Search

IntroductionCerebrovascular reactivity imaging (CVR) is a diagnostic method for assessment of alterations in cerebral blood flow in response to a controlled vascular stimulus. The principal utility is the capacity to evaluate the cerebrovascular reserve, thereby elucidating autoregulatory functioning. In CVR, CO2 gas challenge is the most prevalent method, which elicits a vascular response by alterations in inspired CO2 concentrations. While several systems have been proposed in the literature, only a limited number have been devised to operate in tandem with mechanical ventilation, thus constraining the majority CVR investigations to spontaneously breathing individuals.MethodsWe have developed a new method, denoted Additional CO2, designed to enable CO2 challenge in ventilators. The central idea is the introduction of an additional flow of highly concentrated CO2 into the respiratory circuit, as opposed to administration of the entire gas mixture from a reservoir. By monitoring the main respiratory gas flow emanating from the ventilator, the CO2 concentration in the inspired gas can be manipulated by adjusting the proportion of additional CO2. We evaluated the efficacy of this approach in (1) a ventilator coupled with a test lung and (2) in spontaneously breathing healthy subjects. The method was evaluated by assessment of the precision in attaining target inspired CO2 levels and examination of its performance within a magnetic resonance imaging environment.Results and discussionOur investigations revealed that the Additional CO2 method consistently achieved a high degree of accuracy in reaching target inspired CO2 levels in both mechanical ventilation and spontaneous breathing. We anticipate that these findings will lay the groundwork for a broader implementation of CVR assessments in mechanically ventilated patients.

Introduction: Cognitive impairments in epilepsy are not well-understood. In addition, long-term emotional, interpersonal, and social consequences of the underlying disturbances are important to evaluate.Purpose: To compare cognitive function including language in young adults with focal or generalized epilepsy. In addition, quality of life and self-esteem were investigated.Patients and Methods: Young adults with no primary intellectual disability, 17 with focal epilepsy and 11 with generalized epilepsy participated and were compared to 28 healthy controls. Groups were matched on age (mean = 26 years), sex, and education. Participants were administered a battery of neuropsychological tasks and carried out self-ratings of quality of life, self-esteem, and psychological problems.Results: Similar impairments regarding cognitive function were noted in focal and generalized epilepsy. The cognitive domains tested were episodic long-term memory, executive functions, attention, working memory, visuospatial functions, and language. Both epilepsy groups had lower results compared to controls (effect sizes 0.24–1.07). The total number of convulsive seizures was predictive of episodic long-term memory function. Participants with focal epilepsy reported lower quality of life than participants with generalized epilepsy. Lowered self-esteem values were seen in both epilepsy groups and particularly in those with focal epilepsy. Along with measures of cognitive speed and depression, the total number of seizures explained more than 50% of variation in quality of life.Conclusion: Interestingly, similarities rather than differences characterized the widespread cognitive deficits that were seen in focal and generalized epilepsy, ranging from mild to moderate. These similarities were modified by quality of life and self-esteem. This study confirms the notion that epilepsy is a network disorder.

Narcolepsy type 1 is a chronic sleep disorder with significantly higher BMI reported in more than 50% of adolescent patients, putting them at a higher risk for metabolic syndrome in adulthood. Although well-documented, the body fat distribution and mechanisms behind weight gain in narcolepsy are still not fully understood but may be related to the loss of orexin associated with the disease. Orexin has been linked to the regulation of brown adipose tissue (BAT), a metabolically active fat involved in energy homeostasis. Previous studies have used BMI and waist circumference to characterize adipose tissue increases in narcolepsy but none have investigated its specific distribution. Here, we examine adipose tissue distribution in 19 adolescent patients with narcolepsy type 1 and compare them to 17 of their healthy peers using full body magnetic resonance imaging (MRI). In line with previous findings we saw that the narcolepsy patients had more overall fat than the healthy controls, but contrary to our expectations there were no group differences in supraclavicular BAT, suggesting that orexin may have no effect at all on BAT, at least under thermoneutral conditions. Also, in line with previous reports, we observed that patients had more total abdominal adipose tissue (TAAT), however, we found that they had a lower ratio between visceral adipose tissue (VAT) and TAAT indicating a relative increase of subcutaneous abdominal adipose tissue (ASAT). This relationship between VAT and ASAT has been associated with a lower risk for metabolic disease. We conclude that while weight gain in adolescents with narcolepsy matches that of central obesity, the lower VAT ratio may suggest a lower risk of developing metabolic disease.

