scholarly journals The Memory for Latent Representations: An Account of Working Memory that Builds on Visual Knowledge for Efficient and Detailed Visual Representations

2021 ◽  
Author(s):  
Shekoofeh Hedayati ◽  
Ryan O’Donnell ◽  
Brad Wyble
Keyword(s):  
Working Memory ◽  
Visual System ◽  
Critical Role ◽  
Mechanistic Explanation ◽  
Shape Information ◽  
Visual Knowledge ◽  
Proposed Model ◽  
Categorical Information ◽  
Latent Representations ◽  
Efficient Memory

AbstractVisual knowledge obtained from our lifelong experience of the world plays a critical role in our ability to build short-term memories. We propose a mechanistic explanation of how working memories are built from the latent representations of visual knowledge and can then be reconstructed. The proposed model, Memory for Latent Representations (MLR), features a variational autoencoder with an architecture that corresponds broadly to the human visual system and an activation-based binding pool of neurons that binds items' attributes to tokenized representations. The simulation results revealed that shape information for stimuli that the model was trained on, can be encoded and retrieved efficiently from latents in higher levels of the visual hierarchy. On the other hand, novel patterns that are completely outside the training set can be stored from a single exposure using only latents from early layers of the visual system. Moreover, a given stimulus in working memory can have multiple codes, representing specific visual features such as shape or color, in addition to categorical information. Finally, we validated our model by testing a series of predictions against behavioral results acquired from WM tasks. The model provides a compelling demonstration of visual knowledge yielding the formation of compact visual representation for efficient memory encoding.

scholarly journals Graph contextualized attention network for predicting synthetic lethality in human cancers

2021 ◽  
Author(s):  
Yahui Long ◽  
Min Wu ◽  
Yong Liu ◽  
Jie Zheng ◽  
Chee Keong Kwoh ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Critical Role ◽  
Design Feature ◽  
Cost Effective ◽  
Attention Network ◽  
New Genes ◽  
Lab Experiments ◽  
Proposed Model ◽  
Multiple Feature ◽  
Wet Lab

Abstract Motivation Synthetic Lethality (SL) plays an increasingly critical role in the targeted anticancer therapeutics. In addition, identifying SL interactions can create opportunities to selectively kill cancer cells without harming normal cells. Given the high cost of wet-lab experiments, in silico prediction of SL interactions as an alternative can be a rapid and cost-effective way to guide the experimental screening of candidate SL pairs. Several matrix factorization-based methods have recently been proposed for human SL prediction. However, they are limited in capturing the dependencies of neighbors. In addition, it is also highly challenging to make accurate predictions for new genes without any known SL partners. Results In this work, we propose a novel graph contextualized attention network named GCATSL to learn gene representations for SL prediction. First, we leverage different data sources to construct multiple feature graphs for genes, which serve as the feature inputs for our GCATSL method. Second, for each feature graph, we design node-level attention mechanism to effectively capture the importance of local and global neighbors and learn local and global representations for the nodes, respectively. We further exploit multi-layer perceptron (MLP) to aggregate the original features with the local and global representations and then derive the feature-specific representations. Third, to derive the final representations, we design feature-level attention to integrate feature-specific representations by taking the importance of different feature graphs into account. Extensive experimental results on three datasets under different settings demonstrated that our GCATSL model outperforms 14 state-of-the-art methods consistently. In addition, case studies further validated the effectiveness of our proposed model in identifying novel SL pairs. Availability Python codes and dataset are freely available on GitHub (https://github.com/longyahui/GCATSL) and Zenodo (https://zenodo.org/record/4522679) under the MIT license.

