory power, functional connectivity, and signal complexity. Our findings suggest that neural signal features hold promise for facilitating early identification and targeted remediation in young children at risk for ASD.
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Affiliation(s)
- David M Simon
- Neuroscience Graduate Program, Vanderbilt Brain Institute, Vanderbilt University Medical Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Vanderbilt University, Nashville, TN, USA
| | - Cara R Damiano
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, USA
| | - Tiffany G Woynaroski
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lisa V Ibañez
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Michael Murias
- Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Wendy L Stone
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Mark T Wallace
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry, Vanderbilt University, Nashville, TN, USA
| | - Carissa J Cascio
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA.
- Department of Psychiatry, Vanderbilt University, Nashville, TN, USA.
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71
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Foster JJ, Sutterer DW, Serences JT, Vogel EK, Awh E. Alpha-Band Oscillations Enable Spatially and Temporally Resolved Tracking of Covert Spatial Attention. Psychol Sci 2017; 28:929-941. [PMID: 28537480 DOI: 10.1177/0956797617699167] [Citation(s) in RCA: 103] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Covert spatial attention is essential for humans' ability to direct limited processing resources to the relevant aspects of visual scenes. A growing body of evidence suggests that rhythmic neural activity in the alpha frequency band (8-12 Hz) tracks the spatial locus of covert attention, which suggests that alpha activity is integral to spatial attention. However, extant work has not provided a compelling test of another key prediction: that alpha activity tracks the temporal dynamics of covert spatial orienting. In the current study, we examined the time course of spatially specific alpha activity after central cues and during visual search. Critically, the time course of this activity tracked trial-by-trial variations in orienting latency during visual search. These findings provide important new evidence for the link between rhythmic brain activity and covert spatial attention, and they highlight a powerful approach for tracking the spatial and temporal dynamics of this core cognitive process.
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Affiliation(s)
- Joshua J Foster
- 1 Department of Psychology, University of Chicago.,2 Institute for Mind and Biology, University of Chicago
| | - David W Sutterer
- 1 Department of Psychology, University of Chicago.,2 Institute for Mind and Biology, University of Chicago
| | - John T Serences
- 3 Department of Psychology, University of California, San Diego.,4 Neurosciences Graduate Program, University of California, San Diego
| | - Edward K Vogel
- 1 Department of Psychology, University of Chicago.,2 Institute for Mind and Biology, University of Chicago
| | - Edward Awh
- 1 Department of Psychology, University of Chicago.,2 Institute for Mind and Biology, University of Chicago
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72
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Multivariate EEG analyses support high-resolution tracking of feature-based attentional selection. Sci Rep 2017; 7:1886. [PMID: 28507285 PMCID: PMC5432503 DOI: 10.1038/s41598-017-01911-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 04/03/2017] [Indexed: 11/09/2022] Open
Abstract
The primary electrophysiological marker of feature-based selection is the N2pc, a lateralized posterior negativity emerging around 180–200 ms. As it relies on hemispheric differences, its ability to discriminate the locus of focal attention is severely limited. Here we demonstrate that multivariate analyses of raw EEG data provide a much more fine-grained spatial profile of feature-based target selection. When training a pattern classifier to determine target position from EEG, we were able to decode target positions on the vertical midline, which cannot be achieved using standard N2pc methodology. Next, we used a forward encoding model to construct a channel tuning function that describes the continuous relationship between target position and multivariate EEG in an eight-position display. This model can spatially discriminate individual target positions in these displays and is fully invertible, enabling us to construct hypothetical topographic activation maps for target positions that were never used. When tested against the real pattern of neural activity obtained from a different group of subjects, the constructed maps from the forward model turned out statistically indistinguishable, thus providing independent validation of our model. Our findings demonstrate the power of multivariate EEG analysis to track feature-based target selection with high spatial and temporal precision.
