1
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Adegoke MA, Teter O, Meaney DF. Flexibility of in vitro cortical circuits influences resilience from microtrauma. Front Cell Neurosci 2022; 16:991740. [PMID: 36589287 PMCID: PMC9803265 DOI: 10.3389/fncel.2022.991740] [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: 07/11/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma. Methods Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca2+ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands. Results We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands. Conclusion Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.
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Affiliation(s)
- Modupe A. Adegoke
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States
| | - Olivia Teter
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States
| | - David F. Meaney
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States,Department of Neurosurgery, Penn Center for Brain Injury and Repair, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States,*Correspondence: David F. Meaney,
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2
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Fakhar K, Hilgetag CC. Systematic perturbation of an artificial neural network: A step towards quantifying causal contributions in the brain. PLoS Comput Biol 2022; 18:e1010250. [PMID: 35714139 PMCID: PMC9246164 DOI: 10.1371/journal.pcbi.1010250] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 06/30/2022] [Accepted: 05/25/2022] [Indexed: 11/24/2022] Open
Abstract
Lesion inference analysis is a fundamental approach for characterizing the causal contributions of neural elements to brain function. This approach has gained new prominence through the arrival of modern perturbation techniques with unprecedented levels of spatiotemporal precision. While inferences drawn from brain perturbations are conceptually powerful, they face methodological difficulties. Particularly, they are challenged to disentangle the true causal contributions of the involved elements, since often functions arise from coalitions of distributed, interacting elements, and localized perturbations have unknown global consequences. To elucidate these limitations, we systematically and exhaustively lesioned a small artificial neural network (ANN) playing a classic arcade game. We determined the functional contributions of all nodes and links, contrasting results from sequential single-element perturbations with simultaneous perturbations of multiple elements. We found that lesioning individual elements, one at a time, produced biased results. By contrast, multi-site lesion analysis captured crucial details that were missed by single-site lesions. We conclude that even small and seemingly simple ANNs show surprising complexity that needs to be addressed by multi-lesioning for a coherent causal characterization. The motto “No causation without manipulation” is canonical to scientific endeavors. In particular, neuroscience seeks to identify which brain elements are causally involved in cognition and behavior, by perturbing them. However, due to multi-dimensional interactions among the elements, this goal has remained challenging. Here, we used an Artificial Neural Network as a ground-truth model to compare the inferential capacities of two principal approaches, lesioning a system one element at a time versus sampling from the set of all possible combinations of lesions. We show that lesioning one element at a time provides misleading results. Hence, we argue for employing exhaustive perturbation regimes. We further advocate using simulation experiments and ground-truth models to verify the assumptions and limitations of current approaches for brain mapping by perturbation.
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Affiliation(s)
- Kayson Fakhar
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
- * E-mail:
| | - Claus C. Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
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3
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Pinto L, Tank DW, Brody CD. Multiple timescales of sensory-evidence accumulation across the dorsal cortex. eLife 2022; 11:e70263. [PMID: 35708483 PMCID: PMC9203055 DOI: 10.7554/elife.70263] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical areas seem to form a hierarchy of intrinsic timescales, but the relevance of this organization for cognitive behavior remains unknown. In particular, decisions requiring the gradual accrual of sensory evidence over time recruit widespread areas across this hierarchy. Here, we tested the hypothesis that this recruitment is related to the intrinsic integration timescales of these widespread areas. We trained mice to accumulate evidence over seconds while navigating in virtual reality and optogenetically silenced the activity of many cortical areas during different brief trial epochs. We found that the inactivation of all tested areas affected the evidence-accumulation computation. Specifically, we observed distinct changes in the weighting of sensory evidence occurring during and before silencing, such that frontal inactivations led to stronger deficits on long timescales than posterior cortical ones. Inactivation of a subset of frontal areas also led to moderate effects on behavioral processes beyond evidence accumulation. Moreover, large-scale cortical Ca2+ activity during task performance displayed different temporal integration windows. Our findings suggest that the intrinsic timescale hierarchy of distributed cortical areas is an important component of evidence-accumulation mechanisms.
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Affiliation(s)
- Lucas Pinto
- Department of Neuroscience, Northwestern UniversityChicagoUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - David W Tank
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
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4
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van Assche M, Klug J, Dirren E, Richiardi J, Carrera E. Preparing for a Second Attack: A Lesion Simulation Study on Network Resilience After Stroke. Stroke 2022; 53:2038-2047. [DOI: 10.1161/strokeaha.121.037372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Does the brain become more resilient after a first stroke to reduce the consequences of a new lesion? Although recurrent strokes are a major clinical issue, whether and how the brain prepares for a second attack is unknown. This is due to the difficulties to obtain an appropriate dataset of stroke patients with comparable lesions, imaged at the same interval after onset. Furthermore, timing of the recurrent event remains unpredictable.
Methods:
Here, we used a novel clinical lesion simulation approach to test the hypothesis that resilience in brain networks increases during stroke recovery. Sixteen highly selected patients with a lesion restricted to the primary motor cortex were recruited. At 3 time points of the index event (10 days, 3 weeks, 3 months), we mimicked recurrent infarcts by deletion of nodes in brain networks (resting-state functional magnetic resonance imaging). Graph measures were applied to determine resilience (global efficiency after attack) and wiring cost (mean degree) of the network.
Results:
At 10 days and 3 weeks after stroke, resilience was similar in patients and controls. However, at 3 months, although motor function had fully recovered, resilience to clinically representative simulated lesions was higher compared to controls (cortical lesion
P
=0.012; subcortical:
P
=0.009; cortico-subcortical:
P
=0.009). Similar results were found after random (
P
=0.012) and targeted (
P
=0.015) attacks.
Conclusions:
Our results suggest that, in this highly selected cohort of patients with lesions restricted to the primary motor cortex, brain networks reconfigure to increase resilience to future insults. Lesion simulation is an innovative approach, which may have major implications for stroke therapy. Individualized neuromodulation strategies could be developed to foster resilient network reconfigurations after a first stroke to limit the consequences of future attacks.
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Affiliation(s)
- Mitsouko van Assche
- Stroke Research Group, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, Geneva, Switzerland (M.v.A., J.K., E.D., E.C.)
| | - Julian Klug
- Stroke Research Group, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, Geneva, Switzerland (M.v.A., J.K., E.D., E.C.)
| | - Elisabeth Dirren
- Stroke Research Group, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, Geneva, Switzerland (M.v.A., J.K., E.D., E.C.)
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland (J.R.)
| | - Emmanuel Carrera
- Stroke Research Group, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, Geneva, Switzerland (M.v.A., J.K., E.D., E.C.)
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5
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Shu P, Zhu H, Jin W, Zhou J, Tong S, Sun J. The Resilience and Vulnerability of Human Brain Networks Across the Lifespan. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1756-1765. [PMID: 34410925 DOI: 10.1109/tnsre.2021.3105991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Resilience, the ability for a system to maintain its basic functionality when suffering from lesions, is a critical property for human brain, especially in the brain aging process. This study adopted a novel metric of network resilience, the Resilience Index (RI), to assess human brain resilience with three different lifespan datasets. Based on the structural brain networks constructed from diffusion tensor imaging (DTI), we observed an inverted-U relationship between RI and age, that is, RI increased during development and early adulthood, reached a peak at about 35 years old, and then decreased during aging, which suggested that brain resilience could be quantified by RI. Furthermore, we studied brain network vulnerability by the decreases in RI when virtual lesions occurred to nodes (i.e., brain regions) or edges (i.e., structural brain connectivity). We found that the strong edges were markedly vulnerable, and the homotopic edges were the most prominent representatives of vulnerable edges. In other words, an arbitrary attack on homotopic edges would have a high probability to degrade brain network resilience. These findings suggest the change of human brain resilience across the lifespan and provide a new perspective for exploring human brain vulnerability.
