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Gillespie AK, Astudillo Maya D, Denovellis EL, Desse S, Frank LM. Neurofeedback training can modulate task-relevant memory replay rate in rats. eLife 2024; 12:RP90944. [PMID: 38958562 PMCID: PMC11221834 DOI: 10.7554/elife.90944] [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: 07/04/2024] Open
Abstract
Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.
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Affiliation(s)
- Anna K Gillespie
- Departments of Biological Structure and Lab Medicine & Pathology, University of WashingtonSeattleUnited States
- Departments of Physiology and Psychiatry and the Kavli Institute for Fundamental Neuroscience, University of California, San FranciscoSan FranciscoUnited States
| | - Daniela Astudillo Maya
- Departments of Physiology and Psychiatry and the Kavli Institute for Fundamental Neuroscience, University of California, San FranciscoSan FranciscoUnited States
| | - Eric L Denovellis
- Departments of Physiology and Psychiatry and the Kavli Institute for Fundamental Neuroscience, University of California, San FranciscoSan FranciscoUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
| | - Sachi Desse
- Departments of Physiology and Psychiatry and the Kavli Institute for Fundamental Neuroscience, University of California, San FranciscoSan FranciscoUnited States
| | - Loren M Frank
- Departments of Physiology and Psychiatry and the Kavli Institute for Fundamental Neuroscience, University of California, San FranciscoSan FranciscoUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
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2
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Feldman MJ, Bliss-Moreau E, Lindquist KA. The neurobiology of interoception and affect. Trends Cogn Sci 2024; 28:643-661. [PMID: 38395706 PMCID: PMC11222051 DOI: 10.1016/j.tics.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 02/25/2024]
Abstract
Scholars have argued for centuries that affective states involve interoception, or representations of the state of the body. Yet, we lack a mechanistic understanding of how signals from the body are transduced, transmitted, compressed, and integrated by the brains of humans to produce affective states. We suggest that to understand how the body contributes to affect, we first need to understand information flow through the nervous system's interoceptive pathways. We outline such a model and discuss how unique anatomical and physiological aspects of interoceptive pathways may give rise to the qualities of affective experiences in general and valence and arousal in particular. We conclude by considering implications and future directions for research on interoception, affect, emotions, and human mental experiences.
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Affiliation(s)
- M J Feldman
- Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - E Bliss-Moreau
- Department of Psychology, University of California Davis, Davis, CA, USA; California National Primate Research Center, University of California Davis, Davis, CA, USA
| | - K A Lindquist
- Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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3
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Aucoin A, Lin KK, Gothard KM. Detection of latent brain states from baseline neural activity in the amygdala. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.14.598974. [PMID: 38915563 PMCID: PMC11195171 DOI: 10.1101/2024.06.14.598974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The amygdala responds to a large variety of socially and emotionally salient environmental and interoceptive stimuli. The context in which these stimuli occur determines their social and emotional significance. In canonical neurophysiological studies, the fast-paced succession of stimuli and events induce phasic changes in neural activity. During inter-trial intervals neural activity is expected to return to a stable and relatively featureless baseline. Context, such as the presence of a social partner, or the similarity of trials in a blocked design, induces brain states that can transcend the fast-paced succession of stimuli and can be recovered from the baseline firing rate of neurons. Indeed, the baseline firing rates of neurons in the amygdala change between blocks of trials of gentle grooming touch, delivered by a trusted social partner, and non-social airflow stimuli, delivered by a computer-controlled air valve. In this experimental paradigm, the presence of the groomer alone was sufficient to induce small but significant changes in baseline firing rates. Here, we examine local field potentials (LFP) recorded during these baseline periods to determine whether context was encoded by network dynamics that emerge in the local field potentials from the activity of large ensembles of neurons. We found that machine learning techniques can reliably decode social vs. non-social context from spectrograms of baseline local field potentials. Notably, decoding accuracy improved significantly with access to broad-band information. No significant differences were detected between the nuclei of the amygdala that receive direct or indirect inputs from areas of the prefrontal cortex known to coordinate flexible, context-dependent behaviors. The lack of nuclear specificity suggests that context-related synaptic inputs arise from a shared source, possibly interoceptive inputs that signal the sympathetic- vs. parasympathetic-dominated states characterizing non-social and social blocks, respectively.
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Affiliation(s)
- Alexa Aucoin
- Program in Applied Mathematics, University of Arizona
| | - Kevin K Lin
- Program in Applied Mathematics, University of Arizona
- Department of Mathematics, University of Arizona
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4
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Corredor D, Segobin S, Hinault T, Eustache F, Dayan J, Guillery-Girard B, Naveau M. The multiscale topological organization of the functional brain network in adolescent PTSD. Cereb Cortex 2024; 34:bhae246. [PMID: 38864573 PMCID: PMC11167567 DOI: 10.1093/cercor/bhae246] [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: 01/04/2024] [Revised: 05/17/2024] [Accepted: 05/18/2024] [Indexed: 06/13/2024] Open
Abstract
The experience of an extremely aversive event can produce enduring deleterious behavioral, and neural consequences, among which posttraumatic stress disorder (PTSD) is a representative example. Although adolescence is a period of great exposure to potentially traumatic events, the effects of trauma during adolescence remain understudied in clinical neuroscience. In this exploratory work, we aim to study the whole-cortex functional organization of 14 adolescents with PTSD using a data-driven method tailored to our population of interest. To do so, we built on the network neuroscience framework and specifically on multilayer (multisubject) community analysis to study the functional connectivity of the brain. We show, across different topological scales (the number of communities composing the cortex), a hyper-colocalization between regions belonging to occipital and pericentral regions and hypo-colocalization in middle temporal, posterior-anterior medial, and frontal cortices in the adolescent PTSD group compared to a nontrauma exposed group of adolescents. These preliminary results raise the question of an altered large-scale cortical organization in adolescent PTSD, opening an interesting line of research for future investigations.
