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Bardella G, Giuffrida V, Giarrocco F, Brunamonti E, Pani P, Ferraina S. Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network. Netw Neurosci 2024; 8:597-622. [PMID: 38952814 PMCID: PMC11168728 DOI: 10.1162/netn_a_00365] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.
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Affiliation(s)
- Giampiero Bardella
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Valentina Giuffrida
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Franco Giarrocco
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Pierpaolo Pani
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Stefano Ferraina
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
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Lichtenfeld MJ, Mulvey AG, Nejat H, Xiong YS, Carlson BM, Mitchell BA, Mendoza-Halliday D, Westerberg JA, Desimone R, Maier A, Kaas JH, Bastos AM. The laminar organization of cell types in macaque cortex and its relationship to neuronal oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.27.587084. [PMID: 38585801 PMCID: PMC10996711 DOI: 10.1101/2024.03.27.587084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The canonical microcircuit (CMC) has been hypothesized to be the fundamental unit of information processing in cortex. Each CMC unit is thought to be an interconnected column of neurons with specific connections between excitatory and inhibitory neurons across layers. Recently, we identified a conserved spectrolaminar motif of oscillatory activity across the primate cortex that may be the physiological consequence of the CMC. The spectrolaminar motif consists of local field potential (LFP) gamma-band power (40-150 Hz) peaking in superficial layers 2 and 3 and alpha/beta-band power (8-30 Hz) peaking in deep layers 5 and 6. Here, we investigate whether specific conserved cell types may produce the spectrolaminar motif. We collected laminar histological and electrophysiological data in 11 distinct cortical areas spanning the visual hierarchy: V1, V2, V3, V4, TEO, MT, MST, LIP, 8A/FEF, PMD, and LPFC (area 46), and anatomical data in DP and 7A. We stained representative slices for the three main inhibitory subtypes, Parvalbumin (PV), Calbindin (CB), and Calretinin (CR) positive neurons, as well as pyramidal cells marked with Neurogranin (NRGN). We found a conserved laminar structure of PV, CB, CR, and pyramidal cells. We also found a consistent relationship between the laminar distribution of inhibitory subtypes with power in the local field potential. PV interneuron density positively correlated with gamma (40-150 Hz) power. CR and CB density negatively correlated with alpha (8-12 Hz) and beta (13-30 Hz) oscillations. The conserved, layer-specific pattern of inhibition and excitation across layers is therefore likely the anatomical substrate of the spectrolaminar motif. Significance Statement Neuronal oscillations emerge as an interplay between excitatory and inhibitory neurons and underlie cognitive functions and conscious states. These oscillations have distinct expression patterns across cortical layers. Does cellular anatomy enable these oscillations to emerge in specific cortical layers? We present a comprehensive analysis of the laminar distribution of the three main inhibitory cell types in primate cortex (Parvalbumin, Calbindin, and Calretinin positive) and excitatory pyramidal cells. We found a canonical relationship between the laminar anatomy and electrophysiology in 11 distinct primate areas spanning from primary visual to prefrontal cortex. The laminar anatomy explained the expression patterns of neuronal oscillations in different frequencies. Our work provides insight into the cortex-wide cellular mechanisms that generate neuronal oscillations in primates.
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Manea AMG, Maisson DJN, Voloh B, Zilverstand A, Hayden B, Zimmermann J. Neural timescales reflect behavioral demands in freely moving rhesus macaques. Nat Commun 2024; 15:2151. [PMID: 38461167 PMCID: PMC10925022 DOI: 10.1038/s41467-024-46488-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 02/28/2024] [Indexed: 03/11/2024] Open
Abstract
Previous work demonstrated a highly reproducible cortical hierarchy of neural timescales at rest, with sensory areas displaying fast, and higher-order association areas displaying slower timescales. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this lack of variability in the hierarchical organization of neural timescales could reflect the structure of the laboratory contexts. We posit that unconstrained paradigms are ideal to test whether the dynamics of neural timescales reflect behavioral demands. Here we measured timescales of local field potential activity while male rhesus macaques foraged in an open space. We found a hierarchy of neural timescales that differs from previous work. Importantly, although the magnitude of neural timescales expanded with task engagement, the brain areas' relative position in the hierarchy was stable. Next, we demonstrated that the change in neural timescales is dynamic and contains functionally-relevant information, differentiating between similar events in terms of motor demands and associated reward. Finally, we demonstrated that brain areas are differentially affected by these behavioral demands. These results demonstrate that while the space of neural timescales is anatomically constrained, the observed hierarchical organization and magnitude is dependent on behavioral demands.
