Changes in functional brain network topology after successful and unsuccessful corpus callosotomy for Lennox-Gastaut Syndrome.
ABSTRACT: Corpus callosotomy (CC) is an effective palliative surgical treatment for patients with Lennox-Gastaut Syndrome (LGS). However, research on the long-term functional effects of CC is sparse. We aimed to investigate these effects and their associated clinical conditions over the two years after CC. Long-term clinical EEG recordings of 30 patients with LGS who had good and bad seizure outcome after CC were collected and retrospectively studied. It was found that CC caused brain network 'hubs' to shift from paramedian to lateral regions in the good-recovery group, which reorganized the brain network into a more homogeneous state. We also found increased local clustering coefficients in patients with bad outcomes and decreases, implying enhanced network integration, in patients with good outcomes. The small worldness of brain networks in patients with good outcomes increased in the two years after CC, whereas it decreased in patients with bad outcomes. The covariation of small-worldness with the rate of reduction in seizure frequency suggests that this can be used as an indicator of CC outcome. Local and global network changes during the long-term state might be associated with the postoperative recovery process and could serve as indicators for CC outcome and long-term LGS recovery.
Project description:<h4>Objectives</h4>This study aimed to investigate the functional network effects of corpus callosotomy (CC), a well-recognized palliative surgical therapy for patients with Lennox-Gastaut syndrome (LGS). Specifically, we sought to gain insight into the effects of CC on LGS remission, based on brain networks in LGS by calculating network metrics and evaluating by network measures before and after surgery.<h4>Methods</h4>Electroencephalographic recordings made during preoperative and 3-month postoperative states in 14 patients with LGS who had undergone successful CC were retrospectively analyzed. First, undirected correlation matrices were constituted for the mathematical expression of functional networks. Then, we plotted these networks to analyze the effects of CC on connectivity. In addition, conventional local and global network measures were applied to evaluate differences in network topology between preoperative and postoperative states.<h4>Results</h4>In the preoperative state, hubs were mainly distributed around the paramedian regions. After CC, the hubs moved from the paramedian regions to the dual-hemisphere and even the lateral regions. Thus, the general connectivity state became more homogeneous, which was verified by network plots and statistical analysis of local measures. The results of global network measures indicated a decreased clustering coefficient in the delta band, decreased characteristic path length in both the delta and gamma bands, and increased global efficiency in the gamma band.<h4>Conclusion</h4>Our results showed a consistent variation in the global brain network that converted to a small-world topology with an optimal balance of functional integration and segregation of the network. Such changes were positively correlated with satisfactory surgery results, which could be interpreted as being indicative of LGS recovery process after CC. For patients with refractory LGS along with no focal epileptogenic zone findings, which were not suitable for the resective surgical therapy, our results verified that CC could work as an effective surgical treatment option.
Project description:Targeted speech therapy can lead to substantial naming improvement in some subjects with anomia following dominant-hemisphere stroke. We investigated whether treatment-induced improvement in naming is associated with poststroke preservation of structural neural network architecture.Twenty-four patients with poststroke chronic aphasia underwent 30 hours of speech therapy over a 2-week period and were assessed at baseline and after therapy. Whole brain maps of neural architecture were constructed from pretreatment diffusion tensor magnetic resonance imaging to derive measures of global brain network architecture (network small-worldness) and regional network influence (nodal betweenness centrality). Their relationship with naming recovery was evaluated with multiple linear regressions.Treatment-induced improvement in correct naming was associated with poststroke preservation of global network small worldness and of betweenness centrality in temporal lobe cortical regions. Together with baseline aphasia severity, these measures explained 78% of the variability in treatment response.Preservation of global and left temporal structural connectivity broadly explains the variability in treatment-related naming improvement in aphasia. These findings corroborate and expand on previous classical lesion-symptom mapping studies by elucidating some of the mechanisms by which brain damage may relate to treated aphasia recovery. Favorable naming outcomes may result from the intact connections between spared cortical areas that are functionally responsive to treatment.
