Complexity Analysis of the Default Mode Network Using Resting-State fMRI in Down Syndrome: Relationships Highlighted by a Neuropsychological Assessment

Abstract

Background: Studies on complexity indicators in the field of functional connectivity derived from resting-state fMRI (rs-fMRI) in Down syndrome (DS) samples and their possible relationship with cognitive functioning variables are rare. We analyze how some complexity indicators estimated in the subareas that constitute the default mode network (DMN) might be predictors of the neuropsychological outcomes evaluating Intelligence Quotient (IQ) and cognitive performance in persons with DS. Methods: Twenty-two DS people were assessed with the Kaufman Brief Test of Intelligence (KBIT) and Frontal Assessment Battery (FAB) tests, and fMRI signals were recorded in a resting state over a six-minute period. In addition, 22 controls, matched by age and sex, were evaluated with the same rs-fMRI procedure. Results: There was a significant difference in complexity indicators between groups: the control group showed less complexity than the DS group. Moreover, the DS group showed more variance in the complexity indicator distributions than the control group. In the DS group, significant and negative relationships were found between some of the complexity indicators in some of the DMN networks and the cognitive performance scores. Conclusions: The DS group is characterized by more complex DMN networks and exhibits an inverse relationship between complexity and cognitive performance based on the negative parameter estimates.

GnRH replacement rescues cognition in Down syndrome

“…Resting-state functional MRI (rs-fMRI) showed altered default mode network (DMN) in our DS cohort (Fig. 7O), as previously reported ( 46 , 47 ).…”

Brain signal complexity in adults with Down syndrome: Potential application in the detection of mild cognitive impairment

“…For instance, Hemmati et al (2013) studied EEG signals by means of fractal dimension in a sample of children with DS, and results indicated that patients with DS showed higher complexity values than controls. Such tendency was confirmed in fMRI studies focused on the estimation of complexity values in young adults ( Carbó-Carreté et al, 2020 ; Figueroa-Jimenez et al, 2021 ).…”

A role for GnRH in olfaction and cognition: Implications for veterinary medicine

“…Whether this could be due, at least in part, to an imbalance in the GnRH neuronal network is not known. However, a recent pilot study in human patients with Down syndrome (Manfredi-Lozano et al, 2022) who present with both altered learning capabilities and high anxiety shows that pulsatile GnRH therapy restoring the natural pattern of GnRH release improves cognitive performances by 20-30% and that this is accompanied by a decreased functional connectivity in the anxiety-related neuronal network linking the hippocampus to the amygdala to control values (Figueroa-Jimenez, Canete-Masse, et al, 2021;Figueroa-Jimenez, Carbo-Carrete, et al, 2021), as shown by resting-state functional magnetic resonance imaging (fMRI). It would be interesting to determine whether this ventral default mode network linking the hippocampus to the amygdala is also hyperactive in neutered dogs when compared to un-gonadectomized dogs using fMRI.…”

“…Of note, bilateral orchidectomy did not affect the rescue of olfaction or recognition memory by pulsatile GnRH, suggesting that the functional improvements observed were independent of the gonadotropic effects of GnRH, and could instead be due to the mobilization of cognitive reserves in male Ts65Dn mice (Manfredi‐Lozano et al, 2022). In a pilot open‐label study of 7 human patients with Down syndrome, pulsatile GnRH therapy using a LutrePulse pump, a safe treatment used for four decades in patients with CHH (Hoffman & Crowley Jr., 1982), for 6 months increased cognitive performances in these patients by 20–30% and restored functional connectivity in neuronal networks known to be altered in Down syndrome (Manfredi‐Lozano et al, 2022), approaching control values using resting‐state functional magnetic resonance imaging (Figueroa‐Jimenez, Canete‐Masse, et al, 2021; Figueroa‐Jimenez, Carbo‐Carrete, et al, 2021; Huang et al, 2015).…”