Investigation of the relationships among educational application (APP) quality, computer anxiety and student engagement

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jung-Chieh Lee ◽  
Liang Nan Xiong
Keyword(s):  
Student Engagement ◽  
Computer Anxiety ◽  
Critical Role ◽  
System Quality ◽  
Is Success ◽  
Content Type ◽  
Mediating Role ◽  
Proposed Model ◽  
Traditional Classroom Teaching ◽  
Educational Applications

PurposeNumerous educational applications (APP) have been developed to assist traditional classroom teaching and student learning. APP quality plays a critical role in influencing students' learning behaviors. However, the role negative mindsets, especially computer anxiety, play in how APP quality affects student engagement remains unknown. To address the relationships among APP quality, computer anxiety and student engagement in an APP-based learning environment, we developed an extended information system (IS) success model that includes interface and instructor quality.Design/methodology/approachTo empirically test the proposed model, we conducted a survey with a sample of 225 university students and examined the hypotheses using the partial least squares (PLS) method.FindingsComputer anxiety was demonstrated to fully mediate the relationships between student engagement and interface quality and service quality and system quality. In addition, the instructor quality acts as a partial mediator of the relationship between computer anxiety and student engagement.Originality/valueThis study reveals the important mediating role of computer anxiety in APP-assisted learning and the special status of instructor quality and user experience in influencing student engagement. The findings of this study shed meaningful light on the practical implications for instructors and APP software developers.

scholarly journals The Neural Basis of Reversible Sentence Comprehension: Evidence from Voxel-based Lesion Symptom Mapping in Aphasia

2012 ◽  
Vol 24 (1) ◽  
pp. 212-222 ◽  
Author(s):  
Malathi Thothathiri ◽  
Daniel Y. Kimberg ◽  
Myrna F. Schwartz
Keyword(s):  
Working Memory ◽  
Parietal Cortex ◽  
Sentence Comprehension ◽  
Critical Role ◽  
Broca's Area ◽  
Neural Basis ◽  
Phonological Working Memory ◽  
Large Group ◽  
Complex Sentences ◽  
Lesion Symptom Mapping

We explored the neural basis of reversible sentence comprehension in a large group of aphasic patients (n = 79). Voxel-based lesion symptom mapping revealed a significant association between damage in temporo-parietal cortex and impaired sentence comprehension. This association remained after we controlled for phonological working memory. We hypothesize that this region plays an important role in the thematic or what–where processing of sentences. In contrast, we detected weak or no association between reversible sentence comprehension and the ventrolateral pFC, which includes Broca's area, even for syntactically complex sentences. This casts doubt on theories that presuppose a critical role for this region in syntactic computations.

scholarly journals Conceptual distinctiveness does not improve visual working memory for objects but aids object-location binding

2021 ◽  
Author(s):  
Yuri Markov ◽  
Igor Utochkin
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Competitive Interactions ◽  
Object Location ◽  
Location Information ◽  
Limited Capacity ◽  
Common Features ◽  
Categorical Information ◽  
Location Binding ◽  
Different Sources

Visual working memory (VWM) is prone to interference from stored items competing for its limited capacity. These competitive interactions can arise from different sources. For example, one such source is poor item distinctiveness causing a failure to discriminate between items sharing common features. Another source of interference is imperfect binding, a problem of determining which of the remembered features belonged to which object or which item was in which location. In two experiments, we studied how the conceptual distinctiveness of real-world objects (i.e., whether the objects belong to the same or different basic categories) affects VWM for objects and object-location binding. In Experiment 1, we found that distinctiveness did not affect memory for object identities or for locations, but low-distinctive objects were more frequently reported at “swapped” locations that originally went with different objects. In Experiment 2 we found evidence that the effect of distinctiveness on the object-location swaps was due to the use of categorical information for binding. In particular, we found that observers swapped the location of a tested object with another object from the same category more frequently than with any of the objects from another category. This suggests that observers can use some coarse category-location information when objects are conceptually distinct. Taken together, our findings suggest that object distinction and object-location binding act upon different components of VWM.

scholarly journals Prefrontal and Parietal Attractor Networks Mediate Working Memory Judgments

2020 ◽  
Author(s):  
Sihai Li ◽  
Christos Constantinidis ◽  
Xue-Lian Qi
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Dorsolateral Prefrontal Cortex ◽  
Critical Role ◽  
Memory Task ◽  
Delayed Response ◽  
Persistent Activity ◽  
Neural Basis ◽  
Brain Areas ◽  
Dorsolateral Prefrontal

