A circuit-based approach to modulate hypersexuality in Parkinson's disease.

AIM: Impulse-control disorder is a common neuropsychiatric complication in Parkinson's disease (PD) under dopamine replacement therapy. Prior studies tested the balance between enhanced desire towards reward and cognitive control deficits, hypothesized to be biased towards the former in impulse control disorders. We provide evidence for this hypothesis by measuring behavioral and neural patterns behind the influence of sexual desire over response inhibition and tools towards functional restoration using repetitive transcranial stimulation in patients with hypersexuality as predominant impulsive disorder. METHODS: The effect of sexual cues on inhibition was measured with a novel erotic stop-signal task under on and off dopaminergic medication. Task-related functional and anatomical connectivity models were estimated in 16 hypersexual and 17 nonhypersexual patients with PD as well as in 17 healthy controls. Additionally, excitatory neuromodulation using intermittent theta-burst stimulation (sham-controlled) was applied over the pre-supplementary motor area in 20 additional hypersexual patients with PD aiming to improve response inhibition. RESULTS: Compared with their nonhypersexual peers, patients with hypersexuality recruited caudate, pre-supplementary motor area, ventral tegmental area, and anterior cingulate cortex while on medication. Reduced connectivity was found between pre-supplementary motor area and caudate nucleus in hypersexual compared with nonhypersexual patients (while medicated), a result paralleled by compensatory enhanced anatomical connectivity. Furthermore, stimulation over the pre-supplementary motor area improved response inhibition in hypersexual patients with PD when exposed to sexual cues. CONCLUSION: This study, therefore, has identified a specific fronto-striatal and mesolimbic circuitry underlying uncontrolled sexual responses in medicated patients with PD where cortical neuromodulation halts its expression.

Bilateral staged magnetic resonance-guided focused ultrasound thalamotomy for the treatment of essential tremor: a case series study.

BACKGROUND: Unilateral magnetic resonance-guided focused ultrasound (FUS) thalamotomy is efficacious for the treatment of medically refractory essential tremor (ET). Viability of bilateral FUS ablation is unexplored. METHODS: Patients diagnosed with medically refractory ET and previously treated with unilateral FUS thalamotomy at least 5 months before underwent bilateral treatment. The timepoints were baseline (before first thalamotomy) and FUS1 and FUS2 (4 weeks before and 6 months after second thalamotomy, respectively). The primary endpoint was safety. Efficacy was assessed through the Clinical Rating Scale for Tremor (CRST), which includes subscales for tremor examination (part A), task performance (part B) and tremor-related disability (part C). RESULTS: Nine patients were treated. No permanent adverse events were registered. Six patients presented mild gait instability and one dysarthria, all resolving within the first few weeks. Three patients reported perioral hypoesthesia, resolving in one case. Total CRST score improved by 71% from baseline to FUS2 (from 52.3±12 to 15.5±9.4, p<0.001), conveying a 67% reduction in bilateral upper limb A+B (from 32.3±7.8 to 10.8±7.3, p=0.001). Part C decreased by 81% (from 16.4±3.6 to 3.1±2.9, p<0.001). Reduction in head and voice tremor was 66% (from 1.2±0.44 to 0.4±0.54, p=0.01) and 45% (from 1.8±1.1 to 1±0.8, p=0.02), respectively. CONCLUSION: Bilateral staged FUS thalamotomy for ET is feasible and might be safe and effective. Voice and head tremor might also improve. A controlled study is warranted.

Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T1-weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women.

Molecular imaging to track Parkinson's disease and atypical parkinsonisms: New imaging frontiers.

Molecular imaging has proven to be a powerful tool for investigation of parkinsonian disorders. One current challenge is to identify biomarkers of early changes that may predict the clinical trajectory of parkinsonian disorders. Exciting new tracer developments hold the potential for in vivo markers of underlying pathology. Herein, we provide an overview of molecular imaging advances and how these approaches help us to understand PD and atypical parkinsonisms. © 2016 International Parkinson and Movement Disorder Society.

Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment.

