Memory profiling with paired associate learning in Alzheimer's disease, mild cognitive impairment, and healthy aging.

2008 ◽  
Vol 22 (6) ◽  
pp. 718-728 ◽  
Author(s):  
K. E. Pike ◽  
C. C. Rowe ◽  
S. A. Moss ◽  
G. Savage
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Aging ◽  
Paired Associate ◽  
Paired Associate Learning ◽  
Associate Learning

scholarly journals Effects of nicotinic cholinergic system manipulations on paired-associate learning (PAL) in mice

SURG Journal ◽  
2014 ◽  
Vol 7 (1) ◽  
pp. 33-46
Author(s):  
Melissa Milanovic
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Task Performance ◽  
Nicotinic Receptor ◽  
Cholinergic System ◽  
Paired Associate ◽  
Paired Associate Learning ◽  
Associate Learning ◽  
Future Drug

Rationale: The ability to perform on the Cambridge Neuropsychological Test Automated Battery touchscreen paired-associate learning (PAL) test is predictive of Alzheimer’s disease and Mild Cognitive Impairment. Recently, an automated computer touchscreen PAL task for mice has been developed. Pharmacological validation of this task is warranted to establish it as a useful tool in future drug discovery pertaining to Alzheimer’s disease and Mild Cognitive Impairment. Objectives: This investigation provides a systematic analysis of nicotinic involvement within the PAL task for mice. Particularly, the effects of systemic administration of nicotinic cholinergic agents (agonist and antagonist) on PAL task performance in C57BL/6 mice were investigated. This was done to detect whether bidirectional modification of performance is consequent upon these manipulations. Methods: Upon acquiring the PAL task, nicotine (nicotinic receptor agonist; 0.1, 0.5, and 1.0 mg/kg) and mecamylamine (nicotinic receptor antagonist; 0.3, 1.0, and 3.0 mg/kg) were administered intraperitoneally to the mice in a within-subjects design, prior to daily sessions in the PAL task. Results: Nicotine did not have any significant effect on PAL performance improvement at any doses. However, mecamylamine did increase perseverative responding and reaction time in the mice. Such impairment effects are interpreted as being attentional in nature. Conclusion: This investigation indicates that mice indeed acquire the rodent PAL task, deeming it a valuable tool for future drug discovery. Further, the nicotinic cholinergic system appears to be implicated in PAL task performance, with greater effects seen with deactivation rather than activation of the system, and with these effects appearing to be of an attentional nature. Keywords: paired-associate learning (PAL); Alzheimer’s disease; nicotinic cholingeric system; touchscreen

scholarly journals A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

2019 ◽  
Author(s):  
FR Farina ◽  
DD Emek-Savaş ◽  
L Rueda-Delgado ◽  
R Boyle ◽  
H Kiiski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Healthy Aging ◽  
Neurodegenerative Disorder ◽  
Low Cost ◽  
Structural Mri ◽  
Lower Accuracy

AbstractAlzheimer’s disease (AD) is a neurodegenerative disorder characterised by severe cognitive decline and loss of autonomy. AD is the leading cause of dementia. AD is preceded by mild cognitive impairment (MCI). By 2050, 68% of new dementia cases will occur in low- and middle-income countries. In the absence of objective biomarkers, psychological assessments are typically used to diagnose MCI and AD. However, these require specialist training and rely on subjective judgements. The need for low-cost, accessible and objective tools to aid AD and MCI diagnosis is therefore crucial. Electroencephalography (EEG) has potential as one such tool: it is relatively inexpensive (cf. magnetic resonance imaging; MRI) and is portable. In this study, we collected resting state EEG, structural MRI and rich neuropsychological data from older adults (55+ years) with AD, with MCI and from healthy controls (n~60 per group). Our goal was to evaluate the utility of EEG, relative to MRI, for the classification of MCI and AD. We also assessed the performance of combined EEG and behavioural (Mini-Mental State Examination; MMSE) and structural MRI classification models. Resting state EEG classified AD and HC participants with moderate accuracy (AROC=0.76), with lower accuracy when distinguishing MCI from HC participants (AROC=0.67). The addition of EEG data to MMSE scores had no additional value compared to MMSE alone. Structural MRI out-performed EEG (AD vs HC, AD vs MCI: AROCs=1.00; HC vs MCI: AROC=0.73). Resting state EEG does not appear to be a suitable tool for classifying AD. However, EEG classification accuracy was comparable to structural MRI when distinguishing MCI from healthy aging, although neither were sufficiently accurate to have clinical utility. This is the first direct comparison of EEG and MRI as classification tools in AD and MCI participants.

O1-02-06 Deactivation in healthy aging, mild cognitive impairment and Alzheimer's disease

2004 ◽  
Vol 25 ◽  
pp. S13
Author(s):  
Frederik Barkhof ◽  
Serge A. Rombouts ◽  
Rutger Goekoop ◽  
Philip Scheltens
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Aging
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