Spatial attention modulates visual gamma oscillations across the human ventral stream

Oscillatory synchronization in the gamma frequency range has been proposed as a neuronal mechanism to prioritize processing of relevant stimuli over competing ones. Recent studies in animals found that selective spatial attention enhanced gamma-band synchronization in high-order visual areas (V4) and increased the gamma peak frequency in V1. The existence of such mechanisms in the human visual system is yet to be fully demonstrated. In this study, we used MEG, in combination with an optimised stimulus design, to record visual gamma oscillations from human early visual cortex, while participants performed a visuospatial attention cueing task. First, we reconstructed virtual sensors in V1/V2, where gamma oscillations were strongly induced by visual stimulation alone. Second, following the results of a statistical comparison between conditions of attention, we reconstructed cortical activity also in inferior occipital-temporal regions (V4). The results indicated that gamma amplitude was modulated by spatial attention across the cortical hierarchy, both in the early visual cortex and in higher-order regions of the ventral visual pathway. In contrast, we found no evidence for an increase in the gamma peak frequency in V1/V2 with attention. The gamma response tended to peak earlier in V1/V2 than in V4 by approximately 70 ms, consistent with a feed-forward role of gamma-band activity in propagating sensory representations across the visual cortical hierarchy. Together, these findings suggest that differences in experimental design or methodology can account for the inconsistencies in previous animal and human studies. Furthermore, our results are in line with the hypothesis of enhanced gamma-band synchronization as an attentional mechanism in the human visual cortex

Phase‐amplitude coupling profiles differ in frontal and auditory cortices of bats

Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1–4 Hz), theta (4–8 Hz) or gamma (>30 Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase‐amplitude coupling (PAC) is one such plausible and well‐described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal‐auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local‐field potentials (LFPs), we show that the amplitude of gamma‐band activity couples with the phase of low‐frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high‐gamma frequencies (1‐4/75‐100 Hz), whereas in the AC the coupling is strongest in the delta‐theta/low‐gamma (2‐8/25‐55 Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal‐auditory cortex network

Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.

Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer's forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer's self-motion.R01 NS104585 - NINDS NIH HHS; U01 EB023820 - NIBIB NIH HHSPublished versio

Spatial attention modulates visual gamma oscillations across the human ventral stream

Oscillatory synchronization in the gamma frequency range has been proposed as a neuronal mechanism to prioritize processing of relevant stimuli over competing ones. Recent studies in animals found that selective spatial attention enhanced gamma-band synchronization in high-order visual areas (V4) and increased the gamma peak frequency in V1. The existence of such mechanisms in the human visual system is yet to be fully demonstrated. In this study, we used MEG, in combination with an optimised stimulus design, to record visual gamma oscillations from human early visual cortex, while participants performed a visuospatial attention cueing task. First, we reconstructed virtual sensors in V1/V2, where gamma oscillations were strongly induced by visual stimulation alone. Second, following the results of a statistical comparison between conditions of attention, we reconstructed cortical activity also in inferior occipital-temporal regions (V4). The results indicated that gamma amplitude was modulated by spatial attention across the cortical hierarchy, both in the early visual cortex and in higher-order regions of the ventral visual pathway. In contrast, we found no evidence for an increase in the gamma peak frequency in V1/V2 with attention. The gamma response tended to peak earlier in V1/V2 than in V4 by approximately 70 ms, consistent with a feed-forward role of gamma-band activity in propagating sensory representations across the visual cortical hierarchy. Together, these findings suggest that differences in experimental design or methodology can account for the inconsistencies in previous animal and human studies. Furthermore, our results are in line with the hypothesis of enhanced gamma-band synchronization as an attentional mechanism in the human visual cortex

An exploration into the link between brain rhythms and synaptic plasticity in health and infectious disease