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Affiliation(s)
- David Corredor
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
| | - Shailendra Segobin
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
| | - Thomas Hinault
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
| | - Francis Eustache
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
| | - Jacques Dayan
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
- Pôle Hospitalo-Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Centre Hospitalier Guillaume Régnier, Université Rennes 1, Rennes 35700, France
| | - Bérengère Guillery-Girard
- Centre Cyceron, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie Université, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, Caen 14000, France
| | - Mikaël Naveau
- UNICAEN, CNRS, INSERM, CEA, UAR3408 CYCERON, Normandie Université, Caen 14000, France
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5
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Tao Y, Schubert T, Wiley R, Stark C, Rapp B. Cortical and Subcortical Mechanisms of Orthographic Word-form Learning. J Cogn Neurosci 2024; 36:1071-1098. [PMID: 38527084 DOI: 10.1162/jocn_a_02147] [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: 03/27/2024]
Abstract
We examined the initial stages of orthographic learning in real time as literate adults learned spellings for spoken pseudowords during fMRI scanning. Participants were required to learn and store orthographic word forms because the pseudoword spellings were not uniquely predictable from sound to letter mappings. With eight learning trials per word form, we observed changes in the brain's response as learning was taking place. Accuracy was evaluated during learning, immediately after scanning, and 1 week later. We found evidence of two distinct learning systems-hippocampal and neocortical-operating during orthographic learning, consistent with the predictions of dual systems theories of learning/memory such as the complementary learning systems framework [McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychological Review, 102, 419-457, 1995]. The bilateral hippocampus and the visual word form area (VWFA) showed significant BOLD response changes over learning, with the former exhibiting a rising pattern and the latter exhibiting a falling pattern. Moreover, greater BOLD signal increase in the hippocampus was associated with better postscan recall. In addition, we identified two distinct bilateral brain networks that mirrored the rising and falling patterns of the hippocampus and VWFA. Functional connectivity analysis revealed that regions within each network were internally synchronized. These novel findings highlight, for the first time, the relevance of multiple learning systems in orthographic learning and provide a paradigm that can be used to address critical gaps in our understanding of the neural bases of orthographic learning in general and orthographic word-form learning specifically.
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Fernandino L, Binder JR. How does the "default mode" network contribute to semantic cognition? BRAIN AND LANGUAGE 2024; 252:105405. [PMID: 38579461 PMCID: PMC11135161 DOI: 10.1016/j.bandl.2024.105405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 02/26/2024] [Accepted: 03/23/2024] [Indexed: 04/07/2024]
Abstract
This review examines whether and how the "default mode" network (DMN) contributes to semantic processing. We review evidence implicating the DMN in the processing of individual word meanings and in sentence- and discourse-level semantics. Next, we argue that the areas comprising the DMN contribute to semantic processing by coordinating and integrating the simultaneous activity of local neuronal ensembles across multiple unimodal and multimodal cortical regions, creating a transient, global neuronal ensemble. The resulting ensemble implements an integrated simulation of phenomenological experience - that is, an embodied situation model - constructed from various modalities of experiential memory traces. These situation models, we argue, are necessary not only for semantic processing but also for aspects of cognition that are not traditionally considered semantic. Although many aspects of this proposal remain provisional, we believe it provides new insights into the relationships between semantic and non-semantic cognition and into the functions of the DMN.
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Affiliation(s)
- Leonardo Fernandino
- Department of Neurology, Medical College of Wisconsin, USA; Department of Biomedical Engineering, Medical College of Wisconsin, USA.
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, USA; Department of Biophysics, Medical College of Wisconsin, USA
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7
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Hinzen W, Palaniyappan L. The 'L-factor': Language as a transdiagnostic dimension in psychopathology. Prog Neuropsychopharmacol Biol Psychiatry 2024; 131:110952. [PMID: 38280712 DOI: 10.1016/j.pnpbp.2024.110952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 12/20/2023] [Accepted: 01/23/2024] [Indexed: 01/29/2024]
Abstract
Thoughts and moods constituting our mental life incessantly change. When the steady flow of this dynamics diverges in clinical directions, the possible pathways involved are captured through discrete diagnostic labels. Yet a single vulnerable neurocognitive system may be causally involved in psychopathological deviations transdiagnostically. We argue that language viewed as integrating cortical functions is the best current candidate, whose forms of breakdown along its different dimensions are then manifest as symptoms - from prosodic abnormalities and rumination in depression to distortions of speech perception in verbal hallucinations, distortions of meaning and content in delusions, or disorganized speech in formal thought disorder. Spontaneous connected speech provides continuous objective readouts generating a highly accessible bio-behavioral marker with the potential of revolutionizing neuropsychological measurement. This argument turns language into a transdiagnostic 'L-factor' providing an analytical and mechanistic substrate for previously proposed latent general factors of psychopathology ('p-factor') and cognitive functioning ('c-factor'). Together with immense practical opportunities afforded by rapidly advancing natural language processing (NLP) technologies and abundantly available data, this suggests a new era of translational clinical psychiatry, in which both psychopathology and language may be rethought together.
