The influence of semantic and phonological factors on syntactic decisions: An event-related brain potential study

During language production and comprehension, information about a word's syntactic properties is sometimes needed. While the decision about the grammatical gender of a word requires access to syntactic knowledge, it has also been hypothesized that semantic (i.e., biological gender) or phonological information (i.e., sound regularities) may influence this decision. Event-related potentials (ERPs) were measured while native speakers of German processed written words that were or were not semantically and/or phonologically marked for gender. Behavioral and ERP results showed that participants were faster in making a gender decision when words were semantically and/or phonologically gender marked than when this was not the case, although the phonological effects were less clear. In conclusion, our data provide evidence that even though participants performed a grammatical gender decision, this task can be influenced by semantic and phonological factors

High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas

The amygdala is composed of multiple nuclei with unique functions and connections in the limbic system and to the rest of the brain. However, standard in vivo neuroimaging tools to automatically delineate the amygdala into its multiple nuclei are still rare. By scanning postmortem specimens at high resolution (100-150µm) at 7T field strength (n = 10), we were able to visualize and label nine amygdala nuclei (anterior amygdaloid, cortico-amygdaloid transition area; basal, lateral, accessory basal, central, cortical medial, paralaminar nuclei). We created an atlas from these labels using a recently developed atlas building algorithm based on Bayesian inference. This atlas, which will be released as part of FreeSurfer, can be used to automatically segment nine amygdala nuclei from a standard resolution structural MR image. We applied this atlas to two publicly available datasets (ADNI and ABIDE) with standard resolution T1 data, used individual volumetric data of the amygdala nuclei as the measure and found that our atlas i) discriminates between Alzheimer's disease participants and age-matched control participants with 84% accuracy (AUC=0.915), and ii) discriminates between individuals with autism and age-, sex- and IQ-matched neurotypically developed control participants with 59.5% accuracy (AUC=0.59). For both datasets, the new ex vivo atlas significantly outperformed (all p < .05) estimations of the whole amygdala derived from the segmentation in FreeSurfer 5.1 (ADNI: 75%, ABIDE: 54% accuracy), as well as classification based on whole amygdala volume (using the sum of all amygdala nuclei volumes; ADNI: 81%, ABIDE: 55% accuracy). This new atlas and the segmentation tools that utilize it will provide neuroimaging researchers with the ability to explore the function and connectivity of the human amygdala nuclei with unprecedented detail in healthy adults as well as those with neurodevelopmental and neurodegenerative disorders

Mapping interactions with the chaperone network reveals factors that protect against tau aggregation.

A network of molecular chaperones is known to bind proteins ('clients') and balance their folding, function and turnover. However, it is often unclear which chaperones are critical for selective recognition of individual clients. It is also not clear why these key chaperones might fail in protein-aggregation diseases. Here, we utilized human microtubule-associated protein tau (MAPT or tau) as a model client to survey interactions between ~30 purified chaperones and ~20 disease-associated tau variants (~600 combinations). From this large-scale analysis, we identified human DnaJA2 as an unexpected, but potent, inhibitor of tau aggregation. DnaJA2 levels were correlated with tau pathology in human brains, supporting the idea that it is an important regulator of tau homeostasis. Of note, we found that some disease-associated tau variants were relatively immune to interactions with chaperones, suggesting a model in which avoiding physical recognition by chaperone networks may contribute to disease

Two-Dimensional Electrophoresis of Tau Mutants Reveals Specific Phosphorylation Pattern Likely Linked to Early Tau Conformational Changes

The role of Tau phosphorylation in neurofibrillary degeneration linked to Alzheimer's disease remains to be established. While transgenic mice based on FTDP-17 Tau mutations recapitulate hallmarks of neurofibrillary degeneration, cell models could be helpful for exploratory studies on molecular mechanisms underlying Tau pathology. Here, “human neuronal cell lines” overexpressing Wild Type or mutated Tau were established. Two-dimensional electrophoresis highlights that mutated Tau displayed a specific phosphorylation pattern, which occurs in parallel to the formation of Tau clusters as visualized by electron microscopy. In fact, this pattern is also displayed before Tau pathology onset in a well established mouse model relevant to Tau aggregation in Alzheimer's disease. This study suggests first that pathological Tau mutations may change the distribution of phosphate groups. Secondly, it is possible that this molecular event could be one of the first Tau modifications in the neurofibrillary degenerative process, as this phenomenon appears prior to Tau pathology in an in vivo model and is linked to early steps of Tau nucleation in Tau mutants cell lines. Such cell lines consist in suitable and evolving models to investigate additional factors involved in molecular pathways leading to whole Tau aggregation

