Siamese Graph Convolutional Network quantifies increasing structure-function discrepancy over the cognitive decline continuum.

BACKGROUND AND OBJECTIVE: Alzheimer's disease dementia (ADD) is well known to induce alterations in both structural and functional brain connectivity. However, reported changes in connectivity are mostly limited to global/local network features, which have poor specificity for diagnostic purposes. Following recent advances in machine learning, deep neural networks, particularly Graph Neural Network (GNN) based approaches, have found applications in brain research as well. The majority of existing applications of GNNs employ a single network (uni-modal or structure/function unified), despite the widely accepted view that there is a nontrivial interdependence between the brain's structural connectivity and the neural activity patterns, which is hypothesized to be disrupted in ADD. This disruption is quantified as a discrepancy score by the proposed "structure-function discrepancy learning network" (sfDLN) and its distribution is studied over the spectrum of clinical cognitive decline. The measured discrepancy score is utilized as a diagnostic biomarker and is compared with state-of-the-art diagnostic classifiers. METHODS: sfDLN is a GNN with a siamese architecture built on the hypothesis that the mismatch between structural and functional connectivity patterns increases over the cognitive decline spectrum, starting from subjective cognitive impairment (SCI), passing through a mid-stage mild cognitive impairment (MCI), and ending up with ADD. The structural brain connectome (sNET) built using diffusion MRI-based tractography and the novel, sparse (lean) functional brain connectome (ℓNET) built using fMRI are input to sfDLN. The siamese sfDLN is trained to extract connectome representations and a discrepancy (dissimilarity) score that complies with the proposed hypothesis and is blindly tested on an MCI group. RESULTS: The sfDLN generated structure-function discrepancy scores show high disparity between ADD and SCI subjects. Leave-one-out experiments of SCI-ADD classification over a cohort of 42 subjects reach 88% accuracy, surpassing state-of-the-art GNN-based classifiers in the literature. Furthermore, a blind assessment over a cohort of 46 MCI subjects confirmed that it captures the intermediary character of the MCI group. GNNExplainer module employed to investigate the anatomical determinants of the observed discrepancy confirms that sfDLN attends to cortical regions neurologically relevant to ADD. CONCLUSION: In support of our hypothesis, the harmony between the structural and functional organization of the brain degrades with increasing cognitive decline. This discrepancy, shown to be rooted in brain regions neurologically relevant to ADD, can be quantified by sfDLN and outperforms state-of-the-art GNN-based ADD classification methods when used as a biomarker.

Diffusion tensor imaging in photosensitive and nonphotosensitive juvenile myoclonic epilepsy.

INTRODUCTION/BACKGROUND: Juvenile myoclonic epilepsy (JME) syndrome is known to cause alterations in brain structure and white matter integrity. The study aimed to determine structural white matter changes in patients with JME and to reveal the differences between the photosensitive (PS) and nonphotosensitive (NPS) subgroups by diffusion tensor imaging (DTI) using the tract-based spatial statistics (TBSS) method. METHODS: This study included data from 16 PS, 15 NPS patients with JME, and 41 healthy participants. The mean fractional anisotropy (FA) values of these groups were calculated, and comparisons were made via the TBSS method over FA values in the whole-brain and 81 regions of interest (ROI) obtained from the John Hopkins University White Matter Atlas. RESULTS: In the whole-brain TBSS analysis, no significant differences in FA values were observed in pairwise comparisons of JME patient group and subgroups with healthy controls (HCs) and in comparison between JME subgroups. In ROI-based TBSS analysis, an increase in FA values of right anterior corona radiata and left corticospinal pathways was found in JME patient group compared with HC group. When comparing JME-PS patients with HCs, an FA increase was observed in the bilateral anterior corona radiata region, whereas when comparing JME-NPS patients with HCs, an FA increase was observed in bilateral corticospinal pathway. Moreover, in subgroup comparison, an increase in FA values was noted in corpus callosum genu region in JME-PS compared with JME-NPS. CONCLUSIONS: Our results support the disruption in thalamofrontal white matter integrity in JME, and subgroups and highlight the importance of using different analysis methods to show the underlying microstructural changes.

