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Nagy B, Protzner AB, Czigler B, Gaál ZA. Resting-state neural dynamics changes in older adults with post-COVID syndrome and the modulatory effect of cognitive training and sex. GeroScience 2024:10.1007/s11357-024-01324-8. [PMID: 39210163 DOI: 10.1007/s11357-024-01324-8] [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: 03/28/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
Post-COVID syndrome manifests with numerous neurological and cognitive symptoms, the precise origins of which are still not fully understood. As females and older adults are more susceptible to developing this condition, our study aimed to investigate how post-COVID syndrome alters intrinsic brain dynamics in older adults and whether biological sex and cognitive training might modulate these effects, with a specific focus on older females. The participants, aged between 60 and 75 years, were divided into three experimental groups: healthy old female, post-COVID old female and post-COVID old male. They underwent an adaptive task-switching training protocol. We analysed multiscale entropy and spectral power density of resting-state EEG data collected before and after the training to assess neural signal complexity and oscillatory power, respectively. We found no difference between post-COVID females and males before training, indicating that post-COVID similarly affected both sexes. However, cognitive training was effective only in post-COVID females and not in males, by modulating local neural processing capacity. This improvement was further evidenced by comparing healthy and post-COVID females, wherein the latter group showed increased finer timescale entropy (1-30 ms) and higher frequency band power (11-40 Hz) before training, but these differences disappeared following cognitive training. Our results suggest that in older adults with post-COVID syndrome, there is a pronounced shift from more global to local neural processing, potentially contributing to accelerated neural aging in this condition. However, cognitive training seems to offer a promising intervention method for modulating these changes in brain dynamics, especially among females.
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Affiliation(s)
- Boglárka Nagy
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
| | | | - Zsófia Anna Gaál
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
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Song C, Zhang X, Zhang Y, Han S, Ma K, Mao X, Lian Y, Cheng J. Comparision of spontaneous brain activity between hippocampal sclerosis and MRI-negative temporal lobe epilepsy. Epilepsy Behav 2024; 157:109751. [PMID: 38820678 DOI: 10.1016/j.yebeh.2024.109751] [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: 12/27/2023] [Revised: 03/05/2024] [Accepted: 03/21/2024] [Indexed: 06/02/2024]
Abstract
BACKGROUND Hippocampal sclerosis (HS) is a prevalent cause of temporal lobe epilepsy (TLE). However, up to 30% of individuals with TLE present negative magnetic resonance imaging (MRI) findings. A comprehensive grasp of the similarities and differences in brain activity among distinct TLE subtypes holds significant clinical and scientific importance. OBJECTIVE To comprehensively examine the similarities and differences between TLE with HS (TLE-HS) and MRI-negative TLE (TLE-N) regarding static and dynamic abnormalities in spontaneous brain activity (SBA). Furthermore, we aimed to determine whether these alterations correlate with epilepsy duration and cognition, and to determine a potential differential diagnostic index for clinical utility. METHODS We measured 12 SBA metrics in 38 patients with TLE-HS, 51 with TLE-N, and 53 healthy volunteers. Voxel-wise analysis of variance (ANOVA) and post-hoc comparisons were employed to compare these metrics. The six static metrics included amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), degree centrality (DC), and global signal correlation (GSCorr). Additionally, six corresponding dynamic metrics were assessed: dynamic ALFF (dALFF), dynamic fALFF (dfALFF), dynamic ReHo (dReHo), dynamic DC (dDC), dynamic VMHC (dVMHC), and dynamic GSCorr (dGSCorr). Receiver operating characteristic (ROC) curve analysis of abnormal indices was employed. Spearman correlation analyses were also conducted to examine the relationship between the abnormal indices, epilepsy duration and cognition scores. RESULTS Both TLE-HS and TLE-N presented as extensive neural network disorders, sharing similar patterns of SBA alterations. The regions with increased fALFF, dALFF, and dfALFF levels were predominantly observed in the mesial temporal lobe, thalamus, basal ganglia, pons, and cerebellum, forming a previously proposed mesial temporal epilepsy network. Conversely, decreased SBA metrics (fALFF, ReHo, dReHo, DC, GSCorr, and VMHC) consistently appeared in the lateral temporal lobe ipsilateral to the epileptic foci. Notably, SBA alterations were more obvious in patients with TLE-HS than in those with TLE-N. Additionally, patients with TLE-HS exhibited reduced VMHC in both mesial and lateral temporal lobes compared with patients with TLE-N, with the hippocampus displaying moderate discriminatory power (AUC = 0.759). Correlation analysis suggested that alterations in SBA indicators may be associated with epilepsy duration and cognitive scores. CONCLUSIONS The simultaneous use of static and dynamic SBA metrics provides evidence supporting the characterisation of both TLE-HS and TLE-N as complex network diseases, facilitating the exploration of mechanisms underlying epileptic activity and cognitive impairment. Overall, SBA abnormality patterns were generally similar between the TLE-HS and TLE-N groups, encompassing networks related to TLE and auditory and occipital visual functions. These changes were more pronounced in the TLE-HS group, particularly within the mesial and lateral temporal lobes.
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Affiliation(s)
- Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Xinyue Mao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
| | - Yajun Lian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province.
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Wu YH, Podvalny E, Levinson M, He BJ. Network mechanisms of ongoing brain activity's influence on conscious visual perception. Nat Commun 2024; 15:5720. [PMID: 38977709 PMCID: PMC11231278 DOI: 10.1038/s41467-024-50102-9] [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: 11/27/2023] [Accepted: 06/28/2024] [Indexed: 07/10/2024] Open
Abstract
Sensory inputs enter a constantly active brain, whose state is always changing from one moment to the next. Currently, little is known about how ongoing, spontaneous brain activity participates in online task processing. We employed 7 Tesla fMRI and a threshold-level visual perception task to probe the effects of prestimulus ongoing brain activity on perceptual decision-making and conscious recognition. Prestimulus activity originating from distributed brain regions, including visual cortices and regions of the default-mode and cingulo-opercular networks, exerted a diverse set of effects on the sensitivity and criterion of conscious recognition, and categorization performance. We further elucidate the mechanisms underlying these behavioral effects, revealing how prestimulus activity modulates multiple aspects of stimulus processing in highly specific and network-dependent manners. These findings reveal heretofore unknown network mechanisms underlying ongoing brain activity's influence on conscious perception, and may hold implications for understanding the precise roles of spontaneous activity in other brain functions.
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Affiliation(s)
- Yuan-Hao Wu
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Ella Podvalny
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, 10016, USA
- The Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Max Levinson
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Biyu J He
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
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4
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Northoff G, Zilio F, Zhang J. Beyond task response-Pre-stimulus activity modulates contents of consciousness. Phys Life Rev 2024; 49:19-37. [PMID: 38492473 DOI: 10.1016/j.plrev.2024.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 03/03/2024] [Indexed: 03/18/2024]
Abstract
The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).
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Affiliation(s)
- Georg Northoff
- University of Ottawa, Institute of Mental Health Research at the Royal Ottawa Hospital, Ottawa, Canada.
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy
| | - Jianfeng Zhang
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China.
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5
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Liang Q, Ma J, Chen X, Lin Q, Shu N, Dai Z, Lin Y. A Hybrid Routing Pattern in Human Brain Structural Network Revealed By Evolutionary Computation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:1895-1909. [PMID: 38194401 DOI: 10.1109/tmi.2024.3351907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
The human brain functional connectivity network (FCN) is constrained and shaped by the communication processes in the structural connectivity network (SCN). The underlying communication mechanism thus becomes a critical issue for understanding the formation and organization of the FCN. A number of communication models supported by different routing strategies have been proposed, with shortest path (SP), random diffusion (DIF), and spatial navigation (NAV) as the most typical, respectively requiring network global knowledge, local knowledge, and both for path seeking. Yet these models all assumed every brain region to use one routing strategy uniformly, ignoring convergent evidence that supports the regional heterogeneity in both terms of biological substrates and functional roles. In this regard, the current study developed a hybrid communication model that allowed each brain region to choose a routing strategy from SP, DIF, and NAV independently. A genetic algorithm was designed to uncover the underlying region-wise hybrid routing strategy (namely HYB). The HYB was found to outperform the three typical routing strategies in predicting FCN and facilitating robust communication. Analyses on HYB further revealed that brain regions in lower-order functional modules inclined to route signals using global knowledge, while those in higher-order functional modules preferred DIF that requires only local knowledge. Compared to regions that used global knowledge for routing, regions using DIF had denser structural connections, participated in more functional modules, but played a less dominant role within modules. Together, our findings further evidenced that hybrid routing underpins efficient SCN communication and locally heterogeneous structure-function coupling.
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Guan Z, Yu J, Shi Z, Liu X, Yu R, Lai T, Yang C, Dong H, Chen R, Wei L. Dynamic graph transformer network via dual-view connectivity for autism spectrum disorder identification. Comput Biol Med 2024; 174:108415. [PMID: 38599070 DOI: 10.1016/j.compbiomed.2024.108415] [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: 09/10/2023] [Revised: 03/17/2024] [Accepted: 04/03/2024] [Indexed: 04/12/2024]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that requires objective and accurate identification methods for effective early intervention. Previous population-based methods via functional connectivity (FC) analysis ignore the differences between positive and negative FCs, which provide the potential information complementarity. And they also require additional information to construct a pre-defined graph. Meanwhile, two challenging demand attentions are the imbalance of performance caused by the class distribution and the inherent heterogeneity of multi-site data. In this paper, we propose a novel dynamic graph Transformer network based on dual-view connectivity for ASD Identification. It is based on the Autoencoders, which regard the input feature as individual feature and without any inductive bias. First, a dual-view feature extractor is designed to extract individual and complementary information from positive and negative connectivity. Then Graph Transformer network is innovated with a hot plugging K-Nearest Neighbor (KNN) algorithm module which constructs a dynamic population graph without any additional information. Additionally, we introduce the PolyLoss function and the Vrex method to address the class imbalance and improve the model's generalizability. The evaluation experiment on 1102 subjects from the ABIDE I dataset demonstrates our method can achieve superior performance over several state-of-the-art methods and satisfying generalizability for ASD identification.
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Affiliation(s)
- Zihao Guan
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Jiaming Yu
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Zhenshan Shi
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350002, China
| | - Xiumei Liu
- Developmental and Behavior Pediatrics Department, Fujian Children's Hospital - Fujian Branch of Shanghai Children's Medical Center, Fuzhou, 350002, China; College of Clinical Medicine for Obstetrics Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350012, China
| | - Renping Yu
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Taotao Lai
- College of Computer and Control Engineering, Minjiang University, Fuzhou, 350108, China
| | - Changcai Yang
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Heng Dong
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Riqing Chen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Lifang Wei
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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7
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Christidi F, Orgianelis I, Merkouris E, Koutsokostas C, Tsiptsios D, Karavasilis E, Psatha EA, Tsiakiri A, Serdari A, Aggelousis N, Vadikolias K. A Comprehensive Review on the Role of Resting-State Functional Magnetic Resonance Imaging in Predicting Post-Stroke Motor and Sensory Outcomes. Neurol Int 2024; 16:189-201. [PMID: 38392953 PMCID: PMC10892788 DOI: 10.3390/neurolint16010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/05/2024] [Accepted: 01/12/2024] [Indexed: 02/25/2024] Open
Abstract
Stroke is a major leading cause of chronic disability, often affecting patients' motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging, and it allows for the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of a prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcomes. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcomes in stroke patients and evaluate the effects of different interventions.
