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Phillips WA, Bachmann T, Spratling MW, Muckli L, Petro LS, Zolnik T. Cellular psychology: relating cognition to context-sensitive pyramidal cells. Trends Cogn Sci 2024:S1364-6613(24)00224-9. [PMID: 39353837 DOI: 10.1016/j.tics.2024.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 09/05/2024] [Accepted: 09/06/2024] [Indexed: 10/04/2024]
Abstract
'Cellular psychology' is a new field of inquiry that studies dendritic mechanisms for adapting mental events to the current context, thus increasing their coherence, flexibility, effectiveness, and comprehensibility. Apical dendrites of neocortical pyramidal cells have a crucial role in cognition - those dendrites receive input from diverse sources, including feedback, and can amplify the cell's feedforward transmission if relevant in that context. Specialized subsets of inhibitory interneurons regulate this cooperative context-sensitive processing by increasing or decreasing amplification. Apical input has different effects on cellular output depending on whether we are awake, deeply asleep, or dreaming. Furthermore, wakeful thought and imagery may depend on apical input. High-resolution neuroimaging in humans supports and complements evidence on these cellular mechanisms from other mammals.
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Affiliation(s)
- William A Phillips
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, UK.
| | - Talis Bachmann
- Institute of Psychology, University of Tartu, Tartu, Estonia.
| | - Michael W Spratling
- Department of Behavioral and Cognitive Sciences, University of Luxembourg, L-4366 Esch-Belval, Luxembourg
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QB, UK; Imaging Centre of Excellence, College of Medical, Veterinary and Life Sciences, University of Glasgow and Queen Elizabeth University Hospital, Glasgow, UK
| | - Lucy S Petro
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QB, UK; Imaging Centre of Excellence, College of Medical, Veterinary and Life Sciences, University of Glasgow and Queen Elizabeth University Hospital, Glasgow, UK
| | - Timothy Zolnik
- Department of Biochemistry, Charité Universitätsmedizin Berlin, Berlin 10117, Germany; Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
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2
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Papale P, Wang F, Morgan AT, Chen X, Gilhuis A, Petro LS, Muckli L, Roelfsema PR, Self MW. The representation of occluded image regions in area V1 of monkeys and humans. Curr Biol 2023; 33:3865-3871.e3. [PMID: 37643620 DOI: 10.1016/j.cub.2023.08.010] [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: 04/25/2023] [Revised: 07/04/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023]
Abstract
Neuronal activity in the primary visual cortex (V1) is driven by feedforward input from within the neurons' receptive fields (RFs) and modulated by contextual information in regions surrounding the RF. The effect of contextual information on spiking activity occurs rapidly and is therefore challenging to dissociate from feedforward input. To address this challenge, we recorded the spiking activity of V1 neurons in monkeys viewing either natural scenes or scenes where the information in the RF was occluded, effectively removing the feedforward input. We found that V1 neurons responded rapidly and selectively to occluded scenes. V1 responses elicited by occluded stimuli could be used to decode individual scenes and could be predicted from those elicited by non-occluded images, indicating that there is an overlap between visually driven and contextual responses. We used representational similarity analysis to show that the structure of V1 representations of occluded scenes measured with electrophysiology in monkeys correlates strongly with the representations of the same scenes in humans measured with functional magnetic resonance imaging (fMRI). Our results reveal that contextual influences rapidly alter V1 spiking activity in monkeys over distances of several degrees in the visual field, carry information about individual scenes, and resemble those in human V1. VIDEO ABSTRACT.
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Affiliation(s)
- Paolo Papale
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands.
| | - Feng Wang
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands
| | - A Tyler Morgan
- Centre for Cognitive NeuroImaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK; Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Xing Chen
- Department of Ophthalmology, University of Pittsburgh School of Medicine, 203 Lothrop St, Pittsburgh, PA 15213, USA
| | - Amparo Gilhuis
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands
| | - Lucy S Petro
- Centre for Cognitive NeuroImaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK; Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Lars Muckli
- Centre for Cognitive NeuroImaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK; Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Pieter R Roelfsema
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academic Medical Centre, Postbus 22660, 1100 DD Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, 75012 Paris, France.
| | - Matthew W Self
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands
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3
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Petro LS, Smith FW, Abbatecola C, Muckli L. The Spatial Precision of Contextual Feedback Signals in Human V1. BIOLOGY 2023; 12:1022. [PMID: 37508451 PMCID: PMC10376409 DOI: 10.3390/biology12071022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/23/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023]
Abstract
Neurons in the primary visual cortex (V1) receive sensory inputs that describe small, local regions of the visual scene and cortical feedback inputs from higher visual areas processing the global scene context. Investigating the spatial precision of this visual contextual modulation will contribute to our understanding of the functional role of cortical feedback inputs in perceptual computations. We used human functional magnetic resonance imaging (fMRI) to test the spatial precision of contextual feedback inputs to V1 during natural scene processing. We measured brain activity patterns in the stimulated regions of V1 and in regions that we blocked from direct feedforward input, receiving information only from non-feedforward (i.e., feedback and lateral) inputs. We measured the spatial precision of contextual feedback signals by generalising brain activity patterns across parametrically spatially displaced versions of identical images using an MVPA cross-classification approach. We found that fMRI activity patterns in cortical feedback signals predicted our scene-specific features in V1 with a precision of approximately 4 degrees. The stimulated regions of V1 carried more precise scene information than non-stimulated regions; however, these regions also contained information patterns that generalised up to 4 degrees. This result shows that contextual signals relating to the global scene are similarly fed back to V1 when feedforward inputs are either present or absent. Our results are in line with contextual feedback signals from extrastriate areas to V1, describing global scene information and contributing to perceptual computations such as the hierarchical representation of feature boundaries within natural scenes.
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Affiliation(s)
- Lucy S Petro
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QB, UK
- Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Fraser W Smith
- School of Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - Clement Abbatecola
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QB, UK
- Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QB, UK
- Imaging Centre for Excellence (ICE), College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G51 4LB, UK
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4
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Combined influence of medication and symptom severity on visual processing in bipolar disorder. J Psychiatr Res 2022; 147:135-141. [PMID: 35032946 DOI: 10.1016/j.jpsychires.2022.01.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 12/18/2021] [Accepted: 01/03/2022] [Indexed: 12/16/2022]
Abstract
Previous studies have reported visual impairments in patients with bipolar disorder (BPD), but unclear were whether clinical variables would be associated with those disturbances. Here, we investigate the relationship between visual functioning, in terms of color discrimination, and the impact of BPD duration, mood state, and the patients' medication. Forty-five participants (25-45 years old) were recruited for this study. Color discrimination was performed using the Cambridge Colour Test. Serial multiple mediations were run to investigate the assumption of association between color discrimination and the clinical variables. Our findings showed that, compared with healthy controls, BPD patients' performance was worse for the Protan, Deutan, and Tritan vectors, revealing deterioration of color discrimination. In addition, the mediation analyses revealed a strong direct (p < .001) and moderate-to-high indirect effects (p < .01) of medication and symptom severity on color discrimination. Overall, both longer the duration of the disease and greater the symptom severity of BPD patients resulted in worse performance. It highlights the importance of examining the wider clinical context of an affective disorder to understand how it affects visual processing in this population.
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5
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van Kemenade BM, Wilbertz G, Müller A, Sterzer P. Non-stimulated regions in early visual cortex encode the contents of conscious visual perception. Hum Brain Mapp 2021; 43:1394-1402. [PMID: 34862702 PMCID: PMC8837582 DOI: 10.1002/hbm.25731] [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: 06/15/2021] [Revised: 11/07/2021] [Accepted: 11/08/2021] [Indexed: 11/11/2022] Open
Abstract
Predictions shape our perception. The theory of predictive processing poses that our brains make sense of incoming sensory input by generating predictions, which are sent back from higher to lower levels of the processing hierarchy. These predictions are based on our internal model of the world and enable inferences about the hidden causes of the sensory input data. It has been proposed that conscious perception corresponds to the currently most probable internal model of the world. Accordingly, predictions influencing conscious perception should be fed back from higher to lower levels of the processing hierarchy. Here, we used functional magnetic resonance imaging and multivoxel pattern analysis to show that non‐stimulated regions of early visual areas contain information about the conscious perception of an ambiguous visual stimulus. These results indicate that early sensory cortices in the human brain receive predictive feedback signals that reflect the current contents of conscious perception.
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Affiliation(s)
- Bianca M van Kemenade
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.,Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.,Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - Gregor Wilbertz
- Department of Psychology, Freie Universität Berlin, Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - Annalena Müller
- Department of Experimental and Biological Psychology, University of Potsdam, Potsdam, Germany.,Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - Philipp Sterzer
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
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6
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Li MS, Abbatecola C, Petro LS, Muckli L. Numerosity Perception in Peripheral Vision. Front Hum Neurosci 2021; 15:750417. [PMID: 34803635 PMCID: PMC8597708 DOI: 10.3389/fnhum.2021.750417] [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: 07/30/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022] Open
Abstract
Peripheral vision has different functional priorities for mammals than foveal vision. One of its roles is to monitor the environment while central vision is focused on the current task. Becoming distracted too easily would be counterproductive in this perspective, so the brain should react to behaviourally relevant changes. Gist processing is good for this purpose, and it is therefore not surprising that evidence from both functional brain imaging and behavioural research suggests a tendency to generalize and blend information in the periphery. This may be caused by the balance of perceptual influence in the periphery between bottom-up (i.e., sensory information) and top-down (i.e., prior or contextual information) processing channels. Here, we investigated this interaction behaviourally using a peripheral numerosity discrimination task with top-down and bottom-up manipulations. Participants compared numerosity between the left and right peripheries of a screen. Each periphery was divided into a centre and a surrounding area, only one of which was a task relevant target region. Our top-down task modulation was the instruction which area to attend - centre or surround. We varied the signal strength by altering the stimuli durations i.e., the amount of information presented/processed (as a combined bottom-up and recurrent top-down feedback factor). We found that numerosity perceived in target regions was affected by contextual information in neighbouring (but irrelevant) areas. This effect appeared as soon as stimulus duration allowed the task to be reliably performed and persisted even at the longest duration (1 s). We compared the pattern of results with an ideal-observer model and found a qualitative difference in the way centre and surround areas interacted perceptually in the periphery. When participants reported on the central area, the irrelevant surround would affect the response as a weighted combination - consistent with the idea of a receptive field focused in the target area to which irrelevant surround stimulation leaks in. When participants report on surround, we can best describe the response with a model in which occasionally the attention switches from task relevant surround to task irrelevant centre - consistent with a selection model of two competing streams of information. Overall our results show that the influence of spatial context in the periphery is mandatory but task dependent.
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Affiliation(s)
- Min Susan Li
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
| | - Clement Abbatecola
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
| | - Lucy S Petro
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
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7
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Svanera M, Morgan AT, Petro LS, Muckli L. A self-supervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. J Vis 2021; 21:5. [PMID: 34259828 PMCID: PMC8288063 DOI: 10.1167/jov.21.7.5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 05/14/2021] [Indexed: 11/24/2022] Open
Abstract
The promise of artificial intelligence in understanding biological vision relies on the comparison of computational models with brain data with the goal of capturing functional principles of visual information processing. Convolutional neural networks (CNN) have successfully matched the transformations in hierarchical processing occurring along the brain's feedforward visual pathway, extending into ventral temporal cortex. However, we are still to learn if CNNs can successfully describe feedback processes in early visual cortex. Here, we investigated similarities between human early visual cortex and a CNN with encoder/decoder architecture, trained with self-supervised learning to fill occlusions and reconstruct an unseen image. Using representational similarity analysis (RSA), we compared 3T functional magnetic resonance imaging (fMRI) data from a nonstimulated patch of early visual cortex in human participants viewing partially occluded images, with the different CNN layer activations from the same images. Results show that our self-supervised image-completion network outperforms a classical object-recognition supervised network (VGG16) in terms of similarity to fMRI data. This work provides additional evidence that optimal models of the visual system might come from less feedforward architectures trained with less supervision. We also find that CNN decoder pathway activations are more similar to brain processing compared to encoder activations, suggesting an integration of mid- and low/middle-level features in early visual cortex. Challenging an artificial intelligence model to learn natural image representations via self-supervised learning and comparing them with brain data can help us to constrain our understanding of information processing, such as neuronal predictive coding.
