Geary, R. | bioRxiv Science

bioRxiv2026

Arginine Kinase 1 regulates energy homeostasis in Drosophila muscle development

In Drosophila, Arginine kinase 1 (Argk1) is involved in maintaining ATP homeostasis during bursts of activity in tissues with high and variable rates of energy turnover such as muscle. However, its role beyond stress conditions is less understood. Here, we show that Argk1 maintains energy homeostasis during flight muscle development and is required for animal viability and proper muscle function. The knockdown of Argk1 causes defects in both early and late stages of myogenesis. In the proliferating myoblasts associated with the wing disc, Argk1 depletion results in a reduction in cell size without changes in cell cycle progression. Single cell RNA-sequencing revealed that the overall composition of differentiating and undifferentiating myoblasts is not altered. Nonetheless, Argk1 knockdown causes broad alterations in the expression of genes involved in various metabolic pathways. This correlates with low levels in both ATP content and NAD+/NADH ratio. Later in muscle development, Argk1-depleted muscles completely lack spontaneous muscle contractions that are essential in myofibrillogenesis. Accordingly, Argk1 knockdown results in severe defects in sarcomere structure, while the mitochondrial network is highly fragmented. Furthermore, muscle growth is severely reduced. Thus, our data reveal an essential role for Argk1 in maintaining energy homeostasis throughout muscle development, which is required to meet the demand to support myofibrillogenesis, muscle growth and proper muscle function.

developmental biology↗

bioRxiv2022

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness

While some state-of-the-art artificial neural network systems in computer vision are strikingly accurate models of the corresponding primate visual processing, there are still many discrepancies between these models and the behavior of primates on object recognition tasks. Many current models suffer from extreme sensitivity to adversarial attacks and often do not align well with the image-by-image behavioral error patterns observed in humans. Previous research has provided strong evidence that primate object recognition behavior can be very accurately predicted by neural population activity in the inferior temporal (IT) cortex, a brain area in the late stages of the visual processing hierarchy. Therefore, here we directly test whether making the late stage representations of models more similar to that of macaque IT produces new models that exhibit more robust, primate-like behavior. We conducted chronic, large-scale multi-electrode recordings across the IT cortex in six non-human primates (rhesus macaques). We then use these data to fine-tune (end-to-end) the model "IT" representations such that they are more aligned with the biological IT representations, while preserving accuracy on object recognition tasks. We generate a cohort of models with a range of IT similarity scores validated on held-out animals across two image sets with distinct statistics. Across a battery of optimization conditions, we observed a strong correlation between the models IT-likeness and alignment with human behavior, as well as an increase in its adversarial robustness. We further assessed the limitations of this approach and find that the improvements in behavioral alignment and adversarial robustness generalize across different image statistics, but not to object categories outside of those covered in our IT training set. Taken together, our results demonstrate that building models that are more aligned with the primate brain leads to more robust and human-like behavior, and call for larger neural data-sets to further augment these gains.

neuroscience↗