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Affiliation(s)
- Foteini Christidi
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Ilias Orgianelis
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Ermis Merkouris
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Christos Koutsokostas
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Dimitrios Tsiptsios
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Efstratios Karavasilis
- Department of Radiology, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (E.K.); (E.A.P.)
| | - Evlampia A. Psatha
- Department of Radiology, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (E.K.); (E.A.P.)
| | - Anna Tsiakiri
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
| | - Aspasia Serdari
- Department of Child and Adolescent Psychiatry, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| | - Nikolaos Aggelousis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece;
| | - Konstantinos Vadikolias
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (F.C.); (I.O.); (E.M.); (C.K.); (A.T.); (K.V.)
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Nugiel T, Demeter DV, Mitchell ME, Garza A, Hernandez AE, Juranek J, Church JA. Brain connectivity and academic skills in English learners. Cereb Cortex 2024; 34:bhad414. [PMID: 38044467 PMCID: PMC10793574 DOI: 10.1093/cercor/bhad414] [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: 06/22/2023] [Revised: 10/11/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023] Open
Abstract
English learners (ELs) are a rapidly growing population in schools in the United States with limited experience and proficiency in English. To better understand the path for EL's academic success in school, it is important to understand how EL's brain systems are used for academic learning in English. We studied, in a cohort of Hispanic middle-schoolers (n = 45, 22F) with limited English proficiency and a wide range of reading and math abilities, brain network properties related to academic abilities. We applied a method for localizing brain regions of interest (ROIs) that are group-constrained, yet individually specific, to test how resting state functional connectivity between regions that are important for academic learning (reading, math, and cognitive control regions) are related to academic abilities. ROIs were selected from task localizers probing reading and math skills in the same participants. We found that connectivity across all ROIs, as well as connectivity of just the cognitive control ROIs, were positively related to measures of reading skills but not math skills. This work suggests that cognitive control brain systems have a central role for reading in ELs. Our results also indicate that an individualized approach for localizing brain function may clarify brain-behavior relationships.
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Affiliation(s)
- Tehila Nugiel
- Department of Psychology, Florida State University, Tallahassee, FL 32304, United States
| | - Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92037, United States
| | - Mackenzie E Mitchell
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - AnnaCarolina Garza
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, United States
| | - Arturo E Hernandez
- Department of Psychology, University of Houston, Houston, TX 77204, United States
| | - Jenifer Juranek
- Department of Pediatrics, University of Texas Health Science Center, Houston, TX 77225, United States
| | - Jessica A Church
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, United States
- Biomedical Imaging Center, The University of Texas at Austin, Austin, TX 78712, United States
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Lefebvre J, Hutt A. Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study. CHAOS (WOODBURY, N.Y.) 2023; 33:123110. [PMID: 38055720 DOI: 10.1063/5.0167771] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/09/2023] [Indexed: 12/08/2023]
Abstract
Event-related synchronization and desynchronization (ERS/ERD) are well-known features found experimentally in brain signals during cognitive tasks. Their understanding promises to have much better insights into neural information processes in cognition. Under the hypothesis that neural information affects the endogenous neural noise level in populations, we propose to employ a stochastic mean-field model to explain ERS/ERD in the γ-frequency range. The work extends previous mean-field studies by deriving novel effects from finite network size. Moreover, numerical simulations of ERS/ERD and their analytical explanation by the mean-field model suggest several endogenous noise modulation schemes, which may modulate the system's synchronization.
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Affiliation(s)
- J Lefebvre
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, Ontario M5S 2E4, Canada
| | - A Hutt
- ICube, MLMS, University of Strasbourg, MIMESIS Team, Inria Nancy-Grand Est, 67000 Strasbourg, France
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10
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Zelmann R, Paulk AC, Tian F, Balanza Villegas GA, Dezha Peralta J, Crocker B, Cosgrove GR, Richardson RM, Williams ZM, Dougherty DD, Purdon PL, Cash SS. Differential cortical network engagement during states of un/consciousness in humans. Neuron 2023; 111:3479-3495.e6. [PMID: 37659409 PMCID: PMC10843836 DOI: 10.1016/j.neuron.2023.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 06/13/2023] [Accepted: 08/08/2023] [Indexed: 09/04/2023]
Abstract
What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.
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Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Fangyun Tian
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
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Churchill NW, Roudaia E, Jean Chen J, Gilboa A, Sekuler A, Ji X, Gao F, Lin Z, Masellis M, Goubran M, Rabin JS, Lam B, Cheng I, Fowler R, Heyn C, Black SE, MacIntosh BJ, Graham SJ, Schweizer TA. Persistent post-COVID headache is associated with suppression of scale-free functional brain dynamics in non-hospitalized individuals. Brain Behav 2023; 13:e3212. [PMID: 37872889 PMCID: PMC10636408 DOI: 10.1002/brb3.3212] [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: 04/10/2023] [Revised: 07/14/2023] [Accepted: 07/20/2023] [Indexed: 10/25/2023] Open
Abstract
INTRODUCTION Post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) is a growing concern, with headache being a particularly debilitating symptom with high prevalence. The long-term effects of COVID-19 and post-COVID headache on brain function remain poorly understood, particularly among non-hospitalized individuals. This study focused on the power-law scaling behavior of functional brain dynamics, indexed by the Hurst exponent (H). This measure is suppressed during physiological and psychological distress and was thus hypothesized to be reduced in individuals with post-COVID syndrome, with greatest reductions among those with persistent headache. METHODS Resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging data were collected for 57 individuals who had COVID-19 (32 with no headache, 14 with ongoing headache, 11 recovered) and 17 controls who had cold and flu-like symptoms but tested negative for COVID-19. Individuals were assessed an average of 4-5 months after COVID testing, in a cross-sectional, observational study design. RESULTS No significant differences in H values were found between non-headache COVID-19 and control groups., while those with ongoing headache had significantly reduced H values, and those who had recovered from headache had elevated H values, relative to non-headache groups. Effects were greatest in temporal, sensorimotor, and insular brain regions. Reduced H in these regions was also associated with decreased BOLD activity and local functional connectivity. CONCLUSIONS These findings provide new insights into the neurophysiological mechanisms that underlie persistent post-COVID headache, with reduced BOLD scaling as a potential biomarker that is specific to this debilitating condition.
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Affiliation(s)
- Nathan W. Churchill
- Neuroscience Research Program, St. Michael's HospitalTorontoOntarioCanada
- Keenan Research Centre for Biomedical Science, St. Michael's HospitalTorontoOntarioCanada
- Physics DepartmentToronto Metropolitan UniversityTorontoOntarioCanada
| | - Eugenie Roudaia
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
| | - J. Jean Chen
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Institute of Biomedical EngineeringUniversity of TorontoTorontoOntarioCanada
| | - Asaf Gilboa
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Department of PsychologyUniversity of TorontoTorontoOntarioCanada
| | - Allison Sekuler
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Department of PsychologyUniversity of TorontoTorontoOntarioCanada
- Department of Psychology, Neuroscience & BehaviourMcMaster UniversityHamiltonOntarioCanada
| | - Xiang Ji
- LC Campbell Cognitive Neurology Research Group, Sunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Fuqiang Gao
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
| | - Zhongmin Lin
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada
| | - Mario Masellis
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences CentreUniversity of TorontoTorontoOntarioCanada
| | - Maged Goubran
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada
- Harquail Centre for NeuromodulationSunnybrook Research InstituteTorontoOntarioCanada
| | - Jennifer S. Rabin
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences CentreUniversity of TorontoTorontoOntarioCanada
- Harquail Centre for NeuromodulationSunnybrook Research InstituteTorontoOntarioCanada
- Rehabilitation Sciences InstituteUniversity of TorontoTorontoOntarioCanada
| | - Benjamin Lam
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences CentreUniversity of TorontoTorontoOntarioCanada
| | - Ivy Cheng
- Evaluative Clinical SciencesSunnybrook Research InstituteTorontoOntarioCanada
- Integrated Community ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Department of MedicineUniversity of TorontoTorontoOntarioCanada
| | - Robert Fowler
- Department of MedicineUniversity of TorontoTorontoOntarioCanada
- Emergency & Critical Care Research ProgramSunnybrook Research InstituteTorontoOntarioCanada
| | - Chris Heyn
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Department of Medical ImagingUniversity of TorontoTorontoOntarioCanada
| | - Sandra E. Black
- Rotman Research InstituteBaycrest Academy for Research and EducationTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences CentreUniversity of TorontoTorontoOntarioCanada
| | - Bradley J. MacIntosh
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada
- Computational Radiology & Artificial Intelligence Unit, Division of Radiology and Nuclear MedicineOslo University HospitalOsloNorway
| | - Simon J. Graham
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada
| | - Tom A. Schweizer
- Neuroscience Research Program, St. Michael's HospitalTorontoOntarioCanada
- Keenan Research Centre for Biomedical Science, St. Michael's HospitalTorontoOntarioCanada
- Faculty of Medicine (Neurosurgery)University of TorontoTorontoOntarioCanada
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12
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Lv C, Xiao Z, Sun Y, Zhang R, Feng T, Turel O, He Q. Gender-specific resting-state rDMPFC-centric functional connectivity underpinnings of intertemporal choice. Cereb Cortex 2023; 33:10066-10075. [PMID: 37526227 DOI: 10.1093/cercor/bhad265] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 06/24/2023] [Accepted: 06/25/2023] [Indexed: 08/02/2023] Open
Abstract
Although studies have observed gender differences in intertemporal choice, the neural bases of these differences require further research. The current study used resting state functional connectivity (rsFC) to explore the gender-specific neural basis of intertemporal choice in three independent samples (n1 = 86, n2 = 297, n3 = 172). Behaviorally, three samples (S1, S2, and S3) consistently demonstrated that men had larger delay discounting rate (log k) than women. Then, whole-brain functional connectivity analyses were performed for different genders in S2 and S3 using the right dorsomedial prefrontal cortex (rDMPFC) as a region of interest. By subtracting the common rsFC patterns of different genders, we identified gender-specific log k-related rsFC patterns with significant gender differences in S2. This was verified in an independent sample (S3). Specifically, in women, log k was found to be positively correlated with the rsFC between rDMPFC and anterior cingulate cortex/right orbitofrontal cortex. In contrast, in men, log k was negatively correlated with rsFC between rDMPFC and left orbitofrontal cortex/right precuneus. These gender differences were confirmed by slope tests. The findings highlight how gender may differ when engaging in intertemporal choice. They improve the understanding of gender differences in decision impulsivity and its underlying neural bases.
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Affiliation(s)
- Chenyu Lv
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Zhibing Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yachen Sun
- Mental Health Education in Primary and Secondary School Magazine, Kaiming Press, Beijing 100029, China
| | - Rong Zhang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Tingyong Feng
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Ofir Turel
- School of Computing and Information Systems, The University of Melbourne, Parkville, VIC, Australia
| | - Qinghua He
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, China
- Southwest University Branch, Collaborative Innovation Center of Assessment toward Basic Education Quality at Beijing Normal University, Chongqing, China
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13
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Brændholt M, Kluger DS, Varga S, Heck DH, Gross J, Allen MG. Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations. Neurosci Biobehav Rev 2023; 152:105262. [PMID: 37271298 DOI: 10.1016/j.neubiorev.2023.105262] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 05/03/2023] [Accepted: 05/24/2023] [Indexed: 06/06/2023]
Abstract
Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.
