1
|
Li B, Zhang S. Registered Report Stage II: Decoding the category information from evoked potentials to visible and invisible visual objects. Int J Psychophysiol 2024; 205:112446. [PMID: 39389167 DOI: 10.1016/j.ijpsycho.2024.112446] [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: 07/15/2024] [Revised: 09/18/2024] [Accepted: 10/07/2024] [Indexed: 10/12/2024]
Abstract
Previous studies that use decoding methods and EEG to investigate the neural representation of the category information of visual objects focused mainly on consciously processed visual objects. It remains unclear whether the category information of unconsciously processed visual objects can be decoded and whether the decoding performance is different for consciously and unconsciously processed visual objects. The present study compared the neural decoding of the animacy category of visible and invisible visual objects via EEG and decoding methods. The results revealed that the animacy of visible visual objects could be decoded above the chance level by the P200, N300, and N400, but not by the early N/P100. However, the animacy of invisible visual objects could not be decoded above the chance level by neither early nor late ERP components. The decoding accuracy was greater for visible visual objects than that for invisible visual objects for the P200, N300 and N400. These results suggested that access to animacy category information for visual objects requires conscious processing.
Collapse
Affiliation(s)
- Bingbing Li
- School of Education Science, Jiangsu Normal University, Xuzhou, Jiangsu, China.
| | - Shuhui Zhang
- School of Education Science, Jiangsu Normal University, Xuzhou, Jiangsu, China.
| |
Collapse
|
2
|
Coraci D, Douven I, Cevolani G. Inference to the best neuroscientific explanation. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE 2024; 107:33-42. [PMID: 39128362 DOI: 10.1016/j.shpsa.2024.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 05/30/2024] [Accepted: 06/25/2024] [Indexed: 08/13/2024]
Abstract
Neuroscientists routinely use reverse inference (RI) to draw conclusions about cognitive processes from neural activation data. However, despite its widespread use, the methodological status of RI is a matter of ongoing controversy, with some critics arguing that it should be rejected wholesale on the grounds that it instantiates a deductively invalid argument form. In response to these critiques, some have proposed to conceive of RI as a form of abduction or inference to the best explanation (IBE). We side with this response but at the same time argue that a defense of RI requires more than identifying it as a form of IBE. In this paper, we give an analysis of what determines the quality of an RI conceived as an IBE and on that basis argue that whether an RI is warranted needs to be decided on a case-by-case basis. Support for our argument will come from a detailed methodological discussion of RI in cognitive neuroscience in light of what the recent literature on IBE has identified as the main quality indicators for IBEs.
Collapse
Affiliation(s)
| | - Igor Douven
- CNRS/Panthéon-Sorbonne University, IHPST, France.
| | | |
Collapse
|
3
|
Vigotsky AD, Iannetti GD, Apkarian AV. Mental state decoders: game-changers or wishful thinking? Trends Cogn Sci 2024; 28:884-895. [PMID: 38991876 DOI: 10.1016/j.tics.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 07/13/2024]
Abstract
Decoding mental and perceptual states using fMRI has become increasingly popular over the past two decades, with numerous highly-cited studies published in high-profile journals. Nevertheless, what have we learned from these decoders? In this opinion, we argue that fMRI-based decoders are not neurophysiologically informative and are not, and likely cannot be, applicable to real-world decision-making. The former point stems from the fact that decoding models cannot disentangle neural mechanisms from their epiphenomena. The latter point stems from both logical and ethical constraints. Constructing decoders requires precious time and resources that should instead be directed toward scientific endeavors more likely to yield meaningful scientific progress.
Collapse
Affiliation(s)
| | - Gian Domenico Iannetti
- Italian Institute of Technology (IIT), Rome, Italy; University College London (UCL), London, UK
| | | |
Collapse
|
4
|
Bretton ZH, Kim H, Banich MT, Lewis-Peacock JA. Suppressing the Maintenance of Information in Working Memory Alters Long-term Memory Traces. J Cogn Neurosci 2024; 36:2117-2136. [PMID: 38940738 PMCID: PMC11383534 DOI: 10.1162/jocn_a_02206] [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: 06/29/2024]
Abstract
The sensory recruitment hypothesis conceptualizes information in working memory as being activated representations of information in long-term memory. Accordingly, changes made to an item in working memory would be expected to influence its subsequent retention. Here, we tested the hypothesis that suppressing information from working memory, which can reduce short-term access to that information, may also alter its long-term neural representation. We obtained fMRI data (n = 25; 13 female / 12 male participants) while participants completed a working memory removal task with scene images as stimuli, followed by a final surprise recognition test of the examined items. We applied a multivariate pattern analysis to the data to quantify the engagement of suppression on each trial, to track the contents of working memory during suppression, and to assess representational changes afterward. Our analysis confirms previous reports that suppression of information in working memory involves focused attention to target and remove unwanted information. Furthermore, our findings provide new evidence that even a single dose of suppression of an item in working memory can (if engaged with sufficient strength) produce lasting changes in its neural representation, particularly weakening the unique, item-specific features, which leads to forgetting. Our study sheds light on the underlying mechanisms that contribute to the suppression of unwanted thoughts and highlights the dynamic interplay between working memory and long-term memory.
Collapse
Affiliation(s)
| | - Hyojeong Kim
- University of Texas at Austin
- University of Colorado
| | | | | |
Collapse
|
5
|
Knyazev GG, Savostyanov AN, Bocharov AV, Rudych PD, Saprigyn AE. Multivariate pattern analysis of cooperation and competition in constructive action. Neuropsychologia 2024; 202:108956. [PMID: 39002772 DOI: 10.1016/j.neuropsychologia.2024.108956] [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: 07/11/2023] [Revised: 06/22/2024] [Accepted: 07/10/2024] [Indexed: 07/15/2024]
Abstract
The neural underpinning of cooperative and competitive constructive activity has been investigated using mass-univariate approaches. In this study, we sought to compare the results of these approaches with the results of multivariate pattern analysis (MVPA). In particular, we wanted to test whether MVPA supports the claim made in previous studies that cooperation is associated with the activity of reward-related brain circuits. Participants were required to construct a pattern on the screen either individually or in cooperation or competition with another person during an fMRI scan. Both the MVPA classification methods and the representational similarity analysis indicated the involvement of orbitofrontal and ventromedial prefrontal areas in processes that distinguish between cooperation and competition, and activation analysis showed that these areas are more active during cooperation than during competition. However, a single trial analysis showed that the effect was reversed when only winning trials were considered. In these trials, activation of reward-related areas was higher during competition than during cooperation. Moreover, the contrast between won and lost trials in terms of reward circuits involvement was sharper under competition than under cooperation. Thus, although cooperation can be generally more rewarding than competition, it is associated with smaller difference between trials lost and trials won in terms of reward circuits activation. One may speculate that in cooperation, victory and defeat are shared with the partner and, contrary to competition, are not experienced as personal achievement or failure.
Collapse
Affiliation(s)
- G G Knyazev
- Institute of Neurosciences and Medicine, Novosibirsk, Russia.
| | - A N Savostyanov
- Institute of Neurosciences and Medicine, Novosibirsk, Russia; Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
| | - A V Bocharov
- Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - P D Rudych
- Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - A E Saprigyn
- Institute of Neurosciences and Medicine, Novosibirsk, Russia
| |
Collapse
|
6
|
Karthik G, Cao CZ, Demidenko MI, Jahn A, Stacey WC, Wasade VS, Brang D. Auditory cortex encodes lipreading information through spatially distributed activity. Curr Biol 2024; 34:4021-4032.e5. [PMID: 39153482 PMCID: PMC11387126 DOI: 10.1016/j.cub.2024.07.073] [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: 01/03/2024] [Revised: 04/29/2024] [Accepted: 07/19/2024] [Indexed: 08/19/2024]
Abstract
Watching a speaker's face improves speech perception accuracy. This benefit is enabled, in part, by implicit lipreading abilities present in the general population. While it is established that lipreading can alter the perception of a heard word, it is unknown how these visual signals are represented in the auditory system or how they interact with auditory speech representations. One influential, but untested, hypothesis is that visual speech modulates the population-coded representations of phonetic and phonemic features in the auditory system. This model is largely supported by data showing that silent lipreading evokes activity in the auditory cortex, but these activations could alternatively reflect general effects of arousal or attention or the encoding of non-linguistic features such as visual timing information. This gap limits our understanding of how vision supports speech perception. To test the hypothesis that the auditory system encodes visual speech information, we acquired functional magnetic resonance imaging (fMRI) data from healthy adults and intracranial recordings from electrodes implanted in patients with epilepsy during auditory and visual speech perception tasks. Across both datasets, linear classifiers successfully decoded the identity of silently lipread words using the spatial pattern of auditory cortex responses. Examining the time course of classification using intracranial recordings, lipread words were classified at earlier time points relative to heard words, suggesting a predictive mechanism for facilitating speech. These results support a model in which the auditory system combines the joint neural distributions evoked by heard and lipread words to generate a more precise estimate of what was said.
Collapse
Affiliation(s)
- Ganesan Karthik
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Cody Zhewei Cao
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Andrew Jahn
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - William C Stacey
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Vibhangini S Wasade
- Henry Ford Hospital, Detroit, MI 48202, USA; Department of Neurology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - David Brang
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA.
| |
Collapse
|
7
|
Marsicano G, Bertini C, Ronconi L. Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data. Neurosci Biobehav Rev 2024; 164:105795. [PMID: 38977116 DOI: 10.1016/j.neubiorev.2024.105795] [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: 04/30/2024] [Revised: 06/21/2024] [Accepted: 07/03/2024] [Indexed: 07/10/2024]
Abstract
Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.
Collapse
Affiliation(s)
- Gianluca Marsicano
- Department of Psychology, University of Bologna, Viale Berti Pichat 5, Bologna 40121, Italy; Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Via Rasi e Spinelli 176, Cesena 47023, Italy.
| | - Caterina Bertini
- Department of Psychology, University of Bologna, Viale Berti Pichat 5, Bologna 40121, Italy; Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Via Rasi e Spinelli 176, Cesena 47023, Italy.
| | - Luca Ronconi
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
| |
Collapse
|
8
|
Feilong M, Jiahui G, Gobbini MI, Haxby JV. A cortical surface template for human neuroscience. Nat Methods 2024; 21:1736-1742. [PMID: 39014074 PMCID: PMC11399089 DOI: 10.1038/s41592-024-02346-y] [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] [Received: 04/12/2023] [Accepted: 06/06/2024] [Indexed: 07/18/2024]
Abstract
Neuroimaging data analysis relies on normalization to standard anatomical templates to resolve macroanatomical differences across brains. Existing human cortical surface templates sample locations unevenly because of distortions introduced by inflation of the folded cortex into a standard shape. Here we present the onavg template, which affords uniform sampling of the cortex. We created the onavg template based on openly available high-quality structural scans of 1,031 brains-25 times more than existing cortical templates. We optimized the vertex locations based on cortical anatomy, achieving an even distribution. We observed consistently higher multivariate pattern classification accuracies and representational geometry inter-participant correlations based on onavg than on other templates, and onavg only needs three-quarters as much data to achieve the same performance compared with other templates. The optimized sampling also reduces CPU time across algorithms by 1.3-22.4% due to less variation in the number of vertices in each searchlight.