Hyperconnecitivity between dorsal attention and frontoparietal networks predicts treatment response in obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) presented with repetitive obsessions and/or compulsions were associated with disrupted resting-state functional connectivity (rs-FC). To investigate the pharmacological treatment effect on rs-FC changes in OCD patients we conducted the seed-to-voxel FC analyses using dorsal attention network (DAN), default mode network (DMN), salience network (SN) and frontoparietal network (FPN) and basal ganglia seeds. Twenty-two healthy subjects and twenty-four unmedicated OCD patients underwent resting-state functional magnetic resonance imaging. Patients were rescanned after 12 weeks of escitalopram treatment. We found increased FC both within the DAN and between the DAN and the FPN which was ameliorated after medication and correlated significantly with the clinical improvement in obsession scores. We also observed an anticorrelation between the left caudate and the supplementary motor area in unmedicated OCD patients which also normalized with treatment. Results further showed treatment related normalization of orbitofrontal cortex hyperconnectivity with DMN and hypoconnectivity with DAN whereas aberrant FC between the SN and visual areas appears to be a medication effect. We suggest that DAN to FPN hyperconnectivity which is positively correlated with clinical improvement in obsession scores at pre-treatment stage in present study has a potential for being a neuroimaging marker to predict the treatment response in OCD.

Shrinkage of olfactory amygdala connotes cognitive impairment in patients with Parkinson's disease.

During the caudo-rostral progression of Lewy pathology, the amygdala is involved relatively early in Parkinson's disease (PD). However, lesser is known about the volumetric differences at the amygdala subdivisions, although the evidence mainly implicates the olfactory amygdala. We aimed to investigate the volumetric differences between the amygdala's nuclear and sectoral subdivisions in the PD cognitive impairment continuum compared to healthy controls (HC). The volumes of nine nuclei of the amygdala were estimated with FreeSurfer (nuclear parcellation-NP) from T1-weighted images of PD patients with normal cognition (PD-CN), PD with mild cognitive impairment (PD-MCI), PD with dementia (PD-D), and HC. The appropriate nuclei were then merged to obtain three sectors of the amygdala (sectoral parcellation-SP). The nuclear and sectoral volumes were compared among the four groups and between the hyposmic and normosmic PD patients. There was a significant difference in the total amygdala volume among the four groups. In terms of nuclei, the bilateral cortico-amygdaloid transition area (CAT) and sectors superficial cortex-like region (sCLR) volumes of PD-MCI and PD-D were less than those of the PD-CN and HC. A linear discriminant analysis revealed that left CAT and left sCLR volumes classified the PD-CN and cognitively impaired PD (PD-CI: PD-MCI plus PD-D) with 90.7% accuracy according to NP and 85.2% accuracy to SP. Similarly, left CAT and sCLR volumes correctly identified the hyposmic and normosmic PD with 64.8% and 61.1% accuracies. Notably, the left olfactory amygdala volume successfully discriminated cognitive impairment in PD and could be used as neuroimaging-based support for PD-CI diagnosis. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09887-y.

Morphometric analysis of medial temporal lobe subregions in Alzheimer's disease using high-resolution MRI.

The spread pattern of progressive degeneration seen in Alzheimer's disease (AD) to small-scale medial temporal lobe subregions is critical for early diagnosis. In this context, it was aimed to examine the morphometric changes of the hippocampal subfields, amygdala nuclei, entorhinal cortex (ERC), and parahippocampal cortex (PHC) using MRI. MRI data of patients diagnosed with 20 Alzheimer's disease dementia (ADD), 30 amnestic mild cognitive impairment (aMCI), and 30 subjective cognitive impairment (SCI) without demographic differences were used. Segmentation and parcellation were performed using FreeSurfer. The segmentation process obtained volume values of 12 hippocampal subfields and 9 amygdala nuclei. Thickness values of ERC and PHC were calculated with the parcellation process. ANCOVA was performed using age, education and gender as covariates to evaluate the intergroup differences. Linear discriminant analysis was used to investigate whether atrophy predicted groups at an early stage. ERC and PHC thickness decreased significantly throughout the disease continuum, while only ERC was affected in the early stage. When the hippocampal and amygdala subfields were compared volumetrically, significant differences were found in the amygdala between the SCI and aMCI groups. In the early period, only volume reduction in the anterior amygdaloid area of the amygdala nuclei exceeded the significance threshold. Research on AD primarily focuses on original hippocampocentric structures and their main function which is episodic memory. Our results emphasized the significance of so far relatively neglected olfactocentric structures and their functions, such as smell and social cognition in the pre-dementia stages of the AD process.

Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease.

OBJECTIVE: Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD. METHODS: MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit. RESULTS: The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants. CONCLUSIONS: Our findings revealed the importance of the Papez circuit as target regions along the AD. SIGNIFICANCE: The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.

Comparison of FreeSurfer and CAT12 Software in Parcel-Based Cortical Thickness Calculations.

Several approaches have emerged to measure the cortical thickness (CT), which can be broadly divided into surface-based and voxel-based algorithms. We aimed to compare parcel-based CT estimation of the widely used FreeSurfer (FS) software and CAT12 software, which is a widely used voxel-based approach, and evaluate the test-retest (TRT) reliability of both methods. MRI images of 417 healthy individuals were analyzed. TRT reliability was performed on 60 participants. The mean CT of the parcels of the Desikan-Killiany atlas were calculated both in FS and CAT12. Linear mixed model was performed to compare the two methods and the TRT reliability, and paired-sample t-test for post-hoc analyses. Linear regression analyses were utilized to examine the regressions between the two methods and between different sessions with each method. CT values calculated using the two methods were significantly correlated (R2adj = 0.67). The significant interaction effect between the method and the parcels were due to larger CT values of FS in 32 of 68 parcels, whereas CT values of CAT12 were higher in 31 of 68 parcels. The TRT reliabilities of both approaches were excellent (FS R2adj = 0.95, CAT12 R2adj = 0.93). We conclude that both techniques can provide equally valid results for groups comparisons or follow-up studies as long as they are not mixed with each other.

Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning.

OBJECTIVE: To investigate metabolic changes of mild cognitive impairment in Parkinson's disease (PD-MCI) using proton magnetic resonance spectroscopic imaging (1H-MRSI). METHODS: Sixteen healthy controls (HC), 26 cognitively normal Parkinson's disease (PD-CN) patients, and 34 PD-MCI patients were scanned in this prospective study. Neuropsychological tests were performed, and three-dimensional 1H-MRSI was obtained at 3 T. Metabolic parameters and neuropsychological test scores were compared between PD-MCI, PD-CN, and HC. The correlations between neuropsychological test scores and metabolic intensities were also assessed. Supervised machine learning algorithms were applied to classify HC, PD-CN, and PD-MCI groups based on metabolite levels. RESULTS: PD-MCI had a lower corrected total N-acetylaspartate over total creatine ratio (tNAA/tCr) in the right precentral gyrus, corresponding to the sensorimotor network (p = 0.01), and a lower tNAA over myoinositol ratio (tNAA/mI) at a part of the default mode network, corresponding to the retrosplenial cortex (p = 0.04) than PD-CN. The HC and PD-MCI patients were classified with an accuracy of 86.4% (sensitivity = 72.7% and specificity = 81.8%) using bagged trees. CONCLUSION: 1H-MRSI revealed metabolic changes in the default mode, ventral attention/salience, and sensorimotor networks of PD-MCI patients, which could be summarized mainly as 'posterior cortical metabolic changes' related with cognitive dysfunction.

Volumetric changes within hippocampal subfields in Alzheimer's disease continuum.