There is growing evidence as to the benefits of collecting BOLD fMRI data with increased sampling rates. However, many of the newly developed acquisition techniques developed to collect BOLD data with ultra-short TRs require hardware, software, and non-standard analytic pipelines that may not be accessible to all researchers. We propose to incorporate the method of shifted echo into a standard multi-slice, gradient echo EPI sequence to achieve a higher sampling rate with a TR of less than one second with acceptable spatial resolution. We further propose to incorporate temporal averaging of consecutively acquired EPI volumes to both ameliorate the reduced temporal signal-to-noise inherent in ultra-fast EPI sequences and reduce the data burden. BOLD data were collected from eleven healthy subjects performing a simple, event-related visual-motor task with four different EPI sequences: 1) reference EPI sequence with TR = 1440 ms, 2) shifted echo EPI sequence with TR = 700 ms, 3) shifted echo EPI sequence with every two consecutively acquired EPI volumes averaged and effective TR = 1400 ms, and 4) shifted echo EPI sequence with every four consecutively acquired EPI volumes averaged and effective TR = 2800 ms. Both the temporally averaged sequences exhibited increased temporal signal-to-noise over the shifted echo EPI sequence. The shifted echo sequence with every two EPI volumes averaged also had significantly increased BOLD signal change compared with the other three sequences, while the shifted echo sequence with every four EPI volumes averaged had significantly decreased BOLD signal change compared with the other three sequences. The results indicated that incorporating the method of shifted echo into a standard multi-slice EPI sequence is a viable method for achieving increased sampling rate for collecting event-related BOLD data. Further, consecutively averaging every two consecutively acquired EPI volumes significantly increased the measured BOLD signal change and the subsequently calculated activation map statistics.

Narcolepsy is a chronic sleep disorder caused by a loss of hypocretin-1 producing neurons in the hypothalamus. Previous neuroimaging studies have investigated brain function in narcolepsy during rest using positron emission tomography (PET) and single photon emission computed tomography (SPECT). In addition to hypothalamic and thalamic dysfunction they showed aberrant prefrontal perfusion and glucose metabolism in narcolepsy. Given these findings in brain structure and metabolism in narcolepsy, we anticipated that changes in functional magnetic resonance imaging (fMRI) resting state network (RSN) dynamics might also be apparent in patients with narcolepsy. The objective of this study was to investigate and describe brain microstate activity in adolescents with narcolepsy and correlate these to RSNs using simultaneous fMRI and electroencephalography (EEG). Sixteen adolescents (ages 13–20) with a confirmed diagnosis of narcolepsy were recruited and compared to age-matched healthy controls. Simultaneous EEG and fMRI data were collected during 10 min of wakeful rest. EEG data were analyzed for microstates, which are discrete epochs of stable global brain states obtained from topographical EEG analysis. Functional MRI data were analyzed for RSNs. Data showed that narcolepsy patients were less likely than controls to spend time in a microstate which we found to be related to the default mode network and may suggest a disruption of this network that is disease specific. We concluded that adolescents with narcolepsy have altered resting state brain dynamics.

In this functional magnetic resonance imaging (fMRI) study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal) thoughts and increase default mode network (DMN) activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention) but decreased recognition for unpleasantly-judged items (which depend on externallyoriented attention). To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding (SE) activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding (UE) recruits two key medial posterior DMN regions, the posterior cingulate cortex (PCC) and precuneus (PCU). A region of interest (ROI) analysis including classic DMN areas, revealed significantly greater involvement of the medial prefrontal cortex (mPFC) in pleasant compared to unpleasant judgments, suggesting this region's involvement in self-referential (i.e., internal) processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful) and pleasantness was observed for the PCC, PCU and inferior frontal gyrus (IFG). Overall, our results suggest the involvement of medial frontal and parietal DMN regions during the evaluation of self-referential pleasantness. We discuss these results in terms of the introspective referential of pleasantness judgments and the differential brain modulation based on internally- vs. externally-oriented attention during encoding. [ABSTRACT FROM AUTHOR]