During wakefulness, synapses are strengthened to enable memory formation. Whereas, during sleep, weaker connections are ‘pruned’ to help consolidate memories. These synaptic alterations are related to cortical oscillations, which are generally faster during wakefulness (30-80Hz, gamma), and slower during deep sleep (1-4Hz, delta). Synaptic strength is thought to decrease during delta rhythms (compared to gamma rhythms). Neuroinflammation can disturb these brain rhythms and lead to a decline in cognitive function, which may result from aberrations in synaptic plasticity. To test the laminar and cellular changes in synaptic plasticity during sleep- and wake-related oscillations, in vitro electrophysiology and immunofluorescence were employed using acute rat neocortical slices. To examine the effect of neuroinflammation on these brain states, systemic infection was induced using synthetic analogues of pathogenic bacterial and viral material, and a biological parasitic disease model. The expression of an immediate early gene (IEG) marker of neuronal plasticity (Arc) was higher during delta oscillations compared to gamma oscillations and was concentrated to mid-apical dendrite bundles from layer V intrinsically bursting cells. These bundles represented cortical microcolumns which are known to exhibit synchronous activity, allowing parallel processing of information. Increased Arc expression in these columns during delta oscillations may promote synaptic rescaling and highlights the role of cortical microcolumns in memory consolidation. A balance of pro- and anti-inflammatory cytokines was found after short term systemic infection which gave way to a predominately pro-inflammatory state when the infection was longer term. The oscillatory activity also changed, with a continued decline in gamma power. However, delta power increased short term but decreased with a longer infection. The systemic infection had no effect on cortical plasticity. These results were corroborated in a mouse model of Leishmaniasis and show that systemic infection alters neuronal communication by changes to oscillatory activity, but does not change synaptic plasticity levels

Quality control of visual gamma oscillation frequency in studies of pharmacology, cognitive neuroscience and large-scale multi-site collaborations

In visual cortex, high-contrast grating stimuli induce neurons to oscillate synchronously with a centre frequency in the gamma range (~30–80 Hz). The peak frequency of visual gamma oscillations is modulated by numerous factors, including stimulus properties, cortical architecture and genetics, however, it can be measured reliably over time. As demonstrated by both animal models and human pharmacological studies, the gamma peak frequency is determined by the excitation/inhibition balance and the time constants of GABAergic processes. This oscillatory parameter could thus reflect inter-individual differences in cortical function/physiology, representing a possible biomarker for pharmacological treatment in conditions such as epilepsy, autism and schizophrenia. This thesis demonstrates the importance of measuring the gamma peak frequency accurately and reliably in magnetoencephalographic (MEG) recordings. In Chapter 2, a novel quality-control (QC) approach was validated for peak frequency estimation and identification of poor-quality data. In Chapter 3, QC of a previous pharmacological MEG study of visual gamma with tiagabine revealed a marked drug-induced reduction of peak frequency. Although contrasting with the null finding originally reported (Muthukumaraswamy et al., 2013), the result is supported by both animal models and recent human studies, demonstrating the potentialities of appropriate QC routines. In Chapter 4, testing for the effect of spatial attention on the gamma peak frequency in primary visual cortex resulted in no evidence of a change. However, the modulation of gamma amplitude by attention was consistent with a role in feed-forward signal propagation across the visual hierarchy. In Chapter 5, the QC approach was used to compare visual gamma data recorded at different sites of the UK MEG Partnership, demonstrating the feasibility of combining data from different MEG systems. These results have implications particularly for pharmacological and large-scale multi-site studies, both of which are emerging as promising approaches for the study of brain function with MEG

A study of behavioural, cognitive and neural markers underlying visuospatial learning