Collapse
Affiliation(s)
- Ma Feilong
- Center for Cognitive Neuroscience, Dartmouth College, Hanover, NH, USA.
| | - Guo Jiahui
- Center for Cognitive Neuroscience, Dartmouth College, Hanover, NH, USA
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
| | - Maria Ida Gobbini
- Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - James V Haxby
- Center for Cognitive Neuroscience, Dartmouth College, Hanover, NH, USA.
| |
Collapse
|
9
|
Duecker K, Idiart M, van Gerven M, Jensen O. Oscillations in an artificial neural network convert competing inputs into a temporal code. PLoS Comput Biol 2024; 20:e1012429. [PMID: 39259769 PMCID: PMC11419396 DOI: 10.1371/journal.pcbi.1012429] [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] [Received: 04/22/2024] [Revised: 09/23/2024] [Accepted: 08/17/2024] [Indexed: 09/13/2024] Open
Abstract
The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems.
Collapse
Affiliation(s)
- Katharina Duecker
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America
| | - Marco Idiart
- Institute of Physics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Marcel van Gerven
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Ole Jensen
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| |
Collapse
|
10
|
Farahani FV, Nebel MB, Wager TD, Lindquist MA. Effects of connectivity hyperalignment (CHA) on estimated brain network properties: from coarse-scale to fine-scale. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.27.609817. [PMID: 39253413 PMCID: PMC11383013 DOI: 10.1101/2024.08.27.609817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Recent gains in functional magnetic resonance imaging (fMRI) studies have been driven by increasingly sophisticated statistical and computational techniques and the ability to capture brain data at finer spatial and temporal resolution. These advances allow researchers to develop population-level models of the functional brain representations underlying behavior, performance, clinical status, and prognosis. However, even following conventional preprocessing pipelines, considerable inter-individual disparities in functional localization persist, posing a hurdle to performing compelling population-level inference. Persistent misalignment in functional topography after registration and spatial normalization will reduce power in developing predictive models and biomarkers, reduce the specificity of estimated brain responses and patterns, and provide misleading results on local neural representations and individual differences. This study aims to determine how connectivity hyperalignment (CHA)-an analytic approach for handling functional misalignment-can change estimated functional brain network topologies at various spatial scales from the coarsest set of parcels down to the vertex-level scale. The findings highlight the role of CHA in improving inter-subject similarities, while retaining individual-specific information and idiosyncrasies at finer spatial granularities. This highlights the potential for fine-grained connectivity analysis using this approach to reveal previously unexplored facets of brain structure and function.
Collapse
Affiliation(s)
- Farzad V Farahani
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Martin A Lindquist
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|
11
|
Varlet M, Grootswagers T. Measuring information alignment in hyperscanning research with representational analyses: moving beyond interbrain synchrony. Front Hum Neurosci 2024; 18:1385624. [PMID: 39118818 PMCID: PMC11306121 DOI: 10.3389/fnhum.2024.1385624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/16/2024] [Indexed: 08/10/2024] Open
Abstract
Hyperscanning, which enables the recording of brain activity from multiple individuals simultaneously, has been increasingly used to investigate the neuropsychological processes underpinning social interaction. Previous hyperscanning research has primarily focused on interbrain synchrony, demonstrating an enhanced alignment of brain waves across individuals during social interaction. However, using EEG hyperscanning simulations, we here show that interbrain synchrony has low sensitivity to information alignment across people. Surprisingly, interbrain synchrony remains largely unchanged despite manipulating whether two individuals are seeing same or different things at the same time. Furthermore, we show that hyperscanning recordings do contain indices of interpersonal information alignment and that they can be captured using representational analyses. These findings highlight major limitations of current hyperscanning research and offer a promising alternative for investigating interactive minds.
Collapse
Affiliation(s)
- Manuel Varlet
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, NSW, Australia
- School of Psychology, Western Sydney University, Sydney, NSW, Australia
| | - Tijl Grootswagers
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, NSW, Australia
- School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, NSW, Australia
| |
Collapse
|
12
|
Zhang W, Chen X, Wang S. The representation of noun-verb distinction in left posterior middle temporal gyrus: evidence from representation similarity analyses. Cereb Cortex 2024; 34:bhae242. [PMID: 39030743 DOI: 10.1093/cercor/bhae242] [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: 03/18/2024] [Revised: 05/14/2024] [Accepted: 05/23/2024] [Indexed: 07/22/2024] Open
Abstract
Nouns and verbs are fundamental grammatical building blocks of languages. A key question is whether and where the noun-verb division was represented in the brain. Previous studies mainly used univariate analyses to examine this issue. However, the interpretation of activated brain regions in univariate analyses may be confounded with general cognitive processing and/or confounding variables. We addressed these limitations by using partial representation similarity analysis (RSA) of Chinese nouns and verbs with different levels of imageability. Participants were asked to complete the 1-back grammatical class probe (GCP; an explicit measure) and the 1-back word probe (WP; an implicit measure) tasks while undergoing functional magnetic resonance imaging. RSA results showed that the activation pattern in the left posterior middle temporal gyrus (LpMTG) was significantly correlated with the grammatical class representational dissimilarity matrix in the GCP task after eliminating the potential confounding variables. Moreover, the LpMTG did not overlap with the frontal-parietal regions that were activated by verbs vs. nouns or the task effect (CRP vs. WP) in univariate analyses. These results highlight the role of LpMTG in distinguishing nouns from verbs rather than general cognitive processing.
Collapse
Affiliation(s)
- Wenjia Zhang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Zhongshan Avenue 55, Guangzhou, Guangdong 510631, China
- School of Psychology, South China Normal University, Zhongshan Avenue 55, Guangzhou, Guangdong 510631, China
- Key Laboratory for Artificial Intelligence and Cognitive Neuroscience of Language, Xi'an International Studies University, South Wenyuan Road 6, Xi'an, Shaanxi 710128, China
| | - Xuemei Chen
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Zhongshan Avenue 55, Guangzhou, Guangdong 510631, China
- School of Psychology, South China Normal University, Zhongshan Avenue 55, Guangzhou, Guangdong 510631, China
| | - Suiping Wang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Zhongshan Avenue 55, Guangzhou, Guangdong 510631, China
| |
Collapse
|
13
|
Teng Y, Li HX, Chen SX, Castellanos FX, Yan CG, Hu X. Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking. Neuroimage 2024; 294:120627. [PMID: 38723877 DOI: 10.1016/j.neuroimage.2024.120627] [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: 12/12/2023] [Revised: 04/07/2024] [Accepted: 04/24/2024] [Indexed: 05/18/2024] Open
Abstract
Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.
Collapse
Affiliation(s)
- Yue Teng
- Department of Psychology, Renmin University of China, Beijing 100872, China; Laboratory of the Department of Psychology, Renmin University of China, Beijing 100872, China; Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, 100872 China
| | - Hui-Xian Li
- The Third Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
| | - Sylvia Xiaohua Chen
- Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, USA; Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaomeng Hu
- Department of Psychology, Renmin University of China, Beijing 100872, China; Laboratory of the Department of Psychology, Renmin University of China, Beijing 100872, China; Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, 100872 China,.
| |
Collapse
|
14
|
Wang J, Lapate RC. Emotional state dynamics impacts temporal memory. Cogn Emot 2024:1-20. [PMID: 38898587 DOI: 10.1080/02699931.2024.2349326] [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: 02/14/2023] [Accepted: 02/13/2024] [Indexed: 06/21/2024]
Abstract
Emotional fluctuations are ubiquitous in everyday life, but precisely how they sculpt the temporal organisation of memories remains unclear. Here, we designed a novel task - the Emotion Boundary Task - wherein participants viewed sequences of negative and neutral images surrounded by a colour border. We manipulated perceptual context (border colour), emotional-picture valence, as well as the direction of emotional-valence shifts (i.e., shifts from neutral-to-negative and negative-to-neutral events) to create events with a shared perceptual and/or emotional context. We measured memory for temporal order and temporal distances for images processed within and across events. Negative images processed within events were remembered as closer in time compared to neutral ones. In contrast, temporal distances were remembered as longer for images spanning neutral-to-negative shifts - suggesting temporal dilation in memory with the onset of a negative event following a previously-neutral state. The extent of negative-picture induced temporal dilation in memory correlated with dispositional negativity across individuals. Lastly, temporal order memory was enhanced for recently-presented negative (versus neutral) images. These findings suggest that emotional-state dynamics matters when considering emotion-temporal memory interactions: While persistent negative events may compress subjectively remembered time, dynamic shifts from neutral-to-negative events produce temporal dilation in memory, with implications for adaptive emotional functioning.
Collapse
Affiliation(s)
- Jingyi Wang
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Regina C Lapate
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, USA
| |
Collapse
|
15
|
Bavard S, Stuchlý E, Konovalov A, Gluth S. Humans can infer social preferences from decision speed alone. PLoS Biol 2024; 22:e3002686. [PMID: 38900903 PMCID: PMC11189591 DOI: 10.1371/journal.pbio.3002686] [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] [Received: 12/01/2023] [Accepted: 05/21/2024] [Indexed: 06/22/2024] Open
Abstract
Humans are known to be capable of inferring hidden preferences and beliefs of their conspecifics when observing their decisions. While observational learning based on choices has been explored extensively, the question of how response times (RT) impact our learning of others' social preferences has received little attention. Yet, while observing choices alone can inform us about the direction of preference, they reveal little about the strength of this preference. In contrast, RT provides a continuous measure of strength of preference with faster responses indicating stronger preferences and slower responses signaling hesitation or uncertainty. Here, we outline a preregistered orthogonal design to investigate the involvement of both choices and RT in learning and inferring other's social preferences. Participants observed other people's behavior in a social preferences task (Dictator Game), seeing either their choices, RT, both, or no information. By coupling behavioral analyses with computational modeling, we show that RT is predictive of social preferences and that observers were able to infer those preferences even when receiving only RT information. Based on these findings, we propose a novel observational reinforcement learning model that closely matches participants' inferences in all relevant conditions. In contrast to previous literature suggesting that, from a Bayesian perspective, people should be able to learn equally well from choices and RT, we show that observers' behavior substantially deviates from this prediction. Our study elucidates a hitherto unknown sophistication in human observational learning but also identifies important limitations to this ability.