Synaptic dysfunction is a core deficit in Alzheimer's disease, preceding hallmark pathological abnormalities. Resting-state magnetoencephalography (MEG) was used to assess whether functional connectivity patterns, as an index of synaptic dysfunction, are associated with CSF biomarkers [i.e., phospho-tau (p-tau) and amyloid beta (Aß42) levels]. We studied 12 human subjects diagnosed with mild cognitive impairment due to Alzheimer's disease, comparing those with normal and abnormal CSF levels of the biomarkers. We also evaluated the association between aberrant functional connections and structural connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impact of cognitive deficits and CSF variables on network disorganization. One-third of the patients converted to Alzheimer's disease during a follow-up period of 2.5 years. Patients with abnomal CSF p-tau and Aß42 levels exhibited both reduced and increased functional connectivity affecting limbic structures such as the anterior/posterior cingulate cortex, orbitofrontal cortex, and medial temporal areas in different frequency bands. A reduction in posterior cingulate functional connectivity mediated by p-tau was associated with impaired axonal integrity of the hippocampal cingulum. We noted that several connectivity abnormalities were predicted by CSF biomarkers and cognitive scores. These preliminary results indicate that CSF markers of amyloid deposition and neuronal injury in early Alzheimer's disease associate with a dual pattern of cortical network disruption, affecting key regions of the default mode network and the temporal cortex. MEG is useful to detect early synaptic dysfunction associated with Alzheimer's disease brain pathology in terms of functional network organization. SIGNIFICANCE STATEMENT: In this preliminary study, we used magnetoencephalography and an integrative approach to explore the impact of CSF biomarkers, neuropsychological scores, and white matter structural abnormalities on neural function in mild cognitive impairment. Disruption in functional connectivity between several pairs of cortical regions associated with abnormal levels of biomarkers, cognitive deficits, or with impaired axonal integrity of hippocampal tracts. Amyloid deposition and tau protein-related neuronal injury in early Alzheimer's disease are associated with synaptic dysfunction and a dual pattern of cortical network disorganization (i.e., desynchronization and hypersynchronization) that affects key regions of the default mode network and temporal areas.

Multimodal description of whole brain connectivity: A comparison of resting state MEG, fMRI, and DWI.

Structural and functional connectivity (SC and FC) have received much attention over the last decade, as they offer unique insight into the coordination of brain functioning. They are often assessed independently with three imaging modalities: SC using diffusion-weighted imaging (DWI), FC using functional magnetic resonance imaging (fMRI), and magnetoencephalography/electroencephalography (MEG/EEG). DWI provides information about white matter organization, allowing the reconstruction of fiber bundles. fMRI uses blood-oxygenation level-dependent (BOLD) contrast to indirectly map neuronal activation. MEG and EEG are direct measures of neuronal activity, as they are sensitive to the synchronous inputs in pyramidal neurons. Seminal studies have targeted either the electrophysiological substrate of BOLD or the anatomical basis of FC. However, multimodal comparisons have been scarcely performed, and the relation between SC, fMRI-FC, and MEG-FC is still unclear. Here we present a systematic comparison of SC, resting state fMRI-FC, and MEG-FC between cortical regions, by evaluating their similarities at three different scales: global network, node, and hub distribution. We obtained strong similarities between the three modalities, especially for the following pairwise combinations: SC and fMRI-FC; SC and MEG-FC at theta, alpha, beta and gamma bands; and fMRI-FC and MEG-FC in alpha and beta. Furthermore, highest node similarity was found for regions of the default mode network and primary motor cortex, which also presented the highest hubness score. Distance was partially responsible for these similarities since it biased all three connectivity estimates, but not the unique contributor, since similarities remained after controlling for distance.

Dynamic risk control by human nucleus accumbens.

Real-world decisions about reward often involve a complex counterbalance of risk and value. Although the nucleus accumbens has been implicated in the underlying neural substrate, its criticality to human behaviour remains an open question, best addressed with interventional methodology that probes the behavioural consequences of focal neural modulation. Combining a psychometric index of risky decision-making with transient electrical modulation of the nucleus accumbens, here we reveal profound, highly dynamic alteration of the relation between probability of reward and choice during therapeutic deep brain stimulation in four patients with treatment-resistant psychiatric disease. Short-lived phasic electrical stimulation of the region of the nucleus accumbens dynamically altered risk behaviour, transiently shifting the psychometric function towards more risky decisions only for the duration of stimulation. A critical, on-line role of human nucleus accumbens in dynamic risk control is thereby established.