ABSTRACTThe dorsolateral prefrontal cortex plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here we addressed whether this predictive ability extends to categorical judgments based on information retained in working memory, and is present in other brain areas. We trained monkeys in a novel, Match-Stay, Nonmatch-Go task, which required them to observe two stimuli presented in sequence with an intervening delay period between them. If the two stimuli were different, the monkeys had to saccade to the location of the second stimulus; if they were the same, they held fixation. Neurophysiological recordings were performed in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC. We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and towards the location of the second stimulus would result in categorical errors. Indeed, for both areas, when the first stimulus appeared in a neuron’s preferred location, the neuron showed significantly higher firing rates in correct than in error trials. When the first stimulus appeared at a nonpreferred location and the second stimulus at a preferred, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and the magnitude of neuronal firing rate deviations is revealing of the contents of working memory as it determines performance.SIGNIFICANCE STATEMENTThe neural basis of working memory and the areas mediating this function is a topic of controversy. Persistent activity in the prefrontal cortex has traditionally been thought to be the neural correlate of working memory, however recent studies have proposed alternative mechanisms and brain areas. Here we show that persistent activity in both the dorsolateral prefrontal cortex and posterior parietal cortex predicts behavior in a working memory task that requires a categorical judgement. Our results offer support to the idea that a network of neurons in both areas act as an attractor network that maintains information in working memory, which informs behavior.

Manifold Visual Working Memory

2020 ◽  
pp. 311-332
Author(s):  
Nicole Hakim ◽  
Edward Awh ◽  
Edward K. Vogel
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Neural Activity ◽  
Long Term Memory ◽  
Term Memory ◽  
Memory Representations ◽  
Latent Representations ◽  
Definition Of ◽  
Spatial Locations

Visual working memory allows us to maintain information in mind for use in ongoing cognition. Research on visual working memory often characterizes it within the context of its interaction with long-term memory (LTM). These embedded-processes models describe memory representations as existing in three potential states: inactivated LTM, including all representations stored in LTM; activated LTM, latent representations that can quickly be brought into an active state due to contextual priming or recency; and the focus of attention, an active but sharply limited state in which only a small number of items can be represented simultaneously. This chapter extends the embedded-processes framework of working memory. It proposes that working memory should be defined operationally based on neural activity. By defining working memory in this way, the important theoretical distinction between working memory and LTM is maintained, while still acknowledging that they operate together. It is additionally proposed that active working memory should be further subdivided into at least two subcomponent processes that index item-based storage and currently prioritized spatial locations. This fractionation of working memory is based on recent research that has found that the maintenance of information distinctly relies on item-based representations as well as prioritization of spatial locations. It is hoped that this updated framework of the definition of working memory within the embedded-processes model provides further traction for understanding how we maintain information in mind.

Strategic Human Resource Development Alignment

2016 ◽  
pp. 85-100
Author(s):  
Ann Herd ◽  
Meera Alagaraja
Keyword(s):  
Human Resource Development ◽  
Human Resource ◽  
Critical Role ◽  
Resource Development ◽  
Future Research ◽  
Global Marketplace ◽  
Strategic Objectives ◽  
Organizational Learning Culture ◽  
Proposed Model ◽  
And Performance

The critical role of human resource development (HRD) in helping organizations identify and meet their strategic objectives in today's competitive and ever-changing global marketplace is increasingly being recognized by both scholars and practitioners. While many HRD scholars have examined the importance of HRD alignment with the organization's strategic objectives, there exist few conceptualizations of this alignment from the employee's perspective. Drawing on strategic HRD and management “line of sight” literature, the purpose of this chapter is to explore the theoretical conceptualization and a proposed model of employee perceptions of the strategic alignment of HRD in their organizations. Strategic HRD alignment from the employee's perspective is explored, and future research directions are discussed, in relation to strategic HRD, organizational learning culture, perceived investment in employee development, and performance-related outcomes for which HRD scholar-practitioners strive in their quest to facilitate organizational strategic objectives.