Collapse
Affiliation(s)
- Sophie Bavard
- Department of Psychology, University of Hamburg, Hamburg, Germany
| | - Erik Stuchlý
- Department of Psychology, University of Hamburg, Hamburg, Germany
| | - Arkady Konovalov
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Sebastian Gluth
- Department of Psychology, University of Hamburg, Hamburg, Germany
| |
Collapse
|
16
|
Chen Y, Xu J, Wu J, Chen H, Kang Y, Yang Y, Gong Z, Huang Y, Wang H, Wang B, Zhan S, Tan W. Aberrant concordance among dynamics of spontaneous brain activity in patients with migraine without aura: A multivariate pattern analysis study. Heliyon 2024; 10:e30008. [PMID: 38737279 PMCID: PMC11088259 DOI: 10.1016/j.heliyon.2024.e30008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 04/08/2024] [Accepted: 04/18/2024] [Indexed: 05/14/2024] Open
Abstract
Background Alterations in the static and dynamic characteristics of spontaneous brain activity have been extensively studied to investigate functional brain changes in migraine without aura (MwoA). However, alterations in concordance among the dynamics of spontaneous brain activity in MwoA remain largely unknown. This study aimed to determine the possibilities of diagnosis based on the concordance indices. Methods Resting-state functional MRI scans were performed on 32 patients with MwoA and 33 matched healthy controls (HCs) in the first cohort, as well as 36 patients with MwoA and 32 HCs in the validation cohort. The dynamic indices including fractional amplitude of low-frequency fluctuation, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity were analyzed. We calculated the concordance of grey matter volume-wise (across voxels) and voxel-wise (across time windows) to quantify the degree of integration among different functional levels represented by these dynamic indices. Subsequently, the voxel-wise concordance alterations were analyzed as features for multi-voxel pattern analysis (MVPA) utilizing the support vector machine. Results Compared with that of HCs, patients with MwoA had lower whole-grey matter volume-wise concordance, and the mean value of volume-wise concordance was negatively correlated with the frequency of migraine attacks. The MVPA results revealed that the most discriminative brain regions were the right thalamus, right cerebellar Crus II, left insula, left precentral gyrus, right cuneus, and left inferior occipital gyrus. Conclusions Concordance alterations in the dynamics of spontaneous brain activity in brain regions could be an important feature in the identification of patients with MwoA.
Collapse
Affiliation(s)
- Yilei Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jun Xu
- Pharmacy Department, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jiazhen Wu
- Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hui Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yingjie Kang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yuchan Yang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhigang Gong
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yanwen Huang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hui Wang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bo Wang
- Department of Acupuncture and Moxibustion, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Songhua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wenli Tan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| |
Collapse
|
17
|
Turk-Browne NB, Aslin RN. Infant neuroscience: how to measure brain activity in the youngest minds. Trends Neurosci 2024; 47:338-354. [PMID: 38570212 DOI: 10.1016/j.tins.2024.02.003] [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: 06/30/2023] [Revised: 01/08/2024] [Accepted: 02/09/2024] [Indexed: 04/05/2024]
Abstract
The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.
Collapse
Affiliation(s)
- Nicholas B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Wu Tsai Institute, Yale University, New Haven, CT 06510, USA.
| | - Richard N Aslin
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| |
Collapse
|
18
|
Park Y, Zhang Y, Schwartz F, Iuculano T, Chang H, Menon V. Integrated number sense tutoring remediates aberrant neural representations in children with mathematical disabilities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.09.587577. [PMID: 38645139 PMCID: PMC11030345 DOI: 10.1101/2024.04.09.587577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Number sense is essential for early mathematical development but it is compromised in children with mathematical disabilities (MD). Here we investigate the impact of a personalized 4-week Integrated Number Sense (INS) tutoring program aimed at improving the connection between nonsymbolic (sets of objects) and symbolic (Arabic numerals) representations in children with MD. Utilizing neural pattern analysis, we found that INS tutoring not only improved cross-format mapping but also significantly boosted arithmetic fluency in children with MD. Critically, the tutoring normalized previously low levels of cross-format neural representations in these children to pre-tutoring levels observed in typically developing, especially in key brain regions associated with numerical cognition. Moreover, we identified distinct, 'inverted U-shaped' neurodevelopmental changes in the MD group, suggesting unique neural plasticity during mathematical skill development. Our findings highlight the effectiveness of targeted INS tutoring for remediating numerical deficits in MD, and offer a foundation for developing evidence-based educational interventions.
Collapse
Affiliation(s)
- Yunji Park
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Yuan Zhang
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Flora Schwartz
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Teresa Iuculano
- Centre National de la Recherche Scientifique & Université Paris Sorbonne, Paris 75016, France
| | - Hyesang Chang
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305
- Stanford Neuroscience Institute, Stanford University, Stanford, California, CA, 94305
- Symbolic Systems Program, Stanford University, Stanford, California, CA, 94305
| |
Collapse
|
19
|
Knyazev GG, Savostyanov AN, Bocharov AV, Saprigyn AE. Individual differences in the neural representation of cooperation and competition. Neurosci Lett 2024; 828:137738. [PMID: 38521404 DOI: 10.1016/j.neulet.2024.137738] [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: 11/29/2023] [Revised: 02/10/2024] [Accepted: 03/20/2024] [Indexed: 03/25/2024]
Abstract
Much evidence links the Big Five's agreeableness to a propensity for cooperation and aggressiveness to a propensity for competition. However, the neural basis for these associations is unknown. In this functional magnetic resonance imaging study, using multivariate pattern analysis of data recorded during a computer game in which participants were required to construct target patterns either in cooperation or in competition with another person, we sought to determine how individual differences in neural representations of cooperative and competitive behavior relate to individual differences in agreeableness and aggressiveness. During cooperation, agreeableness was positively correlated with the consistency of spatial patterns of neural activation in the left temporoparietal junction (TPJ) and showed positive correlations with inter-subject similarity in the dynamics of neural responses in the posterior default mode network hub and areas involved in the regulation of attention, movement planning, and visual perception. During competition, aggressiveness was positively correlated with the consistency of spatial patterns in the left and right TPJ and showed positive correlations with neural dynamics in visual processing and movement regulation areas. These results are consistent with the assumption that agreeable individuals are more involved in cooperative interactions with others, whereas aggression-prone individuals are more involved in competitive interactions.
Collapse
Affiliation(s)
- G G Knyazev
- Institute of Neurosciences and Medicine, Novosibirsk, Russia.
| | - A N Savostyanov
- Institute of Neurosciences and Medicine, Novosibirsk, Russia; Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
| | - A V Bocharov
- Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - A E Saprigyn
- Institute of Neurosciences and Medicine, Novosibirsk, Russia
| |
Collapse
|
20
|
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.
Collapse
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
| |
Collapse
|
21
|
Goldstein A, Grinstein-Dabush A, Schain M, Wang H, Hong Z, Aubrey B, Nastase SA, Zada Z, Ham E, Feder A, Gazula H, Buchnik E, Doyle W, Devore S, Dugan P, Reichart R, Friedman D, Brenner M, Hassidim A, Devinsky O, Flinker A, Hasson U. Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns. Nat Commun 2024; 15:2768. [PMID: 38553456 PMCID: PMC10980748 DOI: 10.1038/s41467-024-46631-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 03/04/2024] [Indexed: 04/02/2024] Open
Abstract
Contextual embeddings, derived from deep language models (DLMs), provide a continuous vectorial representation of language. This embedding space differs fundamentally from the symbolic representations posited by traditional psycholinguistics. We hypothesize that language areas in the human brain, similar to DLMs, rely on a continuous embedding space to represent language. To test this hypothesis, we densely record the neural activity patterns in the inferior frontal gyrus (IFG) of three participants using dense intracranial arrays while they listened to a 30-minute podcast. From these fine-grained spatiotemporal neural recordings, we derive a continuous vectorial representation for each word (i.e., a brain embedding) in each patient. Using stringent zero-shot mapping we demonstrate that brain embeddings in the IFG and the DLM contextual embedding space have common geometric patterns. The common geometric patterns allow us to predict the brain embedding in IFG of a given left-out word based solely on its geometrical relationship to other non-overlapping words in the podcast. Furthermore, we show that contextual embeddings capture the geometry of IFG embeddings better than static word embeddings. The continuous brain embedding space exposes a vector-based neural code for natural language processing in the human brain.
Collapse
Affiliation(s)
- Ariel Goldstein
- Business School, Data Science department and Cognitive Department, Hebrew University, Jerusalem, Israel.
- Google Research, Tel Aviv, Israel.
| | | | | | - Haocheng Wang
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Zhuoqiao Hong
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Bobbi Aubrey
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
- New York University Grossman School of Medicine, New York, NY, USA
| | - Samuel A Nastase
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Zaid Zada
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Eric Ham
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Harshvardhan Gazula
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Werner Doyle
- New York University Grossman School of Medicine, New York, NY, USA
| | - Sasha Devore
- New York University Grossman School of Medicine, New York, NY, USA
| | - Patricia Dugan
- New York University Grossman School of Medicine, New York, NY, USA
| | - Roi Reichart
- Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology, Haifa, Israel
| | - Daniel Friedman
- New York University Grossman School of Medicine, New York, NY, USA
| | - Michael Brenner
- Google Research, Tel Aviv, Israel
- School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
| | | | - Orrin Devinsky
- New York University Grossman School of Medicine, New York, NY, USA
| | - Adeen Flinker
- New York University Grossman School of Medicine, New York, NY, USA
- New York University Tandon School of Engineering, Brooklyn, NY, USA
| | - Uri Hasson
- Google Research, Tel Aviv, Israel
- Department of Psychology and the Neuroscience Institute, Princeton University, Princeton, NJ, USA
| |
Collapse
|
22
|
Wang J, Lapate RC. Emotional state dynamics impacts temporal memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.25.550412. [PMID: 38464043 PMCID: PMC10925226 DOI: 10.1101/2023.07.25.550412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Emotional fluctuations are ubiquitous in everyday life, but precisely how they sculpt the temporal organization of memories remains unclear. Here, we designed a novel task-the Emotion Boundary Task-wherein participants viewed sequences of negative and neutral images surrounded by a color border. We manipulated perceptual context (border color), emotional valence, as well as the direction of emotional-valence shifts (i.e., shifts from neutral-to-negative and negative-to-neutral events) to create encoding events comprised of image sequences with a shared perceptual and/or emotional context. We measured memory for temporal order and subjectively remembered temporal distances for images processed within and across events. Negative images processed within events were remembered as closer in time compared to neutral ones. In contrast, temporal distance was remembered as longer for images spanning neutral-to-negative shifts-suggesting temporal dilation in memory with the onset of a negative event following a previously-neutral state. The extent of this negative-picture induced temporal dilation in memory correlated with dispositional negativity across individuals. Lastly, temporal order memory was enhanced for recently presented negative (compared to neutral) images. These findings suggest that emotional-state dynamics matters when considering emotion-temporal memory interactions: While persistent negative events may compress subjectively remembered time, dynamic shifts from neutral to negative events produce temporal dilation in memory, which may be relevant for adaptive emotional functioning.
