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Harel A, Shriki O. Task-guided attention increases non-linearity of steady-state visually evoked potentials. J Neural Eng 2024; 21:056031. [PMID: 39326449 DOI: 10.1088/1741-2552/ad8032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 09/26/2024] [Indexed: 09/28/2024]
Abstract
Objective.Attention is a multifaceted cognitive process, with nonlinear dynamics playing a crucial role. We investigated the involvement of nonlinear processes in top-down visual attention.Approach.The research paradigm employed a contrast-modulated sequence of letters and numerals, encircled by a consistently flickering white square on a black background-a setup that generated steady-state visually evoked potentials. Nonlinear processes are recognized for eliciting and modulating the harmonics of constant frequencies. Using the rhythmic entrainment source separation technique, we examined the fundamental and harmonic frequencies of each stimulus to evaluate the underlying nonlinear dynamics during stimulus processing.Main results.In line with prior research, our findings indicate that the power spectrum density of electroencephalogram responses is influenced by both task presence and stimulus contrast. We discovered that actively searching for a target within a letter stream heightened the amplitude of the fundamental frequency and harmonics related to the background flickering stimulus. While the fundamental frequency amplitude remained unaffected by the stimulus contrast, a lower contrast led to an increase in the second harmonic's amplitude. We assessed the relationship between the contrast response function and the nonlinear-based harmonic responses.Significance.Our findings contribute to a more nuanced understanding of the nonlinear processes impacting top-down visual attention.
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Affiliation(s)
- Asaf Harel
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Oren Shriki
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Zhang J, Zhou H, Wang S. Distinct visual processing networks for foveal and peripheral visual fields. Commun Biol 2024; 7:1259. [PMID: 39367101 PMCID: PMC11452663 DOI: 10.1038/s42003-024-06980-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Accepted: 09/27/2024] [Indexed: 10/06/2024] Open
Abstract
Foveal and peripheral vision are two distinct modes of visual processing essential for navigating the world. However, it remains unclear if they engage different neural mechanisms and circuits within the visual attentional system. Here, we trained macaques to perform a free-gaze visual search task using natural face and object stimuli and recorded a large number of 14588 visually responsive units from a broadly distributed network of brain regions involved in visual attentional processing. Foveal and peripheral units had substantially different proportions across brain regions and exhibited systematic differences in encoding visual information and visual attention. The spike-local field potential (LFP) coherence of foveal units was more extensively modulated by both attention and visual selectivity, thus indicating differential engagement of the attention and visual coding network compared to peripheral units. Furthermore, we delineated the interaction and coordination between foveal and peripheral processing for spatial attention and saccade selection. Together, the systematic differences between foveal and peripheral processing provide valuable insights into how the brain processes and integrates visual information from different regions of the visual field.
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Affiliation(s)
- Jie Zhang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
- Peng Cheng Laboratory, Shenzhen, 518000, China.
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Huihui Zhou
- Peng Cheng Laboratory, Shenzhen, 518000, China.
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Shuo Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
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Zhang J, Zhou H, Wang S. Distinct visual processing networks for foveal and peripheral visual fields. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.24.600415. [PMID: 38979165 PMCID: PMC11230199 DOI: 10.1101/2024.06.24.600415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Foveal and peripheral vision are two distinct modes of visual processing essential for navigating the world. However, it remains unclear if they engage different neural mechanisms and circuits within the visual attentional system. Here, we trained macaques to perform a free-gaze visual search task using natural face and object stimuli and recorded a large number of 14588 visually responsive neurons from a broadly distributed network of brain regions involved in visual attentional processing. Foveal and peripheral units had substantially different proportions across brain regions and exhibited systematic differences in encoding visual information and visual attention. The spike-LFP coherence of foveal units was more extensively modulated by both attention and visual selectivity, thus indicating differential engagement of the attention and visual coding network compared to peripheral units. Furthermore, we delineated the interaction and coordination between foveal and peripheral processing for spatial attention and saccade selection. Finally, the search became more efficient with increasing target-induced desynchronization, and foveal and peripheral units exhibited different correlations between neural responses and search behavior. Together, the systematic differences between foveal and peripheral processing provide valuable insights into how the brain processes and integrates visual information from different regions of the visual field. Significance Statement This study investigates the systematic differences between foveal and peripheral vision, two crucial components of visual processing essential for navigating our surroundings. By simultaneously recording from a large number of neurons in the visual attentional neural network, we revealed substantial variations in the proportion and functional characteristics of foveal and peripheral units across different brain regions. We uncovered differential modulation of functional connectivity by attention and visual selectivity, elucidated the intricate interplay between foveal and peripheral processing in spatial attention and saccade selection, and linked neural responses to search behavior. Overall, our study contributes to a deeper understanding of how the brain processes and integrates visual information for active visual behaviors.
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Zehra SR, Mu J, Burkitt AN, Grayden DB. Effect of alpha range activity on SSVEP decoding in brain-computer interfaces. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083637 DOI: 10.1109/embc40787.2023.10340956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Brain-computer interfaces (BCIs) facilitate direct communication between the brain and external devices. For BCI technology to be commercialized for wide scale applications, BCIs should be accurate, efficient, and exhibit consistency in performance for a wide variety of users. A core challenge is the physiological and anatomical differences amongst people, which causes a high variability amongst participants in BCI studies. Hence, it becomes necessary to analyze the mechanisms causing this variability and address them by improving the decoding algorithms. In this paper, a publicly available steady-state visual evoked potential (SSVEP) dataset is analyzed to study the effect of SSVEP flicker on the endogenous alpha power and the subsequent overall effect on the classification accuracy of the participants. It was observed that the participants with classification accuracy below 95% showed increased alpha power in their brain activities. Incorrect prediction in the decoding algorithm was observed a maximum number of times when the predicted frequency was in the range 9-12 Hz. We conclude that frequencies between 9-12 Hz may result in below par performance in some participants when canonical correlation analysis is used for classification.Clinical relevance-If alpha-band frequencies are used for SSVEP stimulation, alpha power interference in EEG may alter BCI accuracy for some users.
