Dysfunctions of cerebral networks precede recognition memory deficits in early Parkinson's disease

Brain atrophy progression in Parkinson's disease is shaped by connectivity and local vulnerability

Brain atrophy has been reported in the early stages of Parkinson's disease, but there have been few longitudinal studies. How intrinsic properties of the brain, such as anatomical connectivity, local cell-type distribution and gene expression combine to determine the pattern of disease progression also remains unknown. One hypothesis proposes that the disease stems from prion-like propagation of misfolded alpha-synuclein via the connectome that might cause varying degrees of tissue damage based on local properties. Here, we used MRI data from the Parkinson Progression Markers Initiative to map the progression of brain atrophy over 1, 2 and 4 years compared with baseline. We derived atrophy maps for four time points using deformation-based morphometry applied to T₁-weighted MRI from 120 de novo Parkinson's disease patients, 74 of whom had imaging at all four time points (50 Men: 24 Women) and 157 healthy control participants (115 Men: 42 Women). In order to determine factors that may influence neurodegeneration, we related atrophy progression to brain structural and functional connectivity, cell-type expression and gene ontology enrichment analyses. After regressing out the expected age and sex effects associated with normal ageing, we found that atrophy significantly progressed over 2 and 4 years in the caudate, nucleus accumbens, hippocampus and posterior cortical regions. This progression was shaped by both structural and functional brain connectivity. Also, the progression of atrophy was more pronounced in regions with a higher expression of genes related to synapses and was inversely related to the prevalence of oligodendrocytes and endothelial cells. In sum, we demonstrate that the progression of atrophy in Parkinson's disease is in line with the prion-like propagation hypothesis of alpha-synuclein and provide evidence that synapses may be especially vulnerable to synucleinopathy. In addition to identifying vulnerable brain regions, this study reveals different factors that may be implicated in the neurotoxic mechanisms leading to progression in Parkinson's disease. All brain maps generated here are available on request.

Brain connectivity markers in advanced Parkinson's disease for predicting mild cognitive impairment

OBJECTIVES

Mild cognitive impairment (MCI) is a well-defined non-motor manifestation and a harbinger of dementia in Parkinson's disease. This study is to investigate brain connectivity markers of MCI using diffusion tensor imaging and resting-state functional MRI, and help MCI diagnosis in PD patients.

METHODS

We evaluated 131 advanced PD patients (disease duration > 5 years; 59 patients with MCI) and 48 healthy control subjects who underwent a diffusion-weighted and resting-state functional MRI scanning. The patients were randomly assigned to training (n = 100) and testing (n = 31) groups. According to the Brainnetome Atlas, ROI-based structural and functional connectivity analysis was employed to extract connectivity features. To identify features with significant discriminative power for patient classification, all features were put into an all-relevant feature selection procedure within cross-validation loops.

RESULTS

Nine features were identified to be significantly relevant to patient classification. They showed significant differences between PD patients with and without MCI and positively correlated with the MoCA score. Five of them did not differ between general MCI subjects and healthy controls from the ADNI database, which suggested that they could uniquely play a part in the MCI diagnosis of PD. On basis of these relevant features, the random forest model constructed from the training group achieved an accuracy of 83.9% in the testing group, to discriminate patients with and without MCI.

CONCLUSIONS

The results of our study provide preliminary evidence that structural and functional connectivity abnormalities may contribute to cognitive impairment and allow to predict the outcome of MCI diagnosis in PD.

KEY POINTS

• Nine MCI markers were identified using an all-relevant feature selection procedure. • Five of nine markers differed between MCI and NC in PD, but not in general persons. • A random forest model achieved an accuracy of 83.9% for MCI diagnosis in PD.

Multisite non-invasive brain stimulation in Parkinson's disease: A scoping review

BACKGROUND:

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, characterized by cardinal motor symptoms in addition to cognitive impairment. New insights concerning multisite non-invasive brain stimulation effects have been gained, which can now be used to develop innovative treatment approaches.

OBJECTIVE:

Map the researchs involving multisite non-invasive brain stimulation in PD, synthesize the available evidence and discuss future directions.

METHODS:

The databases PubMed, PsycINFO, CINAHL, LILACS and The Cochrane Library were searched from inception until April 2020, without restrictions on the date of publication or the language in which it was published. The reviewers worked in pairs and sequentially evaluated the titles, abstracts and then the full text of all publications identified as potentially relevant.