Collapse
|
23
|
Fan D, Zhao H, Liu H, Niu H, Liu T, Wang Y. Abnormal brain activities of cognitive processes in cerebral small vessel disease: A systematic review of task fMRI studies. J Neuroradiol 2024; 51:155-167. [PMID: 37844660 DOI: 10.1016/j.neurad.2023.10.005] [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: 06/08/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 10/18/2023]
Abstract
Cerebral small vessel disease (CSVD) is characterized by widespread functional changes in the brain, as evident from abnormal brain activations during cognitive tasks. However, the existing findings in this area are not yet conclusive. We systematically reviewed 25 studies reporting task-related fMRI in five cognitive domains in CSVD, namely executive function, working memory, processing speed, motor, and affective processing. The findings highlighted: (1) CSVD affects cognitive processes in a domain-specific manner; (2) Compensatory and regulatory effects were observed simultaneously in CSVD, which may reflect the interplay between the negative impact of brain lesion and the positive impact of cognitive reserve. Combined with behavioral and functional findings in CSVD, we proposed an integrated model to illustrate the relationship between altered activations and behavioral performance in different stages of CSVD: functional brain changes may precede and be more sensitive than behavioral impairments in the early pre-symptomatic stage; Meanwhile, compensatory and regulatory mechanisms often occur in the early stages of the disease, while dysfunction/decompensation and dysregulation often occur in the late stages. Overall, abnormal hyper-/hypo-activations are crucial for understanding the mechanisms of small vessel lesion-induced behavioral dysfunction, identifying potential neuromarker and developing interventions to mitigate the impact of CSVD on cognitive function.
Collapse
Affiliation(s)
- Dongqiong Fan
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Haichao Zhao
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China; Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China
| | - Hao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Haijun Niu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
| | - Yilong Wang
- Department of Neurology, Beijing TianTan Hospital, Capital Medical University, Beijing, China; Chinese Institute for Brain Research, Beijing, China; National Center for Neurological Disorders, Beijing, China.
| |
Collapse
|
24
|
Read ML, Berry SC, Graham KS, Voets NL, Zhang J, Aggleton JP, Lawrence AD, Hodgetts CJ. Scene-selectivity in CA1/subicular complex: Multivoxel pattern analysis at 7T. Neuropsychologia 2024; 194:108783. [PMID: 38161052 DOI: 10.1016/j.neuropsychologia.2023.108783] [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: 09/30/2023] [Revised: 12/21/2023] [Accepted: 12/27/2023] [Indexed: 01/03/2024]
Abstract
Prior univariate functional magnetic resonance imaging (fMRI) studies in humans suggest that the anteromedial subicular complex of the hippocampus is a hub for scene-based cognition. However, it is possible that univariate approaches were not sufficiently sensitive to detect scene-related activity in other subfields that have been implicated in spatial processing (e.g., CA1). Further, as connectivity-based functional gradients in the hippocampus do not respect classical subfield boundary definitions, category selectivity may be distributed across anatomical subfields. Region-of-interest approaches, therefore, may limit our ability to observe category selectivity across discrete subfield boundaries. To address these issues, we applied searchlight multivariate pattern analysis to 7T fMRI data of healthy adults who undertook a simultaneous visual odd-one-out discrimination task for scene and non-scene (including face) visual stimuli, hypothesising that scene classification would be possible in multiple hippocampal regions within, but not constrained to, anteromedial subicular complex and CA1. Indeed, we found that the scene-selective searchlight map overlapped not only with anteromedial subicular complex (distal subiculum, pre/para subiculum), but also inferior CA1, alongside posteromedial (including retrosplenial) and parahippocampal cortices. Probabilistic overlap maps revealed gradients of scene category selectivity, with the strongest overlap located in the medial hippocampus, converging with searchlight findings. This was contrasted with gradients of face category selectivity, which had stronger overlap in more lateral hippocampus, supporting ideas of parallel processing streams for these two categories. Our work helps to map the scene, in contrast to, face processing networks within, and connected to, the human hippocampus.
Collapse
Affiliation(s)
- Marie-Lucie Read
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Samuel C Berry
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; Department of Psychology, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK
| | - Kim S Graham
- School of Philosophy, Psychology and Language Sciences, Dugald Stewart Building, University of Edinburgh, 3 Charles Street, Edinburgh, EH8 9AD, UK
| | - Natalie L Voets
- Wellcome Centre for Integrative Neuroimaging, FMRIB Building, John Radcliffe Hospital, Oxford, OX3 9DU2, UK
| | - Jiaxiang Zhang
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; School of Mathematics and Computer Science, Swansea University, Swansea SA1 8DD, UK
| | - John P Aggleton
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Andrew D Lawrence
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; School of Philosophy, Psychology and Language Sciences, Dugald Stewart Building, University of Edinburgh, 3 Charles Street, Edinburgh, EH8 9AD, UK
| | - Carl J Hodgetts
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; Department of Psychology, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK.
| |
Collapse
|
25
|
Hauptman M, Elli G, Pant R, Bedny M. Neural specialization for 'visual' concepts emerges in the absence of vision. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.23.552701. [PMID: 37662234 PMCID: PMC10473738 DOI: 10.1101/2023.08.23.552701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Vision provides a key source of information about many concepts, including 'living things' (e.g., tiger) and visual events (e.g., sparkle). According to a prominent theoretical framework, neural specialization for different conceptual categories is shaped by sensory features, e.g., living things are neurally dissociable from navigable places because living things concepts depend more on visual features. We tested this framework by comparing the neural basis of 'visual' concepts across sighted (n=22) and congenitally blind (n=21) adults. Participants judged the similarity of words varying in their reliance on vision while undergoing fMRI. We compared neural responses to living things nouns (birds, mammals) and place nouns (natural, manmade). In addition, we compared visual event verbs (e.g., 'sparkle') to non-visual events (sound emission, hand motion, mouth motion). People born blind exhibited distinctive univariate and multivariate responses to living things in a temporo-parietal semantic network activated by nouns, including the precuneus (PC). To our knowledge, this is the first demonstration that neural selectivity for living things does not require vision. We additionally observed preserved neural signatures of 'visual' light events in the left middle temporal gyrus (LMTG+). Across a wide range of semantic types, neural representations of sensory concepts develop independent of sensory experience.
Collapse
Affiliation(s)
- Miriam Hauptman
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Giulia Elli
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Rashi Pant
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
- Department of Biological Psychology & Neuropsychology, Universität Hamburg, Germany
| | - Marina Bedny
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|
26
|
Rizza A, Pedale T, Mastroberardino S, Olivetti Belardinelli M, Van der Lubbe RHJ, Spence C, Santangelo V. Working Memory Maintenance of Visual and Auditory Spatial Information Relies on Supramodal Neural Codes in the Dorsal Frontoparietal Cortex. Brain Sci 2024; 14:123. [PMID: 38391698 PMCID: PMC10886761 DOI: 10.3390/brainsci14020123] [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: 12/18/2023] [Revised: 01/19/2024] [Accepted: 01/20/2024] [Indexed: 02/24/2024] Open
Abstract
The frontoparietal attention network plays a pivotal role during working memory (WM) maintenance, especially under high-load conditions. Nevertheless, there is ongoing debate regarding whether this network relies on supramodal or modality-specific neural signatures. In this study, we used multi-voxel pattern analysis (MVPA) to evaluate the neural representation of visual versus auditory information during WM maintenance. During fMRI scanning, participants maintained small or large spatial configurations (low- or high-load trials) of either colour shades or sound pitches in WM for later retrieval. Participants were less accurate in retrieving high- vs. low-load trials, demonstrating an effective manipulation of WM load, irrespective of the sensory modality. The frontoparietal regions involved in maintaining high- vs. low-load spatial maps in either sensory modality were highlighted using a conjunction analysis. Widespread activity was found across the dorsal frontoparietal network, peaking on the frontal eye fields and the superior parietal lobule, bilaterally. Within these regions, MVPAs were performed to quantify the pattern of distinctness of visual vs. auditory neural codes during WM maintenance. These analyses failed to reveal distinguishable patterns in the dorsal frontoparietal regions, thus providing support for a common, supramodal neural code associated with the retention of either visual or auditory spatial configurations.
Collapse
Affiliation(s)
- Aurora Rizza
- Department of Psychology, Sapienza University of Rome, P.le A. Moro 5, 00185 Rome, Italy
| | - Tiziana Pedale
- Functional Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy
| | - Serena Mastroberardino
- Department of Philosophy, Social Sciences & Education, University of Perugia, Piazza G. Ermini 1, 06123 Perugia, Italy
| | - Marta Olivetti Belardinelli
- Department of Psychology, Sapienza University of Rome, P.le A. Moro 5, 00185 Rome, Italy
- ECONA, Interuniversity Centre for Research on Cognitive Processing in Natural and Artificial Systems, Sapienza University of Rome, Via dei Marsi 78, 00185 Rome, Italy
| | - Rob H J Van der Lubbe
- Cognition, Data and Education, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
- Laboratory of Vision Science and Optometry, Adam Mickiewicz University, Wieniawskiego 1, 61-712 Poznan, Poland
| | - Charles Spence
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Oxford OX2 6BW, UK
| | - Valerio Santangelo
- Functional Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy
- Department of Philosophy, Social Sciences & Education, University of Perugia, Piazza G. Ermini 1, 06123 Perugia, Italy
| |
Collapse
|
27
|
Vidaurre D. A generative model of electrophysiological brain responses to stimulation. eLife 2024; 12:RP87729. [PMID: 38231034 PMCID: PMC10945576 DOI: 10.7554/elife.87729] [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] [Indexed: 01/18/2024] Open
Abstract
Each brain response to a stimulus is, to a large extent, unique. However this variability, our perceptual experience feels stable. Standard decoding models, which utilise information across several areas to tap into stimuli representation and processing, are fundamentally based on averages. Therefore, they can focus precisely on the features that are most stable across stimulus presentations. But which are these features exactly is difficult to address in the absence of a generative model of the signal. Here, I introduce genephys, a generative model of brain responses to stimulation publicly available as a Python package that, when confronted with a decoding algorithm, can reproduce the structured patterns of decoding accuracy that we observe in real data. Using this approach, I characterise how these patterns may be brought about by the different aspects of the signal, which in turn may translate into distinct putative neural mechanisms. In particular, the model shows that the features in the data that support successful decoding-and, therefore, likely reflect stable mechanisms of stimulus representation-have an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory component. At the individual trial level, still, responses are found to be highly variable, which can be due to various factors including phase noise and probabilistic activations.
