Kognition

KurzzeitgedächtnisStudienlage & Dosis

Working Memory, 7±2 Items, Aufrechterhaltung.

Studienlage in Zahlen

Studien gesamt: 195
Mit Abstract: 43
Meta / Systematic / RCT: 0
Häufig zitiert: 4
Erscheinungsjahre: 2017–2026

Kurzzeitgedächtnis im Kontext von Kognition

Dieses Thema ist Teil unserer Welt „Kognition". Dort findest du Methodik, Studienlage und Hebel mit dem größten Effekt — sowie die Reihenfolge, in der sich Hebel sinnvoll aufeinander aufbauen.

Zur Welt Kognition

Top-Studien zu Kurzzeitgedächtnis

Sortiert nach einflussreichen Zitationen und Erscheinungsjahr.

XGBoost-SHAP-based interpretable diagnostic framework for alzheimer's disease.
BMC medical informatics and decision making2023n=4.463122 einflussreiche Zitationen
Background Due to the class imbalance issue faced when Alzheimer’s disease (AD) develops from normal cognition (NC) to mild cognitive impairment (MCI), present clinical practice is met with challenges regarding the auxiliary diagnosis of…
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification.
IEEE transactions on bio-medical engineering2019n=200121 einflussreiche Zitationen
Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction framework based on convolutional neural networks (CNNs) for automatic sleep staging, and,…
Attention-Based LSTM for Non-Contact Sleep Stage Classification Using IR-UWB Radar.
IEEE journal of biomedical and health informatics202126 einflussreiche Zitationen
Manual scoring of sleep stages from polysomnography (PSG) records is essential to understand the sleep quality and architecture. Since the PSG requires specialized personnel, a lab environment, and uncomfortable sensors, non-contact sleep…
Rehabilitative Effects of Virtual Reality Technology for Mild Cognitive Impairment: A Systematic Review With Meta-Analysis
Frontiers in Psychology2020n=6126 einflussreiche Zitationen
<b>Objective:</b> To evaluate the impact of virtual reality (VR) technology on the cognitive functions (overall cognitive ability, executive function, short-term memory, and long-term memory) of people with mild cognitive impairment (MCI).…
The effect of mind–body exercise on memory in older adults: a systematic review and meta-analysis
Aging Clinical and Experimental Research20201 einflussreiche Zitationen
<h4>Objectives</h4>The current systematic review aims to examine the effect of mind-body exercise on different memory types in the elderly population.<h4>Methods</h4>Four literature databases (Pubmed, Cochrane library, Embase and Sinomed)…
The Effectiveness of Computerized Cognitive Training in Patients With Poststroke Cognitive Impairment: Systematic Review and Meta-Analysis
Journal of Medical Internet Research2025n=875
<h4>Background</h4>Stroke often triggers poststroke cognitive impairment (PSCI) within 6 months, impairing memory, attention, and executive function while exacerbating physical disabilities and mortality. Computerized cognitive training…
Cogmed cognitive training for working memory: a systematic review and meta-analysis.
Neuroscience2025
The interest in computerized training to enhance and rehabilitate cognitive functions is increasing. However, the efficacy of these methods, particularly in improving working memory (WM), remains debated. This systematic review aimed to…
Effects of chronic physical exercise on executive functions and episodic memory in clinical and healthy older adult populations: a systematic review and meta-analysis protocol
Systematic Reviews2024
<h4>Background</h4>Executive functions (EFs) and episodic memory are fundamental components of cognition that deteriorate with age and are crucial for independent living. While numerous reviews have explored the effect of exercise on these…
D3CNet: Long-term time series prediction based on dual decomposition and dual-channel hybrid network
Neural Networks2026
Recently, time series forecasting has been widely used in many fields. Time series feature extraction is a key research area, and the complexity and diversity of data make traditional feature decomposition methods difficult to adapt.…
Hierarchical memory-based deep reinforcement learning in simulated survival environments
Neural Networks2026
In complex decision-making tasks, agents often suffer from memory interference, inefficient exploration under sparse rewards, and limited adaptability in dynamic environments. While existing deep reinforcement learning (DRL) methods often…