Objectives
While widespread cortical and subcortical brain functional abnormalities have been found in bipolar disorder, the changes that take place between illness phases and recovery are less ...clearly documented. Only a small number of longitudinal studies of manic patients, in particular, have been carried out.
Methods
Twenty‐six bipolar patients underwent fMRI during performance of the n‐back working memory task when manic and again after recovery. Twenty‐six matched healthy controls were also scanned on two occasions. Task‐related activations and de‐activations were examined.
Results
When manic, the patients showed clusters of significantly reduced activation in the left dorsolateral prefrontal cortex (DLPFC)/precentral cortex and the parietal cortex/superior precuneus bilaterally. They also showed failure of de‐activation in the ventromedial frontal cortex (vmPFC). After recovery, activation in the left DLPFC/precentral cortex and in the bilateral parietal cortex/superior precuneus clusters increased significantly. However, failure of de‐activation remained present in the vmPFC.
Conclusions
Recovery from mania is associated with normalization of DLPFC and parietal hypoactivation, but not with vmPFC failure of de‐activation, which accordingly appears to represent a trait abnormality in the disorder.
Despite diffusion tensor imaging (DTI) evidence for widespread fractional anisotropy (FA) reductions in the brain white matter of patients with bipolar disorder, questions remain regarding the ...specificity and sensitivity of FA abnormalities as opposed to other diffusion metrics in the disorder. We conducted a whole‐brain voxel‐based multicompartment diffusion MRI study on 316 participants (i.e., 158 patients and 158 matched healthy controls) employing four diffusion metrics: the mean diffusivity (MD) and FA estimated from DTI, and the intra‐axonal signal fraction (IASF) and microscopic axonal parallel diffusivity (Dpar) derived from the spherical mean technique. Our findings provide novel evidence about widespread abnormalities in other diffusion metrics in BD. An extensive overlap between the FA and IASF results suggests that the lower FA in patients may be caused by a reduced intra‐axonal volume fraction or a higher macromolecular content in the intra‐axonal water. We also found a diffuse alteration in MD involving white and grey matter tissue and more localised changes in Dpar. A Machine Learning analysis revealed that FA, followed by IASF, were the most helpful metric for the automatic diagnosis of BD patients, reaching an accuracy of 72%. Number of mood episodes, age of onset/duration of illness, psychotic symptoms, and current treatment with lithium, antipsychotics, antidepressants, and antiepileptics were all significantly associated with microstructure abnormalities. Lithium treatment was associated with less microstructure abnormality.
A whole‐brain voxel‐based approach combining DTI and SMT diffusion‐derived metrics to reveal specific brain tissue microstructure abnormalities in bipolar disorder (BD) was carried out. We also evaluate the sensitivity of various diffusion metrics for the automatic diagnosis of BD through machine learning algorithms and cross‐validation. Finally, we look for differences between BD subtypes and the possible effect of duration of illness, age at onset, history of psychosis, and pharmacological treatment with lithium, antidepressant, antipsychotic, and antiepileptic drugs.
The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide and has had unprecedented effects in healthcare ...systems, economies and society. COVID-19 clinical presentation primarily affects the respiratory system causing bilateral pneumonia, but it is increasingly being recognized as a systemic disease, with neurologic manifestations reported in patients with mild symptoms but, most frequently, in those in a severe condition. Elderly individuals are at high risk of developing severe forms of COVID-19 due to factors associated with ageing and a higher prevalence of medical comorbidities and, therefore, they are more vulnerable to possible lasting neuropsychiatric and cognitive impairments. Several reports have described insomnia, depressed mood, anxiety, post-traumatic stress disorder and cognitive impairment in a proportion of patients after discharge from the hospital. The potential mechanisms underlying these symptoms are not fully understood but are probably multifactorial, involving direct neurotrophic effect of SARS-CoV-2, consequences of long intensive care unit stays, the use of mechanical ventilation and sedative drugs, brain hypoxia, systemic inflammation, secondary effects of medications used to treat COVID-19 and dysfunction of peripheral organs. Chronic diseases such as dementia are a particular concern not only because they are associated with higher rates of hospitalization and mortality but also because COVID-19 further exacerbates the vulnerability of those with cognitive impairment. In patients with dementia, COVID-19 frequently has an atypical presentation with mental status changes complicating the early identification of cases. COVID-19 has had a dramatical impact in long-term care facilities, where rates of infection and mortality have been very high. Community measures implemented to slow the spread of the virus have forced to social distancing and cancellation of cognitive stimulation programs, which may have contributed to generate loneliness, behavioral symptoms and worsening of cognition in patients with dementia. COVID-19 has impacted the functioning of Memory Clinics, research programs and clinical trials in the Alzheimer´s field, triggering the implementation of telemedicine. COVID-19 survivors should be periodically evaluated with comprehensive cognitive and neuropsychiatric assessments, and specific mental health and cognitive rehabilitation programs should be provided for those suffering long-term cognitive and psychiatric sequelae.
