Neurons, networks, and behaviour: Investigating multiscale interactions between brain regions and their behavioural correlates

Abstract

Understanding the interactions between different brain regions is vital for unravelling the complexities of brain disorders and brain functions such as cognition, behaviour, and memory. While previous investigations of inter-regional communication were primarily performed via neuroimaging and electroencephalography, these are of limited spatial and temporal resolution. Recent technological advances and improved recording techniques have opened new avenues in cross-region intracranial recordings, allowing us to explore the interactions between brain regions at a finer scale than ever before.

This thesis addresses the analysis of inter-regional interactions using a variety of data types obtained from simultaneous recordings of brain activity. To facilitate this analysis, we introduce Simuran, a software tool that enables the analysis of different data formats and promotes interoperability between neural data and analysis tools.

Using Simuran, we investigate the impact of anterior thalamic lesion or inactivation in rats on the hippocampus, subiculum, and retrosplenial cortex. Our results reveal that anterior thalamic lesions disrupt spatial cell coding in the subiculum while leaving CA1 spatial cell coding intact. Interestingly, at the local field potential level, the effect of these lesions is not clear in the subiculum alone; rather, differences emerge when comparing local field potentials across brain regions and examining the relationship between local field potentials and spiking activity.

Next, we explore interactions at the neuron-level and consider the likelihood of recording structurally connected neurons across regions using simulations and statistics. Our findings indicate that modern recording techniques offer a high probability of capturing synaptically connected neurons across well-connected brain areas. Leveraging this connection probability, we turn to analysing large-scale datasets. The results suggest that task performance involves a balance between consistency in the represented information via highly correlated neural activity, while avoiding excessive redundancy. Additionally, patterns in neural ensembles exhibit similarities during both correct and incorrect task performances.

This research builds upon solid foundations to consider cross-region interactions in the brain, shedding light on observed behaviours and highlighting exciting opportunities to leverage modern technology and analytics.