bioRxiv Science⌕ Search

Biology subjects

Conlan, E. C.

Publications and source records attributed to Conlan, E. C..

2 recordsLinked to original sources

Assessing the Relative Impact of Grasp and Object on Inferior Frontal Gyrus Activity during a Grasping Task

The lateral grasp network, responsible for translating visual properties of an object to execution of a motor act, is comprised of the anterior intraparietal area (AIP), area F5, and the primary motor cortex (M1). Non-human primate studies of F5 have shown that it encodes a wide range of hand positions and object properties. Human studies in F5s human homologue, the inferior frontal gyrus (IFG), have leveraged this areas ability to encode grasp-object pairs for the purposes of Brain Machine Interface (BMI) control. However, whether modulation is driven by grasp, object, or the interaction between grasp and object is unclear. In the present study, sixty-four features were recorded from IFG during a motor visualization task where grasp and object were varied. Grasp was found to be the predominant factor driving modulation of IFG signals. Object was found to only be weakly represented in neural data. However, object contribution peaked earlier than grasp contribution, indicating early integration of object information. Grasp-object interactions were also found to have a significant impact. Cortical separation between grasping conditions varied based on the object presented. In addition, subspace analysis showed that the underlying neural population structure associated with each object type was significantly different from one another. Despite the impact of object type, the present study suggests that due to the significantly larger impact of grasp, BMI decoders can be used to decode grasp with above chance accuracy across a variety of grasp-object pairs.

bioengineering↗

Neural Mechanisms of Mixed Speech and Grasp Representation in Sensorimotor Cortices

Recent brain-machine interface (BMI) studies have challenged traditional views of functional specialization in human motor cortices, suggesting that regions associated with hand control also support speech. The extent of this dual functionality as well as the neural mechanisms underlying it are unclear. We address this by analyzing intracortical neural activity from seven brain regions (spanning motor, premotor, somatosensory and parietal regions) across two human participants with tetraplegia. Across all regions, grasp decoding was robust. In addition, we achieved reliable discrete-word decoding during silent reading as well as vocalized speech. Both tasks largely recruited overlapping neural populations within each region, yet these populations reconfigured their functional connectivity between tasks. Additionally, subspace analyses revealed segregated computations for speech and grasping despite mixed selectivity at the single channel level. Our findings support multi-functional BMIs capable of decoding speech and grasping from the same implant and highlight ventral premotor area 6r as a novel target.

neuroscience↗