Glutamate in the pathophysiology of schizophrenia

2020 ◽  
pp. 287-296
Author(s):  
Daniel C. Javitt
Keyword(s):  
Visual System ◽  
Visual Processing ◽  
Negative Symptoms ◽  
Glutamate Release ◽  
Critical Role ◽  
Brain Regions ◽  
Long Term Memory ◽  
Subcortical Structures ◽  
Impaired Metabolism

Glutamate theories of schizophrenia were first proposed over 30 years ago and since that time have become increasingly accepted. Theories are supported by the ability of N-methyl-D-aspartate receptor (NMDAR) antagonists such as phencyclidine (PCP) or ketamine to induce symptoms that closely resemble those of schizophrenia. Moreover, NMDAR antagonists uniquely reproduce the level of negative symptoms and cognitive deficits observed in schizophrenia, suggesting that such models may be particularly appropriate to poor outcome forms of the disorder. As opposed to dopamine, which is most prominent within frontostriatal brain regions, glutamate neurons are present throughout cortex and subcortical structures. Thus, NMDAR theories predict widespread disturbances across cortical and thalamic pathways, including sensory brain regions. In auditory cortex, NMDAR play a critical role in the generation of mismatch negativity (MMN), which may therefore serve as a translational marker of NMDAR dysfunction across species. In the visual system, NMDAR play a critical role in function of the magnocellular visual system. Deficits in both auditory and visual processing contribute to social and communication deficits, which, in turn, lead to poor functional outcome. By contrast, NMDAR dysfunction within the frontohippocampal system may contribute to well described deficits in working memory, executive processing and long-term memory formation. Deficits in NMDAR function may be driven by disturbances in presynaptic glutamate release, impaired metabolism of NMDAR modulators such as glycine or D-serine, or intrinsic abnormalities in NMDAR themselves.

Concurrent verbal working memory load constrains cross-linguistic translation activation: A visual world eye-tracking study on Hindi–English bilinguals

2020 ◽  
pp. 1-30
Author(s):  
Seema Prasad ◽  
Ramesh Kumar Mishra
Keyword(s):  
Working Memory ◽  
Memory Load ◽  
Critical Role ◽  
Verbal Working Memory ◽  
Spoken Word ◽  
Cognitive Resources ◽  
Visual World ◽  
Sequence Recognition ◽  
Word Onset ◽  
Study Participants

Abstract Does a concurrent verbal working memory (WM) load constrain cross-linguistic activation? In a visual world study, participants listened to Hindi (L1) or English (L2) spoken words and viewed a display containing the phonological cohort of the translation equivalent (TE cohort) of the spoken word and 3 distractors. Experiment 1 was administered without a load. Participants then maintained two or four letters (Experiment 2) or two, six or eight letters (Experiment 3) in WM and were tested on backward sequence recognition after the visual world display. Greater looks towards TE cohorts were observed in both the language directions in Experiment 1. With a load, TE cohort activation was inhibited in the L2 – L1 direction and observed only in the early stages after word onset in the L1 – L2 direction suggesting a critical role of language direction. These results indicate that cross-linguistic activation as seen through eye movements depends on cognitive resources such as WM.

scholarly journals The Dynamic-Processing Model of Working Memory

2020 ◽  
Vol 29 (4) ◽  
pp. 378-387
Author(s):  
Nathan S. Rose
Keyword(s):  
Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Short Term ◽  
Dynamic Activity ◽  
Mind And Brain ◽  
Latent Representations ◽  
Dynamic Processing ◽  
Conventional Models ◽  
The Mind

Recent shifts in the understanding of how the mind and brain retain information in working memory (WM) call for revision to traditional theories. Evidence of dynamic, “activity-silent,” short-term retention processes diverges from conventional models positing that information is always retained in WM by sustained neural activity in buffers. Such evidence comes from machine-learning methods that can decode patterns of brain activity and the simultaneous administration of transcranial magnetic stimulation (TMS) to causally manipulate brain activity in specific areas and time points. TMS can “ping” brain areas to both reactivate latent representations retained in WM and affect memory performance. On the basis of these findings, I argue for a supplement to sustained retention mechanisms. Brain-decoding methods also reveal that dynamic levels of representational codes are retained in WM, and these vary according to task context, from perceptual (sensory) codes in posterior areas to abstract, recoded representations distributed across frontoparietal regions. A dynamic-processing model of WM is advanced to account for the overall pattern of results.

Sign in / Sign up

Export Citation Format

Share Document