Neurodegeneration in Alzheimer's disease continuum (ADC) starts from the transentorhinal cortex and progresses within hippocampal circuitry following the connectivity of its subfields transsynaptically. We aimed to track volumetric changes of the hippocampal subfields by comparing three stages of the ADC. MRI data of 15 patients diagnosed with Alzheimer's disease dementia (ADD), 15 patients with amnestic mild cognitive impairment (MCI), and 15 individuals with subjective cognitive impairment (SCI) were analyzed. The hippocampal formation was subdivided into CA1, CA3, subiculum (SUB), and dentate gyrus (DG) using FreeSurfer and volumetric values were obtained. The volumetric values were analyzed with ANCOVA and intracranial volume was selected as a covariate. ANCOVA results of the hippocampal subfields displayed statistically significant differences among the three groups in bilateral CA1, SUB, and DG volumes (Right CA1: F = 7.316, p = 0.002; left CA1: F = 6.768, p = 0.003; right SUB: F = 9.390, p < 0.001; left SUB: F = 5.925, p = 0.005; right DG: F = 9.469, p < 0.001; left DG: F = 9.354, p < 0.001), while CA3 volumes were not significantly different among the groups. Post hoc comparisons revealed that volume reductions in bilateral CA1, DG, and SUB were present in ADD compared to both MCI and SCI groups. No significant volumetric changes were found between the SCI and MCI groups. While our results are generally consistent with the literature in terms of the CA1 and SUB findings, they additionally point to the importance of the significant volume loss in DG and the resilience of the CA3 sector.

Altered Resting State Functional Connectivity and Its Correlation with Cognitive Functions at Ultra High Risk for Psychosis.

The aim of this study is to identify robust resting state-functional connectivity (rs-FC) alterations and their correlations with the neuropsychological characteristics of Ultra-High Risk (UHR) for psychosis subjects compared to healthy controls (HCs). Twenty individuals with UHR and sixteen HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a cognitive battery evaluating attention, episodic memory and executive functions. Compared to HCs, UHR individuals showed working memory and set-shifting impairments. In functional connectivity (FC) analyses, the Default Mode Network (DMN) of the UHR subjects displayed increased FC with the visual areas and decreased FC with the Dorsal Attention Network (DAN). Additionally, the salience network (SN) of the UHR subjects displayed increased connectivity with wide posterior cortical areas in the temporal, parietal and occipital lobes, corresponding to posterior nodes of the SN itself, the Somato-Motor Network (SMN) and the DAN. The SN connectivity with the left SMN and DAN was positively correlated with the Trail Making Test - B scores of the UHR subjects. These findings show that the SN and DMN, which mostly show abnormal connectivity patterns in psychosis, are also affected in UHR subjects, while the SN plays a more central role with its hyperconnectivity to the DAN and SMN.

Default mode and dorsal attention network involvement in visually guided motor sequence learning.

Motor sequence learning (MSL) paradigms are often used to investigate the neural processes underlying the acquisition of complex motor skills. Behavioral and neuroimaging studies have indicated an early stage in which spatial learning is prominent and a late stage of automatized performance after multiple training periods. Functional magnetic resonance imaging (fMRI) studies yielded both decreased and increased activations of the sensorimotor and association areas. However, task-negative and task-positive intrinsic connectivity networks (ICNs), the default mode (DMN) and dorsal attention (DAN) networks involved in governing attention demands during various task conditions were not specifically addressed in most studies. In the present fMRI study, a visually guided MSL (VMSL) task was used for bringing roles of visuospatial and motor attention into foreground in order to investigate the role of attention-related ICNs in MSL. Seventeen healthy, right-handed participants completed training and test sessions of VMSL during fMRI on the 1st day. Then, after daily training for three consecutive days outside the scanner, they were re-tested during the 5th day's scanning session. When test session after early learning period was compared with training session, activation decrease was observed in the occipito-temporal fusiform cortex, while task-related suppression of DMN was reduced. Reduced deactivation after early learning was correlated with decreased error rates. After late learning stage we observed activation decreases in bilateral superior parietal lobules of task-positive DAN, dorsal precunei, and cerebellum. Reduced activity in left posterior parietal and right cerebellar regions were correlated with gains in speed, error rate, respectively. This dissociation in activity changes of DMN and DAN related areas suggests that DAN shows high contribution during both early and late MSL stages, possibly due to attention requirement for automatization of spatial and temporal aspects of motor sequence. In contrast, spatial learning occurring during early MSL stage was sufficient for releasing DMN resources.