Collapse
Affiliation(s)
- Diego Vidaurre
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus UniversityAarhusDenmark
- Department of Psychiatry, Oxford UniversityOxfordUnited Kingdom
| |
Collapse
|
28
|
Khalil R, Agnoli S, Mastria S, Kondinska A, Karim AA, Godde B. Individual differences and creative ideation: neuromodulatory signatures of mindset and response inhibition. Front Neurosci 2023; 17:1238165. [PMID: 38125402 PMCID: PMC10731982 DOI: 10.3389/fnins.2023.1238165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 11/10/2023] [Indexed: 12/23/2023] Open
Abstract
This study addresses the modulatory role of individual mindset in explaining the relationship between response inhibition (RI) and divergent thinking (DT) using transcranial direct current stimulation (tDCS). Forty undergraduate students (22 male and 18 female), aged between 18 and 23 years (average age = 19 years, SD = 1.48), were recruited. Participants received either anodal tDCS of the right IFG coupled with cathodal tDCS of the left IFG (R + L-; N = 19) or the opposite coupling (R-L+; N = 21). We tested DT performance using the alternative uses task (AUT), measuring participants' fluency, originality, and flexibility in the response production, as well as participants' mindsets. Furthermore, we applied a go-no-go task to examine the role of RI before and after stimulating the inferior frontal gyrus (IFG) using tDCS. The results showed that the mindset levels acted as moderators on stimulation conditions and enhanced RI on AUT fluency and flexibility but not originality. Intriguingly, growth mindsets have opposite moderating effects on the change in DT, resulting from the tDCS stimulation of the left and the right IFG, with reduced fluency but enhanced flexibility. Our findings imply that understanding neural modulatory signatures of ideational processes with tDCS strongly benefits from evaluating cognitive status and control functions.
Collapse
Affiliation(s)
- Radwa Khalil
- School of Business, Social and Decision Sciences, Constructor University, Bremen, Germany
| | - Sergio Agnoli
- Department of Life Sciences, University of Trieste, Trieste, Italy
- Marconi Institute for Creativity, Sasso Marconi, Italy
| | - Serena Mastria
- Department of Psychology, University of Bologna, Bologna, Italy
| | - Angela Kondinska
- School of Business, Social and Decision Sciences, Constructor University, Bremen, Germany
| | - Ahmed A. Karim
- School of Business, Social and Decision Sciences, Constructor University, Bremen, Germany
- Department of Psychiatry and Psychotherapy, University Clinic Tübingen, Tübingen, Germany
- Department of Health Psychology and Neurorehabilitation, SRH Mobile University, Riedlingen, Germany
| | - Ben Godde
- School of Business, Social and Decision Sciences, Constructor University, Bremen, Germany
| |
Collapse
|
29
|
Nordt M, Gomez J, Natu VS, Rezai AA, Finzi D, Kular H, Grill-Spector K. Longitudinal development of category representations in ventral temporal cortex predicts word and face recognition. Nat Commun 2023; 14:8010. [PMID: 38049393 PMCID: PMC10696026 DOI: 10.1038/s41467-023-43146-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 11/01/2023] [Indexed: 12/06/2023] Open
Abstract
Regions in ventral temporal cortex that are involved in visual recognition of categories like words and faces undergo differential development during childhood. However, categories are also represented in distributed responses across high-level visual cortex. How distributed category representations develop and if this development relates to behavioral changes in recognition remains largely unknown. Here, we used functional magnetic resonance imaging to longitudinally measure the development of distributed responses across ventral temporal cortex to 10 categories in school-age children over several years. Our results reveal both strengthening and weakening of category representations with age, which was mainly driven by changes across category-selective voxels. Representations became particularly more distinct for words in the left hemisphere and for faces bilaterally. Critically, distinctiveness for words and faces across category-selective voxels in left and right lateral ventral temporal cortex, respectively, predicted individual children's word and face recognition performance. These results suggest that the development of distributed representations in ventral temporal cortex has behavioral ramifications and advance our understanding of prolonged cortical development during childhood.
Collapse
Affiliation(s)
- Marisa Nordt
- Department of Psychology, Stanford University, Stanford, CA, USA.
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen, Aachen, Germany.
- JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, RWTH Aachen & Research Centre Juelich, Juelich, Germany.
| | - Jesse Gomez
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Vaidehi S Natu
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Alex A Rezai
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Dawn Finzi
- Department of Psychology, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Holly Kular
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA, USA
- Neurosciences Program, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| |
Collapse
|
30
|
Gwilliams L, Flick G, Marantz A, Pylkkänen L, Poeppel D, King JR. Introducing MEG-MASC a high-quality magneto-encephalography dataset for evaluating natural speech processing. Sci Data 2023; 10:862. [PMID: 38049487 PMCID: PMC10695966 DOI: 10.1038/s41597-023-02752-5] [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: 07/29/2022] [Accepted: 11/16/2023] [Indexed: 12/06/2023] Open
Abstract
The "MEG-MASC" dataset provides a curated set of raw magnetoencephalography (MEG) recordings of 27 English speakers who listened to two hours of naturalistic stories. Each participant performed two identical sessions, involving listening to four fictional stories from the Manually Annotated Sub-Corpus (MASC) intermixed with random word lists and comprehension questions. We time-stamp the onset and offset of each word and phoneme in the metadata of the recording, and organize the dataset according to the 'Brain Imaging Data Structure' (BIDS). This data collection provides a suitable benchmark to large-scale encoding and decoding analyses of temporally-resolved brain responses to speech. We provide the Python code to replicate several validations analyses of the MEG evoked responses such as the temporal decoding of phonetic features and word frequency. All code and MEG, audio and text data are publicly available to keep with best practices in transparent and reproducible research.
Collapse
Affiliation(s)
- Laura Gwilliams
- Department of Psychology, Stanford University, Stanford, USA.
- Department of Psychology, New York University, New York, USA.
- NYU Abu Dhabi Institute, Abu Dhabi, United Arab Emirates.
| | - Graham Flick
- Department of Psychology, New York University, New York, USA
- NYU Abu Dhabi Institute, Abu Dhabi, United Arab Emirates
- Department of Linguistics, New York University, New York, USA
- Rotman Research Institute, Baycrest Hospital, Toronto, Canada
| | - Alec Marantz
- Department of Psychology, New York University, New York, USA
- NYU Abu Dhabi Institute, Abu Dhabi, United Arab Emirates
- Department of Linguistics, New York University, New York, USA
| | - Liina Pylkkänen
- Department of Psychology, New York University, New York, USA
- NYU Abu Dhabi Institute, Abu Dhabi, United Arab Emirates
- Department of Linguistics, New York University, New York, USA
| | - David Poeppel
- Department of Psychology, New York University, New York, USA
- Ernst Struengmann Institute for Neuroscience, Frankfurt, Germany
| | - Jean-Rémi King
- Department of Psychology, New York University, New York, USA
- LSP, École normale supérieure, PSL University, CNRS, 75005, Paris, France
| |
Collapse
|
31
|
Rastegarnia S, St-Laurent M, DuPre E, Pinsard B, Bellec P. Brain decoding of the Human Connectome Project tasks in a dense individual fMRI dataset. Neuroimage 2023; 283:120395. [PMID: 37832707 DOI: 10.1016/j.neuroimage.2023.120395] [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: 04/03/2023] [Revised: 09/21/2023] [Accepted: 09/27/2023] [Indexed: 10/15/2023] Open
Abstract
Brain decoding aims to infer cognitive states from patterns of brain activity. Substantial inter-individual variations in functional brain organization challenge accurate decoding performed at the group level. In this paper, we tested whether accurate brain decoding models can be trained entirely at the individual level. We trained several classifiers on a dense individual functional magnetic resonance imaging (fMRI) dataset for which six participants completed the entire Human Connectome Project (HCP) task battery >13 times over ten separate fMRI sessions. We evaluated nine decoding methods, from Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP) to Graph Convolutional Neural Networks (GCN). All decoders were trained to classify single fMRI volumes into 21 experimental conditions simultaneously, using ∼7 h of fMRI data per participant. The best prediction accuracies were achieved with GCN and MLP models, whose performance (57-67 % accuracy) approached state-of-the-art accuracy (76 %) with models trained at the group level on >1 K hours of data from the original HCP sample. Our SVM model also performed very well (54-62 % accuracy). Feature importance maps derived from MLP -our best-performing model- revealed informative features in regions relevant to particular cognitive domains, notably in the motor cortex. We also observed that inter-subject classification achieved substantially lower accuracy than subject-specific models, indicating that our decoders learned individual-specific features. This work demonstrates that densely-sampled neuroimaging datasets can be used to train accurate brain decoding models at the individual level. We expect this work to become a useful benchmark for techniques that improve model generalization across multiple subjects and acquisition conditions.
Collapse
Affiliation(s)
- Shima Rastegarnia
- Université de Montréal, Montréal, QC, Canada; Centre de Recherche de L'Institut Universitaire de Gériatrie de Montréal, Montréal, Canada.
| | - Marie St-Laurent
- Centre de Recherche de L'Institut Universitaire de Gériatrie de Montréal, Montréal, Canada
| | | | - Basile Pinsard
- Centre de Recherche de L'Institut Universitaire de Gériatrie de Montréal, Montréal, Canada
| | - Pierre Bellec
- Université de Montréal, Montréal, QC, Canada; Centre de Recherche de L'Institut Universitaire de Gériatrie de Montréal, Montréal, Canada
| |
Collapse
|
32
|
Bruera A, Tao Y, Anderson A, Çokal D, Haber J, Poesio M. Modeling Brain Representations of Words' Concreteness in Context Using GPT-2 and Human Ratings. Cogn Sci 2023; 47:e13388. [PMID: 38103208 DOI: 10.1111/cogs.13388] [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: 04/19/2023] [Revised: 09/12/2023] [Accepted: 10/27/2023] [Indexed: 12/18/2023]
Abstract
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation ("bat", in a baseball vs. a vampire context), as well as more nuanced differences of meaning-for example, polysemous words such as "book", which can be interpreted in distinct but related senses ("explain a book", information, vs. "open a book", object) whose differences are fine-grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb-noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine-grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness.
Collapse
Affiliation(s)
- Andrea Bruera
- School of Electronic Engineering and Computer Science, Cognitive Science Research Group, Queen Mary University of London
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences
| | - Yuan Tao
- Department of Cognitive Science, Johns Hopkins University
| | | | - Derya Çokal
- Department of German Language and Literature I-Linguistics, University of Cologne
| | - Janosch Haber
- School of Electronic Engineering and Computer Science, Cognitive Science Research Group, Queen Mary University of London
- Chattermill, London
| | - Massimo Poesio
- School of Electronic Engineering and Computer Science, Cognitive Science Research Group, Queen Mary University of London
- Department of Information and Computing Sciences, University of Utrecht
| |
Collapse
|
33
|
Smith BB, Zhao Y, Lindquist MA, Caffo B. Regression models for partially localized fMRI connectivity analyses. FRONTIERS IN NEUROIMAGING 2023; 2:1178359. [PMID: 38025311 PMCID: PMC10679340 DOI: 10.3389/fnimg.2023.1178359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023]
Abstract
Background Brain functional connectivity analysis of resting-state functional magnetic resonance imaging (fMRI) data is typically performed in a standardized template space assuming consistency of connections across subjects. Analysis methods can come in the form of one-edge-at-a-time analyses or dimension reduction/decomposition methods. Common to these approaches is an assumption that brain regions are functionally aligned across subjects; however, it is known that this functional alignment assumption is often violated. Methods In this paper, we use subject-level regression models to explain intra-subject variability in connectivity. Covariates can include factors such as geographic distance between two pairs of brain regions, whether the two regions are symmetrically opposite (homotopic), and whether the two regions are members of the same functional network. Additionally, a covariate for each brain region can be included, to account for the possibility that some regions have consistently higher or lower connectivity. This style of analysis allows us to characterize the fraction of variation explained by each type of covariate. Additionally, comparisons across subjects can then be made using the fitted connectivity regression models, offering a more parsimonious alternative to edge-at-a-time approaches. Results We apply our approach to Human Connectome Project data on 268 regions of interest (ROIs), grouped into eight functional networks. We find that a high proportion of variation is explained by region covariates and network membership covariates, while geographic distance and homotopy have high relative importance after adjusting for the number of predictors. We also find that the degree of data repeatability using our connectivity regression model-which uses only partial location information about pairs of ROI's-is comparably as high as the repeatability obtained using full location information. Discussion While our analysis uses data that have been transformed into a common template-space, we also envision the method being useful in multi-atlas registration settings, where subject data remains in its own geometry and templates are warped instead. These results suggest the tantalizing possibility that fMRI connectivity analysis can be performed in subject-space, using less aggressive registration, such as simple affine transformations, multi-atlas subject-space registration, or perhaps even no registration whatsoever.