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Affiliation(s)
- Malthe Brændholt
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Daniel S Kluger
- Institute for Biomagnetism and Biosignal Analysis, University of Münster, Germany.
| | - Somogy Varga
- School of Culture and Society, Aarhus University, Denmark; The Centre for Philosophy of Epidemiology, Medicine and Public Health, University of Johannesburg, South Africa
| | - Detlef H Heck
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN
| | - Joachim Gross
- Institute for Biomagnetism and Biosignal Analysis, University of Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Germany
| | - Micah G Allen
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark; Cambridge Psychiatry, University of Cambridge, UK
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14
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Yao S, Zhu Q, Zhang Q, Cai Y, Liu S, Pang L, Jing Y, Yin X, Cheng H. Managing Cancer and Living Meaningfully (CALM) alleviates chemotherapy related cognitive impairment (CRCI) in breast cancer survivors: A pilot study based on resting-state fMRI. Cancer Med 2023; 12:16231-16242. [PMID: 37409628 PMCID: PMC10469649 DOI: 10.1002/cam4.6285] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 06/12/2023] [Accepted: 06/14/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Chemotherapy related cognitive impairment (CRCI) is a type of memory and cognitive impairment induced by chemotherapy and has become a growing clinical problem. Breast cancer survivors (BCs) refer to patients from the moment of breast cancer diagnosis to the end of their lives. Managing Cancer and Living Meaningfully (CALM) is a convenient and easy-to-apply psychological intervention that has been proven to improve quality of life and alleviate CRCI in BCs. However, the underlying neurobiological mechanisms remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) has become an effective method for understanding the neurobiological mechanisms of brain networks in CRCI. The fractional amplitude of low-frequency fluctuations (fALFF) and ALFF have often been used in analyzing the power and intensity of spontaneous regional resting state neural activity. METHODS The recruited BCs were randomly divided into the CALM group and the care as usual (CAU) group. All BCs were evaluated by the Functional Assessment of Cancer Therapy Cognitive Function (FACT-Cog) before and after CALM or CAU. The rs-fMRI imaging was acquired before and after CALM intervention in CALM group BCs. The BCs were defined as before CALM intervention (BCI) group and after CALM intervention (ACI) group. RESULTS There were 32 BCs in CALM group and 35 BCs in CAU group completed the overall study. There were significant differences between the BCI group and the ACI group in the FACT-Cog-PCI scores. Compared with the BCI group, the ACI group showed lower fALFF signal in the left medial frontal gyrus and right sub-gyral and higher fALFF in the left occipital_sup and middle occipital gyrus. There was a significant positive correlation between hippocampal ALFF value and FACT-Cog-PCI scores. CONCLUSIONS CALM intervention may have an effective function in alleviating CRCI of BCs. The altered local synchronization and regional brain activity may be correlated with the improved cognitive function of BCs who received the CALM intervention. The ALFF value of hippocampus seems to be an important factor in reflect cognitive function in BCs with CRCI and the neural network mechanism of CALM intervention deserves further exploration to promote its application.
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Affiliation(s)
- Senbang Yao
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Qinqin Zhu
- Department of RadiologyQuzhou People's HospitalQuzhouChina
| | - Qianqian Zhang
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Yinlian Cai
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Shaochun Liu
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Lulian Pang
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Yanyan Jing
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Xiangxiang Yin
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Cancer and Cognition LaboratoryAnhui Medical UniversityHefeiChina
| | - Huaidong Cheng
- Department of OncologyThe Second Affiliated Hospital of Anhui Medical UniversityHefeiChina
- Shenzhen Clinical Medical School of Southern Medical UniversityShenzhenChina
- Department of OncologyShenzhen Hospital of Southern Medical UniversityShenzhenChina
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15
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Zhang C, Wang Y, Jing X, Yan JH. Brain mechanisms of mental processing: from evoked and spontaneous brain activities to enactive brain activity. PSYCHORADIOLOGY 2023; 3:kkad010. [PMID: 38666106 PMCID: PMC10917368 DOI: 10.1093/psyrad/kkad010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/23/2023] [Accepted: 06/29/2023] [Indexed: 04/28/2024]
Abstract
Within the context of the computer metaphor, evoked brain activity acts as a primary carrier for the brain mechanisms of mental processing. However, many studies have found that evoked brain activity is not the major part of brain activity. Instead, spontaneous brain activity exhibits greater intensity and coevolves with evoked brain activity through continuous interaction. Spontaneous and evoked brain activities are similar but not identical. They are not separate parts, but always dynamically interact with each other. Therefore, the enactive cognition theory further states that the brain is characterized by unified and active patterns of activity. The brain adjusts its activity pattern by minimizing the error between expectation and stimulation, adapting to the ever-changing environment. Therefore, the dynamic regulation of brain activity in response to task situations is the core brain mechanism of mental processing. Beyond the evoked brain activity and spontaneous brain activity, the enactive brain activity provides a novel framework to completely describe brain activities during mental processing. It is necessary for upcoming researchers to introduce innovative indicators and paradigms for investigating enactive brain activity during mental processing.
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Affiliation(s)
- Chi Zhang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Xiujuan Jing
- Tianfu College of Southwestern University of Finance and Economics, Chengdu 610052, China
| | - Jin H Yan
- Sports Psychology Department, China Institute of Sport Science, Beijing 100061, China
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16
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Underlying differences in resting-state activity metrics related to sensitivity to punishment. Behav Brain Res 2023; 437:114152. [PMID: 36228781 DOI: 10.1016/j.bbr.2022.114152] [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: 08/18/2022] [Revised: 09/20/2022] [Accepted: 10/06/2022] [Indexed: 11/07/2022]
Abstract
Reinforcement sensitivity theory (RST) of personality establishes the punishment sensitivity trait as a source of variation in defensive avoidance/approach behaviors. These individual differences reflect dissimilar sensitivity and reactivity of the fight-flight-freeze and behavioral inhibition systems (FFFS/BIS). The sensitivity to punishment (SP) scale has been widely used in personality research aimed at studying the activity of these systems. Structural and functional neuroimaging studies have confirmed the core biological correlates of FFFS/BIS in humans. Nonetheless, some brain functional features derived from resting-state blood-oxygen level-dependent (BOLD) activity and its association with the punishment sensitivity dimension remain unclear. This relationship would shed light on stable neural activity patterns linked to anxiety-like behaviors and anxiety predisposition. In this study, we analyzed functional activity metrics "at rest" [e.g., regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF)] and their relationship with SP in key FFFS/BIS regions (e.g., amygdala, hippocampus, and periaqueductal gray) in a sample of 127 healthy adults. Our results revealed a significant negative correlation between the fALFF within all these regions and the scores on SP. Our findings suggest aberrant neural activity (lower fALFF) within the brain's defense system in participants with high trait anxiety, which in turn could reflect lower FFFS/BIS activation thresholds. These neurally-located differences could lead to pathological fear/anxiety behaviors arising from the FFFS and BIS.
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17
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Baharlouei H, Ali Salehinejad M, Talimkhani A, Nitsche MA. The Effect of Non-invasive Brain Stimulation on Gait in Healthy Young and Older Adults: A Systematic Review of the Literature. Neuroscience 2023; 516:125-140. [PMID: 36720301 DOI: 10.1016/j.neuroscience.2023.01.026] [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: 05/21/2022] [Revised: 12/26/2022] [Accepted: 01/21/2023] [Indexed: 01/31/2023]
Abstract
BACKGROUND AND OBJECTIVES Walking is an important function which requires coordinated activity of sensory-motor neural networks. Noninvasive brain stimulation (NIBS) is a safe neuromodulatory technique with motor function-improving effects. This study aimed to determine the effect of different types of NIBS interventions explored in randomized controlled trials on gait in healthy young and older adults. METHODS Based on the PRISMA approach, we conducted an electronic search in PubMed, Web of Science, Scopus, and PEDro for randomized clinical trials assessing the effect of NIBS on gait in healthy young and older adults and performed a narrative review. RESULTS Fourteen studies were included in this systematic review. According to the outcomes, transcranial direct current stimulation (tDCS) over the motor cortex and transcranial alternating current stimulation (tACS) over the cerebellum seem to be promising for improving gait characteristics such as speed, synchronization, and variability. Furthermore, tDCS over the dorsolateral prefrontal cortex (DLPFC) improved gait speed and reduced gait parameter variability under dual-task conditions. Only one repetitive transcranial magnetic stimulation was available, which showed no effects. No studies were available for transcranial random noise stimulation, and transcranial pulsed current stimulation. Moreover, the intervention parameters of the included studies were heterogeneous, and studies comparing directly specific intervention protocols were missing. CONCLUSION NIBS is a promising approach to improve gait in healthy young and older adults. Anodal tDCS over the motor areas and DLPFC, and tACS over the cerebellum have shown positive effects on gait.
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Affiliation(s)
- Hamzeh Baharlouei
- Musculoskeletal Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Mohammad Ali Salehinejad
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany.
| | - Ailin Talimkhani
- Department of Physical Therapy, School of Rehabilitation Sciences, Hamadan University of Medical Sciences, Hamadan, Iran.
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany.
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18
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Yu Q, Ouyang M, Detre J, Kang H, Hu D, Hong B, Fang F, Peng Y, Huang H. Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network. eLife 2023; 12:e78397. [PMID: 36693116 PMCID: PMC9873253 DOI: 10.7554/elife.78397] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 01/12/2023] [Indexed: 01/25/2023] Open
Abstract
Human infancy is characterized by most rapid regional cerebral blood flow (rCBF) increases across lifespan and emergence of a fundamental brain system default-mode network (DMN). However, how infant rCBF changes spatiotemporally across the brain and how the rCBF increase supports emergence of functional networks such as DMN remains unknown. Here, by acquiring cutting-edge multi-modal MRI including pseudo-continuous arterial-spin-labeled perfusion MRI and resting-state functional MRI of 48 infants cross-sectionally, we elucidated unprecedented 4D spatiotemporal infant rCBF framework and region-specific physiology-function coupling across infancy. We found that faster rCBF increases in the DMN than visual and sensorimotor networks. We also found strongly coupled increases of rCBF and network strength specifically in the DMN, suggesting faster local blood flow increase to meet extraneuronal metabolic demands in the DMN maturation. These results offer insights into the physiological mechanism of brain functional network emergence and have important implications in altered network maturation in brain disorders.
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Affiliation(s)
- Qinlin Yu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Minhui Ouyang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - John Detre
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Neurology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Huiying Kang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Di Hu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Bo Hong
- Department of Biomedical Engineering, Tsinghua UniversityBeijingChina
| | - Fang Fang
- School of Psychological and Cognitive Sciences, Peking UniversityBeijingChina
| | - Yun Peng
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Hao Huang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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19
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Tanglay O, Dadario NB, Chong EHN, Tang SJ, Young IM, Sughrue ME. Graph Theory Measures and Their Application to Neurosurgical Eloquence. Cancers (Basel) 2023; 15:556. [PMID: 36672504 PMCID: PMC9857081 DOI: 10.3390/cancers15020556] [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: 11/29/2022] [Revised: 01/04/2023] [Accepted: 01/14/2023] [Indexed: 01/18/2023] Open
Abstract
Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.