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6
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Tao Y, Rapp B. Investigating the network consequences of focal brain lesions through comparisons of real and simulated lesions. Sci Rep 2021; 11:2213. [PMID: 33500494 PMCID: PMC7838400 DOI: 10.1038/s41598-021-81107-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 01/04/2021] [Indexed: 11/12/2022] Open
Abstract
Given the increased interest in the functional human connectome, a number of computer simulation studies have sought to develop a better quantitative understanding of the effects of focal lesions on the brain’s functional network organization. However, there has been little work evaluating the predictions of this simulation work vis a vis real lesioned connectomes. One of the few relevant studies reported findings from real chronic focal lesions that only partially confirmed simulation predictions. We hypothesize that these discrepancies arose because although the effects of focal lesions likely consist of two components: short-term node subtraction and long-term network re-organization, previous simulation studies have primarily modeled only the short-term consequences of the subtraction of lesioned nodes and their connections. To evaluate this hypothesis, we compared network properties (modularity, participation coefficient, within-module degree) between real functional connectomes obtained from chronic stroke participants and “pseudo-lesioned” functional connectomes generated by subtracting the same sets of lesioned nodes/connections from healthy control connectomes. We found that, as we hypothesized, the network properties of real-lesioned connectomes in chronic stroke differed from those of the pseudo-lesioned connectomes which instantiated only the short-term consequences of node subtraction. Reflecting the long-term consequences of focal lesions, we found re-organization of the neurotopography of global and local hubs in the real but not the pseudo-lesioned connectomes. We conclude that the long-term network re-organization that occurs in response to focal lesions involves changes in functional connectivity within the remaining intact neural tissue that go well beyond the short-term consequences of node subtraction.
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Affiliation(s)
- Yuan Tao
- Department of Cognitive Science, Johns Hopkins University, Baltimore, USA.
| | - Brenda Rapp
- Department of Cognitive Science, Johns Hopkins University, Baltimore, USA
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7
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Chien JH, Colloca L, Korzeniewska A, Meeker TJ, Bienvenu OJ, Saffer MI, Lenz FA. Behavioral, Physiological and EEG Activities Associated with Conditioned Fear as Sensors for Fear and Anxiety. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6751. [PMID: 33255916 PMCID: PMC7728331 DOI: 10.3390/s20236751] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 11/03/2020] [Accepted: 11/10/2020] [Indexed: 11/16/2022]
Abstract
Anxiety disorders impose substantial costs upon public health and productivity in the USA and worldwide. At present, these conditions are quantified by self-report questionnaires that only apply to behaviors that are accessible to consciousness, or by the timing of responses to fear- and anxiety-related words that are indirect since they do not produce fear, e.g., Dot Probe Test and emotional Stroop. We now review the conditioned responses (CRs) to fear produced by a neutral stimulus (conditioned stimulus CS+) when it cues a painful laser unconditioned stimulus (US). These CRs include autonomic (Skin Conductance Response) and ratings of the CS+ unpleasantness, ability to command attention, and the recognition of the association of CS+ with US (expectancy). These CRs are directly related to fear, and some measure behaviors that are minimally accessible to consciousness e.g., economic scales. Fear-related CRs include non-phase-locked phase changes in oscillatory EEG power defined by frequency and time post-stimulus over baseline, and changes in phase-locked visual and laser evoked responses both of which include late potentials reflecting attention or expectancy, like the P300, or contingent negative variation. Increases (ERS) and decreases (ERD) in oscillatory power post-stimulus may be generalizable given their consistency across healthy subjects. ERS and ERD are related to the ratings above as well as to anxious personalities and clinical anxiety and can resolve activity over short time intervals like those for some moods and emotions. These results could be incorporated into an objective instrumented test that measures EEG and CRs of autonomic activity and psychological ratings related to conditioned fear, some of which are subliminal. As in the case of instrumented tests of vigilance, these results could be useful for the direct, objective measurement of multiple aspects of the risk, diagnosis, and monitoring of therapies for anxiety disorders and anxious personalities.
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Affiliation(s)
- Jui-Hong Chien
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287-7713, USA; (J.-H.C.); (T.J.M.); (M.I.S.)
| | - Luana Colloca
- Department of Pain Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD 21201-1595, USA;
- Department of Anesthesiology, School of Medicine, University of Maryland, Baltimore, MD 21201-1595, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21287-7713, USA;
| | - Timothy J. Meeker
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287-7713, USA; (J.-H.C.); (T.J.M.); (M.I.S.)
| | - O. Joe Bienvenu
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD 21287-7713, USA;
| | - Mark I. Saffer
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287-7713, USA; (J.-H.C.); (T.J.M.); (M.I.S.)
| | - Fred A. Lenz
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287-7713, USA; (J.-H.C.); (T.J.M.); (M.I.S.)
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8
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Pinto L, Rajan K, DePasquale B, Thiberge SY, Tank DW, Brody CD. Task-Dependent Changes in the Large-Scale Dynamics and Necessity of Cortical Regions. Neuron 2019; 104:810-824.e9. [PMID: 31564591 PMCID: PMC7036751 DOI: 10.1016/j.neuron.2019.08.025] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 06/18/2019] [Accepted: 08/13/2019] [Indexed: 12/15/2022]
Abstract
Neural activity throughout the cortex is correlated with perceptual decisions, but inactivation studies suggest that only a small number of areas are necessary for these behaviors. Here we show that the number of required cortical areas and their dynamics vary across related tasks with different cognitive computations. In a visually guided virtual T-maze task, bilateral inactivation of only a few dorsal cortical regions impaired performance. In contrast, in tasks requiring evidence accumulation and/or post-stimulus memory, performance was impaired by inactivation of widespread cortical areas with diverse patterns of behavioral deficits across areas and tasks. Wide-field imaging revealed widespread ramps of Ca2+ activity during the accumulation and visually guided tasks. Additionally, during accumulation, different regions had more diverse activity profiles, leading to reduced inter-area correlations. Using a modular recurrent neural network model trained to perform analogous tasks, we argue that differences in computational strategies alone could explain these findings.
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Affiliation(s)
- Lucas Pinto
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Kanaka Rajan
- Joseph Henry Laboratories of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10014, USA
| | - Brian DePasquale
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Stephan Y Thiberge
- Bezos Center for Neural Dynamics, Princeton University, Princeton, NJ 08544, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Bezos Center for Neural Dynamics, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Howard Hughes Medical Institute, Princeton University, Princeton, NJ 08544, USA.
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9
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Farooq H, Chen Y, Georgiou TT, Tannenbaum A, Lenglet C. Network curvature as a hallmark of brain structural connectivity. Nat Commun 2019; 10:4937. [PMID: 31666510 PMCID: PMC6821808 DOI: 10.1038/s41467-019-12915-x] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 10/03/2019] [Indexed: 12/14/2022] Open
Abstract
Although brain functionality is often remarkably robust to lesions and other insults, it may be fragile when these take place in specific locations. Previous attempts to quantify robustness and fragility sought to understand how the functional connectivity of brain networks is affected by structural changes, using either model-based predictions or empirical studies of the effects of lesions. We advance a geometric viewpoint relying on a notion of network curvature, the so-called Ollivier-Ricci curvature. This approach has been proposed to assess financial market robustness and to differentiate biological networks of cancer cells from healthy ones. Here, we apply curvature-based measures to brain structural networks to identify robust and fragile brain regions in healthy subjects. We show that curvature can also be used to track changes in brain connectivity related to age and autism spectrum disorder (ASD), and we obtain results that are in agreement with previous MRI studies. The brain can often continue to function despite lesions in many areas, but damage to particular locations may have serious effects. Here, the authors use the concept of Ollivier-Ricci curvature to investigate the robustness of brain networks.
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Affiliation(s)
- Hamza Farooq
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA.
| | - Yongxin Chen
- School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Tryphon T Georgiou
- Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA
| | - Allen Tannenbaum
- Departments of Computer Science and Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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10
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Bayrak Ş, Khalil AA, Villringer K, Fiebach JB, Villringer A, Margulies DS, Ovadia-Caro S. The impact of ischemic stroke on connectivity gradients. Neuroimage Clin 2019; 24:101947. [PMID: 31376644 PMCID: PMC6676042 DOI: 10.1016/j.nicl.2019.101947] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 07/08/2019] [Accepted: 07/17/2019] [Indexed: 11/19/2022]
Abstract
The functional organization of the brain can be represented as a low-dimensional space that reflects its macroscale hierarchy. The dimensions of this space, described as connectivity gradients, capture the similarity of areas' connections along a continuous space. Studying how pathological perturbations with known effects on functional connectivity affect these connectivity gradients provides support for their biological relevance. Previous work has shown that localized lesions cause widespread functional connectivity alterations in structurally intact areas, affecting a network of interconnected regions. By using acute stroke as a model of the effects of focal lesions on the connectome, we apply the connectivity gradient framework to depict how functional reorganization occurs throughout the brain, unrestricted by traditional definitions of functional network boundaries. We define a three-dimensional connectivity space template based on functional connectivity data from healthy controls. By projecting lesion locations into this space, we demonstrate that ischemic strokes result in dimension-specific alterations in functional connectivity over the first week after symptom onset. Specifically, changes in functional connectivity were captured along connectivity Gradients 1 and 3. The degree of functional connectivity change was associated with the distance from the lesion along these connectivity gradients (a measure of functional similarity) regardless of the anatomical distance from the lesion. Together, these results provide support for the biological validity of connectivity gradients and suggest a novel framework to characterize connectivity alterations after stroke.
