Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises

Acknowledgements We would like to thank Erik Rexstad and Rob Williams for useful reviews of this manuscript. The collection of visual and acoustic data was funded by the UK Department of Energy & Climate Change, the Scottish Government, Collaborative Offshore Wind Research into the Environment (COWRIE) and Oil & Gas UK. Digital aerial surveys were funded by Moray Offshore Renewables Ltd and additional funding for analysis of the combined datasets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF. We thank colleagues at the University of Aberdeen, Moray First Marine, NERI, Hi-Def Aerial Surveying Ltd and Ravenair for essential support in the field, particularly Tim Barton, Bill Ruck, Rasmus Nielson and Dave Rutter. Thanks also to Andy Webb, David Borchers, Len Thomas, Kelly McLeod, David L. Miller, Dinara Sadykova and Thomas Cornulier for advice on survey design and statistical approache. Data Accessibility Data are available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.cf04gPeer reviewedPublisher PD

Two spatially distinct posterior alpha sources fulfill different functional roles in attention

Directing attention helps extracting relevant information and suppressing distracters. Alpha brain oscillations (8-12Hz) are crucial for this process, with power decreases facilitating processing of important information and power increases inhibiting brain regions processing irrelevant information. Evidence for this phenomenon arises from visual attention studies (Worden et al., 2000b), however, the effect also exists in other modalities, including the somatosensory system (Haegens et al., 2011) and inter-sensory attention tasks (Foxe and Snyder, 2011). We investigated in human participants (10 females, 10 males) the role of alpha oscillations in focused (0/100%) vs. divided (40/60%) attention, both across modalities (visual/somatosensory; Experiment 1) and within the same modality (visual domain: across hemifields; Experiment 2) while recording EEG over 128 scalp electrodes. In Experiment 1 participants divided their attention between visual and somatosensory modality to determine the temporal/spatial frequency of a target stimulus (vibrotactile stimulus/Gabor grating). In Experiment 2, participants divided attention between two visual hemifields to identify the orientation of a Gabor grating. In both experiments, pre-stimulus alpha power in visual areas decreased linearly with increasing attention to visual stimuli. In contrast, pre-stimulus alpha power in parietal areas was lower when attention was divided between modalities/hemifields, compared to focused attention. These results suggest there are two alpha sources, where one reflects the ‘visual spotlight of attention’ and the other reflects attentional effort. To our knowledge, this is the first study to show that attention recruits two spatially distinct alpha sources in occipital and parietal brain regions, acting simultaneously but serving different functions in attention

Developing core outcomes sets: Methods for identifying and including patient-reported outcomes (PROs)

Background: Synthesis of patient-reported outcome (PRO) data is hindered by the range of available PRO measures (PROMs) composed of multiple scales and single items with differing terminology and content. The use of core outcome sets, an agreed minimum set of outcomes to be measured and reported in all trials of a specific condition, may improve this issue but methods to select core PRO domains from the many available PROMs are lacking. This study examines existing PROMs and describes methods to identify health domains to inform the development of a core outcome set, illustrated with an example.Methods: Systematic literature searches identified validated PROMs from studies evaluating radical treatment for oesophageal cancer. PROM scale/single item names were recorded verbatim and the frequency of similar names/scales documented. PROM contents (scale components/single items) were examined for conceptual meaning by an expert clinician and methodologist and categorised into health domains. A patient advocate independently checked this categorisation.Results: Searches identified 21 generic and disease-specific PROMs containing 116 scales and 32 single items with 94 different verbatim names. Identical names for scales were repeatedly used (for example, 'physical function' in six different measures) and others were similar (overlapping face validity) although component items were not always comparable. Based on methodological, clinical and patient expertise, 606 individual items were categorised into 32 health domains.Conclusion: This study outlines a methodology for identifying candidate PRO domains from existing PROMs to inform a core outcome set to use in clinical trials

Evidence that the negative BOLD response is neuronal in origin: a simultaneous EEG–BOLD–CBF study in humans

