101 research outputs found

    Development of a high sensitivity ammonia sensor: Phase 1 feasibility study report (01/05/18 – 31/08/18)

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    Gas sensor technologies for monitoring atmospheric concentrations of ammonia gas are reviewed and summarised in this report

    Wearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography

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    One of the most severe limitations of functional neuroimaging techniques, such as magnetoencephalography (MEG), is that participants must maintain a fixed head position during data acquisition. This imposes restrictions on the characteristics of the experimental cohorts that can be scanned and the experimental questions that can be addressed. For these reasons, the use of ‘wearable’ neuroimaging, in which participants can move freely during scanning, is attractive. The most successful example of wearable neuroimaging is electroencephalography (EEG), which employs lightweight and flexible instrumentation that makes it useable in almost any experimental setting. However, EEG has major technical limitations compared to MEG, and therefore the development of wearable MEG, or hybrid MEG/EEG systems, is a compelling prospect. In this paper, we combine and compare EEG and MEG measurements, the latter made using a new generation of optically-pumped magnetometers (OPMs). We show that these new second generation commercial OPMs, can be mounted on the scalp in an ‘EEG-like’ cap, enabling the acquisition of high fidelity electrophysiological measurements. We show that these sensors can be used in conjunction with conventional EEG electrodes, offering the potential for the development of hybrid MEG/EEG systems. We compare concurrently measured signals, showing that, whilst both modalities offer high quality data in stationary subjects, OPM-MEG measurements are less sensitive to artefacts produced when subjects move. Finally, we show using simulations that OPM-MEG offers a fundamentally better spatial specificity than EEG. The demonstrated technology holds the potential to revolutionise the utility of functional brain imaging, exploiting the flexibility of wearable systems to facilitate hitherto impractical experimental paradigms

    Investigation of the neurovascular coupling in positive and negative BOLD responses in human brain at 7T

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    Decreases in stimulus-dependent blood oxygenation level dependent (BOLD) signal and their underlying neurovascular origins have recently gained considerable interest. In this study a multi-echo, BOLD-corrected vascular space occupancy (VASO) functional magnetic resonance imaging (fMRI) technique was used to investigate neurovascular responses during stimuli that elicit positive and negative BOLD responses in human brain at 7 T. Stimulus-induced BOLD, cerebral blood volume (CBV), and cerebral blood flow (CBF) changes were measured and analyzed in ‘arterial’ and ‘venous’ blood compartments in macro- and microvasculature. We found that the overall interplay of mean CBV, CBF and BOLD responses is similar for tasks inducing positive and negative BOLD responses. Some aspects of the neurovascular coupling however, such as the temporal response, cortical depth dependence, and the weighting between ‘arterial’ and ‘venous’ contributions, are significantly different for the different task conditions. Namely, while for excitatory tasks the BOLD response peaks at the cortical surface, and the CBV change is similar in cortex and pial vasculature, inhibitory tasks are associated with a maximum negative BOLD response in deeper layers, with CBV showing strong constriction of surface arteries and a faster return to baseline. The different interplays of CBV, CBF and BOLD during excitatory and inhibitory responses suggests different underlying hemodynamic mechanisms

    Seasonal analysis of submicron aerosol in Old Delhi using high-resolution aerosol mass spectrometry: chemical characterisation, source apportionment and new marker identification

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    We present the first real-time composition of submicron particulate matter (PM1) in Old Delhi using high-resolution aerosol mass spectrometry (HR-AMS). Old Delhi is one of the most polluted locations in the world, and PM1 concentrations reached ∼ 750 µg m−3 during the most polluted period, the post-monsoon period, where PM1 increased by 188 % over the pre-monsoon period. Sulfate contributes the largest inorganic PM1 mass fraction during the pre-monsoon (24 %) and monsoon (24 %) periods, with nitrate contributing most during the post-monsoon period (8 %). The organics dominate the mass fraction (54 %–68 %) throughout the three periods, and, using positive matrix factorisation (PMF) to perform source apportionment analysis of organic mass, two burning-related factors were found to contribute the most (35 %) to the post-monsoon increase. The first PMF factor, semi-volatility biomass burning organic aerosol (SVBBOA), shows a high correlation with Earth observation fire counts in surrounding states, which links its origin to crop residue burning. The second is a solid fuel OA (SFOA) factor with links to local open burning due to its high composition of polyaromatic hydrocarbons (PAHs) and novel AMS-measured marker species for polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Two traffic factors were resolved: one hydrocarbon-like OA (HOA) factor and another nitrogen-rich HOA (NHOA) factor. The N compounds within NHOA were mainly nitrile species which have not previously been identified within AMS measurements. Their PAH composition suggests that NHOA is linked to diesel and HOA to compressed natural gas and petrol. These factors combined make the largest relative contribution to primary PM1 mass during the pre-monsoon and monsoon periods while contributing the second highest in the post-monsoon period. A cooking OA (COA) factor shows strong links to the secondary factor, semi-volatility oxygenated OA (SVOOA). Correlations with co-located volatile organic compound (VOC) measurements and AMS-measured organic nitrogen oxides (OrgNO) suggest SVOOA is formed from aged COA. It is also found that a significant increase in chloride concentrations (522 %) from pre-monsoon to post-monsoon correlates well with SVBBOA and SFOA, suggesting that crop residue burning and open waste burning are responsible. A reduction in traffic emissions would effectively reduce concentrations across most of the year. In order to reduce the post-monsoon peak, sources such as funeral pyres, solid waste burning and crop residue burning should be considered when developing new air quality policy

    Two spatiotemporally distinct value systems shape reward-based learning in the human brain

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    Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants’ switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning

    Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

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    Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning

    Neurobiological substrates of cognitive rigidity and autonomic inflexibility in generalized anxiety disorder

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    Generalized anxiety disorder (GAD) is characterized by difficulties in inhibiting both perseverative thoughts (worry and rumination) and autonomic arousal. We investigated the neurobiological substrates of such abnormal inhibitory processes, hypothesizing aberrant functional coupling within ‘default mode’ (DMN) and autonomic brain networks. Functional imaging and heart rate variability (HRV) data were acquired from GAD patients and controls during performance of three tracking tasks interspersed with a perseverative cognition (PC) induction. After detection of infrequent target stimuli, activity within putative DMN hubs was suppressed, consistent with a redirection of attentional resources from internal to external focus. This magnitude of activity change was attenuated in patients and individuals with higher trait PC, but was predicted by individual differences in HRV. Following the induction of PC in controls, this pattern of neural reactivity became closer to that of GAD patients. Results support, at a neural level, the association between cognitive inflexibility and autonomic rigidity
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