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Affiliation(s)
- Wolfram Hinzen
- Department of Translation & Language Sciences, Universitat Pompeu Fabra, Barcelona, Spain; Institut Català de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal H4H1R3, Quebec, Canada; Robarts Research Institute & Lawson Health Research Institute, London, ON, Canada
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8
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Xu M, Lin R, Wen H, Wang Y, Wong J, Peng Z, Liu L, Nie B, Luo J, Tang X, Cui S. Electroacupuncture Enhances the Functional Connectivity of Limbic System to Neocortex in the 5xFAD Mouse Model of Alzheimer's Disease. Neuroscience 2024; 544:28-38. [PMID: 38423162 DOI: 10.1016/j.neuroscience.2024.02.025] [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: 09/01/2023] [Revised: 02/04/2024] [Accepted: 02/24/2024] [Indexed: 03/02/2024]
Abstract
Our previous study revealed that acupuncture may exhibit therapeutic effects on Alzheimer's disease (AD) through the activation of metabolism in memory-related brain regions. However, the underlying functional mechanism remains poorly understood and warrants further investigation. In this study, we used resting-state functional magnetic resonance imaging (rsfMRI) to explore the potential effect of electroacupuncture (EA) on the 5xFAD mouse model of AD. We found that the EA group exhibited significant improvements in the number of platforms crossed and the time spent in the target quadrant when compared with the Model group (p < 0.05). The functional connectivity (FC) of left hippocampus (Hip) was enhanced significantly among 12 regions of interest (ROIs) in the EA group (p < 0.05). Based on the left Hip as the seed point, the rsfMRI analysis of the entire brain revealed increased FC between the limbic system and the neocortex in the 5xFAD mice after EA treatment. Additionally, the expression of amyloid-β(Aβ) protein and deposition in the Hip showed a downward trend in the EA group compared to the Model group (p < 0.05). In conclusion, our findings indicate that EA treatment can improve the learning and memory abilities and inhibit the expression of Aβ protein and deposition of 5xFAD mice. This improvement may be attributed to the enhancement of the resting-state functional activity and connectivity within the limbic-neocortical neural circuit, which are crucial for cognition, motor function, as well as spatial learning and memory abilities in AD mice.
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Affiliation(s)
- Mingzhu Xu
- Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518100, China.
| | - Run Lin
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China
| | - Huaneng Wen
- Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518100, China; The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Yixiao Wang
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China
| | - John Wong
- MGH Institute of Health Professions, Boston, MA, USA
| | - Zhihua Peng
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China
| | - Lu Liu
- Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518100, China
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100000, China
| | - Jing Luo
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China
| | - Xiaoyu Tang
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China
| | - Shaoyang Cui
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen 518034, China.
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9
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Zárate-Rochín AM. Contemporary neurocognitive models of memory: A descriptive comparative analysis. Neuropsychologia 2024; 196:108846. [PMID: 38430963 DOI: 10.1016/j.neuropsychologia.2024.108846] [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: 11/03/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
The great complexity involved in the study of memory has given rise to numerous hypotheses and models associated with various phenomena at different levels of analysis. This has allowed us to delve deeper in our knowledge about memory but has also made it difficult to synthesize and integrate data from different lines of research. In this context, this work presents a descriptive comparative analysis of contemporary models that address the structure and function of multiple memory systems. The main goal is to outline a panoramic view of the key elements that constitute these models in order to visualize both the current state of research and possible future directions. The elements that stand out from different levels of analysis are distributed neural networks, hierarchical organization, predictive coding, homeostasis, and evolutionary perspective.
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Affiliation(s)
- Alba Marcela Zárate-Rochín
- Instituto de Investigaciones Cerebrales, Universidad Veracruzana, Dr. Castelazo Ayala s/n, Industrial Animas, 91190, Xalapa-Enríquez, Veracruz, Mexico.
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10
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Cortese A, Kawato M. The cognitive reality monitoring network and theories of consciousness. Neurosci Res 2024; 201:31-38. [PMID: 38316366 DOI: 10.1016/j.neures.2024.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 01/17/2024] [Accepted: 01/17/2024] [Indexed: 02/07/2024]
Abstract
Theories of consciousness abound. However, it is difficult to arbitrate reliably among competing theories because they target different levels of neural and cognitive processing or anatomical loci, and only some were developed with computational models in mind. In particular, theories of consciousness need to fully address the three levels of understanding of the brain proposed by David Marr: computational theory, algorithms and hardware. Most major theories refer to only one or two levels, often indirectly. The cognitive reality monitoring network (CRMN) model is derived from computational theories of mixture-of-experts architecture, hierarchical reinforcement learning and generative/inference computing modules, addressing all three levels of understanding. A central feature of the CRMN is the mapping of a gating network onto the prefrontal cortex, making it a prime coding circuit involved in monitoring the accuracy of one's mental states and distinguishing them from external reality. Because the CRMN builds on the hierarchical and layer structure of the cerebral cortex, it may connect research and findings across species, further enabling concrete computational models of consciousness with new, explicitly testable hypotheses. In sum, we discuss how the CRMN model can help further our understanding of the nature and function of consciousness.
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Affiliation(s)
- Aurelio Cortese
- Computational Neuroscience Labs, ATR Institute International, Kyoto 619-0228, Japan.
| | - Mitsuo Kawato
- Computational Neuroscience Labs, ATR Institute International, Kyoto 619-0228, Japan; XNef, Kyoto 619-0288, Japan.
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11
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Clancy KJ, Devignes Q, Ren B, Pollmann Y, Nielsen SR, Howell K, Kumar P, Belleau EL, Rosso IM. Spatiotemporal dynamics of hippocampal-cortical networks underlying the unique phenomenological properties of trauma-related intrusive memories. Mol Psychiatry 2024:10.1038/s41380-024-02486-9. [PMID: 38454081 DOI: 10.1038/s41380-024-02486-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 02/07/2024] [Accepted: 02/12/2024] [Indexed: 03/09/2024]
Abstract
Trauma-related intrusive memories (TR-IMs) possess unique phenomenological properties that contribute to adverse post-traumatic outcomes, positioning them as critical intervention targets. However, transdiagnostic treatments for TR-IMs are scarce, as their underlying mechanisms have been investigated separate from their unique phenomenological properties. Extant models of more general episodic memory highlight dynamic hippocampal-cortical interactions that vary along the anterior-posterior axis of the hippocampus (HPC) to support different cognitive-affective and sensory-perceptual features of memory. Extending this work into the unique properties of TR-IMs, we conducted a study of eighty-four trauma-exposed adults who completed daily ecological momentary assessments of TR-IM properties followed by resting-state functional magnetic resonance imaging (rs-fMRI). Spatiotemporal dynamics of anterior and posterior hippocampal (a/pHPC)-cortical networks were assessed using co-activation pattern analysis to investigate their associations with different properties of TR-IMs. Emotional intensity of TR-IMs was inversely associated with the frequency and persistence of an aHPC-default mode network co-activation pattern. Conversely, sensory features of TR-IMs were associated with more frequent co-activation of the HPC with sensory cortices and the ventral attention network, and the reliving of TR-IMs in the "here-and-now" was associated with more persistent co-activation of the pHPC and the visual cortex. Notably, no associations were found between HPC-cortical network dynamics and conventional symptom measures, including TR-IM frequency or retrospective recall, underscoring the utility of ecological assessments of memory properties in identifying their neural substrates. These findings provide novel insights into the neural correlates of the unique features of TR-IMs that are critical for the development of individualized, transdiagnostic treatments for this pervasive, difficult-to-treat symptom.