Project description:With the aim to identify rare genetic variation involved in stroke recovery, this is a pilot study on extreme phenotypes of good and bad recovery.
Exome sequencing was performed on 41 and 49 samples in the bad and good recovery subset, respectively.
Rare Variant association Analysis was performed on the exome sequencing results.
Project description:A main goal in the analysis of a complex system is to infer its underlying network structure from time-series observations of its behaviour. The inference process is often done by using bi-variate similarity measures, such as the cross-correlation (CC) or mutual information (MI), however, the main factors favouring or hindering its success are still puzzling. Here, we use synthetic neuron models in order to reveal the main topological properties that frustrate or facilitate inferring the underlying network from CC measurements. Specifically, we use pulse-coupled Izhikevich neurons connected as in the Caenorhabditis elegans neural networks as well as in networks with similar randomness and small-worldness. We analyse the effectiveness and robustness of the inference process under different observations and collective dynamics, contrasting the results obtained from using membrane potentials and inter-spike interval time-series. We find that overall, small-worldness favours network inference and degree heterogeneity hinders it. In particular, success rates in C. elegans networks - that combine small-world properties with degree heterogeneity - are closer to success rates in Erdös-Rényi network models rather than those in Watts-Strogatz network models. These results are relevant to understand better the relationship between topological properties and function in different neural networks.
Project description:Research suggests that disruption of brain networks might explain cognitive deficits in multiple sclerosis (MS). The reliability and effectiveness of graph theoretic network metrics as measures of cognitive performance were tested in 37 people with MS and 23 controls. Specifically, relationships with cognitive performance (linear regression against the paced auditory serial addition test-3 seconds [PASAT-3], symbol digit modalities test [SDMT], and attention network test) and 1-month reliability (using the intraclass correlation coefficient [ICC]) of network metrics were measured using both resting-state functional and diffusion magnetic resonance imaging data. Cognitive impairment was directly related to measures of brain network segregation and inversely related to network integration (prediction of PASAT-3 by small worldness, modularity, characteristic path length, R2?=?0.55; prediction of SDMT by small worldness, global efficiency, and characteristic path length, R2?=?0.60). Reliability of the measures for 1 month in a subset of nine participants was mostly rated as good (ICC >0.6) for both controls and MS patients in both functional and diffusion data, but was highly dependent on the chosen parcellation and graph density, with the 0.2-0.5 density range being the most reliable. This suggests that disrupted network organization predicts cognitive impairment in MS and its measurement is reliable for a 1-month period. These new findings support the hypothesis of network disruption as a major determinant of cognitive deficits in MS and the future possibility of the application of derived metrics as surrogate outcomes in trials of therapies for cognitive impairment.
Project description:Morphological alterations of brain structure are generally assumed to be involved in the pathophysiology of obsessive–compulsive disorder (OCD). Yet, little is known about the morphological connectivity properties of structural brain networks in OCD or about the heritability of those morphological connectivity properties. To better understand these properties, we conducted a study that defined three different groups: OCD group with 30 subjects, siblings group with 19 subjects, and matched controls group with 30 subjects. A structural brain network was constructed using 68 cortical regions of each subject within their respective group (i.e., one brain network for each group). Both small-worldness and modularity were measured to reflect the morphological connectivity properties of each constructed structural brain network. When compared to the matched controls, the structural brain networks of patients with OCD indeed exhibited atypical small-worldness and modularity. Specifically, small-worldness showed decreased local efficiency, and modularity showed reduced intra-connectivity in Module III (default mode network) and increased interconnectivity between Module I (executive function) and Module II (cognitive control/spatial). Intriguingly, the structured brain networks of the unaffected siblings showed similar small-worldness and modularity as OCD patients. Based on the atypical structural brain networks observed in OCD patients and their unaffected siblings, abnormal small-worldness and modularity may indicate a candidate endophenotype for OCD.
Project description:The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.
