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 Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists

Cognitive Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists

Cognitive enhancers, also known as "smart drugs," are substances used to enhance memory, mental alertness, and concentration. These can be natural or synthetic and improve cognition in conditions like Alzheimer's disease (AD) and other neurodegenerative diseases. Some common examples include caffeine, amphetamines, methylphenidate, modafinil, arecoline, donepezil, vortioxetine, and piracetam. These enhancers work on the principle of synaptic plasticity and altered circuit function.

You might also read

Related Articles

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

Sort by

Same author

Landscape of copy number variants in Spanish people with dementia.

NPJ genomic medicine·2026

Same author

Preserved gaze cueing in Parkinson's disease: Differential temporal modulation of social and non-social attentional orienting.

Behavioural brain research·2026

Same author

Informing drivers about events and their location in Variable Message Signs: effects of words versus pictograms.

Frontiers in psychology·2026

Same author

The Deese/Roediger-McDermott (DRM) illusion in short-term memory: Opposite effects of retention interval on true and false recognition.

Memory & cognition·2026

Same author

Endogenous Theta as a Function of Task Load and Working Memory Capacity: Revisiting the Role of Slower Frequencies in Theta-Gamma Coupling.

Journal of cognitive neuroscience·2026

Same author

Assessment of Language Impairments Towards Identifying Markers for Early Diagnosis of Pathological Cognitive Decline.

Behavioral sciences (Basel, Switzerland)·2026

Search research articles

Related Experiment Video

Updated: May 5, 2026

Author Spotlight: Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Author Spotlight: Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Published on: April 21, 2023

Phasic and tonic alerting in mild cognitive impairment: A preliminary study.

Diana Martella¹, Salvadora Manzanares², Guillermo Campoy³

¹Basque Center on Cognition, Brain and Language, Paseo Miketelegi, 20009 Donostia-San Sebastián, Spain.

Experimental Gerontology

|November 21, 2013

Summary

Mild cognitive impairment (MCI) patients show impaired alerting networks, particularly vigilance. Enhancing alerting improves executive network function, suggesting attention deficits contribute to MCI.

Keywords:

Attention Network Test Mild cognitive impairment Sensitivity Tonic alerting Vigilance

More Related Videos

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

Transcranial Pulse Stimulation for Alzheimer's Patients

Transcranial Pulse Stimulation for Alzheimer's Patients

Published on: April 4, 2025

Related Experiment Videos

Last Updated: May 5, 2026

Author Spotlight: Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Author Spotlight: Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Published on: April 21, 2023

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

Transcranial Pulse Stimulation for Alzheimer's Patients

Transcranial Pulse Stimulation for Alzheimer's Patients

Published on: April 4, 2025

Area of Science:

Cognitive Neuroscience
Neuropsychology
Gerontology

Background:

Mild cognitive impairment (MCI) is a transitional stage between normal aging and dementia.
Attentional network dysfunction is increasingly recognized as a potential contributor to cognitive decline in MCI.
Posner's cognitive neuroscience framework provides a model for understanding attentional processes.

Purpose of the Study:

To assess attentional network functioning in different subtypes of MCI patients.
To investigate the specific deficits within the alerting, orienting, and executive networks in MCI.
To explore the role of vigilance and phasic alerting in MCI attentional performance.

Main Methods:

Utilized the Attention Network Test (ANTI-V) to evaluate orienting, executive, and alerting networks.
Included 20 MCI patients (amnestic, non-amnestic, multiple-domain) and 18 healthy controls (HC).
Measured tonic alerting (vigilance) and the impact of phasic alerting (warning tone) on network performance.

Main Results:

All MCI subtypes demonstrated a selective impairment in the tonic component of alerting (vigilance), indicated by decreased d' sensitivity.
MCI patients' executive network performance improved to healthy control levels when facilitated by phasic alerting.
These findings highlight a specific deficit in endogenous alerting within the attentional system of MCI patients.

Conclusions:

A core attentional deficit, particularly in the endogenous component of alerting, significantly contributes to the cognitive and behavioral impairments observed in MCI.
Targeting and improving alerting network function may be a potential therapeutic strategy for MCI.
This study underscores the importance of attentional network analysis in understanding the pathophysiology of MCI.