Cognitive impairment in the euthymic phase is a well-established finding in bipolar disorder. However, its brain structural and/or functional correlates are uncertain.
Thirty-three euthymic bipolar ...patients with preserved memory and executive function and 28 euthymic bipolar patients with significant memory and/or executive impairment, as defined using two test batteries, the Rivermead Behavioural Memory Test (RBMT) and the Behavioural Assessment of the Dysexecutive Syndrome (BADS), plus 28 healthy controls underwent structural MRI using voxel-based morphometry (VBM). Twenty-seven of the cognitively preserved patients, 23 of the cognitively impaired patients and 28 controls also underwent fMRI during performance of the n-back working memory task.
No clusters of grey or white matter volume difference were found between the two patient groups. During n-back performance, the cognitively impaired patients showed hypoactivation compared to the cognitively preserved patients in a circumscribed region in the right dorsolateral prefrontal cortex. Both patient groups showed failure of de-activation in the medial frontal cortex compared to the healthy controls.
Cognitive impairment in euthymic bipolar patients appears from this study to be unrelated to structural brain abnormality, but there was some evidence for an association with altered prefrontal function.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objectives
Neuroimaging studies have revealed evidence of brain functional abnormalities in bipolar depressive disorder (BDD) and major depressive disorder (MDD). However, few studies to date have ...compared these two mood disorders directly.
Methods
Matched groups of 26 BDD type I patients, 26 MDD patients and 26 healthy controls underwent functional magnetic resonance imaging (fMRI) while performing the n‐back working memory task. A whole‐brain ANOVA was used to compare the three groups and clusters of significant difference were examined further using region‐of‐interest (ROI) analysis.
Results
The whole‐brain ANOVA revealed a single cluster of significant difference in the medial frontal cortex. The BDD and MDD patients both showed failure to deactivate in this area compared to the controls. The BDD patients showed significantly greater failure of deactivation than the MDD patients, which was not accounted for by differences in severity or chronicity of illness between them.
Conclusions
Failure of deactivation, considered to reflect default mode network dysfunction, is present to a greater extent in bipolar than unipolar depression. The study of this network may be useful in the search for brain markers that distinguish the two disorders.
Epilepsy is a chronic disease of the central nervous system characterized by an electrical imbalance in neurons. It is the second most prevalent neurological disease, with 50 million people affected ...around the world, and 30% of all epilepsies do not respond to available treatments. Currently, the main hypothesis about the molecular processes that trigger epileptic seizures and promote the neurotoxic effects that lead to cell death focuses on the exacerbation of the glutamate pathway and the massive influx of Ca2+ into neurons by different factors. However, other mechanisms have been proposed, and most of them have also been described in other neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, or multiple sclerosis. Interestingly, and mainly because of these common molecular links and the lack of effective treatments for these diseases, some antiseizure drugs have been investigated to evaluate their therapeutic potential in these pathologies. Therefore, in this review, we thoroughly investigate the common molecular pathways between epilepsy and the major neurodegenerative diseases, examine the incidence of epilepsy in these populations, and explore the use of current and innovative antiseizure drugs in the treatment of refractory epilepsy and other neurodegenerative diseases.