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Affiliation(s)
- Michele Svanera
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, UK
| | - Andrew T Morgan
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, UK
| | - Lucy S Petro
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, UK
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, UK
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8
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Keitel A, Gross J, Kayser C. Shared and modality-specific brain regions that mediate auditory and visual word comprehension. eLife 2020; 9:e56972. [PMID: 32831168 PMCID: PMC7470824 DOI: 10.7554/elife.56972] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 08/18/2020] [Indexed: 12/22/2022] Open
Abstract
Visual speech carried by lip movements is an integral part of communication. Yet, it remains unclear in how far visual and acoustic speech comprehension are mediated by the same brain regions. Using multivariate classification of full-brain MEG data, we first probed where the brain represents acoustically and visually conveyed word identities. We then tested where these sensory-driven representations are predictive of participants' trial-wise comprehension. The comprehension-relevant representations of auditory and visual speech converged only in anterior angular and inferior frontal regions and were spatially dissociated from those representations that best reflected the sensory-driven word identity. These results provide a neural explanation for the behavioural dissociation of acoustic and visual speech comprehension and suggest that cerebral representations encoding word identities may be more modality-specific than often upheld.
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Affiliation(s)
- Anne Keitel
- Psychology, University of DundeeDundeeUnited Kingdom
- Institute of Neuroscience and Psychology, University of GlasgowGlasgowUnited Kingdom
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of GlasgowGlasgowUnited Kingdom
- Institute for Biomagnetism and Biosignalanalysis, University of MünsterMünsterGermany
| | - Christoph Kayser
- Department for Cognitive Neuroscience, Faculty of Biology, Bielefeld UniversityBielefeldGermany
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9
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Zhang X, Sun Y, Liu W, Zhang Z, Wu B. Twin mechanisms: Rapid scene recognition involves both feedforward and feedback processing. Acta Psychol (Amst) 2020; 208:103101. [PMID: 32485339 DOI: 10.1016/j.actpsy.2020.103101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 05/07/2020] [Accepted: 05/20/2020] [Indexed: 11/25/2022] Open
Abstract
The low spatial frequency (LSF) component of visual information rapidly conveyed coarse information for global perception, while the high spatial frequency (HSF) component delivered fine-grained information for detailed analyses. The feedforward theorists deemed that a coarse-to-fine process was sufficient for a rapid scene recognition. Based on the response priming paradigm, the present study aimed to deeply explore how different spatial frequency interacted with each other during rapid scene recognition. The response priming paradigm posited that as long as the prime slide could be rapidly recognized, the prime-target system was behaviorally equivalent to a feedforward system. Adopting broad spatial frequency images, experiment 1 revealed a typical response priming effect. But in experiment 2, when the HSF and the LSF components of the same pictures were separately presented, neither the LSF-to-HSF sequence nor the HSF-to-LSF sequence reproduced the response priming effect. These results demonstrated that LSF or HSF component alone was not sufficient for rapid scene recognition and, further, that the integration of different spatial frequency needed some early feedback loops. These findings supported that the local recurrent processing loops among early visual cortex was involved during rapid scene recognition.
