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The ability to sustain attention differs across people and changes within a single person over time. Although recent work has demonstrated that patterns of functional brain connectivity predict individual differences in sustained attention, whether these same patterns capture fluctuations in attention within individuals remains unclear. Here, across five independent studies, we demonstrate that the sustained attention connectome-based predictive model (CPM), a validated model of sustained attention function, generalizes to predict attentional state from data collected across minutes, days, weeks, and months. Furthermore, the sustained attention CPM is sensitive to within-subject state changes induced by propofol as well as sevoflurane, such that individuals show functional connectivity signatures of stronger attentional states when awake than when under deep sedation and light anesthesia. Together, these results demonstrate that fluctuations in attentional state reflect variability in the same functional connectivity patterns that predict individual differences in sustained attention.

This work examines the influence of changes in baseline activity on the intrinsic functional connectivity fMRI (fc-fMRI) in humans. Baseline brain activity was altered by inducing anesthesia (sevoflurane end-tidal concentration 1%) in human volunteers and fc-fMRI maps between the pre-anesthetized and anesthetized conditions were compared across different brain networks. We particularly focused on low-level sensory areas (primary somatosensory, visual, and auditory cortices), the thalamus, and pain (insula), memory (hippocampus) circuits, and the default mode network (DMN), the latter three to examine higher-order brain regions. The results indicate that, while fc-fMRI patterns did not significantly differ (p<0.005; 20-voxel cluster threshold) in sensory cortex and in the DMN between the pre- and anesthetized conditions, fc-fMRI in high-order cognitive regions (i.e. memory and pain circuits) was significantly altered by anesthesia. These findings provide further evidence that fc-fMRI reflects intrinsic brain properties, while also demonstrating that 0.5 MAC sevoflurane anesthesia preferentially modulates higher-order connections.

Glutamatergic neurotransmission mediated by N -methyl- d -aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain’s global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate’s role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

Preclinical research suggests that N-methyl-D-aspartate glutamate receptors (NMDA-Rs) have a crucial role in working memory (WM). In this study, we investigated the role of NMDA-Rs in the brain activation and connectivity that subserve WM. Because of its importance in WM, the lateral prefrontal cortex, particularly the dorsolateral prefrontal cortex and its connections, were the focus of analyses. Healthy participants (n=22) participated in a single functional magnetic resonance imaging session. They received saline and then the NMDA-R antagonist ketamine while performing a spatial WM task. Time-course analysis was used to compare lateral prefrontal activation during saline and ketamine administration. Seed-based functional connectivity analysis was used to compare dorsolateral prefrontal connectivity during the two conditions and global-based connectivity was used to test for laterality in these effects. Ketamine reduced accuracy on the spatial WM task and brain activation during the encoding and early maintenance (EEM) period of task trials. Decrements in task-related activation during EEM were related to performance deficits. Ketamine reduced connectivity in the DPFC network bilaterally, and region-specific reductions in connectivity were related to performance. These results support the hypothesis that NMDA-Rs are critical for WM. The knowledge gained may be helpful in understanding disorders that might involve glutamatergic deficits such as schizophrenia and developing better treatments.

Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.

The analysis of spontaneous fluctuations of functional magnetic resonance imaging (fMRI) signals has recently gained attention as a powerful tool for investigating brain circuits in a non-invasive manner. Correlation-based connectivity analysis investigates the correlations of spontaneous fluctuations of the fMRI signal either between a single seed region of interest (ROI) and the rest of the brain or between multiple ROIs. To do this, a priori knowledge is required for defining the ROI(s) and without such knowledge functional connectivity fMRI cannot be used as an exploratory tool for investigating the functional organization of the brain and its modulation under different conditions. In this work we examine two indices that provide voxel based maps reflecting the intrinsic connectivity contrast (ICC) of individual tissue elements without the need for defining ROIs and hence require no a priori information or assumptions. These voxel based ICC measures can also be used to delineate regions of interest for further functional or network analyses. The indices were applied to the study of sevoflurane anesthesia-induced alterations in intrinsic connectivity. In concordance with previous studies, the results show that sevoflurane affects different brain circuits in a heterogeneous manner. In addition ICC analyses revealed changes in regions not previously identified using conventional ROI connectivity analyses, probably because of an inappropriate choice of the ROI in the earlier studies. This work highlights the importance of such voxel based connectivity methodology. ► We devised a novel metric to produce intrinsic connectivity contrast (ICC) maps. ► This new metric does not need a priori knowledge for defining any ROIs. ► ICC can be used as an exploratory tool for investigating the functional organization. ► ICC revealed sevoflurane-induced changes not identified by ROI connectivity analyses.

