Showing papers by "Rajanikant Panda published in 2023"
TL;DR: In this paper , the authors study the propagation of endogenous and in-silico exogenous perturbations in patients with disorders of consciousness, based upon directed and causal interactions estimated from resting-state fMRI data, fitted to a linear model of activity propagation.
Abstract: The study of the brain's dynamical activity is opening a window to help the clinical assessment of patients with disorders of consciousness. For example, glucose uptake and the dysfunctional spread of naturalistic and synthetic stimuli has proven useful to characterize hampered consciousness. However, understanding of the mechanisms behind loss of consciousness following brain injury is still missing. Here, we study the propagation of endogenous and in‐silico exogenous perturbations in patients with disorders of consciousness, based upon directed and causal interactions estimated from resting‐state fMRI data, fitted to a linear model of activity propagation. We found that patients with disorders of consciousness suffer decreased capacity for neural propagation and responsiveness to events, and that this can be related to severe reduction of glucose metabolism as measured with [18F]FDG‐PET. In particular, we show that loss of consciousness is related to the malfunctioning of two neural circuits: the posterior cortical regions failing to convey information, in conjunction with reduced broadcasting of information from subcortical, temporal, parietal and frontal regions. These results shed light on the mechanisms behind disorders of consciousness, triangulating network function with basic measures of brain integrity and behavior.
2 citations
TL;DR: After a single session rTMS, the connectivity measures approached normality and patients with ET revealed significantly higher integration, lower segregation with higher metastability and increased intrinsic ignition.
Abstract: Background Emerging evidence support the view that brain stimulation might improve essential tremor (ET) by altering brain networks and facilitating plasticity. Yet, we are still missing a mechanistic explanation of the whole brain dynamics underlying these plasticity defining changes. Method In this study, we explored the effect of low-frequency repetitive transcranial magnetic stimulation (rTMS) over left primary motor cortex (L-M1) on functional connectivity dynamics (FCD) in patients with ET. Resting-state fMRI (RsfMRI) was acquired before and after a single session of rTMS in 30 patients with ET and compared with RsfMRI of 20 age and gender matched healthy controls (HCs). We have measured the effect of brain stimulation using network topological re-organization through whole brain integration and segregation, brain stability and capacity of neural propagation through metastability and intrinsic ignition. Results Patients with ET had altered FCD measures compared to controls. After a single session rTMS, the brain connectivity measures approached normality and patients with ET revealed significantly higher integration, lower segregation with higher metastability and increased intrinsic ignition. Conclusion Brain metastability and intrinsic ignition measures could be valuable tools in appreciating mechanisms of brain stimulation in ET and other neurological diseases.
1 citations
TL;DR: In this paper , the authors investigated the role of the default mode network (DMN) in individuals with disorders of consciousness (DoC), such as unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) and employed a robust cross-validation approach, which demonstrated that the connectivity between frontal and left parietal brain regions reliably distinguish UWS patients from MCS patients and controls.
Abstract: Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states – unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) – is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially “covert” awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET-diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET– and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET– with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET– from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET– from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG– based effective connectivity for identifying patients with potential covert awareness. Author Summary Our study investigates the role of the Default Mode Network (DMN) in individuals with disorders of consciousness (DoC), such as unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Previous neuroimaging studies have suggested a role for the DMN in DoC, but its ability to differentiate between UWS and MCS remain unclear. Using advance brain imaging and modelling techniques, we analyzed data from DoC patients with traumatic brain injury and healthy controls. Our findings reveal a key difference in left frontoparietal connectivity when comparing UWS to MCS patients and healthy individuals. To validate our results, we employed a robust cross-validation approach, which demonstrated that the connectivity between frontal and left parietal brain regions reliably discriminates UWS patients from MCS patients and controls. Furthermore, we extended our analysis to include patients with potential covert awareness, showcasing the clinical utility of our findings. We successfully classified these patients as conscious with high accuracy. This research significantly contributes to our understanding of the DMN in DoC and highlights the potential use of electroencephalography-based connectivity analysis in clinical settings. By identifying specific alterations in the DMN after severe brain injury, our study may aid in the accurate diagnosis and management of individuals with disorders of consciousness, potentially improving their overall outcomes.
