Role of artificial intelligence techniques and neuroimaging modalities in detection of Parkinson's disease: a systematic review

N Aggarwal, BS Saini, S Gupta - Cognitive Computation, 2024 - Springer
Abstract Parkinson's disease (PD), a neurodegenerative disorder, is caused due to the lack
of dopamine neurotransmitters throughout the substantia nigra. Its diagnosis in the earlier …

Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture

E Hoekzema, H van Steenbergen, M Straathof… - Nature …, 2022 - nature.com
While animal studies have demonstrated a unique reproduction-related neuroplasticity, little
is known on the effects of pregnancy on the human brain. Here we investigated whether …

Evaluation of functional MRI-based human brain parcellation: a review

P Moghimi, AT Dang, Q Do, TI Netoff… - Journal of …, 2022 - journals.physiology.org
Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can
significantly affect the outcome of the analysis. In recent years, several novel approaches for …

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning

A Alorf, MUG Khan - Computers in Biology and Medicine, 2022 - Elsevier
Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive
abilities. Recently, various neuroimaging modalities and machine learning methods have …

[HTML][HTML] Amyloid induced hyperexcitability in default mode network drives medial temporal hyperactivity and early tau accumulation

J Giorgio, JN Adams, A Maass, WJ Jagust… - Neuron, 2024 - cell.com
In early Alzheimer's disease (AD) β-amyloid (Aβ) deposits throughout association cortex and
tau appears in the entorhinal cortex (EC). Why these initially appear in disparate locations is …

Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder

Y Du, Z Fu, Y Xing, D Lin, G Pearlson… - Communications …, 2021 - nature.com
Schizophrenia (SZ) and autism spectrum disorder (ASD) share considerable clinical
features and intertwined historical roots. It is greatly needed to explore their similarities and …

Preparing fMRI data for statistical analysis

A Nieto-Castanon - arXiv preprint arXiv:2210.13564, 2022 - arxiv.org
This chapter describes several procedures used to prepare fMRI data for statistical analyses.
It includes the description of common preprocessing steps, such as spatial realignment …

OViTAD: Optimized vision transformer to predict various stages of Alzheimer's disease using resting-state fMRI and structural MRI data

S Sarraf, A Sarraf, DD DeSouza, JAE Anderson… - Brain Sciences, 2023 - mdpi.com
Advances in applied machine learning techniques for neuroimaging have encouraged
scientists to implement models to diagnose brain disorders such as Alzheimer's disease at …

[HTML][HTML] Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease

J Giorgio, SM Landau, WJ Jagust, P Tino, Z Kourtzi… - NeuroImage: Clinical, 2020 - Elsevier
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes
from normal cognition to mild cognitive impairment (MCI) and progression to dementia …

Surface-based analysis increases the specificity of cortical activation patterns and connectivity results

S Brodoehl, C Gaser, R Dahnke, OW Witte… - Scientific reports, 2020 - nature.com
Spatial smoothing of functional magnetic resonance imaging (fMRI) data can be performed
on volumetric images and on the extracted surface of the brain. Smoothing on the unfolded …