Alexander Lebedev

The stock market is a bellwether of socio-economic changes that may directly affect individual well-being. Using large-scale UK-biobank data generated over 14 years, we applied specification curve analysis to rigorously identify significant associations between the local stock market index (FTSE100) and 479,791 UK residents’ mood, as well as their alcohol intake and blood pressure adjusting the results for a large number of potential confounders, including age, sex, linear and non-linear effects of time, research site, other stock market indexes. Furthermore, we found similar associations between FTSE100 and volumetric measures of affective brain regions in a subsample (n = 39,755; measurements performed over 5.5 years), which were particularly strong around phase transitions characterized by maximum volatility in the market. The main findings did not depend on applied effect-size estimation criteria (linear methods or mutual information criterion) and were replicated in two indepen...

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness. From The ADNI database, 185 AD, and 225 healthy controls (HC) were randomly split into training and testing datasets. 165 subjects with mild cognitive impairment (MCI) were distributed according to the month of conversion to dementia (4-year follow-up). Structural 1.5-T MRI-scans were processed using Freesurfer segmentation and cortical reconstruction....

Background: Cognitive aging creates major individual and societal burden, motivating search for treatment and preventive care strategies. Behavioural interventions can improve cognitive performance in older age, but effects are small. Basic research has implicated dopaminergic signaling in plasticity. We investigated whether transient enhancement of dopaminergic neurotransmission via administration of L-dopa improves effects of cognitive training on performance. Methods: Participants for this randomised, parallel-group, double-blind, placebo-controlled trial were recruited via newspaper advertisements. Inclusion criteria were: age of 65-75 years, Mini-Mental State Examination score >25, absence of serious medical conditions. Eligible subjects were randomly allocated to either receive 100/25mg L-dopa/benserazide or placebo prior to each of twenty cognitive training sessions administered during a four-week period. Participants and staff were masked to group assignment. Primary outc...

Despite recently resurrected scientific interest in classical psychedelics, few studies have focused on potential harms associated with abuse of these substances. In particular, the link between psychedelic use and psychotic symptoms has been debated while no conclusive evidence has been presented. Here, we studied an adult population (n = 1032) with a special focus on young (18–35 years) and healthy individuals (n = 701) to evaluate the association of psychedelic drug use with schizotypy and evidence integration impairment typically observed in psychosis-spectrum disorders. Experimental behavioural testing was performed in a subsample of the subjects (n = 39). We observed higher schizotypy scores in psychedelic users in the total sample. However, the effect size was notably small and only marginally significant when considering young and healthy subjects (Cohen’s d = 0.13). Controlling for concomitant drug use, none of our analyses found significant associations between psychedelic...

Background Parkinson’s disease (PD) affects many physiological systems essential for balance control. Recent studies suggest that intensive and cognitively demanding physical exercise programs are capable of inducing plastic brain changes in PD. We have developed a highly challenging balance training (the HiBalance) program that emphasizes critical aspects of balance control through progressively introducing more challenging exercises which incorporates dual-tasking. Earlier studies have shown it to be effective in improving balance, gait and dual-tasking. The study design has thereafter been adjusted to link intervention-induced behavioral changes to brain morphology and function. Specifically, in this randomized controlled trial, we will determine the effects of the HiBalance program on balance, gait and cognition and relate this to task-evoked functional MRI (fMRI), as well as brain-derived neurotrophic factor (BDNF) in participants with mild-moderate PD. Methods One hundred part...

Several previous studies suggest that clinical high risk for psychosis (CHR) is associated with prefrontal functional abnormalities and more widespread reduced grey matter in prefrontal, temporal and parietal areas. We investigated neural correlates to CHR in medication-naïve patients. 41 CHR patients and 37 healthy controls were examined with 1.5 Tesla MRI, yielding functional scans while performing an N-back task and structural T1-weighted brain images. Functional and structural data underwent automated preprocessing steps in SPM and Freesurfer, correspondingly. The groups were compared employing mass-univariate strategy within the generalized linear modelling framework. CHR demonstrated reduced suppression of the medial temporal lobe (MTL) regions during n-back task. We also found that, consistent with previous findings, CHR subjects demonstrated thinning in prefrontal, cingulate, insular and inferior temporal areas, as well as reduced hippocampal volumes. The present findings ad...

