The language profile of progressive supranuclear palsy.

A progressive speech/language disorder, such as the non fluent/agrammatic variant of primary progressive aphasia and progressive apraxia of speech, can be due to neuropathologically verified Progressive Supranuclear Palsy (PSP). The prevalence of linguistic deficits and the linguistic profile in PSP patients who present primarily with a movement disorder is unknown. In the present study, we investigated speech and language performance in a sample of clinically diagnosed PSP patients using a comprehensive language battery, including, besides traditional language tests, a detailed analysis of connected speech (picture description task assessing 26 linguistic features). The aim was to identify the most affected linguistic levels in seventeen PSP with a movement disorder presentation, compared to 21 patients with Parkinson's disease and 27 healthy controls. Machine learning methods were used to detect the most relevant language tests and linguistic features characterizing the language profile of PSP patients. Our results indicate that even non-clinically aphasic PSP patients have subtle language deficits, in particular involving the lexical-semantic and discourse levels. Patients with the Richardson's syndrome showed a lower performance in the word comprehension task with respect to the other PSP phenotypes with predominant frontal presentation, parkinsonism and progressive gait freezing. The present findings support the usefulness of a detailed language assessment in all patients in the PSP spectrum.

Short-Term Classification Learning Promotes Rapid Global Improvements of Information Processing in Human Brain Functional Connectome.

Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connections. While long-term motor memories have been found to alter functional connectivity in the resting human brain, a graph topological investigation of the short-time effects of learning are still not widely investigated. For instance, classification learning is known to orchestrate rapid modulation of diverse memory systems like short-term and visual working memories but how the brain functional connectome accommodates such modulations is unclear. We used publicly available repositories (openfmri.org) selecting three experiments, two focused on short-term classification learning along two consecutive runs where learning was promoted by trial-by-trial feedback errors, while a further experiment was used as supplementary control. We analyzed the functional connectivity extracted from BOLD fMRI signals, and estimated the graph information processing in the cerebral networks. The information processing capability, characterized by complex network statistics, significantly improved over runs, together with the subject classification accuracy. Instead, null-learning experiments, where feedbacks came with poor consistency, did not provoke any significant change in the functional connectivity over runs. We propose that learning induces fast modifications in the overall brain network dynamics, definitely ameliorating the short-term potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions.

Interference and conflict monitoring in individuals with amnestic mild cognitive impairment: A structural study of the anterior cingulate cortex.

Amnestic mild cognitive impairment (aMCI) is a clinical condition characterized by memory impairment in the absence of any other cognitive impairment and is commonly associated with high conversion to Alzheimer's disease. Recent evidence shows that executive functions and selective attention mechanisms could also be impaired in aMCI. In this study, we investigated performance differences (i.e., reaction times [RTs] and accuracy) between a group of aMCI participants and a group of age-matched healthy individuals on the attentional network task (ANT) focusing on situations with increased interference. In particular, we assessed the relationship between interference and conflict effects and grey matter volumes (GMVs) of the anterior cingulate cortex (ACC)/pre-supplementary motor area in the entire sample because of its crucial role in conflict monitoring. When compared with controls, aMCI participants were less accurate on the ANT, showing increased interference and conflict effects, but no differences in RTs. In addition, aMCI participants exhibited lower GMV in the ACC than controls. While better accuracy for interference and conflict effects was associated with an increase of GMV in the ACC for both groups, RTs from the interference effect were negatively correlated with GMV of the ACC only in aMCI participants. In other words, lower GMV values of the ACC were paralleled with significantly impaired performance in terms of interference resolution. In conclusion, our study suggests the presence of a selective impairment in interference and conflict monitoring in aMCI, which in turn is associated with decreased GMVs in the ACC.

Functional correlates of preserved naming performance in amnestic Mild Cognitive Impairment.

Naming abilities are typically preserved in amnestic Mild Cognitive Impairment (aMCI), a condition associated with increased risk of progression to Alzheimer's disease (AD). We compared the functional correlates of covert picture naming and word reading between a group of aMCI subjects and matched controls. Unimpaired picture naming performance was associated with more extensive activations, in particular involving the parietal lobes, in the aMCI group. In addition, in the condition associated with higher processing demands (blocks of categorically homogeneous items, living items), increased activity was observed in the aMCI group, in particular in the left fusiform gyrus. Graph analysis provided further evidence of increased modularity and reduced integration for the homogenous sets in the aMCI group. The functional modifications associated with preserved performance may reflect, in the case of more demanding tasks, compensatory mechanisms for the subclinical involvement of semantic processing areas by AD pathology.

The Compression Flow as a Measure to Estimate the Brain Connectivity Changes in Resting State fMRI and 18FDG-PET Alzheimer's Disease Connectomes.

The human brain appears organized in compartments characterized by seemingly specific functional purposes on many spatial scales. A complementary functional state binds information from specialized districts to return what is called integrated information. These fundamental network dynamics undergoes to severe disarrays in diverse degenerative conditions such as Alzheimer's Diseases (AD). The AD represents a multifarious syndrome characterized by structural, functional, and metabolic landmarks. In particular, in the early stages of AD, adaptive functional modifications of the brain networks mislead initial diagnoses because cognitive abilities may result indiscernible from normal subjects. As a matter of facts, current measures of functional integration fail to catch significant differences among normal, mild cognitive impairment (MCI) and even AD subjects. The aim of this work is to introduce a new topological feature called Compression Flow (CF) to finely estimate the extent of the functional integration in the brain networks. The method uses a Monte Carlo-like estimation of the information integration flows returning the compression ratio between the size of the injected information and the size of the condensed information within the network. We analyzed the resting state connectomes of 75 subjects of the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI) repository. Our analyses are focused on the 18FGD-PET and functional MRI (fMRI) acquisitions in several clinical screening conditions. Results indicated that CF effectively discriminate MCI, AD and normal subjects by showing a significant decrease of the functional integration in the AD and MCI brain connectomes. This result did not emerge by using a set of common complex network statistics. Furthermore, CF was best correlated with individual clinical scoring scales. In conclusion, we presented a novel measure to quantify the functional integration that resulted efficient to discriminate different stages of dementia and to track the individual progression of the impairments prospecting a proficient usage in a wide range of pathophysiological and physiological studies as well.