Detection of visual and frontoparietal network perfusion deficits in Parkinson's disease dementia.

Mild cognitive impairment of Parkinson's disease (PD) may be an early manifestation that may progressively worsen to dementia. Cognitive decline has been associated with changes in the brain perfusion pattern. This study aimed to evaluate cerebral blood flow (CBF) deficits specific to different stages of cognitive decline. Seventeen patients with cognitively normal PD (PD-CN), 18 patients with PD with mild cognitive impairment (PD-MCI), and 16 patients with PD with dementia (PDD) were included in this study. The participants were scanned using a 3 T Philips MRI scanner. Arterial spin labelling magnetic resonance (ASL-MR) images were acquired, followed by calculation of the CBF maps, and registration onto the MNI152 brain atlas. A whole-brain voxel-based CBF comparison was performed among the patient groups using age as a covariate. The mean age of patients with PDD was significantly higher than that of patients with PD-MCI (P = 0.015) and PD-CN (P = 0.001). The CBF values of the three groups were significantly different in the left cuneus of the visual network (VN), left inferior frontal gyrus of the frontoparietal network (FPN), and left dorsomedial nucleus of the thalamus. PDD had lower perfusion values than PD-MCI group in the same regions detected in the main group analysis. Additionally, comparison of PDD with PD-CN and non-demented groups revealed that the perfusion reduction extended into the bilateral cuneus of the VN, bilateral thalami, and left inferior frontal gyrus of the FPN. PDD could be separated from PD-MCI and PD-CN stages with CBF deficits in non-dopaminergically mediated posterior and dopaminergically mediated frontal networks.

Functional connectivity disturbances of ascending reticular activating system and posterior thalamus in juvenile myoclonic epilepsy in relation with photosensitivity: A resting-state fMRI study.

OBJECTIVE: Juvenile myoclonic epilepsy (JME) is typified by the occurrence of myoclonic seizures after awakening, though another common trait is myoclonic seizures triggered by photic stimulation. We aimed to investigate the functional connectivity (FC) of nuclei in the ascending reticular activating system (ARAS), thalamus and visual cortex in JME with and without photosensitivity. METHODS: We examined 29 patients with JME (16 photosensitive (PS), 13 non- photosensitive-(NPS)) and 28 healthy controls (HCs) using resting-state functional magnetic resonance imaging (rs-fMRI). Seed-to-voxel FC analyses were performed using 25 seeds, including the thalamus, visual cortex, and ARAS nuclei. RESULTS: Mesencephalic reticular formation seed revealed significant hyperconnectivity between the bilateral paracingulate gyrus and anterior cingulate cortex in JME group, and in both JME-PS and JME-NPS subgroups compared to HCs (pFWE-corr < 0.001; pFWE-corr < 0.001; pFWE-corr = 0.002, respectively). Locus coeruleus seed displayed significant hyperconnectivity with the bilateral lingual gyri, intracalcarine cortices, occipital poles and left occipital fusiform gyrus in JME-PS group compared to HCs (pFWE-corr <0.001). Additionally, locus coeruleus seed showed significant hyperconnectivity in JME-PS group compared to JME-NPS group with a cluster corresponding to the bilateral lingual gyri and right intracalcarine cortex (pFWE-corr < 0.001). Lastly, the right posterior nuclei of thalamus revealed significant hyperconnectivity with the right superior lateral occipital cortex in JME-PS group compared to HCs (pFWE-corr < 0.002). CONCLUSIONS: In JME, altered functional connectivity of the arousal networks might contribute to the understanding of myoclonia after awakening, whereas increased connectivity of posterior thalamus might explain photosensitivity.

Functional Connectivity Analysis in Heterozygous Glucocerebrosidase Mutation Carriers.