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Affiliation(s)
- Onur Tanglay
- UNSW School of Clinical Medicine, Faulty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St, New Brunswick, NJ 08901, USA
| | - Elizabeth H. N. Chong
- Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore
| | - Si Jie Tang
- School of Medicine, University of California Davis, Sacramento, CA 95817, USA
| | - Isabella M. Young
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Michael E. Sughrue
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
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20
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Becker R, Hervais-Adelman A. Individual theta-band cortical entrainment to speech in quiet predicts word-in-noise comprehension. Cereb Cortex Commun 2023; 4:tgad001. [PMID: 36726796 PMCID: PMC9883620 DOI: 10.1093/texcom/tgad001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 12/17/2022] [Accepted: 12/18/2022] [Indexed: 01/09/2023] Open
Abstract
Speech elicits brain activity time-locked to its amplitude envelope. The resulting speech-brain synchrony (SBS) is thought to be crucial to speech parsing and comprehension. It has been shown that higher speech-brain coherence is associated with increased speech intelligibility. However, studies depending on the experimental manipulation of speech stimuli do not allow conclusion about the causality of the observed tracking. Here, we investigate whether individual differences in the intrinsic propensity to track the speech envelope when listening to speech-in-quiet is predictive of individual differences in speech-recognition-in-noise, in an independent task. We evaluated the cerebral tracking of speech in source-localized magnetoencephalography, at timescales corresponding to the phrases, words, syllables and phonemes. We found that individual differences in syllabic tracking in right superior temporal gyrus and in left middle temporal gyrus (MTG) were positively associated with recognition accuracy in an independent words-in-noise task. Furthermore, directed connectivity analysis showed that this relationship is partially mediated by top-down connectivity from premotor cortex-associated with speech processing and active sensing in the auditory domain-to left MTG. Thus, the extent of SBS-even during clear speech-reflects an active mechanism of the speech processing system that may confer resilience to noise.
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Affiliation(s)
- Robert Becker
- Corresponding author: Neurolinguistics, Department of Psychology, University of Zurich (UZH), Zurich, Switzerland.
| | - Alexis Hervais-Adelman
- Neurolinguistics, Department of Psychology, University of Zurich, Zurich 8050, Switzerland,Neuroscience Center Zurich, University of Zurich and Eidgenössische Technische Hochschule Zurich, Zurich 8057, Switzerland
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21
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Togo H, Nakamura T, Wakasugi N, Takahashi Y, Hanakawa T. Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait. Neuroimage Clin 2023; 37:103342. [PMID: 36739790 PMCID: PMC9932566 DOI: 10.1016/j.nicl.2023.103342] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 01/23/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Freezing of gait (FOG) is a gait disorder affecting patients with Parkinson's disease (PD) and related disorders. The pathophysiology of FOG is unclear because of its phenomenological complexity involving motor, cognitive, and emotional aspects of behavior. Here we used resting-state functional MRI to retrieve functional connectivity (FC) correlated with the New FOG questionnaire (NFOGQ) reflecting severity of FOG in 67 patients with PD. NFOGQ scores were correlated with FCs in the extended basal ganglia network (BGN) involving the striatum and amygdala, and in the extra-cerebellum network (CBLN) involving the frontoparietal network (FPN). These FCs represented interactions across the emotional (amygdala), subcortical motor (BGN and CBLN), and cognitive networks (FPN). Using these FCs as features, we constructed statistical models that explained 40% of the inter-individual variances of FOG severity and that discriminated between PD patients with and without FOG. The amygdala, which connects to the subcortical motor (BGN and CBLN) and cognitive (FPN) networks, may have a pivotal role in interactions across the emotional, cognitive, and subcortical motor networks. Future refinement of the machine learning-based classifier using FCs may clarify the complex pathophysiology of FOG further and help diagnose and evaluate FOG in clinical settings.
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Affiliation(s)
- Hiroki Togo
- Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Yoshida-Konoe, Sakyo-ku, Kyoto 606-8501, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan
| | - Tatsuhiro Nakamura
- Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Yoshida-Konoe, Sakyo-ku, Kyoto 606-8501, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan
| | - Noritaka Wakasugi
- Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan
| | - Yuji Takahashi
- Department of Neurology, National Center Hospital, National Center of Neurology and Psychiatry (NCNP), Tokyo, 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan
| | - Takashi Hanakawa
- Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Yoshida-Konoe, Sakyo-ku, Kyoto 606-8501, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan.
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22
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Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity. Neuroimage 2022; 262:119555. [PMID: 35963506 PMCID: PMC10044499 DOI: 10.1016/j.neuroimage.2022.119555] [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: 06/09/2022] [Revised: 08/01/2022] [Accepted: 08/09/2022] [Indexed: 11/22/2022] Open
Abstract
Regional homogeneity (ReHo) is a measure of local functional brain connectivity that has been reported to be altered in a wide range of neuropsychiatric disorders. Computed from brain resting-state functional MRI time series, ReHo is also sensitive to fluctuations in cerebral blood flow (CBF) that in turn may be influenced by cerebrovascular health. We accessed cerebrovascular health with Framingham cardiovascular risk score (FCVRS). We hypothesize that ReHo signal may be influenced by regional CBF; and that these associations can be summarized as FCVRS→CBF→ReHo. We used three independent samples to test this hypothesis. A test-retest sample of N = 30 healthy volunteers was used for test-retest evaluation of CBF effects on ReHo. Amish Connectome Project (ACP) sample (N = 204, healthy individuals) was used to evaluate association between FCVRS and ReHo and testing if the association diminishes given CBF. The UKBB sample (N = 6,285, healthy participants) was used to replicate the effects of FCVRS on ReHo. We observed strong CBF→ReHo links (p<2.5 × 10-3) using a three-point longitudinal sample. In ACP sample, marginal and partial correlations analyses demonstrated that both CBF and FCVRS were significantly correlated with the whole-brain average (p<10-6) and regional ReHo values, with the strongest correlations observed in frontal, parietal, and temporal areas. Yet, the association between ReHo and FCVRS became insignificant once the effect of CBF was accounted for. In contrast, CBF→ReHo remained significantly linked after adjusting for FCVRS and demographic covariates (p<10-6). Analysis in N = 6,285 replicated the FCVRS→ReHo effect (p = 2.7 × 10-27). In summary, ReHo alterations in health and neuropsychiatric illnesses may be partially driven by region-specific variability in CBF, which is, in turn, influenced by cardiovascular factors.
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23
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Altered gamma oscillations and beta-gamma coupling in drug-naive first-episode major depressive disorder: Association with sleep and cognitive disturbance. J Affect Disord 2022; 316:99-108. [PMID: 35973509 DOI: 10.1016/j.jad.2022.08.022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 06/25/2022] [Accepted: 08/10/2022] [Indexed: 01/24/2023]
Abstract
OBJECTIVE Gamma oscillations contribute to the pathogenesis mechanisms of major depressive disorder (MDD) have been proposed, but gamma activity is not well characterized. This study is the first attempt to investigate the altered gamma oscillations in first-episode MDD, particularly the beta-gamma coupling, and to determine the potential symptomatic relationship with the identified gamma dysregulation. METHODS Resting electroencephalography was recorded for 43 drug-naive first-episode MDD and 57 healthy control (HC) subjects. Integrated analysis of relative spectral power, weighted phase lag index, and phase-amplitude coupling (PAC) were utilized to reveal the alterations of gamma activities. Pearson's correlation was implemented to identify the relationship between altered gamma activities and the clinical depressive symptoms, which were categorized into four factors: anxiety somatization, retardation, cognitive disturbance, and sleep disturbance. RESULTS Compared with HC subjects, MDD patients showed not only significantly decreased gamma powers in the left temporal and the bilateral occipital regions but also weakened gamma connectivity between the left hemisphere and the right frontal region. Furthermore, attenuated beta-gamma PAC of MDD patients was observed in the left temporal regions. Importantly, the suppression of left occipital mid- and high gamma oscillations were negatively correlated with sleep disturbance, while the deficits in left temporal beta-mid-gamma PAC and beta-high gamma PAC showed negative correlations with cognitive disturbance. LIMITATIONS Important limitations are the small sample size and the possible inclusion of bipolar depression in the MDD group. CONCLUSIONS Our findings provide the first evidence that in first-episode MDD, aberrant gamma powers and beta-gamma coupling are associated with sleep and cognitive impairments, respectively, deepening our understanding of the physiological mechanisms underlying sleep and cognitive symptoms in first-episode MDD. Altered gamma oscillations emerge as promising biomarkers for diagnosing MDD.
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24
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Damiani S, Tarchi L, La-Torraca-Vittori P, Scalabrini A, Castellini G, Ricca V, Fusar-Poli P, Politi P. State-dependent reductions of local brain connectivity in schizophrenia and their relation to performance and symptoms: A functional magnetic resonance imaging study. Psychiatry Res Neuroimaging 2022; 326:111541. [PMID: 36122541 DOI: 10.1016/j.pscychresns.2022.111541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 08/01/2022] [Accepted: 09/04/2022] [Indexed: 11/17/2022]
Abstract
State-dependent reallocation of cognitive resources is impaired in schizophrenia and may be underlined by alterations in brain local-connectivity. Increasing evidence suggests local connectivity reductions from rest to task in healthy individuals, while insufficient information is available for schizophrenia spectrum. Resting-state and stop-signal task fMRI scans of 107 healthy controls and 32 patients with DSM-IV-TR schizophrenia or schizoaffective disorder were analyzed. As primary aim we measured within-group shifts in local-connectivity from rest to task as voxel-wise Regional Homogeneity (ReHo-shift). Secondary aims were to test: i) Between-groups differences in ReHo-rest, ReHo-task and ReHo-shift; ii) ReHo covariations with task performance (=shorter reaction times) and severity of symptoms (SAPS/SANS scores). Age, sex, and education were accounted for as covariates. Motion, global-signal-regression, antipsychotic dosage and smoothing associations with ReHo were evaluated. Rest-to-task ReHo reductions occurred in both groups on a whole-brain level (False-Discovery-Rate p=0.05). Trends of greater ReHo reductions in patients versus controls were observed. Controls performed better than patients (p<0.001). ReHo negatively correlated with performance in both groups. ReHo-shift predicted worse performance in controls, but better performance in patients (uncorrected p=0.05). ReHo reductions correlated with severity of symptoms. State-dependent reconfigurations in local-connectivity provide new links between neurobiology and behavioral/clinical features of the schizophrenia spectrum.
