Semantic Memory in Neurodegenerative Disorders: New Insights and Ongoing Challenges

Semantic memory (SM) is the form of declarative memory responsible for learning, storing, and retrieving knowledge about the world for goal-directed purposes.From a computational viewpoint, SM depends on the integrity of semantic representations, memory mechanisms, and control processes. Its multi-componential nature characterizes SM as a function that is sustained by a large-scale distributed network of neural resources.Over the years, researchers in the fields of neuropsychology and cognitive neuroscience have shown a special interest in SM, both from academic and clinical standpoints. Differently from most cognitive abilities, in fact, SM does not appear to show a steep age-related decline. Conversely, forms of neurodegeneration (e.g., clinical variants of the Alzheimer’s disease and Frontotemporal Lobar Degeneration spectra) are known to influence performance on SM tests since the earliest clinical stages.While the role of semantic processing may thus be seen as pivotal in the search for valid, reliable and sustainable clinical disease markers, researchers also face a number of important challenges.Arguably, the denominator shared by all these challenges is linked to the need for establishing a link between the function and its operationalizations. Performance on tests that are typically used to quantify SM, in fact, are also influenced by other non-semantic and/or non-mnesic abilities, which limits their interpretation and applicability. As this is an important limitation in the field, there is a need for initiatives that can put this thematic area in the spotlight, and lead to new insight.Specifically, this Research Topic aims to address the following questions: • How can SM assessment be disentangled from the influence of non-semantic and non-mnesic cognitive demands? • Which novel measures and paradigms best detect early, subtle, and disease-specific semantic decline? • How can computational, language-based, and digital approaches scale and refine clinical SM assessment?This Article collection addresses this unmet need, by gathering research articles in the following areas: • Studies with a focus on semantic memory in neurodegenerative diseases, emphasizing its role in clinical assessment, disease monitoring, and prognosis • New neuropsychological tests to assess semantic memory in patients, including tools designed to detect subtle and early semantic deficits and to provide a more in-depth and multidimensional evaluation of impairments, also considering ecological validity • Focus on under-studied populations besides the most investigated ones, such as Alzheimer’s disease, including rarer dementias and atypical variants, in order to better characterize disease-specific semantic profiles and improve differential diagnosis • New possibilities for the automatic and remote assessment of lexico-semantic processing, including computational and language-based approaches (artificial intelligence, natural language processing) and portable device-based instruments designed for scalable, ecological, and remote cognitive evaluation • Integration of behavioral, neuroimaging, and computational approaches to better understand the organization and neural underpinnings of semantic memory and its breakdown across neurodegenerative conditions • Translational perspectives, with implications for early diagnosis, intervention, and patient care, with a specific focus on how semantic impairments can inform clinical practice and targeted rehabilitation strategiesThis research topic welcomes: Original Research, Review, Mini Review, Systematic Review, Perspective, Brief Research Report, Methods. Topic editors: Francesca Conca, Matteo De Marco, Sonia Di Tella Source: https://www.frontiersin.org/research-topics/81890/semantic-memory-in-neurodegenerative-disorders-new-insights-and-ongoing-challenges