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Affiliation(s)
- Kevin J Clancy
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Quentin Devignes
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, USA
| | - Yara Pollmann
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Sienna R Nielsen
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Kristin Howell
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Poornima Kumar
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Emily L Belleau
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, 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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12
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Orlando IF, O'Callaghan C, Lam A, McKinnon AC, Tan JBC, Michaelian JC, Kong SDX, D'Rozario AL, Naismith SL. Sleep spindle architecture associated with distinct clinical phenotypes in older adults at risk for dementia. Mol Psychiatry 2024; 29:402-411. [PMID: 38052981 PMCID: PMC11116104 DOI: 10.1038/s41380-023-02335-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 12/07/2023]
Abstract
Sleep spindles are a hallmark of non-REM sleep and play a fundamental role in memory consolidation. Alterations in these spindles are emerging as sensitive biomarkers for neurodegenerative diseases of ageing. Understanding the clinical presentations associated with spindle alterations may help to elucidate the functional role of these distinct electroencephalographic oscillations and the pathophysiology of sleep and neurodegenerative disorders. Here, we use a data-driven approach to examine the sleep, memory and default mode network connectivity phenotypes associated with sleep spindle architecture in older adults (mean age = 66 years). Participants were recruited from a specialist clinic for early diagnosis and intervention for cognitive decline, with a proportion showing mild cognitive deficits on neuropsychological testing. In a sample of 88 people who underwent memory assessment, overnight polysomnography and resting-state fMRI, a k-means cluster analysis was applied to spindle measures of interest: fast spindle density, spindle duration and spindle amplitude. This resulted in three clusters, characterised by preserved spindle architecture with higher fast spindle density and longer spindle duration (Cluster 1), and alterations in spindle architecture (Clusters 2 and 3). These clusters were further characterised by reduced memory (Clusters 2 and 3) and nocturnal hypoxemia, associated with sleep apnea (Cluster 3). Resting-state fMRI analysis confirmed that default mode connectivity was related to spindle architecture, although directionality of this relationship differed across the cluster groups. Together, these results confirm a diversity in spindle architecture in older adults, associated with clinically meaningful phenotypes, including memory function and sleep apnea. They suggest that resting-state default mode connectivity during the awake state can be associated with sleep spindle architecture; however, this is highly dependent on clinical phenotype. Establishing relationships between clinical and neuroimaging features and sleep spindle alterations will advance our understanding of the bidirectional relationships between sleep changes and neurodegenerative diseases of ageing.
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Affiliation(s)
- Isabella F Orlando
- Brain and Mind Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Claire O'Callaghan
- Brain and Mind Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Aaron Lam
- Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia
- School of Psychology, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia
| | - Andrew C McKinnon
- Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia
- School of Psychology, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia
| | - Joshua B C Tan
- Brain and Mind Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Johannes C Michaelian
- Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia
- School of Psychology, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia
| | - Shawn D X Kong
- Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia
- School of Psychology, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia
- NHMRC Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration (CogSleep CRE), Sydney, NSW, Australia
| | - Angela L D'Rozario
- NHMRC Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration (CogSleep CRE), Sydney, NSW, Australia
- School of Psychological Sciences, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
- CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University, Sydney, NSW, Australia
| | - Sharon L Naismith
- Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia.
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia.
- School of Psychology, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia.
- NHMRC Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration (CogSleep CRE), Sydney, NSW, Australia.
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13
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Sohn W, Di X, Liang Z, Zhang Z, Biswal BB. Explorations of using a convolutional neural network to understand brain activations during movie watching. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576341. [PMID: 38328194 PMCID: PMC10849516 DOI: 10.1101/2024.01.20.576341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Neuroimaging studies increasingly use naturalistic stimuli like video clips to trigger complex brain activations, but the complexity of such stimuli makes it difficult to assign specific functions to the resulting brain activations, particularly for higher-level content like social interactions. To address this challenge, researchers have turned to deep neural networks, e.g., convolutional neural networks (CNNs). CNNs have shown success in image recognition due to their different levels of features enabling high performance. In this study, we used pre-trained VGG-16, a popular CNN model, to analyze video data and extract hierarchical features from low-level shallow layers to high-level deeper layers, linking these activations to different levels of activation of the human brain. We hypothesized that activations in different layers of VGG-16 would be associated with different levels of brain activation and visual processing hierarchy in the brain. We were also curious about which brain regions would be associated with deeper convolutional layers in VGG-16. The study analyzed a functional MRI (fMRI) dataset where participants watched the cartoon movie Partly Cloudy. Frames of the videos were fed into VGG-16, and activation maps from different kernels and layers were extracted. Time series of the average activation patterns for each kernel were created and fed into a voxel-wise model to study brain activations. Results showed that lower convolutional layers (1st convolutional layer) were mostly associated with lower visual regions, but some kernels (6, 19, 24, 42, 55, and 58) surprisingly showed associations with activations in the posterior cingulate cortex, part of the default mode network. Deeper convolutional layers were associated with more anterior and lateral portions of the visual cortex (e.g., the lateral occipital complex) and the supramarginal gyrus. Analyzing activation features associated with different brain regions showed the promise and limitations of using CNNs to link video content to brain functions.