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73
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Voytek B, Samaha J, Rolle CE, Greenberg Z, Gill N, Porat S, Kader T, Rahman S, Malzyner R, Gazzaley A. Preparatory Encoding of the Fine Scale of Human Spatial Attention. J Cogn Neurosci 2017; 29:1302-1310. [PMID: 28294717 DOI: 10.1162/jocn_a_01124] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Our attentional focus is constantly shifting: In one moment, our attention may be intently concentrated on a specific spot, whereas in another moment we might spread our attention more broadly. Although much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is known about how we shift the aperture of attention from more narrowly to more broadly focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate-with varying degrees of certainty-approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that, with decreasing certainty regarding the precise location of the impending target, participant RTs increased whereas target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8-12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and RT nearly 1 sec later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution and how that influences behavior.
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Affiliation(s)
- Bradley Voytek
- 1 University of California, San Francisco.,2 University of California, San Diego
| | - Jason Samaha
- 1 University of California, San Francisco.,3 University of Wisconsin-Madison
| | | | | | | | - Shai Porat
- 1 University of California, San Francisco
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74
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Battistoni E, Stein T, Peelen MV. Preparatory attention in visual cortex. Ann N Y Acad Sci 2017; 1396:92-107. [PMID: 28253445 DOI: 10.1111/nyas.13320] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2016] [Revised: 01/16/2017] [Accepted: 01/19/2017] [Indexed: 12/01/2022]
Abstract
Top-down attention is the mechanism that allows us to selectively process goal-relevant aspects of a scene while ignoring irrelevant aspects. A large body of research has characterized the effects of attention on neural activity evoked by a visual stimulus. However, attention also includes a preparatory phase before stimulus onset in which the attended dimension is internally represented. Here, we review neurophysiological, functional magnetic resonance imaging, magnetoencephalography, electroencephalography, and transcranial magnetic stimulation (TMS) studies investigating the neural basis of preparatory attention, both when attention is directed to a location in space and when it is directed to nonspatial stimulus attributes (content-based attention) ranging from low-level features to object categories. Results show that both spatial and content-based attention lead to increased baseline activity in neural populations that selectively code for the attended attribute. TMS studies provide evidence that this preparatory activity is causally related to subsequent attentional selection and behavioral performance. Attention thus acts by preactivating selective neurons in the visual cortex before stimulus onset. This appears to be a general mechanism that can operate on multiple levels of representation. We discuss the functional relevance of this mechanism, its limitations, and its relation to working memory, imagery, and expectation. We conclude by outlining open questions and future directions.
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Affiliation(s)
- Elisa Battistoni
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Timo Stein
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy.,Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Marius V Peelen
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
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75
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Samaha J, Iemi L, Postle BR. Prestimulus alpha-band power biases visual discrimination confidence, but not accuracy. Conscious Cogn 2017; 54:47-55. [PMID: 28222937 DOI: 10.1016/j.concog.2017.02.005] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 01/30/2017] [Accepted: 02/06/2017] [Indexed: 10/20/2022]
Abstract
The magnitude of power in the alpha-band (8-13Hz) of the electroencephalogram (EEG) prior to the onset of a near threshold visual stimulus predicts performance. Together with other findings, this has been interpreted as evidence that alpha-band dynamics reflect cortical excitability. We reasoned, however, that non-specific changes in excitability would be expected to influence signal and noise in the same way, leaving actual discriminability unchanged. Indeed, using a two-choice orientation discrimination task, we found that discrimination accuracy was unaffected by fluctuations in prestimulus alpha power. Decision confidence, on the other hand, was strongly negatively correlated with prestimulus alpha power. This finding constitutes a clear dissociation between objective and subjective measures of visual perception as a function of prestimulus cortical excitability. This dissociation is predicted by a model where the balance of evidence supporting each choice drives objective performance but only the magnitude of evidence supporting the selected choice drives subjective reports, suggesting that human perceptual confidence can be suboptimal with respect to tracking objective accuracy.
