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Khadir A, Ghamsari SS, Badri S, Beigzadeh B. Discriminating orientation information with phase consistency in alpha and low-gamma frequency bands: an EEG study. Sci Rep 2024; 14:12007. [PMID: 38796618 PMCID: PMC11127946 DOI: 10.1038/s41598-024-62934-y] [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: 03/30/2023] [Accepted: 05/22/2024] [Indexed: 05/28/2024] Open
Abstract
Recent studies suggest that noninvasive imaging methods (EEG, MEG) in the human brain scalp can decode the content of visual features information (orientation, color, motion, etc.) in Visual-Working Memory (VWM). Previous work demonstrated that with the sustained low-frequency Event-Related Potential (ERP under 6 Hz) of scalp EEG distributions, it is possible to accurately decode the content of orientation information in VWM during the delay interval. In addition, previous studies showed that the raw data captured by a combination of the occi-parietal electrodes could be used to decode the orientation. However, it is unclear whether the orientation information is available in other frequency bands (higher than 6 Hz) or whether this information is feasible with fewer electrodes. Furthermore, the exploration of orientation information in the phase values of the signal has not been well-addressed. In this study, we propose that orientation information is also accessible through the phase consistency of the occipital region in the alpha band frequency. Our results reveal a significant difference between orientations within 200 ms after stimulus offset in early visual sensory processing, with no apparent effect in power and Event-Related Oscillation (ERO) during this period. Additionally, in later periods (420-500 ms after stimulus offset), a noticeable difference is observed in the phase consistency of low gamma-band activity in the occipital area. Importantly, our findings suggest that phase consistency between trials of the orientation feature in the occipital alpha and low gamma-band can serve as a measure to obtain orientation information in VWM. Furthermore, the study demonstrates that phase consistency in the alpha and low gamma band can reflect the distribution of orientation-selective neuron numbers in the four main orientations in the occipital area.
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Affiliation(s)
- Alireza Khadir
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Shamim Sasani Ghamsari
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Samaneh Badri
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Borhan Beigzadeh
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.
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2
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Moyal R, Turker HB, Luh WM, Swallow KM. Auditory Target Detection Enhances Visual Processing and Hippocampal Functional Connectivity. Front Psychol 2022; 13:891682. [PMID: 35769754 PMCID: PMC9234495 DOI: 10.3389/fpsyg.2022.891682] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 05/18/2022] [Indexed: 11/20/2022] Open
Abstract
Though dividing one's attention between two input streams typically impairs performance, detecting a behaviorally relevant stimulus can sometimes enhance the encoding of unrelated information presented at the same time. Previous research has shown that selection of this kind boosts visual cortical activity and memory for concurrent items. An important unanswered question is whether such effects are reflected in processing quality and functional connectivity in visual regions and in the hippocampus. In this fMRI study, participants were asked to memorize a stream of naturalistic images and press a button only when they heard a predefined target tone (400 or 1,200 Hz, counterbalanced). Images could be presented with a target tone, with a distractor tone, or without a tone. Auditory target detection increased activity throughout the ventral visual cortex but lowered it in the hippocampus. Enhancements in functional connectivity between the ventral visual cortex and the hippocampus were also observed following auditory targets. Multi-voxel pattern classification of image category was more accurate on target tone trials than on distractor and no tone trials in the fusiform gyrus and parahippocampal gyrus. This effect was stronger in visual cortical clusters whose activity was more correlated with the hippocampus on target tone than on distractor tone trials. In agreement with accounts suggesting that subcortical noradrenergic influences play a role in the attentional boost effect, auditory target detection also caused an increase in locus coeruleus activity and phasic pupil responses. These findings outline a network of cortical and subcortical regions that are involved in the selection and processing of information presented at behaviorally relevant moments.