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Affiliation(s)
- Ana M G Manea
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA.
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
| | - David J-N Maisson
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Voloh
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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4
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Wei Y, Zhang C, Peng Y, Chen C, Han S, Wang W, Zhang Y, Lu H, Cheng J. MRI Assessment of Intrinsic Neural Timescale and Gray Matter Volume in Parkinson's Disease. J Magn Reson Imaging 2024; 59:987-995. [PMID: 37318377 DOI: 10.1002/jmri.28864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Numerous studies have indicated altered temporal features of the brain function in Parkinson's disease (PD), and the autocorrelation magnitude of intrinsic neural signals, called intrinsic neural timescales, were often applied to estimate how long neural information stored in local brain areas. However, it is unclear whether PD patients at different disease stages exhibit abnormal timescales accompanied with abnormal gray matter volume (GMV). PURPOSE To assess the intrinsic timescale and GMV in PD. STUDY TYPE Prospective. POPULATION 74 idiopathic PD patients (44 early stage (PD-ES) and 30 late stage (PD-LS), as determined by the Hoehn and Yahr (HY) severity classification scale), and 73 healthy controls (HC). FIELD STRENGTH/SEQUENCE 3.0 T MRI scanner; magnetization prepared rapid acquisition gradient echo and echo planar imaging sequences. ASSESSMENT The timescales were estimated by using the autocorrelation magnitude of neural signals. Voxel-based morphometry was performed to calculate GMV in the whole brain. Severity of motor symptoms and cognitive impairments were assessed using the unified PD rating scale, the HY scale, the Montreal cognitive assessment, and the mini-mental state examination. STATISTICAL TEST Analysis of variance; two-sample t-test; Spearman rank correlation analysis; Mann-Whitney U test; Kruskal-Wallis' H test. A P value <0.05 was considered statistically significant. RESULTS The PD group had significantly abnormal intrinsic timescales in the sensorimotor, visual, and cognitive-related areas, which correlated with the symptom severity (ρ = -0.265, P = 0.022) and GMV (ρ = 0.254, P = 0.029). Compared to the HC group, the PD-ES group had significantly longer timescales in anterior cortical regions, whereas the PD-LS group had significantly shorter timescales in posterior cortical regions. CONCLUSION This study suggested that PD patients have abnormal timescales in multisystem and distinct patterns of timescales and GMV in cerebral cortex at different disease stages. This may provide new insights for the neural substrate of PD. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chunyan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yuanyuan Peng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chen Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Hong Lu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
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Lurie DJ, Pappas I, D'Esposito M. Cortical timescales and the modular organization of structural and functional brain networks. Hum Brain Mapp 2024; 45:e26587. [PMID: 38339903 PMCID: PMC10823764 DOI: 10.1002/hbm.26587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 02/12/2024] Open
Abstract
Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.
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Affiliation(s)
- Daniel J. Lurie
- Department of PsychologyUniversity of CaliforniaBerkeleyCaliforniaUSA
- Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPennsylvaniaUSA
| | - Ioannis Pappas
- Department of Neurology, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Mark D'Esposito
- Department of Psychology and Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
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Lurie DJ, Pappas I, D'Esposito M. Cortical timescales and the modular organization of structural and functional brain networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548751. [PMID: 37502887 PMCID: PMC10370009 DOI: 10.1101/2023.07.12.548751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.
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Affiliation(s)
- Daniel J Lurie
- Department of Psychology, University of California, Berkeley
| | - Ioannis Pappas
- Department of Neurology, Keck School of Medicine, University of Southern California
| | - Mark D'Esposito
- Department of Psychology and Helen Wills Neuroscience Institute, University of California, Berkeley
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7
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Manea AMG, Zilverstand A, Hayden B, Zimmermann J. Neural timescales reflect behavioral demands in freely moving rhesus macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534470. [PMID: 37034608 PMCID: PMC10081241 DOI: 10.1101/2023.03.27.534470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
Previous work has demonstrated remarkably reproducible and consistent hierarchies of neural timescales across cortical areas at rest. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this previously found lack of variability in the hierarchical organization of neural timescales could be a reflection of the structure of the laboratory contexts in which they were measured. Indeed, computational work demonstrates the existence of multiple temporal hierarchies within the same anatomical network when the input structure is altered. We posit that unconstrained behavioral environments where relatively little temporal demands are imposed from the experimenter are an ideal test bed to address the question of whether the hierarchical organization and the magnitude of neural timescales reflect ongoing behavioral demands. To tackle this question, we measured timescales of local field potential activity while rhesus macaques were foraging freely in a large open space. We find a hierarchy of neural timescales that is unique to this foraging environment. Importantly, although the magnitude of neural timescales generally expanded with task engagement, the brain areas' relative position in the hierarchy was stable across the recording sessions. Notably, the magnitude of neural timescales monotonically expanded with task engagement across a relatively long temporal scale spanning the duration of the recording session. Over shorter temporal scales, the magnitude of neural timescales changed dynamically around foraging events. Moreover, the change in the magnitude of neural timescales contained functionally relevant information, differentiating between seemingly similar events in terms of motor demands and associated reward. That is, the patterns of change were associated with the cognitive and behavioral meaning of these events. Finally, we demonstrated that brain areas were differentially affected by these behavioral demands - i.e., the expansion of neural timescales was not the same across all areas. Together, these results demonstrate that the observed hierarchy of neural timescales is context-dependent and that changes in the magnitude of neural timescales are closely related to overall task engagement and behavioral demands.