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Affiliation(s)
- Wonbum Sohn
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07029, USA
- Rutgers Biomedical and Health Sciences, Rutgers School of Graduate Studies, Newark, NJ, 07039, USA
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07029, USA
| | - Zhen Liang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China, 518060
| | - Zhiguo Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, 518060, China
| | - Bharat B. Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07029, USA
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14
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Aggleton JP, Vann SD, O'Mara SM. Converging diencephalic and hippocampal supports for episodic memory. Neuropsychologia 2023; 191:108728. [PMID: 37939875 DOI: 10.1016/j.neuropsychologia.2023.108728] [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: 07/26/2023] [Revised: 10/25/2023] [Accepted: 11/03/2023] [Indexed: 11/10/2023]
Abstract
To understand the neural basis of episodic memory it is necessary to appreciate the significance of the fornix. This pathway creates a direct link between those temporal lobe and medial diencephalic sites responsible for anterograde amnesia. A collaboration with Andrew Mayes made it possible to recruit and scan 38 patients with colloid cysts in the third ventricle, a condition associated with variable fornix damage. Complete fornix loss was seen in three patients, who suffered chronic long-term memory problems. Volumetric analyses involving all 38 patients then revealed a highly consistent relationship between mammillary body volume and the recall of episodic memory. That relationship was not seen for working memory or tests of recognition memory. Three different methods all supported a dissociation between recollective-based recognition (impaired) and familiarity-based recognition (spared). This dissociation helped to show how the mammillary body-anterior thalamic nuclei axis, as well as the hippocampus, is vital for episodic memory yet is not required for familiarity-based recognition. These findings set the scene for a reformulation of temporal lobe and diencephalic amnesia. In this revised model, these two regions converge on overlapping cortical areas, including retrosplenial cortex. The united actions of the hippocampal formation and the anterior thalamic nuclei on these cortical areas enable episodic memory encoding and consolidation, impacting on subsequent recall.
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Affiliation(s)
- John P Aggleton
- School of Psychology, Cardiff University, Cardiff, CF10 3AT, Wales, United Kingdom.
| | - Seralynne D Vann
- School of Psychology, Cardiff University, Cardiff, CF10 3AT, Wales, United Kingdom
| | - Shane M O'Mara
- School of Psychology and Trinity College Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, Dublin, D02 PN40, Ireland.
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15
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Mckeown B, Strawson WH, Zhang M, Turnbull A, Konu D, Karapanagiotidis T, Wang HT, Leech R, Xu T, Hardikar S, Bernhardt B, Margulies D, Jefferies E, Wammes J, Smallwood J. Experience sampling reveals the role that covert goal states play in task-relevant behavior. Sci Rep 2023; 13:21710. [PMID: 38066069 PMCID: PMC10709616 DOI: 10.1038/s41598-023-48857-0] [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: 05/26/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023] Open
Abstract
Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states. However, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established deliberate task focus was linked to faster target detection, and brain states underlying this experience-and target detection-were associated with activity patterns emphasizing the fronto-parietal network. In contrast, brain states underlying off-task experiences-and vigilance periods-were linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states.
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Affiliation(s)
- Brontë Mckeown
- Psychology Department, Queen's University, Kingston, K7L 3N6, Canada.
| | - Will H Strawson
- Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, BN1 9RH, UK
| | - Meichao Zhang
- CAS Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Adam Turnbull
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Delali Konu
- Department of Psychology, Durham University, Durham, DH1 3LE, UK
| | | | - Hao-Ting Wang
- Centre de Recherche de l'institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, H3W 1W5, Canada
| | - Robert Leech
- Centre for Neuroimaging Science, King's College, London, SE5 8AF, UK
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, 10022, USA
| | - Samyogita Hardikar
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
| | - Boris Bernhardt
- Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, Canada
| | - Daniel Margulies
- Integrative Neuroscience and Cognition Center (UMR 8002, Centre National de la Recherche Scientifique (CNRS) and Université de Paris, 75006, Paris, France
| | | | - Jeffrey Wammes
- Psychology Department, Queen's University, Kingston, K7L 3N6, Canada
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16
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Jeong H, Namboodiri VMK, Jung MW, Andermann ML. Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions. Curr Biol 2023; 33:5185-5198.e4. [PMID: 37995696 PMCID: PMC10842729 DOI: 10.1016/j.cub.2023.10.073] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 08/29/2023] [Accepted: 10/31/2023] [Indexed: 11/25/2023]
Abstract
Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 ripples during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and ripple events differ from dorsal CA1. We identified three clusters of putative excitatory neurons in mouse visual cortex that are preferentially excited together with either dorsal or intermediate CA1 ripples or suppressed before both ripples. Neurons in each cluster were evenly distributed across primary and higher visual cortices and co-active even in the absence of ripples. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence preceding and predicting ripples: (1) suppression of ripple-suppressed cortical neurons, (2) thalamic silence, and (3) activation of intermediate CA1-ripple-activated cortical neurons. We propose that coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.
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Affiliation(s)
- Huijeong Jeong
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Center for Synaptic Brain Dysfunctions, Institute for Basic Science, 291 Daehak-ro, Daejeon 34141, Republic of Korea; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Republic of Korea
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Neuroscience Graduate Program, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Weill Institute for Neuroscience, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA.
| | - Min Whan Jung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, 291 Daehak-ro, Daejeon 34141, Republic of Korea; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Republic of Korea.
| | - Mark L Andermann
- Division of Endocrinology, Metabolism, and Diabetes, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA; Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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17
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Varma MM, Yu R. A spontaneous neural replay account for involuntary autobiographical memories and déjà vu experiences. Behav Brain Sci 2023; 46:e380. [PMID: 37961766 DOI: 10.1017/s0140525x23000109] [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: 11/15/2023]
Abstract
Barzykowski and Moulin argue both involuntary autobiographical memories and déjà vu experiences rely on the same involuntary memory retrieval processes but their underlying neurological basis remains unclear. We propose spontaneous neural replay in the default mode network (DMN) and hippocampus as the basis for involuntary autobiographical memories, whereas for déjà vu experiences such transient activation is limited to the DMN.