TL;DR: Transient erythroblastopenia of childhood (TEC) is a rare and benign condition characterized by moderate to severe normocytic anemia with low reticulocytes and a spontaneous recovery as mentioned in this paper .
TL;DR: In this paper , the effect of lemon essential oil inhalation on healthy participants' alertness level and their neural correlates using magnetic resonance imaging (MRI) was examined using the Karolinska Sleepiness Scale.
TL;DR: In this paper , the authors investigated altered brain dynamics during the non-ordinary state of consciousness induced by hypnosis and found increased delta connectivity between left and right frontal, as well as between right frontal and parietal regions, decreased connectivity for alpha and beta-2 bands.
Abstract: Hypnosis has been shown to be of clinical utility; however, its underlying neural mechanisms remain unclear. This study aims to investigate altered brain dynamics during the non-ordinary state of consciousness induced by hypnosis. We studied high-density EEG in 9 healthy participants during eyes-closed wakefulness and during hypnosis, induced by a muscle relaxation and eyes fixation procedure. Using hypotheses based on internal and external awareness brain networks, we assessed region-wise brain connectivity between 6 ROI (right and left frontal, right and left parietal, upper and lower midline regions) at the scalp level and compared across conditions. Data-driven, graph-theory analyses were also carried out to characterize brain network topology in terms of brain network segregation and integration. During hypnosis, we observed (1) increased delta connectivity between left and right frontal, as well as between right frontal and parietal regions, (2) decreased connectivity for alpha (between right frontal and parietal and between upper and lower midline regions) and beta-2 bands (between upper midline and right frontal, frontal and parietal, also between upper and lower midline regions), and (3) increased network segregation (short-range connections) in delta and alpha bands, and increased integration (long-range connections) in beta-2 band. These higher network integration and segregation were measured bilaterally in frontal and right parietal electrodes, which were identified as central hub regions during hypnosis. This modified connectivity and increased network integration-segregation properties suggest a modification of the internal and external awareness brain networks that may reflect efficient cognitive-processing and lower incidences of mind-wandering during hypnosis.
TL;DR: In this paper , an information-theoretical approach based on intrinsic ignition and the concept of transfer entropy (TE) was applied to assess the spatiotemporal dynamics after VIM-MRgFUS.
TL;DR: In this article , the authors presented the brain-imaging method of resting-state fMRI (rs-fMRI) and illustrates its application in neuroentrepreneurship for the first time.
Abstract: Despite many calls, functional brain magnetic resonance imaging (fMRI) studies are relatively rare in the domain of entrepreneurship research. This methodological brief presents the brain-imaging method of resting-state fMRI (rs-fMRI) and illustrates its application in neuroentrepreneurship for the first time. In contrast to the traditional task-based fMRI approach, rs-fMRI observes the brain in the absence of cognitive tasks or presentation of stimuli, which offers benefits for improving our understanding of the entrepreneurial mind. Here, we describe the method and provide methodological motivations for performing brain resting-state functional neuroimaging studies on entrepreneurs. In addition, we illustrate the use of seed-based correlation analysis, one of the most common analytical approaches for analyzing rs-fMRI data. In this illustration, we show that habitual entrepreneurs have increased functional connectivity between the insula (a region associated with cognitive flexibility) and the anterior prefrontal cortex (a key region for explorative choice) as compared to managers. This increased connectivity could help promote flexible behavior. Thus in brief, we provide an exemplar of a novel way to expand our understanding of the brain in the domain of entrepreneurship. We discuss possible directions for future research and challenges to be addressed to facilitate the inclusion of re-fMRI studies into neuroentrepreneurship.