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Seghier ML, Price CJ. Interpreting and validating complexity and causality in lesion-symptom prognoses. Brain Commun 2023; 5:fcad178. [PMID: 37346231 PMCID: PMC10279811 DOI: 10.1093/braincomms/fcad178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/08/2023] [Accepted: 06/04/2023] [Indexed: 06/23/2023] Open
Abstract
This paper considers the steps needed to generate pragmatic and interpretable lesion-symptom mappings that can be used for clinically reliable prognoses. The novel contributions are 3-fold. We first define and inter-relate five neurobiological and five methodological constraints that need to be accounted for when interpreting lesion-symptom associations and generating synthetic lesion data. The first implication is that, because of these constraints, lesion-symptom mapping needs to focus on probabilistic relationships between Lesion and Symptom, with Lesion as a multivariate spatial pattern, Symptom as a time-dependent behavioural profile and evidence that Lesion raises the probability of Symptom. The second implication is that in order to assess the strength of probabilistic causality, we need to distinguish between causal lesion sites, incidental lesion sites, spared but dysfunctional sites and intact sites, all of which might affect the accuracy of the predictions and prognoses generated. We then formulate lesion-symptom mappings in logical notations, including combinatorial rules, that are then used to evaluate and better understand complex brain-behaviour relationships. The logical and theoretical framework presented applies to any type of neurological disorder but is primarily discussed in relationship to stroke damage. Accommodating the identified constraints, we discuss how the 1965 Bradford Hill criteria for inferring probabilistic causality, post hoc, from observed correlations in epidemiology-can be applied to lesion-symptom mapping in stroke survivors. Finally, we propose that rather than rely on post hoc evaluation of how well the causality criteria have been met, the neurobiological and methodological constraints should be addressed, a priori, by changing the experimental design of lesion-symptom mappings and setting up an open platform to share and validate the discovery of reliable and accurate lesion rules that are clinically useful.
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Affiliation(s)
- Mohamed L Seghier
- Correspondence to: Mohamed Seghier Department of Biomedical Engineering Khalifa University of Science and Technology PO BOX: 127788, Abu Dhabi, UAE E-mail:
| | - Cathy J Price
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
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Mohan V, Parekh P, Lukose A, Moirangthem S, Saini J, Schretlen DJ, John JP. Patterns of Impaired Neurocognitive Performance on the Global Neuropsychological Assessment, and Their Brain Structural Correlates in Recent-onset and Chronic Schizophrenia. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2023; 21:340-358. [PMID: 37119227 PMCID: PMC10157005 DOI: 10.9758/cpn.2023.21.2.340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 09/19/2022] [Accepted: 10/12/2022] [Indexed: 05/01/2023]
Abstract
Objective Schizophrenia is associated with impairment in multiple cognitive domains. There is a paucity of research on the effect of prolonged illness duration (≥ 15 years) on cognitive performance along multiple domains. In this pilot study, we used the Global Neuropsychological Assessment (GNA), a brief cognitive battery, to explore the patterns of cognitive impairment in recent-onset (≤ 2 years) compared to chronic schizophrenia (≥ 15 years), and correlate cognitive performance with brain morphometry in patients and healthy adults. Methods We assessed cognitive performance in patients with recent-onset (n = 17, illness duration ≤ 2 years) and chronic schizophrenia (n = 14, duration ≥ 15 years), and healthy adults (n = 16) using the GNA and examined correlations between cognitive scores and gray matter volumes computed from T1-weighted magnetic resonance imaging images. Results We observed cognitive deficits affecting multiple domains in the schizophrenia samples. Selectively greater impairment of perceptual comparison speed was found in adults with chronic schizophrenia (p = 0.009, η2partial = 0.25). In the full sample (n = 47), perceptual comparison speed correlated significantly with gray matter volumes in the anterior and medial temporal lobes (TFCE, FWE p < 0.01). Conclusion Along with generalized deficit across multiple cognitive domains, selectively greater impairment of perceptual comparison speed appears to characterize chronic schizophrenia. This pattern might indicate an accelerated or premature cognitive aging. Anterior-medial temporal gray matter volumes especially of the left hemisphere might underlie the impairment noted in this domain in schizophrenia.
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Affiliation(s)
- Vineeth Mohan
- Multimodal Brain Image Analysis Laboratory (MBIAL), Bangalore, India
- Department of Clinical Neurosciences, Bangalore, India
| | - Pravesh Parekh
- Multimodal Brain Image Analysis Laboratory (MBIAL), Bangalore, India
- ADBS Neuroimaging Centre (ANC), Bangalore, India
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Ammu Lukose
- Multimodal Brain Image Analysis Laboratory (MBIAL), Bangalore, India
| | - Sydney Moirangthem
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - David J. Schretlen
- Department of Psychiatry and Behavioral Sciences, MD, USA
- Russel M. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - John P. John
- Multimodal Brain Image Analysis Laboratory (MBIAL), Bangalore, India
- ADBS Neuroimaging Centre (ANC), Bangalore, India
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
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Seghier ML. The elusive metric of lesion load. Brain Struct Funct 2023; 228:703-716. [PMID: 36947181 DOI: 10.1007/s00429-023-02630-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/15/2023] [Indexed: 03/23/2023]
Abstract
One of the widely used metrics in lesion-symptom mapping is lesion load that codes the amount of damage to a given brain region of interest. Lesion load aims to reduce the complex 3D lesion information into a feature that can reflect both site of damage, defined by the location of the region of interest, and size of damage within that region of interest. Basically, the process of estimation of lesion load converts a voxel-based lesion map into a region-based lesion map, with regions defined as atlas-based or data-driven spatial patterns. Here, after examining current definitions of lesion load, four methodological issues are discussed: (1) lesion load is agnostic to the location of damage within the region of interest, and it disregards damage outside the region of interest, (2) lesion load estimates are prone to errors introduced by the uncertainty in lesion delineation, spatial warping of the lesion/region, and binarization of the lesion/region, (3) lesion load calculation depends on brain parcellation selection, and (4) lesion load does not necessarily reflect a white matter disconnection. Overall, lesion load, when calculated in a robust way, can serve as a clinically-useful feature for explaining and predicting post-stroke outcome and recovery.
