Effect of Implicit Theory on Effort Allocation Strategies in Multiple Task-Choice Situations: An Investigation From a Socio-Ecological Perspective

Implicit theories refer to two assumptions that people make about the malleability of one’s ability. Previous studies have argued that incremental theorists (who believe that ability is malleable) are more adaptive than entity theorists (who believe that ability is fixed) when facing achievement setbacks. In the present research, we assumed that the adaptive implicit theory would be different when people could choose from a wider range of tasks. It was hypothesized that incremental theorists would sustain their efforts in the first task even when it was difficult, whereas entity theorists would try to find the most appropriate task. In a pair of laboratory experiments, participants had to maximize their outcomes when allowed to choose a task to engage in, from two options. When participants were allowed to practice the two tasks (Study 1), incremental theorists tended to allocate their effort solely to the first task, whereas entity theorists tended to put equal effort into both. When participants were informed that they could switch from the assigned task (Study 2), incremental theorists tended to persist in the first task regardless of its difficulty, whereas entity theorists tended to switch more quickly if the task was difficult. These results supported our hypothesis of two effort allocation strategies and implied that, in certain situations, entity theorists could be more adaptive than incremental theorists. Based on these findings, we conducted a social survey on the difficulty of switching tasks with a real-life setting as an environmental factor that determines the adaptive implicit theory (Study 3). It was revealed that the academic performance of incremental and entity theorists was moderated by the difficulty of switching tasks in their learning environment at school. Cultural differences in implicit theories may be explained by differences in the difficulty of switching tasks in education and career choices in each society.

Attention-Guided Multispectral and Panchromatic Image Classification

Multi-sensor image can provide supplementary information, usually leading to better performance in classification tasks. However, the general deep neural network-based multi-sensor classification method learns each sensor image separately, followed by a stacked concentrate for feature fusion. This way requires a large time cost for network training, and insufficient feature fusion may cause. Considering efficient multi-sensor feature extraction and fusion with a lightweight network, this paper proposes an attention-guided classification method (AGCNet), especially for multispectral (MS) and panchromatic (PAN) image classification. In the proposed method, a share-split network (SSNet) including a shared branch and multiple split branches performs feature extraction for each sensor image, where the shared branch learns basis features of MS and PAN images with fewer learn-able parameters, and the split branch extracts the privileged features of each sensor image via multiple task-specific attention units. Furthermore, a selective classification network (SCNet) with a selective kernel unit is used for adaptive feature fusion. The proposed AGCNet can be trained by an end-to-end fashion without manual intervention. The experimental results are reported on four MS and PAN datasets, and compared with state-of-the-art methods. The classification maps and accuracies show the superiority of the proposed AGCNet model.

Context value updating and multidimensional neuronal encoding in the retrosplenial cortex

The retrosplenial cortex (RSC) has diverse functional inputs and is engaged by various sensory, spatial, and associative learning tasks. We examine how multiple functional aspects are integrated on the single-cell level in the RSC and how the encoding of task-related parameters changes across learning. Using a visuospatial context discrimination paradigm and two-photon calcium imaging in behaving mice, a large proportion of dysgranular RSC neurons was found to encode multiple task-related dimensions while forming context-value associations across learning. During reversal learning requiring increased cognitive flexibility, we revealed an increased proportion of multidimensional encoding neurons that showed higher decoding accuracy for behaviorally relevant context-value associations. Chemogenetic inactivation of RSC led to decreased behavioral context discrimination during learning phases in which context-value associations were formed, while recall of previously formed associations remained intact. RSC inactivation resulted in a persistent positive behavioral bias in valuing contexts, indicating a role for the RSC in context-value updating.

Screening Tests for Cognitive Impairment in Elderly Thai Adults: A Systematic Review

Background: Elderly adults in Thailand are expected to represent 20% of the population in 2021. Screening tools are crucial in initiating cognitive assessments of elderly adults. Clinicians and researchers should select the tools best suited for the characteristics of their population. Several screening tools have been studied in elderly Thai adults over the past 30 years. Objective: To review the data on the screening tests for cognitive impairment currently available in Thailand, and to assess their respective strengths and issues. Materials and Methods: Seven electronic databases including MEDLINE, Embase, PsycINFO, Scopus, Google Scholar, and two specializing in Thai journals, which are ThaiJo and TDC-ThaiLIS, were searched. A hand-search of the reference lists was also undertaken. Two reviewers independently screened the articles, assessed their quality using the QUADAS-2 checklist, and extracted relevant data. Any discrepancies were resolved through discussion. Results: Twenty-eight studies assessing 33 screening tests were included. The tests were categorized into three groups, multiple-task, single-task, and questionnaire-based tools. Six articles studied their accuracy in community-based populations, while the rest were conducted at tertiary-care centers. The highest sensitivities for dementia detection were demonstrated by the Chula Mental Test for the multiple-task assessment test, and the Clock-Drawing Test for the single-task cognitive test. Conclusion: Various screening tests for cognitive impairment have been examined in the Thai population. The present study main observation was that many researchers did not clearly address their methodology and biases. Tackling these issues will ensure a high-quality methodology and validity of screening tests. Future studies should focus on either developing appropriate tools or adapting the existing tools to better suit elderly Thai adults. Keywords: Aging; Cognition; Cognitive Test; Dementia; Screening

Reliable Part Guided Multiple Level Attention Learning for Person Re-Identification

Person Re-ID is challenged by background clutter, body misalignment and part missing. In this paper, we propose a reliable part-based multiple levels attention deep network to learn multiple scales salience representation. In particular, person alignment and key point detection are sequentially carried out to locate three relative stable body components, then fused attention (FA) mode is designed to capture the fine-grained salient features from effective spatial of valuable channels of each part, regional attention mode is succeeded to weight the importance of different parts for highlighting the representative parts while suppressing the valueless ones. A late fusion-based multiple-task loss is finally adopted to further optimize the valuable feature representation. Experimental results demonstrate that the proposed method achieves state-of-the-art performances on three challenging benchmarks: Market-1501, DukeMTMC-reID and CUHK03.

Adapting non-invasive human recordings along multiple task-axes shows unfolding of spontaneous and over-trained choice

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to three task-axes, relevant and irrelevant sensory inputs and response direction in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a progression from processing sensory input to processing the response. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive overtraining common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after overtraining.

Parallel representation of context and multiple context-dependent values in ventro-medial prefrontal cortex

Value representations in ventromedial prefrontal-cortex (vmPFC) are known to guide decisions. But how preferable available options are depends on one's current task. Goal-directed behavior, which involves changing between different task-contexts, therefore requires to know how valuable the same options will be in different contexts. We tested whether multiple task-dependent values influence behavior and asked if they are integrated into a single value representation or are co-represented in parallel within vmPFC signals. Thirty five participants alternated between tasks in which stimulus color or motion predicted rewards. Our results provide behavioral and neural evidence for co-activation of both contextually-relevant and -irrelevant values, and suggest a link between multivariate neural representations and the influence of the irrelevant context and its associated value on behavior. Importantly, current task context could be decoded from the same region, and better context-decodability was associated with stronger (relevant-)value representations. Evidence for choice conflicts was found only in the motor cortex, where the competing values are likely resolved into action.