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Klar P, Çatal Y, Jocham G, Langner R, Northoff G. Time-dependent scale-free brain dynamics during naturalistic inputs. Neuroimage 2025; 314:121255. [PMID: 40347997 DOI: 10.1016/j.neuroimage.2025.121255] [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: 08/05/2024] [Revised: 01/20/2025] [Accepted: 05/08/2025] [Indexed: 05/14/2025] Open
Abstract
Environmental processes, such as auditory and visual inputs, often follow power-law distributions with a time-dependent and constantly changing spectral exponent, β(t). However, it remains unclear how the brain's scale-free dynamics continuously respond to naturalistic inputs, such as by potentially alternating instead of static levels of the spectral exponent. Our fMRI study investigates the brain's dynamic, time-dependent spectral exponent, β(t), during movie-watching, and uses time-varying inter-subject correlation, ISC(t), to assess the extent to which input dynamics are reflected as shared brain activity across subjects in early sensory regions. Notably, we investigate the level of ISC particularly based on the modulation by time-dependent scale-free dynamics or β(t). We obtained three key findings: First, the brain's β(t) showed a distinct temporal structure in visual and auditory regions during naturalistic inputs compared to the resting-state, investigated in the 7 Tesla Human Connectome Project dataset. Second, β(t) and ISC(t) were positively correlated during naturalistic inputs. Third, grouping subjects based on the Rest-to-Movie standard deviation change of the time-dependent spectral exponent β(t) revealed that the brain's relative shift from intrinsic to stimulus-driven scale-free dynamics modulates the level of shared brain activity, or ISC(t), and thus the imprinting of inputs on brain activity. This modulation was further supported by the observation that the two groups displayed significantly different β(t)-ISC(t) correlations, where the group with a higher mean of ISC(t) during inputs also exhibited a higher β(t)-ISC(t) correlation in visual and auditory regions. In summary, our fMRI study underscores a positive relationship between time-dependent scale-free dynamics and ISC, where higher spectral exponents correspond to higher degrees of shared brain activity during ongoing audiovisual inputs.
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Affiliation(s)
- Philipp Klar
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, Ontario K1Z 7K4, Canada
| | - Gerhard Jocham
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Georg Northoff
- University of Ottawa, Institute of Mental Health Research at the Royal Ottawa Hospital, 145 Carling Avenue, Rm. 6435, Ottawa, Ontario K1Z 7K4, Canada
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2
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Northoff G, Ventura B. Bridging the gap of brain and experience - Converging Neurophenomenology with Spatiotemporal Neuroscience. Neurosci Biobehav Rev 2025; 173:106139. [PMID: 40204159 DOI: 10.1016/j.neubiorev.2025.106139] [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: 01/31/2025] [Revised: 03/13/2025] [Accepted: 04/05/2025] [Indexed: 04/11/2025]
Abstract
Neuroscience faces the challenge of connecting brain and mind, with the mind manifesting in first-person experience while the brain's neural activity can only be investigated in third-person perspective. To connect neural and mental states, Neurophenomenology provides a methodological toolkit for systematically linking first-person subjective experience with third-person objective observations of the brain's neural activity. However, beyond providing a systematic methodological strategy ('disciplined circularity'), it leaves open how neural activity and subjective experience are related among themselves, independent of our methodological strategy. The recently introduced Spatiotemporal Neuroscience suggests that neural activity and subjective experience share a commonly underlying feature as their "common currency", notably analogous spatiotemporal dynamics. Can Spatiotemporal Neuroscience inform Neurophenomenology to allow for a deeper and more substantiative connection of first-person experience and third-person neural activity? The goal of our paper is to show how Spatiotemporal Neuroscience and Neurophenomenology can be converged and integrated with each other to gain better understanding of the brain-mind connection. We describe their convergence on theoretical grounds which, subsequently, is illustrated by empirical examples like self, meditation, and depression. In conclusion, we propose that the integration of Neurophenomenology and Spatiotemporal Neuroscience can provide complementary insights, enrich both fields, allows for deeper understanding of brain-mind connection, and opens the door for developing novel methodological approaches in their empirical investigation.
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Affiliation(s)
- Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada.
| | - Bianca Ventura
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada; School of Psychology, University of Ottawa, 136 Jean-Jacques Lussier, Ottawa, ON K1N 6N5, Canada.
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3
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Pang R, Baker CA, Murthy M, Pillow J. Inferring neural population codes for Drosophila acoustic communication. Proc Natl Acad Sci U S A 2025; 122:e2417733122. [PMID: 40388613 DOI: 10.1073/pnas.2417733122] [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: 09/09/2024] [Accepted: 03/26/2025] [Indexed: 05/21/2025] Open
Abstract
Social communication between animals is often mediated by sequences of acoustic signals, sometimes spanning long timescales. How auditory neural circuits respond to extended input sequences to guide behavior is not understood. We address this problem using Drosophila acoustic communication, a behavior involving the male's production of and female's response to long, highly variable courtship songs. Here we ask whether female neural and behavioral responses to song are better described by a linear-nonlinear feature detection model vs. a nonlinear accumulation model. Comparing both models against head-fixed neural recordings and pure-behavioral recordings of unrestrained courtship, we found that while both models could explain the neural data, the accumulation model better predicted female locomotion during courtship, outperforming several alternative predictors. To understand how the accumulation model encoded song to predict locomotion, we analyzed the relationship between neural activity simulated by the model and female locomotion during courtship-this revealed the model's reliance on heterogeneous nonlinear adaptation and slow integration. Finally, we asked how adaptation and integration processes could cooperate across the model neural population to encode temporal patterns in song. Simulations revealed how adaptation can transform song inputs prior to integration, allowing fine-scale song information to be retained in the population code for long periods. Thus, modeling fly auditory responses as a nonlinearly adaptive, accumulating population code accounts for female locomotor responses to song during courtship and suggests a biologically plausible mechanism for the online encoding of extended communication sequences.
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Affiliation(s)
- Rich Pang
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540
| | - Christa A Baker
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540
| | - Jonathan Pillow
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540
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4
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Zhou H, Wu J, Li J, Pan Z, Lu J, Shen M, Wang T, Hu Y, Gao Z. Event cache: An independent component in working memory. SCIENCE ADVANCES 2025; 11:eadt3063. [PMID: 40408491 PMCID: PMC12101497 DOI: 10.1126/sciadv.adt3063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Accepted: 04/22/2025] [Indexed: 05/25/2025]
Abstract
Working memory (WM) has been a major focus of cognitive science and neuroscience for the past 50 years. While most WM research has centered on the mechanisms of objects, there has been a lack of investigation into the cognitive and neural mechanisms of events, which are the building blocks of our experience. Using confirmatory factor analysis, psychophysical experiments, and resting-state and task functional magnetic resonance imaging methods, our study demonstrated that events have an independent storage space within WM, named as event cache, with distinct neural correlates compared to object storage in WM. We found the cerebellar network to be the most essential network for event cache, with the left cerebellum Crus I being particularly involved in encoding and maintaining events. Our findings shed critical light on the neuropsychological mechanism of WM by revealing event cache as an independent component of WM and encourage the reconsideration of theoretical models for WM.
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Affiliation(s)
- Hui Zhou
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou 310058, China
| | - Jinglan Wu
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jiaofeng Li
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zhihe Pan
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jinying Lu
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Mowei Shen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Tengfei Wang
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yuzheng Hu
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou 310058, China
- MOE Frontiers Science Center for Brain Science & Brain-Machine Integration, Zhejiang University, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311121, China
| | - Zaifeng Gao
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
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5
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Soyuhos O, Zirnsak M, Moore T, Chaudhuri R, Chen X. Selective control of prefrontal neural timescales by parietal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.09.30.615928. [PMID: 39896639 PMCID: PMC11785006 DOI: 10.1101/2024.09.30.615928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
Intrinsic neural timescales quantify how long spontaneous neuronal activity patterns persist, reflecting dynamics of endogenous fluctuations. We measured intrinsic timescales of frontal eye field (FEF) neurons and examined their changes during posterior parietal cortex (PPC) inactivation. We observed two distinct classes of FEF neurons based on their intrinsic timescales: short-timescale neurons (∼25 ms) or long-timescale neurons (∼100 ms). Short-timescale neurons showed stronger transient visual responses, suggesting their role in rapid visual processing, whereas long-timescale neurons exhibited pronounced sustained attentional modulation, suggesting their role in maintaining stimulus-driven attention. During PPC inactivation, intrinsic timescales increased in both neuron types, with a significantly larger effect in short-timescale neurons. In addition, PPC inactivation reduced attentional modulation, particularly in long-timescale neurons. Our findings provide the first causal evidence linking intrinsic local neural timescales to long-range inter-area communications. These findings also suggest the presence of at least two distinct network motifs that support different neuronal dynamics and functional computations within the FEF.
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Goldstein A, Wang H, Niekerken L, Schain M, Zada Z, Aubrey B, Sheffer T, Nastase SA, Gazula H, Singh A, Rao A, Choe G, Kim C, Doyle W, Friedman D, Devore S, Dugan P, Hassidim A, Brenner M, Matias Y, Devinsky O, Flinker A, Hasson U. A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations. Nat Hum Behav 2025; 9:1041-1055. [PMID: 40055549 PMCID: PMC12106081 DOI: 10.1038/s41562-025-02105-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 01/09/2025] [Indexed: 05/28/2025]
Abstract
This study introduces a unified computational framework connecting acoustic, speech and word-level linguistic structures to study the neural basis of everyday conversations in the human brain. We used electrocorticography to record neural signals across 100 h of speech production and comprehension as participants engaged in open-ended real-life conversations. We extracted low-level acoustic, mid-level speech and contextual word embeddings from a multimodal speech-to-text model (Whisper). We developed encoding models that linearly map these embeddings onto brain activity during speech production and comprehension. Remarkably, this model accurately predicts neural activity at each level of the language processing hierarchy across hours of new conversations not used in training the model. The internal processing hierarchy in the model is aligned with the cortical hierarchy for speech and language processing, where sensory and motor regions better align with the model's speech embeddings, and higher-level language areas better align with the model's language embeddings. The Whisper model captures the temporal sequence of language-to-speech encoding before word articulation (speech production) and speech-to-language encoding post articulation (speech comprehension). The embeddings learned by this model outperform symbolic models in capturing neural activity supporting natural speech and language. These findings support a paradigm shift towards unified computational models that capture the entire processing hierarchy for speech comprehension and production in real-world conversations.
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Affiliation(s)
- Ariel Goldstein
- Department of Cognitive and Brain Sciences and Business School, Hebrew University, Jerusalem, Israel.
