Complexity of Frontal Cortex fNIRS Can Support Alzheimer Disease Diagnosis in Memory and Visuo-Spatial Tests

Abstract

Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer’s Disease (AD) and they can be assessed at early stages employing clinical tests. However, performance in a single test is generally not indicative of AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests in an ecological setting to support diagnosis. Indeed, neuroimaging should not alter clinical practice allowing free doctor-patient interaction. However, block-designed paradigms, necessary for standard functional neuroimaging analysis, require tests adaptation. Novel signal analysis procedures (e.g., signal complexity evaluation) may be useful to establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS complexity (through Sample Entropy metric) in frontal cortex of early AD and controls during three tests that assess visuo-spatial and short-term-memory abilities (Clock Drawing Test, Digit Span Test, Corsi Block Tapping Test). A channel-based analysis of fNIRS complexity during the tests revealed AD-induced changes. Importantly, a multivariate analysis of fNIRS complexity provided good specificity and sensitivity to AD. This outcome was compared to cognitive tests performances that were predictive of AD in only one test. Our results demonstrated the capabilities of fNIRS and complexity metric to support early AD diagnosis.

Application of functional near-infrared spectroscopy in the healthcare industry: A review

“…An entropy-based fNIRS signal complexity analysis demonstrated that the digit span task (DST) could help classify AD. 244 A time-series analysis revealed that the reduction or decline in HbO levels becomes steeper when the intensity of AD progresses. 236…”

“…The clock drawing test (CDT) scores can adequately be used to di®erentiate between healthy individuals and AD patients; however, the entropy analysis conducted on fNIRS recordings while the subjects were performing the CDT resulted in signi¯cant di®erences between the results of AD patients and healthy subjects. 244…”

“…Compared to the CDT and DST results, the results of the Corsi block-tapping test were the most effective in di®erentiating AD patients from healthy subjects via entropy analysis. 244 9.6. Driving task AD patients exhibited lower HbO values than those of healthy individuals, and the act of applying the brake during the task and HbO changes were negatively related while these were positively related in healthy persons.…”

Multiscale Entropy Approaches and Their Applications

“…For an early Alzheimer’s disease (AD) diagnosis, Perpetuini et al used sample entropy and the MSE of functional near infrared spectroscopy (fNIRS) in the frontal cortex of early AD and healthy controls during three tests that were used to assess visuo-spatial and short-term-memory abilities [ 19 ]. A multivariate analysis revealed promising results (good specificity and sensitivity) in the capabilities of fNIRS and complexity for an early diagnosis.…”

fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks

“…Furthermore, Jin et al investigated permutation entropy to analyze differences in experts and novices solving science problems [ 20 ]. Studying frontal cortex fNIRS signals, SampEn was suggested as a biomarker for Alzheimer’s disease diagnosis [ 21 , 22 , 23 ], and Angsuwatanakul et al [ 24 ] investigated the effects of working memory experiments on SampEn estimated from fNIRS series. Also, though applied as an information theoretic approach to investigate linear effects in fNIRS rather than analyze topological entropy in phase space, differential entropy has been investigated in Keshmeri et al as a biomarker that preserves variational information in the assessment of working memory [ 25 , 26 ].…”