1
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Ma AC, Cameron AD, Wiener M. Memorability shapes perceived time (and vice versa). Nat Hum Behav 2024; 8:1296-1308. [PMID: 38649460 DOI: 10.1038/s41562-024-01863-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 03/13/2024] [Indexed: 04/25/2024]
Abstract
Visual stimuli are known to vary in their perceived duration. Some visual stimuli are also known to linger for longer in memory. Yet, whether these two features of visual processing are linked is unknown. Despite early assumptions that time is an extracted or higher-order feature of perception, more recent work over the past two decades has demonstrated that timing may be instantiated within sensory modality circuits. A primary location for many of these studies is the visual system, where duration-sensitive responses have been demonstrated. Furthermore, visual stimulus features have been observed to shift perceived duration. These findings suggest that visual circuits mediate or construct perceived time. Here we present evidence across a series of experiments that perceived time is affected by the image properties of scene size, clutter and memorability. More specifically, we observe that scene size and memorability dilate time, whereas clutter contracts it. Furthermore, the durations of more memorable images are also perceived more precisely. Conversely, the longer the perceived duration of an image, the more memorable it is. To explain these findings, we applied a recurrent convolutional neural network model of the ventral visual system, in which images are progressively processed over time. We find that more memorable images are processed faster, and that this increase in processing speed predicts both the lengthening and the increased precision of perceived durations. These findings provide evidence for a link between image features, time perception and memory that can be further explored with models of visual processing.
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Affiliation(s)
- Alex C Ma
- Department of Psychology, George Mason University, Fairfax, VA, USA
| | - Ayana D Cameron
- Department of Psychology, George Mason University, Fairfax, VA, USA
| | - Martin Wiener
- Department of Psychology, George Mason University, Fairfax, VA, USA.
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2
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Aguado-López B, Palenciano AF, Peñalver JMG, Díaz-Gutiérrez P, López-García D, Avancini C, Ciria LF, Ruz M. Proactive selective attention across competition contexts. Cortex 2024; 176:113-128. [PMID: 38772050 DOI: 10.1016/j.cortex.2024.04.009] [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: 02/07/2024] [Revised: 04/03/2024] [Accepted: 04/16/2024] [Indexed: 05/23/2024]
Abstract
Selective attention is a cognitive function that helps filter out unwanted information. Theories such as the biased competition model (Desimone & Duncan, 1995) explain how attentional templates bias processing towards targets in contexts where multiple stimuli compete for resources. However, it is unclear how the anticipation of different levels of competition influences the nature of attentional templates, in a proactive fashion. In this study, we used electroencephalography (EEG) to investigate how the anticipated demands of attentional selection (either high or low stimuli competition contexts) modulate target-specific preparatory brain activity and its relationship with task performance. To do so, participants performed a sex/gender judgment task in a cue-target paradigm where, depending on the block, target and distractor stimuli appeared simultaneously (high competition) or sequentially (low competition). Multivariate Pattern Analysis (MVPA) showed that, in both competition contexts, there was a preactivation of the target category to select, with a ramping-up profile at the end of the preparatory interval. However, cross-classification showed no generalization across competition conditions, suggesting different preparatory formats. Notably, time-frequency analyses showed differences between anticipated competition demands, with higher theta band power for high than low competition, which mediated the impact of subsequent stimuli competition on behavioral performance. Overall, our results show that, whereas preactivation of the internal templates associated with the category to select are engaged in advance in high and low competition contexts, their underlying neural patterns differ. In addition, these codes could not be associated with theta power, suggesting that they reflect different preparatory processes. The implications of these findings are crucial to increase our understanding of the nature of top-down processes across different contexts.
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Affiliation(s)
- Blanca Aguado-López
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain
| | - Ana F Palenciano
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain
| | - José M G Peñalver
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain
| | - Paloma Díaz-Gutiérrez
- Department of Management, Faculty of Business and Economics, University of Antwerp, 2000, Belgium
| | - David López-García
- Data Science & Computational Intelligence Institute, University of Granada, CP 18071, Spain
| | - Chiara Avancini
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain
| | - Luis F Ciria
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain
| | - María Ruz
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada 18071, Spain.