- Google Research, Mountain View, CA, USA.
| | - Haocheng Wang
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Leonard Niekerken
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | - Zaid Zada
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Bobbi Aubrey
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Samuel A Nastase
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Harshvardhan Gazula
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Aditi Singh
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Aditi Rao
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Gina Choe
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Catherine Kim
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Werner Doyle
- New York University School of Medicine, New York, NY, USA
| | | | - Sasha Devore
- New York University School of Medicine, New York, NY, USA
| | - Patricia Dugan
- New York University School of Medicine, New York, NY, USA
| | | | - Michael Brenner
- Google Research, Mountain View, CA, USA
- School of Engineering and Applied Science, Harvard University, Boston, MA, USA
| | | | - Orrin Devinsky
- New York University School of Medicine, New York, NY, USA
| | - Adeen Flinker
- New York University School of Medicine, New York, NY, USA
| | - Uri Hasson
- Department of Psychology and the Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
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7
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Ma Y, Vafaie N, Kragel PA. Embedding emotion concepts in cognitive maps. Neurosci Biobehav Rev 2025; 172:106089. [PMID: 40057255 DOI: 10.1016/j.neubiorev.2025.106089] [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: 11/25/2024] [Revised: 02/17/2025] [Accepted: 03/03/2025] [Indexed: 03/14/2025]
Abstract
Emotion knowledge is organized in a two-dimensional space known as the affective circumplex, which is thought to develop from core affective feelings and the co-occurrence of emotional events. Neural studies reveal that emotion concepts and cognitive maps of space and abstract concepts are represented in hippocampal-prefrontal systems. We propose that the circumplex is formed by learning the transitions between emotion concepts, a process mediated by a reciprocal network involving hippocampal cells that encode emotion concepts and grid cells in medial entorhinal and ventral prefrontal cortices that encode the relations between them. We anticipate that testing this hypothesis will shed light on the debate about whether emotions are biologically basic or constructed from core affective dimensions.
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Affiliation(s)
- Yumeng Ma
- Department of Psychology, Emory University, USA
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8
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Kolibius LD, Josselyn SA, Hanslmayr S. On the origin of memory neurons in the human hippocampus. Trends Cogn Sci 2025; 29:421-433. [PMID: 40037964 DOI: 10.1016/j.tics.2025.01.013] [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: 09/03/2024] [Revised: 01/22/2025] [Accepted: 01/27/2025] [Indexed: 03/06/2025]
Abstract
The hippocampus is essential for episodic memory, yet its coding mechanism remains debated. In humans, two main theories have been proposed: one suggests that concept neurons represent specific elements of an episode, while another posits a conjunctive code, where index neurons code the entire episode. Here, we integrate new findings of index neurons in humans and other animals with the concept-specific memory framework, proposing that concept neurons evolve from index neurons through overlapping memories. This process is supported by engram literature, which posits that neurons are allocated to a memory trace based on excitability and that reactivation induces excitability. By integrating these insights, we connect two historically disparate fields of neuroscience: engram research and human single neuron episodic memory research.
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Affiliation(s)
- Luca D Kolibius
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA.
| | - Sheena A Josselyn
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada; Department of Psychology, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Simon Hanslmayr
- School of Psychology and Neuroscience and Centre for Neurotechnology, University of Glasgow, Glasgow, UK; Centre for Neurotechnology, University of Glasgow, Glasgow, UK.
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9
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Duffy JS, Bellgrove MA, Murphy PR, O'Connell RG. Disentangling sources of variability in decision-making. Nat Rev Neurosci 2025; 26:247-262. [PMID: 40114010 DOI: 10.1038/s41583-025-00916-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/26/2025] [Indexed: 03/22/2025]
Abstract
Even the most highly-trained observers presented with identical choice-relevant stimuli will reliably exhibit substantial trial-to-trial variability in the timing and accuracy of their choices. Despite being a pervasive feature of choice behaviour and a prominent phenotype for numerous clinical disorders, the capability to disentangle the sources of such intra-individual variability (IIV) remains limited. In principle, computational models of decision-making offer a means of parsing and estimating these sources, but methodological limitations have prevented this potential from being fully realized in practice. In this Review, we first discuss current limitations of algorithmic models for understanding variability in decision-making behaviour. We then highlight recent advances in behavioural paradigm design, novel analyses of cross-trial behavioural and neural dynamics, and the development of neurally grounded computational models that are now making it possible to link distinct components of IIV to well-defined neural processes. Taken together, we demonstrate how these methods are opening up new avenues for systematically analysing the neural origins of IIV, paving the way for a more refined, holistic understanding of decision-making in health and disease.
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Affiliation(s)
- Jade S Duffy
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Mark A Bellgrove
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Peter R Murphy
- Department of Psychology, Maynooth University, Kildare, Ireland
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland.
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10
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Aili R, Zhou S, Xu X, He X, Lu C. The cortical architecture representing the linguistic hierarchy of the conversational speech. Neuroimage 2025; 311:121180. [PMID: 40158671 DOI: 10.1016/j.neuroimage.2025.121180] [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: 09/10/2024] [Revised: 03/24/2025] [Accepted: 03/28/2025] [Indexed: 04/02/2025] Open
Abstract
Recent studies demonstrate that the brain parses natural language into smaller units represented in lower-order regions and larger units in higher-order regions. Most of these studies, however, have been conducted on unidirectional narrative speech, leaving the linguistic hierarchy and its cortical representation in bidirectional conversational speech unexplored. To address this gap, we simultaneously measured brain activity from two individuals using functional near-infrared spectroscopy (fNIRS) hyperscanning while they engaged in a naturalistic conversation. Using a Pre-trained Language Model (PLM) and Representational Similarity Analysis (RSA), we demonstrated that conversational speech, jointly produced by two interlocutors in a turn-taking manner, exhibits a linguistic hierarchy, characterized by a boundary effect between linguistic units and an incremental context effect. Furthermore, a gradient pattern of shared cortical representation of the linguistic hierarchy was identified at the dyadic rather than the individual level. Interpersonal neural synchronization (INS) in the left superior temporal cortex was associated with turn representation, whereas INS in the medial prefrontal cortex was linked to topic representation. These findings further validated the distinctiveness of linguistic units of different sizes. Together, our results provide original evidence for the linguistic hierarchy and the underlying cortical architecture during a naturalistic conversation, extending the hierarchical nature of natural language from unidirectional narrative speech to bidirectional conversational speech.
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Affiliation(s)
- Ruhuiya Aili
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Siyuan Zhou
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, 610066, China
| | - Xinran Xu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xiangyu He
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Chunming Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
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11
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Chen Y, Zada Z, Nastase SA, Ashby FG, Ghosh SS. Context modulates brain state dynamics and behavioral responses during narrative comprehension. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.04.05.647323. [PMID: 40236133 PMCID: PMC11996513 DOI: 10.1101/2025.04.05.647323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/17/2025]
Abstract
Narrative comprehension is inherently context-sensitive, yet the brain and cognitive mechanisms by which brief contextual priming shapes story interpretation remain unclear. Using hidden Markov modeling (HMM) of fMRI data, we identified dynamic brain states as participants listened to an ambiguous spoken story under two distinct narrative contexts (affair vs. paranoia). We uncovered both context-invariant states-engaging auditory, language, and default mode networks-and context-specific states characterized by differential recruitment of control, salience, and visual networks. Narrative context selectively modulated the influence of character speech and linguistic features on brain state expression, with the central character's speech enhancing activation in shared states but suppressing activation in context-specific ones. Independent behavioral analyses revealed parallel context-dependent effects, with character-driven features exerting strong, selectively modulated influences on participants' judgments of narrative evidence. These findings demonstrate that brief narrative priming actively reshapes brain state dynamics and feature sensitivity during story comprehension, revealing how context guides moment-by-moment interpretive processing in naturalistic settings.
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12
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Katsumi Y, Howe IA, Eckbo R, Wong B, Quimby M, Hochberg D, McGinnis SM, Putcha D, Wolk DA, Touroutoglou A, Dickerson BC. Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease. Brain 2025; 148:1329-1344. [PMID: 39412999 PMCID: PMC11969453 DOI: 10.1093/brain/awae327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 08/31/2024] [Accepted: 10/01/2024] [Indexed: 10/18/2024] Open
Abstract
Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11-0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.
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Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Inola A Howe
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Daisy Hochberg
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain/Mind Medicine, Department of Neurology, Brigham & Women’s Hospital, Boston, MA 02115, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain/Mind Medicine, Department of Neurology, Brigham & Women’s Hospital, Boston, MA 02115, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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13
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Wahlheim CN, Zacks JM. Memory updating and the structure of event representations. Trends Cogn Sci 2025; 29:380-392. [PMID: 39668061 PMCID: PMC12103877 DOI: 10.1016/j.tics.2024.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2024] [Revised: 11/16/2024] [Accepted: 11/18/2024] [Indexed: 12/14/2024]
Abstract
People form memories of specific events and use those memories to make predictions about similar new experiences. Living in a dynamic environment presents a challenge: How does one represent valid prior events in memory while encoding new experiences when things change? There is evidence for two seemingly contradictory classes of mechanism: One differentiates outdated event features by making them less similar or less accessible than updated event features. The other integrates updated features of new events with outdated memories, and the relationship between them, into a structured representation. Integrative encoding may occur when changed events trigger inaccurate predictions based on remembered prior events. We propose that this promotes subsequent recollection of events and their order, enabling adaptation to environmental changes.
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Affiliation(s)
- Christopher N Wahlheim
- Department of Psychology, The University of North Carolina at Greensboro, Greensboro, NC 27402, USA.
| | - Jeffrey M Zacks
- Department of Psychological & Brain Sciences, Washington University in Saint Louis, Saint Louis, MO 63130, USA.
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14
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Liu X, Zhang Z, Gan L, Yu P, Dai J. Medium Spiny Neurons Mediate Timing Perception in Coordination with Prefrontal Neurons in Primates. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2412963. [PMID: 39932056 PMCID: PMC12021029 DOI: 10.1002/advs.202412963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 12/19/2024] [Indexed: 04/26/2025]
Abstract
Timing perception is a fundamental cognitive function that allows organisms to navigate their environment effectively, encompassing both prospective and retrospective timing. Despite significant advancements in understanding how the brain processes temporal information, the neural mechanisms underlying these two forms of timing remain largely unexplored. In this study, it aims to bridge this knowledge gap by elucidating the functional roles of various neuronal populations in the striatum and prefrontal cortex (PFC) in shaping subjective experiences of time. Utilizing a large-scale electrode array, it recorded responses from over 3000 neurons in the striatum and PFC of macaque monkeys during timing tasks. The analysis classified neurons into distinct groups and revealed that retrospective and prospective timings are governed by separate neural processes. Specifically, this study demonstrates that medium spiny neurons (MSNs) in the striatum play a crucial role in facilitating these timing processes. Through cell-type-specific manipulation, it identified D2-MSNs as the primary contributors to both forms of timing. Additionally, the findings indicate that effective processing of timing requires coordination between the PFC and the striatum. In summary, this study advances the understanding of the neural foundations of timing perception and highlights its behavioral implications.