Alpha-band hypersynchronization in progressive mild cognitive impairment: a magnetoencephalography study.

People with mild cognitive impairment (MCI) show a high risk to develop Alzheimer's disease (AD; Petersen et al., 2001). Nonetheless, there is a lack of studies about how functional connectivity patterns may distinguish between progressive (pMCI) and stable (sMCI) MCI patients. To examine whether there were differences in functional connectivity between groups, MEG eyes-closed recordings from 30 sMCI and 19 pMCI subjects were compared. The average conversion time of pMCI was 1 year, so they were considered as fast converters. To this end, functional connectivity in different frequency bands was assessed with phase locking value in source space. Then the significant differences between both groups were correlated with neuropsychological scores and entorhinal, parahippocampal, and hippocampal volumes. Both groups did not differ in age, gender, or educational level. pMCI patients obtained lower scores in episodic and semantic memory and also in executive functioning. At the structural level, there were no differences in hippocampal volume, although some were found in left entorhinal volume between both groups. Additionally, pMCI patients exhibit a higher synchronization in the alpha band between the right anterior cingulate and temporo-occipital regions than sMCI subjects. This hypersynchronization was inversely correlated with cognitive performance, both hippocampal volumes, and left entorhinal volume. The increase in phase synchronization between the right anterior cingulate and temporo-occipital areas may be predictive of conversion from MCI to AD.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered.

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical connections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 different brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very-large-scale integration circuits analyses, shows that functional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrangements for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal-ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organizations that can only be identified when the physical locations of the nodes are included in the analysis.

Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of conditions of mild cognitive impairment.

Whole brain resting state connectivity is a promising biomarker that might help to obtain an early diagnosis in many neurological diseases, such as dementia. Inferring resting-state connectivity is often based on correlations, which are sensitive to indirect connections, leading to an inaccurate representation of the real backbone of the network. The precision matrix is a better representation for whole brain connectivity, as it considers only direct connections. The network structure can be estimated using the graphical lasso (GL), which achieves sparsity through l1-regularization on the precision matrix. In this paper, we propose a structural connectivity adaptive version of the GL, where weaker anatomical connections are represented as stronger penalties on the corresponding functional connections. We applied beamformer source reconstruction to the resting state MEG recordings of 81 subjects, where 29 were healthy controls, 22 were single-domain amnestic Mild Cognitive Impaired (MCI), and 30 were multiple-domain amnestic MCI. An atlas-based anatomical parcellation of 66 regions was obtained for each subject, and time series were assigned to each of the regions. The fiber densities between the regions, obtained with deterministic tractography from diffusion-weighted MRI, were used to define the anatomical connectivity. Precision matrices were obtained with the region specific time series in five different frequency bands. We compared our method with the traditional GL and a functional adaptive version of the GL, in terms of log-likelihood and classification accuracies between the three groups. We conclude that introducing an anatomical prior improves the expressivity of the model and, in most cases, leads to a better classification between groups.

Temporal ordering of cognitive impairment in Parkinson's disease patients based on disease progression models.

INTRODUCTION: Identifying Parkinson's disease (PD) patients at risk of cognitive decline is crucial for enhancing clinical interventions. While several models predicting cognitive decline in PD exist, a new machine learning framework called disease progression models (DPMs) offers a data-driven approach to understand disease evolution. METHODS: We enrolled 423 PD patients and 196 healthy controls from the Parkinson's Progression Markers Initiative (PPMI). Our study encompassed a range of biomarkers, including motor, neurocognitive, and neuroimaging evaluations at baseline and annually. A methodology was employed to select optimal combinations of biomarkers for constructing DPMs with superior predictive capabilities for both diagnosing and estimating conversion times toward cognitive decline. RESULTS: At baseline, the approach showed excellent performance in identifying individuals at high risk of cognitive decline within the first five years. Furthermore, the proposed timeline from cognitive impairment to dementia was also used to explore clinical events such as the onset of cognitive impairment, the development of dementia or amyloid pathology. The presence of amyloid pathology did not alter the progression of cognitive impairment among PD patients. CONCLUSIONS: Neuropsychological measures and certain biomarkers, including cerebrospinal fluid (CSF) amyloid beta 42 (Aß42) and dopamine transporter deficits, can be used to predict cognitive decline and estimate a timeline from cognitive impairment to dementia, with amyloid pathology preceding the onset of dementia in many cases. Our DPMs suggested that the profiles of CSF Aß42 and phosphorylated tau in PD patients may differ from those in aging patients and those with Alzheimer's disease.