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Affiliation(s)
- Jason Samaha
- Department of Psychology, The University of Wisconsin-Madison, Madison, WI, USA.
| | - Luca Iemi
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Germany
| | - Bradley R Postle
- Department of Psychology, The University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, The University of Wisconsin-Madison, Madison, WI, USA
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76
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Distinct Oscillatory Frequencies Underlie Excitability of Human Occipital and Parietal Cortex. J Neurosci 2017; 37:2824-2833. [PMID: 28179556 DOI: 10.1523/jneurosci.3413-16.2017] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Revised: 01/26/2017] [Accepted: 01/31/2017] [Indexed: 01/01/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) of human occipital and posterior parietal cortex can give rise to visual sensations called phosphenes. We used near-threshold TMS with concurrent EEG recordings to measure how oscillatory brain dynamics covary, on single trials, with the perception of phosphenes after occipital and parietal TMS. Prestimulus power and phase, predominantly in the alpha band (8-13 Hz), predicted occipital TMS phosphenes, whereas higher-frequency beta-band (13-20 Hz) power (but not phase) predicted parietal TMS phosphenes. TMS-evoked responses related to phosphene perception were similar across stimulation sites and were characterized by an early (200 ms) posterior negativity and a later (>300 ms) parietal positivity in the time domain and an increase in low-frequency (∼5-7 Hz) power followed by a broadband decrease in alpha/beta power in the time-frequency domain. These correlates of phosphene perception closely resemble known electrophysiological correlates of conscious perception of near-threshold visual stimuli. The regionally differential pattern of prestimulus predictors of phosphene perception suggests that distinct frequencies may reflect cortical excitability in occipital versus posterior parietal cortex, calling into question the broader assumption that the alpha rhythm may serve as a general index of cortical excitability.SIGNIFICANCE STATEMENT Alpha-band oscillations are thought to reflect cortical excitability and are therefore ascribed an important role in gating information transmission across cortex. We probed cortical excitability directly in human occipital and parietal cortex and observed that, whereas alpha-band dynamics indeed reflect excitability of occipital areas, beta-band activity was most predictive of parietal cortex excitability. Differences in the state of cortical excitability predicted perceptual outcomes (phosphenes), which were manifest in both early and late patterns of evoked activity, revealing the time course of phosphene perception. Our findings prompt revision of the notion that alpha activity reflects excitability across all of cortex and suggest instead that excitability in different regions is reflected in distinct frequency bands.
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77
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Bullock T, Elliott JC, Serences JT, Giesbrecht B. Acute Exercise Modulates Feature-selective Responses in Human Cortex. J Cogn Neurosci 2016; 29:605-618. [PMID: 27897672 DOI: 10.1162/jocn_a_01082] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
An organism's current behavioral state influences ongoing brain activity. Nonhuman mammalian and invertebrate brains exhibit large increases in the gain of feature-selective neural responses in sensory cortex during locomotion, suggesting that the visual system becomes more sensitive when actively exploring the environment. This raises the possibility that human vision is also more sensitive during active movement. To investigate this possibility, we used an inverted encoding model technique to estimate feature-selective neural response profiles from EEG data acquired from participants performing an orientation discrimination task. Participants (n = 18) fixated at the center of a flickering (15 Hz) circular grating presented at one of nine different orientations and monitored for a brief shift in orientation that occurred on every trial. Participants completed the task while seated on a stationary exercise bike at rest and during low- and high-intensity cycling. We found evidence for inverted-U effects; such that the peak of the reconstructed feature-selective tuning profiles was highest during low-intensity exercise compared with those estimated during rest and high-intensity exercise. When modeled, these effects were driven by changes in the gain of the tuning curve and in the profile bandwidth during low-intensity exercise relative to rest. Thus, despite profound differences in visual pathways across species, these data show that sensitivity in human visual cortex is also enhanced during locomotive behavior. Our results reveal the nature of exercise-induced gain on feature-selective coding in human sensory cortex and provide valuable evidence linking the neural mechanisms of behavior state across species.