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Affiliation(s)
- Xinhe Liu
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen‐Hong Kong Institutes of Brain ScienceShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- CAS Key Laboratory of Brain Connectome and Manipulationthe Brain Cognition and Brain Disease InstitutesShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- Guangdong Provincial Key Laboratory of Brain Connectome and BehaviorShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
| | - Zhiting Zhang
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen‐Hong Kong Institutes of Brain ScienceShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- CAS Key Laboratory of Brain Connectome and Manipulationthe Brain Cognition and Brain Disease InstitutesShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- Guangdong Provincial Key Laboratory of Brain Connectome and BehaviorShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
| | - Lu Gan
- Research Center for Medical Artificial IntelligenceShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
| | - Panke Yu
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen‐Hong Kong Institutes of Brain ScienceShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- University of Chinese Academy of SciencesBeijing100049China
| | - Ji Dai
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen‐Hong Kong Institutes of Brain ScienceShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- CAS Key Laboratory of Brain Connectome and Manipulationthe Brain Cognition and Brain Disease InstitutesShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- Guangdong Provincial Key Laboratory of Brain Connectome and BehaviorShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
- University of Chinese Academy of SciencesBeijing100049China
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15
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Labendzki P, Goupil L, Wass S. Temporal patterns in the complexity of child-directed song lyrics reflect their functions. COMMUNICATIONS PSYCHOLOGY 2025; 3:48. [PMID: 40128378 PMCID: PMC11933259 DOI: 10.1038/s44271-025-00219-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 02/24/2025] [Indexed: 03/26/2025]
Abstract
Content produced for young audiences is structured to present opportunities for learning and social interactions. This research examines multi-scale temporal changes in predictability in Child-directed songs. We developed a technique based on Kolmogorov complexity to quantify the rate of change of textual information content over time. This method was applied to a corpus of 922 English, Spanish, and French publicly available child and adult-directed texts. Child-directed song lyrics (CDSongs) showed overall lower complexity compared to Adult-directed songs (ADsongs), and lower complexity was associated with a higher number of YouTube views. CDSongs showed a relatively higher information rate at the beginning and end compared to ADSongs. CDSongs and ADSongs showed a non-uniform information rate, but these periodic oscillatory patterns were more predictable in CDSongs compared to ADSongs. These findings suggest that the optimal balance between predictability and expressivity in information content differs between child- and adult-directed content, but also changes over timescales to potentially support multiple children's needs.
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Affiliation(s)
- Pierre Labendzki
- Department of Psychology, University of East London, London, UK.
| | - Louise Goupil
- Université Grenoble Alpes, CNRS, LPNC, Grenoble, France
| | - Sam Wass
- Department of Psychology, University of East London, London, UK
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16
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Luppi AI, Uhrig L, Tasserie J, Shafiei G, Muta K, Hata J, Okano H, Golkowski D, Ranft A, Ilg R, Jordan D, Gini S, Liu ZQ, Yee Y, Signorelli CM, Cofre R, Destexhe A, Menon DK, Stamatakis EA, Connor CW, Gozzi A, Fulcher BD, Jarraya B, Misic B. Comprehensive profiling of anaesthetised brain dynamics across phylogeny. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.22.644729. [PMID: 40196621 PMCID: PMC11974681 DOI: 10.1101/2025.03.22.644729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
The intrinsic dynamics of neuronal circuits shape information processing and cognitive function. Combining non-invasive neuroimaging with anaesthetic-induced suppression of information processing provides a unique opportunity to understand how local dynamics mediate the link between neurobiology and the organism's functional repertoire. To address this question, we compile a unique dataset of multi-scale neural activity during wakefulness and anesthesia encompassing human, macaque, marmoset, mouse and nematode. We then apply massive feature extraction to comprehensively characterize local neural dynamics across > 6 000 time-series features. Using dynamics as a common space for comparison across species, we identify a phylogenetically conserved dynamical profile of anaesthesia that encompasses multiple features, including reductions in intrinsic timescales. This dynamical signature has an evolutionarily conserved spatial layout, covarying with transcriptional profiles of excitatory and inhibitory neurotransmission across human, macaque and mouse cortex. At the network level, anesthetic-induced changes in local dynamics manifest as reductions in inter-regional synchrony. This relationship between local dynamics and global connectivity can be recapitulated in silico using a connectome-based computational model. Finally, this dynamical regime of anaesthesia is experimentally reversed in vivo by deep-brain stimulation of the centromedian thalamus in the macaque, resulting in restored arousal and behavioural responsiveness. Altogether, comprehensive dynamical phenotyping reveals that spatiotemporal isolation of local neural activity during anesthesia is conserved across species and anesthetics.
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Affiliation(s)
- Andrea I. Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Centre for Eudaimonia and Human Flourishing, Department of Psychiatry, University of Oxford, Oxford, UK
- St John’s College, University of Cambridge, Cambridge, UK
| | - Lynn Uhrig
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, Gif-sur-Yvette, France
- Department of Anesthesiology and Critical Care, Necker Hospital, Université de Paris Cité, Paris, France
| | - Jordy Tasserie
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, Gif-sur-Yvette, France
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Golia Shafiei
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kanako Muta
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo, Japan
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama Japan
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo, Japan
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama Japan
- Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo, Japan
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama Japan
- Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo, Japan
| | - Daniel Golkowski
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, Technical University of Munich, Munich, Germany
| | - Rudiger Ilg
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- Asklepios Clinic, Department of Neurology, Bad Tolz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Silvia Gini
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
- Centre for Mind/Brain Sciences, University of Trento, Italy
| | - Zhen-Qi Liu
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Yohan Yee
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Camilo M. Signorelli
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, Gif-sur-Yvette, France
- Center for Philosophy of Artificial Intelligence, University of Copenhagen, Copenhagen, Denmark
| | - Rodrigo Cofre
- Paris-Saclay University, CNRS, Paris-Saclay Institute for Neuroscience (NeuroPSI), Saclay, France
| | - Alain Destexhe
- Paris-Saclay University, CNRS, Paris-Saclay Institute for Neuroscience (NeuroPSI), Saclay, France
| | - David K. Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Emmanuel A. Stamatakis
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Christopher W. Connor
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Biomedical Engineering, Physiology and Biophysics, Boston University, Boston, Massachusetts
| | - Alessandro Gozzi
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Sydney, Australia
| | - Bechir Jarraya
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, Gif-sur-Yvette, France
- Department of Neurology, Foch Hospital, Suresnes, France
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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17
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Hasson U. Uncovering a Timescale Hierarchy by Studying the Brain in a Natural Context. J Neurosci 2025; 45:e2368242025. [PMID: 40107727 PMCID: PMC11924986 DOI: 10.1523/jneurosci.2368-24.2025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2024] [Revised: 01/03/2025] [Accepted: 01/07/2025] [Indexed: 03/22/2025] Open
Abstract
As we train multiple generations of students to narrowly design clever, carefully controlled experiments in our confined lab spaces, we may fail to notice, as a field, that we have overlooked fundamental aspects of human cognition. This is a first-person account of how our research and understanding of the neural code were forever transformed when we decided to open the lab's door to the natural world. This journey started with the decision to shift from controlled stimuli to natural dynamic and "messy" stimuli. This transition enabled us to focus on how information is accumulated and processed over time. As a result, we have discovered a new topographic mapping of the hierarchy of cortical processing timescales. I will conclude with a general observation of the paradigm shift occurring in the field as it increasingly emphasizes the study of the neural processes that underlie human behavior in natural, everyday contexts. I am excited to share this journey with you.
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Affiliation(s)
- Uri Hasson
- Psychology Department and the Neuroscience Institute, Princeton University, Princeton, New Jersey 08544
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18
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Khoury CF, Ferrone M, Runyan CA. Local Differences in Network Organization in the Auditory and Parietal Cortex, Revealed with Single Neuron Activation. J Neurosci 2025; 45:e1385242025. [PMID: 39890466 PMCID: PMC11905346 DOI: 10.1523/jneurosci.1385-24.2025] [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: 07/19/2024] [Revised: 01/17/2025] [Accepted: 01/22/2025] [Indexed: 02/03/2025] Open
Abstract
The structure of local circuits is highly conserved across the cortex, yet the spatial and temporal properties of population activity differ fundamentally in sensory-level and association-level areas. In the sensory cortex, population activity has a shorter timescale and decays sharply over distance, supporting a population code for the fine-scale features of sensory stimuli. In the association cortex, population activity has a longer timescale and spreads over wider distances, a code that is suited to holding information in memory and driving behavior. We tested whether these differences in activity dynamics could be explained by differences in network structure. We targeted photostimulations to single excitatory neurons of layer 2/3, while monitoring surrounding population activity using two-photon calcium imaging. Experiments were performed in the auditory (AC) and posterior parietal cortex (PPC) within the same mice of both sexes, which also expressed a red fluorophore in somatostatin-expressing interneurons (SOM). In both cortical regions, photostimulations resulted in a spatially restricted zone of positive influence on neurons closely neighboring the targeted neuron and a more spatially diffuse zone of negative influence affecting more distant neurons (akin to a network-level "suppressive surround"). However, the relative spatial extents of positive and negative influence were different in AC and PPC. In PPC, the central zone of positive influence was wider, but the negative suppressive surround was more narrow than in AC, which could account for the larger-scale network dynamics in PPC. The more narrow central positive influence zone and wider suppressive surround in AC could serve to sharpen sensory representations.
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Affiliation(s)
- Christine F Khoury
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Michael Ferrone
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Caroline A Runyan
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
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19
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Northoff G, Buccellato A, Zilio F. Connecting brain and mind through temporo-spatial dynamics: Towards a theory of common currency. Phys Life Rev 2025; 52:29-43. [PMID: 39615425 DOI: 10.1016/j.plrev.2024.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Accepted: 11/20/2024] [Indexed: 03/01/2025]
Abstract
Despite major progress in our understanding of the brain, the connection of neural and mental features, that is, brain and mind, remains yet elusive. In our 2020 target paper ("Is temporospatial dynamics the 'common currency' of brain and mind? Spatiotemporal Neuroscience") we proposed the "Common currency hypothesis": temporo-spatial dynamics are shared by neural and mental features, providing their connection. The current paper aims to further support and extend the original description of such common currency into a first outline of a "Common currency theory" (CCT) of neuro-mental relationship. First, we extend the range of examples to thoughts, meditation, depression and attention all lending support that temporal characteristics, (i.e. dynamics) are shared by both neural and mental features. Second, we now also show empirical examples of how spatial characteristics, i.e., topography, are shared by neural and mental features; this is illustrated by topographic reorganization of both neural and mental states in depression and meditation. Third, considering the neuro-mental connection in theoretical terms, we specify their relationship by distinct forms of temporospatial correspondences, ranging on a continuum from simple to complex. In conclusion, we extend our initial hypothesis about the key role of temporo-spatial dynamics in neuro-mental relationship into a first outline of an integrated mind-brain theory, the "Common currency theory" (CCT).
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.
| | - Andrea Buccellato
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Federico Zilio
- Department of Philosophy, Sociology, Education, and Applied Psychology, University of Padova, Italy.