Project description:Patient-reported outcomes (PROs) have been previously considered "soft" end-points because of the lack of association of the reported outcome to measurable biological parameters. The present study aimed to assess whether electrocardiographic measures are associated to PROs changes. We evaluated the association between heart rate (HR), QRS and QT/QTc durations and PROs, classified as "good" or "bad" according to the patients' overall feeling of health, in patients from the Chiron project. Twenty-four chronic heart failure (HF) patients were enrolled in the study (71% male, mean age 62.9?±?9.4 years, 42% ischemic etiology, 15 NYHA class II and 9 class III) providing 1086 days of usable physiological recordings (4?hours/day). The mean HR was significantly higher in the "bad" than in the "good" PROs class (74.0?±?6.4 bpm vs 68.0?±?7.2 bpm; p?<?0.001). Conversely, the ratio between movement and rest activities showed significantly higher values in "good" compared to "bad" PROs. We also found significantly longer QTc and QRS durations in patients with "bad" PROs compared to patients with "good" PROs. That in patients with mild to moderate HF, higher HR, wider QRS and longer QTc, as well as a reduced HR ratio between movement and rest, were associated with "bad" PROs is clinically noteworthy because the association of worse PROs with measurable variations of biological parameters may help physicians in evaluating PROs reliability itself and in their clinical decisions. Whether a timely intervention on these biological parameters may prevent adverse outcomes is important and deserves to be investigated in further studies.
Project description:Corpus callosotomy (CC) is the surgical strategy for drug-resistant epileptic seizures including epileptic spasms (ES). In this study we report a subtype of ES which is accompanied by two consecutive muscular contractions. This subtype has not been previously classified and may emerge via a complex epileptic network. We named these seizures "epileptic spasms with biphasic muscular contractions (ES-BMC)" and analyzed the association between them and CC outcomes. We enrolled 17 patients with ES who underwent CC before 20 years of age, and analyzed the records of long-term video-electroencephalogram (EEG) recordings. The outcomes of CC were ES-free (Engel's classification I) in 7 and residual ES (II to IV) in 10 patients. We statistically analyzed the associations between the presence of preoperative ES-BMC and the outcomes. Ages at CC ranged from 17 to 237 months. We analyzed 4-44 ictal EEGs for each patient. Five patients presented with ES-BMC with 6-40% of their whole ES on the presurgical video-EEG recordings, and all of them exhibited residual ES outcomes following CC. A Fisher's exact test revealed a significant positive correlation between the presence of preoperative ES-BMC and persistence of ES following CC (p = 0.044, odds ratio = 15.0, risk ratio = 2.0). The presence of ES-BMC may be useful in the presurgical prediction of CC outcomes in patients with ES.
Project description:Cortical thickness and gyrification abnormalities in anorexia nervosa (AN) have been recently described, but no attempt has been made to explore their organizational patterns to characterize the neurobiology of the disorder in the different stages of its course. The aim of this study was to explore cortical thickness and gyrification patterns by means of graph theory tools in 38 patients with AN, 20 fully recovered patients, and 38 healthy women (HC). All participants underwent high-resolution magnetic resonance imaging. Connectome properties were compared between: 1) AN patients and HC, 2) fully recovered patients and HC, 3) patients with a full remission at a 3-year follow-up assessment and patients who had not recovered. Small-worldness was greater in patients with acute AN in comparison to HC in both cortical thickness and gyrification networks. In the cortical thickness network, patients with AN also showed increased Local Efficiency, Modularity and Clustering coefficients, whereas integration measures were lower in the same group. Patients with a poor outcome showed higher segregation measures and lower small-worldness in the gyrification network, but no differences emerged for the cortical thickness network. For both cortical thickness and gyrification patterns, regional analyses revealed differences between patients with different outcomes. Different patterns between cortical thickness and gyrification networks are probably due to their peculiar developmental trajectories and sensitivity to environmental influences. The role of gyrification network alterations in predicting the outcome suggests a role of early maturational processes in the prognosis of AN.