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Affiliation(s)
- Şeyma Bayrak
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany
| | - Ahmed A Khalil
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kersten Villringer
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jochen B Fiebach
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany; Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) UMR 7225, Frontlab, Institut du Cerveau et de la Moelle épinière, Paris, France.
| | - Smadar Ovadia-Caro
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Neurology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
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11
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Valero-Cabré A, Toba MN, Hilgetag CC, Rushmore RJ. Perturbation-driven paradoxical facilitation of visuo-spatial function: Revisiting the 'Sprague effect'. Cortex 2019; 122:10-39. [PMID: 30905382 DOI: 10.1016/j.cortex.2019.01.031] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 12/17/2018] [Accepted: 01/30/2019] [Indexed: 01/29/2023]
Abstract
The 'Sprague Effect' described in the seminal paper of James Sprague (Science 153:1544-1547, 1966a) is an unexpected paradoxical effect in which a second brain lesion reversed functional deficits induced by an earlier lesion. It was observed initially in the cat where severe and permanent contralateral visually guided attentional deficits generated by the ablation of large areas of the visual cortex were reversed by the subsequent removal of the superior colliculus (SC) opposite to the cortical lesion or by the splitting of the collicular commissure. Physiologically, this effect has been explained in several ways-most notably by the reduction of the functional inhibition of the ipsilateral SC by the contralateral SC, and the restoration of normal interactions between cortical and midbrain structures after ablation. In the present review, we aim at reappraising the 'Sprague Effect' by critically analyzing studies that have been conducted in the feline and human brain. Moreover, we assess applications of the 'Sprague Effect' in the rehabilitation of visually guided attentional impairments by using non-invasive therapeutic approaches such as transcranial magnetic stimulation (TMS) and transcranial direct-current stimulation (tDCS). We also review theoretical models of the effect that emphasize the inhibition and balancing between the two hemispheres and show implications for lesion inference approaches. Last, we critically review whether the resulting inter-hemispheric rivalry theories lead toward an efficient rehabilitation of stroke in humans. We conclude by emphasizing key challenges in the field of 'Sprague Effect' applications in order to design better therapies for brain-damaged patients.
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Affiliation(s)
- Antoni Valero-Cabré
- Cerebral Dynamics, Plasticity and Rehabilitation Group, Frontlab Team, Brain and Spine Institute, ICM, Paris, France; CNRS UMR 7225, Inserm UMR S 1127, Sorbonne Universités, UPMC Paris 06, F-75013, IHU-A-ICM, Paris, France; Laboratory for Cerebral Dynamics, Plasticity & Rehabilitation, Boston University School of Medicine, Boston, MA, USA.
| | - Monica N Toba
- Laboratory of Functional Neurosciences (EA 4559), University Hospital of Amiens and University of Picardy Jules Verne, Amiens, France
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany; Department of Health Sciences, Boston University, Boston, MA, USA
| | - R Jarrett Rushmore
- Laboratory for Cerebral Dynamics, Plasticity & Rehabilitation, Boston University School of Medicine, Boston, MA, USA.
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12
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Pagani E, Rocca MA, De Meo E, Horsfield MA, Colombo B, Rodegher M, Comi G, Filippi M. Structural connectivity in multiple sclerosis and modeling of disconnection. Mult Scler 2019; 26:220-232. [PMID: 30625050 DOI: 10.1177/1352458518820759] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is characterized by focal white matter damage, and when the brain is modeled as a network, lesions can be treated as disconnection events. OBJECTIVE To evaluate whether modeling disconnection caused by lesions helps explain motor and cognitive impairment in MS. METHODS Pathways connecting 116 cortical regions were reconstructed with magnetic resonance imaging (MRI) tractography from diffusion tensors averaged across healthy controls (HCs); maps of pathways were applied to 227 relapse-onset MS patients and 50 HCs to derive structural connectivity. Then, the likelihood of individual connections passing through lesions was used to model disconnection. Patients were grouped according to clinical phenotype (113 relapsing-remitting multiple sclerosis (RRMS), 69 secondary progressive multiple sclerosis (SPMS), 45 benign MS), and then network metrics were compared between groups (analysis of variance (ANOVA)) and correlated with motor and cognitive scores (linear regression). RESULTS Global metrics differentiated RRMS from SPMS and benign MS patients, but not benign from SPMS patients. Nodal connectivity strength replicated global results. After disconnection, few nodes were significantly different between benign MS and RRMS patients. Correlations revealed nodes pertinent to motor and cognitive dysfunctions; these became slightly stronger after disconnection. CONCLUSION Connectivity did not change greatly after modeled disconnection, suggesting that the brain network is robust against damage caused by MS lesions.
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Affiliation(s)
- Elisabetta Pagani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy/Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Ermelinda De Meo
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy/Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | | | - Bruno Colombo
- Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Mariaemma Rodegher
- Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Giancarlo Comi
- Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy/Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Plebe A. The search of "canonical" explanations for the cerebral cortex. HISTORY AND PHILOSOPHY OF THE LIFE SCIENCES 2018; 40:40. [PMID: 29905901 DOI: 10.1007/s40656-018-0205-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Accepted: 06/07/2018] [Indexed: 06/08/2023]
Abstract
This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be "canonical". This "canonical" core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr's theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop.
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Affiliation(s)
- Alessio Plebe
- Department of Cognitive Science, Università degli Studi di Messina, v. Concezione 8, Messina, Italy.
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14
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Xu T, Jha A, Nachev P. The dimensionalities of lesion-deficit mapping. Neuropsychologia 2017; 115:134-141. [PMID: 28935195 PMCID: PMC6018623 DOI: 10.1016/j.neuropsychologia.2017.09.007] [Citation(s) in RCA: 35] [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: 05/31/2017] [Revised: 08/09/2017] [Accepted: 09/07/2017] [Indexed: 11/18/2022]
Abstract
Lesion-deficit mapping remains the most powerful method for localising function in the human brain. As the highest court of appeal where competing theories of cerebral function conflict, it ought to be held to the most stringent inferential standards. Though at first sight elegantly transferable, the mass-univariate statistical framework popularized by functional imaging is demonstrably ill-suited to the task, both theoretically and empirically. The critical difficulty lies with the handling of the data's intrinsically high dimensionality. Conceptual opacity and computational complexity lead lesion-deficit mappers to neglect two distinct sets of anatomical interactions: those between areas unified by function, and those between areas unified by the natural pattern of pathological damage. Though both are soluble through high-dimensional multivariate analysis, the consequences of ignoring them are radically different. The former will bleach and coarsen a picture of the functional anatomy that is nonetheless broadly faithful to reality; the latter may alter it beyond all recognition. That the field continues to cling to mass-univariate methods suggests the latter problem is misidentified with the former, and that their distinction is in need of elaboration. We further argue that the vicious effects of lesion-driven interactions are not limited to anatomical localisation but will inevitably degrade purely predictive models of function such as those conceived for clinical prognostic use. Finally, we suggest there is a great deal to be learnt about lesion-mapping by simulation-based modelling of lesion data, for the fundamental problems lie upstream of the experimental data themselves.
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Affiliation(s)
| | - Ashwani Jha
- Institute of Neurology, UCL, UK; National Hospital for Neurology and Neurosurgery, Queen Square, UK
| | - Parashkev Nachev
- Institute of Neurology, UCL, UK; National Hospital for Neurology and Neurosurgery, Queen Square, UK.
