Individual Differences in the Connectivity of Left and Right Anterior Temporal Lobes Relate to Modality and Category Effects in Semantic Categorisation

Contemporary neuroscientific accounts suggest that ventral anterior temporal lobe (ATL) regions act as a bilateral heteromodal semantic hub. However, research also shows graded functional differences between the hemispheres relating to linguistic versus non-linguistic semantic tasks and to knowledge of objects versus people. Individual differences in connectivity from bilateral ATL and between left and right ATL might therefore give rise to differences in function within this system. We investigated whether the relative strength of intrinsic connectivity from left and right ATL would relate to differences in performance on semantic tasks. We examined resting-state fMRI in 74 individuals and, in a separate session, examined semantic categorisation, manipulating stimulus type (famous faces versus landmarks) and modality of presentation (visual versus verbal). We found that people with greater connectivity between left and right ATL were more efficient at categorising landmarks, especially when these were presented visually. In addition, participants who showed stronger connectivity from right than left ATL to medial occipital cortex showed more efficient semantic categorisation of landmarks regardless of modality of presentation. These findings show that individual differences in the intrinsic connectivity of left and right ATL are associated with effects of category and modality in semantic categorisation. The results can be interpreted in terms of graded differences in the strengths of inputs from ‘spoke’ regions, such as regions of visual cortex, to a bilateral yet partially segregated semantic ‘hub’, encompassing left and right ATL.

Timecourse and convergence of abstract and concrete knowledge in the anterior temporal lobe

How is conceptual knowledge organized and retrieved by the brain? Recent evidence points to the anterior temporal lobe (ATL) as a crucial semantic hub integrating both abstract and concrete conceptual features according to a dorsal-to-medial gradient. It is however unclear when this conceptual gradient emerges and how semantic information reaches the ATL during conceptual retrieval. Here we used a multiple regression approach to magnetoencephalography signals of spoken words, combined with dimensionality reduction in concrete and abstract semantic feature spaces. Results showed that the dorsal-to-medial abstract-to-concrete ATL gradient emerges only in late stages of word processing: Abstract and concrete semantic information are initially encoded in posterior temporal regions and travel along separate cortical pathways eventually converging in the ATL. The present finding sheds light on the neural dynamics of conceptual processing that shape the organization of knowledge in the anterior temporal lobe.

AB1168 THE ANALYSIS OF “BIG DATA” AND PROCESSING OF UNSTRUCTURED INFORMATION (SEMANTIC HUB PLATFORM) TO IDENTIFY PATIENTS WITH SEVERE GOUT IN THE RUSSIAN FEDERATION.