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Affiliation(s)
- Mohith M Varma
- Department of Management, School of Business, Hong Kong Baptist University, Hong Kong, S.A.R. China
| | - Rongjun Yu
- Department of Management, School of Business, Hong Kong Baptist University, Hong Kong, S.A.R. China
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18
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Kucyi A, Kam JWY, Andrews-Hanna JR, Christoff K, Whitfield-Gabrieli S. Recent advances in the neuroscience of spontaneous and off-task thought: implications for mental health. NATURE MENTAL HEALTH 2023; 1:827-840. [PMID: 37974566 PMCID: PMC10653280 DOI: 10.1038/s44220-023-00133-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/25/2023] [Indexed: 11/19/2023]
Abstract
People spend a remarkable 30-50% of awake life thinking about something other than what they are currently doing. These experiences of being "off-task" can be described as spontaneous thought when mental dynamics are relatively flexible. Here we review recent neuroscience developments in this area and consider implications for mental wellbeing and illness. We provide updated overviews of the roles of the default mode network and large-scale network dynamics, and we discuss emerging candidate mechanisms involving hippocampal memory (sharp-wave ripples, replay) and neuromodulatory (noradrenergic and serotonergic) systems. We explore how distinct brain states can be associated with or give rise to adaptive and maladaptive forms of thought linked to distinguishable mental health outcomes. We conclude by outlining new directions in the neuroscience of spontaneous and off-task thought that may clarify mechanisms, lead to personalized biomarkers, and facilitate therapy developments toward the goals of better understanding and improving mental health.
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Affiliation(s)
- Aaron Kucyi
- Department of Psychological and Brain Sciences, Drexel University
| | - Julia W. Y. Kam
- Department of Psychology and Hotchkiss Brain Institute, University of Calgary
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19
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Feliciano-Ramos PA, Galazo M, Penagos H, Wilson M. Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices. Learn Mem 2023; 30:221-236. [PMID: 37758288 PMCID: PMC10547389 DOI: 10.1101/lm.053834.123] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/25/2023] [Indexed: 10/03/2023]
Abstract
Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.
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Affiliation(s)
- Pedro A Feliciano-Ramos
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Maria Galazo
- Neuroscience Program, Tulane Brain Institute, Tulane University, New Orleans, Louisana 70118, USA
- Department of Cell and Molecular Biology, Tulane Brain Institute, Tulane University, New Orleans, Louisana 70118, USA
| | - Hector Penagos
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Center for Brains, Minds, and Machines, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Matthew Wilson
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Center for Brains, Minds, and Machines, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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20
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Zhou S, Wei T, Liu X, Liu Y, Song W, Que X, Xing Y, Wang Z, Tang Y. Causal effects of COVID-19 on structural changes in specific brain regions: a Mendelian randomization study. BMC Med 2023; 21:261. [PMID: 37468885 DOI: 10.1186/s12916-023-02952-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 06/19/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Previous studies have found a correlation between coronavirus disease 2019 (COVID-19) and changes in brain structure and cognitive function, but it remains unclear whether COVID-19 causes brain structural changes and which specific brain regions are affected. Herein, we conducted a Mendelian randomization (MR) study to investigate this causal relationship and to identify specific brain regions vulnerable to COVID-19. METHODS Genome-wide association study (GWAS) data for COVID-19 phenotypes (28,900 COVID-19 cases and 3,251,161 controls) were selected as exposures, and GWAS data for brain structural traits (cortical thickness and surface area from 51,665 participants and volume of subcortical structures from 30,717 participants) were selected as outcomes. Inverse-variance weighted method was used as the main estimate method. The weighted median, MR-Egger, MR-PRESSO global test, and Cochran's Q statistic were used to detect heterogeneity and pleiotropy. RESULTS The genetically predicted COVID-19 infection phenotype was nominally associated with reduced cortical thickness in the caudal middle frontal gyrus (β = - 0.0044, p = 0.0412). The hospitalized COVID-19 phenotype was nominally associated with reduced cortical thickness in the lateral orbitofrontal gyrus (β = - 0.0049, p = 0.0328) and rostral middle frontal gyrus (β = - 0.0022, p = 0.0032) as well as with reduced cortical surface area of the middle temporal gyrus (β = - 10.8855, p = 0.0266). These causal relationships were also identified in the severe COVID-19 phenotype. Additionally, the severe COVID-19 phenotype was nominally associated with reduced cortical thickness in the cuneus (β = - 0.0024, p = 0.0168); reduced cortical surface area of the pericalcarine (β = - 2.6628, p = 0.0492), superior parietal gyrus (β = - 5.6310, p = 0.0408), and parahippocampal gyrus (β = - 0.1473, p = 0.0297); and reduced volume in the hippocampus (β = - 15.9130, p = 0.0024). CONCLUSIONS Our study indicates a suggestively significant association between genetic predisposition to COVID-19 and atrophy in specific functional regions of the human brain. Patients with COVID-19 and cognitive impairment should be actively managed to alleviate neurocognitive symptoms and minimize long-term effects.
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Affiliation(s)
- Shaojiong Zhou
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Tao Wei
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Xiaoduo Liu
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Yufei Liu
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Weiyi Song
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Xinwei Que
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China
| | - Yi Xing
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China.
| | - Zhibin Wang
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China.
| | - Yi Tang
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, 45 Changchun Street, Beijing, 100053, China.
- Neurodegenerative Laboratory of Ministry of Education of the Peoples Republic of China, Beijing, China.
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21
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Mill RD, Cole MW. Neural representation dynamics reveal computational principles of cognitive task learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.546751. [PMID: 37425922 PMCID: PMC10327096 DOI: 10.1101/2023.06.27.546751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
During cognitive task learning, neural representations must be rapidly constructed for novel task performance, then optimized for robust practiced task performance. How the geometry of neural representations changes to enable this transition from novel to practiced performance remains unknown. We hypothesized that practice involves a shift from compositional representations (task-general activity patterns that can be flexibly reused across tasks) to conjunctive representations (task-specific activity patterns specialized for the current task). Functional MRI during learning of multiple complex tasks substantiated this dynamic shift from compositional to conjunctive representations, which was associated with reduced cross-task interference (via pattern separation) and behavioral improvement. Further, we found that conjunctions originated in subcortex (hippocampus and cerebellum) and slowly spread to cortex, extending multiple memory systems theories to encompass task representation learning. The formation of conjunctive representations hence serves as a computational signature of learning, reflecting cortical-subcortical dynamics that optimize task representations in the human brain.
