Early Detection of Human Decision-Making in Concealed Object Visual Searching Tasks: An EEG-BiLSTM Study.

Detecting concealed objects presents a significant challenge for human and artificial intelligent systems. Detecting concealed objects task necessitates a high level of human attention and cognitive effort to complete the task successfully. Thus, in this study, we use concealed objects as stimuli for our decision-making experimental paradigms to quantify participants' decision-making performance. We applied a deep learning model, Bi-directional Long Short Term Memory (BiLSTM), to predict the participant's decision accuracy by using their electroencephalogram (EEG) signals as input. The classifier model demonstrated high accuracy, reaching 96.1% with an epoching time range of 500 ms following the stimulus event onset. The results revealed that the parietal-occipital brain region provides highly informative information for the classifier in the concealed visual searching tasks. Furthermore, the neural mechanism underlying the concealed visual-searching and decision-making process was explained by analyzing serial EEG components. The findings of this study could contribute to the development of a fault alert system, which has the potential to improve human decision-making performance.

Classification of inattentional blindness using brain dynamics of ERPs.

Situational awareness (SA) is vital for understanding our surroundings. Multiple variables, including inattentive blindness (IB), contribute to the deterioration of SA, which may have detrimental effects on individuals' cognitive performance. IB occurs due to attentional limitations, ignoring critical information and resulting in a loss of SA and a decline in general performance, particularly in complicated situations requiring substantial cognitive resources. To the best of our knowledge, however, past research has not fully uncovered the neurological characteristics of IB nor classified these characteristics in life-alike virtual situations. Therefore, the purpose of this study is to determine whether ERP dynamics in the brain may be utilised as a neural feature to predict the occurrence of IB using machine learning (ML) algorithms. In a virtual reality simulation of an IB experiment, 30 participants' behaviour and Electroencephalography (EEG) measurements were obtained. Participants were given a target detection task in the IB experiment without knowing the unattended shapes displayed on the background building. The targets were presented in three different sensory modalities (auditory, visual, and visual-auditory). On the post-experiment questionnaire, participants who claimed not to have noticed the unattended shapes were assigned to the IB group. Subsequently, the Aware group was formed from individuals who reported seeing the unattended shapes. Using EEGNet to classify IB and Aware groups demonstrated a high classification performance. According to the research, ERP brain dynamics are associated with the awareness of unattended shapes and have the potential to serve as a reliable indication for predicting the visual consciousness of unexpected objects.(p/)(p)Clinical relevance- This research offers a potential brain marker for the mixed-reality and BCI systems that will be used in the future to identify cognitive deterioration, maintain attentional capacity, and prevent disasters.

Distinction of the object recognition and object identification in the brain-computer interfaces applications.

Object recognition is a complex cognitive process in which information is integrated and processed by various brain regions. Previous studies have shown that both the visual and temporal cortices are active during object recognition and identification. However, although object recognition and object identification are similar, these processes are considered distinct functions in the brain. Despite this, the differentiation between object recognition and identification has yet to be clearly defined for use in brain-computer interface (BCI) applications. This research aims to utilize neural features related to object recognition and identification and classify these features to differentiate between the two processes. The results demonstrate that several classifiers achieved high levels of accuracy, with the XGBoost classifier using a Linear Booster achieving the highest accuracy at 96% and a F1 score of 0.97. This ability to distinguish between object recognition and identification can be a beneficial aspect of a BCI object recognition system as it could help determine the intended target object for a user.

Ventral and Dorsal Stream EEG Channels: Key Features for EEG-Based Object Recognition and Identification.

Object recognition and object identification are multifaceted cognitive operations that require various brain regions to synthesize and process information. Prior research has evidenced the activity of both visual and temporal cortices during these tasks. Notwithstanding their similarities, object recognition and identification are recognized as separate brain functions. Drawing from the two-stream hypothesis, our investigation aims to understand whether the channels within the ventral and dorsal streams contain pertinent information for effective model learning regarding object recognition and identification tasks. By utilizing the data we collected during the object recognition and identification experiment, we scrutinized EEGNet models, trained using channels that replicate the two-stream hypothesis pathways, against a model trained using all available channels. The outcomes reveal that the model trained solely using the temporal region delivered a high accuracy level in classifying four distinct object categories. Specifically, the object recognition and object identification models achieved an accuracy of 89% and 85%, respectively. By incorporating the channels that mimic the ventral stream, the model's accuracy was further improved, with the object recognition model and object identification model achieving an accuracy of 95% and 94%, respectively. Furthermore, the Grad-CAM result of the trained models revealed a significant contribution from the ventral and dorsal stream channels toward the training of the EEGNet model. The aim of our study is to pinpoint the optimal channel configuration that provides a swift and accurate brain-computer interface system for object recognition and identification.

Implementing patient-reported outcomes into routine care: an audit of cancer patients from two local health districts in New South Wales to understand their capabilities and preferences.