Skull Density Ratio as Arm-Allocation Parameter for a Controlled Focused Ultrasound Trial in Parkinson's Disease.

BACKGROUND: MR-guided focused ultrasound (FUS) thermoablation is an established therapy for movement disorders. FUS candidates must meet a predefined threshold of skull density ratio (SDR), a parameter that accounts for the efficiency in reaching ablative temperatures. Randomized sham-controlled trials to provide definitive therapeutic evidence employ pure randomization of subjects into active treatment or control arms. The latter design has several general limitations. OBJECTIVE: To demonstrate that SDR values are not associated with clinically and demographically relevant variables in patients with Parkinson's disease (PD). This in turn would allow using SDR as an arm-allocation parameter, separating patients who will receive active FUS treatment and best medical management treatment (BMT). METHODS: We studied a cohort of 215 PD patients who were candidates for FUS subthalamotomy to determine if the SDR was correlated with demographic or clinical variables that could introduce bias for group allocation in a controlled trial. RESULTS: SDR was unassociated with age, gender, and clinical motor features nor with levodopa daily dose in our cohort of PD patients. A negative association with age was found for the female subgroup. CONCLUSIONS: Our results show that in a PD population considered for FUS subthalamotomy treatment, the SDR may be a valid group-allocation parameter. This could be considered as the basis for a controlled study comparing FUS subthalamotomy vs BMT.

Prospective Long-term Follow-up of Focused Ultrasound Unilateral Subthalamotomy for Parkinson Disease.

BACKGROUND AND OBJECTIVES: Unilateral magnetic resonance-guided focused ultrasound subthalamotomy (FUS-STN) has been shown to improve the cardinal motor features of Parkinson disease (PD). Whether this effect is sustained is not known. This study aims to report the long-term outcome of patients with PD treated with unilateral FUS-STN. METHODS: We conducted a prospective open-label study of patients with asymmetrical PD who underwent unilateral FUS-STN. All patients were evaluated up to 36 months after treatment. The primary outcome was the difference from baseline to 36 months after FUS-STN in the score of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor part (III) for the treated hemibody in the off-medication state. The safety outcome included all adverse events occurring during follow-up. Secondary outcomes were the change in the MDS-UPDRS III score on-medication; subscores of rigidity, bradykinesia, tremor, and axial features; total MDS-UPDRS III; and the MDS-UPDRS part IV. Functional disability and quality of life were assessed using the MDS-UPDRS II and the PDQ39, respectively. Patient impression of change and satisfaction with the treatment were self-assessed. The Wilcoxon signed-rank test with subsequent Bonferroni's correction was used for data analysis. RESULTS: Thirty-two patients with PD were evaluated at 36 months after treatment. The mean (±SD) age at baseline was 56.0 ± 10.1 years, with a mean disease duration of 6.8 ± 2.8 years. The MDS-UPDRS III score for the treated hemibody off-medication was improved by 52.3% from baseline to 3 years (score reduction from 19.0 ± 3.2 to 8.9 ± 3.3, 95% CI 8.7 to 11.6, p < 0.001), and all specific motor features were improved from baseline. No disabling or delayed adverse events were reported. The total MDS-UPDRS III off-medication score was 22.9% lower at 3 years than before treatment (36.8 ± 7.4 vs 27.4 ± 6.2, 95% CI 6.0 to 11.5, p < 0.001). The MDS-UPDRS II, IV, and PDQ39 scores and levodopa dose were equivalent to those at baseline. DISCUSSION: The benefit of unilateral FUS-STN on PD motor features is sustained in the long term. FUS-STN contributes to better clinical control over several years of evolution. NCT02912871/03454425. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence on the utility of focused ultrasound unilateral subthalamotomy in the treatment of people with Parkinson disease.