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10
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Gravel N, Renken RJ, Harvey BM, Deco G, Cornelissen FW, Gilson M. Propagation of BOLD Activity Reveals Task-dependent Directed Interactions Across Human Visual Cortex. Cereb Cortex 2020; 30:5899-5914. [PMID: 32577717 DOI: 10.1093/cercor/bhaa165] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 03/13/2020] [Accepted: 05/02/2020] [Indexed: 11/14/2022] Open
Abstract
It has recently been shown that large-scale propagation of blood-oxygen-level-dependent (BOLD) activity is constrained by anatomical connections and reflects transitions between behavioral states. It remains to be seen, however, if the propagation of BOLD activity can also relate to the brain's anatomical structure at a more local scale. Here, we hypothesized that BOLD propagation reflects structured neuronal activity across early visual field maps. To explore this hypothesis, we characterize the propagation of BOLD activity across V1, V2, and V3 using a modeling approach that aims to disentangle the contributions of local activity and directed interactions in shaping BOLD propagation. It does so by estimating the effective connectivity (EC) and the excitability of a noise-diffusion network to reproduce the spatiotemporal covariance structure of the data. We apply our approach to 7T fMRI recordings acquired during resting state (RS) and visual field mapping (VFM). Our results reveal different EC interactions and changes in cortical excitability in RS and VFM, and point to a reconfiguration of feedforward and feedback interactions across the visual system. We conclude that the propagation of BOLD activity has functional relevance, as it reveals directed interactions and changes in cortical excitability in a task-dependent manner.
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Affiliation(s)
- Nicolás Gravel
- Neural Dynamics of Visual Cognition Group, Department of Education and Psychology, Freie University Berlin, 14195 Berlin, Germany.,Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Remco J Renken
- Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.,Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Ben M Harvey
- Experimental Psychology, Helmholtz Institute, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain.,Institució Catalana de la Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany.,School of Psychological Sciences, Monash University, VIC 3800 Melbourne, Australia
| | - Frans W Cornelissen
- Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Matthieu Gilson
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain
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11
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Vizioli L, De Martino F, Petro LS, Kersten D, Ugurbil K, Yacoub E, Muckli L. Multivoxel Pattern of Blood Oxygen Level Dependent Activity can be sensitive to stimulus specific fine scale responses. Sci Rep 2020; 10:7565. [PMID: 32371891 PMCID: PMC7200825 DOI: 10.1038/s41598-020-64044-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 04/08/2020] [Indexed: 12/25/2022] Open
Abstract
At ultra-high field, fMRI voxels can span the sub-millimeter range, allowing the recording of blood oxygenation level dependent (BOLD) responses at the level of fundamental units of neural computation, such as cortical columns and layers. This sub-millimeter resolution, however, is only nominal in nature as a number of factors limit the spatial acuity of functional voxels. Multivoxel Pattern Analysis (MVPA) may provide a means to detect information at finer spatial scales that may otherwise not be visible at the single voxel level due to limitations in sensitivity and specificity. Here, we evaluate the spatial scale of stimuli specific BOLD responses in multivoxel patterns exploited by linear Support Vector Machine, Linear Discriminant Analysis and Naïve Bayesian classifiers across cortical depths in V1. To this end, we artificially misaligned the testing relative to the training portion of the data in increasing spatial steps, then investigated the breakdown of the classifiers’ performances. A one voxel shift led to a significant decrease in decoding accuracy (p < 0.05) across all cortical depths, indicating that stimulus specific responses in a multivoxel pattern of BOLD activity exploited by multivariate decoders can be as precise as the nominal resolution of single voxels (here 0.8 mm isotropic). Our results further indicate that large draining vessels, prominently residing in proximity of the pial surface, do not, in this case, hinder the ability of MVPA to exploit fine scale patterns of BOLD signals. We argue that tailored analytical approaches can help overcoming limitations in high-resolution fMRI and permit studying the mesoscale organization of the human brain with higher sensitivities.
