Rajeswaran, P. | Search bioRxiv

bioRxiv2024

Mapping eye, arm, and reward information in frontal motor cortices using electrocorticography in non-human primates

Goal-directed reaches give rise to dynamic neural activity across the brain as we move our eyes and arms, and process outcomes. High spatiotemporal resolution mapping of multiple cortical areas will improve our understanding of how these neural computations are spatially and temporally distributed across the brain. In this study, we used micro-electrocorticography ({micro}ECoG) recordings in two male monkeys performing visually guided reaches to map information related to eye movements, arm movements, and receiving rewards over a 1.37 cm2 area of frontal motor cortices (primary motor cortex, premotor cortex, frontal eye field, and dorsolateral pre-frontal cortex). Time-frequency and decoding analyses revealed that eye and arm movement information shifts across brain regions during a reach, likely reflecting shifts from planning to execution. We then used phase-based analyses to reveal potential overlaps of eye and arm information. We found that arm movement decoding performance was impacted by task-irrelevant eye movements, consistent with the presence of intermixed eye and arm information across much of motor cortices. Phase-based analyses also identified reward-related activity primarily around the principal sulcus in the pre-frontal cortex as well as near the arcuate sulcus in the premotor cortex. Our results demonstrate {micro}ECoGs strengths for functional mapping and provide further detail on the spatial distribution of eye, arm, and reward information processing distributed across frontal cortices during reaching. These insights advance our understanding of the overlapping neural computations underlying coordinated movements and reveal opportunities to leverage these signals to enhance future brain-computer interfaces. Significance statement Picking up your coffee mug requires coordinating movements of your eyes and hand and processing the outcomes of those movements. Mapping how neural activity relates to different functions helps us understand how the brain performs these computations. Many mapping techniques have limited spatial or temporal resolution, restricting our ability to dissect computations that overlap closely in space and time. We used micro-electrocorticography recordings to map neural activity across multiple cortical areas while monkeys made goal-directed reaches. These measurements revealed high spatial and temporal resolution maps of neural activity related to eye, arm, and reward information processing. These maps reveal overlapping neural computations underlying movement and open opportunities to use eye and reward information to improve therapies to restore motor function.

neuroscience↗

bioRxiv2024

Selective inflammation of the tumor microenvironment and invigorated T cell-mediated tumor control upon induced systemic inactivation of TREX1

Therapeutic innate immune stimulation within the tumor microenvironment can potentiate endogenous antitumor T cell immunity. DNase 3-repair exonuclease 1 (TREX1) is essential for cellular DNA disposal which prevents autoimmunity ensuing from cGAS/STING activation by endogenous DNA. Optimal strategies to therapeutically leverage cGAS/STING signalling for cancer therapy are highly sought after. TREX1-deficient tumor cells elicit enhanced protective immunity in syngeneic models. Here we show that induced inactivation of the Trex1 gene in (non-malignant) host cells is well tolerated and yields improved type I IFN- and T cell-dependent control of established TREX1-competent tumors with selective immune cell infiltration of tumor, but not other tissues. Intra-tumoral T cell proliferation and numbers of effector and effector-like exhausted cells massively increased, enabling complete rejection in synergy with checkpoint inhibition. We conclude that systemic TREX1 inhibition is a promising approach to boost anti-tumor immunity, that can overcome immune evasion by cancer cell- intrinsic cGAS/STING inactivation.

immunology↗

bioRxiv2024

Assistive sensory-motor perturbations influence learned neural representations

Task errors are used to learn and refine motor skills. We investigated how task assistance influences learned neural representations using Brain-Computer Interfaces (BCIs), which map neural activity into movement via a decoder. We analyzed motor cortex activity as monkeys practiced BCI with a decoder that adapted to improve or maintain performance over days. Over time, task-relevant information became concentrated in fewer neurons, unlike with fixed decoders. At the population level, task information also became largely confined to a few neural modes that accounted for an unexpectedly small fraction of the population variance. A neural network model suggests the adaptive decoders directly contribute to forming these more compact neural representations. Our findings show that assistive decoders manipulate error information used for long-term learning computations like credit assignment, which informs our understanding of motor learning and has implications for designing real-world BCIs.

neuroscience↗