ABSTRACT
RGB color is a basic visual feature. Here we use machine learning and visual evoked potential (VEP) of electroencephalogram (EEG) data to investigate the decoding features of the time courses and space location that extract it, and whether they depend on a common brain cortex channel. We show that RGB color information can be decoded from EEG data and, with the task-irrelevant paradigm, features can be decoded across fast changes in VEP stimuli. These results are consistent with the theory of both event-related potential (ERP) and P300 mechanisms. The latency on time course is shorter and more temporally precise for RGB color stimuli than P300, a result that does not depend on a task-relevant paradigm, suggesting that RGB color is an updating signal that separates visual events. Meanwhile, distribution features are evident for the brain cortex of EEG signal, providing a space correlate of RGB color in classification accuracy and channel location. Finally, space decoding of RGB color depends on the channel classification accuracy and location obtained through training and testing EEG data. The result is consistent with channel power value distribution discharged by both VEP and electrophysiological stimuli mechanisms.
ABSTRACT
Visual color sensing is generated by electrical discharges from endocranial neuronal sources that penetrate the skull and reach to the cerebral cortex. However, the space location of the source generated by this neural mechanism remains elusive. In this paper, we emulate the generation of visual color signal by task-irrelevant stimuli to activate brain neurons, where its consequences over the cerebral cortex is experimentally tracked. We first document the changes to brain color sensing using electroencephalography (EEG), and find that the sensing classification accuracy of primary visual cortex (V1) regions was positively correlated with the space correlation of visual evoked potential (VEP) power distribution under machine learning decoding. We then explore the decoded results to trace the brain activity neural source location of EEG inversion problem and assess its reconstructive possibility. We show that visual color EEG in V1 can reconstruct endocranial neuronal source location, through the machine learning decoding of channel location.
ABSTRACT
The broad-complex, tramtrack (ttk) and bric-a-brac/poxvirus and zinc finger proteins (BTB/POZ) domain is highly conserved in a large family of eukaryotic proteins and is crucial for the latter's diverse roles in mediating interactions among proteins that are involved in transcription regulation and chromatin structures. From a fetal brain cDNA library, we isolated a cDNA of 2489 base pairs (bp) encoding a novel human BTB domain-containing protein named BTBD10. The cDNA contained an open-reading frame (ORF) of 1428 bp encoding a putative 475-amino acid (aa) protein. The BTBD10 gene was located on human chromosome 11p15.2 and consisted of nine exons spanning about 75.2 kilobase pairs (kb) of the human genome. The cDNA microarray analysis showed that BTBD10 was down-regulated in all 18 glioma samples. The expression pattern of BTBD10 gene was examined by multiple tissue cDNA (MTC) panels (Clontech), which showed a ubiquitous expression pattern in the 16 tissues examined with high expression in adult brain, testis and small intestine and weak expression in the heart, lung, liver, kidney, pancreas, spleen, thymus, prostate, ovary and colon. The subcellular localization result revealed that BTBD10 was located specifically in the nucleus of HEK293 and COS7 cell lines, suggesting that it may function in transcriptional regulation. The different expression patterns of BTBD10 in different grades of glioma versus normal brain were also examined by RT-PCR and Northern blot. We also investigated the expression of BTBD10 in hepatocellular carcinoma, ovary cancer and lung cancer, and the results revealed no significant difference in these three tumors. All these data suggested that BTBD10 might play a role in glioma.