RESULTS:

Twelve articles met the inclusion criteria. The target brain regions included mainly the combination of a motor and a frontal area, such as stimulation of the primary motor córtex associated with the dorsolateral prefrontal cortex. Most of the trials showed that this modality was only more effective for the motor component, or for the cognitive and/or non-motor, separately.

CONCLUSIONS:

Despite the results being encouraging for the use of the multisite aproach, the indication for PD management should be carried out with caution and deserves scientific deepening.

Impact of Antiepileptic Drugs on Cognition and Neuromagnetic Activity in Childhood Epilepsy With Centrotemporal Spikes: A Magnetoencephalography Study

Objective: Childhood epilepsy with centrotemporal spikes (CECTS), the most common childhood epilepsy, still lacks longitudinal imaging studies involving antiepileptic drugs (AEDs). In order to examine the effect of AEDs on cognition and brain activity. We investigated the neuromagnetic activities and cognitive profile in children with CECTS before and after 1 year of treatment.

Methods: Fifteen children with CECTS aged 6–12 years underwent high-sampling magnetoencephalography (MEG) recordings before treatment and at 1 year after treatment, and 12 completed the cognitive assessment (The Wechsler Intelligence Scale for Children). Next, magnetic source location and functional connectivity (FC) were investigated in order to characterize interictal neuromagnetic activity in the seven frequency sub-bands, including: delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), gamma (30–80 Hz), ripple (80–250 Hz), and fast ripple (250–500 Hz).

Results: After 1 year of treatment, children with CECTS had increased scores on full-scale intelligence quotient, verbal comprehension index (VCI) and perceptual reasoning index (PRI). Alterations of neural activity occurred in specific frequency bands. Source location, in the 30–80 Hz frequency band, was significantly increased in the posterior cingulate cortex (PCC) after treatment. Moreover, FC analysis demonstrated that after treatment, the connectivity between the PCC and the medial frontal cortex (MFC) was enhanced in the 8–12 Hz frequency band. Additionally, the whole-brain network distribution was more dispersed in the 80–250 Hz frequency band.

Conclusion: Intrinsic neural activity has frequency-dependent characteristic. AEDs have impact on regional activity and FC of the default mode network (DMN). Normalization of aberrant DMN in children with CECTS after treatment is likely the reason for improvement of cognitive function.

Hippocampal correlates of episodic memory in Parkinson's disease: A systematic review of magnetic resonance imaging studies

The present review asks whether magnetic resonance imaging (MRI) studies are able to define neural correlates of episodic memory within the hippocampus in Parkinson's disease (PD). Systematic searches were performed in PubMed, Web of Science, Medline, CINAHL, and EMBASE using search terms related to structural and functional MRI (fMRI), the hippocampus, episodic memory, and PD. Risk of bias was assessed for each study using the Newtown-Ottawa Scale. Thirty-nine studies met inclusion criteria; eight fMRI, seven diffusion MRI (dMRI), and 24 structural MRI (14 exploring whole hippocampus and 10 exploring hippocampal subfields). Critical analysis of the literature revealed mixed evidence from functional and dMRI, but stronger evidence from sMRI of the hippocampus as a biomarker for episodic memory impairment in PD. Hippocampal subfield studies most often implicated CA1, CA3/4, and subiculum volume in episodic memory and cognitive decline in PD. Despite differences in imaging methodology, study design, and sample characteristics, MRI studies have helped elucidate an important neural correlate of episodic memory impairment in PD with both clinical and theoretical implications. Natural progression of this work encourages future research on hippocampal subfield function as a potential biomarker of, or therapeutic target for, episodic memory dysfunction in PD.

Episodic Memory Impairment in Parkinson's Disease: Disentangling the Role of Encoding and Retrieval

OBJECTIVE

The source of episodic memory (EM) impairment in Parkinson's disease (PD) is still unclear. In the present study, we sought to quantify specifically encoding, consolidation, and retrieval process deficits in a list-learning paradigm by a novel method, the item-specific deficit approach (ISDA).

METHODS

We applied the ISDA method to the Free and Cued Selective Reminding Test (FCSRT) in a sample of 15 PD patients and 15 healthy participants.

RESULTS

The results revealed differences in free recall performance between PD patients and controls. These patients, however, benefited from cues as much as controls did, and total recall did not differ between groups. When analyzing the ISDA indices for encoding, consolidation, and retrieval deficits, the results showed a general memory deficit, but with a clear focus on encoding and retrieval, as revealed by the sensitivity values. Moreover, controlling for initial learning did not eliminate group effects in retrieval.