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Affiliation(s)
- Stefano Damiani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy.
| | - Livio Tarchi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy; Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | | | - Andrea Scalabrini
- Department of Human and Social Sciences, University of Bergamo, Bergamo, BG, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy; Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; National Institute for Health Research, Maudsley Biomedical Research Centre, London, UK
| | - Pierluigi Politi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
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25
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Chan RW, Cron GO, Asaad M, Edelman BJ, Lee HJ, Adesnik H, Feinberg D, Lee JH. Distinct local and brain-wide networks are activated by optogenetic stimulation of neurons specific to each layer of motor cortex. Neuroimage 2022; 263:119640. [PMID: 36176220 PMCID: PMC10025169 DOI: 10.1016/j.neuroimage.2022.119640] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 11/20/2022] Open
Abstract
Primary motor cortex (M1) consists of a stack of interconnected but distinct layers (L1-L6) which affect motor control through large-scale networks. However, the brain-wide functional influence of each layer is poorly understood. We sought to expand our knowledge of these layers' circuitry by combining Cre-driver mouse lines, optogenetics, fMRI, and electrophysiology. Neuronal activities initiated in Drd3 neurons (within L2/3) were mainly confined within M1, while stimulation of Scnn1a, Rbp4, and Ntsr1 neurons (within L4, L5, and L6, respectively) evoked distinct responses in M1 and motor-related subcortical regions, including striatum and motor thalamus. We also found that fMRI responses from targeted stimulations correlated with both local field potentials (LFPs) and spike changes. This study represents a step forward in our understanding of how different layers of primary motor cortex are embedded in brain-wide circuitry.
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Affiliation(s)
- Russell W Chan
- Department of Neurology and Neurological Sciences, Stanford University, CA 94305, USA
| | - Greg O Cron
- Department of Neurology and Neurological Sciences, Stanford University, CA 94305, USA
| | - Mazen Asaad
- Department of Molecular and Cellular Physiology, Stanford University, CA 94305, USA
| | - Bradley J Edelman
- Department of Neurology and Neurological Sciences, Stanford University, CA 94305, USA
| | - Hyun Joo Lee
- Department of Neurology and Neurological Sciences, Stanford University, CA 94305, USA
| | - Hillel Adesnik
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
| | - David Feinberg
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
| | - Jin Hyung Lee
- Department of Neurology and Neurological Sciences, Stanford University, CA 94305, USA; Department of Bioengineering, Stanford University, CA 94305, USA; Department of Neurosurgery, Stanford University, CA 94305, USA; Department of Electrical Engineering, Stanford University, CA 94305, USA.
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26
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Allen M, Levy A, Parr T, Friston KJ. In the Body’s Eye: The computational anatomy of interoceptive inference. PLoS Comput Biol 2022; 18:e1010490. [PMID: 36099315 PMCID: PMC9506608 DOI: 10.1371/journal.pcbi.1010490] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 09/23/2022] [Accepted: 08/13/2022] [Indexed: 11/24/2022] Open
Abstract
A growing body of evidence highlights the intricate linkage of exteroceptive perception to the rhythmic activity of the visceral body. In parallel, interoceptive inference theories of affective perception and self-consciousness are on the rise in cognitive science. However, thus far no formal theory has emerged to integrate these twin domains; instead, most extant work is conceptual in nature. Here, we introduce a formal model of cardiac active inference, which explains how ascending cardiac signals entrain exteroceptive sensory perception and uncertainty. Through simulated psychophysics, we reproduce the defensive startle reflex and commonly reported effects linking the cardiac cycle to affective behaviour. We further show that simulated ‘interoceptive lesions’ blunt affective expectations, induce psychosomatic hallucinations, and exacerbate biases in perceptual uncertainty. Through synthetic heart-rate variability analyses, we illustrate how the balance of arousal-priors and visceral prediction errors produces idiosyncratic patterns of physiological reactivity. Our model thus offers a roadmap for computationally phenotyping disordered brain-body interaction. Understanding interactions between the brain and the body has become a topic of increased interest in computational neuroscience and psychiatry. A particular question here concerns how visceral, homeostatic rhythms such as the heart beat influence sensory, affective, and cognitive processing. To better understand these and other oscillatory brain-body interactions, we here introduce a novel computational model of interoceptive inference in which a synthetic agent’s perceptual beliefs are coupled to the rhythm of the heart. Our model both helps to explain emerging empirical data indicating that perceptual inference depends upon beat-to-beat heart rhythms, and can be used to better quantify intra- and inter-individual differences in heart-brain coupling. Using proof-of-principle simulations, we demonstrate how future empirical works could utilize our model to better understand and stratify disorders of interoception and brain-body interaction.
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Affiliation(s)
- Micah Allen
- Centre of Functionally Integrative Neuroscience, Aarhus University Hospital, Denmark
- Cambridge Psychiatry, Cambridge University, Cambridge, United Kingdom
- * E-mail:
| | - Andrew Levy
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Karl J. Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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27
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Huang Z, Gao W, Wu Z, Li G, Nie J. Functional brain activity is highly associated with cortical myelination in neonates. Cereb Cortex 2022; 33:3985-3995. [PMID: 36030387 DOI: 10.1093/cercor/bhac321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/12/2022] Open
Abstract
Functional organization of the human cerebral cortex is highly constrained by underlying brain structures, but how functional activity is associated with different brain structures during development is not clear, especially at the neonatal stage. Since long-range functional connectivity is far from mature in the dynamically developing neonatal brain, it is of great scientific significance to investigate the relationship between different structural and functional features at the local level. To this end, for the first time, correlation and regression analyses were performed to examine the relationship between cortical morphology, cortical myelination, age, and local brain functional activity, as well as functional connectivity strength using high-resolution structural and resting-state functional MRI data of 177 neonates (29-44 postmenopausal weeks, 98 male and 79 female) from both static and dynamic perspectives. We found that cortical myelination was most strongly associated with local brain functional activity across the cerebral cortex than other cortical structural features while controlling the age effect. These findings suggest the crucial role of cortical myelination in local brain functional development at birth, providing valuable insights into the fundamental biological basis of functional activity at this early developmental stage.
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Affiliation(s)
- Ziyi Huang
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Wenjian Gao
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University,Guangzhou 510631, China
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jingxin Nie
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
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28
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Yamashita M, Shimokawa T, Tanemura R. Default mode network-associated intrinsic connectivity relates to individual learnability differences in errorless and trial-and-error learning. APPLIED NEUROPSYCHOLOGY. ADULT 2022:1-9. [PMID: 35998649 DOI: 10.1080/23279095.2022.2111518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The intrinsic functional network architecture accounts for task-evoked brain activity changes and variabilities in cognitive performance. Relationships between the intrinsic functional network architecture and task performance or learning ability have been previously reported. However, the relationships between learning benefits and the characteristics of intrinsic functional network architecture for different types of learning methods remain unclear. In this study, we used graph theoretical analysis to examine the relationships between intrinsic functional network connectivity and learning benefits in two well-known learning methods in the field of cognitive rehabilitation-errorless learning (EL learning) and trial-and-error learning (T&E learning). We focused on the default mode network (DMN) as a task-relevant network, which can differentiate between EL and T&E learning and was found to be more important for T&E learning in a previous study. Participants performed a color-name association task with both learning methods. The graph metrics used were within-network connectivity and efficiency for the DMN. Within-DMN connectivity and DMN efficiency showed a significantly weak positive correlation with T&E scores but not with EL scores. These findings show that the intrinsic integration strength within the DMN relates to individuals' learnability through the T&E method.
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Affiliation(s)
- Madoka Yamashita
- Department of Rehabilitation, Kansai Medical University, Osaka, Japan
- Department of Rehabilitation Science, Graduate School of Health Sciences Discipline, Life and Medical Sciences Area, Kobe University, Kobe, Hyogo, Japan
| | - Tetsuya Shimokawa
- Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
| | - Rumi Tanemura
- Department of Rehabilitation Science, Graduate School of Health Sciences Discipline, Life and Medical Sciences Area, Kobe University, Kobe, Hyogo, Japan
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29
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Ciardo F, De Tommaso D, Wykowska A. Human-like behavioral variability blurs the distinction between a human and a machine in a nonverbal Turing test. Sci Robot 2022; 7:eabo1241. [PMID: 35895925 DOI: 10.1126/scirobotics.abo1241] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Variability is a property of biological systems, and in animals (including humans), behavioral variability is characterized by certain features, such as the range of variability and the shape of its distribution. Nevertheless, only a few studies have investigated whether and how variability features contribute to the ascription of humanness to robots in a human-robot interaction setting. Here, we tested whether two aspects of behavioral variability, namely, the standard deviation and the shape of distribution of reaction times, affect the ascription of humanness to robots during a joint action scenario. We designed an interactive task in which pairs of participants performed a joint Simon task with an iCub robot placed by their side. Either iCub could perform the task in a preprogrammed manner, or its button presses could be teleoperated by the other member of the pair, seated in the other room. Under the preprogrammed condition, the iCub pressed buttons with reaction times falling within the range of human variability. However, the distribution of the reaction times did not resemble a human-like shape. Participants were sensitive to humanness, because they correctly detected the human agent above chance level. When the iCub was controlled by the computer program, it passed our variation of a nonverbal Turing test. Together, our results suggest that hints of humanness, such as the range of behavioral variability, might be used by observers to ascribe humanness to a humanoid robot.
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Affiliation(s)
- F Ciardo
- Social Cognition in Human-Robot Interaction, Italian Institute of Technology, Genoa, Italy
| | - D De Tommaso
- Social Cognition in Human-Robot Interaction, Italian Institute of Technology, Genoa, Italy
| | - A Wykowska
- Social Cognition in Human-Robot Interaction, Italian Institute of Technology, Genoa, Italy
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30
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Tagawa M, Takei Y, Kato Y, Suto T, Hironaga N, Ohki T, Takahashi Y, Fujihara K, Sakurai N, Ujita K, Tsushima Y, Fukuda M. Disrupted local beta band networks in schizophrenia revealed through graph analysis: A magnetoencephalography study. Psychiatry Clin Neurosci 2022; 76:309-320. [PMID: 35397141 DOI: 10.1111/pcn.13362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 03/14/2022] [Accepted: 03/25/2022] [Indexed: 11/30/2022]
Abstract
AIMS Schizophrenia (SZ) is characterized by psychotic symptoms and cognitive impairment, and is hypothesized to be a 'dysconnection' syndrome due to abnormal neural network formation. Although numerous studies have helped elucidate the pathophysiology of SZ, many aspects of the mechanism underlying psychotic symptoms remain unknown. This study used graph theory analysis to evaluate the characteristics of the resting-state network (RSN) in terms of microscale and macroscale indices, and to identify candidates as potential biomarkers of SZ. Specifically, we discriminated topological characteristics in the frequency domain and investigated them in the context of psychotic symptoms in patients with SZ. METHODS We performed graph theory analysis of electrophysiological RSN data using magnetoencephalography to compare topological characteristics represented by microscale (degree centrality and clustering coefficient) and macroscale (global efficiency, local efficiency, and small-worldness) indices in 29 patients with SZ and 38 healthy controls. In addition, we investigated the aberrant topological characteristics of the RSN in patients with SZ and their relationship with SZ symptoms. RESULTS SZ was associated with a decreased clustering coefficient, local efficiency, and small-worldness, especially in the high beta band. In addition, macroscale changes in the low beta band are closely associated with negative symptoms. CONCLUSIONS The local networks of patients with SZ may disintegrate at both the microscale and macroscale levels, mainly in the beta band. Adopting an electrophysiological perspective of SZ as a failure to form local networks in the beta band will provide deeper insights into the pathophysiology of SZ as a 'dysconnection' syndrome.