The promise of transcranial direct-current stimulation (tDCS) as a modulator of cognition has appealed to researchers, media, and the general public. Researchers have suggested that tDCS may increase effects of cognitive training. In this study of 123 older adults, we examined the interactive effects of 20 sessions of anodal tDCS over the left prefrontal cortex (vs. sham tDCS) and simultaneous working memory training (vs. control training) on change in cognitive abilities. Stimulation did not modulate gains from pre- to posttest on latent factors of either trained or untrained tasks in a statistically significant manner. A supporting meta-analysis ( n = 266), including younger as well as older individuals, showed that, when combined with training, tDCS was not much more effective than sham tDCS at changing working memory performance ( g = 0.07, 95% confidence interval, or CI = [−0.21, 0.34]) and global cognition performance ( g = −0.01, 95% CI = [−0.29, 0.26]) assessed in the absenc...

Transcranial direct current stimulation (tDCS) has been put forward as a non-pharmacological alternative for alleviating cognitive decline in old age. Although results have shown some promise, little is known about the optimal stimulation parameters for modulation in the cognitive domain. In this study, the effects of tDCS over the dorsolateral prefrontal cortex (dlPFC) on working memory performance were investigated in thirty older adults. An N-back task assessed working memory before, during and after anodal tDCS at a current strength of 1 mA and 2 mA, in addition to sham stimulation. The study used a single-blind, cross-over design. The results revealed no significant effect of tDCS on accuracy or response times during or after stimulation, for any of the current strengths. These results suggest that a single session of tDCS over the dlPFC is unlikely to improve working memory, as assessed by an N-back task, in old age.

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Beca...

Objective To examine neuroanatomical changes associated with depressive symptoms in Alzheimer's disease (AD) and the relationship between brain structure and cerebrospinal fluid (CSF) AD biomarkers in depressed and non-depressed patients. Methods Two independent cohorts were used in this study. The first cohort (KI) was collected from the Memory Clinic at Karolinska University Hospital and consisted of 41 AD patients. The second cohort was selected and downloaded from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI) and consisted of 148 patient. Patients underwent medical, neuropsychological assessment, laboratory analyses of CSF, including β amyloid 1–42 (Aβ 42), total τ (t-τ), phosphorylated τ 181 (p-τ) and brain MRI examination. In the KI cohort, depression was assessed using the Cornell Scale for Depression in Dementia, and in the ADNI cohort the Geriatric Depression Scale was applied. 3D T1-weighted MRI images were processed using automated steps for segmentation and surface reconstruction implemented in Freesurfer. General linear model analysis was used as a statistical approach. Results Cortical thinning in AD patients with depressive symptoms compared with those without was observed in the left parietal and temporal brain regions in both cohorts. Negative correlation between cortical thickness and t-τ was greater in depressed compared with non-depressed AD patients in precuneus and parahippocampal cortex. Conclusions Our findings suggest that depressive symptoms in AD patients are associated with cortical thinning in temporal and parietal regions. In addition, our findings suggest that τ protein pathology in these areas may contribute to the development of depressive symptoms in AD.

Our aim was to assess cortical thickness in a large multicenter cohort of drug-naive patients with early Parkinson disease (PD), with and without mild cognitive impairment (MCI), and explore the cognitive correlates of regional cortical thinning. One hundred twenty-three newly diagnosed patients with PD and 56 healthy controls with 3-tesla structural MRI scans and complete neuropsychological assessment from the Parkinson's Progression Markers Initiative were included. Modified Movement Disorders Society Task Force level II criteria were applied to diagnose MCI in PD. FreeSurfer image processing and analysis software was used to measure cortical thickness across groups and the association with cognitive domains and tests. In patients with MCI, atrophy was found in temporal, parietal, frontal, and occipital areas compared with controls. Specific regional thinning in the right inferior temporal cortex was also found in cognitively normal patients. Memory, executive, and visuospatial performance was associated with temporoparietal and superior frontal thinning, suggesting a relationship between cognitive impairment and both anterior and posterior cortical atrophy in the whole patient sample. These findings confirm that MCI is associated with widespread cortical atrophy. In addition, they suggest that regional cortical thinning is already present at the time of diagnosis in patients with early, untreated PD who do not meet the criteria for MCI. Together, the results indicate that cortical thinning can serve as a marker for initial cognitive decline in early PD.

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness.

From The ADNI database, 185 AD, and 225 healthy controls (HC) were randomly split into training and testing datasets. 165 subjects with mild cognitive impairment (MCI) were distributed according to the month of conversion to dementia (4-year follow-up). Structural 1.5-T MRI-scans were processed using Freesurfer segmentation and cortical reconstruction. Using the resulting output, AD/HC classifiers were trained. Training included model tuning and performance assessment using out-of-bag estimation. Subsequently the classifiers were validated on the AD/HC test set and for the ability to predict MCI-to-AD conversion. Models' between-cohort robustness was additionally assessed using the AddNeuroMed dataset acquired with harmonized clinical and imaging protocols.

