Neuromagnetic effects of pico-Tesla stimulation

We used a double-blind experimental design to look for an effect of pico-Tesla magnetic stimulation in healthy subjects. Pico-Tesla stimulation is thought to increase the dominant frequency of 2–7 Hz oscillations in the human brain. We used magnetoencephalography to measure resting state brain activity. Each subject had two separate recording sessions consisting of three runs in between which they were given real or sham pT stimulation. We then tried to predict the real and sham stimulation sessions based on changes in the mean peak frequency in the 2–7 Hz band. Our predictions for these individual runs were 8 out of 14 at chance level (p = 0.39). After unblinding, we found no significant effect (p = 0.11) of an increase in the frequency range (2–7 Hz) across the subject group. Finally, we performed a Bayesian model comparison between the effect size predicted from previous clinical studies and a null model. Even though this study had a sensitivity advantage of at least one order of magnitude over previous work, we found the null model to be significantly (2000 times) more likely

Rewarding Subjective Effects of the NMDAR Antagonist Nitrous Oxide (Laughing Gas) Are Moderated by Impulsivity and Depressive Symptoms in Healthy Volunteers

BACKGROUND: Nitrous oxide (N2O) is an anaesthetic gas with both therapeutic and abuse potential. As an NMDAR antagonist, its effects are expected to resemble those of the prototypical NMDAR antagonist, ketamine. Here, we examine the subjective rewarding effects of N2O using measures previously employed in studies of ketamine. We also test for moderation of these effects by bipolar phenotype, depressive symptoms, and impulsivity. METHODS: Healthy volunteers were randomised to either 50% N2O (n=40) or medical air (n=40). Self-reported rewarding (liking and wanting), and alcohol-like effects were assessed pre-, peri- and post-inhalation. RESULTS: Effect sizes for the various rewarding/alcohol-like effects of N2O were generally similar to those reported in studies of moderate-dose ketamine. Impulsivity moderated the subjective reinforcing (liking) effects of inhaled gas, while depressive symptoms moderated motivational (wanting [more]) effects. However, depression and impulsivity had opposite directional influences, such that higher impulsivity was associated with higher N2O-liking, and higher depression, with lower N2O-wanting. CONCLUSIONS: To the extent that static (versus longitudinal) subjective rewarding effects are a reliable indicator of future problematic drug use, our findings suggests that impulsivity and depression may respectively predispose and protect against N2O abuse. Future studies should examine if these moderators are relevant for other NMDAR antagonists, including ketamine, and novel ketamine-like therapeutics and recreational drugs. Similarities between moderate-dose N2O and moderate-dose ketamine in the intensity of certain subjective effects suggest that N2O may, at least partially, substitute for ketamine as a safe and easily-implemented experimental tool for probing reward-related NMDAR function and dysfunction in humans

Discrimination of cortical laminae using MEG.

Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2mm translation and 2° rotation at SNR>11dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2014) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm, and show that it is possible to discriminate between these cortical layer models in real data

High precision anatomy for MEG.

Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1mm. Estimates of relative co-registration error were <1.5mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG

Optimising experimental design for MEG resting state functional connectivity measurement

The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of co-registration method and data recording duration. We show that the use of a foam head-cast, which is known to improve co-registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies

On-ScalpMEG

The development of new magnetic sensor technologies with relaxed thermal insulation requirements as compared to conventional magnetoencephalography (MEG) sensors has led to the birth of the field of on-scalp MEG, where sensor systems are flexibly placed directly on the scalp surface. Such improved proximity between the sensors and the brain has been theoretically demonstrated to boost signal levels and neuroimaging spatial resolution. Since the first on-scalp MEG measurements in 2012, a number of studies have experimentally verified these advantages with the two leading sensor technologies, namely, high criticaltemperature SQUIDs (high-Tc SQUIDs) and optically pumped magnetometers (OPMs). Current challenges being addressed that are specific to on-scalp MEG include relatively high sensor noise levels (specifically for high-Tc SQUIDs), limited bandwidth (specifically for OPMs), co-registration of a flexible sensor array, increased sensor crosstalk due to the denser spatial sampling required for improved spatial resolution, and engineering of a full-head system. The prospect for discovery of a neuroimaging challenge that on-scalp MEG uniquely solves is likely to push development further and possibly initiate utilization to a similar-or larger-scale as conventional MEG has reached today

Representation of probabilistic outcomes during risky decision-making

Goal-directed behaviour requires prospectively retrieving and evaluating multiple possible action outcomes. While a plethora of studies suggested sequential retrieval for deterministic choice outcomes, it remains unclear whether this is also the case when integrating multiple probabilistic outcomes of the same action. We address this question by capitalising on magnetoencephalography (MEG) in humans who made choices in a risky foraging task. We train classifiers to distinguish MEG field patterns during presentation of two probabilistic outcomes (reward, loss), and then apply these to decode such patterns during deliberation. First, decoded outcome representations have a temporal structure, suggesting alternating retrieval of the outcomes. Moreover, the probability that one or the other outcome is being represented depends on loss magnitude, but not on loss probability, and it predicts the chosen action. In summary, we demonstrate decodable outcome representations during probabilistic decision-making, which are sequentially structured, depend on task features, and predict subsequent action