Objective It has been established that the implementation of patient-reported outcome measures (PROMs) in routine care provides significant benefits to patients, providers and health services. However, there are patient-level barriers that must be identified and addressed for the successful implementation of PROMs. This study aimed to understand the capabilities and preferences of our cancer patient population prior to implementation of electronically collected PROMs (ePROMs). Specifically, we conducted a clinic audit to determine the proportion of patients in clinics with access to out-of-clinic internet; those preferring to complete PROMs on paper or via an electronic device; those capable of completing PROMs in English; and those anticipating requiring assistance to complete PROMs. Methods Patients receiving cancer treatment or follow-up care at two Local Health Districts (LHDs) in New South Wales, Australia, completed a questionnaire (audit form) with items about internet and mobile access, communication preferences and assistance needed to complete PROMs. Participant demographic and treatment information were extracted from their electronic medical records. Results Across both LHDs, 637 of 1668 participants (38%) completed the audit forms. Mean participant age was 65 years (range = 23-98), 53% were female, and 92% were outpatients. Patients in the two LHDs differed in their levels of internet and email access, and ability to complete PROMs independently in English, suggesting that some LHD-specific tailoring of implementation strategies is necessary to optimise ePROMs uptake. Conclusion This study highlights the importance of understanding the specific local contexts and patient populations, including potential technology and language barriers, which can influence patient ability to complete ePROMs.

Multiple Pleomorphic Tetramers of Thermostable Direct Hemolysin from Grimontia hollisae in Exerting Hemolysis and Membrane Binding.

Oligomerization of protein into specific quaternary structures plays important biological functions, including regulation of gene expression, enzymes activity, and cell-cell interactions. Here, we report the determination of two crystal structures of the Grimontia hollisae (formally described as Vibrio hollisae) thermostable direct hemolysin (Gh-TDH), a pore-forming toxin. The toxin crystalized in the same space group of P21212, but with two different crystal packing patterns, each revealing three consistent tetrameric oligomerization forms called Oligomer-I, -II, and -III. A central pore with comparable depth of ~50 Å but differing in shape and size was observed in all determined toxin tetrameric oligomers. A common motif of a toxin dimer was found in all determined structures, suggesting a plausible minimum functional unit within the tetrameric structure in cell membrane binding and possible hemolytic activity. Our results show that bacterial toxins may form a single or highly symmetric oligomerization state when exerting their biological functions. The dynamic nature of multiple symmetric oligomers formed upon release of the toxin may open a niche for bacteria survival in harsh living environments.

Site-directed mutations of thermostable direct hemolysin from Grimontia hollisae alter its arrhenius effect and biophysical properties.

Recombinant thermostable direct hemolysin from Grimontia hollisae (Gh-rTDH) exhibits paradoxical Arrhenius effect, where the hemolytic activity is inactivated by heating at 60 °C but is reactivated by additional heating above 80 °C. This study investigated individual or collective mutational effect of Tyr53, Thr59, and Ser63 positions of Gh-rTDH on hemolytic activity, Arrhenius effect, and biophysical properties. In contrast to the Gh-rTDH wild-type (Gh-rTDH(WT)) protein, a 2-fold decrease of hemolytic activity and alteration of Arrhenius effect could be detected from the Gh-rTDH(Y53H/T59I) and Gh-rTDH(T59I/S63T) double-mutants and the Gh-rTDH(Y53H/T59I/S63T) triple-mutant. Differential scanning calorimetry results showed that the Arrhenius effect-loss and -retaining mutants consistently exhibited higher and lower endothermic transition temperatures, respectively, than that of the Gh-rTDH(WT). Circular dichroism measurements of Gh-rTDH(WT) and Gh-rTDH(mut) showed a conspicuous change from a ß-sheet to α-helix structure around the endothermic transition temperature. Consistent with the observation is the conformational change of the proteins from native globular form into fibrillar form, as determined by Congo red experiments and transmission electron microscopy.

Purification, crystallization and preliminary X-ray analysis of a thermostable direct haemolysin from Grimontia hollisae.

Vibrio hollisae, a halophilic species recently reclassified as Grimontia hollisae, is a causative agent of gastroenteritis and septicaemia. One important pathogenic Vibrio factor, thermostable direct haemolysin (TDH), has been purified and crystallized in two crystal forms using the vapour-diffusion method. The crystals belonged to an orthorhombic space group, with unit-cell parameters a = 104.8, b = 112.4, c = 61.3 Šand a = 122.9, b = 123.3, c = 89.8 Å. The crystals contained either four or eight molecules per asymmetric unit, with predicted solvent contents of 49.4 and 46.3% and Matthews coefficients (V(M)) of 2.4 and 2.3 Å(3) Da(-1), respectively. These crystals were suitable for structure determination, which would yield structural details related to the cytotoxicity and oligomeric structure of this pore-forming toxin.