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20
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Bein O, Niv Y. Schemas, reinforcement learning and the medial prefrontal cortex. Nat Rev Neurosci 2025; 26:141-157. [PMID: 39775183 DOI: 10.1038/s41583-024-00893-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/03/2024] [Indexed: 01/11/2025]
Abstract
Schemas are rich and complex knowledge structures about the typical unfolding of events in a context; for example, a schema of a dinner at a restaurant. In this Perspective, we suggest that reinforcement learning (RL), a computational theory of learning the structure of the world and relevant goal-oriented behaviour, underlies schema learning. We synthesize literature about schemas and RL to offer that three RL principles might govern the learning of schemas: learning via prediction errors, constructing hierarchical knowledge using hierarchical RL, and dimensionality reduction through learning a simplified and abstract representation of the world. We then suggest that the orbitomedial prefrontal cortex is involved in both schemas and RL due to its involvement in dimensionality reduction and in guiding memory reactivation through interactions with posterior brain regions. Last, we hypothesize that the amount of dimensionality reduction might underlie gradients of involvement along the ventral-dorsal and posterior-anterior axes of the orbitomedial prefrontal cortex. More specific and detailed representations might engage the ventral and posterior parts, whereas abstraction might shift representations towards the dorsal and anterior parts of the medial prefrontal cortex.
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Affiliation(s)
- Oded Bein
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
| | - Yael Niv
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Psychology Department, Princeton University, Princeton, NJ, USA
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21
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Li X, Eickhoff SB, Weis S. Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions. Hum Brain Mapp 2025; 46:e70164. [PMID: 39960115 PMCID: PMC11831449 DOI: 10.1002/hbm.70164] [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: 09/18/2024] [Revised: 01/22/2025] [Accepted: 01/31/2025] [Indexed: 02/20/2025] Open
Abstract
While the use of naturalistic stimuli such as movie clips for understanding individual differences and brain-behaviour relationships attracts increasing interest, the influence of stimulus selection remains largely unclear. By using machine learning to predict individual traits (phenotypes) from brain activity evoked during various movie clips, we show that different movie stimuli can result in distinct prediction performances. In brain regions related to lower-level processing of the stimulus, prediction to a certain degree benefits from stronger synchronisation of brain activity across subjects. By contrast, better predictions in frontoparietal brain regions are mainly associated with larger inter-subject variability. Furthermore, we demonstrate that while movie clips with rich social content in general achieve better predictions, the importance of specific movie features for prediction highly depends on the phenotype under investigation. Overall, our findings underscore the importance of careful stimulus selection and provide novel insights into stimulus selection for phenotype prediction in naturalistic conditions, opening new avenues for future research.
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Affiliation(s)
- Xuan Li
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems NeuroscienceMedical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems NeuroscienceMedical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems NeuroscienceMedical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
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22
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Ma Y, Skipper JI. Individual differences in wellbeing are supported by separable sets of co-active self- and visual-attention-related brain networks. Sci Rep 2025; 15:5524. [PMID: 39952989 PMCID: PMC11828889 DOI: 10.1038/s41598-025-86762-w] [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: 03/13/2024] [Accepted: 01/14/2025] [Indexed: 02/17/2025] Open
Abstract
How does the brain support 'wellbeing'? Because it is a multidimensional construct, it is likely the product of multiple co-active brain networks that vary across individuals. This is perhaps why prior neuroimaging studies have found inconsistent anatomical associations with wellbeing. Furthermore, these used 'laboratory-style' or 'resting-state' methods not amenable to finding manifold networks. To address these issues, we had participants watch a full-length romantic comedy-drama film during functional magnetic resonance imaging. We hypothesised that individual differences in wellbeing measured before scanning would be correlated with individual differences in brain networks associated with 'embodied' and 'narrative' self-related processing. Indeed, searchlight spatial inter-participant representational similarity and subsequent analyses revealed seven sets of co-activated networks associated with individual differences in wellbeing. Two were 'embodied self' related, including brain regions associated with autonomic and affective processing. Three sets were 'narrative self' related, involving speech, language, and autobiographical memory-related regions. Finally, two sets of visual-attention-related networks emerged. These results suggest that the neurobiology of wellbeing in the real world is supported by diverse but functionally definable and separable sets of networks. This has implications for psychotherapy where individualised interventions might target, e.g., neuroplasticity in language-related narrative over embodied self or visual-attentional related processes.
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Affiliation(s)
- Yumeng Ma
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
- Experimental Psychology, University College London, London, UK.
- Department of Psychology, Emory University, Atlanta, GA, USA.
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23
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Wu K, Gollo LL. Mapping and modeling age-related changes in intrinsic neural timescales. Commun Biol 2025; 8:167. [PMID: 39901043 PMCID: PMC11791184 DOI: 10.1038/s42003-025-07517-x] [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: 09/27/2024] [Accepted: 01/10/2025] [Indexed: 02/05/2025] Open
Abstract
Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and dynamics. However, the impact of these structural changes on temporal coding in the aging brain remains unclear. We mapped intrinsic timescales and gray matter volume (GMV) using magnetic resonance imaging (MRI) in young and elderly adults. We found shorter intrinsic timescales across multiple large-scale functional networks in the elderly cohort, and a significant positive association between intrinsic timescales and GMV. Additionally, age-related decline in performance on visual discrimination tasks was linked to a reduction in intrinsic timescales in the cuneus. To explain these age-related shifts, we developed an age-dependent spiking neuron network model. In younger subjects, brain regions were near a critical branching regime, while regions in elderly subjects had fewer neurons and synapses, pushing the dynamics toward a subcritical regime. The model accurately reproduced the empirical results, showing longer intrinsic timescales in young adults due to critical slowing down. Our findings reveal how age-related structural brain changes may drive alterations in brain dynamics, offering testable predictions and informing possible interventions targeting cognitive decline.
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Affiliation(s)
- Kaichao Wu
- Brain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | - Leonardo L Gollo
- Brain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
- Instituto de Física Interdisciplinary Sistemas Complejos, IFISC (UIB-CSIC), Campus Universitat de les Illes Balears, Palma de Mallorca, Spain.
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24
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Wass SV, Perapoch Amadó M, Northrop T, Marriott Haresign I, Phillips EAM. Foraging and inertia: Understanding the developmental dynamics of overt visual attention. Neurosci Biobehav Rev 2025; 169:105991. [PMID: 39722410 DOI: 10.1016/j.neubiorev.2024.105991] [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: 09/26/2024] [Revised: 12/05/2024] [Accepted: 12/19/2024] [Indexed: 12/28/2024]
Abstract
During early life, we develop the ability to choose what we focus on and what we ignore, allowing us to regulate perception and action in complex environments. But how does this change influence how we spontaneously allocate attention to real-world objects during free behaviour? Here, in this narrative review, we examine this question by considering the time dynamics of spontaneous overt visual attention, and how these develop through early life. Even in early childhood, visual attention shifts occur both periodically and aperiodically. These reorientations become more internally controlled as development progresses. Increasingly with age, attention states also develop self-sustaining attractor dynamics, known as attention inertia, in which the longer an attention episode lasts, the more the likelihood increases of its continuing. These self-sustaining dynamics are driven by amplificatory interactions between engagement, comprehension, and distractibility. We consider why experimental measures show decline in sustained attention over time, while real-world visual attention often demonstrates the opposite pattern. Finally, we discuss multi-stable attention states, where both hypo-arousal (mind-wandering) and hyper-arousal (fragmentary attention) may also show self-sustaining attractor dynamics driven by moment-by-moment amplificatory child-environment interactions; and we consider possible applications of this work, and future directions.
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Affiliation(s)
- S V Wass
- BabyDevLab, School of Psychology, University of East London, Water Lane, London E15 4LZ, UK.
| | - M Perapoch Amadó
- BabyDevLab, School of Psychology, University of East London, Water Lane, London E15 4LZ, UK
| | - T Northrop
- BabyDevLab, School of Psychology, University of East London, Water Lane, London E15 4LZ, UK
| | - I Marriott Haresign
- BabyDevLab, School of Psychology, University of East London, Water Lane, London E15 4LZ, UK
| | - E A M Phillips
- BabyDevLab, School of Psychology, University of East London, Water Lane, London E15 4LZ, UK
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25
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Fan Y, Wang M, Fang F, Ding N, Luo H. Two-dimensional neural geometry underpins hierarchical organization of sequence in human working memory. Nat Hum Behav 2025; 9:360-375. [PMID: 39511344 DOI: 10.1038/s41562-024-02047-8] [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] [Accepted: 10/02/2024] [Indexed: 11/15/2024]
Abstract
Working memory (WM) is constructive in nature. Instead of passively retaining information, WM reorganizes complex sequences into hierarchically embedded chunks to overcome capacity limits and facilitate flexible behaviour. Here, to investigate the neural mechanisms underlying hierarchical reorganization in WM, we performed two electroencephalography and one magnetoencephalography experiments, wherein humans retain in WM a temporal sequence of items, that is, syllables, which are organized into chunks, that is, multisyllabic words. We demonstrate that the one-dimensional sequence is represented by two-dimensional neural representational geometry in WM arising from left prefrontal and temporoparietal regions, with separate dimensions encoding item position within a chunk and chunk position in the sequence. Critically, this two-dimensional geometry is observed consistently in different experimental settings, even during tasks not encouraging hierarchical reorganization in WM and correlates with WM behaviour. Overall, these findings strongly support that complex sequences are reorganized into factorized multidimensional neural representational geometry in WM, which also speaks to general structure-based organizational principles given WM's involvement in many cognitive functions.
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Affiliation(s)
- Ying Fan
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
| | - Muzhi Wang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
| | - Fang Fang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Nai Ding
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China.
- State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
| | - Huan Luo
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
- Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China.
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26
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Li Y, Zhang J, Li X, Zhang Z. Uncovering narrative aging: an underlying neural mechanism compensated through spatial constructional ability. Commun Biol 2025; 8:104. [PMID: 39837995 PMCID: PMC11751312 DOI: 10.1038/s42003-025-07501-5] [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: 04/17/2024] [Accepted: 01/08/2025] [Indexed: 01/23/2025] Open
Abstract
"The narrative" is a complex cognitive process that has sparked a debate on whether its features age through maintenance or decline. To address this question, we attempted to uncover the narrative aging and its underlying neural characteristics with a cross-validation based cognitive neuro-decoding statistical framework. This framework used a total of 740 healthy older participants with completed narrative and extensive neuropsychological tests and MRI scans. The results indicated that narrative comprises macro and micro structures, with the macrostructure involving complex cognitive processes more relevant to aging. For the brain functional basis, brain hub nodes contributing to macrostructure were predominantly found in the angular gyrus and medial frontal lobe, while microstructure hub nodes were located in the supramarginal gyrus and middle cingulate cortex. Moreover, networks enriched by macrostructure included the default mode network and fronto-parietal network, indicating a higher functional gradient compared to the microstructure-enriched dorsal attention network. Additionally, an interesting finding showed that macrostructure increases in spatial contribution with age, suggesting a compensatory interaction where brain regions related to spatial-constructional ability have a greater impact on macrostructure. These results, supported by neural-level validation and multimodal structural MRI, provide detailed insights into the compensatory effect in the narrative aging process.
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Affiliation(s)
- Yumeng Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, 100875, China
| | - Junying Zhang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, 100875, China.
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, 100875, China.
