Novel measure of the weigh distribution balance on the brain network: Graph complexity applied to schizophrenia

Abstract

Abstract-The aim of this study was to assess brain complexity dynamics in schizophrenia (SCH) patients during an auditory oddball task. For that task, we applied a novel graph measure based on the balance of the node weighs distribution. Previous studies applied complexity parameters that were strongly dependent on network topology. This fact could bias the results besides being necessary correction techniques as surrogating process. In the present study, we applied a novel graph complexity measure from the information theory: Shannon Graph Complexity (SGC). Complexity patterns form electroencephalographic recordings of 20 healthy controls and 20 SCH patients during an auditory oddball task were analyzed. Results showed a significantly more pronounced decrease of SGC for controls than for SCH patients during the cognitive task. These findings suggest an important change in the brain configuration towards more balanced networks, mainly in the connections related to longrange interactions. Since these changes are significantly more pronounced in controls, it implies a deficit in the neural network reorganization in SCH patients. In addition, SGC showed a suitable discrimination ability using a leave-one-out cross-validation: 0.725 accuracy and 0.752 area under receiver operating characteristics curve. The novel complexity measure proposed in this study demonstrated to be independent of network topology and, therefore, it complements traditional graph measures to characterize brain networks.

Characterization of Neural Activity using Complex Network Theory. Application to the Identification of the Altered Neural Substrates in Schizophrenia

“…In this regard, phase synchronization was suggested as a key mechanism of dynamical neuronal communication, and can provide a useful measure of neural integration in sensory task-relevant procedures [47]. These findings are consistent with another study that showed greater differences between controls and SCH patients in the assessment of the evoked response than in the evaluation of the total response (induced and evoked) in delta band [32]. Therefore, the significant reduction of the irregularity in the evoked response for controls and the less evident difference in the evoked response for SCH patients reveals that activation response is weakly phase-locked to stimulus in schizophrenia.…”

“…Low frequencies, like alpha band, are related to long-range interactions [20], suggesting that impaired activation response of long-range interactions might contribute to the pathological process. The lower irregularity reduction in the cognitive response of SCH patients seems to be associated with an abnormal information processing, as well as it could be related to the disrupted integrative functions of local and distributed neural circuits [32]. This result suggests that SCH is accompanied by a disrupted network reorganization of neural functions responsible of the P300 generation, mainly in long-range interaction.…”

“…9 In order to overcome these limitations, we introduce a novel definition of complexity that is independent of network topology. In our preliminary study, 32 we defined a novel graph complexity measure based on information theory; nevertheless, the dependences on basic network parameters were not assessed. SGC is based on analyzing the weight distribution balance of the network.…”

“…Specifically, we assessed the dynamic irregularity patterns through synchronized-averaging (SA) and single-trial (ST) analyses. Few studies addressed the characterization of neural dynamics considering these two approaches jointly [32]. Furthermore, to the best of our knowledge, irregularity patters using these two approaches have never been studied in SCH.…”