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Affiliation(s)
- Ana M G Manea
- Department of Neuroscience, University of Minnesota, Minneapolis MN
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis MN
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis MN
| | - Benjamin Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis MN
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis MN
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Northoff G, Vatansever D, Scalabrini A, Stamatakis EA. Ongoing Brain Activity and Its Role in Cognition: Dual versus Baseline Models. Neuroscientist 2022:10738584221081752. [PMID: 35611670 DOI: 10.1177/10738584221081752] [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] [Indexed: 12/20/2022]
Abstract
What is the role of the brain's ongoing activity for cognition? The predominant perspectives associate ongoing brain activity with resting state, the default-mode network (DMN), and internally oriented mentation. This triad is often contrasted with task states, non-DMN brain networks, and externally oriented mentation, together comprising a "dual model" of brain and cognition. In opposition to this duality, however, we propose that ongoing brain activity serves as a neuronal baseline; this builds upon Raichle's original search for the default mode of brain function that extended beyond the canonical default-mode brain regions. That entails what we refer to as the "baseline model." Akin to an internal biological clock for the rest of the organism, the ongoing brain activity may serve as an internal point of reference or standard by providing a shared neural code for the brain's rest as well as task states, including their associated cognition. Such shared neural code is manifest in the spatiotemporal organization of the brain's ongoing activity, including its global signal topography and dynamics like intrinsic neural timescales. We conclude that recent empirical evidence supports a baseline model over the dual model; the ongoing activity provides a global shared neural code that allows integrating the brain's rest and task states, its DMN and non-DMN, and internally and externally oriented cognition.
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9
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Manea AMG, Zilverstand A, Ugurbil K, Heilbronner S, Zimmermann J. Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain. eLife 2022; 11:75540. [PMID: 35234612 PMCID: PMC8923667 DOI: 10.7554/elife.75540] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole-brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field fMRI performed at 10.5 Tesla to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match functional connectivity gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.
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Affiliation(s)
- Ana M G Manea
- Department of Neuroscience, University of Minnesota, Minneapolis, United States
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States
| | - Sarah Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, United States
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10
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Wolff A, Berberian N, Golesorkhi M, Gomez-Pilar J, Zilio F, Northoff G. Intrinsic neural timescales: temporal integration and segregation. Trends Cogn Sci 2022; 26:159-173. [PMID: 34991988 DOI: 10.1016/j.tics.2021.11.007] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/19/2021] [Accepted: 11/23/2021] [Indexed: 12/11/2022]
Abstract
We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal-transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.
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Affiliation(s)
- Annemarie Wolff
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Nareg Berberian
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Mehrshad Golesorkhi
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicia, (CIBER-BBN), Madrid, Spain
| | - Federico Zilio
- Department of Philosophy, Sociology, Education, and Applied Psychology, University of Padova, Padua, Italy
| | - 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.