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Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE.
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE.
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Plancher G, Naëgelé B, Guinet V, Portrat S, Colliot P. Stroke damages attentional maintenance in working memory. J Neuropsychol 2023; 17:81-88. [PMID: 35941079 DOI: 10.1111/jnp.12287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 07/13/2022] [Indexed: 11/30/2022]
Abstract
Stroke is the main cause of acquired disability in adults, and specific deficits in working memory (WM) are among the most common cognitive consequences. In neuropsychological routine, WM is most of the time investigated in the framework of the multicomponent model (Baddeley & Hitch, 1974, The psychology of learning and motivation, 47). Using a more recent theoretical WM model, the time-based resource-sharing (TBRS) model (Barrouillet et al., 2011, Psychol. Rev., 118, 175), the aim of the present study was to investigate in young post-stroke patients to which extent attentional maintenance is impaired in WM. To address this question, we discarded other factors known to directly influence WM performance, that is processing speed and short-term memory span. We proposed to 53 post-stroke patients and to 63 healthy controls a complex span paradigm in which participants were asked to alternate between the memorization of a series of images and a concurrent parity judgement task of a series of digits. To investigate the attentional maintenance processes, we manipulated the cognitive load (CL) of the concurrent task. CL effect is typically interpreted as the involvement of attentional maintenance processes. The task was adapted to each participant according to their processing speed and memory span. As expected, the results showed higher recall performance in healthy controls compared with post-stroke patients. Consistent with the literature, we also observed higher performance when the CL was low compared with high. However, the improvement in recall at low CL was smaller for post-stroke patients compared with controls, suggesting that post-stroke WM deficit could be in part due to a deficit of the attentional maintenance processes.
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Affiliation(s)
- Gaën Plancher
- Laboratoire d'Étude des Mécanismes Cognitifs, Université Lumière Lyon 2, Paris, France.,Institut Universitaire de France (IUF), Paris, France
| | | | - Victoria Guinet
- Department of Functional Neurology and Epileptology, Hospices Civils de Lyon, Bron, France
| | - Sophie Portrat
- Université Savoie Mont-Blanc, Université Grenoble Alpes, CNRS, LPNC, Grenoble, France
| | - Pascale Colliot
- Laboratoire d'Étude des Mécanismes Cognitifs, Université Lumière Lyon 2, Paris, France
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Hausman HK, Hardcastle C, Albizu A, Kraft JN, Evangelista ND, Boutzoukas EM, Langer K, O'Shea A, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, Porges E, DeKosky ST, Hishaw GA, Wu S, Marsiske M, Cohen R, Alexander GE, Woods AJ. Cingulo-opercular and frontoparietal control network connectivity and executive functioning in older adults. GeroScience 2022; 44:847-866. [PMID: 34950997 PMCID: PMC9135913 DOI: 10.1007/s11357-021-00503-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/15/2021] [Indexed: 10/19/2022] Open
Abstract
Executive function is a cognitive domain that typically declines in non-pathological aging. Two cognitive control networks that are vulnerable to aging-the cingulo-opercular (CON) and fronto-parietal control (FPCN) networks-play a role in various aspects of executive functioning. However, it is unclear how communication within these networks at rest relates to executive function subcomponents in older adults. This study examines the associations between CON and FPCN connectivity and executive function performance in 274 older adults across working memory, inhibition, and set-shifting tasks. Average CON connectivity was associated with better working memory, inhibition, and set-shifting performance, while average FPCN connectivity was associated solely with working memory. CON region of interest analyses revealed significant connections with classical hub regions (i.e., anterior cingulate and anterior insula) for each task, language regions for verbal working memory, right hemisphere dominance for inhibitory control, and widespread network connections for set-shifting. FPCN region of interest analyses revealed largely right hemisphere fronto-parietal connections important for working memory and a few temporal lobe connections for set-shifting. These findings characterize differential brain-behavior relationships between cognitive control networks and executive function in aging. Future research should target these networks for intervention to potentially attenuate executive function decline in older adults.
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Affiliation(s)
- Hanna K Hausman
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Cheshire Hardcastle
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jessica N Kraft
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Emanuel M Boutzoukas
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Kailey Langer
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Eric Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Steven T DeKosky
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Samuel Wu
- Department of Biostatistics, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Michael Marsiske
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Ronald Cohen
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Gene E Alexander
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
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