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3
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Faghel-Soubeyrand S, Richoz AR, Waeber D, Woodhams J, Caldara R, Gosselin F, Charest I. Neural computations in prosopagnosia. Cereb Cortex 2024; 34:bhae211. [PMID: 38795358 PMCID: PMC11127037 DOI: 10.1093/cercor/bhae211] [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: 12/27/2022] [Revised: 04/30/2024] [Accepted: 05/03/2024] [Indexed: 05/27/2024] Open
Abstract
We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PS's ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PS's early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PS' brain representations with those of deep neural networks (DNN). We found that the computations underlying PS' brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PS's deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics.
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Affiliation(s)
- Simon Faghel-Soubeyrand
- Département de psychologie, Université de Montréal, 90 av. Vincent D’indy, Montreal, H2V 2S9, Canada
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Woodstock Rd, Oxford OX2 6GG
| | - Anne-Raphaelle Richoz
- Département de psychologie, Université de Fribourg, RM 01 bu. C-3.117Rue P.A. de Faucigny 21700 Fribourg, Switzerland
| | - Delphine Waeber
- Département de psychologie, Université de Fribourg, RM 01 bu. C-3.117Rue P.A. de Faucigny 21700 Fribourg, Switzerland
| | - Jessica Woodhams
- School of Psychology, University of Birmingham, Hills Building, Edgbaston Park Rd, Birmingham B15 2TT, UK
| | - Roberto Caldara
- Département de psychologie, Université de Fribourg, RM 01 bu. C-3.117Rue P.A. de Faucigny 21700 Fribourg, Switzerland
| | - Frédéric Gosselin
- Département de psychologie, Université de Montréal, 90 av. Vincent D’indy, Montreal, H2V 2S9, Canada
| | - Ian Charest
- Département de psychologie, Université de Montréal, 90 av. Vincent D’indy, Montreal, H2V 2S9, Canada
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4
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Qiu Y, Li H, Liao J, Chen K, Wu X, Liu B, Huang R. Forming cognitive maps for abstract spaces: the roles of the human hippocampus and orbitofrontal cortex. Commun Biol 2024; 7:517. [PMID: 38693344 PMCID: PMC11063219 DOI: 10.1038/s42003-024-06214-5] [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: 06/09/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
How does the human brain construct cognitive maps for decision-making and inference? Here, we conduct an fMRI study on a navigation task in multidimensional abstract spaces. Using a deep neural network model, we assess learning levels and categorized paths into exploration and exploitation stages. Univariate analyses show higher activation in the bilateral hippocampus and lateral prefrontal cortex during exploration, positively associated with learning level and response accuracy. Conversely, the bilateral orbitofrontal cortex (OFC) and retrosplenial cortex show higher activation during exploitation, negatively associated with learning level and response accuracy. Representational similarity analysis show that the hippocampus, entorhinal cortex, and OFC more accurately represent destinations in exploitation than exploration stages. These findings highlight the collaboration between the medial temporal lobe and prefrontal cortex in learning abstract space structures. The hippocampus may be involved in spatial memory formation and representation, while the OFC integrates sensory information for decision-making in multidimensional abstract spaces.
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Affiliation(s)
- Yidan Qiu
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China
| | - Huakang Li
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Jiajun Liao
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China
| | - Kemeng Chen
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China
| | - Xiaoyan Wu
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China
| | - Bingyi Liu
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China
| | - Ruiwang Huang
- School of Psychology; Center for the Study of Applied Psychology; Key Laboratory of Mental Health and Cognitive Science of Guangdong Province; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; South China Normal University, Guangzhou, 510631, China.