Collapse
Affiliation(s)
- Bonnie B. Smith
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Martin A. Lindquist
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Brian Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| |
Collapse
|
34
|
Walker EY, Pohl S, Denison RN, Barack DL, Lee J, Block N, Ma WJ, Meyniel F. Studying the neural representations of uncertainty. Nat Neurosci 2023; 26:1857-1867. [PMID: 37814025 DOI: 10.1038/s41593-023-01444-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 08/30/2023] [Indexed: 10/11/2023]
Abstract
The study of the brain's representations of uncertainty is a central topic in neuroscience. Unlike most quantities of which the neural representation is studied, uncertainty is a property of an observer's beliefs about the world, which poses specific methodological challenges. We analyze how the literature on the neural representations of uncertainty addresses those challenges and distinguish between 'code-driven' and 'correlational' approaches. Code-driven approaches make assumptions about the neural code for representing world states and the associated uncertainty. By contrast, correlational approaches search for relationships between uncertainty and neural activity without constraints on the neural representation of the world state that this uncertainty accompanies. To compare these two approaches, we apply several criteria for neural representations: sensitivity, specificity, invariance and functionality. Our analysis reveals that the two approaches lead to different but complementary findings, shaping new research questions and guiding future experiments.
Collapse
Affiliation(s)
- Edgar Y Walker
- Department of Physiology and Biophysics, Computational Neuroscience Center, University of Washington, Seattle, WA, USA
| | - Stephan Pohl
- Department of Philosophy, New York University, New York, NY, USA
| | - Rachel N Denison
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - David L Barack
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
- Department of Philosophy, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer Lee
- Center for Neural Science, New York University, New York, NY, USA
| | - Ned Block
- Department of Philosophy, New York University, New York, NY, USA
| | - Wei Ji Ma
- Center for Neural Science, New York University, New York, NY, USA
- Department of Psychology, New York University, New York, NY, USA
| | - Florent Meyniel
- Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, Gif-sur-Yvette, France.
| |
Collapse
|
35
|
Wu H, Zuo Z, Yuan Z, Zhou T, Zhuo Y, Zheng N, Chen B. Neural representation of gestalt grouping and attention effect in human visual cortex. J Neurosci Methods 2023; 399:109980. [PMID: 37783351 DOI: 10.1016/j.jneumeth.2023.109980] [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: 05/31/2023] [Revised: 08/29/2023] [Accepted: 09/29/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND The brain aggregates meaningless local sensory elements to form meaningful global patterns in a process called perceptual grouping. Current brain imaging studies have found that neural activities in V1 are modulated during visual grouping. However, how grouping is represented in each of the early visual areas, and how attention alters these representations, is still unknown. NEW METHOD We adopted MVPA to decode the specific content of perceptual grouping by comparing neural activity patterns between gratings and dot lattice stimuli which can be grouped with proximity law. Furthermore, we quantified the grouping effect by defining the strength of grouping, and assessed the effect of attention on grouping. RESULTS We found that activity patterns to proximity grouped stimuli in early visual areas resemble these to grating stimuli with the same orientations. This similarity exists even when there is no attention focused on the stimuli. The results also showed a progressive increase of representational strength of grouping from V1 to V3, and attention modulation to grouping is only significant in V3 among all the visual areas. COMPARISON WITH EXISTING METHODS Most of the previous work on perceptual grouping has focused on how activity amplitudes are modulated by grouping. Using MVPA, the present work successfully decoded the contents of neural activity patterns corresponding to proximity grouping stimuli, thus shed light on the availability of content-decoding approach in the research on perceptual grouping. CONCLUSIONS Our work found that the content of the neural activity patterns during perceptual grouping can be decoded in the early visual areas under both attended and unattended task, and provide novel evidence that there is a cascade processing for proximity grouping through V1 to V3. The strength of grouping was larger in V3 than in any other visual areas, and the attention modulation to the strength of grouping was only significant in V3 among all the visual areas, implying that V3 plays an important role in proximity grouping.
Collapse
Affiliation(s)
- Hao Wu
- School of Electrical Engineering, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China.
| | - Zejian Yuan
- National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an, Shaanxi 710049, China; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Tiangang Zhou
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Yan Zhuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Nanning Zheng
- National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an, Shaanxi 710049, China; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Badong Chen
- National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an, Shaanxi 710049, China; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| |
Collapse
|
36
|
Chen Y, Yang Y, Gong Z, Kang Y, Zhang Y, Chen H, Zeng K, Men X, Wang J, Huang Y, Wang H, Zhan S, Tan W, Wang W. Altered effective connectivity from cerebellum to motor cortex in chronic low back pain: A multivariate pattern analysis and spectral dynamic causal modeling study. Brain Res Bull 2023; 204:110794. [PMID: 37871687 DOI: 10.1016/j.brainresbull.2023.110794] [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: 04/03/2023] [Revised: 08/01/2023] [Accepted: 10/17/2023] [Indexed: 10/25/2023]
Abstract
To explore the central processing mechanism of pain perception in chronic low back pain (cLBP) using multi-voxel pattern analysis (MVPA) based on the static and dynamic fractional amplitude of low-frequency fluctuations (fALFF) analysis, and spectral dynamic causal modeling (spDCM). Thirty-two patients with cLBP and 29 matched healthy controls (HCs) for the first cohort and 24 patients with cLBP and 22 HCs for the validation cohort underwent resting-state fMRI scan. The alterations in static and dynamic fALFF were as classification features to distinguish patients with cLBP from HCs. The brain regions gotten from the MVPA results were used for further spDCM analysis. We found that the most discriminative brain regions that contributed to the classification were the right supplementary motor area (SMA.R), left paracentral lobule (PCL.L), and bilateral cerebellar Crus II. The spDCM results displayed decreased excitatory influence from the bilateral cerebellar Crus II to PCL.L in patients with cLBP compared with HCs. Moreover, the conversion of effective connectivity from the bilateral cerebellar Crus II to SMA.R from excitatory influence to inhibitive influence, and the effective connectivity strength exhibited partially mediated effects on Chinese Short Form Oswestry Disability Index Questionnaire (C-SFODI) scores. Our findings suggest that the cerebellum and its weakened or inhibited connections to the motor cortex may be one of the underlying feedback pathways for pain perception in cLBP, and partially mediate the degree of dysfunction.
Collapse
Affiliation(s)
- Yilei Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yuchan Yang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhigang Gong
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yingjie Kang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yingying Zhang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hui Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ke Zeng
- Department of Tuina, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiubo Men
- Department of Tuina, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jianwei Wang
- Department of Tuina, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yanwen Huang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hui Wang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Songhua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wenli Tan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Wei Wang
- Department of Tuina, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| |
Collapse
|
37
|
Lee Y, Seo Y, Lee Y, Lee D. Dimensional emotions are represented by distinct topographical brain networks. Int J Clin Health Psychol 2023; 23:100408. [PMID: 37663040 PMCID: PMC10472247 DOI: 10.1016/j.ijchp.2023.100408] [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: 03/16/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023] Open
Abstract
The ability to recognize others' facial emotions has become increasingly important after the COVID-19 pandemic, which causes stressful situations in emotion regulation. Considering the importance of emotion in maintaining a social life, emotion knowledge to perceive and label emotions of oneself and others requires an understanding of affective dimensions, such as emotional valence and emotional arousal. However, limited information is available about whether the behavioral representation of affective dimensions is similar to their neural representation. To explore the relationship between the brain and behavior in the representational geometries of affective dimensions, we constructed a behavioral paradigm in which emotional faces were categorized into geometric spaces along the valence, arousal, and valence and arousal dimensions. Moreover, we compared such representations to neural representations of the faces acquired by functional magnetic resonance imaging. We found that affective dimensions were similarly represented in the behavior and brain. Specifically, behavioral and neural representations of valence were less similar to those of arousal. We also found that valence was represented in the dorsolateral prefrontal cortex, frontal eye fields, precuneus, and early visual cortex, whereas arousal was represented in the cingulate gyrus, middle frontal gyrus, orbitofrontal cortex, fusiform gyrus, and early visual cortex. In conclusion, the current study suggests that dimensional emotions are similarly represented in the behavior and brain and are presented with differential topographical organizations in the brain.
Collapse
Affiliation(s)
| | | | - Youngju Lee
- Cognitive Science Research Group, Korea Brain Research Institute, 61 Cheomdan-ro, Dong-gu, Daegu 41062, Republic of Korea
| | - Dongha Lee
- Cognitive Science Research Group, Korea Brain Research Institute, 61 Cheomdan-ro, Dong-gu, Daegu 41062, Republic of Korea
| |
Collapse
|
38
|
Patel T, Morales M, Pickering MJ, Hoffman P. A common neural code for meaning in discourse production and comprehension. Neuroimage 2023; 279:120295. [PMID: 37536526 DOI: 10.1016/j.neuroimage.2023.120295] [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: 01/22/2023] [Revised: 06/28/2023] [Accepted: 07/23/2023] [Indexed: 08/05/2023] Open
Abstract
How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.