CONCLUSIONS

Our findings reveal a mixed pattern in PD patients, with deficits in both encoding and retrieval processes in memory. Also, despite the fact that an encoding dysfunction may explain some of the deficits observed at retrieval, it cannot fully account for the differences, highlighting that both encoding and retrieval factors are necessary to understand memory deficits in PD.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

Cerebellar Contribution to Motor and Non-motor Functions in Parkinson's Disease: A Meta-Analysis of fMRI Findings

Background: Parkinson's disease (PD) results in both motor and non-motor symptoms. Traditionally, the underlying mechanism of PD has been linked to neurodegeneration of the basal ganglia. Yet it does not adequately account for the non-motor symptoms of the disease, suggesting that other brain regions may be involved. One such region is the cerebellum, which is known to be involved, together with the basal ganglia, in both motor and non-motor functions. Many studies have found the cerebellum to be hyperactive in PD patients, a finding that is seldom discussed in detail, and warrants further examination. The current study thus aims to examine quantitively the current literature on the cerebellar involvement in both motor and non-motor functioning in PD. Methods: A meta-analysis of functional neuroimaging literature was conducted with Seed-based D mapping. Only the studies testing functional activation in response to motor and non-motor paradigms in PD and healthy controls (HC) were included in the meta-analysis. Separate analyses were conducted by including only studies with non-motor paradigms, as well as meta-regressions with UPDRS III scores and disease duration. Results: A total of 57 studies with both motor and non-motor paradigms fulfilled our inclusion criteria and were included in the meta-analysis, which revealed hyperactivity in Crus I-II and vermal III in PD patients compared to HC. An analysis including only studies with cognitive paradigms revealed a cluster of increased activity in PD patients encompassing lobule VIIB and VIII. Another meta-analysis including the only 20 studies that employed motor paradigms did not reveal any significant group differences. However, a descriptive analysis of these studies revealed that 60% of them reported cerebellar hyperactivations in PD and included motor paradigm with significant cognitive task demands, as opposed to 40% presenting the opposite pattern and using mainly force grip tasks. The meta-regression with UPDRS III scores found a negative association between motor scores and activation in lobule VI and vermal VII-VIII. No correlation was found with disease duration. Discussion: The present findings suggest that one of the main cerebellar implications in PD is linked to cognitive functioning. The negative association between UPDRS scores and activation in regions implicated in motor functioning indicate that there is less involvement of these areas as the disease severity increases. In contrast, the lack of correlation with disease duration seems to indicate that the cerebellar activity may be a compensatory mechanism to the dysfunctional basal ganglia, where certain sub-regions of the cerebellum are employed to cope with motor demands. Yet future longitudinal studies are needed to fully address this possibility.

Diffusion tensor imaging: a smart move to olfactory pathway imaging; comparative study of chronic sinonasal polyposis patients and normal control

Background

Olfaction is critically important for a good quality of life and incorporated in many physiological domains such as attention, emotion, memory, and airflow motor control. Olfactory researches have been expanded in the last decade due to close relation between the olfactory disorders and different brain diseases. Diagnosis of anosmia and hyposmia are based on history, smell tests, and physical examination which rely on the patient’s response without an objective measure of impairment. This study assessed the value of volumetry and DTI parameters as objective measurements for olfactory dysfunction.

Fourteen patients with chronic sinonasal polyposis for at least 6 months were included in this study; all of them underwent tailored MRI examination including volumetry and DTI for olfactory bulbs and tracts. The results were compared to the same number of age and sex-matched healthy control group.

Results

The study results showed that olfactory bulb and tract (OB/T) volume, FA and ADC could distinguish between patients and healthy controls. Statistically significant differences were noticed between the FA & ADC values of patient and control groups (p < 0.05) and a highly significant one was noticed as regarding the OT volume (p < 0.001).

Conclusion

MR volumetry and DTI parameters can be used as objective measurements for the olfactory dysfunction for patients with chronic sinonasal polyposis.

Accelerated forgetting and verbal memory consolidation process in idiopathic nondement Parkinson's disease

OBJECTIVE

Episodic memory impairment and underlying pathophysiology in Parkinson's Disease (PD) is poorly investigated. Formerly, it was thought to be a secondary effect of impairment in fronto-striatal circuit. However, recent studies hypothesized that there is a dual progression of PD and memory loss is possibly related to posterior cortex rather than frontal. To understand the impairment, underlying mechanisms should be investigated. Although consolidation is one of these mechanisms consolidation phase of episodic memory in PD was not investigated yet. Recently accelerated long term forgetting (ALF) phenomenon is emphasized in consolidation researches.