Background:the prevalence of gout and hyperuricemia (HU) in the world remains high, with a stable high incidence of severe gout [1]. There are no data on the prevalence and features of severe gout in the population of the Russian Federation (RF).Objectives:To determine the percentage of patients (pts) with severe gout in the RF among pts with gout who are looking for information about their disease on the Internet, to clarify their average age, gender distribution, comorbidity, difficulties in diagnosing and treating, to get an idea of the most relevant online requests in this cohort.Methods:We used technology for analyzing “big data” and processing unstructured information (semantic intelligence) (the Semantic Hub platform, which scans Google and Yandex environments). For efficient processing of text corpora, several specialized converters were used. The resulting format for these converters is an XML representation of the source data. The study was based on real-life patient cases (specialized social networks, forums, and other sources of user-generated content). Messages from pts with gout and their relatives were used. Severe gout is characterized by frequent polyarticular flares or chronic arthritis, subcutaneous tophi, the presence of concomitant conditions.Results:A total of 16253 messages were processed, with ‘gout’ entered as a search word. A total of 1691 gout pts were identified. The average age of online-active pts - 47.2 years. Men 60.5%. Severe gout was identified in 194 of 1691 (11.5%) pts, with 59% of pts aged 29 to 45 years. The proportion of men among pts with severe gout is 71%. Comorbidities most often include diabetes mellitus and metabolic syndrome - 24%, CKD - 51%, arterial hypertension-14%. Pts with severe gout have 1.9 comorbidities on average, while other pts with gout -1.1. The groups are comparable by age. Among 90 links related to medical specialties that pts visited before being referred to a rheumatologist, the first three leading positions were - orthopaedic surgeon (30%), general practitioner (25.8%), surgeon (21%). Sixty percent of pts reported that the time between the first attack and the diagnosis of gout was less than six months. The remaining 40% of pts report that this period lasted from 1 to 15 years. Less than 42% of pts were prescribed urate-lowering therapy (ULT) during internal consultation of a physician, and only 23% of physicians recommended ULT to pts with gout during online consultation. According to pts’ reports, treatment includes 3 main groups of drugs: NSAIDs, intra-articular corticosteroids and ULT. Compliance with life-time ULT is very low. The most commonly requested topic on the Internet - attacks during holidays - 2426 messages, the second is held by the topic of lifestyle – 1899 messages, the third place - problems of comorbidities – 1813 references, and only in the fourth position - 1662 messages- the topic of ULT.Conclusion:The percentage of pts with severe gout is 11.5% among gout pts who are looking for information about their condition on the Internet, which is consistent with the data from the largest original papers in the RF on the prevalence of severe gout [2]. More than a half of pts with severe gout (59%) are men aged 29 to 45 years. The decreased online activity of pts over 46 years old may be due to the low motivation for treatment of this cohort. Gout pts are rather more concerned about lifestyle than medical problems. This may also indicate the absence of the consistent compliance of this patient category to life-time therapy. Inadequate long-term therapy and late diagnosis may be the main factors for severe gout in young and active pts.References:[1]Kuo CF, Grainge MJ, Zhang W, Doherty M. Global epidemiology of gout: prevalence, incidence and risk factors. Nat Rev Rheumatol. 2015 Nov;11(11):649-62.[2]Eliseev MS, Barskova VG, Denisov IS. The dynamics of clinical manifestations of gout in men (data from 7-year retrospective surveillance). Terapevticheskii arkhiv. 2015;87(5):10–5Disclosure of Interests:Ekaterina Ilinykh: None declared, Maxim Elisеev Speakers bureau: Novartis, Menarini Group, Alium

White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia

The hub-and-spoke semantic representation theory posits that semantic knowledge is processed in a neural network, which contains an amodal hub, the sensorimotor modality-specific regions, and the connections between them. The exact neural basis of the hub, regions and connectivity remains unclear. Semantic dementia could be an ideal lesion model to construct the semantic network as this disease presents both amodal and modality-specific semantic processing (e.g. colour) deficits. The goal of the present study was to identify, using an unbiased data-driven approach, the semantic hub and its general and modality-specific semantic white matter connections by investigating the relationship between the lesion degree of the network and the severity of semantic deficits in 33 patients with semantic dementia. Data of diffusion-weighted imaging and behavioural performance in processing knowledge of general semantic and six sensorimotor modalities (i.e. object form, colour, motion, sound, manipulation and function) were collected from each subject. Specifically, to identify the semantic hub, we mapped the white matter nodal degree value (a graph theoretical index) of the 90 regions in the automated anatomical labelling atlas with the general semantic abilities of the patients. Of the regions, only the left fusiform gyrus was identified as the hub because its structural connectivity strength (i.e. nodal degree value) could significantly predict the general semantic processing of the patients. To identify the general and modality-specific semantic connections of the semantic hub, we separately correlated the white matter integrity values of each tract connected with the left fusiform gyrus, with the performance for general semantic processing and each of six semantic modality processing. The results showed that the hub region worked in concert with nine other regions in the semantic memory network for general semantic processing. Moreover, the connection between the hub and the left calcarine was associated with colour-specific semantic processing. The observed effects could not be accounted for by potential confounding variables (e.g. total grey matter volume, regional grey matter volume and performance on non-semantic control tasks). Our findings refine the neuroanatomical structure of the semantic network and underline the critical role of the left fusiform gyrus and its connectivity in the network.

Semantic representations in the temporal pole predict false memories

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the “semantic hub” of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.