The Thalamus and Brainstem Act As Key Hubs in Alterations of Human Brain Network Connectivity Induced by Mild Propofol Sedation

Despite their routine use during surgical procedures, no consensus has yet been reached on the precise mechanisms by which hypnotic anesthetic agents produce their effects. Molecular, animal and human studies have suggested disruption of thalamocortical communication as a key component of anesthetic action at the brain systems level. Here, we used the anesthetic agent, propofol, to modulate consciousness and to evaluate differences in the interactions of remote neural networks during altered consciousness. We investigated the effects of propofol, at a dose that produced mild sedation without loss of consciousness, on spontaneous cerebral activity of 15 healthy volunteers using functional magnetic resonance imaging (fMRI), exploiting oscillations (<0.1 Hz) in blood oxygenation level-dependent signal across functionally connected brain regions. We considered the data as a graph, or complex network of nodes and links, and used eigenvector centrality (EC) to characterize brain network properties. The EC mapping of fMRI data in healthy humans under propofol mild sedation demonstrated a decrease of centrality of the thalamus versus an increase of centrality within the pons of the brainstem, highlighting the important role of these two structures in regulating consciousness. Specifically, the decrease of thalamus centrality results from its disconnection from a widespread set of cortical and subcortical regions, while the increase of brainstem centrality may be a consequence of its increased influence, in the mildly sedated state, over a few highly central cortical regions key to the default mode network such as the posterior and anterior cingulate cortices

Effects of caffeine on reaction time are mediated by attentional rather than motor processes

Background Caffeine has a well-established effect on reaction times (RTs) but the neurocognitive mechanisms underlying this are unclear. Methods In the present study, 15 female participants performed an oddball task after ingesting caffeine or a placebo, and electroencephalographic data were obtained. Single-trial P3b latencies locked to the stimulus and to the response were extracted and mediation models were fitted to the data to test whether caffeine’s effect on RTs was mediated by its effect on either type of P3b latencies. Results Stimulus-locked latencies showed clear evidence of mediation, with approximately a third of the effect of caffeine on RTs running through the processes measured by stimulus-locked latencies. Caffeine did not affect response-locked latencies, so could not mediate the effect. Discussion These findings are consistent with caffeine’s effect on RTs being a result of its effect on perceptual-attentional processes, rather than motor processes. The study is the first to apply mediation analysis to single-trial P3b data and this technique holds promise for mental chronometric studies into the effects of psychopharmacological agents. The R code for performing the single trial analysis and mediation analysis are included as supplementary materials

Psychogenic Seizure Imitating Narcolepsy

Psychogenic or functional neurological disorders (FND) often occur in the practice of a neurologist. Diagnosis of FND usually causes significant difficulties. Among FND, psychogenic non-epileptic seizures (PNES) comprise around 40% cases. Sometimes it is necessary to differentiate PNES from narcolepsy. We describe a 55-year-old man with frequent brief and sudden sleep-like attacks in combination with nocturnal sleep disturbance. During attacks he was unresponsive, snoring but maintained posture. He resisted passive eye opening but with rolling eyes. The patient was confused on waking. In the interictal period, there were FND signs including give-way weakness of the left hand, typical functional “leg-dragging” gait, mistake in the finger-to-nose test. Video-electroencephalogram monitoring did not detect specific epileptic activity or sleep pattern during the attacks. Polysomnography showed multiple waking episodes during the night, but no typical pattern of narcolepsy was found in the multiple sleep latency test. The patient had frequent urgent hospitalizations due to different diseases and numerous invasive procedures. Six month later, the patient obtained state related disability financial benefit, after which hospitalizations in various hospitals continued, and PNES became shorter and less pronounced. </jats:p

Extracting drug mechanism and pharmacodynamic information from clinical electroencephalographic data using generalised semi-linear canonical correlation analysis

Conventional analysis of clinical resting electroencephalography (EEG) recordings typically involves assessment of spectral power in pre-defined frequency bands at specific electrodes. EEG is a potentially useful technique in drug development for measuring the pharmacodynamic (PD) effects of a centrally acting compound and hence to assess the likelihood of success of a novel drug based on pharmacokinetic-pharmacodynamic (PK-PD) principles. However, the need to define the electrodes and spectral bands to be analysed a priori is limiting where the nature of the drug-induced EEG effects is initially not known. We describe the extension to human EEG data of a generalised semi-linear canonical correlation analysis (GSLCCA), developed for small animal data. GSLCCA uses data from the whole spectrum, the entire recording duration and multiple electrodes. It provides interpretable information on the mechanism of drug action and a PD measure suitable for use in PK-PD modelling. Data from a study with low (analgesic) doses of the μ-opioid agonist, remifentanil, in 12 healthy subjects were analysed using conventional spectral edge analysis and GSLCCA. At this low dose, the conventional analysis was unsuccessful but plausible results consistent with previous observations were obtained using GSLCCA, confirming that GSLCCA can be successfully applied to clinical EEG data

Extracting drug mechanism and pharmacodynamic information from clinical electroencephalographic data using generalised semi-linear canonical correlation analysis

Conventional analysis of clinical resting electroencephalography (EEG) recordings typically involves assessment of spectral power in pre-defined frequency bands at specific electrodes. EEG is a potentially useful technique in drug development for measuring the pharmacodynamic (PD) effects of a centrally acting compound and hence to assess the likelihood of success of a novel drug based on pharmacokinetic-pharmacodynamic (PK-PD) principles. However, the need to define the electrodes and spectral bands to be analysed a priori is limiting where the nature of the drug-induced EEG effects is initially not known. We describe the extension to human EEG data of a generalised semi-linear canonical correlation analysis (GSLCCA), developed for small animal data. GSLCCA uses data from the whole spectrum, the entire recording duration and multiple electrodes. It provides interpretable information on the mechanism of drug action and a PD measure suitable for use in PK-PD modelling. Data from a study with low (analgesic) doses of the μ-opioid agonist, remifentanil, in 12 healthy subjects were analysed using conventional spectral edge analysis and GSLCCA. At this low dose, the conventional analysis was unsuccessful but plausible results consistent with previous observations were obtained using GSLCCA, confirming that GSLCCA can be successfully applied to clinical EEG data