Transcranial Magnetic Resonance-Guided Focused Ultrasound Thalamotomy in Essential Tremor: A Comprehensive Lesion Characterization.

BACKGROUND: Transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) thalamotomy is a novel and effective treatment for controlling tremor in essential tremor patients. OBJECTIVE: To provide a comprehensive characterization of the radiological, topographical, and volumetric aspects of the tcMRgFUS thalamic lesion, and to quantify how they relate to the clinical outcomes. METHODS: In this study, clinical and radiological data from forty patients with medically-refractory essential tremor treated with unilateral tcMRgFUS thalamotomy were retrospectively analyzed. Treatment efficacy was assessed with Clinical Rating Scale for Tremor (CRST). Lesions were manually segmented on T1, T2, and susceptibility-weighted images, and 3-dimensional topographical analysis was then carried out. Statistical comparisons were performed using nonparametric statistics. RESULTS: The greatest clinical improvement was correlated with a more inferior and posterior lesion, a bigger lesion volume, and percentage of the ventral intermediate nucleus covered by the lesion; whereas, the largest lesions accounted for the occurrence of gait imbalance. Furthermore, the volume of the lesion was significantly predicted by the number of sonications surpassing 52°C. CONCLUSION: Here we provide a comprehensive characterization of the thalamic tcMRgFUS lesion including radiological and topographical analysis. Our results indicate that the location and volume of the lesion were significantly associated with the clinical outcome and that mid-temperatures may be responsible for the lesion size. This could serve ultimately to improve targeting and judgment and to optimize clinical outcome of tcMRgFUS thalamotomy.

Neuroimaging biomarkers for clinical trials in atypical parkinsonian disorders: Proposal for a Neuroimaging Biomarker Utility System.

INTRODUCTION: Therapeutic strategies targeting protein aggregations are ready for clinical trials in atypical parkinsonian disorders. Therefore, there is an urgent need for neuroimaging biomarkers to help with the early detection of neurodegenerative processes, the early differentiation of the underlying pathology, and the objective assessment of disease progression. However, there currently is not yet a consensus in the field on how to describe utility of biomarkers for clinical trials in atypical parkinsonian disorders. METHODS: To promote standardized use of neuroimaging biomarkers for clinical trials, we aimed to develop a conceptual framework to characterize in more detail the kind of neuroimaging biomarkers needed in atypical parkinsonian disorders, identify the current challenges in ascribing utility of these biomarkers, and propose criteria for a system that may guide future studies. RESULTS: As a consensus outcome, we describe the main challenges in ascribing utility of neuroimaging biomarkers in atypical parkinsonian disorders, and we propose a conceptual framework that includes a graded system for the description of utility of a specific neuroimaging measure. We included separate categories for the ability to accurately identify an intention-to-treat patient population early in the disease (Early), to accurately detect a specific underlying pathology (Specific), and the ability to monitor disease progression (Progression). DISCUSSION: We suggest that the advancement of standardized neuroimaging in the field of atypical parkinsonian disorders will be furthered by a well-defined reference frame for the utility of biomarkers. The proposed utility system allows a detailed and graded description of the respective strengths of neuroimaging biomarkers in the currently most relevant areas of application in clinical trials.

Influence of the APOE ε4 allele and mild cognitive impairment diagnosis in the disruption of the MEG resting state functional connectivity in sources space.

