Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cognitive Learning

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...

Cognitive Development During Adulthood

Cognitive Development During Adulthood

Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...

Dementia

Dementia

Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

Language and Cognition

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

Alzheimer's Disease: Overview

Alzheimer's Disease: Overview

Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Promoting contraceptive use among unmarried female migrants in one factory in Shanghai: a pilot workplace intervention.

BMC health services research·2007

Same author

Apoptosis related protein 3, an ATRA-upregulated membrane protein arrests the cell cycle at G1/S phase by decreasing the expression of cyclin D1.

Biochemical and biophysical research communications·2007

Same author

Efficient one-pot synthesis of highly substituted pyridin-2(1H)-ones via the Vilsmeier-Haack reaction of 1-acetyl,1-carbamoyl cyclopropanes.

Organic letters·2007

Same author

Effects of Andrographitis Paniculata extracts on the expression of CD40 in endothelial cells.

Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban·2007

Same author

Theoretical and experimental investigations on the size of alginate microspheres prepared by dropping and spraying.

Journal of microencapsulation·2007

Same author

Beneficial effects of losartan on vascular injury induced by advanced glycosylation end products and their receptors in spontaneous hypertension rats.

Molecular and cellular biochemistry·2007

Search research articles

Related Experiment Video

Updated: Feb 22, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

Jie Zhang¹, Qingyang Li¹, Richard J Caselli²

¹School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ.,Tempe, AZ.

Information Processing in Medical Imaging : Proceedings of the ... Conference

|September 26, 2017

Summary

This summary is machine-generated.

This study introduces a new unsupervised learning method, Multi-Source Multi-Target Dictionary Learning (MMDL), to identify Alzheimer's Disease (AD) biomarkers. MMDL improves prediction accuracy and efficiency for early AD detection using brain imaging data.

Keywords:

Alzheimer’s Disease Dictionary Learning Multi-task

More Related Videos

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Dual-Task Stroop Paradigm for Detecting Cognitive Deficits in High-Functioning Stroke Patients

Dual-Task Stroop Paradigm for Detecting Cognitive Deficits in High-Functioning Stroke Patients

Published on: December 16, 2022

Related Experiment Videos

Last Updated: Feb 22, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Dual-Task Stroop Paradigm for Detecting Cognitive Deficits in High-Functioning Stroke Patients

Dual-Task Stroop Paradigm for Detecting Cognitive Deficits in High-Functioning Stroke Patients

Published on: December 16, 2022

Area of Science:

Biomedical Informatics
Computer Vision
Neuroscience

Background:

Alzheimer's Disease (AD) is the leading cause of dementia, necessitating early detection through biomarkers.
Current multi-task sparse feature learning methods often rely on supervised approaches, facing limitations with insufficient data or missing labels.
Identifying pre-symptomatic AD is crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

To develop an unsupervised framework for multi-task sparse feature learning to address limitations in existing supervised methods.
To propose and evaluate a novel two-stage algorithm, Multi-Source Multi-Target Dictionary Learning (MMDL), for biomarker identification in Alzheimer's Disease.
To enhance the generalization performance and prediction accuracy in identifying Alzheimer's Disease biomarkers.

Main Methods:

Developed a two-stage unsupervised framework: Multi-Source Multi-Target Dictionary Learning (MMDL).
Stage 1: Multi-source dictionary learning to leverage common and individual sparse features across different time points.
Stage 2: Multi-task learning approach to effectively handle missing label information, supported by theoretical analysis.

Main Results:

Empirical studies on a large longitudinal brain imaging dataset (N=3970) involving 2 sources and 5 targets.
MMDL demonstrated improved prediction accuracy compared to state-of-the-art algorithms.
MMDL exhibited enhanced speed efficiency in processing and analyzing the data.

Conclusions:

The proposed MMDL algorithm offers a robust unsupervised solution for multi-task sparse feature learning in biomedical informatics.
MMDL effectively addresses challenges of insufficient features and missing labels, crucial for Alzheimer's Disease biomarker discovery.
The findings suggest MMDL's potential for early and accurate identification of Alzheimer's Disease, enabling timely interventions.