An Integration of Deep Learning and Neuroscience for Machine Consciousness

Conscious processing is a useful aspect of brain function that can be used as a model to design artificial-intelligence devices There are still certain computational features that our conscious brains possess and which machines currently fail to perform those This paper discusses the necessary elements needed to make the device conscious and suggests if those implemented the resulting machine would likely to be considered conscious Consciousness mainly presented as a computational tool that evolved to connect the modular organization of the brain Specialized modules of the brain process information unconsciously and what we subjectively experience as consciousness is the global availability of data which is made possible by a non modular global workspace During conscious perception the global neuronal work space at parieto-frontal part of the brain selectively amplifies relevant pieces of information Supported by large neurons with long axons which makes the long-distance connectivity possible the selected portions of information stabilized and transmitted to all other brain modules The brain areas that have structuring ability seem to match to a specific computational problem The global workspace maintains this information in an active state for as long as it is needed In this paper a broad range of theories and specific problems have been discussed which need to be solved to make the machine conscious Later particular implications of these hypotheses for research approach in neuroscience and machine learning are debate

An Integration of Deep Learning and Neuroscience for Machine Consciousness

Conscious processing is a useful aspect of brain function that can be used as a model to design artificial-intelligence devices. There are still certain computational features that our conscious brains possess, and which machines currently fail to perform those. This paper discusses the necessary elements needed to make the device conscious and suggests if those implemented, the resulting machine would likely to be considered conscious. Consciousness mainly presented as a computational tool that evolved to connect the modular organization of the brain. Specialized modules of the brain process information unconsciously and what we subjectively experience as consciousness is the global availability of data, which is made possible by a non modular global workspace. During conscious perception, the global neuronal work space at parieto-frontal part of the brain selectively amplifies relevant pieces of information. Supported by large neurons with long axons, which makes the long-distance connectivity possible, the selected portions of information stabilized and transmitted to all other brain modules. The brain areas that have structuring ability seem to match to a specific computational problem. The global workspace maintains this information in an active state for as long as it is needed. In this paper, a broad range of theories and specific problems have been discussed, which need to be solved to make the machine conscious. Later particular implications of these hypotheses for research approach in neuroscience and machine learning are debated

Role of Chaperone Mediated Autophagy (CMA) in the Degradation of Misfolded N-CoR Protein in Non-Small Cell Lung Cancer (NSCLC) Cells

Nuclear receptor co-repressor (N-CoR) plays important role in transcriptional control mediated by several tumor suppressor proteins. Recently, we reported a role of misfolded-conformation dependent loss (MCDL) of N-CoR in the activation of oncogenic survival pathway in acute promyelocytic leukemia (APL). Since N-CoR plays important role in cellular homeostasis in various tissues, therefore, we hypothesized that an APL like MCDL of N-CoR might also be involved in other malignancy. Indeed, our initial screening of N-CoR status in various leukemia and solid tumor cells revealed an APL like MCDL of N-CoR in primary and secondary tumor cells derived from non-small cell lung cancer (NSCLC). The NSCLC cell specific N-CoR loss could be blocked by Kaletra, a clinical grade protease inhibitor and by genistein, an inhibitor of N-CoR misfolding previously characterized by us. The misfolded N-CoR presented in NSCLC cells was linked to the amplification of ER stress and was subjected to degradation by NSCLC cell specific aberrant protease activity. In NSCLC cells, misfolded N-CoR was found to be associated with Hsc70, a molecular chaperone involved in chaperone mediated autophagy (CMA). Genetic and chemical inhibition of Lamp2A, a rate limiting factor of CMA, significantly blocked the loss of N-CoR in NSCLC cells, suggesting a crucial role of CMA in N-CoR degradation. These findings identify an important role of CMA-induced degradation of misfolded N-CoR in the neutralization of ER stress and suggest a possible role of misfolded N-CoR protein in the activation of oncogenic survival pathway in NSCLC cells

Gene Expression Profiles of Mst1r-Deficient Mice during Nickel-Induced Acute Lung Injury

Previous studies have shown that mice deficient in the tyrosine kinase domain (TK−/−) of the receptor Mst1r have an increased susceptibility to nickel (Ni)-induced acute lung injury (ALI). Mst1r TK−/− mice have decreased survival times, alterations in cytokine and nitric oxide regulation, and an earlier onset of pulmonary pathology compared with control mice, suggesting that Mst1r signaling, in part, may regulate the response to ALI. To examine the role of Mst1r in ALI in more detail, we compared the gene expression profiles of murine lung mRNA from control and Mst1r TK−/− mice at baseline and after 24 h of particulate Ni sulfate exposure. Microarray analyses showed a total of 343 transcripts that were significantly changed, either by Ni treatment, or between genotypes. Genes responsible for inflammation, edema, and lymphocyte function were altered in the Mst1r TK−/− mice. Interestingly, the genes for several granzymes were increased in Mst1r TK−/− mice before Ni exposure, compared with controls. In addition, the Mst1r TK−/− lungs showed clusters of cells near the vascular endothelium and airways. Immunohistochemistry indicates these clusters are composed of macrophages, T cells, and neutrophils, and that the clusters display granzyme protein production. These results suggest that Mst1r signaling may be involved in the regulation of macrophage and T-lymphocyte activation in vivo during injury. This assessment of gene expression indicates the importance of genetic factors in contributing to lung injury, and points to strategies for intervention in the progression of inflammatory diseases