1910s' brains revisited. Cortical complexity in early 20th century patients with intellectual disability or with dementia praecox

Sandu, Anca-Larisa; Martinot, M-L Paillère; Artiges, Éric; Martinot, Jean‐Luc

doi:10.1111/acps.12243

Cited by 10 publications

(7 citation statements)

References 50 publications

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“…More importantly, several studies have found that information conveyed by FD is additional to that provided by other conventional structural measures (Free et al, 1996 ; King et al, 2009 ; King et al, 2010 ; Lu, 2020 ; Madan & Kensinger, 2016 ; Madan & Kensinger, 2018 ). FD can detect changes in the structural complexity of the cerebral cortex in healthy ageing (Krohn et al, 2019 ; Liu et al, 2020 ; Madan & Kensinger, 2016 ; Marzi et al, 2020 ; Sandu, Staff, et al, 2014 ), neurological disorders (King et al, 2016 ; Ruiz de Miras et al, 2017 ; Sandu, Martinot, et al, 2014 ; Sheelakumari et al, 2018 ) and neuropsychological disorders (Narr et al, 2004 ; Nenadic et al, 2014 ; Nickel et al, 2019 ; Sandu, Rasmussen Jr., et al, 2008 ; Sandu, Specht, et al, 2008 ). Normal brain morphological alterations associated with ageing do not occur homogeneously and are region‐specific, thus region‐specific FD analysis might serve as a biomarker to track therapeutic interventions targeted at disorders associated with accelerated atrophy such as dementia and disease progression such as spinocerebellar ataxia (Marzi et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Age‐associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Nazlee

Waiter

Sandu

2022

Human Brain Mapping

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Cortical morphology changes with ageing and age‐related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age‐related sex differences (3332 males, age ranged 45–79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age‐affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age‐by‐sex‐by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age‐related sex and asymmetry differences that can aid in the future development of sex‐specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

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Section: Introductionmentioning

confidence: 99%

Age‐associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Nazlee

Waiter

Sandu

2022

Human Brain Mapping

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“…Fractal analysis, gyrification index and curvedness have been proposed to quantify the structural complexity of the cortex and select abnormalities in the cortical structure in patients with movement disorders [ 19 – 31 ]. Fractal analysis has shown decreased cortical complexity in patients with mental disorders comparing to normal controls [ 32 – 35 ]. In addition, fractal analysis has been used to investigate relationship between cortical complexity and intelligence as well as cognitive ability [ 36 – 38 ].…”

Section: Introductionmentioning

confidence: 99%

Change in the Cortical Complexity of Spinocerebellar Ataxia Type 3 Appears Earlier than Clinical Symptoms

et al. 2015

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Patients with spinocerebellar ataxia type 3 (SCA3) have exhibited cerebral cortical involvement and various mental deficits in previous studies. Clinically, conventional measurements, such as the Mini-Mental State Examination (MMSE) and electroencephalography (EEG), are insensitive to cerebral cortical involvement and mental deficits associated with SCA3, particularly at the early stage of the disease. We applied a three-dimensional fractal dimension (3D-FD) method, which can be used to quantify the shape complexity of cortical folding, in assessing cortical degeneration. We evaluated 48 genetically confirmed SCA3 patients by employing clinical scales and magnetic resonance imaging and using 50 healthy participants as a control group. According to the Scale for the Assessment and Rating of Ataxia (SARA), the SCA3 patients were diagnosed with cortical dysfunction in the cerebellar cortex; however, no significant difference in the cerebral cortex was observed according to the patients’ MMSE ratings. Using the 3D-FD method, we determined that cortical involvement was more extensive than involvement of traditional olivopontocerebellar regions and the corticocerebellar system. Moreover, the significant correlation between decreased 3D-FD values and disease duration may indicate atrophy of the cerebellar cortex and cerebral cortex in SCA3 patients. The change of the cerebral complexity in the SCA3 patients can be detected throughout the disease duration, especially it becomes substantial at the late stage of the disease. Furthermore, we determined that atrophy of the cerebral cortex may occur earlier than changes in MMSE scores and EEG signals.

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“…These studies found higher cortical complexity in adolescents and less complexity in adulthood (Farahibozorg et al, 2014) with the lowest values of FD for people in the eighth and ninth decades. FD has also been investigated in schizophrenia (Narr et al, 2004;Sandu et al, 2008b;Yotter et al, 2011), manic depression (Bullmore et al, 1994), obsessive-compulsive disorder (Ha et al, 2005), Alzheimer's disease (King et al, 2010), intellectual disability (Sandu et al, 2014), epilepsy (Free et al, 1996), Williams syndrome and dyslexia (Sandu et al, 2008a). Cortical complexity measured by FD is also positively correlated with the number of years of education and the intelligence quotient (Im et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Structural brain complexity and cognitive decline in late life — A longitudinal study in the Aberdeen 1936 Birth Cohort

et al. 2014

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Brain morphology and cognitive ability change with age. Gray and white matter volumes decrease markedly by the 7th decade of life when cognitive decreases first become readily detectable. As a consequence, the shape complexity of the cortical mantle may also change. The purposes of this study are to examine changes over a five year period in brain structural complexity in late life, and to investigate cognitive correlates of any changes. Brain magnetic resonance images at 1.5 Tesla were acquired from the Aberdeen 1936 Birth Cohort at about ages 68 years (243 participants) and 73 years (148 participants returned). Measures of brain complexity were extracted using Fractal Dimension (FD) and calculated using the box-counting method. White matter complexity, brain volumes and cognitive performance were measured at both 68 and 73 years. Childhood ability was measured at age 11 using the Moray House Test. FD and brain volume decrease significantly from age 68 to 73 years. Using a multilevel linear modeling approach, we conclude that individual decreases in late life white matter complexity are not associated with differences in executive function but are linked to information processing speed, auditory-verbal learning, and reasoning in specific models-with adjustment for childhood mental ability. A significant association was found after adjustment for age, brain volume and childhood mental ability. Complexity of white matter is associated with higher fluid cognitive ability and, in a longitudinal study, predicts retention of cognitive ability within late life.

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1910s' brains revisited. Cortical complexity in early 20th century patients with intellectual disability or with dementia praecox

Cited by 10 publications

References 50 publications

Age‐associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Age‐associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Change in the Cortical Complexity of Spinocerebellar Ataxia Type 3 Appears Earlier than Clinical Symptoms

Structural brain complexity and cognitive decline in late life — A longitudinal study in the Aberdeen 1936 Birth Cohort

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