N -methyl-D-aspartate glutamate receptor (NMDA-R) antagonists produce schizophrenia-like positive and negative symptoms in healthy human subjects. Preclinical research suggests that NMDA-R antagonists interfere with the function of gamma-aminobutyric acid (GABA) neurons and alter the brain oscillations. These changes have been hypothesized to contribute to psychosis. In this investigation, we evaluated the hypothesis that the NMDA-R antagonist ketamine produces alterations in cortical functional connectivity during rest that are related to symptoms. We administered ketamine to a primary sample of 22 subjects and to an additional, partially overlapping, sample of 12 subjects. Symptoms before and after the experimental session were rated with the Positive and Negative Syndrome Scale (PANSS). In the primary sample, functional connectivity was measured via functional magnetic resonance imaging almost immediately after infusion began. In the additional sample, this assessment was repeated after 45 min of continuous ketamine infusion. Global, enhanced functional connectivity was observed at both timepoints, and this hyperconnectivity was related to symptoms in a region-specific manner. This study supports the hypothesis that pathological increases in resting brain functional connectivity contribute to the emergence of positive and negative symptoms associated with schizophrenia.

Glutamatergic neurotransmission mediated by N-methyl-d-aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain’s global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate’s role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

The ability to sustain attention differs across people and changes within a single person over time. Although recent work has demonstrated that patterns of functional brain connectivity predict individual differences in sustained attention, whether these same patterns capture fluctuations in attention in single individuals remains unclear. Here, across five independent studies, we demonstrate that the sustained attention connectome-based predictive model (CPM), a validated model of sustained attention function, generalizes to predict attention changes across minutes, days, weeks, and months. Furthermore, the sustained attention CPM is sensitive to within-subject state changes induced by propofol as well as sevoflurane, such that individuals show functional connectivity signatures of stronger attentional states when awake than when under deep sedation and light anesthesia. Together these results demonstrate that fluctuations in attentional state reflect variability in the same functional connectivity patterns that predict individual differences in sustained attention.

Neuraxial blockade is known to have a sedative effect, decreasing the need for inhalational and iv anesthetic agents. The purpose of the present study was to quantify the sedative effect of spinal anesthesia and to determine the time of maximum sedation. This is an observational study in which 20 unsedated patients were scheduled to undergo urologic and orthopedic surgeries under spinal anesthesia. Patients with pre-existing neurological conditions or receiving psychotropic medications were excluded from the study. All received 1.5 mL (11.25 mg) of hyperbaric bupivacaine 0.75% intrathecally. No sedative or narcotic was administered intravenously or intrathecally. The Patient State Analyzer, (PSA-4000) was used to monitor sedation along with Observer's Assessment of Alertness and Sedation (OAA/S) scores every five minutes. Differences in patient state index (PSI) and OAA/S scores are expressed as median and range and were evaluated by Wilcoxon's signed rank test for non-parametric data; P < 0.05 was considered significant. PSI, OAA/S and time at lowest score are expressed as median(range). PSI scores decreased from baseline 99 (96-99) to 78 (56-87) at 35(14.5-54) min into the spinal anesthetic (P < 0.05). OAA/S scores decreased from baseline 5 to 4 (range 3-5) at the time of the lowest PSI scores (P < 0.05). In this elderly patient population, spinal anesthesia induced changes in the processed electroencephalogram with reduction in PSI and OAA/S scores. The reduction in afferent input to the reticular activating system could possibly explain the sedation that has been observed and the reduction in the PSA scores.