Collapse
Affiliation(s)
- Tanvi Patel
- School of Philosophy, Psychology & Language Sciences, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Matías Morales
- School of Philosophy, Psychology & Language Sciences, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Martin J Pickering
- School of Philosophy, Psychology & Language Sciences, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Paul Hoffman
- School of Philosophy, Psychology & Language Sciences, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK.
| |
Collapse
|
39
|
Liu YF, Rapp B, Bedny M. Reading Braille by Touch Recruits Posterior Parietal Cortex. J Cogn Neurosci 2023; 35:1593-1616. [PMID: 37584592 PMCID: PMC10877400 DOI: 10.1162/jocn_a_02041] [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: 08/17/2023]
Abstract
Blind readers use a tactile reading system consisting of raised dot arrays: braille/⠃⠗⠇. How do human brains implement reading by touch? The current study looked for signatures of reading-specific orthographic processes in braille, separate from low-level somatosensory responses and semantic processes. Of specific interest were responses in posterior parietal cortices (PPCs), because of their role in high-level tactile perception. Congenitally blind, proficient braille readers read real words and pseudowords by touch while undergoing fMRI. We leveraged the system of contractions in English braille, where one braille cell can represent multiple English print letters (e.g., "ing" ⠬, "one" ⠐⠕), making it possible to separate physical and orthographic word length. All words in the study consisted of four braille cells, but their corresponding Roman letter spellings varied from four to seven letters (e.g., "con-c-er-t" ⠒⠉⠻⠞. contracted: four cells; uncontracted: seven letters). We found that the bilateral supramarginal gyrus in the PPC increased its activity as the uncontracted word length increased. By contrast, in the hand region of primary somatosensory cortex (S1), activity increased as a function of a low-level somatosensory feature: dot-number per word. The PPC also showed greater response to pseudowords than real words and distinguished between real and pseudowords in multivariate-pattern analysis. Parieto-occipital, early visual and ventral occipito-temporal, as well as prefrontal cortices also showed sensitivity to the real-versus-pseudoword distinction. We conclude that PPC is involved in orthographic processing for braille, that is, braille character and word recognition, possibly because of braille's tactile modality.
Collapse
Affiliation(s)
- Yun-Fei Liu
- Department of Psychological and Brain Sciences, Johns Hopkins University
| | - Brenda Rapp
- Department of Cognitive Science, Johns Hopkins University
| | - Marina Bedny
- Department of Psychological and Brain Sciences, Johns Hopkins University
| |
Collapse
|
40
|
Kuhnke P, Kiefer M, Hartwigsen G. Conceptual representations in the default, control and attention networks are task-dependent and cross-modal. BRAIN AND LANGUAGE 2023; 244:105313. [PMID: 37595340 DOI: 10.1016/j.bandl.2023.105313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/03/2023] [Accepted: 08/10/2023] [Indexed: 08/20/2023]
Abstract
Conceptual knowledge is central to human cognition. Neuroimaging studies suggest that conceptual processing involves modality-specific and multimodal brain regions in a task-dependent fashion. However, it remains unclear (1) to what extent conceptual feature representations are also modulated by the task, (2) whether conceptual representations in multimodal regions are indeed cross-modal, and (3) how the conceptual system relates to the large-scale functional brain networks. To address these issues, we conducted multivariate pattern analyses on fMRI data. 40 participants performed three tasks-lexical decision, sound judgment, and action judgment-on written words. We found that (1) conceptual feature representations are strongly modulated by the task, (2) conceptual representations in several multimodal regions are cross-modal, and (3) conceptual feature retrieval involves the default, frontoparietal control, and dorsal attention networks. Conceptual representations in these large-scale networks are task-dependent and cross-modal. Our findings support theories that assume conceptual processing to rely on a flexible, multi-level architecture.
Collapse
Affiliation(s)
- Philipp Kuhnke
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany; Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | | | - Gesa Hartwigsen
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany; Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| |
Collapse
|
41
|
Peelen MV, Downing PE. Testing cognitive theories with multivariate pattern analysis of neuroimaging data. Nat Hum Behav 2023; 7:1430-1441. [PMID: 37591984 PMCID: PMC7616245 DOI: 10.1038/s41562-023-01680-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 07/12/2023] [Indexed: 08/19/2023]
Abstract
Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the 'how' of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions.
Collapse
Affiliation(s)
- Marius V Peelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
| | - Paul E Downing
- Cognitive Neuroscience Institute, Department of Psychology, Bangor University, Bangor, UK.
| |
Collapse
|
42
|
Rae CL, Raykov P, Ambridge EM, Colling LJ, Gould van Praag CD, Bouyagoub S, Polanski L, Larsson DEO, Critchley HD. Elevated representational similarity of voluntary action and inhibition in Tourette syndrome. Brain Commun 2023; 5:fcad224. [PMID: 37705680 PMCID: PMC10497185 DOI: 10.1093/braincomms/fcad224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 06/07/2023] [Accepted: 08/15/2023] [Indexed: 09/15/2023] Open
Abstract
Many people with Tourette syndrome are able to volitionally suppress tics, under certain circumstances. To understand better the neural mechanisms that underlie this ability, we used functional magnetic resonance neuroimaging to track regional brain activity during performance of an intentional inhibition task. On some trials, Tourette syndrome and comparison participants internally chose to make or withhold a motor action (a button press), while on other trials, they followed 'Go' and 'NoGo' instructions to make or withhold the same action. Using representational similarity analysis, a functional magnetic resonance neuroimaging multivariate pattern analysis technique, we assessed how Tourette syndrome and comparison participants differed in neural activity when choosing to make or to withhold an action, relative to externally cued responses on Go and NoGo trials. Analyses were pre-registered, and the data and code are publicly available. We considered similarity of action representations within regions implicated as critical to motor action release or inhibition and to symptom expression in Tourette syndrome, namely the pre-supplementary motor area, inferior frontal gyrus, insula, caudate nucleus and primary motor cortex. Strikingly, in the Tourette syndrome compared to the comparison group, neural activity within the pre-supplementary motor area displayed greater representational similarity across all action types. Within the pre-supplementary motor area, there was lower response-specific differentiation of activity relating to action and inhibition plans and to internally chosen and externally cued actions, implicating the region as a functional nexus in the symptomatology of Tourette syndrome. Correspondingly, patients with Tourette syndrome may experience volitional tic suppression as an effortful and tiring process because, at the top of the putative motor decision hierarchy, activity within the population of neurons facilitating action is overly similar to activity within the population of neurons promoting inhibition. However, not all pre-supplementary motor area group differences survived correction for multiple comparisons. Group differences in representational similarity were also present in the primary motor cortex. Here, representations of internally chosen and externally cued inhibition were more differentiated in the Tourette syndrome group than in the comparison group, potentially a consequence of a weaker voluntary capacity earlier in the motor hierarchy to suppress actions proactively. Tic severity and premonitory sensations correlated with primary motor cortex and caudate nucleus representational similarity, but these effects did not survive correction for multiple comparisons. In summary, more rigid pre-supplementary motor area neural coding across action categories may constitute a central feature of Tourette syndrome, which can account for patients' experience of 'unvoluntary' tics and effortful tic suppression.
Collapse
Affiliation(s)
- Charlotte L Rae
- School of Psychology, University of Sussex, Brighton BN1 9QH, UK
| | - Petar Raykov
- School of Psychology, University of Sussex, Brighton BN1 9QH, UK
| | | | | | | | - Samira Bouyagoub
- Department of Neuroscience, Brighton & Sussex Medical School, Brighton BN1 9RY, UK
| | - Liliana Polanski
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - Dennis E O Larsson
- School of Psychology, University of Sussex, Brighton BN1 9QH, UK
- Department of Neuroscience, Brighton & Sussex Medical School, Brighton BN1 9RY, UK
| | - Hugo D Critchley
- Department of Neuroscience, Brighton & Sussex Medical School, Brighton BN1 9RY, UK
- Sussex Partnership NHS Foundation Trust, Worthing BN3 7HZ, UK
| |
Collapse
|
43
|
Schütt HH, Kipnis AD, Diedrichsen J, Kriegeskorte N. Statistical inference on representational geometries. eLife 2023; 12:e82566. [PMID: 37610302 PMCID: PMC10446828 DOI: 10.7554/elife.82566] [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: 08/09/2022] [Accepted: 08/07/2023] [Indexed: 08/24/2023] Open
Abstract
Neuroscience has recently made much progress, expanding the complexity of both neural activity measurements and brain-computational models. However, we lack robust methods for connecting theory and experiment by evaluating our new big models with our new big data. Here, we introduce new inference methods enabling researchers to evaluate and compare models based on the accuracy of their predictions of representational geometries: A good model should accurately predict the distances among the neural population representations (e.g. of a set of stimuli). Our inference methods combine novel 2-factor extensions of crossvalidation (to prevent overfitting to either subjects or conditions from inflating our estimates of model accuracy) and bootstrapping (to enable inferential model comparison with simultaneous generalization to both new subjects and new conditions). We validate the inference methods on data where the ground-truth model is known, by simulating data with deep neural networks and by resampling of calcium-imaging and functional MRI data. Results demonstrate that the methods are valid and conclusions generalize correctly. These data analysis methods are available in an open-source Python toolbox (rsatoolbox.readthedocs.io).
Collapse
Affiliation(s)
- Heiko H Schütt
- Zuckerman Institute, Columbia UniversityNew YorkUnited States
| | | | | | | |
Collapse
|
44
|
Nebe S, Reutter M, Baker DH, Bölte J, Domes G, Gamer M, Gärtner A, Gießing C, Gurr C, Hilger K, Jawinski P, Kulke L, Lischke A, Markett S, Meier M, Merz CJ, Popov T, Puhlmann LMC, Quintana DS, Schäfer T, Schubert AL, Sperl MFJ, Vehlen A, Lonsdorf TB, Feld GB. Enhancing precision in human neuroscience. eLife 2023; 12:e85980. [PMID: 37555830 PMCID: PMC10411974 DOI: 10.7554/elife.85980] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/23/2023] [Indexed: 08/10/2023] Open
Abstract
Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.
Collapse
Affiliation(s)
- Stephan Nebe
- Zurich Center for Neuroeconomics, Department of Economics, University of ZurichZurichSwitzerland
| | - Mario Reutter
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
| | - Daniel H Baker
- Department of Psychology and York Biomedical Research Institute, University of YorkYorkUnited Kingdom
| | - Jens Bölte
- Institute for Psychology, University of Münster, Otto-Creuzfeldt Center for Cognitive and Behavioral NeuroscienceMünsterGermany
| | - Gregor Domes
- Department of Biological and Clinical Psychology, University of TrierTrierGermany
- Institute for Cognitive and Affective NeuroscienceTrierGermany
| | - Matthias Gamer
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
| | - Anne Gärtner
- Faculty of Psychology, Technische Universität DresdenDresdenGermany
| | - Carsten Gießing
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University of OldenburgOldenburgGermany
| | - Caroline Gurr
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe UniversityFrankfurtGermany
- Brain Imaging Center, Goethe UniversityFrankfurtGermany
| | - Kirsten Hilger
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
- Department of Psychology, Psychological Diagnostics and Intervention, Catholic University of Eichstätt-IngolstadtEichstättGermany
| | - Philippe Jawinski
- Department of Psychology, Humboldt-Universität zu BerlinBerlinGermany
| | - Louisa Kulke
- Department of Developmental with Educational Psychology, University of BremenBremenGermany
| | - Alexander Lischke
- Department of Psychology, Medical School HamburgHamburgGermany
- Institute of Clinical Psychology and Psychotherapy, Medical School HamburgHamburgGermany
| | - Sebastian Markett
- Department of Psychology, Humboldt-Universität zu BerlinBerlinGermany
| | - Maria Meier
- Department of Psychology, University of KonstanzKonstanzGermany
- University Psychiatric Hospitals, Child and Adolescent Psychiatric Research Department (UPKKJ), University of BaselBaselSwitzerland
| | - Christian J Merz
- Department of Cognitive Psychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University BochumBochumGermany
| | - Tzvetan Popov
- Department of Psychology, Methods of Plasticity Research, University of ZurichZurichSwitzerland
| | - Lara MC Puhlmann
- Leibniz Institute for Resilience ResearchMainzGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Daniel S Quintana
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- NevSom, Department of Rare Disorders & Disabilities, Oslo University HospitalOsloNorway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), University of OsloOsloNorway
| | - Tim Schäfer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe UniversityFrankfurtGermany
- Brain Imaging Center, Goethe UniversityFrankfurtGermany
| | | | - Matthias FJ Sperl
- Department of Clinical Psychology and Psychotherapy, University of GiessenGiessenGermany
- Center for Mind, Brain and Behavior, Universities of Marburg and GiessenGiessenGermany
| | - Antonia Vehlen
- Department of Biological and Clinical Psychology, University of TrierTrierGermany
| | - Tina B Lonsdorf
- Department of Systems Neuroscience, University Medical Center Hamburg-EppendorfHamburgGermany
- Department of Psychology, Biological Psychology and Cognitive Neuroscience, University of BielefeldBielefeldGermany
| | - Gordon B Feld
- Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
- Department of Psychology, Heidelberg UniversityHeidelbergGermany
- Department of Addiction Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
| |
Collapse
|
45
|
Wei J, Yao Z, Huang G, Li L, Liang Z, Zhang L, Zhang Z. Frontal-occipital phase synchronization predicts occipital alpha power in perceptual decision-making. Cogn Neurodyn 2023; 17:815-827. [PMID: 37522043 PMCID: PMC10374503 DOI: 10.1007/s11571-022-09862-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/19/2022] [Accepted: 07/21/2022] [Indexed: 11/03/2022] Open
Abstract
Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4-30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09862-7.