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Affiliation(s)
- Luca Vizioli
- CMRR, University of Minnesota, Minneapolis, MN, United States.
| | - Federico De Martino
- CMRR, University of Minnesota, Minneapolis, MN, United States.,Maastricht University, Maastricht, Netherlands
| | | | - Daniel Kersten
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Kamil Ugurbil
- CMRR, University of Minnesota, Minneapolis, MN, United States
| | - Essa Yacoub
- CMRR, University of Minnesota, Minneapolis, MN, United States
| | - Lars Muckli
- University of Glasgow, Glasgow, United Kingdom
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12
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Walsh KS, McGovern DP, Clark A, O'Connell RG. Evaluating the neurophysiological evidence for predictive processing as a model of perception. Ann N Y Acad Sci 2020; 1464:242-268. [PMID: 32147856 PMCID: PMC7187369 DOI: 10.1111/nyas.14321] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 01/21/2020] [Accepted: 02/03/2020] [Indexed: 12/12/2022]
Abstract
For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.
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Affiliation(s)
- Kevin S. Walsh
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
| | - David P. McGovern
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
- School of PsychologyDublin City UniversityDublinIreland
| | - Andy Clark
- Department of PhilosophyUniversity of SussexBrightonUK
- Department of InformaticsUniversity of SussexBrightonUK
| | - Redmond G. O'Connell
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
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13
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Bogdanova OV, Bogdanov VB, Durand JB, Trotter Y, Cottereau BR. Dynamics of the straight-ahead preference in human visual cortex. Brain Struct Funct 2020; 225:173-186. [PMID: 31792695 PMCID: PMC6957552 DOI: 10.1007/s00429-019-01988-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 11/14/2019] [Indexed: 11/10/2022]
Abstract
The objects located straight-ahead of the body are preferentially processed by the visual system. They are more rapidly detected and evoke stronger BOLD responses in early visual areas than elements that are retinotopically identical but located at eccentric spatial positions. To characterize the dynamics of the underlying neural mechanisms, we recorded in 29 subjects the EEG responses to peripheral targets differing solely by their locations with respect to the body. Straight-ahead stimuli led to stronger responses than eccentric stimuli for several components whose latencies ranged between 70 and 350 ms after stimulus onset. The earliest effects were found at 70 ms for a component that originates from occipital areas, the contralateral P1. To determine whether the straight-ahead direction affects primary visual cortex responses, we performed an additional experiment (n = 29) specifically designed to generate two robust components, the C1 and C2, whose cortical origins are constrained within areas V1, V2 and V3. Our analyses confirmed all the results of the first experiment and also revealed that the C2 amplitude between 130 and 160 ms after stimulus onset was significantly stronger for straight-ahead stimuli. A frequency analysis of the pre-stimulus baseline revealed that gaze-driven alterations in the visual hemi-field containing the straight-ahead direction were associated with a decrease in alpha power in the contralateral hemisphere, suggesting the implication of specific neural modulations before stimulus onset. Altogether, our EEG data demonstrate that preferential responses to the straight-ahead direction can be detected in the visual cortex as early as about 70 ms after stimulus onset.