METHOD

Here it is evaluated the presence of accelerated long-term forgetting in nondemented PD as a consequence of a deficit in consolidation process. 32 patients and 33 controls participated in the study. Turkish Verbal Memory Process Test (VMPT) was applied to both groups. Delayed recall (DR) scores collected after 30 min, one week and six weeks. Forgetting rates were calculated based on these scores.

RESULTS

There was significant difference in DR scores of patients compared to controls in the 30th minute and sixth week. Forgetting rate between 30th minute-1st week did not differ but 1st-6th week was found statistically significant across groups.

CONCLUSIONS

To the best of our knowledge, this is the first study investigating verbal memory consolidation in PD. Results suggested that impairment is possibly related to the late phase of consolidation of verbal memory in neocortex.

Functional MRI in Parkinson's Disease Cognitive Impairment

Functional magnetic resonance imaging (fMRI) has been used to study the neural bases of cognitive deficits in Parkinson's disease for several years. Traditionally, task-based fMRI has been applied to study specific cognitive functions, providing information on disease-related alterations and regarding the physiological bases of normal cognition, the dopaminergic system, and the frontostriatal circuits. More recently, functional connectivity techniques using resting-state fMRI data have been developed. Unconstrained by specific cognitive tasks, these techniques allow assessing whole-brain patterns of connectivity believed to be useful proxies for the underlying functional architecture of the brain. These methods have shown that different types of Parkinson's disease-related cognitive deficits are associated with patterns of altered connectivity within and between resting-state intrinsic connectivity networks. Although methodological standardization and the vulnerability of fMRI techniques to artifacts mandate further technical refinement, early studies provide encouraging results regarding the potential of fMRI-derived parameters for the ultimate goal of individual-subject classification.

Increased brain connectivity and activation after cognitive rehabilitation in Parkinson's disease: a randomized controlled trial

Cognitive rehabilitation programs have demonstrated efficacy in improving cognitive functions in Parkinson's disease (PD), but little is known about cerebral changes associated with an integrative cognitive rehabilitation in PD. To assess structural and functional cerebral changes in PD patients, after attending a three-month integrative cognitive rehabilitation program (REHACOP). Forty-four PD patients were randomly divided into REHACOP group (cognitive rehabilitation) and a control group (occupational therapy). T1-weighted, diffusion weighted and functional magnetic resonance images (fMRI) during resting-state and during a memory paradigm (with learning and recognition tasks) were acquired at pre-treatment and post-treatment. Cerebral changes were assessed with repeated measures ANOVA 2 × 2 for group x time interaction. During resting-state fMRI, the REHACOP group showed significantly increased brain connectivity between the left inferior temporal lobe and the bilateral dorsolateral prefrontal cortex compared to the control group. Moreover, during the recognition fMRI task, the REHACOP group showed significantly increased brain activation in the left middle temporal area compared to the control group. During the learning fMRI task, the REHACOP group showed increased brain activation in the left inferior frontal lobe at post-treatment compared to pre-treatment. No significant structural changes were found between pre- and post-treatment. Finally, the REHACOP group showed significant and positive correlations between the brain connectivity and activation and the cognitive performance at post-treatment. This randomized controlled trial suggests that an integrative cognitive rehabilitation program can produce significant functional cerebral changes in PD patients and adds evidence to the efficacy of cognitive rehabilitation programs in the therapeutic approach for PD.

Modulation of attentional networks by food-related disinhibition

The risk of weight gain is especially related to disinhibition, which indicates the responsiveness to external food stimuli with associated disruptions in eating control. We adapted a food-related version of the attention network task and used functional magnetic resonance imaging to study the effects of disinhibition on attentional networks in 19 normal-weight participants. High disinhibition scores were associated with a rapid reorienting response to food pictures after invalid cueing and with an enhanced alerting effect of a warning cue signalizing the upcoming appearance of a food picture. Imaging data revealed activation of a right-lateralized ventral attention network during reorienting. The faster the reorienting and the higher the disinhibition score, the less activation of this network was observed. The alerting contrast showed activation in visual, temporo-parietal and anterior sites. These modulations of attentional networks by food-related disinhibition might be related to an attentional bias to energy dense and palatable food and increased intake of food in disinhibited individuals.

Verbal Memory in Parkinson's Disease: A Combined DTI and fMRI Study

Background:

While significant progress has been made to determine the functional role of specific gray matter areas underlying verbal memory in Parkinson’s disease (PD), very little is known about the relationship between these regions and their underlying white matter structures.