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Affiliation(s)
- Roy Moyal
- Cognitive Science Program, Department of Psychology, Cornell University, Ithaca, NY, United States
| | - Hamid B. Turker
- Cognitive Science Program, Department of Psychology, Cornell University, Ithaca, NY, United States
| | - Wen-Ming Luh
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| | - Khena M. Swallow
- Cognitive Science Program, Department of Psychology, Cornell University, Ithaca, NY, United States
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3
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Ribeiro FL, Bollmann S, Puckett AM. Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning. Neuroimage 2021; 244:118624. [PMID: 34607019 DOI: 10.1016/j.neuroimage.2021.118624] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/13/2021] [Accepted: 09/27/2021] [Indexed: 10/20/2022] Open
Abstract
Whether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy with cortical shape having been shown to be a useful predictor of the retinotopic organization in early visual cortex. Although the current state-of-the-art in predicting retinotopic maps is able to account for gross individual differences, such models are unable to account for any idiosyncratic differences in the structure-function relationship from anatomical information alone due to their initial assumption of a template. Here we developed a geometric deep learning model capable of exploiting the actual structure of the cortex to learn the complex relationship between brain function and anatomy in human visual cortex such that more realistic and idiosyncratic maps could be predicted. We show that our neural network was not only able to predict the functional organization throughout the visual cortical hierarchy, but that it was also able to predict nuanced variations across individuals. Although we demonstrate its utility for modeling the relationship between structure and function in human visual cortex, our approach is flexible and well-suited for a range of other applications involving data structured in non-Euclidean spaces.
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Affiliation(s)
- Fernanda L Ribeiro
- School of Psychology, The University of Queensland, Saint Lucia, Brisbane, QLD 4072, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia.
| | - Steffen Bollmann
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Alexander M Puckett
- School of Psychology, The University of Queensland, Saint Lucia, Brisbane, QLD 4072, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
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Lee SH, Kravitz DJ, Baker CI. Differential Representations of Perceived and Retrieved Visual Information in Hippocampus and Cortex. Cereb Cortex 2020; 29:4452-4461. [PMID: 30590463 DOI: 10.1093/cercor/bhy325] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 11/22/2018] [Accepted: 11/28/2018] [Indexed: 12/12/2022] Open
Abstract
Memory retrieval is thought to depend on interactions between hippocampus and cortex, but the nature of representation in these regions and their relationship remains unclear. Here, we performed an ultra-high field fMRI (7T) experiment, comprising perception, learning and retrieval sessions. We observed a fundamental difference between representations in hippocampus and high-level visual cortex during perception and retrieval. First, while object-selective posterior fusiform cortex showed consistent responses that allowed us to decode object identity across both perception and retrieval one day after learning, object decoding in hippocampus was much stronger during retrieval than perception. Second, in visual cortex but not hippocampus, there was consistency in response patterns between perception and retrieval, suggesting that substantial neural populations are shared for both perception and retrieval. Finally, the decoding in hippocampus during retrieval was not observed when retrieval was tested on the same day as learning suggesting that the retrieval process itself is not sufficient to elicit decodable object representations. Collectively, these findings suggest that while cortical representations are stable between perception and retrieval, hippocampal representations are much stronger during retrieval, implying some form of reorganization of the representations between perception and retrieval.
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Affiliation(s)
- Sue-Hyun Lee
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.,Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.,Program of Brain and Cognitive Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Dwight J Kravitz
- Department of Psychology, The George Washington University, Washington, DC, USA
| | - Chris I Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
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Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches. Neural Plast 2019; 2019:2724101. [PMID: 31814821 PMCID: PMC6877932 DOI: 10.1155/2019/2724101] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 08/05/2019] [Indexed: 12/30/2022] Open
Abstract
Unsolved questions in computational visual neuroscience research are whether and how neurons and their connecting cortical networks can adapt when normal vision is compromised by a neurodevelopmental disorder or damage to the visual system. This question on neuroplasticity is particularly relevant in the context of rehabilitation therapies that attempt to overcome limitations or damage, through either perceptual training or retinal and cortical implants. Studies on cortical neuroplasticity have generally made the assumption that neuronal population properties and the resulting visual field maps are stable in healthy observers. Consequently, differences in the estimates of these properties between patients and healthy observers have been taken as a straightforward indication for neuroplasticity. However, recent studies imply that the modeled neuronal properties and the cortical visual maps vary substantially within healthy participants, e.g., in response to specific stimuli or under the influence of cognitive factors such as attention. Although notable advances have been made to improve the reliability of stimulus-driven approaches, the reliance on the visual input remains a challenge for the interpretability of the obtained results. Therefore, we argue that there is an important role in the study of cortical neuroplasticity for approaches that assess intracortical signal processing and circuitry models that can link visual cortex anatomy, function, and dynamics.
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Lawrence SJD, Norris DG, de Lange FP. Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex. eLife 2019; 8:e44422. [PMID: 31063127 PMCID: PMC6538372 DOI: 10.7554/elife.44422] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 05/03/2019] [Indexed: 12/22/2022] Open
Abstract
Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer and weaker in deep and superficial layers, while top-down modulations were strongest in the superficial layers. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.
