Gray Matter Volume in Left Rostral Middle Frontal and Left Cerebellar Cortices Predicts Frontal Executive Performance in Alcoholic Subjects

Nakamura-Palacios, Ester Miyuki; Souza, Rodrigo Stênio Moll de; Zago-Gomes, Maria P.; Melo, Adriana Maria Fonseca de; Braga, Flávia; Kubo, Tadeu Takao Almodovar; Gasparetto, Emerson L.

doi:10.1111/acer.12308

Cited by 31 publications

(30 citation statements)

References 43 publications

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“…Our results for the cortical thickness association were obtained in a large sample of young, largely nonsmoking drinkers. This male-only alcoholism risk sample is very different from the studies of older alcoholic subjects recently reported in several articles (Momenan et al, 2012;Nakamura-Palacios et al, 2014;Pennington et al, 2015). The number of reported morphometric differences found tended to involve the frontal lobe, with the effects considerably weaker in men only and after accounting for substance use.…”

Section: Imaging Data Applicationcontrasting

confidence: 67%

Brain connectivity-informed regularization methods for regression

Karas

Brzyski

Džemidžić

et al. 2017

Preprint

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A challenging problem arising in brain imaging research is principled incorporation of information from different imaging modalities. Frequently each modality is analyzed separately using, for instance, dimensionality reduction techniques which result in a loss of mutual information. We propose a novel regularization method to estimate the association between the brain structure features and a scalar outcome within the linear regression framework. Our regularization technique provides a principled approach to utilizing external information arising from the structural brain connectivity to inform the estimation of the regression coefficients. Our proposal extends the classical Tikhonov regularization framework by defining a penalty term based on the structural connectivity-derived Laplacian matrix. In the work presented, we address both theoretical and computational issues. The approach is illustrated using simulated data and compared with other penalized regression methods. Finally, we apply our regularization method to study the associations between the alcoholism phenotypes and brain cortical thickness using a diffusion tensor imaging (DTI) derived measure of structural connectivity.

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Section: Imaging Data Applicationcontrasting

confidence: 67%

Brain connectivity-informed regularization methods for regression

Karas

Brzyski

Džemidžić

et al. 2017

Preprint

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“…found that FAB scores were linked to decreased regional cerebral blood flow in the parietotemporal lobe, posterior cingulate, and frontal regions. Frontal dysfunction measured by the FAB test in diverse pathologies such as stroke (Kopp et al , ), alcohol dependence (Nakamura‐Palacios et al , ), and PSP (Piatella et al , ) was largely localized in frontal regions, although a decline in FAB scores cannot be imputed to specific lesions in frontal cortex except for the performance of the verbal fluency subtest (Chapados and Petrides, ). More recently, FAB scores were also correlated with a reduced connectivity in the precuneus in subjects affected by idiopathic normal pressure hydrocephalus (Khoo et al , ).…”

Section: Resultsmentioning

confidence: 99%

“…In general, the selected 32 studies are focused on testing the diagnostic congruence of the clinical and neuroanatomical aspects of the FAB, of which 17 studies were aimed at identifying the brain regions or the neural substrates involved in EFs measured by the FAB (Matsui et al, 2006;Guedj et al, 2008;Yoshida et al, 2009;Gordon et al, 2010;Kume et al, 2011;Nagata et al, 2011;Oshima et al, 2012;Chapados and Petrides, 2013;Frota et al, 2013;Kopp et al, 2013;Le Pira et al, 2014;Nakamura-Palacios et al, 2014;Brugger et al, 2015;Lee et al, 2015;Pellechia et al, 2015;Piatella et al, 2015;Khoo et al, 2016), and 15 studies at verifying that the FAB was an appropiate tool for the differential diagnosis in neurological diseases (Slachevsky et al, 2004;Lipton et al, 2005;Paviour et al, 2005;Castiglioni et al, 2006;Oguro et al, 2006;Fukui et al, 2009;Mendez et al, 2009;Woodward et al, 2010;Yamao et al, 2011;Boban et al, 2012;Biundo et al, 2013;Kawai et al, 2013;Krudop et al, 2015;Sitek et al, 2015;Stamelou et al, 2015). Table 1 displays the main characteristics and results from the neuroimaging studies.…”

Section: Resultsmentioning

confidence: 99%

The frontal assessment battery in clinical practice: a systematic review

Hurtado-Pomares

Terol-Cantero

Sánchez-Pérez

et al. 2017

Int J Geriat Psychiatry

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“…24 However, previous studies of the neural correlates of FAB reported the involvement of the frontal, temporal, parietal, and cerebellar lobes. [25][26][27][28][29] As such, FAB, as well as CLOX1, may be related to both the frontal and parietal lobes. In the current study, performance on FAB was also related to the right lateral frontal lobe.…”

Section: Discussionmentioning

confidence: 99%

Differences in the neural correlates of frontal lobe tests

et al. 2018

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Background: The Executive Interview (EXIT25), the executive clock-drawing task (CLOX1), and the Frontal Assessment Battery (FAB) are used to assess executive function at the bedside. These tests assess distinct psychometric properties. The aim of this study was to examine differences in the neural correlates of the EXIT25, CLOX1, and FAB based on magnetic resonance imaging. Methods: Fifty-eight subjects (30 with Alzheimer's disease, 10 with mild cognitive impairment, and 18 healthy controls) participated in this study. Multiple regression analyses were performed to examine the brain regions correlated with the EXIT25, CLOX1, and FAB scores. Age, gender, and years of education were included as covariates. Statistical thresholds were set to uncorrected P-values of 0.001 at the voxel level and 0.05 at the cluster level. Results: The EXIT25 score correlated inversely with the regional grey matter volume in the left lateral frontal lobe (Brodmann areas 6, 9, 44, and 45). The CLOX1 score correlated positively with the regional grey matter volume in the right orbitofrontal cortex (Brodmann area 11) and the left supramarginal gyrus (Brodmann area 40). The FAB score correlated positively with the regional grey matter volume in the right precentral gyrus (Brodmann area 6). The left lateral frontal lobe (Brodmann area 9) and the right lateral frontal lobe (Brodmann area 46) were identified as common brain regions that showed association with EXIT25, CLOX1, and FAB based only a voxel-level threshold. Conclusions: The results of this study suggest that the EXIT25, CLOX1, and FAB may be associated with the distinct neural correlates of the frontal cortex.

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Gray Matter Volume in Left Rostral Middle Frontal and Left Cerebellar Cortices Predicts Frontal Executive Performance in Alcoholic Subjects

Abstract: We have concluded that volumetric measurements of left rostral middle frontal and cerebellar cortices seem to be able to predict the frontal executive performance but not the cognitive mental status in alcoholic subjects.

Cited by 31 publications

References 43 publications

Brain connectivity-informed regularization methods for regression

Brain connectivity-informed regularization methods for regression

The frontal assessment battery in clinical practice: a systematic review

Differences in the neural correlates of frontal lobe tests

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