The Auditory Afferent Pathway as a Clinical Marker of Alzheimer’s Disease

2021 ◽  
pp. 1-7
Author(s):  
Kaneez Fatima Shad ◽  
Wissam Soubra ◽  
Dennis John Cordato

Brain stem neural tracts and nuclei may be disturbed prior to observable neuronal atrophy in AD. In this perspective, we discuss the notion of functional deficits presenting prior to structural abnormalities in Alzheimer’s disease (AD). Imaging of inferior colliculi using magnetic resonance spectroscopy (MRS) shows significant decrease in the neuronal markers, N acetyl aspartate/creatine ratio and increase in the glial marker myo-Inositol, in subjects with Mini-Mental State Examination scores greater than 24 and with no signs of atrophy in their MRI of the medial temporal lobe. Abnormalities in components of the auditory event-related potentials (ERPs) are described in cognitive impairment including AD. We observed a significant decrease in amplitude and increase in latency during the first 10 ms of auditory evoked potentials measured on electroencephalography (EEG) indicating slow auditory response of the brainstem. EEG spectral power recorded at the cortex is also associated with neural activity at the level of the inferior colliculi. We postulate that a functional examination of auditory afferent pathways, using non-invasive techniques, such as MRS, brain stem auditory evoked potentials (BAEPs) and ERPs may improve diagnostic accuracy of AD. Functional changes precede structural changes and it is important to further understand the relationship between biochemical and electrophysiological measures such as MRS, BAEPs and EEG.

2015 ◽  
Vol 11 (7S_Part_12) ◽  
pp. P559-P559
Author(s):  
Claudio Babiloni ◽  
Claudio Del Percio ◽  
Nicola Marzano ◽  
Susanna Cordone ◽  
Giuseppe Noce ◽  
...  

Author(s):  
B.L. Brown ◽  
S.B. Hendrix ◽  
M. Cecchi ◽  
J.M. Scott ◽  
J.W. Silcox ◽  
...  

Event-related potentials (ERPs) are a physiological measure of cognitive function that have shown diagnostic and prognostic utility in Alzheimer’s disease (AD). In this study, we used a novel eigenvector-based technique to better understand brain electrophysiological differences between subjects with mild AD and healthy controls (HC). Using ERPs from 75 subjects with mild AD and 95 HC, we first calculated cognitive task eigenvectors within each subject from three conditions and then calculated second-order eigenvector components to compare the AD group to the HC group. A MANOVA of the three second-level components discriminated between AD and HC multivariately (Wilks’ lambda=.4297, p<0.0001, R2 = .5703), and also on each of the three components univariately (all 3 p-values<0.0001). The eigenvector-based technique used in this study accurately discriminated between the mild AD group and HC. As such, this analysis method adds to our understanding of the differences in ERP signal between AD and HC, and could provide a sensitive biomarker for diagnosis and monitoring of AD progression.


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