Altered effective connectivity during performance of an information processing speed task in multiple sclerosis

2011 ◽  
Vol 18 (4) ◽  
pp. 409-417 ◽  
Author(s):  
Victoria M Leavitt ◽  
Glenn Wylie ◽  
Helen M Genova ◽  
Nancy D Chiaravalloti ◽  
John DeLuca
Keyword(s):  
Multiple Sclerosis ◽  
Processing Speed ◽  
Effective Connectivity ◽  
A Priori ◽  
Brain Regions ◽  
Healthy Controls ◽  
Causality Analysis ◽  
Information Processing Speed ◽  
Neural Connections ◽  
Speed Task

Background: Functional magnetic resonance imaging (fMRI) studies of persons with multiple sclerosis (MS) reveal distinct patterns of activation during task performance. We were interested in determining whether distinct patterns of effective connectivity would be revealed with Granger causality analysis (GCA). Objective: To characterize directed neural connections in persons with MS during a processing speed task between brain regions known to be activated in healthy controls. Methods: fMRI and GCA were used to examine effective connectivity underlying performance of a processing speed task in persons with MS. In total, 16 individuals with MS and 17 healthy controls (HC) performed a modified version of the Symbol Digit Modality Task (mSDMT) in the MRI scanner. Eight seed regions were selected on the basis of a priori data showing areas involved in mSDMT performance of HC. Results: Behaviorally, the MS group attained a level of accuracy equivalent to the HC group, although they were significantly slower. While there was a great deal of overlap in the connections relied upon by both groups, the MS group showed significant differences in connectivity between critical brain regions. Specifically, the MS group had more connections from multiple regions to frontal cortices bilaterally relative to HCs. Conclusions: Greater neural recruitment by the MS group relative to HC is consistent with the neural efficiency hypothesis, and lends further support to the notion that more connections must be recruited to maintain performance in the presence of brain pathology.

Altered Effective Connectivity during a Processing Speed Task in Individuals with Multiple Sclerosis

2016 ◽  
Vol 22 (2) ◽  
pp. 216-224 ◽  
Author(s):  
E. Dobryakova ◽  
S.L. Costa ◽  
G.R. Wylie ◽  
J. DeLuca ◽  
H.M. Genova
Keyword(s):  
Multiple Sclerosis ◽  
Processing Speed ◽  
Effective Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Connectivity Pattern ◽  
Control Group ◽  
Dynamic Representation ◽  
Speed Task ◽  
Healthy Participants

AbstractObjectives: Processing speed impairment is the most prevalent cognitive deficit in individuals with multiple sclerosis (MS). However, the neural mechanisms associated with processing speed remain under debate. The current investigation provides a dynamic representation of the functioning of the brain network involved in processing speed by examining effective connectivity pattern during a processing speed task in healthy adults and in MS individuals with and without processing speed impairment. Methods: Group assignment (processing speed impaired vs. intact) was based on participants’ performance on the Symbol Digit Modalities test (Parmenter, Testa, Schretlen, Weinstock-Guttman, & Benedict, 2010). First, brain regions involved in the processing speed task were determined in healthy participants. Time series from these functional regions of interest of each group of participants were then subjected to the effective connectivity analysis (Independent Multiple-Sample Greedy Equivalence Search and Linear, Non-Gaussian Orientation, Fixed Structure algorithms) that showed causal influences of one region on another during task performance. Results: The connectivity pattern of the processing speed impaired group was significantly different from the connectivity pattern of the processing speed intact group and of the healthy control group. Differences in the strength of common connections were also observed. Conclusions: Effective connectivity results reveal that MS individuals with processing speed impairment not only have connections that differ from healthy participants and MS individuals without processing speed impairment, but also have increased strengths of connections. (JINS, 2016, 22, 216–224)

Difficulties in Planning Among Patients with Multiple Sclerosis: A Relative Consequence of Deficits in Information Processing Speed

2013 ◽  
Vol 19 (5) ◽  
pp. 613-620 ◽  
Author(s):  
Emily M. Owens ◽  
Douglas R. Denney ◽  
Sharon G. Lynch
Keyword(s):  
Multiple Sclerosis ◽  
Information Processing ◽  
Processing Speed ◽  
Healthy Controls ◽  
Problem Difficulty ◽  
Sufficient Time ◽  
Information Processing Speed ◽  
Tower Of London ◽  
Planning Ability