BACKGROUND: There is evidence that alterations in functional connectivity (FC) of the striatocortical circuits may appear before the onset of clinical symptoms of Parkinson's disease (PD). OBJECTIVE: The aim of this study was to investigate FC of the striatocortical circuitry in asymptomatic carriers of heterozygous glucocerebrosidase (GBA) mutations, which pose a significant risk for developing PD. METHODS: Twenty-one parents of confirmed Gaucher disease patients who were carrying heterozygous GBA mutations and 18 healthy individuals matched for age and gender were included. GBA mutation analysis was performed in all participants. Clinical evaluation included neurological examination, Mini Mental State Examination, and UPDRS Part III. Structural and functional MRI data of 18 asymptomatic GBA mutation carriers (asGBAmc) and 17 healthy controls (HC) were available. FC was analyzed with seed-based approach. RESULTS: Eleven asymptomatic mutation carriers had heterozygous p.L483P mutation, 6 subjects heterozygous p.N409S mutation and 1 subject heterozygous p.R392G mutation in GBA gene. Mini-Mental State Examination mean score was 28.77 (±1.16) and 29.64 (±0.70) in asGBAmc and HC groups, respectively (p = 0.012). Significant increased connectivityConclusion:Our results suggest that alterations in striatocortical FC can be detected in asymptomatic heterozygous GBA mutation carriers who are at risk of developing PD. These findings may provide insight into network changes during the asymptomatic phase of PD.

B-Tensor: Brain Connectome Tensor Factorization for Alzheimer's Disease.

AD is the highly severe part of the dementia spectrum and impairs cognitive abilities of individuals, bringing economic, societal and psychological burdens beyond the diseased. A promising approach in AD research is the analysis of structural and functional brain connectomes, i.e., sNETs and fNETs, respectively. We propose to use tensor representation (B-tensor) of uni-modal and multi-modal brain connectomes to define a low-dimensional space via tensor factorization. We show on a cohort of 47 subjects, spanning the spectrum of dementia, that diagnosis with an accuracy of 77% to 100% is achievable in a 5D connectome space using different structural and functional connectome constructions in a uni-modal and multi-modal fashion. We further show that multi-modal tensor factorization improves the results suggesting complementary information in structure and function. A neurological assessment of the connectivity patterns identified largely agrees with prior knowledge, yet also suggests new associations that may play a role in the disease progress.

Functional connectivity analysis of patients with temporal lobe epilepsy displaying different ictal propagation patterns.

The pathophysiology of switch-of lateralization and bilateral temporal asynchrony, which are scalp EEG ictal propagation patterns (iPP) in temporal lobe epilepsy (TLE), is poorly understood. We aimed to analyse functional connectivity (FC) of the temporal lobe and related areas in patients with TLE with iPP (iPP-TLE) and without iPP (non-iPP TLE). Twelve patients with iPP-TLE, 13 patients with non-iPP TLE, and 13 healthy controls (HC) underwent resting-state functional MRI (fMRI). Seed-based FC was analysed between the homologous insulae, hippocampi, amygdalae, parahippocampal, superior temporal, and middle temporal gyri. FC was reduced between homologous temporal lobe areas in patients with TLE compared with HCs. Patients with non-iPP TLE displayed decreased FC between the homologous parahippocampal and superior temporal gyri, and patients with iPP-TLE had lower FC between the homologous insulae, parahippocampal and superior temporal gyri compared with HC. Furthermore, patients with iPP-TLE tended to have lower FC between the bilateral insulae when compared with patients with non-iPP TLE. Reduced FC of interhemispheric connections between temporal lobes and related areas might be an adaptive change to protect contralateral areas in seizure propagation. The insula showed decreased FC between two hemispheres in patients with iPP-TLE, assuming a role in ictal scalp propagation pattern changes in TLE.

Neuronavigated rTMS inhibition of right pars triangularis anterior in stuttering: Differential effects on reading and speaking.

Functional neuroimaging studies show an overactivation of speech and language related homologous areas of the right hemisphere in persons who stutter. In this study, we inhibited Broca's homologues using 1 Hz repetitive transcranial magnetic stimulation (rTMS) and assessed its effects on stuttering severity. The investigated cortical areas included pars opercularis (BA44), anterior and posterior pars triangularis (BA45), mouth area on the primary motor cortex (BA4). We collected reading and speaking samples before and after rTMS sessions and calculated the percentage of syllables stuttered. Only right anterior pars triangularis stimulation induced significant changes in speech fluency. Notably, the effects were differential for reading and speaking conditions. Overall, our results provide supportive evidence that right anterior BA45 may be a critical region for stuttering. The observed differential effects following the inhibition of right anterior BA45 merits further study of contributions of this region on different language domains in persons who stutter.