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15
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Aerts H, Fias W, Caeyenberghs K, Marinazzo D. Brain networks under attack: robustness properties and the impact of lesions. Brain 2016; 139:3063-3083. [PMID: 27497487 DOI: 10.1093/brain/aww194] [Citation(s) in RCA: 178] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Revised: 05/13/2016] [Accepted: 06/08/2016] [Indexed: 12/30/2022] Open
Abstract
A growing number of studies approach the brain as a complex network, the so-called 'connectome'. Adopting this framework, we examine what types or extent of damage the brain can withstand-referred to as network 'robustness'-and conversely, which kind of distortions can be expected after brain lesions. To this end, we review computational lesion studies and empirical studies investigating network alterations in brain tumour, stroke and traumatic brain injury patients. Common to these three types of focal injury is that there is no unequivocal relationship between the anatomical lesion site and its topological characteristics within the brain network. Furthermore, large-scale network effects of these focal lesions are compared to those of a widely studied multifocal neurodegenerative disorder, Alzheimer's disease, in which central parts of the connectome are preferentially affected. Results indicate that human brain networks are remarkably resilient to different types of lesions, compared to other types of complex networks such as random or scale-free networks. However, lesion effects have been found to depend critically on the topological position of the lesion. In particular, damage to network hub regions-and especially those connecting different subnetworks-was found to cause the largest disturbances in network organization. Regardless of lesion location, evidence from empirical and computational lesion studies shows that lesions cause significant alterations in global network topology. The direction of these changes though remains to be elucidated. Encouragingly, both empirical and modelling studies have indicated that after focal damage, the connectome carries the potential to recover at least to some extent, with normalization of graph metrics being related to improved behavioural and cognitive functioning. To conclude, we highlight possible clinical implications of these findings, point out several methodological limitations that pertain to the study of brain diseases adopting a network approach, and provide suggestions for future research.
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Affiliation(s)
- Hannelore Aerts
- 1 Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Belgium
| | - Wim Fias
- 2 Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Belgium
| | - Karen Caeyenberghs
- 3 School of Psychology, Faculty of Health Sciences, Australian Catholic University, Australia
| | - Daniele Marinazzo
- 1 Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Belgium
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16
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Zavaglia M, Forkert ND, Cheng B, Gerloff C, Thomalla G, Hilgetag CC. Technical considerations of a game-theoretical approach for lesion symptom mapping. BMC Neurosci 2016; 17:40. [PMID: 27349961 PMCID: PMC4924231 DOI: 10.1186/s12868-016-0275-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 06/15/2016] [Indexed: 08/27/2023] Open
Abstract
Background Various strategies have been used for inferring brain functions from stroke lesions. We explored a new mathematical approach based on game theory, the so-called multi-perturbation Shapley value analysis (MSA), to assess causal function localizations and interactions from multiple perturbation data. We applied MSA to a dataset composed of lesion patterns of 148 acute stroke patients and their National Institutes of Health Stroke Scale (NIHSS) scores, to systematically investigate the influence of different parameter settings on the outcomes of the approach. Specifically, we investigated aspects of MSA methodology including the choice of the predictor algorithm (typology and kernel functions), training dataset (original versus binary), as well as the influence of lesion thresholds. We assessed the suitability of MSA for processing real clinical lesion data and established the central parameters for this analysis. Results We derived general recommendations for the analysis of clinical datasets by MSA and showed that, for the studied dataset, the best approach was to use a linear-kernel support vector machine predictor, trained with a binary training dataset, where the binarization was implemented through a median threshold of lesion size for each region. We demonstrated that the results obtained with different MSA variants lead to almost identical results as the basic MSA. Conclusions MSA is a feasible approach for the multivariate lesion analysis of clinical stroke data. Informed choices need to be made to set parameters that may affect the analysis outcome.
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Affiliation(s)
- Melissa Zavaglia
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany. .,School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, 28759, Bremen, Germany.
| | - Nils D Forkert
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany.,Department of Radiology and Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 4N1, Canada
| | - Bastian Cheng
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany
| | - Claus C Hilgetag
- Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, 20246, Hamburg, Germany.,Department of Health Sciences, Boston University, 635 Commonwealth Ave., Boston, MA, 02215, USA
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17
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Eickhoff SB, Thirion B, Varoquaux G, Bzdok D. Connectivity-based parcellation: Critique and implications. Hum Brain Mapp 2015; 36:4771-92. [PMID: 26409749 DOI: 10.1002/hbm.22933] [Citation(s) in RCA: 192] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2015] [Revised: 07/22/2015] [Accepted: 07/30/2015] [Indexed: 12/13/2022] Open
Abstract
Regional specialization and functional integration are often viewed as two fundamental principles of human brain organization. They are closely intertwined because each functionally specialized brain region is probably characterized by a distinct set of long-range connections. This notion has prompted the quickly developing family of connectivity-based parcellation (CBP) methods in neuroimaging research. CBP assumes that there is a latent structure of parcels in a region of interest (ROI). First, connectivity strengths are computed to other parts of the brain for each voxel/vertex within the ROI. These features are then used to identify functionally distinct groups of ROI voxels/vertices. CBP enjoys increasing popularity for the in-vivo mapping of regional specialization in the human brain. Due to the requirements of different applications and datasets, CBP has diverged into a heterogeneous family of methods. This broad overview critically discusses the current state as well as the commonalities and idiosyncrasies of the main CBP methods. We target frequent concerns faced by novices and veterans to provide a reference for the investigation and review of CBP studies.
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Affiliation(s)
- Simon B Eickhoff
- Institut Für Neurowissenschaften Und Medizin (INM-1), Forschungszentrum Jülich GmbH, Jülich, 52425, Germany.,Institut Für Klinische Neurowissenschaften Und Medizinische Psychologie, Heinrich-Heine Universität Düsseldorf, Düsseldorf, 40225, Germany
| | - Bertrand Thirion
- Parietal Team, INRIA, Neurospin, Bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France
| | - Gaël Varoquaux
- Parietal Team, INRIA, Neurospin, Bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France
| | - Danilo Bzdok
- Institut Für Neurowissenschaften Und Medizin (INM-1), Forschungszentrum Jülich GmbH, Jülich, 52425, Germany.,Institut Für Klinische Neurowissenschaften Und Medizinische Psychologie, Heinrich-Heine Universität Düsseldorf, Düsseldorf, 40225, Germany.,Parietal Team, INRIA, Neurospin, Bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France.,Department of Psychiatry, Psychotherapy and Psychosomatics, Uniklinik RWTH, 52074, Aachen, Germany
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18
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Causal functional contributions and interactions in the attention network of the brain: an objective multi-perturbation analysis. Brain Struct Funct 2015; 221:2553-68. [PMID: 26002616 DOI: 10.1007/s00429-015-1058-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2014] [Accepted: 05/06/2015] [Indexed: 10/23/2022]
Abstract
Spatial attention is a prime example for the distributed network functions of the brain. Lesion studies in animal models have been used to investigate intact attentional mechanisms as well as perspectives for rehabilitation in the injured brain. Here, we systematically analyzed behavioral data from cooling deactivation and permanent lesion experiments in the cat, where unilateral deactivation of the posterior parietal cortex (in the vicinity of the posterior middle suprasylvian cortex, pMS) or the superior colliculus (SC) cause a severe neglect in the contralateral hemifield. Counterintuitively, additional deactivation of structures in the opposite hemisphere reverses the deficit. Using such lesion data, we employed a game-theoretical approach, multi-perturbation Shapley value analysis (MSA), for inferring functional contributions and network interactions of bilateral pMS and SC from behavioral performance in visual attention studies. The approach provides an objective theoretical strategy for lesion inferences and allows a unique quantitative characterization of regional functional contributions and interactions on the basis of multi-perturbations. The quantitative analysis demonstrated that right posterior parietal cortex and superior colliculus made the strongest positive contributions to left-field orienting, while left brain regions had negative contributions, implying that their perturbation may reverse the effects of contralateral lesions or improve normal function. An analysis of functional modulations and interactions among the regions revealed redundant interactions (implying functional overlap) between regions within each hemisphere, and synergistic interactions between bilateral regions. To assess the reliability of the MSA method in the face of variable and incomplete input data, we performed a sensitivity analysis, investigating how much the contribution values of the four regions depended on the performance of specific configurations and on the prediction of unknown performances. The results suggest that the MSA approach is sensitive to categorical, but insensitive to gradual changes in the input data. Finally, we created a basic network model that was based on the known anatomical interactions among cortical-tectal regions and reproduced the experimentally observed behavior in visual orienting. We discuss the structural organization of the network model relative to the causal modulations identified by MSA, to aid a mechanistic understanding of the attention network of the brain.