Unambiguous interpretation of changes in the BOLD signal is challenging because of the complex neurovascular coupling that translates changes in neuronal activity into the subsequent haemodynamic response. In particular, the neurophysiological origin of the negative BOLD response (NBR) remains incompletely understood. Here, we simultaneously recorded BOLD, EEG and cerebral blood flow (CBF) responses to 10 s blocks of unilateral median nerve stimulation (MNS) in order to interrogate the NBR. Both negative BOLD and negative CBF responses to MNS were observed in the same region of the ipsilateral primary sensorimotor cortex (S1/M1) and calculations showed that MNS induced a decrease in the cerebral metabolic rate of oxygen consumption (CMRO2) in this NBR region. The ∆CMRO2/∆CBF coupling ratio (n) was found to be significantly larger in this ipsilateral S1/M1 region (n = 0.91 ± 0.04, M = 10.45%) than in the contralateral S1/M1 (n = 0.65 ± 0.03, M = 10.45%) region that exhibited a positive BOLD response (PBR) and positive CBF response, and a consequent increase in CMRO2 during MNS. The fMRI response amplitude in ipsilateral S1/M1 was negatively correlated with both the power of the 8–13 Hz EEG mu oscillation and somatosensory evoked potential amplitude. Blocks in which the largest magnitude of negative BOLD and CBF responses occurred therefore showed greatest mu power, an electrophysiological index of cortical inhibition, and largest somatosensory evoked potentials. Taken together, our results suggest that a neuronal mechanism underlies the NBR, but that the NBR may originate from a different neurovascular coupling mechanism to the PBR, suggesting that caution should be taken in assuming the NBR simply represents the neurophysiological inverse of the PBR

Post-stimulus fMRI and EEG responses: evidence for a neuronal origin hypothesised to be inhibitory

Post-stimulus undershoots, negative responses following cessation of stimulation, are widely observed in functional magnetic resonance (fMRI) blood oxygenation level dependent (BOLD) data. However, the debate surrounding whether the origin of this response phase is neuronal or vascular, and whether it provides functionally relevant information, that is additional to what is contained in primary response, means that undershoots are widely overlooked. We simultaneously recorded electroencephalography (EEG), BOLD and cerebral blood-flow (CBF) [obtained from arterial spin labelled (ASL) fMRI] fMRI responses to hemifield checkerboard stimulation to test the potential neural origin of the fMRI post-stimulus undershoot. The post-stimulus BOLD and CBF signal amplitudes in both contralateral and ipsilateral visual cortex depended on the post-stimulus power of the 8-13 Hz (alpha) EEG neuronal activity, such that trials with highest EEG power showed largest fMRI undershoots in contralateral visual cortex. This correlation in post-stimulus EEG-fMRI responses was not predicted by the primary response amplitude. In the contralateral visual cortex we observed a decrease in both cerebral rate of oxygen metabolism (CMRO2) and CBF during the post-stimulus phase. In addition, the coupling ratio (n) between CMRO2 and CBF was significantly lower during the positive contralateral primary response phase compared with the post-stimulus phase and we propose that this reflects an altered balance of excitatory and inhibitory neuronal activity. Together our data provide strong evidence that the post-stimulus phase of the BOLD response has a neural origin which reflects, at least partially, an uncoupling of the neuronal responses driving the primary and post-stimulus responses, explaining the uncoupling of the signals measured in the two response phases. We suggest our results are consistent with inhibitory processes driving the post-stimulus EEG and fMRI responses. We therefore propose that new methods are required to model the post-stimulus and primary responses independently, enabling separate investigation of response phases in cognitive function and neurological disease

Global signal modulation of single-trial fMRI response variability: effect on positive vs negative BOLD response relationship

In functional magnetic resonance imaging (fMRI), the relationship between positive BOLD responses (PBRs) and negative BOLD responses (NBRs) to stimulation is potentially informative about the balance of excitatory and inhibitory brain responses in sensory cortex. In this study, we performed three separate experiments delivering visual, motor or somatosensory stimulation unilaterally, to one side of the sensory field, to induce PBR and NBR in opposite brain hemispheres. We then assessed the relationship between the evoked amplitudes of contralateral PBR and ipsilateral NBR at the level of both single-trial and average responses. We measure single-trial PBR and NBR peak amplitudes from individual time-courses, and show that they were positively correlated in all experiments. In contrast, in the average response across trials the absolute magnitudes of both PBR and NBR increased with increasing stimulus intensity, resulting in a negative correlation between mean response amplitudes. Subsequent analysis showed that the amplitude of single-trial PBR was positively correlated with the BOLD response across all grey-matter voxels and was not specifically related to the ipsilateral sensory cortical response. We demonstrate that the global component of this single-trial response modulation could be fully explained by voxel-wise vascular reactivity, the BOLD signal standard deviation measured in a separate resting-state scan (resting state fluctuation amplitude, RSFA). However, bilateral positive correlation between PBR and NBR regions remained. We further report that modulations in the global brain fMRI signal cannot fully account for this positive PBR-NBR coupling and conclude that the local sensory network response reflects a combination of superimposed vascular and neuronal signals. More detailed quantification of physiological and noise contributions to the BOLD signal is required to fully understand the trial-by-trial PBR and NBR relationship compared with that of average responses