Next Article in Journal
Effortful Control and Prefrontal Cortex Functioning in Children with Autism Spectrum Disorder: An fNIRS Study
Next Article in Special Issue
Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory
Previous Article in Journal
Avenanthramide C Prevents Neuronal Apoptosis via PI3K/Akt/GSK3β Signaling Pathway Following Middle Cerebral Artery Occlusion
Previous Article in Special Issue
Random Forest Classification of Alcohol Use Disorder Using fMRI Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures
Article

Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease

1
Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
2
Dipartimento di Farmacia–Scienze del Farmaco, Università degli Studi di Bari, 70125 Bari, Italy
3
Center for Neurodegenerative Diseases and the Aging Brain, Università degli Studi di Bari at Pia Fondazione “Card. G. Panico”, 73039 Tricase, Italy
4
Department of Basic Medicine Neuroscience and Sense Organs, Università degli Studi di Bari, 70124 Bari, Italy
5
Pia Fondazione “Card. G. Panico”, 73039 Tricase, Italy
6
Dipartimento Interateneo di Fisica, Università degli Studi di Bari, 70126 Bari, Italy
7
Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari, 70126 Bari, Italy
*
Authors to whom correspondence should be addressed.
Both authors contributed equally to this work.
Brain Sci. 2020, 10(11), 879; https://doi.org/10.3390/brainsci10110879
Received: 8 October 2020 / Revised: 10 November 2020 / Accepted: 17 November 2020 / Published: 20 November 2020
(This article belongs to the Special Issue Recent Advances in Human Brain Connectivity)
Modeling disease progression through the cognitive scores has become an attractive challenge in the field of computational neuroscience due to its importance for early diagnosis of Alzheimer’s disease (AD). Several scores such as Alzheimer’s Disease Assessment Scale cognitive total score, Mini Mental State Exam score and Rey Auditory Verbal Learning Test provide a quantitative assessment of the cognitive conditions of the patients and are commonly used as objective criteria for clinical diagnosis of dementia and mild cognitive impairment (MCI). On the other hand, connectivity patterns extracted from diffusion tensor imaging (DTI) have been successfully used to classify AD and MCI subjects with machine learning algorithms proving their potential application in the clinical setting. In this work, we carried out a pilot study to investigate the strength of association between DTI structural connectivity of a mixed ADNI cohort and cognitive spectrum in AD. We developed a machine learning framework to find a generalized cognitive score that summarizes the different functional domains reflected by each cognitive clinical index and to identify the connectivity biomarkers more significantly associated with the score. The results indicate that the efficiency and the centrality of some regions can effectively track cognitive impairment in AD showing a significant correlation with the generalized cognitive score (R = 0.7). View Full-Text
Keywords: alzheimer’s disease; biomarker identification; machine learning; brain connectivity; diffusion tensor imaging alzheimer’s disease; biomarker identification; machine learning; brain connectivity; diffusion tensor imaging
Show Figures

Figure 1

MDPI and ACS Style

Lombardi, A.; Amoroso, N.; Diacono, D.; Monaco, A.; Logroscino, G.; De Blasi, R.; Bellotti, R.; Tangaro, S. Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease. Brain Sci. 2020, 10, 879. https://doi.org/10.3390/brainsci10110879

AMA Style

Lombardi A, Amoroso N, Diacono D, Monaco A, Logroscino G, De Blasi R, Bellotti R, Tangaro S. Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease. Brain Sciences. 2020; 10(11):879. https://doi.org/10.3390/brainsci10110879

Chicago/Turabian Style

Lombardi, Angela, Nicola Amoroso, Domenico Diacono, Alfonso Monaco, Giancarlo Logroscino, Roberto De Blasi, Roberto Bellotti, and Sabina Tangaro. 2020. "Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease" Brain Sciences 10, no. 11: 879. https://doi.org/10.3390/brainsci10110879

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop