Unsupervised state representation learning with robotic priors: a robustness benchmark

Our understanding of the world depends highly on our capacity to produce intuitive and simplified representations which can be easily used to solve problems. We reproduce this simplification process using a neural network to build a low dimensional state representation of the world from images acquired by a robot. As in Jonschkowski et al. 2015, we learn in an unsupervised way using prior knowledge about the world as loss functions called robotic priors and extend this approach to high dimension richer images to learn a 3D representation of the hand position of a robot from RGB images. We propose a quantitative evaluation of the learned representation using nearest neighbors in the state space that allows to assess its quality and show both the potential and limitations of robotic priors in realistic environments. We augment image size, add distractors and domain randomization, all crucial components to achieve transfer learning to real robots. Finally, we also contribute a new prior to improve the robustness of the representation. The applications of such low dimensional state representation range from easing reinforcement learning (RL) and knowledge transfer across tasks, to facilitating learning from raw data with more efficient and compact high level representations. The results show that the robotic prior approach is able to extract high level representation as the 3D position of an arm and organize it into a compact and coherent space of states in a challenging dataset.Comment: ICRA 2018 submissio

Deep unsupervised state representation learning with robotic priors: a robustness analysis

International audienceOur understanding of the world depends highly on our capacity to produce intuitive and simplified representations which can be easily used to solve problems. We reproduce this simplification process using a neural network to build a low dimensional state representation of the world from images acquired by a robot. As in Jonschkowski et al. 2015, we learn in an unsupervised way using prior knowledge about the world as loss functions called robotic priors and extend this approach to high dimension richer images to learn a 3D representation of the hand position of a robot from RGB images. We propose a quantitative evaluation metric of the learned representation that uses nearest neighbors in the state space and allows to assess its quality and show both the potential and limitations of robotic priors in realistic environments. We augment image size, add distractors and domain randomization, all crucial components to achieve transfer learning to real robots. Finally, we also contribute a new prior to improve the robustness of the representation. The applications of such low dimensional state representation range from easing reinforcement learning (RL) and knowledge transfer across tasks, to facilitating learning from raw data with more efficient and compact high level representations. The results show that the robotic prior approach is able to extract high level representation as the 3D position of an arm and organize it into a compact and coherent space of states in a challenging dataset

14-3-3theta Protects against Neurotoxicity in a Cellular Parkinson's Disease Model through Inhibition of the Apoptotic Factor Bax

Disruption of 14-3-3 function by alpha-synuclein has been implicated in Parkinson's disease. As 14-3-3s are important regulators of cell death pathways, disruption of 14-3-3s could result in the release of pro-apoptotic factors, such as Bax. We have previously shown that overexpression of 14-3-3θ reduces cell loss in response to rotenone and MPP+ in dopaminergic cell culture and reduces cell loss in transgenic C. elegans that overexpress alpha-synuclein. In this study, we investigate the mechanism for 14-3-3θ's neuroprotection against rotenone toxicity. While 14-3-3s can inhibit many pro-apoptotic factors, we demonstrate that inhibition of one factor in particular, Bax, is important to 14-3-3s' protection against rotenone toxicity in dopaminergic cells. We found that 14-3-3θ overexpression reduced Bax activation and downstream signaling events, including cytochrome C release and caspase 3 activation. Pharmacological inhibition or shRNA knockdown of Bax provided protection against rotenone, comparable to 14-3-3θ's neuroprotective effects. A 14-3-3θ mutant incapable of binding Bax failed to protect against rotenone. These data suggest that 14-3-3θ's neuroprotective effects against rotenone are at least partially mediated by Bax inhibition and point to a potential therapeutic role of 14-3-3s in Parkinson's disease