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

Accurate path integration in continuous attractor network models of grid cells

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of ~10–100 meters and ~1–10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other

Cerebral cortical thickness in chronic pain due to knee osteoarthritis: the effect of pain duration and pain densitization

Objective This study investigates associations between cortical thickness and pain duration, and central sensitization as markers of pain progression in painful knee osteoarthritis. Methods Whole brain cortical thickness and pressure pain thresholds were assessed in 70 participants; 40 patients with chronic painful knee osteoarthritis (age = 66.1± 8.5 years, 21 females, mean duration of pain = 8.5 years), and 30 healthy controls (age = 62.7± 7.4, 17 females). Results Cortical thickness negatively correlated with pain duration mainly in fronto-temporal areas outside of classical pain processing areas (p<0.05, age-controlled, FDR corrected). Pain sensitivity was unrelated to cortical thickness. Patients showed lower cortical thickness in the right anterior insula (p<0.001, uncorrected) with no changes surviving multiple test correction. Conclusion With increasing number of years of suffering from chronic arthritis pain we found increasing cortical thinning in extended cerebral cortical regions beyond recognised pain-processing areas. While the mechanisms of cortical thinning remain to be elucidated, we show that pain progression indexed by central sensitization does not play a major role

Molecular Implication of PP2A and Pin1 in the Alzheimer's Disease Specific Hyperphosphorylation of Tau

Tau phosphorylation and dephosphorylation regulate in a poorly understood manner its physiological role of microtubule stabilization, and equally its integration in Alzheimer disease (AD) related fibrils. A specific phospho-pattern will result from the balance between kinases and phosphatases. The heterotrimeric Protein Phosphatase type 2A encompassing regulatory subunit PR55/Bα (PP2A(T55α)) is a major Tau phosphatase in vivo, which contributes to its final phosphorylation state. We use NMR spectroscopy to determine the dephosphorylation rates of phospho-Tau by this major brain phosphatase, and present site-specific and kinetic data for the individual sites including the pS202/pT205 AT8 and pT231 AT180 phospho-epitopes.We demonstrate the importance of the PR55/Bα regulatory subunit of PP2A within this enzymatic process, and show that, unexpectedly, phosphorylation at the pT231 AT180 site negatively interferes with the dephosphorylation of the pS202/pT205 AT8 site. This inhibitory effect can be released by the phosphorylation dependent prolyl cis/trans isomerase Pin1. Because the stimulatory effect is lost with the dimeric PP2A core enzyme (PP2A(D)) or with a phospho-Tau T231A mutant, we propose that Pin1 regulates the interaction between the PR55/Bα subunit and the AT180 phospho-epitope on Tau.Our results show that phosphorylation of T231 (AT180) can negatively influence the dephosphorylation of the pS202/pT205 AT8 epitope, even without an altered PP2A pool. Thus, a priming dephosphorylation of pT231 AT180 is required for efficient PP2A(T55α)-mediated dephosphorylation of pS202/pT205 AT8. The sophisticated interplay between priming mechanisms reported for certain Tau kinases and the one described here for Tau phosphatase PP2A(T55α) may contribute to the hyperphosphorylation of Tau observed in AD neurons

iTRAQ Analysis of Complex Proteome Alterations in 3xTgAD Alzheimer's Mice: Understanding the Interface between Physiology and Disease

Alzheimer's disease (AD) is characterized by progressive cognitive impairment associated with accumulation of amyloid β-peptide, synaptic degeneration and the death of neurons in the hippocampus, and temporal, parietal and frontal lobes of the cerebral cortex. Analysis of postmortem brain tissue from AD patients can provide information on molecular alterations present at the end of the disease process, but cannot discriminate between changes that are specifically involved in AD versus those that are simply a consequence of neuronal degeneration. Animal models of AD provide the opportunity to elucidate the molecular changes that occur in brain cells as the disease process is initiated and progresses. To this end, we used the 3xTgAD mouse model of AD to gain insight into the complex alterations in proteins that occur in the hippocampus and cortex in AD. The 3xTgAD mice express mutant presenilin-1, amyloid precursor protein and tau, and exhibit AD-like amyloid and tau pathology in the hippocampus and cortex, and associated cognitive impairment. Using the iTRAQ stable-isotope-based quantitative proteomic technique, we performed an in-depth proteomic analysis of hippocampal and cortical tissue from 16 month old 3xTgAD and non-transgenic control mice. We found that the most important groups of significantly altered proteins included those involved in synaptic plasticity, neurite outgrowth and microtubule dynamics. Our findings have elucidated some of the complex proteome changes that occur in a mouse model of AD, which could potentially illuminate novel therapeutic avenues for the treatment of AD and other neurodegenerative disorders