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Affiliation(s)
- Minami Tagawa
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan.,Gunma Prefectural Psychiatric Medical Center, Gunma, Japan
| | - Yuichi Takei
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Yutaka Kato
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan.,Tsutsuji Mental Hospital, Gunma, Japan
| | - Tomohiro Suto
- Gunma Prefectural Psychiatric Medical Center, Gunma, Japan
| | - Naruhito Hironaga
- Brain Center, Faculty of Medicine, Kyushu University, Fukuoka, Japan
| | - Takefumi Ohki
- International Research Center for Neurointelligence (IRCN), The University of Tokyo, Tokyo, Japan
| | - Yumiko Takahashi
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Kazuyuki Fujihara
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan.,Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Noriko Sakurai
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Koichi Ujita
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Yoshito Tsushima
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Masato Fukuda
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan
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31
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Nagy B, Protzner AB, van der Wijk G, Wang H, Cortese F, Czigler I, Gaál ZA. The modulatory effect of adaptive task-switching training on resting-state neural network dynamics in younger and older adults. Sci Rep 2022; 12:9541. [PMID: 35680953 PMCID: PMC9184743 DOI: 10.1038/s41598-022-13708-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/26/2022] [Indexed: 11/08/2022] Open
Abstract
With increasing life expectancy and active aging, it becomes crucial to investigate methods which could compensate for generally detected cognitive aging processes. A promising candidate is adaptive cognitive training, during which task difficulty is adjusted to the participants' performance level to enhance the training and potential transfer effects. Measuring intrinsic brain activity is suitable for detecting possible distributed training-effects since resting-state dynamics are linked to the brain's functional flexibility and the effectiveness of different cognitive processes. Therefore, we investigated if adaptive task-switching training could modulate resting-state neural dynamics in younger (18-25 years) and older (60-75 years) adults (79 people altogether). We examined spectral power density on resting-state EEG data for measuring oscillatory activity, and multiscale entropy for detecting intrinsic neural complexity. Decreased coarse timescale entropy and lower frequency band power as well as increased fine timescale entropy and higher frequency band power revealed a shift from more global to local information processing with aging before training. However, cognitive training modulated these age-group differences, as coarse timescale entropy and lower frequency band power increased from pre- to post-training in the old-training group. Overall, our results suggest that cognitive training can modulate neural dynamics even when measured outside of the trained task.
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Affiliation(s)
- Boglárka Nagy
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, P.O. Box 286, Budapest, 1519, Hungary.
- Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary.
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Mathison Centre, University of Calgary, Calgary, AB, Canada
| | - Gwen van der Wijk
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Hongye Wang
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Filomeno Cortese
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Seaman Family MR Centre, Foothills Medical Centre, University of Calgary, Calgary, AB, Canada
| | - István Czigler
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, P.O. Box 286, Budapest, 1519, Hungary
- Institute of Psychology, Eötvös Loránd University, Budapest, Hungary
| | - Zsófia Anna Gaál
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, P.O. Box 286, Budapest, 1519, Hungary
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Mancuso L, Cavuoti-Cabanillas S, Liloia D, Manuello J, Buzi G, Cauda F, Costa T. Tasks activating the default mode network map multiple functional systems. Brain Struct Funct 2022; 227:1711-1734. [PMID: 35179638 PMCID: PMC9098625 DOI: 10.1007/s00429-022-02467-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/31/2022] [Indexed: 12/30/2022]
Abstract
Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.
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Affiliation(s)
- Lorenzo Mancuso
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | | | - Donato Liloia
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Jordi Manuello
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Giulia Buzi
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | - Franco Cauda
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy.
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
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33
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Pfurtscheller G, Blinowska KJ, Kaminski M, Rassler B, Klimesch W. Processing of fMRI-related anxiety and information flow between brain and body revealed a preponderance of oscillations at 0.15/0.16 Hz. Sci Rep 2022; 12:9117. [PMID: 35650314 PMCID: PMC9160010 DOI: 10.1038/s41598-022-13229-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/23/2022] [Indexed: 11/09/2022] Open
Abstract
Slow oscillations of different center frequencies and their coupling play an important role in brain-body interactions. The crucial question analyzed by us is, whether the low frequency (LF) band (0.05-0.15 Hz) or the intermediate frequency (IMF) band (0.1-0.2 Hz) is more eminent in respect of the information flow between body (heart rate and respiration) and BOLD signals in cortex and brainstem. A recently published study with the LF band in fMRI-naïve subjects revealed an intensive information flow from the cortex to the brainstem and a weaker flow from the brainstem to the cortex. The comparison of both bands revealed a significant information flow from the middle frontal gyrus (MFG) to the precentral gyrus (PCG) and from brainstem to PCG only in the IMF band. This pattern of directed coupling between slow oscillations in the cortex and brainstem not only supports the existence of a pacemaker-like structure in brainstem, but provides first evidence that oscillations centered at 0.15/0.16 Hz can also emerge in brain networks. BOLD oscillations in resting states are dominating at ~ 0.08 Hz and respiratory rates at ~ 0.32 Hz. Therefore, the frequency component at ~ 0.16 Hz (doubling-halving 0.08 Hz or 0.32 Hz) is of special interest, because phase coupled oscillations can reduce the energy demand.
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Affiliation(s)
- Gert Pfurtscheller
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria.
| | - Katarzyna J Blinowska
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4 St., 02-109, Warsaw, Poland.,Faculty of Physics, University of Warsaw, Ul. Pasteura 5, 02-093, Warsaw, Poland
| | - Maciej Kaminski
- Faculty of Physics, University of Warsaw, Ul. Pasteura 5, 02-093, Warsaw, Poland
| | - Beate Rassler
- Carl-Ludwig-Institute of Physiology, University of Leipzig, Leipzig, Germany
| | - Wolfgang Klimesch
- Centre of Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
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34
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Ribeiro M, Castelo-Branco M. Slow fluctuations in ongoing brain activity decrease in amplitude with ageing yet their impact on task-related evoked responses is dissociable from behavior. eLife 2022; 11:e75722. [PMID: 35608164 PMCID: PMC9129875 DOI: 10.7554/elife.75722] [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: 11/20/2021] [Accepted: 05/12/2022] [Indexed: 11/21/2022] Open
Abstract
In humans, ageing is characterized by decreased brain signal variability and increased behavioral variability. To understand how reduced brain variability segregates with increased behavioral variability, we investigated the association between reaction time variability, evoked brain responses and ongoing brain signal dynamics, in young (N=36) and older adults (N=39). We studied the electroencephalogram (EEG) and pupil size fluctuations to characterize the cortical and arousal responses elicited by a cued go/no-go task. Evoked responses were strongly modulated by slow (<2 Hz) fluctuations of the ongoing signals, which presented reduced power in the older participants. Although variability of the evoked responses was lower in the older participants, once we adjusted for the effect of the ongoing signal fluctuations, evoked responses were equally variable in both groups. Moreover, the modulation of the evoked responses caused by the ongoing signal fluctuations had no impact on reaction time, thereby explaining why although ongoing brain signal variability is decreased in older individuals, behavioral variability is not. Finally, we showed that adjusting for the effect of the ongoing signal was critical to unmask the link between neural responses and behavior as well as the link between task-related evoked EEG and pupil responses.
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Affiliation(s)
- Maria Ribeiro
- CIBIT-ICNAS, University of CoimbraCoimbraPortugal
- Faculty of Medicine, University of CoimbraCoimbraPortugal
| | - Miguel Castelo-Branco
- CIBIT-ICNAS, University of CoimbraCoimbraPortugal
- Faculty of Medicine, University of CoimbraCoimbraPortugal
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35
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Nunez-Elizalde AO, Krumin M, Reddy CB, Montaldo G, Urban A, Harris KD, Carandini M. Neural correlates of blood flow measured by ultrasound. Neuron 2022; 110:1631-1640.e4. [PMID: 35278361 PMCID: PMC9235295 DOI: 10.1016/j.neuron.2022.02.012] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 01/06/2022] [Accepted: 02/15/2022] [Indexed: 12/17/2022]
Abstract
Functional ultrasound imaging (fUSI) is an appealing method for measuring blood flow and thus infer brain activity, but it relies on the physiology of neurovascular coupling and requires extensive signal processing. To establish to what degree fUSI trial-by-trial signals reflect neural activity, we performed simultaneous fUSI and neural recordings with Neuropixels probes in awake mice. fUSI signals strongly correlated with the slow (<0.3 Hz) fluctuations in the local firing rate and were closely predicted by the smoothed firing rate of local neurons, particularly putative inhibitory neurons. The optimal smoothing filter had a width of ∼3 s, matched the hemodynamic response function of awake mice, was invariant across mice and stimulus conditions, and was similar in the cortex and hippocampus. fUSI signals also matched neural firing spatially: firing rates were as highly correlated across hemispheres as fUSI signals. Thus, blood flow measured by ultrasound bears a simple and accurate relationship to neuronal firing.
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Affiliation(s)
| | - Michael Krumin
- UCL Institute of Ophthalmology, University College London, London WC1E 6AE, UK
| | - Charu Bai Reddy
- UCL Institute of Ophthalmology, University College London, London WC1E 6AE, UK
| | - Gabriel Montaldo
- Neuro-Electronics Research Flanders, 3001 Leuven, Belgium; Vlaams Instituut voor Biotechnologie (VIB), 3000 Leuven, Belgium; imec, 3001 Leuven, Belgium; Department of Neuroscience, KU Leuven, 3000 Leuven, Belgium
| | - Alan Urban
- Neuro-Electronics Research Flanders, 3001 Leuven, Belgium; Vlaams Instituut voor Biotechnologie (VIB), 3000 Leuven, Belgium; imec, 3001 Leuven, Belgium; Department of Neuroscience, KU Leuven, 3000 Leuven, Belgium
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London WC1E 6AE, UK
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London WC1E 6AE, UK.
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36
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Al Zoubi O, Misaki M, Tsuchiyagaito A, Zotev V, White E, Paulus M, Bodurka J. Machine Learning Evidence for Sex Differences Consistently Influences Resting-State Functional Magnetic Resonance Imaging Fluctuations Across Multiple Independently Acquired Data Sets. Brain Connect 2022; 12:348-361. [PMID: 34269609 PMCID: PMC9131354 DOI: 10.1089/brain.2020.0878] [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: 11/12/2022] Open
Abstract
Background/Introduction: Sex classification using functional connectivity from resting-state functional magnetic resonance imaging (rs-fMRI) has shown promising results. This suggested that sex difference might also be embedded in the blood-oxygen-level-dependent properties such as the amplitude of low-frequency fluctuation (ALFF) and the fraction of ALFF (fALFF). This study comprehensively investigates sex differences using a reliable and explainable machine learning (ML) pipeline. Five independent cohorts of rs-fMRI with over than 5500 samples were used to assess sex classification performance and map the spatial distribution of the important brain regions. Methods: Five rs-fMRI samples were used to extract ALFF and fALFF features from predefined brain parcellations and then were fed into an unbiased and explainable ML pipeline with a wide range of methods. The pipeline comprehensively assessed unbiased performance for within-sample and across-sample validation. In addition, the parcellation effect, classifier selection, scanning length, spatial distribution, reproducibility, and feature importance were analyzed and evaluated thoroughly in the study. Results: The results demonstrated high sex classification accuracies from healthy adults (area under the curve >0.89), while degrading for nonhealthy subjects. Sex classification showed moderate to good intraclass correlation coefficient based on parcellation. Linear classifiers outperform nonlinear classifiers. Sex differences could be detected even with a short rs-fMRI scan (e.g., 2 min). The spatial distribution of important features overlaps with previous results from studies. Discussion: Sex differences are consistent in rs-fMRI and should be considered seriously in any study design, analysis, or interpretation. Features that discriminate males and females were found to be distributed across several different brain regions, suggesting a complex mosaic for sex differences in rs-fMRI. Impact statement The presented study unraveled that sex differences are embedded in the blood-oxygen-level dependent (BOLD) and can be predicted using unbiased and explainable machine learning pipeline. The study revealed that psychiatric disorders and demographics might influence the BOLD signal and interact with the classification of sex. The spatial distribution of the important features presented here supports the notion that the brain is a mosaic of male and female features. The findings emphasize the importance of controlling for sex when conducting brain imaging analysis. In addition, the presented framework can be adapted to classify other variables from resting-state BOLD signals.