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19
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Hilgetag CC, von Luxburg U. Brain network science needs to become predictive. Phys Life Rev 2014; 11:446-7. [DOI: 10.1016/j.plrev.2014.07.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Accepted: 07/02/2014] [Indexed: 11/30/2022]
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20
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Charidimou A, Kasselimis D, Varkanitsa M, Selai C, Potagas C, Evdokimidis I. Why is it difficult to predict language impairment and outcome in patients with aphasia after stroke? J Clin Neurol 2014; 10:75-83. [PMID: 24829592 PMCID: PMC4017023 DOI: 10.3988/jcn.2014.10.2.75] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2012] [Revised: 11/26/2013] [Accepted: 11/27/2013] [Indexed: 12/12/2022] Open
Abstract
One of the most devastating consequences of stroke is aphasia. Communication problems after stroke can severely impair the patient's quality of life and make even simple everyday tasks challenging. Despite intense research in the field of aphasiology, the type of language impairment has not yet been localized and correlated with brain damage, making it difficult to predict the language outcome for stroke patients with aphasia. Our primary objective is to present the available evidence that highlights the difficulties of predicting language impairment after stroke. The different levels of complexity involved in predicting the lesion site from language impairment and ultimately predicting the long-term outcome in stroke patients with aphasia were explored. Future directions and potential implications for research and clinical practice are highlighted.
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Affiliation(s)
- Andreas Charidimou
- Stroke Research Group, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Dimitrios Kasselimis
- Department of Psychology, University of Crete, Rethymno, Greece
- Department of Neurology, Medical School, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece
| | - Maria Varkanitsa
- Division of Psychology and Language Sciences, Department of Linguistics, University College London (UCL), London, UK
| | - Caroline Selai
- Institute of Neurology, The National Hospital for Neurology and Neurosurgery, University College London (UCL), London, UK
| | - Constantin Potagas
- Department of Neurology, Medical School, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece
| | - Ioannis Evdokimidis
- Department of Neurology, Medical School, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece
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21
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Comparative analysis of the macroscale structural connectivity in the macaque and human brain. PLoS Comput Biol 2014; 10:e1003529. [PMID: 24676052 PMCID: PMC3967942 DOI: 10.1371/journal.pcbi.1003529] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2013] [Accepted: 02/07/2014] [Indexed: 01/29/2023] Open
Abstract
The macaque brain serves as a model for the human brain, but its suitability is challenged by unique human features, including connectivity reconfigurations, which emerged during primate evolution. We perform a quantitative comparative analysis of the whole brain macroscale structural connectivity of the two species. Our findings suggest that the human and macaque brain as a whole are similarly wired. A region-wise analysis reveals many interspecies similarities of connectivity patterns, but also lack thereof, primarily involving cingulate regions. We unravel a common structural backbone in both species involving a highly overlapping set of regions. This structural backbone, important for mediating information across the brain, seems to constitute a feature of the primate brain persevering evolution. Our findings illustrate novel evolutionary aspects at the macroscale connectivity level and offer a quantitative translational bridge between macaque and human research. What are the commonalities and differences of human brains when compared to the brains of other primates? The brain can be conceived as a complex network. Its topological properties constrain its function. Ethical and technical reasons necessitate the use of animal brains, like the macaque monkey, as models for the human brain. However, evolutionary changes, including “brain rewiring”, might result in unique human features. Hence, a detailed and quantitative comparative analysis of the connectivity of the brains of the two species is needed. Here, we undertake this task by adopting techniques analogous to those used in comparative studies in other scientific fields. Our approach reveals converging but also diverging wiring patterns. The brain of the two species as a whole is similarly wired. The majority of the brain regions appear to have evolutionary conserved connectivity patterns while for certain regions this appears not to be the case. We also uncover an evolutionary conserved “structural backbone” in the brain of the two species. Our findings highlight common and unique “wiring properties” of the brains of these two primate species and offer a quantitative basis for translating findings from macaque research to human research.
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22
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Fama R, Sullivan EV. Methods of association and dissociation for establishing selective brain-behavior relations. HANDBOOK OF CLINICAL NEUROLOGY 2014; 125:175-81. [PMID: 25307575 PMCID: PMC11095316 DOI: 10.1016/b978-0-444-62619-6.00011-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Methods for identifying and understanding brain structure-function relations have evolved over the past century, from astute observations of selective impairments associated with focal brain damage to dissociations measured by combining quantitative neuropsychologic assessment and brain imaging. Enhanced spatial and temporal resolution in brain imaging modalities has led to refined visualization and quantification of the brain's substructures, microstructural integrity, and functional connectivity of neural networks. The double dissociation model has been a gold standard used to demonstrate that a particular cognitive, emotional, sensory, or motor process is selectively related to a particular brain region or neural network and not to others. This model has provided a fruitful means for testing hypotheses of functional localization and enabled examination and establishment of component processes contributing to complex cognitive and motor functions, parsing multifactorial behaviors and identifying brain regions, and networks subserving these complex abilities. In this chapter we discuss the evolution of the dissociation model and highlight how the modifications of this model are used presently to establish selective brain-behavior relationships in disorders such as chronic alcoholism with a neuropathologic signature but no localizable, space-occupying lesion.
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Affiliation(s)
- Rosemary Fama
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA; Neuroscience Program, SRI International, Menlo Park, CA, USA.
| | - Edith V Sullivan
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
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23
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Tuladhar AM, Snaphaan L, Shumskaya E, Rijpkema M, Fernandez G, Norris DG, de Leeuw FE. Default Mode Network Connectivity in Stroke Patients. PLoS One 2013; 8:e66556. [PMID: 23824302 PMCID: PMC3688936 DOI: 10.1371/journal.pone.0066556] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Accepted: 05/10/2013] [Indexed: 11/18/2022] Open
Abstract
The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 ‘first-ever’ stroke patients. Patients were scanned 9–12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in ‘first-ever’ stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.
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Affiliation(s)
- Anil Man Tuladhar
- Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Centre for Neuroscience, Nijmegen, The Netherlands
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Liselore Snaphaan
- Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Centre for Neuroscience, Nijmegen, The Netherlands
| | - Elena Shumskaya
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognition, Nijmegen, The Netherlands
| | - Mark Rijpkema
- Department of Nuclear Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Guillén Fernandez
- Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Centre for Neuroscience, Nijmegen, The Netherlands
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - David G. Norris
- Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Centre for Neuroscience, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
- MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Centre for Neuroscience, Nijmegen, The Netherlands
- * E-mail:
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Manjaly ZM, Marshall JC, Stephan KE, Gurd JM, Zilles K, Fink GR. Context-dependent interactions of left posterior inferior frontal gyrus in a local visual search task unrelated to language. Cogn Neuropsychol 2012; 22:292-305. [PMID: 21038251 DOI: 10.1080/02643290442000149] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The Embedded Figures Task (EFT) involves search for a target hidden in a complex geometric pattern. Even though the EFT is designed to probe local visual search functions, not language-related processes, neuropsychological studies have demonstrated a strong association between aphasia and impairment on this task. A potential explanation for this relationship was offered by a recent functional MRI study (Manjaly et al., 2003), which demonstrated that a part of the left posterior inferior frontal gyrus (pIFG), overlapping with Broca's region, is crucially involved in the execution of the EFT. This result suggested that pIFG, an area strongly associated with language-related functions, is also part of a network subserving cognitive functions unrelated to language. In this study, we tested this conjecture by analysing the data of Manjaly et al. for context-dependent functional interactions of the pIFG during execution of the EFT. The results showed that during EFT, compared to a similar visual matching task with minimal local search components, pIFG changed its interactions with areas commonly involved in visuospatial processing: Increased contributions to neural activity in left posterior parietal cortex, cerebellar vermis, and extrastriate areas bilaterally, as well as decreased contributions to bilateral temporo-parietal cortex, posterior cingulate cortex, and left dorsal premotor cortex were found. These findings demonstrate that left pIFG can be involved in nonlanguage processes. More generally, however, they provide a concrete example of the notion that there is no general one-to-one mapping between cognitive functions and the activations of individual areas. Instead, it is the spatiotemporal pattern of functional interactions between areas that is linked to a particular cognitive context.