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22
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Xie B, Zhen Z, Guo O, Li H, Guo M, Zhen J. Progress on the hippocampal circuits and functions based on sharp wave ripples. Brain Res Bull 2023:110695. [PMID: 37353037 DOI: 10.1016/j.brainresbull.2023.110695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/18/2023] [Accepted: 06/20/2023] [Indexed: 06/25/2023]
Abstract
Sharp wave ripples (SWRs) are high-frequency synchronization events generated by hippocampal neuronal circuits during various forms of learning and reactivated during memory consolidation and recall. There is mounting evidence that SWRs are essential for storing spatial and social memories in rodents and short-term episodic memories in humans. Sharp wave ripples originate mainly from the hippocampal CA3 and subiculum, and can be transmitted to modulate neuronal activity in cortical and subcortical regions for long-term memory consolidation and behavioral guidance. Different hippocampal subregions have distinct functions in learning and memory. For instance, the dorsal CA1 is critical for spatial navigation, episodic memory, and learning, while the ventral CA1 and dorsal CA2 may work cooperatively to store and consolidate social memories. Here, we summarize recent studies demonstrating that SWRs are essential for the consolidation of spatial, episodic, and social memories in various hippocampal-cortical pathways, and review evidence that SWR dysregulation contributes to cognitive impairments in neurodegenerative and neurodevelopmental diseases.
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Affiliation(s)
- Boxu Xie
- Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zhihang Zhen
- Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Ouyang Guo
- Department of Biology, Boston University, Boston, MA, United States
| | - Heming Li
- Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Moran Guo
- Neurological Laboratory of Hebei Province, Shijiazhuang, China
| | - Junli Zhen
- Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, China; Neurological Laboratory of Hebei Province, Shijiazhuang, China.
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23
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Kamarajan C, Pandey AK, Chorlian DB, Meyers JL, Kinreich S, Pandey G, Subbie-Saenz de Viteri S, Zhang J, Kuang W, Barr PB, Aliev F, Anokhin AP, Plawecki MH, Kuperman S, Almasy L, Merikangas A, Brislin SJ, Bauer L, Hesselbrock V, Chan G, Kramer J, Lai D, Hartz S, Bierut LJ, McCutcheon VV, Bucholz KK, Dick DM, Schuckit MA, Edenberg HJ, Porjesz B. Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features. Behav Sci (Basel) 2023; 13:bs13050427. [PMID: 37232664 DOI: 10.3390/bs13050427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 05/08/2023] [Accepted: 05/11/2023] [Indexed: 05/27/2023] Open
Abstract
Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.
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Affiliation(s)
- Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Ashwini K Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Sivan Kinreich
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Stacey Subbie-Saenz de Viteri
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Jian Zhang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Peter B Barr
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Andrey P Anokhin
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | | | - Samuel Kuperman
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
| | - Laura Almasy
- The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alison Merikangas
- The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah J Brislin
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Lance Bauer
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - Grace Chan
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
| | - Dongbing Lai
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Sarah Hartz
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Laura J Bierut
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Vivia V McCutcheon
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Marc A Schuckit
- Department of Psychiatry, University of California, San Diego, CA 92103, USA
| | | | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
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24
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Tambini A, Miller J, Ehlert L, Kiyonaga A, D’Esposito M. Structured memory representations develop at multiple time scales in hippocampal-cortical networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.06.535935. [PMID: 37066263 PMCID: PMC10104124 DOI: 10.1101/2023.04.06.535935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Influential views of systems memory consolidation posit that the hippocampus rapidly forms representations of specific events, while neocortical networks extract regularities across events, forming the basis of schemas and semantic knowledge. Neocortical extraction of schematic memory representations is thought to occur on a protracted timescale of months, especially for information that is unrelated to prior knowledge. However, this theorized evolution of memory representations across extended timescales, and differences in the temporal dynamics of consolidation across brain regions, lack reliable empirical support. To examine the temporal dynamics of memory representations, we repeatedly exposed human participants to structured information via sequences of fractals, while undergoing longitudinal fMRI for three months. Sequence-specific activation patterns emerged in the hippocampus during the first 1-2 weeks of learning, followed one week later by high-level visual cortex, and subsequently the medial prefrontal and parietal cortices. Schematic, sequence-general representations emerged in the prefrontal cortex after 3 weeks of learning, followed by the medial temporal lobe and anterior temporal cortex. Moreover, hippocampal and most neocortical representations showed sustained rather than time-limited dynamics, suggesting that representations tend to persist across learning. These results show that specific hippocampal representations emerge early, followed by both specific and schematic representations at a gradient of timescales across hippocampal-cortical networks as learning unfolds. Thus, memory representations do not exist only in specific brain regions at a given point in time, but are simultaneously present at multiple levels of abstraction across hippocampal-cortical networks.
