Cortico-hippocampal wave interaction: Insights from neural mass models

2155 

Abstract Submission 

Anna Behler¹, Nikitas Koussis², Michael Breakspear³

¹University of Newcastle, Callaghan, NSW, ²University of Newcastle, New Lambton Heights, New South Wales, ³University of Newcastle, Newcastle, N/A

Anna Behler  
University of Newcastle
Callaghan, NSW

Nikitas Koussis  
University of Newcastle
New Lambton Heights, New South Wales

Michael Breakspear  
University of Newcastle
Newcastle, N/A

Dynamic interactions between subcortical structures and cortical regions are essential to the execution of cognitive functions. In particular, the relationship between the hippocampus and cortex is vital for memory encoding and retrieval (Ren et al., 2018), with both structures demonstrating oscillatory activity marked by propagation of traveling waves (Roberts et al., 2019; Zhang & Jacobs, 2015). As the understanding of wave-wave interactions underlying the integration of these two brain areas is limited, this study focuses on investigating hippocampal waves and their interactions with the cortex computationally, aiming to develop models of these interactions that yield testable predictions.

Biophysically informed non-linear neural mass models (i.e., Jansen-Rit columns) were used to simulate neural activity on a hippocampal mesh and a cortical representation. The coupled models of both brain areas were subjected to parameter sweeps and perturbation analyses to characterize global coherence, phase velocity and to identify preferred wave propagation patterns in the models. Different coupling mechanism between the hippocampus and cortex were then investigated.

A small gradient in external input is crucial for the emergence of traveling waves in the hippocampus, yielding a clear preference for wave directions following the antero-posterior spatial gradient. The nodal phase velocity can be adjusted by tuning the magnitude of the gradient of the external input, i.e. the difference between minimum and maximum of external input; yielding velocities between 0.5 and 2 m/s. Intricate wave interactions, with phase-phase relationships, arose through coupling the hippocampal to the cortex. The nature of these interactions was substantially impacted by the chosen inter-system coupling configuration, including one-to-one, sparse, or clustered coupling schemes. Furthermore, the ratio of inter-system to intra-system coupling strength plays a crucial role in shaping these interactions.

These computational analyses offer detailed mechanistic insights into how traveling waves of neural activity form in the hippocampus and how wave-wave interactions can contribute to cortico-hippocampal functioning. Notably, the hippocampal model fits the wave velocity for slow theta oscillations, aligning with detailed neurophysiological recordings (Zhang & Jacobs, 2015). In sum, the models provide hypotheses that can be directly tested using neuroimaging data from intracranial EEG, such as in epilepsy patients performing cognitive tasks, thereby contributing to a translational neuroscience approach.
By providing testable computational models, our study builds a robust framework for understanding cortico-hippocampal interactions and has significant implications for future research in cognitive neuroscience and neurodegenerative disorders associated with memory dysfunctions.

Other Methods ²

Subcortical Structures ¹

Computational Neuroscience

Cortical Columns

Modeling

Sub-Cortical

Other - Hippocampus