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Zajzon B, Mahmoudian S, Morrison A, Duarte R. Passing the Message: Representation Transfer in Modular Balanced Networks. Front Comput Neurosci 2019; 13:79. [PMID: 31920605 PMCID: PMC6915101 DOI: 10.3389/fncom.2019.00079] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 10/29/2019] [Indexed: 01/08/2023] Open
Abstract
Neurobiological systems rely on hierarchical and modular architectures to carry out intricate computations using minimal resources. A prerequisite for such systems to operate adequately is the capability to reliably and efficiently transfer information across multiple modules. Here, we study the features enabling a robust transfer of stimulus representations in modular networks of spiking neurons, tuned to operate in a balanced regime. To capitalize on the complex, transient dynamics that such networks exhibit during active processing, we apply reservoir computing principles and probe the systems' computational efficacy with specific tasks. Focusing on the comparison of random feed-forward connectivity and biologically inspired topographic maps, we find that, in a sequential set-up, structured projections between the modules are strictly necessary for information to propagate accurately to deeper modules. Such mappings not only improve computational performance and efficiency, they also reduce response variability, increase robustness against interference effects, and boost memory capacity. We further investigate how information from two separate input streams is integrated and demonstrate that it is more advantageous to perform non-linear computations on the input locally, within a given module, and subsequently transfer the result downstream, rather than transferring intermediate information and performing the computation downstream. Depending on how information is integrated early on in the system, the networks achieve similar task-performance using different strategies, indicating that the dimensionality of the neural responses does not necessarily correlate with nonlinear integration, as predicted by previous studies. These findings highlight a key role of topographic maps in supporting fast, robust, and accurate neural communication over longer distances. Given the prevalence of such structural feature, particularly in the sensory systems, elucidating their functional purpose remains an important challenge toward which this work provides relevant, new insights. At the same time, these results shed new light on important requirements for designing functional hierarchical spiking networks.
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Affiliation(s)
- Barna Zajzon
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Sepehr Mahmoudian
- Department of Data-Driven Analysis of Biological Networks, Campus Institute for Dynamics of Biological Networks, Georg August University Göttingen, Göttingen, Germany
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Abigail Morrison
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
- Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Renato Duarte
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
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Scene Representations Conveyed by Cortical Feedback to Early Visual Cortex Can Be Described by Line Drawings. J Neurosci 2019; 39:9410-9423. [PMID: 31611306 PMCID: PMC6867807 DOI: 10.1523/jneurosci.0852-19.2019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/27/2019] [Accepted: 09/23/2019] [Indexed: 11/25/2022] Open
Abstract
Human behavior is dependent on the ability of neuronal circuits to predict the outside world. Neuronal circuits in early visual areas make these predictions based on internal models that are delivered via non-feedforward connections. Despite our extensive knowledge of the feedforward sensory features that drive cortical neurons, we have a limited grasp on the structure of the brain's internal models. Progress in neuroscience therefore depends on our ability to replicate the models that the brain creates internally. Here we record human fMRI data while presenting partially occluded visual scenes. Visual occlusion allows us to experimentally control sensory input to subregions of visual cortex while internal models continue to influence activity in these regions. Because the observed activity is dependent on internal models, but not on sensory input, we have the opportunity to map visual features conveyed by the brain's internal models. Our results show that activity related to internal models in early visual cortex are more related to scene-specific features than to categorical or depth features. We further demonstrate that behavioral line drawings provide a good description of internal model structure representing scene-specific features. These findings extend our understanding of internal models, showing that line drawings provide a window into our brains' internal models of vision. SIGNIFICANCE STATEMENT We find that fMRI activity patterns corresponding to occluded visual information in early visual cortex fill in scene-specific features. Line drawings of the missing scene information correlate with our recorded activity patterns, and thus to internal models. Despite our extensive knowledge of the sensory features that drive cortical neurons, we have a limited grasp on the structure of our brains' internal models. These results therefore constitute an advance to the field of neuroscience by extending our knowledge about the models that our brains construct to efficiently represent and predict the world. Moreover, they link a behavioral measure to these internal models, which play an active role in many components of human behavior, including visual predictions, action planning, and decision making.
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Towards a Unified View on Pathways and Functions of Neural Recurrent Processing. Trends Neurosci 2019; 42:589-603. [PMID: 31399289 DOI: 10.1016/j.tins.2019.07.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 06/21/2019] [Accepted: 07/11/2019] [Indexed: 11/20/2022]
Abstract
There are three neural feedback pathways to the primary visual cortex (V1): corticocortical, pulvinocortical, and cholinergic. What are the respective functions of these three projections? Possible functions range from contextual modulation of stimulus processing and feedback of high-level information to predictive processing (PP). How are these functions subserved by different pathways and can they be integrated into an overarching theoretical framework? We propose that corticocortical and pulvinocortical connections are involved in all three functions, whereas the role of cholinergic projections is limited by their slow response to stimuli. PP provides a broad explanatory framework under which stimulus-context modulation and high-level processing are subsumed, involving multiple feedback pathways that provide mechanisms for inferring and interpreting what sensory inputs are about.