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5
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Heinen R, Bierbrauer A, Wolf OT, Axmacher N. Representational formats of human memory traces. Brain Struct Funct 2024; 229:513-529. [PMID: 37022435 PMCID: PMC10978732 DOI: 10.1007/s00429-023-02636-9] [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: 12/06/2022] [Accepted: 03/28/2023] [Indexed: 04/07/2023]
Abstract
Neural representations are internal brain states that constitute the brain's model of the external world or some of its features. In the presence of sensory input, a representation may reflect various properties of this input. When perceptual information is no longer available, the brain can still activate representations of previously experienced episodes due to the formation of memory traces. In this review, we aim at characterizing the nature of neural memory representations and how they can be assessed with cognitive neuroscience methods, mainly focusing on neuroimaging. We discuss how multivariate analysis techniques such as representational similarity analysis (RSA) and deep neural networks (DNNs) can be leveraged to gain insights into the structure of neural representations and their different representational formats. We provide several examples of recent studies which demonstrate that we are able to not only measure memory representations using RSA but are also able to investigate their multiple formats using DNNs. We demonstrate that in addition to slow generalization during consolidation, memory representations are subject to semantization already during short-term memory, by revealing a shift from visual to semantic format. In addition to perceptual and conceptual formats, we describe the impact of affective evaluations as an additional dimension of episodic memories. Overall, these studies illustrate how the analysis of neural representations may help us gain a deeper understanding of the nature of human memory.
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Affiliation(s)
- Rebekka Heinen
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany.
| | - Anne Bierbrauer
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
- Institute for Systems Neuroscience, Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Oliver T Wolf
- Department of Cognitive Psychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
| | - Nikolai Axmacher
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
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6
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Faghel-Soubeyrand S, Ramon M, Bamps E, Zoia M, Woodhams J, Richoz AR, Caldara R, Gosselin F, Charest I. Decoding face recognition abilities in the human brain. PNAS NEXUS 2024; 3:pgae095. [PMID: 38516275 PMCID: PMC10957238 DOI: 10.1093/pnasnexus/pgae095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 02/20/2024] [Indexed: 03/23/2024]
Abstract
Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilities-super-recognizers-and typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1 s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain.
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Affiliation(s)
- Simon Faghel-Soubeyrand
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK
- Département de psychologie, Université de Montréal, Montréal, Québec H2V 2S9, Canada
| | - Meike Ramon
- Institute of Psychology, University of Lausanne, Lausanne CH-1015, Switzerland
| | - Eva Bamps
- Center for Contextual Psychiatry, Department of Neurosciences, KU Leuven, Leuven ON5, Belgium
| | - Matteo Zoia
- Department for Biomedical Research, University of Bern, Bern 3008, Switzerland
| | - Jessica Woodhams
- Département de psychologie, Université de Montréal, Montréal, Québec H2V 2S9, Canada
- School of Psychology, University of Birmingham, Hills Building, Edgbaston Park Rd, Birmingham B15 2TT, UK
| | | | - Roberto Caldara
- Département de Psychology, Université de Fribourg, Fribourg CH-1700, Switzerland
| | - Frédéric Gosselin
- Département de psychologie, Université de Montréal, Montréal, Québec H2V 2S9, Canada
| | - Ian Charest
- Département de psychologie, Université de Montréal, Montréal, Québec H2V 2S9, Canada
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7
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Karapetian A, Boyanova A, Pandaram M, Obermayer K, Kietzmann TC, Cichy RM. Empirically Identifying and Computationally Modeling the Brain-Behavior Relationship for Human Scene Categorization. J Cogn Neurosci 2023; 35:1879-1897. [PMID: 37590093 PMCID: PMC10586810 DOI: 10.1162/jocn_a_02043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Humans effortlessly make quick and accurate perceptual decisions about the nature of their immediate visual environment, such as the category of the scene they face. Previous research has revealed a rich set of cortical representations potentially underlying this feat. However, it remains unknown which of these representations are suitably formatted for decision-making. Here, we approached this question empirically and computationally, using neuroimaging and computational modeling. For the empirical part, we collected EEG data and RTs from human participants during a scene categorization task (natural vs. man-made). We then related EEG data to behavior to behavior using a multivariate extension of signal detection theory. We observed a correlation between neural data and behavior specifically between ∼100 msec and ∼200 msec after stimulus onset, suggesting that the neural scene representations in this time period are suitably formatted for decision-making. For the computational part, we evaluated a recurrent convolutional neural network (RCNN) as a model of brain and behavior. Unifying our previous observations in an image-computable model, the RCNN predicted well the neural representations, the behavioral scene categorization data, as well as the relationship between them. Our results identify and computationally characterize the neural and behavioral correlates of scene categorization in humans.