Collapse
Affiliation(s)
- Jinwen Wei
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China
| | - Ziqing Yao
- Department of Psychology, The University of Hong Kong, Hong Kong S.A.R, China
| | - Gan Huang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China
| | - Linling Li
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China
| | - Zhen Liang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China
| | - Li Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China
| | - Zhiguo Zhang
- Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| |
Collapse
|
46
|
Klautke J, Foster C, Medendorp WP, Heed T. Dynamic spatial coding in parietal cortex mediates tactile-motor transformation. Nat Commun 2023; 14:4532. [PMID: 37500625 PMCID: PMC10374589 DOI: 10.1038/s41467-023-39959-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 07/05/2023] [Indexed: 07/29/2023] Open
Abstract
Movements towards touch on the body require integrating tactile location and body posture information. Tactile processing and movement planning both rely on posterior parietal cortex (PPC) but their interplay is not understood. Here, human participants received tactile stimuli on their crossed and uncrossed feet, dissociating stimulus location relative to anatomy versus external space. Participants pointed to the touch or the equivalent location on the other foot, which dissociates sensory and motor locations. Multi-voxel pattern analysis of concurrently recorded fMRI signals revealed that tactile location was coded anatomically in anterior PPC but spatially in posterior PPC during sensory processing. After movement instructions were specified, PPC exclusively represented the movement goal in space, in regions associated with visuo-motor planning and with regional overlap for sensory, rule-related, and movement coding. Thus, PPC flexibly updates its spatial codes to accommodate rule-based transformation of sensory input to generate movement to environment and own body alike.
Collapse
Affiliation(s)
- Janina Klautke
- Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany
| | - Celia Foster
- Biopsychology & Cognitive Neuroscience, Bielefeld University, Bielefeld, Germany
- Center of Excellence in Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - W Pieter Medendorp
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Tobias Heed
- Biopsychology & Cognitive Neuroscience, Bielefeld University, Bielefeld, Germany.
- Center of Excellence in Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.
- Cognitive Psychology, Department of Psychology, University of Salzburg, Salzburg, Austria.
- Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
| |
Collapse
|
47
|
Vishne G, Gerber EM, Knight RT, Deouell LY. Distinct ventral stream and prefrontal cortex representational dynamics during sustained conscious visual perception. Cell Rep 2023; 42:112752. [PMID: 37422763 PMCID: PMC10530642 DOI: 10.1016/j.celrep.2023.112752] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 05/12/2023] [Accepted: 06/20/2023] [Indexed: 07/11/2023] Open
Abstract
Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on transient onset responses. This presents a critical challenge for neural theories of consciousness, which should account for the full temporal extent of experience. To address this question, we use intracranial recordings from ten human patients with epilepsy to view diverse images of multiple durations. We reveal that, in sensory regions, despite dramatic changes in activation magnitude, the distributed representation of categories and exemplars remains sustained and stable. In contrast, in frontoparietal regions, we find transient content representation at stimulus onset. Our results highlight the connection between the anatomical and temporal correlates of experience. To the extent perception is sustained, it may rely on sensory representations and to the extent perception is discrete, centered on perceptual updating, it may rely on frontoparietal representations.
Collapse
Affiliation(s)
- Gal Vishne
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
| | - Edden M Gerber
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Robert T Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Leon Y Deouell
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Department of Psychology, The Hebrew University of Jerusalem, Jerusalem 9190501, Israel.
| |
Collapse
|
48
|
Cheng ZJ, Yang L, Zhang WH, Zhang RY. Representational Geometries Reveal Differential Effects of Response Correlations on Population Codes in Neurophysiology and Functional Magnetic Resonance Imaging. J Neurosci 2023; 43:4498-4512. [PMID: 37188515 PMCID: PMC10278677 DOI: 10.1523/jneurosci.2228-22.2023] [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: 12/05/2022] [Revised: 04/05/2023] [Accepted: 05/06/2023] [Indexed: 05/17/2023] Open
Abstract
Two sensory neurons usually display trial-by-trial spike-count correlations given the repeated representations of a stimulus. The effects of such response correlations on population-level sensory coding have been the focal contention in computational neuroscience over the past few years. In the meantime, multivariate pattern analysis (MVPA) has become the leading analysis approach in functional magnetic resonance imaging (fMRI), but the effects of response correlations among voxel populations remain underexplored. Here, instead of conventional MVPA analysis, we calculate linear Fisher information of population responses in human visual cortex (five males, one female) and hypothetically remove response correlations between voxels. We found that voxelwise response correlations generally enhance stimulus information, a result standing in stark contrast to the detrimental effects of response correlations reported in empirical neurophysiological studies. By voxel-encoding modeling, we further show that these two seemingly opposite effects actually can coexist within the primate visual system. Furthermore, we use principal component analysis to decompose stimulus information in population responses onto different principal dimensions in a high-dimensional representational space. Interestingly, response correlations simultaneously reduce and enhance information on higher- and lower-variance principal dimensions, respectively. The relative strength of the two antagonistic effects within the same computational framework produces the apparent discrepancy in the effects of response correlations in neuronal and voxel populations. Our results suggest that multivariate fMRI data contain rich statistical structures that are directly related to sensory information representation, and the general computational framework to analyze neuronal and voxel population responses can be applied in many types of neural measurements.SIGNIFICANCE STATEMENT Despite the vast research interest in the effect of spike-count noise correlations on population codes in neurophysiology, it remains unclear how the response correlations between voxels influence MVPA in human imaging. We used an information-theoretic approach and showed that unlike the detrimental effects of response correlations reported in neurophysiology, voxelwise response correlations generally improve sensory coding. We conducted a series of in-depth analyses and demonstrated that neuronal and voxel response correlations can coexist within the visual system and share some common computational mechanisms. These results shed new light on how the population codes of sensory information can be evaluated via different neural measurements.
Collapse
Affiliation(s)
- Zi-Jian Cheng
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
- Institute of Psychology and Behavioral Science, Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Lingxiao Yang
- School of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
| | - Wen-Hao Zhang
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas 75390
- O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390
| | - Ru-Yuan Zhang
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
- Institute of Psychology and Behavioral Science, Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200241, China
| |
Collapse
|
49
|
Lv X, Funahashi S, Li C, Wu J. Variational relevance evaluation of individual fMRI data enables deconstruction of task-dependent neural dynamics. Commun Biol 2023; 6:491. [PMID: 37147471 PMCID: PMC10163018 DOI: 10.1038/s42003-023-04804-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 04/04/2023] [Indexed: 05/07/2023] Open
Abstract
In neuroimaging research, univariate analysis has always been used to localize "representations" at the microscale, whereas network approaches have been applied to characterize transregional "operations". How are representations and operations linked through dynamic interactions? We developed the variational relevance evaluation (VRE) method to analyze individual task fMRI data, which selects informative voxels during model training to localize the "representation", and quantifies the dynamic contributions of single voxels across the whole-brain to different cognitive functions to characterize the "operation". Using 15 individual fMRI data files for higher visual area localizers, we evaluated the characterization of selected voxel positions of VRE and revealed different object-selective regions functioning in similar dynamics. Using another 15 individual fMRI data files for memory retrieval after offline learning, we found similar task-related regions working in different neural dynamics for tasks with diverse familiarities. VRE demonstrates a promising horizon in individual fMRI research.
Collapse
Affiliation(s)
- Xiaoyu Lv
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China.
- Researh Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, Guangdong, China.
| |
Collapse
|
50
|
Frank SM, Maechler MR, Fogelson SV, Tse PU. Hierarchical categorization learning is associated with representational changes in the dorsal striatum and posterior frontal and parietal cortex. Hum Brain Mapp 2023; 44:3897-3912. [PMID: 37126607 DOI: 10.1002/hbm.26323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/27/2023] [Accepted: 04/16/2023] [Indexed: 05/03/2023] Open
Abstract
Learning and recognition can be improved by sorting novel items into categories and subcategories. Such hierarchical categorization is easy when it can be performed according to learned rules (e.g., "if car, then automatic or stick shift" or "if boat, then motor or sail"). Here, we present results showing that human participants acquire categorization rules for new visual hierarchies rapidly, and that, as they do, corresponding hierarchical representations of the categorized stimuli emerge in patterns of neural activation in the dorsal striatum and in posterior frontal and parietal cortex. Participants learned to categorize novel visual objects into a hierarchy with superordinate and subordinate levels based on the objects' shape features, without having been told the categorization rules for doing so. On each trial, participants were asked to report the category and subcategory of the object, after which they received feedback about the correctness of their categorization responses. Participants trained over the course of a one-hour-long session while their brain activation was measured using functional magnetic resonance imaging. Over the course of training, significant hierarchy learning took place as participants discovered the nested categorization rules, as evidenced by the occurrence of a learning trial, after which performance suddenly increased. This learning was associated with increased representational strength of the newly acquired hierarchical rules in a corticostriatal network including the posterior frontal and parietal cortex and the dorsal striatum. We also found evidence suggesting that reinforcement learning in the dorsal striatum contributed to hierarchical rule learning.
Collapse
Affiliation(s)
- Sebastian M Frank
- Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Marvin R Maechler
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA
| | - Sergey V Fogelson
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA
- Katz School of Science and Health, Yeshiva University, New York, New York, USA
| | - Peter U Tse
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA
| |
Collapse
|