A substantial minority of patients who survive an acquired brain injury develop a state of sympathetic hyperactivity that can persist for weeks or months, consisting of periodic episodes of increased ...heart rate and blood pressure, sweating, hyperthermia, and motor posturing, often in response to external stimuli. The unifying term for the syndrome—paroxysmal sympathetic hyperactivity (PSH)—and clear diagnostic criteria defined by expert consensus were only recently established. PSH has predominantly been described after traumatic brain injury (TBI), in which it is associated with worse outcomes. The pathophysiology of the condition is not completely understood, although most researchers consider it to be a disconnection syndrome with paroxysms driven by a loss of inhibitory control over excitatory autonomic centres. Although therapeutic strategies to alleviate sympathetic outbursts have been proposed, their effects on PSH are inconsistent between patients and their influence on outcome is unknown. Combinations of drugs are frequently used and are chosen on the basis of local custom, rather than on objective evidence. New rigorous tools for diagnosis could allow better characterisation of PSH to enable stratification of patients for future therapeutic trials.
Summary Severe traumatic brain injury (TBI) is currently managed in the intensive care unit with a combined medical–surgical approach. Treatment aims to prevent additional brain damage and to ...optimise conditions for brain recovery. TBI is typically considered and treated as one pathological entity, although in fact it is a syndrome comprising a range of lesions that can require different therapies and physiological goals. Owing to advances in monitoring and imaging, there is now the potential to identify specific mechanisms of brain damage and to better target treatment to individuals or subsets of patients. Targeted treatment is especially relevant for elderly people—who now represent an increasing proportion of patients with TBI—as preinjury comorbidities and their therapies demand tailored management strategies. Progress in monitoring and in understanding pathophysiological mechanisms of TBI could change current management in the intensive care unit, enabling targeted interventions that could ultimately improve outcomes.
Concurrent with mental processes that require rigorous computation and control, a series of automated decisions and actions govern our daily lives, providing efficient and adaptive responses to ...environmental demands. Using a cognitive flexibility task, we show that a set of brain regions collectively known as the default mode network plays a crucial role in such “autopilot” behavior, i.e., when rapidly selecting appropriate responses under predictable behavioral contexts. While applying learned rules, the default mode network shows both greater activity and connectivity. Furthermore, functional interactions between this network and hippocampal and parahippocampal areas as well as primary visual cortex correlate with the speed of accurate responses. These findings indicate a memory-based “autopilot role” for the default mode network, which may have important implications for our current understanding of healthy and adaptive brain processing.
Traumatic brain injury (TBI) can have lifelong and dynamic effects on health and wellbeing. Research on the long-term consequences emphasises that, for many patients, TBI should be conceptualised as ...a chronic health condition. Evidence suggests that functional outcomes after TBI can show improvement or deterioration up to two decades after injury, and rates of all-cause mortality remain elevated for many years. Furthermore, TBI represents a risk factor for a variety of neurological illnesses, including epilepsy, stroke, and neurodegenerative disease. With respect to neurodegeneration after TBI, post-mortem studies on the long-term neuropathology after injury have identified complex persisting and evolving abnormalities best described as polypathology, which includes chronic traumatic encephalopathy. Despite growing awareness of the lifelong consequences of TBI, substantial gaps in research exist. Improvements are therefore needed in understanding chronic pathologies and their implications for survivors of TBI, which could inform long-term health management in this sizeable patient population.
Traumatic axonal injury (TAI) is an important pathoanatomical subgroup of traumatic brain injury (TBI) and a major driver of mortality and functional impairment. Experimental models have provided ...insights into the effects of mechanical deformation on the neuronal cytoskeleton and the subsequent processes that drive axonal injury. There is also increasing recognition that axonal or white matter loss may progress for years post-injury and represent one mechanistic framework for progressive neurodegeneration after TBI. Previous trials of novel therapies have failed to make an impact on clinical outcome, in both TBI in general and TAI in particular. Recent advances in understanding the cellular and molecular mechanisms of injury have the potential to translate into novel therapeutic targets.