Objective:

The objectives of this study were (1) to investigate verbal memory, fractional anisotropy and brain activation differences between PD patients and healthy controls (HC), (2) to explore the neuroanatomical and neurofunctional correlates of verbal memory in PD, and (3) to investigate the relationship between these neuroanatomical and neurofunctional verbal memory correlates in PD.

Methods:

Functional magnetic resonance imaging (fMRI) while performing a verbal memory paradigm and diffusion tensor imaging data (DTI), were acquired in 37 PD patients and 15 age-, sex-, and education-matched HC.

Results:

PD patients showed verbal recognition memory impairment, lower fractional anisotropy in the anterior cingulate tract, and lower brain activation in the inferior orbitofrontal cortex compared to HC. Brain activation in the inferior orbitofrontal cortex correlated significantly with verbal recognition memory impairment in PD patients. In addition, a relationship between brain activation in the inferior orbitofrontal cortex and fractional anisotropy of the uncinate fasciculus was found in PD.

Conclusions:

These results reveal that deficits in verbal memory in PD are accompanied by functional brain activation changes, but also have specific structural correlates related to white matter microstructural integrity.

Altered functional connectivity in the default mode network is associated with cognitive impairment and brain anatomical changes in Parkinson's disease

OBJECTIVE

To assess whether functional neural connectivity is disrupted between the regions of the default mode network (DMN) in Parkinson's disease (PD) and how this connectivity is related to cognition, brain gray matter structure and white matter integrity and diffusivity.

METHODS

Thirty-seven PD patients and 16 healthy controls were evaluated, using resting-state functional magnetic resonance imaging (MRI), T1-weighted MRI, diffusion-weighted imaging and a battery of cognitive tests. Functional connectivity between the regions of the DMN, specifically in the precuneus, anterior and posterior cingulate, medial prefrontal and temporal and inferior parietal cortices was assessed with seed-to-voxel connectivity; gray matter volume and white matter values were determined using voxel-based morphometry and tract-based spatial statistics.

RESULTS

Reduced functional connectivity was observed between the posterior cingulate and medial temporal lobe in PD. Lower cognitive performance, gray matter loss in posterior, medial temporal and parietal areas, and fractional anisotropy reduction in the white matter adjacent to DMN regions were also observed in PD patients compared with healthy controls. Lower DMN functional connectivity correlated with lower verbal and visual memory and visual abilities performance in PD. In addition, lower DMN functional connectivity correlated with lower gray matter volume in the posterior cingulate and precuneus, and with lower white matter fractional anisotropy of the inferior longitudinal and posterior cingulate fasciculi in PD.

CONCLUSIONS

By combining different neuroimaging techniques and cognitive data, results showed that functional connectivity alteration between the regions of the DMN is associated with lower cognitive performance and gray and white matter abnormalities in PD.

Default mode network differences between rigidity- and tremor-predominant Parkinson's disease

BACKGROUND

Parkinson's disease (PD) traditionally is characterized by tremor, rigidity, and bradykinesia, although cognitive impairment also is a common symptom. The clinical presentation of PD is heterogeneous and associated with different risk factors for developing cognitive impairment. PD patients with primary akinetic/rigidity (PDAR) are more likely to develop cognitive deficits compared to those with tremor-predominant symptoms (PDT). Because cognitive impairment in PD appears to be related to changes in the default mode network (DMN), this study tested the hypothesis that DMN integrity is different between PDAR and PDT subtypes.

METHOD

Resting state fMRI (rs-fMRI) and whole brain volumetric data were obtained from 17 PDAR, 15 PDT and 24 healthy controls (HCs) using a 3T scanner. PD patients were matched closely to HCs for demographic and cognitive variables, and showed no symptoms of dementia. Voxel-based morphometry (VBM) was used to examine brain gray matter (GM) volume changes between groups. Independent component analysis (ICA) interrogated differences in the DMN among PDAR, PDT, and HC.

RESULTS

There was decreased activity in the left inferior parietal cortex (IPC) and the left posterior cingulate cortex (PCC) within the DMN between PDAR and both HC and PDT subjects, even after controlling for multiple comparisons, but not between PDT and HC. GM volume differences between groups were detected at a lower threshold (p < 0.001, uncorrected). Resting state activity in IPC and PCC were correlated with some measures of cognitive performance in PD but not in HC.