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11
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Nougaret S, Fascianelli V, Ravel S, Genovesio A. Intrinsic timescales across the basal ganglia. Sci Rep 2021; 11:21395. [PMID: 34725371 PMCID: PMC8560808 DOI: 10.1038/s41598-021-00512-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 09/27/2021] [Indexed: 11/09/2022] Open
Abstract
Recent studies have shown that temporal stability of the neuronal activity over time can be estimated by the structure of the spike-count autocorrelation of neuronal populations. This estimation, called the intrinsic timescale, has been computed for several cortical areas and can be used to propose a cortical hierarchy reflecting a scale of temporal receptive windows between areas. In this study, we performed an autocorrelation analysis on neuronal populations of three basal ganglia (BG) nuclei, including the striatum and the subthalamic nucleus (STN), the input structures of the BG, and the external globus pallidus (GPe). The analysis was performed during the baseline period of a motivational visuomotor task in which monkeys had to apply different amounts of force to receive different amounts of reward. We found that the striatum and the STN have longer intrinsic timescales than the GPe. Moreover, our results allow for the placement of these subcortical structures within the already-defined scale of cortical temporal receptive windows. Estimates of intrinsic timescales are important in adding further constraints in the development of computational models of the complex dynamics among these nuclei and throughout cortico-BG-thalamo-cortical loops.
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Affiliation(s)
- Simon Nougaret
- Institut de Neurosciences de la Timone, UMR7289, Centre National de la Recherche Scientifique and Aix-Marseille Université, Marseille, France. .,Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy.
| | - Valeria Fascianelli
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy.,PhD Program in Behavioral Neuroscience, Sapienza University of Rome, 00185, Rome, Italy
| | - Sabrina Ravel
- Institut de Neurosciences de la Timone, UMR7289, Centre National de la Recherche Scientifique and Aix-Marseille Université, Marseille, France
| | - Aldo Genovesio
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy.
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Golesorkhi M, Gomez-Pilar J, Zilio F, Berberian N, Wolff A, Yagoub MCE, Northoff G. The brain and its time: intrinsic neural timescales are key for input processing. Commun Biol 2021; 4:970. [PMID: 34400800 PMCID: PMC8368044 DOI: 10.1038/s42003-021-02483-6] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 07/19/2021] [Indexed: 02/07/2023] Open
Abstract
We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs' stochastics with the ongoing temporal statistics of the brain's neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.
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Affiliation(s)
- Mehrshad Golesorkhi
- grid.28046.380000 0001 2182 2255School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada ,grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Javier Gomez-Pilar
- grid.5239.d0000 0001 2286 5329Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
| | - Federico Zilio
- grid.5608.b0000 0004 1757 3470Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy
| | - Nareg Berberian
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Annemarie Wolff
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Mustapha C. E. Yagoub
- grid.28046.380000 0001 2182 2255School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
| | - Georg Northoff
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada ,grid.410595.c0000 0001 2230 9154Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China ,grid.13402.340000 0004 1759 700XMental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
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Huh N, Kim SP, Lee J, Sohn JW. Extracting single-trial neural interaction using latent dynamical systems model. Mol Brain 2021; 14:32. [PMID: 33588875 PMCID: PMC7885376 DOI: 10.1186/s13041-021-00740-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/25/2021] [Indexed: 11/10/2022] Open
Abstract
In systems neuroscience, advances in simultaneous recording technology have helped reveal the population dynamics that underlie the complex neural correlates of animal behavior and cognitive processes. To investigate these correlates, neural interactions are typically abstracted from spike trains of pairs of neurons accumulated over the course of many trials. However, the resultant averaged values do not lead to understanding of neural computation in which the responses of populations are highly variable even under identical external conditions. Accordingly, neural interactions within the population also show strong fluctuations. In the present study, we introduce an analysis method reflecting the temporal variation of neural interactions, in which cross-correlograms on rate estimates are applied via a latent dynamical systems model. Using this method, we were able to predict time-varying neural interactions within a single trial. In addition, the pairwise connections estimated in our analysis increased along behavioral epochs among neurons categorized within similar functional groups. Thus, our analysis method revealed that neurons in the same groups communicate more as the population gets involved in the assigned task. We also showed that the characteristics of neural interaction from our model differ from the results of a typical model employing cross-correlation coefficients. This suggests that our model can extract nonoverlapping information about network topology, unlike the typical model.
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Affiliation(s)
- Namjung Huh
- Department of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung, 25601, Republic of Korea.
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
| | - Joonyeol Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419, Republic of Korea.,Department of Biomedical Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Jeong-Woo Sohn
- Department of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung, 25601, Republic of Korea. .,Translational Brain Research Center, International St. Mary's Hospital, Catholic Kwandong University, Incheon, 22711, Republic of Korea.