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Crinion J, Holland AL, Copland DA, Thompson CK, Hillis AE. Neuroimaging in aphasia treatment research: quantifying brain lesions after stroke. Neuroimage 2012; 73:208-14. [PMID: 22846659 DOI: 10.1016/j.neuroimage.2012.07.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Revised: 06/20/2012] [Accepted: 07/22/2012] [Indexed: 10/28/2022] Open
Abstract
New structural and functional neuroimaging methods continue to rapidly develop, offering promising tools for cognitive neuroscientists. In the last 20 years, advanced magnetic resonance imaging (MRI) techniques have provided invaluable insights into how language is represented and processed in the brain and how it can be disrupted by damage to, or dysfunction of, various parts of the brain. Current functional MRI (fMRI) approaches have also allowed researchers to purposefully investigate how individuals recover language after stroke. This paper presents recommendations for quantification of brain lesions derived from discussions among international researchers at the Neuroimaging in Aphasia Treatment Research Workshop held at Northwestern University (Evanston, Illinois, USA). Methods for detailing and characterizing the brain damage that can influence results of fMRI studies in chronic aphasic stroke patients are discussed. Moreover, we aimed to provide the reader with a set of general practical guidelines and references to facilitate choosing adequate structural imaging strategies that facilitate fMRI studies in aphasia treatment research.
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Affiliation(s)
- Jenny Crinion
- University College London, Institute of Cognitive Neuroscience, London, UK.
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Gratton C, Nomura EM, Pérez F, D'Esposito M. Focal brain lesions to critical locations cause widespread disruption of the modular organization of the brain. J Cogn Neurosci 2012; 24:1275-85. [PMID: 22401285 DOI: 10.1162/jocn_a_00222] [Citation(s) in RCA: 240] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Although it is generally assumed that brain damage predominantly affects only the function of the damaged region, here we show that focal damage to critical locations causes disruption of network organization throughout the brain. Using resting state fMRI, we assessed whole-brain network structure in patients with focal brain lesions. Only damage to those brain regions important for communication between subnetworks (e.g., "connectors")--but not to those brain regions important for communication within sub-networks (e.g., "hubs")--led to decreases in modularity, a measure of the integrity of network organization. Critically, this network dysfunction extended into the structurally intact hemisphere. Thus, focal brain damage can have a widespread, nonlocal impact on brain network organization when there is damage to regions important for the communication between networks. These findings fundamentally revise our understanding of the remote effects of focal brain damage and may explain numerous puzzling cases of functional deficits that are observed following brain injury.
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Schoo LA, van Zandvoort MJE, Biessels GJ, Kappelle LJ, Postma A, de Haan EHF. The posterior parietal paradox: Why do functional magnetic resonance imaging and lesion studies on episodic memory produce conflicting results? J Neuropsychol 2011; 5:15-38. [DOI: 10.1348/174866410x504059] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Price CJ, Seghier ML, Leff AP. Predicting language outcome and recovery after stroke: the PLORAS system. Nat Rev Neurol 2010; 6:202-10. [PMID: 20212513 PMCID: PMC3556582 DOI: 10.1038/nrneurol.2010.15] [Citation(s) in RCA: 112] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The ability to comprehend and produce speech after stroke depends on whether the areas of the brain that support language have been damaged. Here, we review two different ways to predict language outcome after stroke. The first depends on understanding the neural circuits that support language. This model-based approach is a challenging endeavor because language is a complex cognitive function that involves the interaction of many different brain areas. The second approach, by contrast, does not require an understanding of why a lesion impairs language; instead, predictions are made on the basis of the recovery of previous patients with the same lesion. This approach requires a database that records the speech and language capabilities of a large population of patients who have, collectively, incurred a comprehensive range of focal brain lesions. In addition, a system is required that converts an MRI scan from a new patient into a three-dimensional description of the lesion and compares this lesion against all others on the database. The outputs of this system are the longitudinal language outcomes of corresponding patients in the database. This approach will provide the patient with a range of probable recovery patterns over a variety of language measures.
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Affiliation(s)
- Cathy J Price
- Wellcome Trust Center for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK.
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Zamora-López G, Zhou C, Kurths J. Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks. Front Neuroinform 2010; 4:1. [PMID: 20428515 PMCID: PMC2859882 DOI: 10.3389/neuro.11.001.2010] [Citation(s) in RCA: 128] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2009] [Accepted: 02/02/2010] [Indexed: 01/21/2023] Open
Abstract
Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated) from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration). The corticocortical networks of cats and macaque monkeys display three prominent characteristics: (i) modular organisation (facilitating the segregation), (ii) abundant alternative processing paths and (iii) the presence of highly connected hubs. Here, we study in detail the organisation and potential function of the cortical hubs by graph analysis and information theoretical methods. We find that the cortical hubs form a spatially delocalised, but topologically central module with the capacity to integrate multisensory information in a collaborative manner. With this, we resolve the underlying anatomical substrate that supports the simultaneous capacity of the cortex to segregate and to integrate multisensory information.
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Affiliation(s)
- Gorka Zamora-López
- Interdisciplinary Center for Dynamics of Complex Systems, University of Potsdam Potsdam, Germany
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Honey CJ, Thivierge JP, Sporns O. Can structure predict function in the human brain? Neuroimage 2010; 52:766-76. [PMID: 20116438 DOI: 10.1016/j.neuroimage.2010.01.071] [Citation(s) in RCA: 413] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2009] [Revised: 01/17/2010] [Accepted: 01/21/2010] [Indexed: 01/07/2023] Open
Abstract
Over the past decade, scientific interest in the properties of large-scale spontaneous neural dynamics has intensified. Concurrently, novel technologies have been developed for characterizing the connective anatomy of intra-regional circuits and inter-regional fiber pathways. It will soon be possible to build computational models that incorporate these newly detailed structural network measurements to make predictions of neural dynamics at multiple scales. Here, we review the practicality and the value of these efforts, while at the same time considering in which cases and to what extent structure does determine neural function. Studies of the healthy brain, of neural development, and of pathology all yield examples of direct correspondences between structural linkage and dynamical correlation. Theoretical arguments further support the notion that brain network topology and spatial embedding should strongly influence network dynamics. Although future models will need to be tested more quantitatively and against a wider range of empirical neurodynamic features, our present large-scale models can already predict the macroscopic pattern of dynamic correlation across the brain. We conclude that as neuroscience grapples with datasets of increasing completeness and complexity, and attempts to relate the structural and functional architectures discovered at different neural scales, the value of computational modeling will continue to grow.
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Alstott J, Breakspear M, Hagmann P, Cammoun L, Sporns O. Modeling the impact of lesions in the human brain. PLoS Comput Biol 2009; 5:e1000408. [PMID: 19521503 PMCID: PMC2688028 DOI: 10.1371/journal.pcbi.1000408] [Citation(s) in RCA: 391] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2009] [Accepted: 05/06/2009] [Indexed: 11/19/2022] Open
Abstract
Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.
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Affiliation(s)
- Jeffrey Alstott
- Program in Cognitive Science, Indiana University, Bloomington, Indiana,
United States of America
| | - Michael Breakspear
- Queensland Institute of Medical Research, Brisbane, Australia
- Royal Brisbane and Women's Hospital, Brisbane,
Australia
- School of Psychiatry, University of South Wales, Sydney,
Australia
- The Black Dog Institute, Sydney, Australia
| | - Patric Hagmann
- Signal Processing Laboratory 5, Ecole Polytechnique
Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, University Hospital Center, University of
Lausanne, Lausanne, Switzerland
| | - Leila Cammoun
- Signal Processing Laboratory 5, Ecole Polytechnique
Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, University Hospital Center, University of
Lausanne, Lausanne, Switzerland
| | - Olaf Sporns
- Program in Cognitive Science, Indiana University, Bloomington, Indiana,
United States of America
- Department of Psychological and Brain Sciences, Indiana University,
Bloomington, Indiana, United States of America
- * E-mail:
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Müller-Linow M, Hilgetag CC, Hütt MT. Organization of excitable dynamics in hierarchical biological networks. PLoS Comput Biol 2008; 4:e1000190. [PMID: 18818769 PMCID: PMC2542420 DOI: 10.1371/journal.pcbi.1000190] [Citation(s) in RCA: 111] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2008] [Accepted: 08/20/2008] [Indexed: 11/25/2022] Open
Abstract
This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.
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Affiliation(s)
- Mark Müller-Linow
- Department of Biology, Bioinformatics Group, Darmstadt University of Technology, Darmstadt, Germany.