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Affiliation(s)
- Agnessa Karapetian
- Freie Universität Berlin, Germany
- Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Germany
| | | | | | - Klaus Obermayer
- Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Germany
- Technische Universität Berlin, Germany
- Humboldt-Universität zu Berlin, Germany
| | | | - Radoslaw M Cichy
- Freie Universität Berlin, Germany
- Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Germany
- Humboldt-Universität zu Berlin, Germany
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8
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Kay K, Bonnen K, Denison RN, Arcaro MJ, Barack DL. Tasks and their role in visual neuroscience. Neuron 2023; 111:1697-1713. [PMID: 37040765 DOI: 10.1016/j.neuron.2023.03.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 04/13/2023]
Abstract
Vision is widely used as a model system to gain insights into how sensory inputs are processed and interpreted by the brain. Historically, careful quantification and control of visual stimuli have served as the backbone of visual neuroscience. There has been less emphasis, however, on how an observer's task influences the processing of sensory inputs. Motivated by diverse observations of task-dependent activity in the visual system, we propose a framework for thinking about tasks, their role in sensory processing, and how we might formally incorporate tasks into our models of vision.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA.
| | - Kathryn Bonnen
- School of Optometry, Indiana University, Bloomington, IN 47405, USA
| | - Rachel N Denison
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Mike J Arcaro
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19146, USA
| | - David L Barack
- Departments of Neuroscience and Philosophy, University of Pennsylvania, Philadelphia, PA 19146, USA
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9
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Graumann M, Wallenwein LA, Cichy RM. Independent spatiotemporal effects of spatial attention and background clutter on human object location representations. Neuroimage 2023; 272:120053. [PMID: 36966853 PMCID: PMC10112276 DOI: 10.1016/j.neuroimage.2023.120053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 03/21/2023] [Accepted: 03/23/2023] [Indexed: 04/04/2023] Open
Abstract
Spatial attention helps us to efficiently localize objects in cluttered environments. However, the processing stage at which spatial attention modulates object location representations remains unclear. Here we investigated this question identifying processing stages in time and space in an EEG and fMRI experiment respectively. As both object location representations and attentional effects have been shown to depend on the background on which objects appear, we included object background as an experimental factor. During the experiments, human participants viewed images of objects appearing in different locations on blank or cluttered backgrounds while either performing a task on fixation or on the periphery to direct their covert spatial attention away or towards the objects. We used multivariate classification to assess object location information. Consistent across the EEG and fMRI experiment, we show that spatial attention modulated location representations during late processing stages (>150 ms, in middle and high ventral visual stream areas) independent of background condition. Our results clarify the processing stage at which attention modulates object location representations in the ventral visual stream and show that attentional modulation is a cognitive process separate from recurrent processes related to the processing of objects on cluttered backgrounds.
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Affiliation(s)
- Monika Graumann
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany; Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, 10117 Berlin, Germany.