Chapter 8 - Multiple Roles of Glycogen Synthase Kinase-3 in Alzheimer's Disease

One of the most notable developments in research concerning Alzheimer's disease is the solid evidence directly linking glycogen synthase kinase-3 (GSK-3) to most, if not all, of the major mechanisms known to contribute to the neuropathology of the disease. GSK-3 interacts with multiple components of the plaque-producing amyloid system associated with Alzheimer's disease. GSK-3 participates in phosphorylating the microtubule-binding protein tau, which may contribute to the formation of neurofibrillary tangles in Alzheimer's disease. GSK-3 interacts with presenilin and other Alzheimer's disease-associated proteins. GSK-3 has a central role in neuronal plasticity and memory. GSK-3 promotes both inflammation and apoptosis. These many links between GSK-3 and Alzheimer's disease are discussed in this chapter

14-3-3θ overexpression reduces rotenone-induced cytochrome C release and caspase 3 cleavage.

<p><b>a)</b> Vector control and 14-3-3θ cells were treated with 5 µM rotenone for 24 hours, and cytosolic fractions were immunoblotted with a mouse monoclonal antibody against cytochrome C. Densitometric quantification includes five independent experiments. Tubulin was used as the loading control for Western blots. Error bars reflect SEM. **p<0.01 (Bonferroni's multiple comparison test). n.s.  =  non-significant. <b>b)</b> Vector control and 14-3-3θ cells were treated with 5 µM rotenone for 24 hours, and cell lysates were immunoblotted with a rabbit polyclonal antibody against cleaved caspase 3. Densitometric quantification includes three independent experiments. Tubulin was used as the loading control for Western blots. Error bars reflect SEM. **p<0.01, ***p<0.001 (Bonferroni's multiple comparison test). n.s.  =  non-significant.</p

Rotenone-induced Bax activation is reduced in 14-3-3θ-overexpressing cells.

<p><b>a) Less Bax translocated to mitochondria in 14-3-3θ cells in response to rotenone.</b> After treatment with 5 µM rotenone for 24 hours, vector control and 14-3-3θ cell lysates were subfractionated into cytosolic and mitochondrial fractions and immunoblotted with a polyclonal rabbit antibody against Bax. For each fraction, lanes for vector control and 14-3-3θ cells are from the same gel and exposure time but are separated for clarity with regard to quantification. Bax levels were normalized to tubulin for the cytosolic fraction or cyclophilin D for the mitochondrial fraction. Bax levels for rotenone-treated cells are shown as the relative percentage of the corresponding untreated cells. Densitometric quantification included seven separate experiments. Error bars reflect SEM. *p<0.05, **p<0.01 (one sample t-test). <b>b) Total Bax levels were unchanged with rotenone treatment in either cell line.</b> After treatment with 5 µM rotenone for 24 hours, whole cell lysates were immunoblotted with an anti-Bax antibody. <b>c) Fewer 14-3-3θ cells were positive for activated Bax upon rotenone treatment.</b> After treatment without (i-iv) or with rotenone (v-viii) for 16 hours, vector control and 14-3-3θ cells were fixed in 2% paraformaldehyde and immunostained with a monoclonal mouse antibody against the active Bax conformation (6A7) and a goat Alexa 488-conjugated anti-mouse secondary antibody (i, ii, v, vi). Nuclei were stained with Hoechst 33342 (iii, iv, vii, viii). The number of 6A7-positive cells was quantitated with rater blind to experimental conditions. Error bars reflect SEM. **p<0.01, ***p<0.001 (Bonferroni's multiple comparison test). Scale bar  = 50 µm. <b>d) Rotenone-induced Bax oligomerization was reduced in 14-3-3θ cells.</b> Vector control and 14-3-3θ stable cells were treated with 5 µM rotenone for 24 hours. Mitochondrially-enriched fractions were crosslinked and immunoblotted for oligomers with an anti-Bax antibody. Cyclophilin D served as loading control. Densitometric quantification includes three independent experiments. Error bars reflect SEM. ***p<0.001 (Bonferroni's multiple comparison test). n.s.  =  non-significant.</p