Evidence map›Paper›PMID 35992607›Full record

ArticleFrontiers in aging neuroscience2022

Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases.

Anita Monteverdi, Fulvia Palesi, Alfredo Costa, Paolo Vitali, Anna Pichiecchio, Matteo Cotta Ramusino, Sara Bernini, Viktor Jirsa, Claudia A M Gandini Wheeler-Kingshott, Egidio D'Angelo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 25 citations in OpenAlex.

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  14. Abnormal cerebellum connectivity patterns related to motor subtypes of Parkinson's disease.Journal of neural transmission (Vienna, Austria : 1996) · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

Anita MonteverdiBrain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.
Fulvia PalesiDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Alfredo CostaDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Paolo VitaliDepartment of Radiology, IRCCS Policlinico San Donato, Milan, Italy.
Anna PichiecchioDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Matteo Cotta RamusinoDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Sara BerniniDementia Research Center, IRCCS Mondino Foundation, Pavia, Italy.
Viktor JirsaInstitut de Neurosciences des Systèmes, INSERM, INS, Aix-Marseille University, Marseille, France.
Claudia A M Gandini Wheeler-KingshottBrain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.
Egidio D'AngeloBrain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.
University of Pavia · ITFondazione Istituto Neurologico Nazionale Casimiro Mondino · ITInserm · FRUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients' excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients' cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer's Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients' conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

Indexed as

Alzheimer’s DiseaseAmyotrophic Lateral Sclerosisbrain dynamicsconnectivityexcitatory/inhibitory balanceFrontotemporal DementiaMRI

Identifiers

PMID35992607
PMCPMC9391060
OpenAlexW4289884060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.