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Abstract
To understand the effects of a cortical lesion it is necessary to consider not only the loss of local neural function, but also the lesion-induced changes in the larger network of endogenous oscillatory interactions in the brain. To investigate how network embedding influences a region's functional role, and the consequences of its being damaged, we implement two models of oscillatory cortical interactions, both of which inherit their coupling architecture from the available anatomical connection data for macaque cerebral cortex. In the first model, node dynamics are governed by Kuramoto phase oscillator equations, and we investigate the sequence in which areas entrain one another in the transition to global synchrony. In the second model, node dynamics are governed by a more realistic neural mass model, and we assess long-run inter-regional interactions using a measure of directed information flow. Highly connected parietal and frontal areas are found to synchronize most rapidly, more so than equally highly connected visual and somatosensory areas, and this difference can be explained in terms of the network's clustered architecture. For both models, lesion effects extend beyond the immediate neighbors of the lesioned site, and the amplitude and dispersal of nonlocal effects are again influenced by cluster patterns in the network. Although the consequences of in vivo lesions will always depend on circuitry local to the damaged site, we conclude that lesions of parietal regions (especially areas 5 and 7a) and frontal regions (especially areas 46 and FEF) have the greatest potential to disrupt the integrative aspects of neocortical function.
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Affiliation(s)
- Christopher J Honey
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana 47405, USA
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35
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Imaging causal interactions during sensorimotor processing. Cortex 2008; 44:598-608. [DOI: 10.1016/j.cortex.2007.08.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2007] [Revised: 08/09/2007] [Accepted: 08/09/2007] [Indexed: 11/20/2022]
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Abstract
The current view of brain organization supports the notion that there is a considerable degree of functional specialization and that many regions can be conceptualized as either 'affective' or 'cognitive'. Popular examples are the amygdala in the domain of emotion and the lateral prefrontal cortex in the case of cognition. This prevalent view is problematic for a number of reasons. Here, I will argue that complex cognitive-emotional behaviours have their basis in dynamic coalitions of networks of brain areas, none of which should be conceptualized as specifically affective or cognitive. Central to cognitive-emotional interactions are brain areas with a high degree of connectivity, called hubs, which are critical for regulating the flow and integration of information between regions.
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Affiliation(s)
- Luiz Pessoa
- Department of Psychological and Brain Sciences, and Programs in Neuroscience and Cognitive Science, Indiana University, Bloomington, Indiana 47405, USA.
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37
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de Lange FP, Roelofs K, Toni I. Motor imagery: a window into the mechanisms and alterations of the motor system. Cortex 2007; 44:494-506. [PMID: 18387583 DOI: 10.1016/j.cortex.2007.09.002] [Citation(s) in RCA: 130] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2007] [Revised: 07/05/2007] [Accepted: 09/18/2007] [Indexed: 11/25/2022]
Abstract
Motor imagery is a widely used paradigm for the study of cognitive aspects of action control, both in the healthy and the pathological brain. In this paper we review how motor imagery research has advanced our knowledge of behavioral and neural aspects of action control, both in healthy subjects and clinical populations. Furthermore, we will illustrate how motor imagery can provide new insights in a poorly understood psychopathological condition: conversion paralysis (CP). We measured behavioral and cerebral responses with functional magnetic resonance imaging (fMRI) in seven CP patients with a lateralized paresis of the arm as they imagined moving the affected or the unaffected hand. Imagined actions were either implicitly induced by the task requirements, or explicitly instructed through verbal instructions. We previously showed that implicitly induced motor imagery of the affected limb leads to larger ventromedial prefrontal responses compared to motor imagery of the unaffected limb. We interpreted this effect in terms of greater self-monitoring of actions during motor imagery of the affected limb. Here, we report new data in support of this interpretation: inducing self-monitoring of actions of both the affected and the unaffected limb (by means of explicitly cued motor imagery) abolishes the activation difference between the affected and the unaffected hand in the ventromedial prefrontal cortex. Our results show that although implicit and explicit motor imagery both entail motor simulations, they differ in terms of the amount of action monitoring they induce. The increased self-monitoring evoked by explicit motor imagery can have profound cerebral consequences in a psychopathological condition.
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Affiliation(s)
- Floris P de Lange
- F.C. Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, Netherlands.
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Stephan KE, Fink GR, Marshall JC. Mechanisms of hemispheric specialization: insights from analyses of connectivity. Neuropsychologia 2006; 45:209-28. [PMID: 16949111 PMCID: PMC2638113 DOI: 10.1016/j.neuropsychologia.2006.07.002] [Citation(s) in RCA: 69] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2006] [Revised: 07/04/2006] [Accepted: 07/06/2006] [Indexed: 12/02/2022]
Abstract
Traditionally, anatomical and physiological descriptions of hemispheric specialization have focused on hemispheric asymmetries of local brain structure or local functional properties, respectively. This article reviews the current state of an alternative approach that aims at unraveling the causes and functional principles of hemispheric specialization in terms of asymmetries in connectivity. Starting with an overview of the historical origins of the concept of lateralization, we briefly review recent evidence from anatomical and developmental studies that asymmetries in structural connectivity may be a critical factor shaping hemispheric specialization. These differences in anatomical connectivity, which are found both at the intra- and inter-regional level, are likely to form the structural substrate of different functional principles of information processing in the two hemispheres. The main goal of this article is to describe how these functional principles can be characterized using functional neuroimaging in combination with models of functional and effective connectivity. We discuss the methodology of established models of connectivity which are applicable to data from positron emission tomography and functional magnetic resonance imaging and review published studies that have applied these approaches to characterize asymmetries of connectivity during lateralized tasks. Adopting a model-based approach enables functional imaging to proceed from mere descriptions of asymmetric activation patterns to mechanistic accounts of how these asymmetries are caused.
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Affiliation(s)
- Klaas Enno Stephan
- Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College London, 12 Queen Square, London, UK.
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40
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Kleinschmidt A, Cohen L. The neural bases of prosopagnosia and pure alexia: recent insights from functional neuroimaging. Curr Opin Neurol 2006; 19:386-91. [PMID: 16914978 DOI: 10.1097/01.wco.0000236619.89710.ee] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW To discuss whether recent functional neuroimaging results can account for clinical phenomenology in visual associative agnosias. RECENT FINDINGS Functional neuroimaging studies in healthy human subjects have identified only two regions of ventral occipitotemporal cortex that invariantly respond to individual faces and visual words, respectively. The signature of face identity coding in the fusiform neural response was shown to be missing in a patient with prosopagnosia. Another case study established that a surgical lesion close to the region sensitive to visual words can result in pure alexia. SUMMARY Evidence is increasing that functional specialization for processing face identity and visual word forms is restricted to two specialized sensory modules in the occipitotemporal cortex. A structural or functional lesion to face-sensitive and word-sensitive regions in the ventral occipitotemporal cortex can provide the most parsimonious account for the clinical syndromes of prosopagnosia and agnosic alexia. This review suggests that functional specialization should be considered in terms of whether exclusively one brain region (instead of many) underpins a defined function and not as whether this brain region underpins exclusively one cognitive function. Such functional specialization seems to exist for at least two higher-order visual perceptual functions, face and word identification.
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Affiliation(s)
- Andreas Kleinschmidt
- Institut National de la Santé et de la Recherche Médicale, Unit 562, Service Hospitalier Frederic Joliot CEA, Orsay, France.
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41
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Bressler SL, Tognoli E. Operational principles of neurocognitive networks. Int J Psychophysiol 2006; 60:139-48. [PMID: 16490271 DOI: 10.1016/j.ijpsycho.2005.12.008] [Citation(s) in RCA: 143] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2005] [Revised: 12/23/2005] [Accepted: 12/23/2005] [Indexed: 10/25/2022]
Abstract
Large-scale neural networks are thought to be an essential substrate for the implementation of cognitive function by the brain. If so, then a thorough understanding of cognition is not possible without knowledge of how the large-scale neural networks of cognition (neurocognitive networks) operate. Of necessity, such understanding requires insight into structural, functional, and dynamical aspects of network operation, the intimate interweaving of which may be responsible for the intricacies of cognition. Knowledge of anatomical structure is basic to understanding how neurocognitive networks operate. Phylogenetically and ontogenetically determined patterns of synaptic connectivity form a structural network of brain areas, allowing communication between widely distributed collections of areas. The function of neurocognitive networks depends on selective activation of anatomically linked cortical and subcortical areas in a wide variety of configurations. Large-scale functional networks provide the cooperative processing which gives expression to cognitive function. The dynamics of neurocognitive network function relates to the evolving patterns of interacting brain areas that express cognitive function in real time. This article considers the proposition that a basic similarity of the structural, functional, and dynamical features of all neurocognitive networks in the brain causes them to function according to common operational principles. The formation of neural context through the coordinated mutual constraint of multiple interacting cortical areas, is considered as a guiding principle underlying all cognitive functions. Increasing knowledge of the operational principles of neurocognitive networks is likely to promote the advancement of cognitive theories, and to seed strategies for the enhancement of cognitive abilities.