AbstractPrevious studies show that MS patients take longer than healthy controls to plan their solutions to Tower of London (TOL) problems but yield conflicting results regarding the quality of their solutions. The present study evaluated performance under untimed or timed conditions to assess the possibility that differences in planning ability only occur when restrictions in solution times are imposed. MS patients (n = 39) and healthy controls (n = 43) completed a computerized version of the TOL under one of two conditions. In the untimed condition, participants were allowed as much time as needed on each problem. In the timed condition, limits were imposed on solution times and time remaining was displayed with each problem. Patients exhibited longer planning times than controls, and the disparity between groups increased with problem difficulty. Planning performance depended upon condition. In the untimed condition, patients and controls performed equally well. When solution times were restricted, however, patients solved fewer problems than controls. MS patients’ planning ability is intact when permitted sufficient time to formulate the required plan. Deficiencies in planning are only evident when time is restricted, and, therefore, are more accurately considered a relative consequence of disease-related problems in information processing speed. (JINS, 2013, 19, 1–8)

Altered functional connectivity and performance variability in relapsing–remitting multiple sclerosis

2014 ◽  
Vol 20 (11) ◽  
pp. 1453-1463 ◽  
Author(s):  
Magdalena Wojtowicz ◽  
Erin L Mazerolle ◽  
Virender Bhan ◽  
John D Fisk
Keyword(s):  
Multiple Sclerosis ◽  
Information Processing ◽  
Functional Connectivity ◽  
Processing Speed ◽  
Resting State ◽  
Healthy Controls ◽  
Information Processing Speed ◽  
Frontal Pole ◽  
Performance Variability ◽  
Relapsing Remitting

Background: Patients with multiple sclerosis (MS) demonstrate slower and more variable performance on attention and information processing speed tasks. Greater variability in cognitive task performance has been shown to be an important predictor of neurologic status and provides a unique measure of cognitive performance in MS patients. Objectives: This study investigated alterations in resting-state functional connectivity associated with within-person performance variability in MS patients. Methods: Relapsing–remitting MS patients and matched healthy controls completed structural MRI and resting-state fMRI (rsfMRI) scans, as well as tests of information processing speed. Performance variability was calculated from reaction time tests of processing speed. rsfMRI connectivity was investigated within regions associated with the default mode network (DMN). Relations between performance variability and functional connectivity in the DMN within MS patients were evaluated. Results: MS patients demonstrated greater reaction time performance variability compared to healthy controls ( p<0.05). For MS patients, more stable performance on a complex processing speed task was associated with greater resting-state connectivity between the ventral medial prefrontal cortex and the frontal pole. Conclusions: Among MS patients, greater functional connectivity between medial prefrontal and frontal pole regions appears to facilitate performance stability on complex speed-dependent information processing tasks.

Trait neuroticism, extraversion, and conscientiousness in multiple sclerosis: Link to cognitive impairment?

2017 ◽  
Vol 24 (2) ◽  
pp. 205-213 ◽  
Author(s):  
Shumita Roy ◽  
Allison S Drake ◽  
María Bárbara Eizaguirre ◽  
Robert Zivadinov ◽  
Bianca Weinstock-Guttman ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cluster Analysis ◽  
Processing Speed ◽  
Cognitively Impaired ◽  
Healthy Controls ◽  
Information Processing Speed ◽  
Adaptive Traits ◽  
Cognitive Domains ◽  
Informant Ratings ◽  
Neo Five Factor Inventory

Background: Previous research suggests that patients with multiple sclerosis (MS) have higher neuroticism, lower extraversion, and lower conscientiousness relative to healthy controls (HCs). However, the prevalence of this maladaptive profile in MS and its relation to cognition is unknown. Objective: Determine prevalence of maladaptive personality among MS patients, compared to HCs, and examine how it relates to cognitive dysfunction. Methods: A sample of 275 MS patients and 55 HCs completed neuroperformance measures of information processing speed and memory. Self and informant ratings were obtained on the NEO Five-Factor Inventory. Results: MS patients had higher neuroticism and lower extraversion than HCs. Cognitively impaired patients were also lower in conscientiousness. Cluster analysis revealed a configuration of these same three traits, representing a maladaptive profile. This profile was found in 50% of the overall MS sample, compared to 24% of HCs. However, only cognitively impaired MS patients had a higher prevalence of maladaptive personality compared to HCs. Among cognitively impaired patients, those with maladaptive traits were impaired in more cognitive domains than those with more adaptive traits. Conclusion: Cognitively impaired MS patients have a higher prevalence of seemingly maladaptive traits compared to HCs, demonstrating an association between cognition and personality in MS.