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Affiliation(s)
- Obada Al Zoubi
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
- Department of Psychiatry, Harvard Medical School/McLean Hospital, Boston, Massachusetts, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | | | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Evan White
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
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37
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Liu S, Liu X, Yan D, Chen S, Liu Y, Hao X, Ou W, Huang Z, Su F, He F, Ming D. Alterations in patients with first-episode depression in the eyes-open and eyes-closed conditions: A resting-state EEG study. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1019-1029. [PMID: 35412986 DOI: 10.1109/tnsre.2022.3166824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Altered resting-state EEG activity has been repeatedly reported in major depressive disorder (MDD), but no robust biomarkers have been identified until now. The poor consistency of EEG alterations may be due to inconsistent resting conditions; that is, the eyes-open (EO) and eyes-closed (EC) conditions. Here, we explored the effect of the EO and EC conditions on EEG biomarkers for discriminating MDD subjects and healthy control (HC) subjects. EEG data were recorded from 30 first-episode MDD and 26 HC subjects during an 8-min resting-state session. The features were extracted using spectral power, Lempel-Ziv complexity, and detrended fluctuation analysis. Significant features were further selected via the sequential backward feature selection algorithm. Support vector machine (SVM), logistic regression, and linear discriminate analysis were used to determine a better resting condition to provide more reliable estimates for identifying MDD. Compared with the HC group, we found that the MDD group exhibited widespread increased β and γ powers (p < 0.01) in both conditions. In the EO condition, the MDD group showed increased complexity and scaling exponents in the α band relative to HC subjects (p < 0.05). The best classification performance of the combined feature sets was found in the EO condition, with the leave-one-out classification accuracy of 89.29%, sensitivity of 90.00%, and specificity of 88.46% using SVM with the linear kernel classifier when the threshold was set to 0.7, followed by the β and γ spectral features with an average accuracy of 83.93%. Overall, EO and EC conditions indeed affected the between-group variance, and the EO condition is suggested as the more separable resting condition to identify depression. Specially, the β and γ powers are suggested as potential biomarkers for first-episode MDD.
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38
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Kawagoe T. Overview of (f)MRI Studies of Cognitive Aging for Non-Experts: Looking through the Lens of Neuroimaging. Life (Basel) 2022; 12:416. [PMID: 35330167 PMCID: PMC8953678 DOI: 10.3390/life12030416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 03/11/2022] [Indexed: 11/20/2022] Open
Abstract
This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial attention, one of the well-studied functions in aging, is discussed from the perspective of neuroimaging.
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Affiliation(s)
- Toshikazu Kawagoe
- Liberal Arts Education Centre, Kyushu Campus, Tokai University, Toroku 9-1-1, Kumamoto-City 862-8652, Kumamoto, Japan
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39
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Xu N, LaGrow TJ, Anumba N, Lee A, Zhang X, Yousefi B, Bassil Y, Clavijo GP, Khalilzad Sharghi V, Maltbie E, Meyer-Baese L, Nezafati M, Pan WJ, Keilholz S. Functional Connectivity of the Brain Across Rodents and Humans. Front Neurosci 2022; 16:816331. [PMID: 35350561 PMCID: PMC8957796 DOI: 10.3389/fnins.2022.816331] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/14/2022] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.
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Affiliation(s)
- Nan Xu
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Theodore J. LaGrow
- Electrical and Computer Engineering, Georgia Tech, Atlanta, GA, United States
| | - Nmachi Anumba
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Azalea Lee
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
- Emory University School of Medicine, Atlanta, GA, United States
| | - Xiaodi Zhang
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Behnaz Yousefi
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Yasmine Bassil
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
| | - Gloria P. Clavijo
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | | | - Eric Maltbie
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Lisa Meyer-Baese
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Wen-Ju Pan
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Shella Keilholz
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
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40
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Aquino KM, Fulcher B, Oldham S, Parkes L, Gollo L, Deco G, Fornito A. On the intersection between data quality and dynamical modelling of large-scale fMRI signals. Neuroimage 2022; 256:119051. [PMID: 35276367 DOI: 10.1016/j.neuroimage.2022.119051] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 01/23/2022] [Accepted: 03/01/2022] [Indexed: 12/25/2022] Open
Abstract
Large-scale dynamics of the brain are routinely modelled using systems of nonlinear dynamical equations that describe the evolution of population-level activity, with distinct neural populations often coupled according to an empirically measured structural connectivity matrix. This modelling approach has been used to generate insights into the neural underpinnings of spontaneous brain dynamics, as recorded with techniques such as resting state functional MRI (fMRI). In fMRI, researchers have many degrees of freedom in the way that they can process the data and recent evidence indicates that the choice of pre-processing steps can have a major effect on empirical estimates of functional connectivity. However, the potential influence of such variations on modelling results are seldom considered. Here we show, using three popular whole-brain dynamical models, that different choices during fMRI preprocessing can dramatically affect model fits and interpretations of findings. Critically, we show that the ability of these models to accurately capture patterns in fMRI dynamics is mostly driven by the degree to which they fit global signals rather than interesting sources of coordinated neural dynamics. We show that widespread deflections can arise from simple global synchronisation. We introduce a simple two-parameter model that captures these fluctuations and performs just as well as more complex, multi-parameter biophysical models. From our combined analyses of data and simulations, we describe benchmarks to evaluate model fit and validity. Although most models are not resilient to denoising, we show that relaxing the approximation of homogeneous neural populations by more explicitly modelling inter-regional effective connectivity can improve model accuracy at the expense of increased model complexity. Our results suggest that many complex biophysical models may be fitting relatively trivial properties of the data, and underscore a need for tighter integration between data quality assurance and model development.
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Affiliation(s)
- Kevin M Aquino
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia; School of Physics, University of Sydney, New South Wales, 2006 Australia.
| | - Ben Fulcher
- School of Physics, University of Sydney, New South Wales, 2006 Australia
| | - Stuart Oldham
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia
| | - Linden Parkes
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Leonardo Gollo
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia
| | - Gustavo Deco
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia; Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona 08010, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona 08010, Spain
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia
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41
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The neural basis of acceptance of uncertain situations: Relationship between ambiguity tolerance and the resting-state functional connectivity of the brain. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-02879-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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42
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Knowing Who You Are: Neural Correlates of Self-concept Clarity and Happiness. Neuroscience 2022; 490:264-274. [DOI: 10.1016/j.neuroscience.2022.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 12/02/2021] [Accepted: 03/03/2022] [Indexed: 01/07/2023]
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43
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Sihn D, Kim SP. Brain Infraslow Activity Correlates With Arousal Levels. Front Neurosci 2022; 16:765585. [PMID: 35281492 PMCID: PMC8914100 DOI: 10.3389/fnins.2022.765585] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 02/07/2022] [Indexed: 12/02/2022] Open
Abstract
The functional role of the brain’s infraslow activity (ISA, 0.01–0.1 Hz) in human behavior has yet to be elucidated. To date, it has been shown that the brain’s ISA correlates with behavioral performance; task performance is more likely to increase when executed at a specific ISA phase. However, it is unclear how the ISA correlates behavioral performance. We hypothesized that the ISA phase correlation of behavioral performance is mediated by arousal. Our data analysis results showed that the electroencephalogram (EEG) ISA phase was correlated with the galvanic skin response (GSR) amplitude, a measure of the arousal level. Furthermore, subjects whose EEG ISA phase correlated with the GSR amplitude more strongly also showed greater EEG ISA modulation during meditation, which implies an intimate relationship between brain ISA and arousal. These results may help improve understanding of the functional role of the brain’s ISA.
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44
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Zhang Q, Cramer SR, Ma Z, Turner KL, Gheres KW, Liu Y, Drew PJ, Zhang N. Brain-wide ongoing activity is responsible for significant cross-trial BOLD variability. Cereb Cortex 2022; 32:5311-5329. [PMID: 35179203 PMCID: PMC9712744 DOI: 10.1093/cercor/bhac016] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/09/2022] [Accepted: 01/11/2022] [Indexed: 12/27/2022] Open
Abstract
A notorious issue of task-based functional magnetic resonance imaging (fMRI) is its large cross-trial variability. To quantitatively characterize this variability, the blood oxygenation level-dependent (BOLD) signal can be modeled as a linear summation of a stimulation-relevant and an ongoing (i.e. stimulation-irrelevant) component. However, systematic investigation on the spatiotemporal features of the ongoing BOLD component and how these features affect the BOLD response is still lacking. Here we measured fMRI responses to light onsets and light offsets in awake rats. The neuronal response was simultaneously recorded with calcium-based fiber photometry. We established that between-region BOLD signals were highly correlated brain-wide at zero time lag, including regions that did not respond to visual stimulation, suggesting that the ongoing activity co-fluctuates across the brain. Removing this ongoing activity reduced cross-trial variability of the BOLD response by ~30% and increased its coherence with the Ca2+ signal. Additionally, the negative ongoing BOLD activity sometimes dominated over the stimulation-driven response and contributed to the post-stimulation BOLD undershoot. These results suggest that brain-wide ongoing activity is responsible for significant cross-trial BOLD variability, and this component can be reliably quantified and removed to improve the reliability of fMRI response. Importantly, this method can be generalized to virtually all fMRI experiments without changing stimulation paradigms.
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Affiliation(s)
- Qingqing Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Samuel R Cramer
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, United States
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Kevin L Turner
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Kyle W Gheres
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, PA 16802, United States
| | - Yikang Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Patrick J Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, United States,Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, PA 16802, United States,Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, United States,Department of Neurosurgery, The Pennsylvania State University, Hershey, PA 17033, United States
| | - Nanyin Zhang
- Corresponding author: Biomedical Engineering and Electrical Engineering, Lloyd & Dorothy Foehr Huck Chair in Brain Imaging, The Huck Institutes of Life Sciences, The Pennsylvania State University, W-341 Millennium Science Complex, University Park, PA 16802, United States.