CONCLUSION

This is the first study to demonstrate DMN differences between cognitively comparable PDAR and PDT subtypes. The DMN differences between PD and HC appear to be driven by the PDAR subtype. Further studies are warranted to understand the underlying neural mechanisms and their relevance to clinical and cognitive outcomes in PDAR and PDT subtypes.

Graph theory network function in Parkinson's disease assessed with electroencephalography

OBJECTIVES

To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D).

METHODS

EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance.

RESULTS

Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD.

CONCLUSIONS

Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD.

SIGNIFICANCE

These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology.

Resting-state functional brain networks in Parkinson's disease

The network approach is increasingly being applied to the investigation of normal brain function and its impairment. In the present review, we introduce the main methodological approaches employed for the analysis of resting‐state neuroimaging data in Parkinson's disease studies. We then summarize the results of recent studies that used a functional network perspective to evaluate the changes underlying different manifestations of Parkinson's disease, with an emphasis on its cognitive symptoms. Despite the variability reported by many studies, these methods show promise as tools for shedding light on the pathophysiological substrates of different aspects of Parkinson's disease, as well as for differential diagnosis, treatment monitoring and establishment of imaging biomarkers for more severe clinical outcomes.

Hemispheric asymmetry of electroencephalography-based functional brain networks

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Magnetic resonance imaging markers for early diagnosis of Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by selective and progressive degeneration, as well as loss of dopaminergic neurons in the substantia nigra. In PD, approximately 60-70% of nigrostriatal neurons are degenerated and 80% of content of the striatal dopamine is reduced before the diagnosis can be established according to widely accepted clinical diagnostic criteria. This condition describes a stage of disease called “prodromal”, where non-motor symptoms, such as olfactory dysfunction, constipation, rapid eye movement behaviour disorder, depression, precede motor sign of PD. Detection of prodromal phase of PD is becoming an important goal for determining the prognosis and choosing a suitable treatment strategy. In this review, we present some non-invasive instrumental approaches that could be useful to identify patients in the prodromal phase of PD or in an early clinical phase, when the first motor symptoms begin to be apparent. Conventional magnetic resonance imaging (MRI) and advanced MRI techniques, such as magnetic resonance spectroscopy imaging, diffusion-weighted and diffusion tensor imaging and functional MRI, are useful to differentiate early PD with initial motor symptoms from atypical parkinsonian disorders, thus, making easier early diagnosis. Functional MRI and diffusion tensor imaging techniques can show abnormalities in the olfactory system in prodromal PD.

Widespread increase of functional connectivity in Parkinson's disease with tremor: a resting-state FMRI study

Parkinson’s disease (PD) is a clinically heterogeneous disease in the symptomatology dominated by tremor, akinesia, or rigidity. Focusing on PD patients with tremor, this study investigated their discoordination patterns of spontaneous brain activity by combining voxel-wise centrality, seed-based functional connectivity, and network efficiency methods. Sixteen patients and 20 matched healthy controls (HCs) were recruited and underwent structural and resting-state functional MRI scan. Compared with the HCs, the patients exhibited increased centrality in the frontal, parietal, and occipital regions while decreased centrality in the cerebellum anterior lobe and thalamus. Seeded at these regions, a distributed network was further identified that encompassed cortical (default mode network, sensorimotor cortex, prefrontal and occipital areas) and subcortical (thalamus and basal ganglia) regions and the cerebellum and brainstem. Graph-based analyses of this network revealed increased information transformation efficiency in the patients. Moreover, the identified network correlated with clinical manifestations in the patients and could distinguish the patients from HCs. Morphometric analyses revealed decreased gray matter volume in multiple regions that largely accounted for the observed functional abnormalities. Together, these findings provide a comprehensive view of network disorganization in PD with tremor and have important implications for understanding neural substrates underlying this specific type of PD.

Functional brain networks and cognitive deficits in Parkinson's disease

Graph-theoretical analyses of functional networks obtained with resting-state functional magnetic resonance imaging (fMRI) have recently proven to be a useful approach for the study of the substrates underlying cognitive deficits in different diseases. We used this technique to investigate whether cognitive deficits in Parkinson's disease (PD) are associated with changes in global and local network measures. Thirty-six healthy controls (HC) and 66 PD patients matched for age, sex, and education were classified as having mild cognitive impairment (MCI) or not based on performance in the three mainly affected cognitive domains in PD: attention/executive, visuospatial/visuoperceptual (VS/VP), and declarative memory. Resting-state fMRI and graph theory analyses were used to evaluate network measures. We have found that patients with MCI had connectivity reductions predominantly affecting long-range connections as well as increased local interconnectedness manifested as higher measures of clustering, small-worldness, and modularity. The latter measures also tended to correlate negatively with cognitive performance in VS/VP and memory functions. Hub structure was also reorganized: normal hubs displayed reduced centrality and degree in MCI PD patients. Our study indicates that the topological properties of brain networks are changed in PD patients with cognitive deficits. Our findings provide novel data regarding the functional substrate of cognitive impairment in PD, which may prove to have value as a prognostic marker.