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Affiliation(s)
- Steven L Bressler
- Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, USA.
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42
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Kronhaus DM, Willshaw DJ. The Cingulate as a Catalyst Region for Global Dysfunction: a Dynamical Modelling Paradigm. Cereb Cortex 2005; 16:1212-24. [PMID: 16251505 DOI: 10.1093/cercor/bhj062] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The anterior cingulate (AC) often exhibits both structural and functional abnormalities in affective disorders. Neither the cause for this vulnerability nor its effect on behaviour is known. Due to its extensive connectivity, minor output changes from the AC may exert widespread consequences. A causal model describing coupling coefficients (effective connectivity) among several brain regions in healthy subjects performing a memory task inspired our work. This stationary causal analysis provides a theoretical framework for our nonlinear dynamical models. We tested the effects of global and local perturbations upon stability of a systems-level neural network of interconnected brain regions. Interactions between regions, represented by path coefficients, were modelled using connectivity matrices. We found that both characteristic behaviour and response to perturbation differed in networks representing perceptual matching and long-delay conditions. Owing to the highly interconnected character of the networks, activation of a few areas was sufficient to trigger characteristic patterns of behaviour. However, only perturbation of key regions resulted in global dysfunction. Likewise, recovery of function was possible by increasing output from some, but not all, regions. We suggest for this recovery to be context specific, conditional on the task, integrity of other regions and global properties such as neuronal excitability.
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Affiliation(s)
- Dina M Kronhaus
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
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43
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Abstract
One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.
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Affiliation(s)
- Klaas Enno Stephan
- The Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College London, UK.
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Kötter R, Stephan KE. Network participation indices: characterizing component roles for information processing in neural networks. Neural Netw 2004; 16:1261-75. [PMID: 14622883 DOI: 10.1016/j.neunet.2003.06.002] [Citation(s) in RCA: 76] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
We propose a set of indices that characterize-on the basis of connectivity data-how a network node participates in a larger network and what roles it may take given the specific sub-network of interest. These Network Participation Indices are derived from simple graph theoretic measures and have the interesting property of linking local features of individual network components to distributed properties that arise within the network as a whole. We use connectivity data on large-scale cortical networks to demonstrate the virtues of this approach and highlight some interesting features that had not been brought up in previously published material. Some implications of our approach for defining network characteristics relevant to functional segregation and functional integration, for example, from functional imaging studies are discussed.
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Affiliation(s)
- Rolf Kötter
- Institute of Anatomy II and C & O Vogt Brain Research Institute, Heinrich Heine University, Moorenstrasse 5, D-40225 Düsseldorf, Germany.
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Abstract
We review some of the progress made in understanding the nature of functional specialization in the human brain, beginning with the anatomical claim that all mental faculties have their own distinct material substrate in different regions of the brain and the psychological claim that each mental faculty is characterized by the content domain with which it deals. This conceptual framework led behavioral neurologists to show how discrete brain lesions provoked different types of language, praxic, gnostic, spatial, and memory disorders. The simplest way of interpreting these anatomoclinical associations was to conjecture that the normal function (now impaired by brain damage) was localized within that lesioned region. It was also realized that cognitive impairments could arise from lesions that spared the functional centers themselves but disconnected them from other centers. Nonetheless, many neuroscientists remained skeptical of the entire paradigm. Accordingly, in the late 19th century functional localization began to be studied in the intact human brain by such techniques as measuring the temperature of different brain regions when different cognitive tasks were performed. During the 20th century these crude techniques gave way to positron emission tomography, functional magnetic resonance imaging, and magnetoencephalography. The relatively precise spatial and temporal resolution of modern methods now raises a crucial question: Do the functional localizations obtained by the anatomoclinical method converge with those implied by the functional neuroimaging of cognition in healthy volunteers? We then conclude with some recent suggestions that functional specialization is not such a fixed property of brain regions as previously supposed.
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Affiliation(s)
- John C Marshall
- University Department of Clinical Neurology, Radcliffe Infirmary, Oxford, UK.
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46
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Keinan A, Meilijson I, Ruppin E. Controlled analysis of neurocontrollers with informational lesioning. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2003; 361:2123-2144. [PMID: 14599312 DOI: 10.1098/rsta.2003.1253] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
How does one aim to understand neural information processing? One of the difficult first challenges is to identify the roles of the network's elements. To this end a functional contribution analysis (FCA) method has been developed and applied for studying the neurocontrollers of evolutionary autonomous agents (EAAs). The FCA processes data composed of multiple lesion experiments and the corresponding performance levels that the agent obtains under these lesions. It calculates the contribution values (CVs) of the network's elements such that the ability to predict the agent's performance under new, unseen lesions is maximized. Previous analysis has found a strong dependence of the CVs and the prediction error on the specific type of lesioning method used, i.e. on the way in which the activity of lesioned neurons is disrupted. We present a new, informational lesioning method (ILM), which views a lesion as a noisy channel and applies a controlled lesion to the network by varying the lesioning level from large to arbitrarily small magnitudes. Studying the ILM within the FCA framework, our main results are threefold: first, that lower lesioning levels permit more accurate FCA predictions; second, that the usage of minute ILM lesioning levels can uncover the long-term effects of elements on the network's functioning; and third, that as the lesioning level decreases, the CVs tend to approach limit values, reflecting the importance of these elements in the intact, normal-functioning neurocontroller.
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Affiliation(s)
- Alon Keinan
- School of Computer Sciences, Tel-Aviv University, Tel-Aviv, Israel.
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47
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Abstract
This article presents a general approach for employing lesion analysis to address the fundamental challenge of localizing functions in a neural system. We describe functional contribution analysis (FCA), which assigns contribution values to the elements of the network such that the ability to predict the network's performance in response to multilesions is maximized. The approach is thoroughly examined on neurocontroller networks of evolved autonomous agents. The FCA portrays a stable set of neuronal contributions and accurate multilesion predictions that are significantly better than those obtained based on the classical single lesion approach. It is also used for a detailed synaptic analysis of the neurocontroller connectivity network, delineating its main functional backbone. The FCA provides a quantitative way of measuring how the network functions are localized and distributed among its elements. Our results question the adequacy of the classical single lesion analysis traditionally used in neuroscience and show that using lesioning experiments to decipher even simple neuronal systems requires a more rigorous multilesion analysis.
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Affiliation(s)
- Ranit Aharonov
- Center for Neural Computation, Hebrew University, Jerusalem, Israel.
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Abstract
Despite great interest in the role of the amygdala in animal and human behaviour, its very existence as a structurally and functionally unified brain component has been questioned, on the grounds that cell groups within it display divergent pharmacological and connectional characteristics. We argue that the question of whether particular brain nuclei constitute a valid structural and functional unit is inherently an evolutionary question, and we present a method for answering it. The method involves phylogenetic analysis of comparative data to determine whether or not separate regions of the putative brain structure show statistically correlated evolution. We find that, in three separate groups of mammals (primates and two groups of insectivores), evolutionary changes in the volumes of amygdala components are strongly correlated, even after controlling for volumetric change in a wide range of limbic and other brain structures. This allows us to reject the strong claim that the amygdala is neither a structural nor a functional unit, and demonstrates the importance of evolutionary analysis in resolving such issues in systems neuroscience.
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Affiliation(s)
- Robert A Barton
- Evolutionary Anthropology Research Group, Department of Anthropology, University of Durham, Durham DH1 3HN, UK.
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Passingham RE, Stephan KE, Kötter R. The anatomical basis of functional localization in the cortex. Nat Rev Neurosci 2002; 3:606-16. [PMID: 12154362 DOI: 10.1038/nrn893] [Citation(s) in RCA: 667] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Richard E Passingham
- Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, UK.
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