Extraction of visual motion information for the control of eye and head movement during head-free pursuit

We investigated how effectively briefly presented visual motion could be assimilated and used to track future target motion with head and eyes during target disappearance. Without vision, continuation of eye and head movement is controlled by internal (extra-retinal) mechanisms, but head movement stimulates compensatory vestibulo-ocular reflex (VOR) responses that must be countermanded for gaze to remain in the direction of target motion. We used target exposures of 50–200 ms at the start of randomised step-ramp stimuli, followed by >400 ms of target disappearance, to investigate the ability to sample target velocity and subsequently generate internally controlled responses. Subjects could appropriately grade gaze velocity to different target velocities without visual feedback, but responses were fully developed only when exposure was >100 ms. Gaze velocities were sustained or even increased during target disappearance, especially when there was expectation of target reappearance, but they were always less than for controls, where the target was continuously visible. Gaze velocity remained in the direction of target motion throughout target extinction, implying that compensatory (VOR) responses were suppressed by internal drive mechanisms. Regression analysis revealed that the underlying compensatory response remained active, but with gain slightly less than unity (0.85), resulting in head-free gaze responses that were very similar to, but slightly greater than, head-fixed. The sampled velocity information was also used to grade head velocity, but in contrast to gaze, head velocity was similar whether the target was briefly or continuously presented, suggesting that head motion was controlled by internal mechanisms alone, without direct influence of visual feedback

Vibrational Strong Coupling with Surface Plasmons and the Presence of Surface Plasmon Stop Bands (article)

This is the final version. Available on open access from American Chemical Society via the DOI in this recordThe datasets associated with this article are available in ORE at https://doi.org/10.24378/exe.1604We demonstrate strong coupling between surface plasmon resonances and molecular vibrational resonances of poly(methyl methacrylate) (PMMA) molecules in the mid-infrared range through the use of grating coupling, complimenting earlier work using microcavities and localized plasmon resonances. We choose the period of the grating so that we may observe strong coupling between the surface plasmon mode associated with a patterned gold film and the C=O vibrational resonance in an overlying polymer film. We present results from experiments and numerical simulations to show that surface plasmon modes provide convenient open cavities for vibrational strong coupling experiments. In addition to providing momentum matching between surface plasmon modes and incident light, gratings may also produce a modification of the surface plasmon properties, notably their dispersion. We further show that for the parameters used in our experiment surface plasmon stop bands are formed, and we find that both stop-band edges undergo strong coupling.Engineering and Physical Sciences Research Council (EPSRC)European Research Council (ERC

Magnetoencephalographic Correlates of Perceptual State During Auditory Bistability

Bistability occurs when two alternative percepts can be derived from the same physical stimulus. To identify the neural correlates of specifc subjective experiences we used a bistable auditory stimulus and determined whether the two perceptual states could be distinguished electrophysiologically. Fourteen participants underwent magnetoencephalography while reporting their perceptual experience while listening to a continuous bistable stream of auditory tones. Participants reported bistability with a similar overall proportion of the two alternative percepts (52% vs 48%). At the individual level, sensor space electrophysiological discrimination between the percepts was possible in 9/14 participants with canonical variate analysis (CVA) or linear support vector machine (SVM) analysis over space and time dimensions. Classifcation was possible in 14/14 subjects with non-linear SVM. Similar efects were noted in an unconstrained source space CVA analysis (classifying 10/14 participants), linear SVM (classifying 9/14 subjects) and non-linear SVM (classifying 13/14 participants). Source space analysis restricted to a priori ROIs showed discrimination was possible in the right and left auditory cortex with each classifcation approach but in the right intraparietal sulcus this was only apparent with non-linear SVM and only in a minority of particpants. Magnetoencephalography can be used to objectively classify auditory experiences from individual subjects

Estimation of total intracranial volume - a comparison of methods

Total intracranial volume is a useful measure of inter-subject variability in pre-morbid brain volume, which has been recommended for inclusion in region of interest and voxel-based morphometric studies of dementia [1]. TIV can be estimated from structural MRI using time-consuming manual tracing or using automated methods. We show that recent improvements to the Statistical Parametric Mapping (SPM) software's unified segmentation method allow highly accurate and unbiased estimates to be obtained rapidly and without interaction

Between Thought and Expression, a Magnetoencephalography Study of the "Tip-of-the-Tongue" Phenomenon