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Neuropsychological and Neurophysiological Mechanisms behind Flickering Light Stimulus Processing. BIOLOGY 2022; 11:biology11121720. [PMID: 36552230 PMCID: PMC9774938 DOI: 10.3390/biology11121720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022]
Abstract
The aim of this review is to summarise current knowledge about flickering light and the underlying processes that occur during its processing in the brain. Despite the growing interest in the topic of flickering light, its clinical applications are still not well understood. Studies using EEG indicate an appearing synchronisation of brain wave frequencies with the frequency of flickering light, and hopefully, it could be used in memory therapy, among other applications. Some researchers have focused on using the flicker test as an indicator of arousal, which may be useful in clinical studies if the background for such a relationship is described. Since flicker testing has a risk of inducing epileptic seizures, however, every effort must be made to avoid high-risk combinations, which include, for example, red-blue light flashing at 15 Hz. Future research should focus on the usage of neuroimaging methods to describe the specific neuropsychological and neurophysiological processes occurring in the brain during the processing of flickering light so that its clinical utility can be preliminarily determined and randomised clinical trials can be initiated to test existing reports.
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Nicholls VI, Wiener JM, Meso AI, Miellet S. The Relative Contribution of Executive Functions and Aging on Attentional Control During Road Crossing. Front Psychol 2022; 13:912446. [PMID: 35645940 PMCID: PMC9133663 DOI: 10.3389/fpsyg.2022.912446] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
As we age, many physical, perceptual and cognitive abilities decline, which can critically impact our day-to-day lives. However, the decline of many abilities is concurrent; thus, it is challenging to disentangle the relative contributions of different abilities in the performance deterioration in realistic tasks, such as road crossing, with age. Research into road crossing has shown that aging and a decline in executive functioning (EFs) is associated with altered information sampling and less safe crossing decisions compared to younger adults. However, in these studies declines in age and EFs were confounded. Therefore, it is impossible to disentangle whether age-related declines in EFs impact on visual sampling and road-crossing performance, or whether visual exploration, and road-crossing performance, are impacted by aging independently of a decline in EFs. In this study, we recruited older adults with maintained EFs to isolate the impacts of aging independently of a decline EFs on road crossing abilities. We recorded eye movements of younger adults and older adults while they watched videos of road traffic and were asked to decide when they could cross the road. Overall, our results show that older adults with maintained EFs sample visual information and make similar road crossing decisions to younger adults. Our findings also reveal that both environmental constraints and EF abilities interact with aging to influence how the road-crossing task is performed. Our findings suggest that older pedestrians' safety, and independence in day-to-day life, can be improved through a limitation of scene complexity and a preservation of EF abilities.
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Affiliation(s)
- Victoria I Nicholls
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom.,Ageing and Dementia Research Centre, Bournemouth University, Poole, United Kingdom
| | - Jan M Wiener
- Ageing and Dementia Research Centre, Bournemouth University, Poole, United Kingdom
| | - Andrew Isaac Meso
- Neuroimaging Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Sebastien Miellet
- School of Psychology, University of Wollongong, Wollongong, NSW, Australia
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Han C, Xu G, Zheng X, Tian P, Zhang K, Yan W, Jia Y, Chen X. Assessing the Effect of the Refresh Rate of a Device on Various Motion Stimulation Frequencies Based on Steady-State Motion Visual Evoked Potentials. Front Neurosci 2022; 15:757679. [PMID: 35069096 PMCID: PMC8777290 DOI: 10.3389/fnins.2021.757679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 12/15/2021] [Indexed: 12/03/2022] Open
Abstract
The refresh rate is one of the important parameters of visual presentation devices, and assessing the effect of the refresh rate of a device on motion perception has always been an important direction in the field of visual research. This study examined the effect of the refresh rate of a device on the motion perception response at different stimulation frequencies and provided an objective visual electrophysiological assessment method for the correct selection of display parameters in a visual perception experiment. In this study, a flicker-free steady-state motion visual stimulation with continuous scanning frequency and different forms (sinusoidal or triangular) was presented on a low-latency LCD monitor at different refresh rates. Seventeen participants were asked to observe the visual stimulation without head movement or eye movement, and the effect of the refresh rate was assessed by analyzing the changes in the intensity of their visual evoked potentials. The results demonstrated that an increased refresh rate significantly improved the intensity of motion visual evoked potentials at stimulation frequency ranges of 7-28 Hz, and there was a significant interaction between the refresh rate and motion frequency. Furthermore, the increased refresh rate also had the potential to enhance the ability to perceive similar motion. Therefore, we recommended using a refresh rate of at least 120 Hz in motion visual perception experiments to ensure a better stimulation effect. If the motion frequency or velocity is high, a refresh rate of≥240 Hz is also recommended.
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Affiliation(s)
- Chengcheng Han
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Guanghua Xu
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
- State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Xiaowei Zheng
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Peiyuan Tian
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Kai Zhang
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Wenqiang Yan
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
- State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Yaguang Jia
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Xiaobi Chen
- School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
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