Cannabis use typically commences during adolescence, a period during which the brain undergoes profound remodeling in areas that are high in cannabinoid receptors and that mediate cognitive control ...and emotion regulation. It is therefore important to determine the impact of adolescent cannabis use on brain function.
We investigate the impact of adolescent cannabis use on brain function by reviewing the functional magnetic resonance imaging studies in adolescent samples.
We systematically reviewed the literature and identified 13 functional neuroimaging studies in adolescent cannabis users (aged 13 to 18 years) performing working memory, inhibition and reward processing tasks.
The majority of the studies found altered brain function, but intact behavioural task performance in adolescent cannabis users versus controls. The most consistently reported differences were in the frontal-parietal network, which mediates cognitive control. Heavier use was associated with abnormal brain function in most samples. A minority of studies controlled for the influence of confounders that can also undermine brain function, such as tobacco and alcohol use, psychopathology symptoms, family history of psychiatric disorders and substance use.
Emerging evidence shows abnormal frontal-parietal network activity in adolescent cannabis users, particularly in heavier users. Brain functional alterations may reflect a compensatory neural mechanism that enables normal behavioural performance. It remains unclear if cannabis exposure drives these alterations, as substance use and mental health confounders have not been systematically examined.
The default-mode network (DMN) comprises a set of brain regions that show deactivations during performance of attentionally demanding tasks, but also activation during certain processes including ...recall of autobiographical memories and processing information about oneself, among others. However, the DMN is not activated in a homogeneous manner during performance of such tasks, so it is not clear to what extent its activation patterns correspond to deactivation patterns seen during attention-demanding tasks. In this fMRI study we compared patterns of activation in response to an autobiographical memory task to those observed in a self/other-reflection task, and compared both to deactivations observed during the n-back working memory task. Autobiographical recall and self-reflection activated several common DMN areas, which were also deactivated below baseline levels by the n-back task. Activation in the medial temporal lobe was seen during autobiographical recall but not the self/other task, and right angular gyrus activity was specifically linked to other-reflection. ROI analysis showed that most, but not all DMN regions were activated above baseline levels during the autobiographical memory and self-reflection tasks. Our results provide evidence for the usefulness of the autobiographical memory task to study DMN activity and support the notion of interacting subsystems within this network.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder.•The direct comparison between both disorders showed significant reductions in all ...measures in patients with schizophrenia.•Cortical volume decrease in schizophrenia was driven by changes in cortical thickness and surface area, whereas in bipolar disorder was exclusively explained by cortical thinning.•Reduced GI was only found in schizophrenia.
The profiles of cortical abnormalities in schizophrenia and bipolar disorder, and how far they resemble each other, have only been studied to a limited extent. The aim of this study was to identify and compare the changes in cortical morphology associated with these pathologies.
A total of 384 subjects, including 128 patients with schizophrenia, 128 patients with bipolar disorder and 127 sex-age-matched healthy subjects, were examined using cortical surface-based morphology. Four cortical structural measures were studied: cortical volume (CV), cortical thickness (CT), surface area (SA) and gyrification index (GI). Group comparisons for each separate cortical measure were conducted.
At a threshold of P = 0.05 corrected, both patient groups showed significant widespread CV and CT reductions in similar areas compared to healthy subjects. However, the changes in schizophrenia were more pronounced. While CV decrease in bipolar disorder was exclusively explained by cortical thinning, in schizophrenia it was driven by changes in CT and partially by SA. Reduced GI was only found in schizophrenia. The direct comparison between both disorders showed significant reductions in all measures in patients with schizophrenia.
Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder, suggesting that both pathologies may be affected by similar environmental and neurodegenerative factors. However, the exclusive alteration in schizophrenia of metrics related to the geometry and curvature of the brain cortical surface (SA, GI) suggests that this group is influenced by additional neurodevelopmental and genetic factors.
•Individual variability in functional activity during a cognitive task was examined.•Schizophrenia had higher variability in functional activity than bipolar disorder.•Higher variability was ...associated with older age, regardless of diagnosis.•Higher variability was related to illness duration, uniquely in schizophrenia.
Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity.
Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a ‘variability score’.
Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e−09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027).
An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.
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