A brain-derived metric for preferred kinetic stimuli

We here address the question of whether there is any correlation between subjective preference for simple configurations within a specific visual domain such as motion and strength of activity in visual areas in which that domain is emphasized. We prepared several distinctive patterns of dots in motion with various characteristics and asked humans to rate them according to their preference, before and while scanning the activity in their brains with functional magnetic resonance imaging. For simplicity, we restricted ourselves to motion in the fronto-parallel plane. Moving patterns produced activity in areas V1, V2, the V3 complex (V3, V3A, V3B) and V5, but only in areas V5, V3A/B and parietal cortex did the preferred kinetic patterns produce stronger activity when compared with the non-preferred ones. In addition, preferred patterns produced activity within field A1 of medial orbito-frontal cortex (mOFC), which is not otherwise activated by kinetic stimuli. Hence, for these areas, stronger neural activity correlated with subjective preference. We conclude that configurations of kinetic stimuli that are subjectively preferred correlate with stronger activity within early visual areas and within mOFC. This opens up the possibility of more detailed studies to relate subjective preferences to strength of activity in early visual areas and to relate activity in them to areas whose activity correlates with the subjective experience of beauty

Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis

Black holes; Chronic active lesions; Volumetric MRIAgujeros negros; Lesiones activas crónicas; Resonancia magnética volumétricaForats negres; Lesions actives cròniques; Ressonància magnètica volumètricaBackground Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion’s metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p < 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p < 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI −0.005 to −0.003, p < 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed-effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95%CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). Conclusions SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity and MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS

Networks of microstructural damage predict disability in multiple sclerosis

Background: Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. // Methods: We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. // Results: We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). // Conclusions: GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials

Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis

Background: Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion's metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives: To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods: 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was &amp; LE; 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results: Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p &lt; 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p &lt; 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI -0.005 to -0.003, p &lt; 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95% CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). Conclusions: SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity , MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS

Longitudinal Metabolite Changes in Progressive Multiple Sclerosis: A Study of 3 Potential Neuroprotective Treatments

BACKGROUND: 1 H-magnetic resonance spectroscopy (1 H-MRS) may provide a direct index for the testing of medicines for neuroprotection and drug mechanisms in multiple sclerosis (MS) through measures of total N-acetyl-aspartate (tNAA), total creatine (tCr), myo-inositol (mIns), total-choline (tCho), and glutamate + glutamine (Glx). Neurometabolites may be associated with clinical disability with evidence that baseline neuroaxonal integrity is associated with upper limb function and processing speed in secondary progressive MS (SPMS). PURPOSE: To assess the effect on neurometabolites from three candidate drugs after 96-weeks as seen by 1 H-MRS and their association with clinical disability in SPMS. STUDY-TYPE: Longitudinal. POPULATION: 108 participants with SPMS randomized to receive neuroprotective drugs amiloride [mean age 55.4 (SD 7.4), 61% female], fluoxetine [55.6 (6.6), 71%], riluzole [54.6 (6.3), 68%], or placebo [54.8 (7.9), 67%]. FIELD STRENGTH/SEQUENCE: 3-Tesla. Chemical-shift-imaging 2D-point-resolved-spectroscopy (PRESS), 3DT1. ASSESSMENT: Brain metabolites in normal appearing white matter (NAWM) and gray matter (GM), brain volume, lesion load, nine-hole peg test (9HPT), and paced auditory serial addition test were measured at baseline and at 96-weeks. STATISTICAL TESTS: Paired t-test was used to analyze metabolite changes in the placebo arm over 96-weeks. Metabolite differences between treatment arms and placebo; and associations between baseline metabolites and upper limb function/information processing speed at 96-weeks assessed using multiple linear regression models. P-value<0.05 was considered statistically significant. RESULTS: In the placebo arm, tCho increased in GM (mean difference = -0.32 IU) but decreased in NAWM (mean difference = 0.13 IU). Compared to placebo, in the fluoxetine arm, mIns/tCr was lower (β = -0.21); in the riluzole arm, GM Glx (β = -0.25) and Glx/tCr (β = -0.29) were reduced. Baseline tNAA(β = 0.22) and tNAA/tCr (β = 0.23) in NAWM were associated with 9HPT scores at 96-weeks. DATA CONCLUSION: 1 H-MRS demonstrated altered membrane turnover over 96-weeks in the placebo group. It also distinguished changes in neuro-metabolites related to gliosis and glutaminergic transmission, due to fluoxetine and riluzole, respectively. Data show tNAA is a potential marker for upper limb function. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 4

Longitudinal metabolite changes in progressive multiple sclerosis:A study of 3 potential neuroprotective treatments