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78
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Iscan Z, Nazarova M, Fedele T, Blagovechtchenski E, Nikulin VV. Pre-stimulus Alpha Oscillations and Inter-subject Variability of Motor Evoked Potentials in Single- and Paired-Pulse TMS Paradigms. Front Hum Neurosci 2016; 10:504. [PMID: 27774060 PMCID: PMC5054042 DOI: 10.3389/fnhum.2016.00504] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 09/26/2016] [Indexed: 12/17/2022] Open
Abstract
Inter- and intra-subject variability of the motor evoked potentials (MEPs) to TMS is a well-known phenomenon. Although a possible link between this variability and ongoing brain oscillations was demonstrated, the results of the studies are not consistent with each other. Exploring this topic further is important since the modulation of MEPs provides unique possibility to relate oscillatory cortical phenomena to the state of the motor cortex probed with TMS. Given that alpha oscillations were shown to reflect cortical excitability, we hypothesized that their power and variability might explain the modulation of subject-specific MEPs to single- and paired-pulse TMS (spTMS, ppTMS, respectively). Neuronal activity was recorded with multichannel electroencephalogram. We used spTMS and two ppTMS conditions: intracortical facilitation (ICF) and short-interval intracortical inhibition (SICI). Spearman correlations were calculated within and across subjects between MEPs and the pre-stimulus power of alpha oscillations in low (8-10 Hz) and high (10-12 Hz) frequency bands. Coefficient of quartile variation was used to measure variability. Across-subject analysis revealed no difference in the pre-stimulus alpha power among the TMS conditions. However, the variability of high-alpha power in spTMS condition was larger than in the SICI condition. In ICF condition pre-stimulus high-alpha power variability correlated positively with MEP amplitude variability. No correlation has been observed between the pre-stimulus alpha power and MEP responses in any of the conditions. Our results show that the variability of the alpha oscillations can be more predictive of TMS effects than the commonly used power of oscillations and we provide further support for the dissociation of high and low-alpha bands in predicting responses produced by the stimulation of the motor cortex.
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Affiliation(s)
- Zafer Iscan
- Centre for Cognition and Decision Making, National Research University Higher School of Economics Moscow, Russia
| | - Maria Nazarova
- Centre for Cognition and Decision Making, National Research University Higher School of EconomicsMoscow, Russia; Research Center of NeurologyMoscow, Russia
| | - Tommaso Fedele
- Centre for Cognition and Decision Making, National Research University Higher School of EconomicsMoscow, Russia; Department of Neurosurgery, University Hospital of Zurich, University of ZurichZurich, Switzerland
| | - Evgeny Blagovechtchenski
- Centre for Cognition and Decision Making, National Research University Higher School of EconomicsMoscow, Russia; Laboratory of Neuroscience and Molecular Pharmacology, Institute of Translational Biomedicine, Saint Petersburg State UniversitySaint Petersburg, Russia
| | - Vadim V Nikulin
- Centre for Cognition and Decision Making, National Research University Higher School of EconomicsMoscow, Russia; Neurophysics Group, Department of Neurology, Charité - University Medicine BerlinBerlin, Germany
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79
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Emrich SM, Johnson JS, Sutterer DW, Postle BR. Comparing the Effects of 10-Hz Repetitive TMS on Tasks of Visual STM and Attention. J Cogn Neurosci 2016; 29:286-297. [PMID: 27626224 DOI: 10.1162/jocn_a_01043] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Numerous studies have demonstrated that visual STM (VSTM) and attention are tightly linked processes that share a number of neuroanatomical substrates. Here, we used repetitive TMS (rTMS) along with simultaneous EEG to examine the causal relationship between intraparietal sulcus functioning and performance on tasks of attention and VSTM. Participants performed two tasks in which they were required to attend to or remember colored items over a brief interval, with 10-Hz rTMS applied on some of the trials. Although no overall behavioral changes were observed across either task, rTMS did affect individual performance on both the attention and VSTM tasks in a manner that was predicted by individual differences in baseline performance. Furthermore, rTMS also affected ongoing oscillations in the alpha and beta bands, and these changes were related to the observed change in behavioral performance. The results reveal a causal relationship between intraparietal sulcus activity and tasks measuring both visual attention and VSTM.
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