Visuospatial (VS) learning is an education format noted for encouraging an individual to use visual exploration and their innate spatial ability in constructing a flexible ‘internal mental representation’ of three-dimensional information. Being a discipline reliant upon this informed consideration, VS methods have found particular application in anatomy education – with tangential evidence linking the inclusion of these methods to greater student understanding of anatomical concepts. Building on these findings, this thesis investigates: (i) the extent of individual and group learning benefits that accompany VS instruction within anatomy education, and (ii) a novel exploration of the cognitive and neuroscientific mechanisms that govern their success. To chart the success of instructional methodology in our reporting, we selected an array of academic performance and accompanying engagement indices. These items had been expressed by numerous modestly-powered prior studies, encompassing a diversity of anatomy cohorts, to be heightened under VS learning. Our initial work in Chapter 2 was therefore to determine if these effects were preserved when VS instruction was introduced within a substantially larger undergraduate anatomy cohort. Findings substantiated the wider applicability of this teaching method, with academic scores in each of the examined categories (didactic, spatial, and extrapolation) being superior to standard course delivery. Conflictingly, lower engagement and desire for VS inclusion was noted in the group receiving this instruction – leading us to attribute this to prevailing misconceptions about the nature of VS learning. In order to determine whether benefits found to characterise VS teaching in anatomy were universally applicable, or attributable to a myriad of demographic and cognitive factors, Chapter 3 explored variation in individual spatial capacity. Interestingly, the prevailing advantage of raw spatial aptitude in males was not associated with improved practical performance. This subsequently allowed a component of underlying psychological reasoning, namely visualisation (Vz) ability, to be highlighted as the clearest indicator of one’s ability to transfer raw spatial intelligence into practical VS understanding. Accompanying the misconceptions of VS learning reported in Chapter 2, participants were found to be poor estimators of their VS ability. Having established that spatial reasoning in anatomy possesses a physiological basis, we conducted a novel exploration of the neuroscientific mechanism evoked in VS learning using electroencephalography (EEG) technology (Chapter 4). This was evaluated by monitoring the neural signals of individuals engaged in two anatomical education workshops (featuring standard or VS instruction). No significant differences in oscillatory power accounted for the influence of VS instruction within any of the assessed frequency ranges (2-45Hz). Objective task outcomes were consistent with those in Chapter 2, finding a similarly elevated ability to address spatial questions following VS instruction. When placed together, the results of Chapters 2, 3 and 4 demonstrate the explicit advantages present for VS instruction in anatomy education. Though further work is required to isolate the specific underlying neural pathways, this appears linked to passive changes in how the human brain processes and later consolidates this information. Findings have important implications for advancing medical educational strategy (Appendix Descriptive Review), and wider understanding of the mechanisms that govern learning.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 202

Using independent components analysis to identify visually driven regions and networks in the human brain, using data collected during movie watching

Traditionally, regions involved in visual processing are mapped in the brain using simple localisers and/or anatomical techniques. As a more efficient (and interesting) alternative, Bartels & Zeki (2004) suggested that independent components analysis (ICA) could be used to segment the brain into functional regions, using data collected during movie watching. The first aim of this thesis was to explore the potential of this technique for reliable identification of visually driven regions and networks. In Chapter 2 I thoroughly and systematically explore the sensitivity of tensor ICA (TICA) to common pre-processing parameters and identify an optimal analysis pipeline. Despite some sensitivity of TICA to the parameters tested, robust components in visually responsive regions could be identified across outputs. Using an optimized pipeline, in Chapter 3 I demonstrate that visually driven components (in particular, peak voxels) are consistent across different samples and movie clips, supporting the use of this technique. In Chapter 4 I show that established resting state networks can be identified in an ICA analysis using movies, and that by increasing dimensionality sub-regions of these networks can be identified. Chapter 5 shows how these reliable components represented visual regions in the motion processing pathway. Based on the success of the technique at the group level, in Chapter 6 I apply the technique to individual observer data. Results show that functional networks and visual regions of interest can be reliably identified, supporting its use in future neuroscientific research. To address the short-comings of BOLD, the second aim of this thesis was to investigate whether MEG frequency data and fMRI bold data could be combined for analysis in a novel technique using TICA. First in Chapter 7 I address some prerequisites for a combined MEG frequency analysis using the technique. On the back of these results, I use the technique to generate interesting cross-frequency components (Chapter 8) and cross modality components using combined MEG and fMRI data (Chapter 9). These results show exciting promise for potential use in future neuroscientific work. In the final chapter, I investigate the potential use of ICA and changing dimensionality for mapping the functional hierarchy of the visual system. With development this could be a useful tool for understanding connectivity between sub-regions of functional networks. These results have important implications for the identification of visually responsive regions and for understanding neural activity during natural viewing