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Sacchetti S, Ceccarelli F, Ferrucci L, Benozzo D, Brunamonti E, Nougaret S, Genovesio A. Macaque monkeys learn and perform a non-match-to-goal task using an automated home cage training procedure. Sci Rep 2021; 11:2700. [PMID: 33514812 PMCID: PMC7846587 DOI: 10.1038/s41598-021-82021-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 01/04/2021] [Indexed: 01/30/2023] Open
Abstract
In neurophysiology, nonhuman primates represent an important model for studying the brain. Typically, monkeys are moved from their home cage to an experimental room daily, where they sit in a primate chair and interact with electronic devices. Refining this procedure would make the researchers' work easier and improve the animals' welfare. To address this issue, we used home-cage training to train two macaque monkeys in a non-match-to-goal task, where each trial required a switch from the choice made in the previous trial to obtain a reward. The monkeys were tested in two versions of the task, one in which they acted as the agent in every trial and one in which some trials were completed by a "ghost agent". We evaluated their involvement in terms of their performance and their interaction with the apparatus. Both monkeys were able to maintain a constant involvement in the task with good, stable performance within sessions in both versions of the task. Our study confirms the feasibility of home-cage training and demonstrates that even with challenging tasks, monkeys can complete a large number of trials at a high performance level, which is a prerequisite for electrophysiological studies of monkey behavior.
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Affiliation(s)
- Stefano Sacchetti
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy ,grid.7841.aPhD Program in Behavioral Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Francesco Ceccarelli
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy ,grid.7841.aPhD Program in Behavioral Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Lorenzo Ferrucci
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Danilo Benozzo
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Emiliano Brunamonti
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Simon Nougaret
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Aldo Genovesio
- grid.7841.aDepartment of Physiology and Pharmacology, SAPIENZA, University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
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Cavanagh SE, Hunt LT, Kennerley SW. A Diversity of Intrinsic Timescales Underlie Neural Computations. Front Neural Circuits 2020; 14:615626. [PMID: 33408616 PMCID: PMC7779632 DOI: 10.3389/fncir.2020.615626] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 11/18/2020] [Indexed: 12/05/2022] Open
Abstract
Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region's position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.
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Affiliation(s)
- Sean E. Cavanagh
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom
| | - Laurence T. Hunt
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
- Max Planck-UCL Centre for Computational Psychiatry and Aging, University College London, London, United Kingdom
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Steven W. Kennerley
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom
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Brief localised monocular deprivation in adults alters binocular rivalry predominance retinotopically and reduces spatial inhibition. Sci Rep 2020; 10:18739. [PMID: 33127963 PMCID: PMC7603489 DOI: 10.1038/s41598-020-75252-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 10/07/2020] [Indexed: 11/29/2022] Open
Abstract
Short-term deprivation (2.5 h) of an eye has been shown to boost its relative ocular dominance in young adults. Here, we show that a much shorter deprivation period (3–6 min) produces a similar paradoxical boost that is retinotopic and reduces spatial inhibition on neighbouring, non-deprived areas. Partial deprivation was conducted in the left hemifield, central vision or in an annular region, later assessed with a binocular rivalry tracking procedure. Post-deprivation, dominance of the deprived eye increased when rivalling images were within the deprived retinotopic region, but not within neighbouring, non-deprived areas where dominance was dependent on the correspondence between the orientation content of the stimuli presented in the deprived and that of the stimuli presented in non-deprived areas. Together, these results accord with other deprivation studies showing V1 activity changes and reduced GABAergic inhibition.
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Multiple timescales of neural dynamics and integration of task-relevant signals across cortex. Proc Natl Acad Sci U S A 2020; 117:22522-22531. [PMID: 32839338 DOI: 10.1073/pnas.2005993117] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
A long-lasting challenge in neuroscience has been to find a set of principles that could be used to organize the brain into distinct areas with specific functions. Recent studies have proposed the orderly progression in the time constants of neural dynamics as an organizational principle of cortical computations. However, relationships between these timescales and their dependence on response properties of individual neurons are unknown, making it impossible to determine how mechanisms underlying such a computational principle are related to other aspects of neural processing. Here, we developed a comprehensive method to simultaneously estimate multiple timescales in neuronal dynamics and integration of task-relevant signals along with selectivity to those signals. By applying our method to neural and behavioral data during a dynamic decision-making task, we found that most neurons exhibited multiple timescales in their response, which consistently increased from parietal to prefrontal and cingulate cortex. While predicting rates of behavioral adjustments, these timescales were not correlated across individual neurons in any cortical area, resulting in independent parallel hierarchies of timescales. Additionally, none of these timescales depended on selectivity to task-relevant signals. Our results not only suggest the existence of multiple canonical mechanisms for increasing timescales of neural dynamics across cortex but also point to additional mechanisms that allow decorrelation of these timescales to enable more flexibility.
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