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Singh MF, Wang A, Cole M, Ching S, Braver TS. Enhancing task fMRI preprocessing via individualized model-based filtering of intrinsic activity dynamics. Neuroimage 2022; 247:118836. [PMID: 34942364 PMCID: PMC10069385 DOI: 10.1016/j.neuroimage.2021.118836] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 12/15/2021] [Accepted: 12/18/2021] [Indexed: 11/27/2022] Open
Abstract
Brain responses recorded during fMRI are thought to reflect both rapid, stimulus-evoked activity and the propagation of spontaneous activity through brain networks. In the current work, we describe a method to improve the estimation of task-evoked brain activity by first "filtering-out the intrinsic propagation of pre-event activity from the BOLD signal. We do so using Mesoscale Individualized NeuroDynamic (MINDy; Singh et al. 2020b) models built from individualized resting-state data to subtract the propagation of spontaneous activity from the task-fMRI signal (MINDy-based Filtering). After filtering, time-series are analyzed using conventional techniques. Results demonstrate that this simple operation significantly improves the statistical power and temporal precision of estimated group-level effects. Moreover, use of MINDy-based filtering increased the similarity of neural activation profiles and prediction accuracy of individual differences in behavior across tasks measuring the same construct (cognitive control). Thus, by subtracting the propagation of previous activity, we obtain better estimates of task-related neural effects.
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Affiliation(s)
- Matthew F Singh
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA; Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA.
| | - Anxu Wang
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Michael Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
| | - ShiNung Ching
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Todd S Braver
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA; Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
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From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC). ENTROPY 2022; 24:e24020270. [PMID: 35205564 PMCID: PMC8871397 DOI: 10.3390/e24020270] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/19/2022] [Accepted: 02/10/2022] [Indexed: 02/01/2023]
Abstract
Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream of consciousness.’ Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According to the theory, the relevant spatiotemporal scale for consciousness is the one in which the system reaches the maximum cause-effect power; IIT currently predicts that experience occurs on the order of short timescales, namely, between 100 and 300 ms (theta and alpha frequency range). This can well account for the integration of single inputs into a particular phenomenal content. However, such short timescales leave open the temporal relation of specific phenomenal contents to others during the course of the ongoing time, that is, the stream of consciousness. For that purpose, we converge the IIT with the Temporo-spatial Theory of Consciousness (TTC), which, assuming a multitude of different timescales, can take into view the temporal integration of specific phenomenal contents with other phenomenal contents over time. On the neuronal side, this is detailed by considering those neuronal mechanisms driving the non-additive interaction of pre-stimulus activity with the input resulting in stimulus-related activity. Due to their non-additive interaction, the single input is not only integrated with others in the short-term timescales of 100–300 ms (alpha and theta frequencies) (as predicted by IIT) but, at the same time, also virtually expanded in its temporal (and spatial) features; this is related to the longer timescales (delta and slower frequencies) that are carried over from pre-stimulus to stimulus-related activity. Such a non-additive pre-stimulus-input interaction amounts to temporo-spatial expansion as a key mechanism of TTC for the constitution of phenomenal contents including their embedding or nesting within the ongoing temporal dynamic, i.e., the stream of consciousness. In conclusion, we propose converging the short-term integration of inputs postulated in IIT (100–300 ms as in the alpha and theta frequency range) with the longer timescales (in delta and slower frequencies) of temporo-spatial expansion in TTC.
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Northoff G, Zilio F. Temporo-spatial Theory of Consciousness (TTC) - Bridging the gap of neuronal activity and phenomenal states. Behav Brain Res 2022; 424:113788. [PMID: 35149122 DOI: 10.1016/j.bbr.2022.113788] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 01/22/2023]
Abstract
Consciousness and its neural mechanisms remain a mystery. Current neuroscientific theories focus predominantly on the external input/stimulus and the associated stimulus-related activity during conscious contents. Despite all progress, we encounter two gaps: (i) a gap between spontaneous and stimulus-related activity; (ii) a gap between neuronal and phenomenal features. A novel, different, and unique approach, Temporo-spatial theory of consciousness (TTC) aims to bridge both gaps. The TTC focuses on the brain's spontaneous activity and how its spatial topography and temporal dynamic shape stimulus-related activity and resurface in the corresponding spatial and temporal features of consciousness, i.e., 'common currency'. The TTC introduces four temporo-spatial mechanisms: expansion, globalization, alignment, and nestedness. These are associated with distinct dimensions of consciousness including phenomenal content, access, form/structure, and level/state, respectively. Following up on the first introduction of the TTC in 2017, we review updates, further develop these temporo-spatial mechanisms, and postulate specific neurophenomenal hypotheses. We conclude that the TTC offers a viable approach for (i) linking spontaneous and stimulus-related activity in conscious states; (ii) determining specific neuronal and neurophenomenal mechanisms for the distinct dimensions of consciousness; (iii) an integrative and unifying framework of different neuroscientific theories of consciousness; and (iv) offers novel empirically grounded conceptual assumptions about the biological and ontological nature of consciousness and its relation to the brain.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China; Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy.
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Braun W, Matsuzaka Y, Mushiake H, Northoff G, Longtin A. Non-additive activity modulation during a decision making task involving tactic selection. Cogn Neurodyn 2022; 16:117-133. [PMID: 35116084 PMCID: PMC8807796 DOI: 10.1007/s11571-021-09702-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 06/28/2021] [Accepted: 07/14/2021] [Indexed: 12/01/2022] Open
Abstract
Human brain imaging has revealed that stimulus-induced activity does generally not simply add to the pre-stimulus activity, but rather builds in a non-additive way on this activity. Here we investigate this subject at the single neuron level and address the question whether and to what extent a strong form of non-additivity where activity drops post-cue is present in different areas of monkey cortex, including prefrontal and agranular frontal areas, during a perceptual decision making task involving action and tactic selection. Specifically we analyze spike train data recorded in vivo from the posterior dorsomedial prefrontal cortex (pmPFC), the supplementary motor area (SMA) and the presupplementary motor area (pre-SMA). For each neuron, we compute the ratio of the trial-averaged pre-stimulus spike count to the trial-averaged post-stimulus count. We also perform the ratio and averaging procedures in reverse order. We find that the statistics of these quantities behave differently across areas. pmPFC involved in tactic selection shows stronger non-additivity compared to the two other areas which more generically just increase their firing rate pos-stimulus. pmPFC behaved more similarly to pre-SMA, a likely consequence of the reciprocal connections between these areas. The trial-averaged ratio statistic was reproduced by a surrogate inhomogeneous Poisson process in which the measured trial-averaged firing rate for a given neuron is used as its time-dependent rate. Principal component analysis (PCA) of the trial-averaged firing rates of neuronal ensembles further reveals area-specific time courses of response to the stimulus, including latency to peak neural response, for the typical population activity. Our work demonstrates subtle forms of area-specific non-additivity based on the fine variability structure of pre- and post-stimulus spiking activity on the single neuron level. It also reveals significant differences between areas for PCA and surrogate analysis, complementing previous observations of regional differences based solely on post-stimulus responses. Moreover, we observe regional differences in non-additivity which are related to the monkey's successful tactic selection and decision making. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-021-09702-0.
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Affiliation(s)
- Wilhelm Braun
- Institut für Genetik, Neural Network Dynamics and Computation, Universität Bonn, Kirschallee 1, 53115 Bonn, Germany.,Department of Physics and Centre for Neural Dynamics, University of Ottawa, 150 Louis-Pasteur Pvt, Ottawa, K1N 6N5 Canada
| | - Yoshiya Matsuzaka
- Division of Neuroscience, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, 1-15-1 Fukumuro, Miyagino ward, Sendai, 983-8536 Japan
| | - Hajime Mushiake
- Department of Physiology, Graduate School of Medicine, Tohoku University, Aoba Ward, Sendai, 981-8558 Japan
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, University of Ottawa Institute of Mental Health Research, Royal Ottawa Mental Health Centre, 1145 Carling Avenue, Ottawa, K1Z 7K4 Canada
| | - André Longtin
- Department of Physics and Centre for Neural Dynamics, University of Ottawa, 150 Louis-Pasteur Pvt, Ottawa, K1N 6N5 Canada
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Abstract
The human brain exhibits the remarkable ability to categorize speech sounds into distinct, meaningful percepts, even in challenging tasks like learning non-native speech categories in adulthood and hearing speech in noisy listening conditions. In these scenarios, there is substantial variability in perception and behavior, both across individual listeners and individual trials. While there has been extensive work characterizing stimulus-related and contextual factors that contribute to variability, recent advances in neuroscience are beginning to shed light on another potential source of variability that has not been explored in speech processing. Specifically, there are task-independent, moment-to-moment variations in neural activity in broadly-distributed cortical and subcortical networks that affect how a stimulus is perceived on a trial-by-trial basis. In this review, we discuss factors that affect speech sound learning and moment-to-moment variability in perception, particularly arousal states—neurotransmitter-dependent modulations of cortical activity. We propose that a more complete model of speech perception and learning should incorporate subcortically-mediated arousal states that alter behavior in ways that are distinct from, yet complementary to, top-down cognitive modulations. Finally, we discuss a novel neuromodulation technique, transcutaneous auricular vagus nerve stimulation (taVNS), which is particularly well-suited to investigating causal relationships between arousal mechanisms and performance in a variety of perceptual tasks. Together, these approaches provide novel testable hypotheses for explaining variability in classically challenging tasks, including non-native speech sound learning.
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50
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Machner B, Braun L, Imholz J, Koch PJ, Münte TF, Helmchen C, Sprenger A. Resting-State Functional Connectivity in the Dorsal Attention Network Relates to Behavioral Performance in Spatial Attention Tasks and May Show Task-Related Adaptation. Front Hum Neurosci 2022; 15:757128. [PMID: 35082607 PMCID: PMC8784839 DOI: 10.3389/fnhum.2021.757128] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 12/10/2021] [Indexed: 11/13/2022] Open
Abstract
Between-subject variability in cognitive performance has been related to inter-individual differences in functional brain networks. Targeting the dorsal attention network (DAN) we questioned (i) whether resting-state functional connectivity (FC) within the DAN can predict individual performance in spatial attention tasks and (ii) whether there is short-term adaptation of DAN-FC in response to task engagement. Twenty-seven participants first underwent resting-state fMRI (PRE run), they subsequently performed different tasks of spatial attention [including visual search (VS)] and immediately afterwards received another rs-fMRI (POST run). Intra- and inter-hemispheric FC between core hubs of the DAN, bilateral intraparietal sulcus (IPS) and frontal eye field (FEF), was analyzed and compared between PRE and POST. Furthermore, we investigated rs-fMRI-behavior correlations between the DAN-FC in PRE/POST and task performance parameters. The absolute DAN-FC did not change from PRE to POST. However, different significant rs-fMRI-behavior correlations were revealed for intra-/inter-hemispheric connections in the PRE and POST run. The stronger the FC between left FEF and IPS before task engagement, the better was the learning effect (improvement of reaction times) in VS (r = 0.521, p = 0.024). And the faster the VS (mean RT), the stronger was the FC between right FEF and IPS after task engagement (r = −0.502, p = 0.032). To conclude, DAN-FC relates to the individual performance in spatial attention tasks supporting the view of functional brain networks as priors for cognitive ability. Despite a high inter- and intra-individual stability of DAN-FC, the change of FC-behavior correlations after task performance possibly indicates task-related adaptation of the DAN, underlining that behavioral experiences may shape intrinsic brain activity. However, spontaneous state fluctuations of the DAN-FC over time cannot be fully ruled out as an alternative explanation.
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Affiliation(s)
- Björn Machner
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
- *Correspondence: Björn Machner, ; orcid.org/0000-0001-7981-2906
| | - Lara Braun
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Jonathan Imholz
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Philipp J. Koch
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Thomas F. Münte
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Christoph Helmchen
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Andreas Sprenger
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
- Department of Psychology II, University of Lübeck, Lübeck, Germany
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