Almost 70 years ago, Alexander Luria incorporated semantic aphasia among his aphasia classifications by demonstrating that deficits in linking the logical relationships of words in a sentence could co-occur with non-linguistic disorders of calculation, spatial gnosis and praxis deficits. In line with his comprehensive approach to the assessment of language and other cognitive functions, he argued that deficits in understanding semantically reversible sentences and prepositional phrases, for example, were in line with a single neuropsychological factor of impaired spatial analysis and synthesis, since understanding such grammatical relationships would also draw on their spatial relationships. Critically, Luria demonstrated the neural underpinnings of this syndrome with the critical implication of the cortex of the left temporal-parietal-occipital (TPO) junction. In this study, we report neuropsychological and lesion profiles of 10 new cases of semantic aphasia. Modern neuroimaging techniques provide support for the relevance of the left TPO area for semantic aphasia, but also extend Luria's neuroanatomical model by taking into account white matter pathways. Our findings suggest that tracts with parietal connectivity – the arcuate fasciculus (long and posterior segments), the inferior fronto-occipital fasciculus, the inferior longitudinal fasciculus, the superior longitudinal fasciculus II and III, and the corpus callosum – are implicated in the linguistic and non-linguistic deficits of patients with semantic aphasia.
Статья посвящена опыту разметки кореферентных связей в корпусе устных пересказов Russian CliPS (Khudyakova et al., 2016). Корпус пред- ставляет собой пересказ фильма о грушах (Chafe, 1980). В статье представлен анализ параметров, которые необходимо учитывать при разметке такого рода текстов. В результате анализа данных, мы пред- лагаем подходить к разметке кореферентных связей в устных текстах с позиции взаимодействия разных систем: собственно кореферентных цепочек в нарративе, элементов речевых сбоев (например, случаев пе- реименования референта и др.), а также элементов интеракции (напри- мер, оценка говорящим степени уверенности в выбранной номинации).
In the present paper we describe an approach to the dynamical clustering of fMRI resting state networks and their connections, in which we use two known mathematical methods for data analysis: topological data analysis and k-means method. With these two methods we found about 4 stable states in group analysis. Dynamics of these states is characterized by periods of stability (blocks) with subsequent transition to another state. Topological data analysis method allowed us to find some regularity in subsequent transitions between blocks of states for individuals but it was not shown that the regularity repeats in all subjects. Topological method gives smoother distribution of dynamic states comparing to k-means method, highlighting about 4 dominant states in percentage, while k-means method gives 1–2 such states.
The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.