The cerebral blood flow deficits in Parkinson's disease with mild cognitive impairment using arterial spin labeling MRI.

Parkinson's disease (PD) with mild cognitive impairment (PD-MCI) is currently diagnosed based on an arbitrarily predefined standard deviation of neuropsychological test scores, and more objective biomarkers for PD-MCI diagnosis are needed. The purpose of this study was to define possible brain perfusion-based biomarkers of not only mild cognitive impairment, but also risky gene carriers in PD using arterial spin labeling magnetic resonance imaging (ASL-MRI). Fifteen healthy controls (HC), 26 cognitively normal PD (PD-CN), and 27 PD-MCI subjects participated in this study. ASL-MRI data were acquired by signal targeting with alternating radio-frequency labeling with Look-Locker sequence at 3 T. Single nucleotide polymorphism genotyping for rs9468 [microtubule-associated protein tau (MAPT) H1/H1 versus H1/H2 haplotype] was performed using a Stratagene Mx3005p real-time polymerase chain-reaction system (Agilent Technologies, USA). There were 15 subjects with MAPT H1/H1 and 11 subjects with MAPT H1/H2 within PD-MCI, and 33 subjects with MAPT H1/H1 and 19 subjects with MAPT H1/H2 within all PD. Voxel-wise differences of cerebral blood flow (CBF) values between HC, PD-CN and PD-MCI were assessed by one-way analysis of variance followed by pairwise post hoc comparisons. Further, the subgroup of PD patients carrying the risky MAPT H1/H1 haplotype was compared with noncarriers (MAPT H1/H2 haplotype) in terms of CBF by a two-sample t test. A pattern that could be summarized as "posterior hypoperfusion" (PH) differentiated the PD-MCI group from the HC group with an accuracy of 92.6% (sensitivity = 93%, specificity = 93%). Additionally, the PD patients with MAPT H1/H1 haplotype had decreased perfusion than the ones with H1/H2 haplotype at the posterior areas of the visual network (VN), default mode network (DMN), and dorsal attention network (DAN). The PH-type pattern in ASL-MRI could be employed as a biomarker of both current cognitive impairment and future cognitive decline in PD.

Evoked and induced EEG oscillations to visual targets reveal a differential pattern of change along the spectrum of cognitive decline in Alzheimer's Disease.

In recent years, quantitative variables derived from the electroencephalogram (EEG) attract an increasing interest for the evaluation of neurodegenerative diseases, as EEG registers the neuro-electric activity with a high temporal resolution and provides a cost-effective and easily accessible, non-invasive method. Event-related oscillations (EROs) as oscillatory responses in the EEG to specific events further provide the possibility to track the cognitive decline in a task-specific manner. Current study in search for potential ERO biomarkers to distinguish different stages of cognitive decline along the Alzheimer's Disease (AD) continuum re-analyzed a combined set of data collected and analyzed in previous studies by Basar and coworkers. Target responses of a visual oddball experiment recorded from 33 AD patients, 46 Mild Cognitive Impairment (MCI) patients and 48 age, gender, and education matched normal elderly controls were analyzed for both evoked (phase-locked) and total (phase-locked + non-phase-locked) ERO powers in delta, theta, alpha, beta and gamma bands by applying continuous wavelet transform (WT) on averaged and single trial data, respectively. The cluster-based nonparametric permutation test implemented in the FieldTrip toolbox revealed significant differences among the three groups. While the total delta and theta responses already significantly declined in the MCI stage with further spatial expansion of the decline in AD, the evoked delta response reached a statistically significant reduction level in the AD stage. We obtained no significant difference among groups for alpha, beta and gamma frequency bands. These results suggest that total delta and theta EROs to oddball targets may be useful for early detection of the disease in MCI stage, while the evoked delta response allows detecting the conversion to AD.