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Affiliation(s)
- Samuel JD Lawrence
- Donders Institute for Brain, Cognition and BehaviourRadboud University NijmegenNijmegenNetherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and BehaviourRadboud University NijmegenNijmegenNetherlands
- Erwin L. Hahn Institute for Magnetic Resonance ImagingUniversity Duisburg-EssenEssenGermany
| | - Floris P de Lange
- Donders Institute for Brain, Cognition and BehaviourRadboud University NijmegenNijmegenNetherlands
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Cardoso MMB, Lima B, Sirotin YB, Das A. Task-related hemodynamic responses are modulated by reward and task engagement. PLoS Biol 2019; 17:e3000080. [PMID: 31002659 PMCID: PMC6493772 DOI: 10.1371/journal.pbio.3000080] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 05/01/2019] [Accepted: 03/29/2019] [Indexed: 01/18/2023] Open
Abstract
Hemodynamic recordings from visual cortex contain powerful endogenous task-related responses that may reflect task-related arousal, or "task engagement" distinct from attention. We tested this hypothesis with hemodynamic measurements (intrinsic-signal optical imaging) from monkey primary visual cortex (V1) while the animals' engagement in a periodic fixation task over several hours was varied through reward size and as animals took breaks. With higher rewards, animals appeared more task-engaged; task-related responses were more temporally precise at the task period (approximately 10-20 seconds) and modestly stronger. The 2-5 minute blocks of high-reward trials led to ramp-like decreases in mean local blood volume; these reversed with ramp-like increases during low reward. The blood volume increased even more sharply when the animal shut his eyes and disengaged completely from the task (5-10 minutes). We propose a mechanism that controls vascular tone, likely along with local neural responses in a manner that reflects task engagement over the full range of timescales tested.
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Affiliation(s)
- Mariana M. B. Cardoso
- Department of Neuroscience, Columbia University, New York, New York, United States of America
- Center for Neural Science, New York University, New York, New York, United States of America
| | - Bruss Lima
- Department of Neuroscience, Columbia University, New York, New York, United States of America
- Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Yevgeniy B. Sirotin
- Department of Neuroscience, Columbia University, New York, New York, United States of America
- Identity and Data Science Laboratory of Science Applications International Corporation, Annapolis Junction, Maryland, United States of America
| | - Aniruddha Das
- Department of Neuroscience, Columbia University, New York, New York, United States of America
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, New York, United States of America
- * E-mail:
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Lawrence SJD, van Mourik T, Kok P, Koopmans PJ, Norris DG, de Lange FP. Laminar Organization of Working Memory Signals in Human Visual Cortex. Curr Biol 2018; 28:3435-3440.e4. [PMID: 30344121 DOI: 10.1016/j.cub.2018.08.043] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 08/07/2018] [Accepted: 08/20/2018] [Indexed: 12/19/2022]
Abstract
The human primary visual cortex (V1) is not only activated by incoming visual information but is also engaged by top-down cognitive processes, such as visual working memory, even in the absence of visual input [1-3]. This feedback may be critical to our ability to visualize specific visual features, as higher-order regions lack the selectivity to represent such information [4]. Clearly, such internally generated signals do not trigger genuine perception of the remembered stimulus, meaning they must be organized in a manner that is different to bottom-up-driven signals. Internally generated signals may be kept separate from incoming sensory data by virtue of the laminar organization of inter-area cortical connections. Namely, bottom-up driving connections target layer 4, located in the middle of the cortical column, and feedback connections target deep and superficial layers and avoid layer 4 [5-7]. Using lamina-resolved fMRI, we simultaneously measured the activity in three early visual cortical areas (V1-V3) that are recruited to represent stimulus information during visual working memory [8]. We observed item-specific working memory signals in early visual cortex. In V1, this item-specific activity was selectively present at deep and superficial cortical depths, avoiding the middle layers, and working-memory-related activity was present at all depths in V2 and V3. These results show for the first time the laminar organization of internally generated signals during visual working memory in the human visual system and provide new insights into how bottom-up and top-down signals in visual cortex are deployed.
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Affiliation(s)
- Samuel J D Lawrence
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands
| | - Tim van Mourik
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands
| | - Peter Kok
- Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Peter J Koopmans
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands; Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | - Floris P de Lange
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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