Facilitative effects of bi-hemispheric tDCS in cognitive deficits of Parkinson disease patients

Parkinson's disease (PD) is a progressive neurodegenerative disorder, primarily characterized by motor symptoms such as tremor, rigidity, bradykinesia, stiffness, slowness and impaired equilibrium. Although the motor symptoms have been the focus in PD, slight cognitive deficits are commonly found in non-demented and non-depressed PD patients, even in early stages of the disease, which have been linked to the subsequent development of pathological dementia. Thus, strongly reducing the quality of life (QoL). Both levodopa therapy and deep brain stimulation (DBS) have yield controversial results concerning the cognitive symptoms amelioration in PD patients. That does not seems to be the case with transcranial direct current stimulation (tDCS), although better stimulation parameters are needed. Therefore we hypothesize that simultaneously delivering cathodal tDCS (or ctDCS), over the right prefrontal cortex delivered with anodal tDCS (or atDCS) to left prefrontal cortex could be potentially beneficial for PD patients, either by mechanisms of homeostatic plasticity and by increases in the extracellular dopamine levels over the striatum.

Functional connectivity within the default mode network is associated with saccadic accuracy in Parkinson's disease: a resting-state FMRI and videooculographic study

In addition to the skeleto-motor deficits, patients with Parkinson's disease (PD) frequently present with oculomotor dysfunctions such as impaired smooth pursuit and saccadic abnormalities. There is increasing evidence for an impaired cortical function to be responsible for oculomotor deficits that are associated with lack of inhibitory control; however, these pathomechanisms still remain poorly understood. By means of "task-free" resting-state functional magnetic resonance imaging (rs-fMRI), functional connectivity changes in PD within the default mode network (DMN) have been reported. The aim of this study was to investigate whether altered functional connectivity within the DMN was correlated with oculomotor parameter changes in PD. Twelve PD patients and 13 matched healthy controls underwent rs-fMRI at 1.5 T and videooculography (VOG) using Eye-Link-System. Rs-fMRI seed-based region-to-region connectivity analysis was performed, including medial prefrontal cortex (mPFC), medial temporal lobe (MTL), posterior cingulate cortex (PCC), and hippocampal formation (HF); while VOG examination comprised ocular reactive saccades, smooth pursuit, and executive tests. Rs-fMRI analysis demonstrated a decreased region-to-region functional connectivity between mPFC and PCC as well as increased connectivity between bilateral HF in PD compared with controls. In VOG, patients and controls differed in terms of executive tests outcome, smooth pursuit eye movement, and visually guided reactive saccades but not in peak eye velocity. A significant relationship was observed between saccadic accuracy and functional connectivity strengths between MTL and PCC. These results suggest that PD-associated changes of DMN connectivity are correlated with PD-associated saccadic hypometria, in particular in the vertical direction.

Resting-state networks in Alzheimer's disease and Parkinson's disease

While there is good evidence for altered resting-state networks, particularly the default mode network (DMN), in both Alzheimer's disease (AD) and amnestic mild cognitive impairment preceding AD, there are rather conflicting data on changes in the DMN in Parkinson's disease (PD) and PD with cognitive impairment. This paper will focus on DMN study results, particularly in PD, as assessed by functional MRI.

Striatal volume is related to phonemic verbal fluency but not to semantic or alternating verbal fluency in early Parkinson's disease

Verbal fluency impairments are frequent in Parkinson’s disease (PD) and they may be present already at early stages. Semantic fluency impairment is associated with Parkinson’s disease dementia and temporal, frontal and cerebellar cortical changes. Few studies have addressed cerebral structural correlates of different verbal fluency tasks in early stage PD. We therefore studied gray matter volumes of T1-weighted MRI images using voxel-based morphometry in relation to semantic, phonemic, and alternating verbal fluency in younger (mean age <65 years), early stage (mean disease duration <3 years), non-demented PD patients (n = 28) and healthy controls (n = 27). We found a significant association between worse phonemic fluency and smaller striatal, namely right caudate gray matter volume in the PD group only (family-wise error corrected p = 0.007). Reduced semantic fluency was associated with smaller gray matter volumes in left parietal cortex (p = 0.037) and at trend level with smaller bilateral cerebellum gray matter volume across groups (p = 0.062), but not in the separate PD or control groups. There were no significant relationships between alternating fluency and gray matter volumes in the whole sample or in the groups separately. The fact that phonemic fluency, but not semantic or alternating fluency, was associated with caudate gray matter volume at early stage PD suggests that different fluency tasks rely on different neural substrates, and that language networks supporting semantic search and verbal-semantic switching are unrelated to brain gray matter volume at early disease stages in PD.