“Tip-of-the-tongue” (TOT) is the phenomenon associated with the inaccessibility of a known word from memory. It is universally experienced, increases in frequency with age, and is most common for proper nouns. It is a good model for the symptom of anomia experienced much more frequently by some aphasic patients following brain injury. Here, we induced the TOT state in older participants while they underwent brain scanning with magnetoencephalography to investigate the changes in oscillatory brain activity associated with failed retrieval of known words. Using confrontation naming of pictures of celebrities, we successfully induced the TOT state in 29% of trials and contrasted it with two other states: “Know” where the participants both correctly recognized the celebrity's face and retrieved their name and “Don't Know” when the participants did not recognize the celebrity. We wished to test Levelt's influential model of speech output by carrying out two analyses, one epoching the data to the point in time when the picture was displayed and the other looking back in time from when the participants first articulated their responses. Our main findings supported the components of Levelt's model, but not their serial activation over time as both semantic and motor areas were identified in both analyses. We also found enduring decreases in the alpha frequency band in the left ventral temporal region during the TOT state, suggesting ongoing semantic search. Finally, we identified reduced beta power in classical peri-sylvian language areas for the TOT condition, suggesting that brain regions that encode linguistic memories are also involved in their attempted retrieval

Watching movies unfold - a frame-by-frame analysis of the associated neural dynamics

Our lives unfold as sequences of events. We experience these events as seamless, although they are composed of individual images captured in between the interruptions imposed by eye blinks and saccades. Events typically involve visual imagery from the real world (scenes), and the hippocampus is frequently engaged in this context. It is unclear, however, whether the hippocampus would be similarly responsive to unfolding events that involve abstract imagery. Addressing this issue could provide insights into the nature of its contribution to event processing, with relevance for theories of hippocampal function. Consequently, during magnetoencephalography (MEG), we had female and male humans watch highly matched unfolding movie events composed of either scene image frames that reflected the real world, or frames depicting abstract patterns. We examined the evoked neuronal responses to each image frame along the time course of the movie events. Only one difference between the two conditions was evident, and that was during the viewing of the first image frame of events, detectable across frontotemporal sensors. Further probing of this difference using source reconstruction revealed greater engagement of a set of brain regions across parietal, frontal, premotor, and cerebellar cortices, with the largest change in broadband (1–30 Hz) power in the hippocampus during scene-based movie events. Hippocampal engagement during the first image frame of scene-based events could reflect its role in registering a recognizable context perhaps based on templates or schemas. The hippocampus, therefore, may help to set the scene for events very early on

Laminar dynamics of high amplitude beta bursts in human motor cortex

Motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient, high amplitude, bursting events rather than slowly modulating oscillations. The timing of these bursting events is tightly linked to behavior, suggesting a more dynamic functional role for beta activity than previously believed. However, the neural mechanisms underlying beta bursts in sensorimotor circuits are poorly understood. To address this, we here leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings. This provides important constraints to theories about the functional role of burst activity for movement control in health and disease, and crucial links between macro-scale phenomena measured in humans and micro-circuit activity recorded from animal models

Testing covariance models for MEG source reconstruction of hippocampal activity

Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral

Synchronization of medial temporal lobe and prefrontal rhythms in human decision-making

Optimal decision making requires that we integrate mnemonic information regarding previous decisions with value signals that entail likely rewards and punishments. The fact that memory and value signals appear to be coded by segregated brain regions, the hippocampus in the case of memory and sectors of prefrontal cortex in the case of value, raises the question as to how they are integrated during human decision making. Using magnetoencephalography to study healthy human participants, we show increased theta oscillations over frontal and temporal sensors during nonspatial decisions based on memories from previous trials. Using source reconstruction we found that the medial temporal lobe (MTL), in a location compatible with the anterior hippocampus, and the anterior cingulate cortex in the medial wall of the frontal lobe are the source of this increased theta power. Moreover, we observed a correlation between theta power in the MTL source and behavioral performance in decision making, supporting a role for MTL theta oscillations in decision-making performance. These MTL theta oscillations were synchronized with several prefrontal sources, including lateral superior frontal gyrus, dorsal anterior cingulate gyrus, and medial frontopolar cortex. There was no relationship between the strength of synchronization and the expected value of choices. Our results indicate a mnemonic guidance of human decision making, beyond anticipation of expected reward, is supported by hippocampal–prefrontal theta synchronization

Peak-Clustering Method for MEG Group Analysis to Minimise Artefacts Due to Smoothness

Magnetoencephalography (MEG), a non-invasive technique for characterizing brain electrical activity, is gaining popularity as a tool for assessing group-level differences between experimental conditions. One method for assessing task-condition effects involves beamforming, where a weighted sum of field measurements is used to tune activity on a voxel-by-voxel basis. However, this method has been shown to produce inhomogeneous smoothness differences as a function of signal-to-noise across a volumetric image, which can then produce false positives at the group level. Here we describe a novel method for group-level analysis with MEG beamformer images that utilizes the peak locations within each participant’s volumetric image to assess group-level effects. We compared our peak-clustering algorithm with SnPM using simulated data. We found that our method was immune to artefactual group effects that can arise as a result of inhomogeneous smoothness differences across a volumetric image. We also used our peak-clustering algorithm on experimental data and found that regions were identified that corresponded with task-related regions identified in the literature. These findings suggest that our technique is a robust method for group-level analysis with MEG beamformer images