PMID- 30190674
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20240330
IS  - 1662-5188 (Print)
IS  - 1662-5188 (Electronic)
IS  - 1662-5188 (Linking)
VI  - 12
DP  - 2018
TI  - A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain 
      Functionality in Healthy Aging and Alzheimer's Disease (AD).
PG  - 60
LID - 10.3389/fncom.2018.00060 [doi]
LID - 60
AB  - Neural oscillations were established with their association with 
      neurophysiological activities and the altered rhythmic patterns are believed to 
      be linked directly to the progression of cognitive decline. 
      Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal 
      activity due to excellent temporal and fair amount of spatial resolution. Single 
      channel, connectivity as well as brain network analysis using MEG data in resting 
      state and task-based experiments were analyzed from existing literature. Single 
      channel analysis studies reported a less complex, more regular and predictable 
      oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal 
      and occipital regions. Investigations on both functional connectivity (FC) and 
      effective (EC) connectivity analysis demonstrated a loss of connectivity in AD 
      compared to healthy control (HC) subjects found in higher frequency bands. It has 
      been reported from multiplex network of MEG study in AD in the affected regions 
      of hippocampus, posterior default mode network (DMN) and occipital areas, 
      however, conclusions cannot be drawn due to limited availability of clinical 
      literature. Potential utilization of high spatial resolution in MEG likely to 
      provide information related to in-depth brain functioning and underlying factors 
      responsible for changes in neuronal waves in AD. This review is a comprehensive 
      report to investigate diagnostic biomarkers for AD may be identified by from MEG 
      data. It is also important to note that MEG data can also be utilized for the 
      same pursuit in combination with other imaging modalities.
FAU - Mandal, Pravat K
AU  - Mandal PK
AD  - Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, 
      India.
AD  - Department of Neurodegeneration, Florey Institute of Neuroscience and Mental 
      Health, Melbourne, VIC, Australia.
FAU - Banerjee, Anwesha
AU  - Banerjee A
AD  - Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, 
      India.
FAU - Tripathi, Manjari
AU  - Tripathi M
AD  - Department of Neurology, All Indian Institute of Medical Sciences, New Delhi, 
      India.
FAU - Sharma, Ankita
AU  - Sharma A
AD  - Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, 
      India.
LA  - eng
PT  - Journal Article
PT  - Review
DEP - 20180823
PL  - Switzerland
TA  - Front Comput Neurosci
JT  - Frontiers in computational neuroscience
JID - 101477956
PMC - PMC6115612
OTO - NOTNLM
OT  - Alzheimer's disease
OT  - effective connectivity
OT  - functional connectivity
OT  - machine learning
OT  - magnetoencephalography
OT  - mild cognitive impairment
OT  - multimodal imaging
OT  - network analysis
EDAT- 2018/09/08 06:00
MHDA- 2018/09/08 06:01
PMCR- 2018/01/01
CRDT- 2018/09/08 06:00
PHST- 2018/03/17 00:00 [received]
PHST- 2018/07/09 00:00 [accepted]
PHST- 2018/09/08 06:00 [entrez]
PHST- 2018/09/08 06:00 [pubmed]
PHST- 2018/09/08 06:01 [medline]
PHST- 2018/01/01 00:00 [pmc-release]
AID - 10.3389/fncom.2018.00060 [doi]
PST - epublish
SO  - Front Comput Neurosci. 2018 Aug 23;12:60. doi: 10.3389/fncom.2018.00060. 
      eCollection 2018.