Magnetic resonance imaging: a biomarker for cognitive impairment in Parkinson's disease?

Dementia is a frequent and disabling complication of Parkinson's disease (PD). Clinicians and researchers lack a biomarker capable of tracking the structural and functional changes that underlie the evolution of cognitive dysfunction in PD. Magnetic resonance imaging (MRI) has been adopted as a biomarker in natural history and interventional studies of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), but its utility as a biomarker for PD and Parkinson's disease dementia (PDD) is unclear. In this review, the authors summarize the studies that have used MRI to investigate cognitive decline in PD, outline limitations of those studies, and suggest directions for future research. PD dementia is associated with extensive cortical atrophy, which may be quantified with structural MRI. More promisingly, patterns of atrophy may be present in those who have PD with MCI (PD-MCI). Subcortical white matter tract degeneration is detectable early in the disease with diffusion tensor imaging and may precede changes observed on conventional structural MRI. Although less well studied, other MR techniques, such as functional MRI, MR perfusion imaging with arterial spin labeling, and MR spectroscopy, have demonstrated differences in activation and metabolism between PD and PDD. In this review, the ability to compare studies was limited by the heterogeneity of study populations, cognitive testing methods, and imaging protocols. Future work should adopt agreed scan protocols, should be adequately powered, and should use carefully phenotyped patients to fully maximize the contribution of MRI as a biomarker for PDD.

Synthesis of novel cognition enhancers with pyrazolo[5,1-c][1,2,4]benzotriazine core acting at γ-aminobutyric acid type A (GABA(A)) receptor

Memory dysfunction associated with aging, neurodegenerative and psychiatric disorders represents an increasing medical need. Advances in research exploring the biological mechanisms underlying learning and memory have opened new potential approaches for development of memory-enhancing therapies addressed to selective neuronal targets. In this work, we synthesized some derivatives with a pyrazolo[5,1-c][1,2,4]benzotriazine core to identify ligands on GABAA receptors subtype (benzodiazepine site on GABAA-receptor) endowed with the potential of enhancing cognition activity without the side effects usually associated with non-selective GABAA modulators. In fact, there is much evidence that GABAA-R (γ-aminobutyric acid, type A receptor) subtype ligands have relevance in learning and memory. In vitro and in vivo tests have been performed. Pharmacological data indicate that compounds 7, 13, 14 and 22 act as dual functional modulators of GABAA-Rs (promnemonic and anxiolytic agents) while only compounds 3 and 10 stand out as selectively displaying good antiamnesic and procognitive activity (1 and 3 mg/kg, respectively).

A critique of Tensor Probabilistic Independent Component Analysis: implications and recommendations for multi-subject fMRI data analysis

Tensor Probabilistic Independent Component Analysis (TPICA) is a popular tool for analyzing multi-subject fMRI data (voxels×time×subjects) because of TPICA's supposed robustness. In this paper, we show that TPICA is not as robust as its authors claim. Specifically, we discuss why TPICA's overall objective is questionable, and we present some flaws related to the iterative nature of the TPICA algorithm. To demonstrate the relevance of these issues, we present a simulation study that compares TPICA versus Parallel Factor Analysis (Parafac) for analyzing simulated multi-subject fMRI data. Our simulation results demonstrate that TPICA produces a systematic bias that increases with the spatial correlation between the true components, and that the quality of the TPICA solution depends on the chosen ICA algorithm and iteration scheme. Thus, TPICA is not robust to small-to-moderate deviations from the model's spatial independence assumption. In contrast, Parafac produces unbiased estimates regardless of the spatial correlation between the true components, and Parafac with orthogonality-constrained voxel maps produces smaller biases than TPICA when the true voxel maps are moderately correlated. As a result, Parafac should be preferred for the analysis multi-subject fMRI data where the underlying components may have spatially overlapping voxel activation patterns.