Traumatic brain injury (TBI) is a critical public health and socio-economic problem throughout the world. Reliable quantification of the burden caused by TBI is difficult owing to inadequate ...standardization and incomplete capture of data on the incidence and outcome of brain injury, with variability in the definition of TBI being partly to blame. Reports show changes in epidemiological patterns of TBI: the median age of individuals who experience TBI is increasing, and falls have now surpassed road traffic incidents as the leading cause of this injury. Despite claims to the contrary, no clear decrease in TBI-related mortality or improvement of overall outcome has been observed over the past two decades. In this Perspectives article, we discuss the strengths and limitations of epidemiological studies, address the variability in its definition, and highlight changing epidemiological patterns. Taken together, these analyses identify a great need for standardized epidemiological monitoring in TBI.
Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between ...low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The default mode network (DMN) has been traditionally assumed to hinder behavioral performance in externally focused, goal-directed paradigms and to provide no active contribution to human cognition. ...However, recent evidence suggests greater DMN activity in an array of tasks, especially those that involve self-referential and memory-based processing. Although data that robustly demonstrate a comprehensive functional role for DMN remains relatively scarce, the global workspace framework, which implicates the DMN in global information integration for conscious processing, can potentially provide an explanation for the broad range of higher-order paradigms that report DMN involvement. We used graph theoretical measures to assess the contribution of the DMN to global functional connectivity dynamics in 22 healthy volunteers during an fMRI-based n-back working-memory paradigm with parametric increases in difficulty. Our predominant finding is that brain modularity decreases with greater task demands, thus adapting a more global workspace configuration, in direct relation to increases in reaction times to correct responses. Flexible default mode regions dynamically switch community memberships and display significant changes in their nodal participation coefficient and strength, which may reflect the observed whole-brain changes in functional connectivity architecture. These findings have important implications for our understanding of healthy brain function, as they suggest a central role for the DMN in higher cognitive processing.
The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its interactions with other networks and offer an explanation within the global workspace theoretical framework. These promising findings may help redefine our understanding of the exact DMN role in human cognition.
Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable ...consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The invasive nature of the current methods for monitoring of intracranial pressure (ICP) has prevented their use in many clinical situations. Several attempts have been made to develop methods to ...monitor ICP non-invasively. The aim of this study is to assess the relationship between ultrasound-based non-invasive ICP (nICP) and invasive ICP measurement in neurocritical care patients.
This was a prospective, single-cohort observational study of patients admitted to a tertiary neurocritical care unit. Patients with brain injury requiring invasive ICP monitoring were considered for inclusion. nICP was assessed using optic nerve sheath diameter (ONSD), venous transcranial Doppler (vTCD) of straight sinus systolic flow velocity (FVsv), and methods derived from arterial transcranial Doppler (aTCD) on the middle cerebral artery (MCA): MCA pulsatility index (PIa) and an estimator based on diastolic flow velocity (FVd). A total of 445 ultrasound examinations from 64 patients performed from 1 January to 1 November 2016 were included. The median age of the patients was 53 years (range 37-64). Median Glasgow Coma Scale at admission was 7 (range 3-14), and median Glasgow Outcome Scale was 3 (range 1-5). The mortality rate was 20%. ONSD and FVsv demonstrated the strongest correlation with ICP (R = 0.76 for ONSD versus ICP; R = 0.72 for FVsv versus ICP), whereas PIa and the estimator based on FVd did not correlate with ICP significantly. Combining the 2 strongest nICP predictors (ONSD and FVsv) resulted in an even stronger correlation with ICP (R = 0.80). The ability to detect intracranial hypertension (ICP ≥ 20 mm Hg) was highest for ONSD (area under the curve AUC 0.91, 95% CI 0.88-0.95). The combination of ONSD and FVsv methods showed a statistically significant improvement of AUC values compared with the ONSD method alone (0.93, 95% CI 0.90-0.97, p = 0.01). Major limitations are the heterogeneity and small number of patients included in this study, the need for specialised training to perform and interpret the ultrasound tests, and the variability in performance among different ultrasound operators.
Of the studied ultrasound nICP methods, ONSD is the best estimator of ICP. The novel combination of ONSD ultrasonography and vTCD of the straight sinus is a promising and easily available technique for identifying critically ill patients with intracranial hypertension.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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