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Relationship between episodic memory and volume of the brain regions of two functional cortical memory systems in multiple sclerosis

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Background/objectiveTwo functional networks are proposed as neuronal support for the complex processes of memory: the anterior temporal and the medial posterior systems. We examined the atrophy of hippocampus (HC) and… Click to show full abstract

Background/objectiveTwo functional networks are proposed as neuronal support for the complex processes of memory: the anterior temporal and the medial posterior systems. We examined the atrophy of hippocampus (HC) and of those areas constituting the two functional memory systems in multiple sclerosis (MS) patients with low disability.MethodsEpisodic memory (EM) was assessed in 88 relapsing MS patients and in 40 healthy controls using Wechsler Memory Scale III (Spanish adaptation). FreeSurfer software was used to calculate normalized volume of total cortex, grey matter, white matter, subcortical grey matter (thalamus and striatum), HC and both the anterior temporal (entorhinal, ventral temporopolar, lateral orbitofrontal, amygdala) and posterior medial systems (thalamus, parahippocampal, posterior cingulate, precuneus, lateral parietal and medial prefrontal). Linear regression analysis was used to identify predictors of memory performance.ResultsTotal grey matter and cortex volumes correlated with all subtypes of EM, and the precuneus volume correlated with overall, immediate and delayed memories. Univariant regression analysis identified an association between the volumes of the posterior medial memory network regions and EM scores. The volume of the left precuneus area was the unique and independent predictor for all EM subtypes except for visual memory, for which left HC volume was also an independent predictor.ConclusionLeft precuneus volume was the best predictor of memory in relapsing MS patients with low disability and mild deficits in EM.

Keywords: volume; memory systems; two functional; multiple sclerosis; systems multiple; memory

Journal Title: Journal of Neurology
Year Published: 2018

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