Citation classics in epilepsy

BACKGROUND: The impact of a scientific article is proportional to the citations it has received. In this study, we set out to identify the most cited works in epileptology in order to evaluate research trends in this field. METHODS: According to the Web of Science database, articles with more than 400 citations qualify as "citation classics". We conducted a literature search on the ISI Web of Science bibliometric database for scientific articles relevant to epilepsy. RESULTS: We retrieved 67 highly cited articles (400 or more citations), which were published in 31 journals: 17 clinical studies, 42 laboratory studies, 5 reviews and 3 classification articles. Clinical studies consisted of epidemiological analyses (n=3), studies on the clinical phenomenology of epilepsy (n=5) – including behavioral and prognostic aspects – and articles focusing on pharmacological (n=6) and non-pharmacological (n=3) treatment. The laboratory studies dealt with genetics (n=6), animal models (n=27), and neurobiology (n=9) – including both neurophysiology and neuropathology studies. The majority (61%) of citation classics on epilepsy were published after 1986, possibly reflecting the expansion of research interest in laboratory studies driven by the development of new methodologies, specifically in the fields of genetics and animal models. Consequently, clinical studies were highly cited both before and after the mid 80s, whilst laboratory researches became widely cited after 1990. CONCLUSIONS: Our study indicates that the main drivers of scientific impact in the field of epileptology have increasingly become genetic and neurobiological studies, along with research on animal models of epilepsy. These articles are able to gain the highest numbers of citations in the time span of a few years and suggest potential directions for future research

Modularità ed esperienza cosciente in una prospettiva neurocognitiva

Conscious experience seems to be an elusive matter of study for neuroscientific research. From an operational and neurocognitive point of view, however, conscious experience can be considered as a collection of events within a bidimensional framework. One dimension relates to wakefulness or the level of arousal, the other dimension relates to experiential contents, the objects of our phenomenal awareness. The variability of these two dimensions notwithstanding, the sense of conscious unity generally appears to be deep, real and immediate. Still, certain neurological conditions provide evidence for the hypothesis that this unity may be the result of a construction achieved by subtle and complex brain mechanisms. Taking the neurocognitive perspective, I will examine data coming from empirical research on patients with epilepsy and present some results from experiments conducted on split-brain patients and individuals in a minimally conscious state, which show how conscious experience may be rooted in the modular organisation of the brain

Pharmacological treatment of tics in Gilles de la Tourette Syndrome

Tourette syndrome is a neurodevelopmental disorder characterised by the chronic presence of multiple motor tics (e.g. eye blinking, shoulder shrugging, etc.) and at least one vocal/phonic tic (e.g. grunting or sniffing). The clinical picture of patients with Tourette syndrome is often complicated by tic-related behavioural problems and associated psychopathology. The pathophysiology of Tourette syndrome is poorly understood, however converging evidence from neuroimaging studies suggests abnormalities within the fronto-striatal pathways. The pharmacological management of the tic symptoms focuses on the dopaminergic and noradrenergic pathways and aims to improve the health-related quality of life of patients

Node detection using high-dimensional fuzzy parcellation applied to the insular cortex

Several functional connectivity approaches require the definition of a set of regions of interest (ROIs) that act as network nodes. Different methods have been developed to define these nodes and to derive their functional and effective connections, most of which are rather complex. Here we aim to propose a relatively simple “one-step” border detection and ROI estimation procedure employing the fuzzy c-mean clustering algorithm. To test this procedure and to explore insular connectivity beyond the two/three-region model currently proposed in the literature, we parcellated the insular cortex of 20 healthy right-handed volunteers scanned in a resting state. By employing a high-dimensional functional connectivity-based clustering process, we confirmed the two patterns of connectivity previously described. This method revealed a complex pattern of functional connectivity where the two previously detected insular clusters are subdivided into several other networks, some of which are not commonly associated with the insular cortex, such as the default mode network and parts of the dorsal attentional network. Furthermore, the detection of nodes was reliable, as demonstrated by the confirmative analysis performed on a replication group of subjects

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

•We present an innovative connectomic approach based on voxel-based morphometry (VBM) meta-data.•We mapped the topological configuration of gray matter abnormalities in autism spectrum disorder (ASD).•ASD co-alteration network tends to overlap with the pathways of structural brain connectivity.•Recognizable cerebral pathological hubs were captured by graph-analysis.•A core sub-network was identified, which provides insight into our understanding of ASD. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored. An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD. Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations. These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

It was recently suggested that in brain disorders neuronal alterations does not occur randomly, but tend to form patterns that resemble those of cerebral connectivity. Following this hypothesis, we studied the network formed by co-altered brain regions in patients with chronic pain. We used a meta-analytical network approach in order to: i) find out whether the neuronal alterations distribute randomly across the brain; ii) find out (in the case of a non-random pattern of distribution) whether a disease-specific pattern of brain co-alterations can be identified and characterized in terms of altered areas (nodes) and propagation links between them (edges); iii) verify whether the co-alteration pattern overlaps with the pattern of functional connectivity; iv) describe the topological properties of the co-alteration network and identify the highly connected nodes that are supposed to have a pre-eminent role in the diffusion timing of neuronal alterations across the brain. Our results indicate that: i) gray matter (GM) alterations do not occur randomly; ii) a symptom-related pattern of structural co-alterations can be identified for chronic pain; iii) this co-alteration pattern resembles the pattern of brain functional connectivity; iv) within the co-alteration network a set of highly connected nodes can be identified.This study provides further support to the hypothesis that neuronal alterations may spread according to the logic of a network-like diffusion suggesting that this type of distribution may also apply to chronic pain. Keywords: Chronic pain, Neuronal alterations, Pathoconnectomics, Co-alteration network, Network analysis, Voxel-based morphometr