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Liu L, Jiang J, Li H, Ding G. Tripartite organization of brain state dynamics underlying spoken narrative comprehension. eLife 2025; 13:RP99997. [PMID: 39835965 PMCID: PMC11750135 DOI: 10.7554/elife.99997] [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: 01/22/2025] Open
Abstract
Speech comprehension involves the dynamic interplay of multiple cognitive processes, from basic sound perception, to linguistic encoding, and finally to complex semantic-conceptual interpretations. How the brain handles the diverse streams of information processing remains poorly understood. Applying Hidden Markov Modeling to fMRI data obtained during spoken narrative comprehension, we reveal that the whole brain networks predominantly oscillate within a tripartite latent state space. These states are, respectively, characterized by high activities in the sensory-motor (State #1), bilateral temporal (State #2), and default mode networks (DMN; State #3) regions, with State #2 acting as a transitional hub. The three states are selectively modulated by the acoustic, word-level semantic, and clause-level semantic properties of the narrative. Moreover, the alignment with both the best performer and the group-mean in brain state expression can predict participants' narrative comprehension scores measured from the post-scan recall. These results are reproducible with different brain network atlas and generalizable to two datasets consisting of young and older adults. Our study suggests that the brain underlies narrative comprehension by switching through a tripartite state space, with each state probably dedicated to a specific component of language faculty, and effective narrative comprehension relies on engaging those states in a timely manner.
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Affiliation(s)
- Lanfang Liu
- Department of Psychology, School of Arts and Sciences, Beijing Normal University at ZhuhaiZhuhaiChina
- Faculty of Psychology, Beijing Normal UniversityBeijingChina
| | - Jiahao Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University & IDG/McGovern Institute for Brain ResearchBeijingChina
| | - Hehui Li
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen UniversityShenzhenChina
| | - Guosheng Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University & IDG/McGovern Institute for Brain ResearchBeijingChina
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28
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Szabó Á, Galla Z, Spekker E, Szűcs M, Martos D, Takeda K, Ozaki K, Inoue H, Yamamoto S, Toldi J, Ono E, Vécsei L, Tanaka M. Oxidative and Excitatory Neurotoxic Stresses in CRISPR/Cas9-Induced Kynurenine Aminotransferase Knockout Mice: A Novel Model for Despair-Based Depression and Post-Traumatic Stress Disorder. FRONT BIOSCI-LANDMRK 2025; 30:25706. [PMID: 39862084 DOI: 10.31083/fbl25706] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 10/24/2024] [Accepted: 11/18/2024] [Indexed: 01/27/2025]
Abstract
BACKGROUNDS Memory and emotion are especially vulnerable to psychiatric disorders such as post-traumatic stress disorder (PTSD), which is linked to disruptions in serotonin (5-HT) metabolism. Over 90% of the 5-HT precursor tryptophan (Trp) is metabolized via the Trp-kynurenine (KYN) metabolic pathway, which generates a variety of bioactive molecules. Dysregulation of KYN metabolism, particularly low levels of kynurenic acid (KYNA), appears to be linked to neuropsychiatric disorders. The majority of KYNA is produced by the aadat (kat2) gene-encoded mitochondrial kynurenine aminotransferase (KAT) isotype 2. Little is known about the consequences of deleting the KYN enzyme gene. METHODS In CRISPR/Cas9-induced aadat knockout (kat2-/-) mice, we examined the effects on emotion, memory, motor function, Trp and its metabolite levels, enzyme activities in the plasma and urine of 8-week-old males compared to wild-type mice. RESULTS Transgenic mice showed more depressive-like behaviors in the forced swim test, but not in the tail suspension, anxiety, or memory tests. They also had fewer center field and corner entries, shorter walking distances, and fewer jumping counts in the open field test. Plasma metabolite levels are generally consistent with those of urine: antioxidant KYNs, 5-hydroxyindoleacetic acid, and indole-3-acetic acid levels were lower; enzyme activities in KATs, kynureninase, and monoamine oxidase/aldehyde dehydrogenase were lower, but kynurenine 3-monooxygenase was higher; and oxidative stress and excitotoxicity indices were higher. Transgenic mice displayed depression-like behavior in a learned helplessness model, emotional indifference, and motor deficits, coupled with a decrease in KYNA, a shift of Trp metabolism toward the KYN-3-hydroxykynurenine pathway, and a partial decrease in the gut microbial Trp-indole pathway metabolite. CONCLUSIONS This is the first evidence that deleting the aadat gene induces depression-like behaviors uniquely linked to experiences of despair, which appear to be associated with excitatory neurotoxic and oxidative stresses. This may lead to the development of a double-hit preclinical model in despair-based depression, a better understanding of these complex conditions, and more effective therapeutic strategies by elucidating the relationship between Trp metabolism and PTSD pathogenesis.
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Affiliation(s)
- Ágnes Szabó
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary
- Doctoral School of Clinical Medicine, University of Szeged, H-6720 Szeged, Hungary
| | - Zsolt Galla
- Department of Pediatrics, Albert Szent-Györgyi Faculty of Medicine, University of Szeged, H-6725 Szeged, Hungary
| | - Eleonóra Spekker
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary
| | - Mónika Szűcs
- Department of Medical Physics and Informatics, Albert Szent-Györgyi Medical School, Faculty of Science and Informatics, University of Szeged, H-6720 Szeged, Hungary
| | - Diána Martos
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary
| | - Keiko Takeda
- Department of Biomedicine, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
| | - Kinuyo Ozaki
- Center of Biomedical Research, Research Center for Human Disease Modeling, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
| | - Hiromi Inoue
- Center of Biomedical Research, Research Center for Human Disease Modeling, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
| | - Sayo Yamamoto
- Center of Biomedical Research, Research Center for Human Disease Modeling, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
| | - József Toldi
- Department of Physiology, Anatomy and Neuroscience, Faculty of Science and Informatics, University of Szeged, H-6726 Szeged, Hungary
| | - Etsuro Ono
- Department of Biomedicine, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
- Center of Biomedical Research, Research Center for Human Disease Modeling, Graduate School of Medical Sciences, Kyushu University, 812-8582 Fukuoka, Japan
| | - László Vécsei
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary
| | - Masaru Tanaka
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary
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29
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Tikochinski R, Goldstein A, Meiri Y, Hasson U, Reichart R. Incremental accumulation of linguistic context in artificial and biological neural networks. Nat Commun 2025; 16:803. [PMID: 39824935 PMCID: PMC11748659 DOI: 10.1038/s41467-025-56162-9] [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: 07/18/2024] [Accepted: 01/08/2025] [Indexed: 01/20/2025] Open
Abstract
Large Language Models (LLMs) have shown success in predicting neural signals associated with narrative processing, but their approach to integrating context over large timescales differs fundamentally from that of the human brain. In this study, we show how the brain, unlike LLMs that process large text windows in parallel, integrates short-term and long-term contextual information through an incremental mechanism. Using fMRI data from 219 participants listening to spoken narratives, we first demonstrate that LLMs predict brain activity effectively only when using short contextual windows of up to a few dozen words. Next, we introduce an alternative LLM-based incremental-context model that combines incoming short-term context with an aggregated, dynamically updated summary of prior context. This model significantly enhances the prediction of neural activity in higher-order regions involved in long-timescale processing. Our findings reveal how the brain's hierarchical temporal processing mechanisms enable the flexible integration of information over time, providing valuable insights for both cognitive neuroscience and AI development.
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Affiliation(s)
- Refael Tikochinski
- The Faculty of Data and Decisions Sciences, Technion - Israel Institute of Technology, Haifa, Israel.
| | - Ariel Goldstein
- Department of Cognitive and Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yoav Meiri
- The Faculty of Data and Decisions Sciences, Technion - Israel Institute of Technology, Haifa, Israel
| | - Uri Hasson
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Roi Reichart
- The Faculty of Data and Decisions Sciences, Technion - Israel Institute of Technology, Haifa, Israel
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30
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Kwon D, Kim J, Yoo SBM, Shim WM. Coordinated representations for naturalistic memory encoding and retrieval in hippocampal neural subspaces. Nat Commun 2025; 16:641. [PMID: 39809735 PMCID: PMC11733261 DOI: 10.1038/s41467-025-55833-x] [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: 05/15/2024] [Accepted: 12/30/2024] [Indexed: 01/16/2025] Open
Abstract
Our naturalistic experiences are organized into memories through multiple processes, including novelty encoding, memory formation, and retrieval. However, the neural mechanisms coordinating these processes remain elusive. Using fMRI data acquired during movie viewing and subsequent narrative recall, we examine hippocampal neural subspaces associated with distinct memory processes and characterized their relationships. We quantify novelty in character co-occurrences and the valence of relationships and estimate event memorability. Within the hippocampus, the novelty subspaces encoding each type exhibit partial overlap, and these overlapping novelty subspaces align with the subspace involved in memorability. Notably, following event boundaries, hippocampal states within these subspaces align inversely along a shared coding axis, predicting subsequent recall performance. This novelty-memorability alignment is selectively observed during encoding but not during retrieval. Finally, the identified functional subspaces reflect the intrinsic functional organization of the hippocampus. Our findings offer insights into how the hippocampus dynamically coordinates representations underlying memory encoding and retrieval at the population level to transform ongoing experiences into enduring memories.
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Affiliation(s)
- Dasom Kwon
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
| | - Jungwoo Kim
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Seng Bum Michael Yoo
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
| | - Won Mok Shim
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
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31
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Sava-Segal C, Grall C, Finn ES. Narrative 'twist' shifts within-individual neural representations of dissociable story features. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.13.632631. [PMID: 39868260 PMCID: PMC11761699 DOI: 10.1101/2025.01.13.632631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Given the same external input, one's understanding of that input can differ based on internal contextual knowledge. Where and how does the brain represent latent belief frameworks that interact with incoming sensory information to shape subjective interpretations? In this study, participants listened to the same auditory narrative twice, with a plot twist in the middle that dramatically shifted their interpretations of the story. Using a robust within-subject whole-brain approach, we leveraged shifts in neural activity between the two listens to identify where latent interpretations are represented in the brain. We considered the narrative in terms of its hierarchical structure, examining how global situation models and their subcomponents-namely, episodes and characters-are represented, finding that they rely on partially distinct sets of brain regions. Results suggest that our brains represent narratives hierarchically, with individual narrative elements being distinct and dynamically updated as a part of changing interpretations of incoming information.
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Affiliation(s)
- Clara Sava-Segal
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Clare Grall
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Emily S. Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
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32
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Granger SJ, Olson EA, Weinstein SJ, Vratimos IR, Lynch B, Ren B, Rosso IM. Aberrant neural event segmentation during a continuous social narrative in trauma-exposed older adolescents and young adults. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2025:10.3758/s13415-024-01252-2. [PMID: 39789397 DOI: 10.3758/s13415-024-01252-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/22/2024] [Indexed: 01/12/2025]
Abstract
Post-traumatic stress and major depressive disorders are associated with "overgeneral" autobiographical memory, or impaired recall of specific life events. Interpersonal trauma exposure, a risk factor for both conditions, may influence how symptomatic trauma-exposed (TE) individuals segment everyday events. The ability to parse experience into units (event segmentation) supports memory. Neural state transitions occur within a cortical hierarchy and play a key role in event segmentation, with regions like the occipital cortex, angular gyrus, and striatum involved in parsing event structure. We examined whether interpersonal trauma exposure was associated with alterations in the cortical hierarchy and striatal activity at neural state transitions in symptomatic TE versus healthy control (HC) individuals. Fifty older adolescents and young adults (29 TE, 21 HC) viewed the film "Partly Cloudy" during functional magnetic resonance imaging. A greedy-state boundary search algorithm assessed the optimal number of events, quality, and segmentation agreement of neural state transitions in the occipital cortex and angular gyrus. Striatal (nucleus accumbens, caudate, and putamen) activity was assessed at occipital and angular gyrus-evoked state transitions. Compared to HCs, TE participants displayed less occipital and greater angular gyrus-evoked optimal number of neural state transitions. TE participants also displayed lower quality of neural state segmentation solutions in occipital and angular cortices compared to HCs. Additionally, TE participants had less putamen activity at angular gyrus-evoked state transitions than HCs. This investigation provides neurobiological insights into aberrant event segmentation in symptomatic TE individuals, shedding light on mechanisms influencing overgeneral memory in trauma-related disorders.
