Functional correlates of preserved naming performance in amnestic Mild Cognitive Impairment

Catricalà, Eleonora; Rosa, Pasquale Anthony Della; Parisi, Laura; Zippo, Antonio G.; Borsa, Virginia Maria; Iadanza, Antonella; Castiglioni, Isabella; Falini, Andrea; Cappa, Stefano F.

doi:10.1016/j.neuropsychologia.2015.01.009

Cited by 17 publications

(11 citation statements)

References 117 publications

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“…Several studies have shown mild lexico-semantic impairments also in the early or prodromal stages, such as in the case of aMCI, using semantic fluency (Joubert et al, 2010; for a review see Gainotti et al, 2014). Inconsistent results are shown by studies using object naming task (i.e., Ahmed et al, 2008; Joubert et al, 2010; but see Adlam et al, 2006; Balthazar et al, 2008; Clague et al, 2011; Choi et al, 2013; Gardini et al, 2013; Catricalà et al, 2015b); while data from naming pictures of unique entities including famous people, famous buildings and famous public events are more consistent (Estévez-González et al, 2004; Ahmed et al, 2008; Joubert et al, 2010; Clague et al, 2011; Gardini et al, 2013). Connected speech analysis appears to be less sensitive than these tasks in detecting subtle lexico-semantic in persons with aMCI when compared to healthy persons.…”

Section: Discussionmentioning

confidence: 88%

Connected Speech in Neurodegenerative Language Disorders: A Review

et al. 2017

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Language assessment has a crucial role in the clinical diagnosis of several neurodegenerative diseases. The analysis of extended speech production is a precious source of information encompassing the phonetic, phonological, lexico-semantic, morpho-syntactic, and pragmatic levels of language organization. The knowledge about the distinctive linguistic variables identifying language deficits associated to different neurodegenerative diseases has progressively improved in the last years. However, the heterogeneity of such variables and of the way they are measured and classified limits any generalization and makes the comparison among studies difficult. Here we present an exhaustive review of the studies focusing on the linguistic variables derived from the analysis of connected speech samples, with the aim of characterizing the language disorders of the most prevalent neurodegenerative diseases, including primary progressive aphasia, Alzheimer's disease, movement disorders, and amyotrophic lateral sclerosis. A total of 61 studies have been included, considering only those reporting group analysis and comparisons with a group of healthy persons. This review first analyzes the differences in the tasks used to elicit connected speech, namely picture description, story narration, and interview, considering the possible different contributions to the assessment of different linguistic domains. This is followed by an analysis of the terminologies and of the methods of measurements of the variables, indicating the need for harmonization and standardization. The final section reviews the linguistic domains affected by each different neurodegenerative disease, indicating the variables most consistently impaired at each level and suggesting the key variables helping in the differential diagnosis among diseases. While a large amount of valuable information is already available, the review highlights the need of further work, including the development of automated methods, to take advantage of the richness of connected speech analysis for both research and clinical purposes.

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Section: Discussionmentioning

confidence: 88%

Connected Speech in Neurodegenerative Language Disorders: A Review

et al. 2017

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“…Seven individuals (five males; age range: 59-81, mean age = 73.285, standard deviation [SD] = 6.897) fulfilled the clinical criteria. Six of these patients were already described in a previous work (Catricala et al, 2015).…”

Section: Participantsmentioning

confidence: 99%

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

Borsa

Rosa

Catricalà

et al. 2016

Journal of Neuropsychology

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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.

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“…In contrast to such a perspective, the functional connectivity network of the human brain proposes a strong global interdependency among regions where alterations of single node dynamics may be echoed widespreadly over the entire network, significantly changing the brain network dynamics. The assumption of localized lesional models inevitably neglects the complex and diffuse damages upon the globally connected brain network, as well as the compensatory or repair mechanisms that, with diverse strength and at diverse time, may arise from the original alterations (Catricalà et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

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

Zippo

Castiglioni

Lin

et al. 2020

Front. Hum. Neurosci.

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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 shortterm potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions.

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Functional correlates of preserved naming performance in amnestic Mild Cognitive Impairment

Cited by 17 publications

References 117 publications

Connected Speech in Neurodegenerative Language Disorders: A Review

Connected Speech in Neurodegenerative Language Disorders: A Review

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

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

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