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Affiliation(s)
- Arielle Tambini
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY
| | - Jacob Miller
- Wu Tsai Institute, Department of Psychiatry, Yale University, New Haven, CT
| | - Luke Ehlert
- Department of Neurobiology and Behavior, University of California. Irvine, CA
| | - Anastasia Kiyonaga
- Department of Cognitive Science, University of California, San Diego, CA
| | - Mark D’Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA
- Department of Psychology, University of California, Berkeley, CA
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25
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Chen ZS, Wilson MA. How our understanding of memory replay evolves. J Neurophysiol 2023; 129:552-580. [PMID: 36752404 PMCID: PMC9988534 DOI: 10.1152/jn.00454.2022] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/20/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023] Open
Abstract
Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York, United States
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, New York, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, New York, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, New York, United States
| | - Matthew A Wilson
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
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26
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Kanaev IA. Entropy and Cross-Level Orderliness in Light of the Interconnection between the Neural System and Consciousness. ENTROPY (BASEL, SWITZERLAND) 2023; 25:418. [PMID: 36981307 PMCID: PMC10047885 DOI: 10.3390/e25030418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/01/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Despite recent advances, the origin and utility of consciousness remains under debate. Using an evolutionary perspective on the origin of consciousness, this review elaborates on the promising theoretical background suggested in the temporospatial theory of consciousness, which outlines world-brain alignment as a critical predisposition for controlling behavior and adaptation. Such a system can be evolutionarily effective only if it can provide instant cohesion between the subsystems, which is possible only if it performs an intrinsic activity modified in light of the incoming stimulation. One can assume that the world-brain interaction results in a particular interference pattern predetermined by connectome complexity. This is what organisms experience as their exclusive subjective state, allowing the anticipation of regularities in the environment. Thus, an anticipative system can emerge only in a regular environment, which guides natural selection by reinforcing corresponding reactions and decreasing the system entropy. Subsequent evolution requires complicated, layered structures and can be traced from simple organisms to human consciousness and society. This allows us to consider the mode of entropy as a subject of natural evolution rather than an individual entity.
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Affiliation(s)
- Ilya A Kanaev
- Department of Philosophy, Sun Yat-sen University, 135 Xingang Xi Rd, Guangzhou 510275, China
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27
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Bellana B, Ladyka-Wojcik N, Lahan S, Moscovitch M, Grady CL. Recollection and prior knowledge recruit the left angular gyrus during recognition. Brain Struct Funct 2023; 228:197-217. [PMID: 36441240 DOI: 10.1007/s00429-022-02597-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 11/09/2022] [Indexed: 11/29/2022]
Abstract
The human angular gyrus (AG) is implicated in recollection, or the ability to retrieve detailed memory content from a specific episode. A separate line of research examining the neural bases of more general mnemonic representations, extracted over multiple episodes, also highlights the AG as a core region of interest. To reconcile these separate views of AG function, the present fMRI experiment used a Remember-Know paradigm with famous (prior knowledge) and non-famous (no prior knowledge) faces to test whether AG activity could be modulated by both task-specific recollection and general prior knowledge within the same individuals. Increased BOLD activity in the left AG was observed during both recollection in the absence of prior knowledge (recollected > non-recollected or correctly rejected non-famous faces) and when prior knowledge was accessed in the absence of experiment-specific recollection (famous > non-famous correct rejections). This pattern was most prominent for the left AG as compared to the broader inferior parietal lobe. Recollection-related responses in the left AG increased with encoding duration and prior knowledge, despite prior knowledge being incidental to the recognition decision. Overall, the left AG appears sensitive to both task-specific recollection and the incidental access of general prior knowledge, thus broadening our notions of the kinds of mnemonic representations that drive activity in this region.
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Affiliation(s)
- Buddhika Bellana
- Department of Psychology, York University, Glendon Campus, Toronto, Canada. .,Department of Psychology, University of Toronto, Toronto, Canada. .,Rotman Research Institute, Baycrest, Toronto, Canada.
| | | | - Shany Lahan
- Department of Human Biology, University of Toronto, Toronto, Canada
| | - Morris Moscovitch
- Department of Psychology, University of Toronto, Toronto, Canada. .,Rotman Research Institute, Baycrest, Toronto, Canada.
| | - Cheryl L Grady
- Department of Psychology, University of Toronto, Toronto, Canada. .,Rotman Research Institute, Baycrest, Toronto, Canada. .,Department of Psychiatry, University of Toronto, Toronto, Canada.
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28
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Zhu Y, Zeng Y, Ren J, Zhang L, Chen C, Fernandez G, Qin S. Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization. eLife 2022; 11:e60190. [PMID: 36476501 PMCID: PMC9815824 DOI: 10.7554/elife.60190] [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: 06/18/2020] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning retroactively enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to distributed transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.
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Affiliation(s)
- Yannan Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Yimeng Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Jingyuan Ren
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Lingke Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Changming Chen
- School of Education, Chongqing Normal UniversityChongqingChina
| | - Guillen Fernandez
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
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29
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Zadbood A, Nastase S, Chen J, Norman KA, Hasson U. Neural representations of naturalistic events are updated as our understanding of the past changes. eLife 2022; 11:79045. [PMID: 36519530 PMCID: PMC9842385 DOI: 10.7554/elife.79045] [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: 03/28/2022] [Accepted: 12/01/2022] [Indexed: 12/23/2022] Open
Abstract
The brain actively reshapes our understanding of past events in light of new incoming information. In the current study, we ask how the brain supports this updating process during the encoding and recall of naturalistic stimuli. One group of participants watched a movie ('The Sixth Sense') with a cinematic 'twist' at the end that dramatically changed the interpretation of previous events. Next, participants were asked to verbally recall the movie events, taking into account the new 'twist' information. Most participants updated their recall to incorporate the twist. Two additional groups recalled the movie without having to update their memories during recall: one group never saw the twist; another group was exposed to the twist prior to the beginning of the movie, and thus the twist information was incorporated both during encoding and recall. We found that providing participants with information about the twist beforehand altered neural response patterns during movie-viewing in the default mode network (DMN). Moreover, presenting participants with the twist at the end of the movie changed the neural representation of the previously-encoded information during recall in a subset of DMN regions. Further evidence for this transformation was obtained by comparing the neural activation patterns during encoding and recall and correlating them with behavioral signatures of memory updating. Our results demonstrate that neural representations of past events encoded in the DMN are dynamically integrated with new information that reshapes our understanding in natural contexts.
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Affiliation(s)
- Asieh Zadbood
- Department of Psychology, Columbia UniversityNew YorkUnited States
| | - Samuel Nastase
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
| | - Janice Chen
- Department of Psychological and Brain Sciences, Johns Hopkins UniversityBaltimoreUnited States
| | - Kenneth A Norman
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
| | - Uri Hasson
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
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