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Petras K, Ten Oever S, Jacobs C, Goffaux V. Coarse-to-fine information integration in human vision. Neuroimage 2018; 186:103-112. [PMID: 30403971 DOI: 10.1016/j.neuroimage.2018.10.086] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Revised: 10/17/2018] [Accepted: 10/31/2018] [Indexed: 12/23/2022] Open
Abstract
Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in naturalistic broad-band stimuli is still unclear. Here we used multivariate decoding of EEG signals to separate the respective contribution of LSF and HSF to the neural response evoked by broad-band images. Participants viewed images of human faces, monkey faces and phase-scrambled versions that were either broad-band or filtered to contain LSF or HSF. We trained classifiers on EEG scalp-patterns evoked by filtered scrambled stimuli and evaluated the derived models on broad-band scrambled and intact trials. We found reduced HSF contribution when LSF was informative towards image content, indicating that coarse information does guide the processing of fine detail, in line with coarse-to-fine theories. We discuss the potential cortical mechanisms underlying such coarse-to-fine feedback.
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Affiliation(s)
- Kirsten Petras
- Research Institute for Psychological Science, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.
| | - Sanne Ten Oever
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Christianne Jacobs
- Research Institute for Psychological Science, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Valerie Goffaux
- Research Institute for Psychological Science, Université Catholique de Louvain, Louvain-la-Neuve, Belgium; Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands; Institute of Neuroscience, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
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19
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Sharpening of Hierarchical Visual Feature Representations of Blurred Images. eNeuro 2018; 5:eN-NWR-0443-17. [PMID: 29756028 PMCID: PMC5940673 DOI: 10.1523/eneuro.0443-17.2018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 03/29/2018] [Accepted: 04/10/2018] [Indexed: 11/21/2022] Open
Abstract
The robustness of the visual system lies in its ability to perceive degraded images. This is achieved through interacting bottom-up, recurrent, and top-down pathways that process the visual input in concordance with stored prior information. The interaction mechanism by which they integrate visual input and prior information is still enigmatic. We present a new approach using deep neural network (DNN) representation to reveal the effects of such integration on degraded visual inputs. We transformed measured human brain activity resulting from viewing blurred images to the hierarchical representation space derived from a feedforward DNN. Transformed representations were found to veer toward the original nonblurred image and away from the blurred stimulus image. This indicated deblurring or sharpening in the neural representation, and possibly in our perception. We anticipate these results will help unravel the interplay mechanism between bottom-up, recurrent, and top-down pathways, leading to more comprehensive models of vision.
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Petro LS, Muckli L. Forecasting Faces in the Cortex: Comment on 'High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy', by Schwiedrzik and Freiwald, Neuron (2017). Trends Cogn Sci 2017; 22:95-97. [PMID: 29269195 PMCID: PMC5774611 DOI: 10.1016/j.tics.2017.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 11/28/2017] [Accepted: 12/05/2017] [Indexed: 10/31/2022]
Abstract
Although theories of predictive coding in the brain abound, we lack key pieces of neuronal data to support these theories. Recently, Schwiedrzik and Freiwald found neurophysiological evidence for predictive codes throughout the face-processing hierarchy in macaque cortex. We highlight how these data enhance our knowledge of cortical information processing, and the impact of this more broadly.
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Affiliation(s)
- Lucy S Petro
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, College of Medical, Veterinary and Life Sciences, University of Glasgow, 58 Hillhead Street, Glasgow, G12 8QB, UK
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, College of Medical, Veterinary and Life Sciences, University of Glasgow, 58 Hillhead Street, Glasgow, G12 8QB, UK.
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