| | - Lara A Wallenwein
- Department of Psychology, Universität Konstanz, 78457 Konstanz, Germany
| | - Radoslaw M Cichy
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany; Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, 10117 Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany
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10
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Xie S, Hoehl S, Moeskops M, Kayhan E, Kliesch C, Turtleton B, Köster M, Cichy RM. Visual category representations in the infant brain. Curr Biol 2022; 32:5422-5432.e6. [PMID: 36455560 PMCID: PMC9796816 DOI: 10.1016/j.cub.2022.11.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 09/22/2022] [Accepted: 11/07/2022] [Indexed: 12/05/2022]
Abstract
Visual categorization is a human core cognitive capacity1,2 that depends on the development of visual category representations in the infant brain.3,4,5,6,7 However, the exact nature of infant visual category representations and their relationship to the corresponding adult form remains unknown.8 Our results clarify the nature of visual category representations from electroencephalography (EEG) data in 6- to 8-month-old infants and their developmental trajectory toward adult maturity in the key characteristics of temporal dynamics,2,9 representational format,10,11,12 and spectral properties.13,14 Temporal dynamics change from slowly emerging, developing representations in infants to quickly emerging, complex representations in adults. Despite those differences, infants and adults already partly share visual category representations. The format of infants' representations is visual features of low to intermediate complexity, whereas adults' representations also encode high-complexity features. Theta band activity contributes to visual category representations in infants, and these representations are shifted to the alpha/beta band in adults. Together, we reveal the developmental neural basis of visual categorization in humans, show how information transmission channels change in development, and demonstrate the power of advanced multivariate analysis techniques in infant EEG research for theory building in developmental cognitive science.
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Affiliation(s)
- Siying Xie
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany,Corresponding author
| | - Stefanie Hoehl
- Faculty of Psychology, Department of Developmental and Educational Psychology, University of Vienna, Liebiggasse, Wien 1010, Austria,Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße, 04103 Leipzig, Germany
| | - Merle Moeskops
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany
| | - Ezgi Kayhan
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße, 04103 Leipzig, Germany,Department of Developmental Psychology, University of Potsdam, Karl-Liebknecht-Straße, 14476 Potsdam, Germany
| | - Christian Kliesch
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße, 04103 Leipzig, Germany,Department of Developmental Psychology, University of Potsdam, Karl-Liebknecht-Straße, 14476 Potsdam, Germany
| | - Bert Turtleton
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany
| | - Moritz Köster
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany,Institute of Psychology, University of Regensburg, Universitätsstraße, 93053 Regensburg, Germany
| | - Radoslaw M. Cichy
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Unter den Linden, 10099 Berlin, Germany,Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, Charitéplatz, 10117 Berlin, Germany,Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Unter den Linden, 10099 Berlin, Germany,Corresponding author
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11
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Ayzenberg V, Behrmann M. Does the brain's ventral visual pathway compute object shape? Trends Cogn Sci 2022; 26:1119-1132. [PMID: 36272937 DOI: 10.1016/j.tics.2022.09.019] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/22/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022]
Abstract
A rich behavioral literature has shown that human object recognition is supported by a representation of shape that is tolerant to variations in an object's appearance. Such 'global' shape representations are achieved by describing objects via the spatial arrangement of their local features, or structure, rather than by the appearance of the features themselves. However, accumulating evidence suggests that the ventral visual pathway - the primary substrate underlying object recognition - may not represent global shape. Instead, ventral representations may be better described as a basis set of local image features. We suggest that this evidence forces a reevaluation of the role of the ventral pathway in object perception and posits a broader network for shape perception that encompasses contributions from the dorsal pathway.
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Affiliation(s)
- Vladislav Ayzenberg
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Psychology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
| | - Marlene Behrmann
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Psychology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; The Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
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12
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Rose D. More on realism, phenomenology, and causation, in reply to Cheng. Perception 2022; 51:853-858. [PMID: 36129072 DOI: 10.1177/03010066221127368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
First, I agree with Cheng that the argument from illusions to indirect realism is controversial, especially as to what is meant by "realism," "veridical," and "sense data" and the background assumptions underlying them. I provide a finer specification of some of the sub-movements that were the specific concerns of my previous article, particularly phenomenology as it currently sees itself in perception research, and the relevance of illusions. Perception has turned out to be far more complex than traditional philosophy realized, as has been revealed by recent research in neuroscience and psychophysics. Lastly, I answer Cheng's question about the "causal exclusion argument" by suggesting it is obviated by the temporal substructure of metaphysical states, and I provide a detailed supporting case in Supplementary Material.
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Affiliation(s)
- David Rose
- School of Psychology, 3660University of Surrey, Guildford, UK
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