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Barnes, G. R.

Publications and source records attributed to Barnes, G. R..

4 recordsLinked to original sources

The neural dynamics of novel scene imagery

Retrieval of long-term episodic memories is characterised by synchronised neural activity between hippocampus and ventromedial prefrontal cortex (vmPFC), with additional evidence that vmPFC activity leads that of the hippocampus. It has been proposed that the mental generation of scene imagery is a crucial component of episodic memory processing. If this is the case, then a comparable interaction between the two brain regions should exist during the construction of novel scene imagery. To address this question, we leveraged the high temporal resolution of magnetoencephalography (MEG) to investigate the construction of novel mental imagery. We tasked male and female humans with imagining scenes and single isolated objects in response to one-word cues. We performed source level power, coherence and causality analyses to characterise the underlying inter-regional interactions. Both scene and object imagination resulted in theta power changes in the anterior hippocampus. However, higher theta coherence was observed between the hippocampus and vmPFC in the scene compared to the object condition. This inter-regional theta coherence also predicted whether or not imagined scenes were subsequently remembered. Dynamic causal modelling of this interaction revealed that vmPFC drove activity in hippocampus during novel scene construction. Additionally, theta power changes in the vmPFC preceded those observed in the hippocampus. These results constitute the first evidence in humans that episodic memory retrieval and scene imagination rely on similar vmPFC-hippocampus neural dynamics. Furthermore, they provide support for theories emphasising similarities between both cognitive processes, and perspectives that propose the vmPFC guides the construction of context-relevant representations in the hippocampus. Significance statementEpisodic memory retrieval is characterised by a dialogue between hippocampus and ventromedial prefrontal cortex (vmPFC). It has been proposed that the mental generation of scene imagery is a crucial component of episodic memory processing. An ensuing prediction would be of a comparable interaction between the two brain regions during the construction of novel scene imagery. Here, we leveraged the high temporal resolution of magnetoencephalography (MEG), and combined it with a scene imagination task. We found that a hippocampal-vmPFC dialogue existed, and that it took the form of vmPFC driving the hippocampus. We conclude that episodic memory and scene imagination share fundamental neural dynamics, and the process of constructing vivid, spatially coherent, contextually appropriate scene imagery is strongly modulated by vmPFC.

neuroscience

Using optically-pumped magnetometers to measure magnetoencephalographic signals in the human cerebellum

We test the feasibility of an optically pumped magnetometer (OPM)-MEG system for the measurement of human cerebellar activity. We show that the OPM system allows for excellent coverage of this structure by decreasing the average sensor-to-cerebellum distance by around 33% (16mm), compared to a standard MEG helmet. This closer proximity to the cerebellum approximately doubles the signal-to-noise ratio (SNR). As a proof of principle, we used an air-puff stimulus to the eyeball in order to elicit cerebellar evoked and induced responses that are well characterized in non-human models. In three subjects, we observed an evoked component at 50ms post stimulus, which originates in the cerebellum (predominantly ipsilateral). This response was followed by a second component at 100ms post stimulus (predominantly contra-lateral). Sensory stimulation also elicited an event-related broadband spectral power change in the ipsilateral cerebellum at ~100ms in all subjects. We conclude that the OPM-MEG technology offers a promising way to advance the understanding of the information processing mechanisms in the human cerebellum.

neuroscience

Laminar-specific cortical dynamics in human visual and sensorimotor cortices

Lower frequency, feedback, activity in the alpha and beta range is thought to predominantly originate from infragranular cortical layers, whereas feedforward signals in the gamma range stem largely from supragranular layers. Distinct anatomical and spectral channels may therefore play specialized roles in communication within hierarchical cortical networks; however, empirical evidence for this organization in humans is limited. We leverage high precision MEG to test this proposal, directly and non-invasively, in human participants during visually guided actions. Visual alpha activity mapped onto deep cortical laminae, whereas visual gamma activity predominantly arose from superficial laminae. This laminar-specificity was echoed in sensorimotor beta and gamma activity. Visual gamma activity scaled with task demands in a way compatible with feedforward signaling. For sensorimotor activity, we observed a more complex relationship with feedback and feedforward processes. Distinct frequency channels thus operate in a laminar-specific manner, but with dissociable functional roles across sensory and motor cortices.

neuroscience

Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithms

Magnetoencephalography (MEG) is a direct measure of neuronal current flow; its anatomical resolution is therefore not constrained by physiology but rather by data quality and the models used to explain these data. Recent simulation work has shown that it is possible to distinguish between signals arising in the deep and superficial cortical laminae given accurate knowledge of these surfaces with respect to the MEG sensors. This previous work has focused around a single inversion scheme (multiple sparse priors) and a single global parametric fit metric (free energy). In this paper we use several different source inversion algorithms and both local and global, as well as parametric and non-parametric fit metrics in order to demonstrate the robustness of the discrimination between layers. We find that only algorithms with some sparsity constraint can successfully be used to make laminar discrimination. Importantly, local t-statistics, global cross-validation and free energy all provide robust and mutually corroborating metrics of fit. We show that discrimination accuracy is affected by patch size estimates, cortical surface features, and lead field strength, which suggests several possible future improvements to this technique. This study demonstrates the possibility of determining the laminar origin of MEG sensor activity, and thus directly testing theories of human cognition that involve laminar- and frequency- specific mechanisms. This possibility can now be achieved using recent developments in high precision MEG, most notably the use of subject-specific head-casts, which allow for significant increases in data quality and therefore anatomically precise MEG recordings.

neuroscience