The apolipoprotein E (APOE) ε4 allele constitutes the major genetic risk for the development of late onset Alzheimer's disease (AD). However, its influence on the neurodegeneration that occurs in early AD remains unresolved. In this study, the resting state magnetoencephalography(MEG) recordings were obtained from 27 aged healthy controls and 36 mild cognitive impairment (MCI) patients. All participants were divided into carriers and non-carriers of the ε4 allele. We have calculated the functional connectivity (FC) in the source space along brain regions estimated using the Harvard-Oxford atlas and in the classical bands. Then, a two way ANOVA analysis (diagnosis and APOE) was performed in each frequency band. The diagnosis effect consisted of a diminished FC within the high frequency bands in the MCI patients, affecting medial temporal and parietal regions. The APOE effect produced a decreased long range FC in delta band in ε4 carriers. Finally, the interaction effect showed that the FC pattern of the right frontal-temporal region could be reflecting a compensatory/disruption process within the ε4 allele carriers. Several of these results correlated with cognitive decline and neuropsychological performance. The present study characterizes how the APOE ε4 allele and MCI status affect the brain's functional organization by analyzing the FC patterns in MEG resting state in the sources space. Therefore a combination of genetic, neuropsychological, and neurophysiological information might help to detect MCI patients at higher risk of conversion to AD and asymptomatic subjects at higher risk of developing a manifest cognitive deterioration.

Functional brain networks: great expectations, hard times and the big leap forward.

Many physical and biological systems can be studied using complex network theory, a new statistical physics understanding of graph theory. The recent application of complex network theory to the study of functional brain networks has generated great enthusiasm as it allows addressing hitherto non-standard issues in the field, such as efficiency of brain functioning or vulnerability to damage. However, in spite of its high degree of generality, the theory was originally designed to describe systems profoundly different from the brain. We discuss some important caveats in the wholesale application of existing tools and concepts to a field they were not originally designed to describe. At the same time, we argue that complex network theory has not yet been taken full advantage of, as many of its important aspects are yet to make their appearance in the neuroscience literature. Finally, we propose that, rather than simply borrowing from an existing theory, functional neural networks can inspire a fundamental reformulation of complex network theory, to account for its exquisitely complex functioning mode.

White matter damage disorganizes brain functional networks in amnestic mild cognitive impairment.

Although progressive functional brain network disruption has been one of the hallmarks of Alzheimer's Disease, little is known about the origin of this functional impairment that underlies cognitive symptoms. We investigated how the loss of white matter (WM) integrity disrupts the organization of the functional networks at different frequency bands. The analyses were performed in a sample of healthy elders and mild cognitive impairment (MCI) subjects. Spontaneous brain magnetic activity (measured with magnetoencephalography) was characterized with phase synchronization analysis, and graph theory was applied to the functional networks. We identified WM areas (using diffusion weighted magnetic resonance imaging) that showed a statistical dependence between the fractional anisotropy and the graph metrics. These regions are part of an episodic memory network and were also related to cognitive functions. Our data support the hypothesis that disruption of the anatomical networks influences the organization at the functional level resulting in the prodromal dementia syndrome of MCI.

Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment.

The neurophysiological changes associated with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) include an increase in low frequency activity, as measured with electroencephalography or magnetoencephalography (MEG). A relevant property of spectral measures is the alpha peak, which corresponds to the dominant alpha rhythm. Here we studied the spatial distribution of MEG resting state alpha peak frequency and amplitude values in a sample of 27 MCI patients and 24 age-matched healthy controls. Power spectra were reconstructed in source space with linearly constrained minimum variance beamformer. Then, 88 Regions of Interest (ROIs) were defined and an alpha peak per ROI and subject was identified. Statistical analyses were performed at every ROI, accounting for age, sex and educational level. Peak frequency was significantly decreased (p < 0.05) in MCIs in many posterior ROIs. The average peak frequency over all ROIs was 9.68 ± 0.71 Hz for controls and 9.05 ± 0.90 Hz for MCIs and the average normalized amplitude was (2.57 ± 0.59)·10(-2) for controls and (2.70 ± 0.49)·10(-2) for MCIs. Age and gender were also found to play a role in the alpha peak, since its frequency was higher in females than in males in posterior ROIs and correlated negatively with age in frontal ROIs. Furthermore, we examined the dependence of peak parameters with hippocampal volume, which is a commonly used marker of early structural AD-related damage. Peak frequency was positively correlated with hippocampal volume in many posterior ROIs. Overall, these findings indicate a pathological alpha slowing in MCI.