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Affiliation(s)
- Steven J Granger
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Elizabeth A Olson
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Sylvie J Weinstein
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Isabelle R Vratimos
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Brian Lynch
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric Biostatistics Laboratory, McLean Hospital, Belmont, MA, USA
| | - Isabelle M Rosso
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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33
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Schott G. A long look at Copley's A Boy with a Flying Squirrel: implications for the default mode network. Brain 2025; 148:3-5. [PMID: 39440936 DOI: 10.1093/brain/awae342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 10/01/2024] [Accepted: 10/10/2024] [Indexed: 10/25/2024] Open
Abstract
What happens in the brain when a person spends three hours viewing a single painting? Geoffrey Schott examines the account of an art history professor who did just that, and considers what their observations reveal about the differences between seeing and looking, and between looking and perceiving.
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Affiliation(s)
- Geoffrey Schott
- The National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
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34
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Li J, Su M, Zhou W. Neural Correlates of Narrative Reading Development: A Comparative fMRI Study of Adults and Children Using Time-Locked Inter-Subject Correlation Analyses. Psychophysiology 2025; 62:e70005. [PMID: 39878134 DOI: 10.1111/psyp.70005] [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: 05/23/2024] [Revised: 12/15/2024] [Accepted: 01/11/2025] [Indexed: 01/31/2025]
Abstract
The naturalistic paradigm and analytical methods present new approaches that are particularly suitable for research concentrating on narrative reading development. We analyzed fMRI data from 44 adults and 42 children engaged in story reading using time-locked inter-subject correlation (ISC), inter-subject representation similarity analysis (IS-RSA), and inter-subject functional correlation (ISFC). The ISC results indicated that for both children and adults, narrative reading recruited not only traditional reading areas but also regions that are sensitive to long-time-scale information, such as the medial prefrontal cortex and hippocampus, which increased involvement from children to adults. The results of the IS-RSA indicated that during narrative reading, children exhibited greater uniqueness in neural patterns, while adults demonstrated greater similarity. The analysis of reading-level subgroups with the ISC and ISFC reveals differences in narrative reading development that span from children to adults, especially for regions sensitive to long-time-scale semantic processing. These results indicate that the maturity and experience play a crucial role in narrative reading development.
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Affiliation(s)
- Jingxiao Li
- Beijing Key Lab of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
| | - Mengmeng Su
- College of Elementary Education, Capital Normal University, Beijing, China
| | - Wei Zhou
- Beijing Key Lab of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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35
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Çatal Y, Keskin K, Wolman A, Klar P, Smith D, Northoff G. Flexibility of intrinsic neural timescales during distinct behavioral states. Commun Biol 2024; 7:1667. [PMID: 39702547 DOI: 10.1038/s42003-024-07349-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 12/02/2024] [Indexed: 12/21/2024] Open
Abstract
Recent neuroimaging studies demonstrate a heterogeneity of timescales prevalent in the brain's ongoing spontaneous activity, labeled intrinsic neural timescales (INT). At the same time, neural timescales also reflect stimulus- or task-related activity. The relationship of the INT during the brain's spontaneous activity with their involvement in task states including behavior remains unclear. To address this question, we combined calcium imaging data of spontaneously behaving mice and human electroencephalography (EEG) during rest and task states with computational modeling. We obtained four primary findings: (i) the distinct behavioral states can be accurately predicted from INT, (ii) INT become longer during behavioral states compared to rest, (iii) INT change from rest to task is correlated negatively with the variability of INT during rest, (iv) neural mass modeling shows a key role of recurrent connections in mediating the rest-task change of INT. Extending current findings, our results show the dynamic nature of the brain's INT in reflecting continuous behavior through their flexible rest-task modulation possibly mediated by recurrent connections.
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Affiliation(s)
- Yasir Çatal
- Mind, Brain Imaging and Neuroethics Research Unit, University of Ottawa, Ontario, ON, Canada.
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada.
| | - Kaan Keskin
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
- Department of Psychiatry, Ege University, Izmir, Turkey
- SoCAT Lab, Ege University, Izmir, Turkey
| | - Angelika Wolman
- Mind, Brain Imaging and Neuroethics Research Unit, University of Ottawa, Ontario, ON, Canada
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Philipp Klar
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - David Smith
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, University of Ottawa, Ontario, ON, Canada
- University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
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Mecklenbrauck F, Sepulcre J, Fehring J, Schubotz RI. Decoding cortical chronotopy-Comparing the influence of different cortical organizational schemes. Neuroimage 2024; 303:120914. [PMID: 39491762 DOI: 10.1016/j.neuroimage.2024.120914] [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: 07/15/2024] [Revised: 10/22/2024] [Accepted: 11/01/2024] [Indexed: 11/05/2024] Open
Abstract
The brain's diverse intrinsic timescales enable us to perceive stimuli with varying temporal persistency. This study aimed to uncover the cortical organizational schemes underlying these variations, revealing the neural architecture for processing a wide range of sensory experiences. We collected resting-state fMRI, task-fMRI, and diffusion-weighted imaging data from 47 individuals. Based on this data, we extracted six organizational schemes: (1) the structural Rich Club (RC) architecture, shown to synchronize the connectome; (2) the structural Diverse Club architecture, as an alternative to the RC based on the network's module structure; (3) the functional uni-to-multimodal gradient, reflected in a wide range of structural and functional features; and (4) the spatial posterior/lateral-to-anterior/medial gradient, established for hierarchical levels of cognitive control. Also, we explored the effects of (5) structural graph theoretical measures of centrality and (6) cytoarchitectural differences. Using Bayesian model comparison, we contrasted the impact of these organizational schemes on (1) intrinsic resting-state timescales and (2) inter-subject correlation (ISC) from a task involving hierarchically nested digit sequences. As expected, resting-state timescales were slower in structural network hubs, hierarchically higher areas defined by the functional and spatial gradients, and thicker cortical regions. ISC analysis demonstrated hints for the engagement of higher cortical areas with more temporally persistent stimuli. Finally, the model comparison identified the uni-to-multimodal gradient as the best organizational scheme for explaining the chronotopy in both task and rest. Future research should explore the microarchitectural features that shape this gradient, elucidating how our brain adapts and evolves across different modes of processing.
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Affiliation(s)
- Falko Mecklenbrauck
- Department of Psychology, Biological Psychology, University of Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Germany.
| | - Jorge Sepulcre
- Department of Radiology and Biomedical Imaging, Yale PET Center, Yale School of Medicine, Yale University, New Haven, CT, USA.
| | - Jana Fehring
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Germany; Institute for Biomagnetism and Biosignal Analysis, Münster, Germany.
| | - Ricarda I Schubotz
- Department of Psychology, Biological Psychology, University of Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Germany.
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37
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Areshenkoff CN, de Brouwer AJ, Gale DJ, Nashed JY, Smallwood J, Flanagan JR, Gallivan JP. Distinct patterns of connectivity with the motor cortex reflect different components of sensorimotor learning. PLoS Biol 2024; 22:e3002934. [PMID: 39625995 PMCID: PMC11644839 DOI: 10.1371/journal.pbio.3002934] [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: 06/07/2024] [Revised: 12/13/2024] [Accepted: 11/08/2024] [Indexed: 12/15/2024] Open
Abstract
Sensorimotor learning is supported by multiple competing processes that operate concurrently, making it a challenge to elucidate their neural underpinnings. Here, using human functional MRI, we identify 3 distinct axes of connectivity between the motor cortex and other brain regions during sensorimotor adaptation. These 3 axes uniquely correspond to subjects' degree of implicit learning, performance errors and explicit strategy use, and involve different brain networks situated at increasing levels of the cortical hierarchy. We test the generalizability of these neural axes to a separate form of motor learning known to rely mainly on explicit processes and show that it is only the Explicit neural axis, composed of higher-order areas in transmodal cortex, that predicts learning in this task. Together, our study uncovers multiple distinct patterns of functional connectivity with motor cortex during sensorimotor adaptation, the component processes that these patterns support, and how they generalize to other forms of motor learning.
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Affiliation(s)
- Corson N. Areshenkoff
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
- Department of Psychology, Queens University, Kingston Ontario, Canada
| | - Anouk J. de Brouwer
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
| | - Daniel J. Gale
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
| | - Joseph Y. Nashed
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
| | | | - J. Randall Flanagan
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
- Department of Psychology, Queens University, Kingston Ontario, Canada
| | - Jason P. Gallivan
- Centre for Neuroscience Studies, Queens University, Kingston Ontario, Canada
- Department of Psychology, Queens University, Kingston Ontario, Canada
- Department of Biomedical and Molecular Sciences, Queens University, Kingston Ontario, Canada
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38
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Masís-Obando R, Norman KA, Baldassano C. How sturdy is your memory palace? Reliable room representations predict subsequent reinstatement of placed objects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.26.625465. [PMID: 39651289 PMCID: PMC11623609 DOI: 10.1101/2024.11.26.625465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2024]
Abstract
Our autobiographical experiences typically occur within the context of familiar spatial locations. When we encode these experiences into memory, we can use our spatial map of the world to help organize these memories and later retrieve their episodic details. However, it is still not well understood what psychological and neural factors make spatial contexts an effective scaffold for storing and accessing memories. We hypothesized that spatial locations with distinctive and stable neural representations would best support the encoding and robust reinstatement of new episodic memories. We developed a novel paradigm that allowed us to quantify the within-participant reliability of a spatial context ("room reliability") prior to memory encoding, which could then be used to predict the degree of successful re-activation of item memories. To do this, we constructed a virtual reality (VR) "memory palace", a custom-built environment made up of 23 distinct rooms that participants explored using a head-mounted VR display. The day after learning the layout of the environment, participants underwent whole-brain fMRI while being presented with videos of the rooms in the memory palace, allowing us to measure the reliability of the neural activity pattern associated with each room. Participants were taken back to VR and asked to memorize the locations of 23 distinct objects randomly placed within each of the 23 rooms, and then returned to the scanner as they recalled the objects and the rooms in which they appeared. We found that our room reliability measure was predictive of object reinstatement across cortex, and further showed that this was driven not only by the group-level reliability of a room across participants, but also the idiosyncratic reliability of rooms within each participant. Together, these results showcase how the quality of the neural representation of a spatial context can be quantified and used to 'audit' its utility as a memory scaffold for future experiences.
