Pailthorpe, B. A. | Search bioRxiv

bioRxiv2025

Neural Mass Model of Auditory Stimulus Responses in Marmoset Cortex.

A composite, heterogeneous neural mass model of the marmoset auditory and pre-frontal cortex (pFC) is used to model negativity mismatch experiments. This builds upon previous analysis of a compact pFC cluster. Simulated average deviant response delays were 132 ms for Auditory areas, and 147 ms for pFC areas, comparable to the 100-250 ms experimentally measured range. Details of responses for each anatomical area are presented. Area TPO is a key output node from the auditory cluster with strong links to pFC. Area AuA1 is activated by the deviant, high frequency, stimulus then turns off after the standard stimuli cease. A NMM response and delay is observed in the pFC sub cluster. Inactivation of AuRPB causes ambiguous spikes in AuA1 and reduced responses, consistent with experimental observations. The simulations facilitate analysis of the driving forces arriving at AuA1 and suggest that feedback from AuRPB to AuA1 is carried over multiple local network pathways. The simulations reproduce the experimentally observed delays and dissect the roles of participating areas and pathways.

neuroscience↗

bioRxiv2024

Network analysis of Marmoset cortical connections reveals pFC and sensory clusters

A new analysis is presented of the retrograde tracer measurements of connections between anatomical areas of the marmoset cortex. The original normalisation of raw data yields the fractional link weight measure, FLNe. That is re-examined to consider other possible measures that reveal the underlying in link weights. Predictions arising from both are used to examine network modules and hubs. With inclusion of the in weights the Infomap algorithm identifies eight structural modules in marmoset cortex. In and out hubs and major connector nodes are identified using module assignment and participation coefficients. Time evolving network tracing around the major hubs reveals medium sized clusters in pFC, temporal, auditory and visual areas; the most tightly coupled and significant of which is in the pFC. A complementary viewpoint is provided by examining the highest traffic links in the cortical network, and reveals parallel sensory flows to pFC and via association areas to frontal areas.

neuroscience↗

bioRxiv2019

Network analysis of mesoscale mouse brain structural connectome reveals modular structure that aligns with anatomical regions and sensory pathways

The Allen mesoscale mouse brain structural connectome is analysed using standard network methods combined with 3D visualizations. The full region-to-region connectivity data is used, with a focus on the strongest structural links. The spatial embedding of links and time evolution of signalling is incorporated, with two-step links included. Modular decomposition using the Infomap method produces 8 network modules that correspond approximately to major brain anatomical regions and system functions. These modules align with the anterior and posterior primary sensory systems and association areas. 3D visualization of network links is facilitated by using a set of simplified schematic coordinates that reduces visual complexity. Selection of key nodes and links, such as sensory pathways and cortical association areas together reveal structural features of the mouse structural connectome consistent with biological functions in the sensory-motor systems, and selective roles of the anterior and posterior cortical association areas of the mouse brain. Time progression of signals along sensory pathways reveals that close links are to local cortical association areas and cross modal, while longer links provide anterior-posterior coordination and inputs to non cortical regions. The fabric of weaker links generally are longer range with some having brain-wide reach. Cortical gradients are evident along sensory pathways within the structural network.\n\nAuthors SummaryNetwork models incorporating spatial embedding and signalling delays are used to investigate the mouse structural connectome. Network models that include time respecting paths are used to trace signaling pathways and reveal separate roles of shorter vs. longer links. Here computational methods work like experimental probes to uncover biologically relevant features. I use the Infomap method, which follows random walks on the network, to decompose the directed, weighted network into 8 modules that align with classical brain anatomical regions and system functions. Primary sensory pathways and cortical association areas are separated into individual modules. Strong, short range links form the sensory-motor paths while weaker links spread brain-wide, possibly coordinating many regions.

neuroscience↗