In the ADNI set, the best AD/HC sensitivity/specificity (88.6%/92.0% — test set) was achieved by combining cortical thickness and volumetric measures. The Random Forest model resulted in significantly higher accuracy compared to the reference classifier (linear Support Vector Machine). The models trained using parcelled and high-dimensional (HD) input demonstrated equivalent performance, but the former was more effective in terms of computation/memory and time costs. The sensitivity/specificity for detecting MCI-to-AD conversion (but not AD/HC classification performance) was further improved from 79.5%/75%–83.3%/81.3% by a combination of morphometric measurements with ApoE-genotype and demographics (age, sex, education). When applied to the independent AddNeuroMed cohort, the best ADNI models produced equivalent performance without substantial accuracy drop, suggesting good robustness sufficient for future clinical implementation.

Cognitive impairment is a common non-motor feature of Parkinson's disease (PD). Understanding the neural mechanisms of this deficit is crucial for the development of efficient methods for treatment monitoring and augmentation of cognitive functions in PD patients. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson's Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with (123)I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox (BCT) was used to extract nodal strength from all ROIs, and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable (LV) scores were matched with the performances in the three cognitive domains (memory, visuospatial, and executive) and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on the modularity of the "cognitive network" was analyzed. For the range of deficits studied, better executive performance was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This profile was also characterized by a relative preservation of nigrostriatal dopaminergic function. The profile associated with better memory performance correlated with increased prefronto-limbic processing, and was not associated with presynaptic striatal dopamine uptake. SBR ratios were negatively correlated with modularity of the "cognitive network," suggesting integrative effects of the preserved nigrostriatal dopamine system on this circuitry.

Context
Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) are the most common neurodegenerative dementia types. It is important to differentiate between them because of the differences in prognosis and treatment approaches.

Objective
Investigate if sparse partial least squares (SPLS) classification of cortical thickness measurements could differentiate between AD and DLB.

Methods
Two independent cohorts without MR-protocol alignment in Norway and Slovenia with 97 AD and DLB subjects were enrolled. Cortical thickness measurements acquired with Freesurfer were used in subsequent SPLS classification runs. The cohorts were analyzed separately and afterwards combined. The models were trained with leave-one-out cross validation and test datasets were used when available. To study the impact of MR-protocol alignment, the classifiers were additionally tested on sets drawn exclusively from the independent cohorts.

Results
The obtained sensitivity/specificity/AUC values were 94.4/88.89/0.978 and 88.2/94.1/0.969 in the Norwegian and Slovenian cohorts, respectively. Both cohorts showed AD-associated pattern of thinning in mid-anterior temporal, occipital and subgenual cingulate cortex, whereas the pattern supportive for DLB included thinning in dorsal cingulate, posterior temporal and lateral orbitofrontal regions. When combining the cohorts, sensitivity/specificity/AUC were 82.1/85.7/0.948 for the training and 77.8/75/0.731 for the testing datasets with the same pattern-of-difference. The models tested on datasets drawn exclusively from the independent cohorts did not produce adequate accuracy.

Conclusion
SPLS classification of cortical thickness is a good method for differentiating between AD and DLB, relatively stable even for mixed data, but not when tested on completely independent data drawn from different cohorts (without MR-protocol alignment).

CONTEXT:
Depression is common in dementia, especially in the early stages, with important clinical implications, but the etiology is unknown and most likely heterogeneous. Antidepressant use in the elderly without dementia has previously been shown to be associated with high risks of adverse events and with structural brain alterations.

OBJECTIVE:
To investigate cortical changes associated with depression and antidepressant use in patients with mild Alzheimer's disease (AD) and Lewy body dementia (LBD).

METHODS:
74 subjects with mild AD and LBD from geriatric and psychiatry outpatient clinics in Western Norway were included. The Montgomery-Asberg Depression Rating Scale (MADRS) was used to assess depression. Automatic preprocessing using Freesurfer included steps for white and grey matter surface reconstruction. The resulting cortical thickness was analyzed using linear modeling.

RESULTS:
Clusters of depression-associated thinning were found in prefrontal and temporal areas. Treatment-associated thinning was observed in the parahippocampal region and was significant even after correction for age, sex, AD/LBD diagnosis, and MADRS scores.

CONCLUSION:
Depression in mild AD and LBD is associated with cortical thinning in prefrontal and temporal areas. The findings suggest that depressive symptoms in mild dementia could develop due to neurodegeneration in the same neural circuits that are critical for depression across different brain disorders. Antidepressant use in patients with mild AD and LBD is associated with parahippocampal thinning. Taken together with low efficacy of antidepressants in cognitively impaired patients and high risks of adverse events, our results suggest a need to re-evaluate the treatment approaches for depression and the role of antidepressants in patients with dementia.