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Addis DR, Szpunar KK. Beyond the episodic-semantic continuum: the multidimensional model of mental representations. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230408. [PMID: 39278248 PMCID: PMC11449204 DOI: 10.1098/rstb.2023.0408] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 05/22/2024] [Accepted: 06/14/2024] [Indexed: 09/18/2024] Open
Abstract
Tulving's concept of mental time travel (MTT), and the related distinction of episodic and semantic memory, have been highly influential contributions to memory research, resulting in a wealth of findings and a deeper understanding of the neurocognitive correlates of memory and future thinking. Many models have conceptualized episodic and semantic representations as existing on a continuum that can help to account for various hybrid forms. Nevertheless, in most theories, MTT remains distinctly associated with episodic representations. In this article, we review existing models of memory and future thinking, and critically evaluate whether episodic representations are distinct from other types of explicit representations, including whether MTT as a neurocognitive capacity is uniquely episodic. We conclude by proposing a new framework, the Multidimensional Model of Mental Representations (MMMR), which can parsimoniously account for the range of past, present and future representations the human mind is capable of creating. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.
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Affiliation(s)
- Donna Rose Addis
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ONM6A 2E1, Canada
- Department of Psychology, University of Toronto, Toronto, ONM5S 3G3, Canada
- School of Psychology, The University of Auckland, Auckland1010, New Zealand
| | - Karl K. Szpunar
- Department of Psychology, Toronto Metropolitan University, Toronto, ONM5B 2K3, Canada
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40
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Lee Y, Chen J. The Relationship between Event Boundary Strength and Pattern Shifts across the Cortical Hierarchy during Naturalistic Movie-viewing. J Cogn Neurosci 2024; 36:2317-2342. [PMID: 38991127 PMCID: PMC11493368 DOI: 10.1162/jocn_a_02213] [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: 07/13/2024]
Abstract
Our continuous experience is spontaneously segmented by the brain into discrete events. However, the beginning of a new event (an event boundary) is not always sharply identifiable: Phenomenologically, event boundaries vary in salience. How are the response profiles of cortical areas at event boundaries modulated by boundary strength during complex, naturalistic movie-viewing? Do cortical responses scale in a graded manner with boundary strength, or do they merely detect boundaries in a binary fashion? We measured "cortical boundary shifts" as transient changes in multivoxel patterns at event boundaries with different strengths (weak, moderate, and strong), determined by across-participant agreement. Cortical regions with different processing timescales were examined. In auditory areas, which have short timescales, cortical boundary shifts exhibited a clearly graded profile in both group-level and individual-level analyses. In cortical areas with long timescales, including the default mode network, boundary strength modulated pattern shift magnitude at the individual participant level. We also observed a positive relationship between boundary strength and the extent of temporal alignment of boundary shifts across different levels of the cortical hierarchy. In addition, hippocampal activity was highest at event boundaries for which cortical boundary shifts were most aligned across hierarchical levels. Overall, we found that event boundary strength modulated cortical pattern shifts strongly in sensory areas and more weakly in higher-level areas and that stronger boundaries were associated with greater alignment of these shifts across the cortical hierarchy.
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41
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Querella P, Majerus S. Sequential syntactic knowledge supports item but not order recall in verbal working memory. Mem Cognit 2024; 52:1737-1761. [PMID: 37872468 DOI: 10.3758/s13421-023-01476-6] [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] [Accepted: 10/04/2023] [Indexed: 10/25/2023]
Abstract
Previous studies have shown that psycholinguistic effects such as lexico-semantic knowledge effects mainly determine item recall in verbal working memory (WM). However, we may expect that syntactic knowledge, involving knowledge about word-level sequential aspects of language, should also impact serial-order aspects of recall in WM. Evidence for this assumption is scarce and inconsistent and has been conducted in language with deterministic syntactic rules. In languages such as French, word position is determined in a probabilistic manner: an adjective is placed before or after a noun, depending on its lexico-semantic properties. We exploited this specificity of the French language for examining the impact of syntactic positional knowledge on both item and serial order recall in verbal WM. We presented lists with adjective-noun pairs for immediate serial recall, the adjectives being in regular or irregular position relative to the nouns. We observed increased recall performance when adjectives occurred in regular position; this effect was observed for item recall but not order recall scores. We propose an integration of verbal WM and syntactic processing models to account for this finding by assuming that the impact of syntactic knowledge on serial-order WM recall is indirect and mediated via syntax-dependent item-retrieval processes.
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Affiliation(s)
- Pauline Querella
- Department of Psychology, Psychology and Cognitive Neuroscience Research Unit, University of Liège, Place des Orateurs 1 (B33), 4000, Liège, Belgium.
| | - Steve Majerus
- Department of Psychology, Psychology and Cognitive Neuroscience Research Unit, University of Liège, Place des Orateurs 1 (B33), 4000, Liège, Belgium
- National Fund for Scientific Research, Brussels, Belgium
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42
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Lehmann K, Bolis D, Friston KJ, Schilbach L, Ramstead MJD, Kanske P. An Active-Inference Approach to Second-Person Neuroscience. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2024; 19:931-951. [PMID: 37565656 PMCID: PMC11539477 DOI: 10.1177/17456916231188000] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Social neuroscience has often been criticized for approaching the investigation of the neural processes that enable social interaction and cognition from a passive, detached, third-person perspective, without involving any real-time social interaction. With the emergence of second-person neuroscience, investigators have uncovered the unique complexity of neural-activation patterns in actual, real-time interaction. Social cognition that occurs during social interaction is fundamentally different from that unfolding during social observation. However, it remains unclear how the neural correlates of social interaction are to be interpreted. Here, we leverage the active-inference framework to shed light on the mechanisms at play during social interaction in second-person neuroscience studies. Specifically, we show how counterfactually rich mutual predictions, real-time bodily adaptation, and policy selection explain activation in components of the default mode, salience, and frontoparietal networks of the brain, as well as in the basal ganglia. We further argue that these processes constitute the crucial neural processes that underwrite bona fide social interaction. By placing the experimental approach of second-person neuroscience on the theoretical foundation of the active-inference framework, we inform the field of social neuroscience about the mechanisms of real-life interactions. We thereby contribute to the theoretical foundations of empirical second-person neuroscience.
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Affiliation(s)
- Konrad Lehmann
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Germany
| | - Dimitris Bolis
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- National Institute for Physiological Sciences, Okazaki, Japan
- Centre for Philosophy of Science, University of Lisbon, Portugal
| | - Karl J. Friston
- Wellcome Centre for Human Neuroimaging, University College London, UK
- VERSES AI Research Lab, Los Angeles, CA, USA
| | - Leonhard Schilbach
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilians Universität, Munich, Germany
- Department of General Psychiatry 2, Clinics of the Heinrich Heine University Düsseldorf, Germany
| | - Maxwell J. D. Ramstead
- Wellcome Centre for Human Neuroimaging, University College London, UK
- VERSES AI Research Lab, Los Angeles, CA, USA
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Germany
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43
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Smith CM, Thompson-Schill SL, Schapiro AC. Rapid Learning of Temporal Dependencies at Multiple Timescales. J Cogn Neurosci 2024; 36:2343-2356. [PMID: 39106164 DOI: 10.1162/jocn_a_02232] [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: 08/09/2024]
Abstract
Our environment contains temporal information unfolding simultaneously at multiple timescales. How do we learn and represent these dynamic and overlapping information streams? We investigated these processes in a statistical learning paradigm with simultaneous short and long timescale contingencies. Human participants (n = 96) played a game where they learned to quickly click on a target image when it appeared in one of nine locations, in eight different contexts. Across contexts, we manipulated the order of target locations: at a short timescale, the order of pairs of sequential locations in which the target appeared; at a longer timescale, the set of locations that appeared in the first versus the second half of the game. Participants periodically predicted the upcoming target location, and later performed similarity judgments comparing the games based on their order properties. Participants showed context-dependent sensitivity to order information at both short and long timescales, with evidence of stronger learning for short timescales. We modeled the learning paradigm using a gated recurrent network trained to make immediate predictions, which demonstrated multilevel learning timecourses and patterns of sensitivity to the similarity structure of the games that mirrored human participants. The model grouped games with matching rule structure and dissociated games based on low-level order information more so than high-level order information. The work shows how humans and models can rapidly and concurrently acquire order information at different timescales.
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44
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Rait LI, Hutchinson JB. Recall as a Window into Hippocampally Defined Events. J Cogn Neurosci 2024; 36:2386-2400. [PMID: 38820552 DOI: 10.1162/jocn_a_02198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
We experience the present as a continuous stream of information, but often experience the past in parcels of unique events or episodes. Decades of research have helped to articulate how we perform this event segmentation in the moment, as well as how events and their boundaries influence what we later remember. More recently, neuroscientific research has suggested that the hippocampus plays a role at critical moments during event formation alongside its established role in enabling subsequent recall. Here, we review and explore the relationship between event processing and recall with the perspective that it can be uniquely characterized by the contributions of the hippocampus and its interactions with the rest of the brain. Specifically, we highlight a growing number of empirical studies suggesting that the hippocampus is important for processing events that have just ended, bridging the gap between the prior and current event, and influencing the contents and trajectories of recalled information. We also catalogue and summarize the multifaceted sets of findings concerning how recall is influenced by event structure. Lastly, we discuss several exciting directions for future research and how our understanding of events might be enriched by characterizing them in terms of the operations of different regions of the brain.
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Goldberg A, Rosario I, Power J, Horga G, Wengler K. Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:10.1162/imag_a_00326. [PMID: 40400776 PMCID: PMC12094611 DOI: 10.1162/imag_a_00326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/25/2025]
Abstract
Intrinsic neural timescales (INT) reflect the time window of neural integration within a brain region and can be measured via resting-state functional magnetic resonance imaging (rs-fMRI). Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on rs-fMRI INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame censoring and global signal regression (GSR). We used a subset of the Human Connectome Project Young Adult (HCP-YA) dataset with runs annotated for breathing patterns (Lynch et al., 2020) and at least one "clean" (reference) run that had minimal head motion and no respiration artifacts; other runs from the same participants ( n = 46 ) were labeled as "non-clean." We found that non-clean runs exhibited brain-wide increases in INT compared with their respective clean runs and that the magnitude of error in INT between non-clean and clean runs correlated with the amount of head motion. Importantly, effect sizes were comparable with INT effects reported in the clinical literature. GSR and high-motion frame censoring improved the similarity between INT maps from non-clean runs and their respective clean run. Using a pseudo-random frame-censoring approach, we uncovered a relationship between the number of censored frames and both the mean INT and mean error, suggesting that frame censoring itself biases INT estimation. A group-level correction procedure reduced this bias and improved similarity between non-clean runs and their respective clean run. Based on our findings, we offer recommendations for rs-fMRI INT studies, which include implementing GSR and high-motion frame censoring with Lomb-Scargle interpolation of censored frames, and performing group-level correction of the bias introduced by frame censoring.
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Affiliation(s)
- Andrew Goldberg
- New York State Psychiatric Institute, New York, NY, United States
| | - Isabella Rosario
- New York State Psychiatric Institute, New York, NY, United States
| | - Jonathan Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, United States
| | - Guillermo Horga
- New York State Psychiatric Institute, New York, NY, United States
- Department of Psychiatry, Columbia University, New York, NY, United States
| | - Kenneth Wengler
- New York State Psychiatric Institute, New York, NY, United States
- Department of Psychiatry, Columbia University, New York, NY, United States
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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46
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Tarder-Stoll H, Baldassano C, Aly M. The brain hierarchically represents the past and future during multistep anticipation. Nat Commun 2024; 15:9094. [PMID: 39438448 PMCID: PMC11496687 DOI: 10.1038/s41467-024-53293-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/01/2024] [Indexed: 10/25/2024] Open
Abstract
Memory for temporal structure enables both planning of future events and retrospection of past events. We investigated how the brain flexibly represents extended temporal sequences into the past and future during anticipation. Participants learned sequences of environments in immersive virtual reality. Pairs of sequences had the same environments in a different order, enabling context-specific learning. During fMRI, participants anticipated upcoming environments multiple steps into the future in a given sequence. Temporal structure was represented in the hippocampus and across higher-order visual regions (1) bidirectionally, with graded representations into the past and future and (2) hierarchically, with further events into the past and future represented in successively more anterior brain regions. In hippocampus, these bidirectional representations were context-specific, and suppression of far-away environments predicted response time costs in anticipation. Together, this work sheds light on how we flexibly represent sequential structure to enable planning over multiple timescales.
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Affiliation(s)
- Hannah Tarder-Stoll
- Department of Psychology, Columbia University, New York, USA.
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada.
| | | | - Mariam Aly
- Department of Psychology, Columbia University, New York, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
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De Soares A, Kim T, Mugisho F, Zhu E, Lin A, Zheng C, Baldassano C. Top-down attention shifts behavioral and neural event boundaries in narratives with overlapping event scripts. Curr Biol 2024; 34:4729-4742.e5. [PMID: 39366378 DOI: 10.1016/j.cub.2024.09.013] [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: 08/08/2023] [Revised: 07/31/2024] [Accepted: 09/06/2024] [Indexed: 10/06/2024]
Abstract
Understanding and remembering the complex experiences of everyday life relies critically on prior schematic knowledge about how events in our world unfold over time. How does the brain construct event representations from a library of schematic scripts, and how does activating a specific script impact the way that events are segmented in time? We developed a novel set of 16 audio narratives, each of which combines one of four location-relevant event scripts (restaurant, airport, grocery store, and lecture hall) with one of four socially relevant event scripts (breakup, proposal, business deal, and meet cute), and presented them to participants in an fMRI study and a separate online study. Responses in the angular gyrus, parahippocampal gyrus, and subregions of the medial prefrontal cortex (mPFC) were driven by scripts related to both location and social information, showing that these regions can track schematic sequences from multiple domains. For some stories, participants were primed to attend to one of the two scripts by training them to listen for and remember specific script-relevant episodic details. Activating a location-related event script shifted the timing of subjective event boundaries to align with script-relevant changes in the narratives, and this behavioral shift was mirrored in the timing of neural responses, with mPFC event boundaries (identified using a hidden Markov model) aligning to location-relevant rather than socially relevant boundaries when participants were location primed. Our findings demonstrate that neural event dynamics are actively modulated by top-down goals and provide new insight into how narrative event representations are constructed through the activation of temporally structured prior knowledge.
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Affiliation(s)
| | - Tony Kim
- Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Franck Mugisho
- Department of Computer Science, Columbia University, New York, NY 10027, USA
| | - Elen Zhu
- Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Allison Lin
- Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Chen Zheng
- Department of Human Development, Teachers College, Columbia University, New York, NY 10027, USA
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48
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Qi Z, Zeng W, Zang D, Wang Z, Luo L, Wu X, Yu J, Mao Y. Classifying disorders of consciousness using a novel dual-level and dual-modal graph learning model. J Transl Med 2024; 22:950. [PMID: 39434088 PMCID: PMC11492684 DOI: 10.1186/s12967-024-05729-z] [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: 06/27/2024] [Accepted: 10/01/2024] [Indexed: 10/23/2024] Open
Abstract
BACKGROUND Disorders of consciousness (DoC) are a group of conditions that affect the level of awareness and communication in patients. While neuroimaging techniques can provide useful information about the brain structure and function in these patients, most existing methods rely on a single modality for analysis and rarely account for brain injury. To address these limitations, we propose a novel method that integrates two neuroimaging modalities, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), to enhance the classification of subjects into different states of consciousness. METHOD AND RESULTS The main contributions of our work are threefold: first, after constructing a dual-model individual graph using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), we introduce a brain injury mask mechanism that consolidates damaged brain regions into a single graph node, enhancing the modeling of brain injuries and reducing deformation effects. Second, to address over-smoothing, we construct a dual-level graph that dynamically construct a population-level graph with node features from individual graphs, to promote the clustering of similar subjects while distinguishing dissimilar ones. Finally, we employ a subgraph exploration model with task-fMRI data to validate the interpretability of our model, confirming that the selected brain regions are task-relevant in cognition. Our experimental results on data from 89 healthy participants and 204 patients with DoC from Huashan Hospital, Fudan University, demonstrate that our method achieves high accuracy in classifying patients into unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), or normal conscious state, outperforming current state-of-the-art methods. The explainability results of our method identified a subset of brain regions that are important for consciousness, such as the default mode network, the salience network, the dorsal attention network, and the visual network. Our method also revealed the relationship between brain networks and language processing in consciousness, and showed that language-related subgraphs can distinguish MCS from UWS patients. CONCLUSION We proposed a novel graph learning method for classifying DoC based on fMRI and DTI data, introducing a brain injury mask mechanism to effectively handle damaged brains. The classification results demonstrate the effectiveness of our method in distinguishing subjects across different states of consciousness, while the explainability results identify key brain regions relevant to this classification. Our study provides new evidence for the role of brain networks and language processing in consciousness, with potential implications for improving the diagnosis and prognosis of patients with DoC.
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Affiliation(s)
- Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China
- National Center for Neurological Disorders, Shanghai, 200030, China
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China
| | - Wenwen Zeng
- School of Information Science and Technology, Fudan University, Shanghai, China
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China.
- National Center for Neurological Disorders, Shanghai, 200030, China.
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China.
- Department of Neurosurgery, China-Japan Friendship Hospital, Beijing, China.
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China
- National Center for Neurological Disorders, Shanghai, 200030, China
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China
| | - Lanqin Luo
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China
- National Center for Neurological Disorders, Shanghai, 200030, China
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China.
- National Center for Neurological Disorders, Shanghai, 200030, China.
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China.
| | - Jinhua Yu
- School of Information Science and Technology, Fudan University, Shanghai, China.
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China.
- National Center for Neurological Disorders, Shanghai, 200030, China.
- Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, 200030, China.
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Chang CHC, Nastase SA, Zadbood A, Hasson U. How a speaker herds the audience: multibrain neural convergence over time during naturalistic storytelling. Soc Cogn Affect Neurosci 2024; 19:nsae059. [PMID: 39223692 PMCID: PMC11421471 DOI: 10.1093/scan/nsae059] [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: 03/28/2024] [Revised: 06/25/2024] [Accepted: 08/31/2024] [Indexed: 09/04/2024] Open
Abstract
Storytelling-an ancient way for humans to share individual experiences with others-has been found to induce neural alignment among listeners. In exploring the dynamic fluctuations in listener-listener (LL) coupling throughout stories, we uncover a significant correlation between LL coupling and lagged speaker-listener (lag-SL) coupling over time. Using the analogy of neural pattern (dis)similarity as distances between participants, we term this phenomenon the "herding effect." Like a shepherd guiding a group of sheep, the more closely listeners mirror the speaker's preceding brain activity patterns (higher lag-SL similarity), the more tightly they cluster (higher LL similarity). This herding effect is particularly pronounced in brain regions where neural alignment among listeners tracks with moment-by-moment behavioral ratings of narrative content engagement. By integrating LL and SL neural coupling, this study reveals a dynamic, multibrain functional network between the speaker and the audience, with the unfolding narrative content playing a mediating role in network configuration.
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Affiliation(s)
- Claire H C Chang
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, United States
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, New Taipei City 235, Taiwan
| | - Samuel A Nastase
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, United States
| | - Asieh Zadbood
- Department of Psychology, Columbia University, New York, NY 10027, United States
| | - Uri Hasson
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, United States
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Dekydtspotter L, Miller AK, Swanson K, Cha JH, Xiong Y, Ahn JH, Gilbert JA, Pope D, Iverson M, Meinert K. Hierarchical neural processing in γ oscillations for syntactic and semantic operations accounts for first- and second-language epistemology. Front Hum Neurosci 2024; 18:1372909. [PMID: 39376494 PMCID: PMC11456458 DOI: 10.3389/fnhum.2024.1372909] [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: 01/18/2024] [Accepted: 08/19/2024] [Indexed: 10/09/2024] Open
Abstract
Introduction We discuss event-related power differences (ERPDs) in low- and broadband-γ oscillations as the embedded-clause edge is processed in wh-dependencies such as Which decision regarding/about him/her did Paul say that Lydie rejected without hesitation? in first (L1) and second language (L2) French speakers. Methods The experimental conditions manipulated whether pronouns appeared in modifiers (Mods; regarding him/her) or in noun complements (Comps; about him/her) and whether they matched or mismatched a matrix-clause subject in gender. Results Across L1 and L2 speakers, we found that anaphora-linked ERPDs for Mods vs. Comps in evoked power first arose in low γ and then in broadband γ. Referential elements first seem to be retrieved from working memory by narrowband processes in low γ and then referential identification seems to be computed in broadband-γ output. Interactions between discourse- and syntax-based referential processes for the Mods vs. Comps in these ERPDs furthermore suggest that multidomain γ-band processing enables a range of elementary operations for discourse and semantic interpretation. Discussion We argue that a multidomain mechanism enabling operations conditioned by the syntactic and semantic nature of the elements processed interacts with local brain microcircuits representing features and feature sets that have been established in L1 or L2 acquisition, accounting for a single language epistemology across learning contexts.
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Affiliation(s)
- Laurent Dekydtspotter
- Department of French & Italian, Indiana University, Bloomington, IN, United States
- Department of Second Language Studies, Indiana University, Bloomington, IN, United States
| | - A. Kate Miller
- Department of World Languages and Cultures, Indiana University–Indianapolis, Indianapolis, IN, United States
| | - Kyle Swanson
- Oral English Proficiency Program, Purdue University, West Lafayette, IN, United States
| | - Jih-Ho Cha
- Department of Second Language Studies, Indiana University, Bloomington, IN, United States
| | - Yanyu Xiong
- Alabama Life Research Institute, University of Alabama, Tuscaloosa, AL, United States
| | - Jae-Hyun Ahn
- Department of Second Language Studies, Indiana University, Bloomington, IN, United States
| | - Jane A. Gilbert
- Department of French & Italian, Indiana University, Bloomington, IN, United States
| | - Decker Pope
- Department of French & Italian, Indiana University, Bloomington, IN, United States
| | - Mike Iverson
- Department of Second Language Studies, Indiana University, Bloomington, IN, United States
| | - Kent Meinert
- Cognitive Science Program, Indiana University, Bloomington, IN, United States
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