Language Processing outside the Realm of Consciousness

The concept “Out of sight, out of mind” has been repeatedly challenged by findings that show visual information biases behavior even without reaching consciousness. However, the depth and complexity of unconscious processing remains elusive. To tackle this issue, we examined whether high-level linguistic information, including syntax and semantics, can be processed without consciousness

Language Processing outside the Realm of Consciousness

The concept “Out of sight, out of mind” has been repeatedly challenged by findings that show visual information biases behavior even without reaching consciousness. However, the depth and complexity of unconscious processing remains elusive. To tackle this issue, we examined whether high-level linguistic information, including syntax and semantics, can be processed without consciousness

On the Border of Implicit and Explicit Processing

Implicit processing plays an important role in maintaining visual functions. After all, at a given moment, our phenomenal experience is inherently limited by various factors, including attention, working memory, etc. In the current proposal, we will tackle major questions in the field and challenge intuitions on implicit/unconscious processing. These questions include the fundamental relation between attention and consciousness, using the level of visual processing as a delineation of explicit and implicit processing, and how implicit decision making perturbs the explicit sense of agency

Mind Wandering in Sensory Cortices

Mind wandering contains rich phenomenology as we experience moment by moment, however, such linkage between our subjective experiences and the underlying neural mechanism has been missing in the literature. Here we report that the sensory contents of mind wandering recruit corresponding sensory cortices, serving as the neural bases of the sensory contents in mind wandering

Task-induced attention load guides and gates unconscious semantic interference

The tight relationship between attention and conscious perception has been extensively researched in the past decades. However, whether attentional modulation extended to unconscious processes remained largely unknown, particularly when it came to abstract and high-level processing. Here we use a double Stroop paradigm to demonstrate that attention load gates unconscious semantic processing. We find that word and color incongruencies between a subliminal prime and a supraliminal target cause slower responses to non-Stroop target words—but only if the task is to name the target word (low-load task), and not if the task is to name the target’s color (high-load task). The task load hypothesis is confirmed by showing that the word-induced incongruence effect can be detected in the color-naming task, but only in the late, practiced trials. We further replicate this task-induced attentional modulation phenomenon in separate experiments with colorless words (word-only) and words with semantic relationship but no orthographic similarities (semantics-only)

Genetic analysis of fish iridoviruses isolated in Taiwan during 2001–2009

To investigate the genetic relationships between field strains of iridoviruses gathered from various fish species in Taiwan, viruses that were collected from 2001 to 2009 were analyzed. Open reading frames encoding the viral major capsid protein (MCP) and adenosine triphosphatase (ATPase) were sequenced for phylogenetic analysis. Our results indicated that iridoviruses from Taiwan aquaculture fishes could be classified into two groups: prior to 2005, the viruses were closely related to members of the genus Ranavirus; and after 2005, they were similar to members of the genus Megalocytivirus. Based on the analysis of MCP amino acid sequences, virus isolates were divided into 4 major genotypes that were related to ISKNV, RSIV, FLIV, and GIV, respectively. Pairwise comparisons of MCP genes showed that the ranavirus was an epidemic pathogen for economically important species in the major production regions and cultured marine fish, while the megalocytivirus isolates were sensitive to host range. In addition, the distribution of synonymous and non-synonymous changes in the MCP gene revealed that the iridoviruses were evolving slowly, and most of the variations were synonymous mutations. The Ka/Ks values were lower than one, and hence, the viruses were under negative selection

Combined Application Therapies of Stem Cells and Drugs in the Neurological Disorder Attenuation

Neurological disorders (NDs) are diseases of the central and peripheral nervous system that affected the hundreds of millions of people worldwide. Temporal lobe epilepsy (TLE) is a common NDs with hallucinations and disturbance of consciousness that cause the abnormal neurological activity in any part of brain. Neuroinflammation (NI) has been identified in epilepsy-related tissue from both experimental and clinical evidence and suspected to participate in the formation of neuronal cell death, reactive gliosis and neuroplastic changes in the hippocampus, may contribute to epileptogenesis. The NI is tightly regulated by microglia, but it is thought that excessive or chronic microglial activation can contribute to neurodegenerative processes. Therefore, the modulation of microglia responses may provide a therapeutic target for the treatment of severe or chronic NI conditions. Although the condition responds well to antiepileptic drugs (AEDs), there are still unresponsive to AEDs in about 1/3 of cases. Neural stem cells are the origin of various types of neural cells during embryonic development. Currently, many results of stem cell therapies in the animal experiments and clinical trials were demonstrated the efficacious therapeutic effects in the attenuated symptoms of ND. Therefore, the combined application therapies of stem cells and drugs may be a promising candidate for the therapeutic strategies of NDs, especially TLE

Location-Aware Visual Question Generation with Lightweight Models

This work introduces a novel task, location-aware visual question generation (LocaVQG), which aims to generate engaging questions from data relevant to a particular geographical location. Specifically, we represent such location-aware information with surrounding images and a GPS coordinate. To tackle this task, we present a dataset generation pipeline that leverages GPT-4 to produce diverse and sophisticated questions. Then, we aim to learn a lightweight model that can address the LocaVQG task and fit on an edge device, such as a mobile phone. To this end, we propose a method which can reliably generate engaging questions from location-aware information. Our proposed method outperforms baselines regarding human evaluation (e.g., engagement, grounding, coherence) and automatic evaluation metrics (e.g., BERTScore, ROUGE-2). Moreover, we conduct extensive ablation studies to justify our proposed techniques for both generating the dataset and solving the task.Comment: EMNLP 202