scholarly journals T1 Relaxation Times in the Cortex and Thalamus Are Associated With Working Memory and Information Processing Speed in Patients With Multiple Sclerosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Christian Thaler ◽  
Isabelle Hartramph ◽  
Jan-Patrick Stellmann ◽  
Christoph Heesen ◽  
Maxim Bester ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Working Memory ◽  
Cognitive Impairment ◽  
Information Processing ◽  
Processing Speed ◽  
T1 Mapping ◽  
Relaxation Times ◽  
Healthy Controls ◽  
Information Processing Speed ◽  
T1 Relaxation

Background: Cortical and thalamic pathologies have been associated with cognitive impairment in patients with multiple sclerosis (MS).Objective: We aimed to quantify cortical and thalamic damage in patients with MS using a high-resolution T1 mapping technique and to evaluate the association of these changes with clinical and cognitive impairment.Methods: The study group consisted of 49 patients with mainly relapsing-remitting MS and 17 age-matched healthy controls who received 3T MRIs including a T1 mapping sequence (MP2RAGE). Mean T1 relaxation times (T1-RT) in the cortex and thalami were compared between patients with MS and healthy controls. Additionally, correlation analysis was performed to assess the relationship between MRI parameters and clinical and cognitive disability.Results: Patients with MS had significantly decreased normalized brain, gray matter, and white matter volumes, as well as increased T1-RT in the normal-appearing white matter, compared to healthy controls (p &lt; 0.001). Partial correlation analysis with age, sex, and disease duration as covariates revealed correlations for T1-RT in the cortex (r = −0.33, p &lt; 0.05), and thalami (right thalamus: r = −0.37, left thalamus: r = −0.50, both p &lt; 0.05) with working memory and information processing speed, as measured by the Symbol-Digit Modalities Test.Conclusion: T1-RT in the cortex and thalamus correlate with information processing speed in patients with MS.

scholarly journals Altered Prefrontal–Basal Ganglia Effective Connectivity in Patients With Poststroke Cognitive Impairment

2020 ◽  
Vol 11 ◽  
Author(s):  
Jing Zhang ◽  
Zixiao Li ◽  
Xingxing Cao ◽  
Lijun Zuo ◽  
Wei Wen ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Basal Ganglia ◽  
Cognitive Decline ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Neuronal Model ◽  
Causal Modeling ◽  
Healthy Controls

We investigated the association between poststroke cognitive impairment and a specific effective network connectivity in the prefrontal–basal ganglia circuit. The resting-state effective connectivity of this circuit was modeled by employing spectral dynamic causal modeling in 11 poststroke patients with cognitive impairment (PSCI), 8 poststroke patients without cognitive impairment (non-PSCI) at baseline and 3-month follow-up, and 28 healthy controls. Our results showed that different neuronal models of effective connectivity in the prefrontal–basal ganglia circuit were observed among healthy controls, non-PSCI, and PSCI patients. Additional connected paths (extra paths) appeared in the neuronal models of stroke patients compared with healthy controls. Moreover, changes were detected in the extra paths of non-PSCI between baseline and 3-month follow-up poststroke, indicating reorganization in the ipsilesional hemisphere and suggesting potential compensatory changes in the contralesional hemisphere. Furthermore, the connectivity strengths of the extra paths from the contralesional ventral anterior nucleus of thalamus to caudate correlated significantly with cognitive scores in non-PSCI and PSCI patients. These suggest that the neuronal model of effective connectivity of the prefrontal–basal ganglia circuit may be sensitive to stroke-induced cognitive decline, and it could be a biomarker for poststroke cognitive impairment 3 months poststroke. Importantly, contralesional brain regions may play an important role in functional compensation of cognitive decline.

scholarly journals Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis

Brain ◽  
2019 ◽  
Vol 143 (1) ◽  
pp. 150-160 ◽  
Author(s):  
Kim A Meijer ◽  
Martijn D Steenwijk ◽  
Linda Douw ◽  
Menno M Schoonheim ◽  
Jeroen J G Geurts
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Fractional Anisotropy ◽  
Long Range ◽  
Short Range ◽  
Brain Regions ◽  
Healthy Controls ◽  
Network Efficiency ◽  
Structural Network ◽  
The Impact

Abstract An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length &lt; quartile 1) and long-range (length &gt; quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P &lt; 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P &lt; 0.001) and total number of fibres (z = −0.44, P &lt; 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P &lt; 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.

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