Background: 1 H-magnetic resonance spectroscopy (1 H-MRS) may provide a direct index for the testing of medicines for neuroprotection and drug mechanisms in multiple sclerosis (MS) through measures of total N-acetyl-aspartate (tNAA), total creatine (tCr), myo-inositol (mIns), total-choline (tCho), and glutamate + glutamine (Glx). Neurometabolites may be associated with clinical disability with evidence that baseline neuroaxonal integrity is associated with upper limb function and processing speed in secondary progressive MS (SPMS). Purpose: To assess the effect on neurometabolites from three candidate drugs after 96-weeks as seen by 1 H-MRS and their association with clinical disability in SPMS. Study-type: Longitudinal. Population: 108 participants with SPMS randomized to receive neuroprotective drugs amiloride [mean age 55.4 (SD 7.4), 61% female], fluoxetine [55.6 (6.6), 71%], riluzole [54.6 (6.3), 68%], or placebo [54.8 (7.9), 67%]. Field strength/sequence: 3-Tesla. Chemical-shift-imaging 2D-point-resolved-spectroscopy (PRESS), 3DT1. Assessment: Brain metabolites in normal appearing white matter (NAWM) and gray matter (GM), brain volume, lesion load, nine-hole peg test (9HPT), and paced auditory serial addition test were measured at baseline and at 96-weeks. Statistical tests: Paired t-test was used to analyze metabolite changes in the placebo arm over 96-weeks. Metabolite differences between treatment arms and placebo; and associations between baseline metabolites and upper limb function/information processing speed at 96-weeks assessed using multiple linear regression models. P-value&lt;0.05 was considered statistically significant. Results: In the placebo arm, tCho increased in GM (mean difference = -0.32 IU) but decreased in NAWM (mean difference = 0.13 IU). Compared to placebo, in the fluoxetine arm, mIns/tCr was lower (β = -0.21); in the riluzole arm, GM Glx (β = -0.25) and Glx/tCr (β = -0.29) were reduced. Baseline tNAA(β = 0.22) and tNAA/tCr (β = 0.23) in NAWM were associated with 9HPT scores at 96-weeks. Data conclusion: 1 H-MRS demonstrated altered membrane turnover over 96-weeks in the placebo group. It also distinguished changes in neuro-metabolites related to gliosis and glutaminergic transmission, due to fluoxetine and riluzole, respectively. Data show tNAA is a potential marker for upper limb function. Level of evidence: 1 TECHNICAL EFFICACY: Stage 4

Augmenting colour communication in English, Greek and Thai

The number of colour names varies across languages. To augment colour communication between speakers of different languages, we need a multilingual method to map how we perceive colours to the words we use to describe them. We evaluate the performance of a supervised colour naming model, Rotated Split Trees (RST), trained by responses from a crowdsourced colour naming experiment in English, Greek and Thai. We assess the generalizability of the model across several colour spaces where it performed best in the CIELUV. A comparison of RST with previous computational colour naming methods using independent psychophysical data in English showed that RST achieves state-of-the-art performance for basic colour categories and identifies five additional categories (n = 16) on the surface of the Munsell system. A demonstration of the performance of RST in segmenting a synthetic image across the colour gamut into colour names in English (n = 30), Greek (n = 28) and Thai (n = 46) further supports earlier findings that speakers can identify 30-50 colour names in their native language

Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes

Objective: In multiple sclerosis (MS), MRI measures at the whole brain or regional level are only modestly associated with disability, while network-based measures are emerging as promising prognostic markers. We sought to demonstrate whether data-driven patterns of covarying regional grey matter (GM) volumes predict future disability in secondary progressive MS (SPMS). Methods: We used cross-sectional structural MRI, and baseline and longitudinal data of Expanded Disability Status Scale, Nine-Hole Peg Test (9HPT) and Symbol Digit Modalities Test (SDMT), from a clinical trial in 988 people with SPMS. We processed T1-weighted scans to obtain GM probability maps and applied spatial independent component analysis (ICA). We repeated ICA on 400 healthy controls. We used survival models to determine whether baseline patterns of covarying GM volume measures predict cognitive and motor worsening. Results: We identified 15 patterns of regionally covarying GM features. Compared with whole brain GM, deep GM and lesion volumes, some ICA components correlated more closely with clinical outcomes. A mainly basal ganglia component had the highest correlations at baseline with the SDMT and was associated with cognitive worsening (HR=1.29, 95% CI 1.09 to 1.52, p<0.005). Two ICA components were associated with 9HPT worsening (HR=1.30, 95% CI 1.06 to 1.60, p<0.01 and HR=1.21, 95% CI 1.01 to 1.45, p<0.05). ICA measures could better predict SDMT and 9HPT worsening (C-index=0.69-0.71) compared with models including only whole and regional MRI measures (C-index=0.65-0.69, p value for all comparison <0.05). Conclusions: The disability progression was better predicted by some of the covarying GM regions patterns, than by single regional or whole-brain measures. ICA, which may represent structural brain networks, can be applied to clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect

Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis

Background: Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion's metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives: To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods: 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results: Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p < 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p < 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI −0.005 to −0.003, p < 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed-effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95%CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). Conclusions: SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity and MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS