Genetic malformations of the human frontal lobe.
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ABSTRACT:
SUBMITTER: Amrom D
PROVIDER: S-EPMC4271974 | biostudies-literature | 2010 Feb
REPOSITORIES: biostudies-literature
Publications
Genetic malformations of the human frontal lobe.
Amrom Dina D Walsh Christopher A CA
Epilepsia 20100201
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Project description:The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.
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Project description:Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.
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Project description:Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.
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Project description:ObjectiveNeuropsychological profiles are heterogeneous both across and within epilepsy syndromes, but especially in frontal lobe epilepsy (FLE), which has complex semiology and epileptogenicity. This study aimed to characterize the cognitive heterogeneity within FLE by identifying cognitive phenotypes and determining their demographic and clinical characteristics.MethodOne hundred and six patients (age 16-66; 44% female) with FLE completed comprehensive neuropsychological testing, including measures within five cognitive domains: language, attention, executive function, processing speed, and verbal/visual learning. Patients were categorized into one of four phenotypes based on the number of impaired domains. Patterns of domain impairment and clinical and demographic characteristics were examined across phenotypes.ResultsTwenty-five percent of patients met criteria for the Generalized Phenotype (impairment in at least four domains), 20% met criteria for the Tri-Domain Phenotype (impairment in three domains), 36% met criteria for the Domain-Specific Phenotype (impairment in one or two domains), and 19% met criteria for the Intact Phenotype (no impairment). Language was the most common domain-specific impairment, followed by attention, executive function, and processing speed. In contrast, learning was the least impacted cognitive domain. The Generalized Phenotype had fewer years of education compared to the Intact Phenotype, but otherwise, there was no differentiation between phenotypes in demographic and clinical variables. However, qualitative analysis suggested that the Generalized and Tri-Domain Phenotypes had a more widespread area of epileptogenicity, whereas the Intact Phenotype most frequently had seizures limited to the lateral frontal region.SignificanceThis study identified four cognitive phenotypes in FLE that were largely indistinguishable in clinical and demographic features, aside from education and extent of epileptogenic zone. These findings enhance our appreciation of the cognitive heterogeneity within FLE and provide additional support for the development and use of cognitive taxonomies in epilepsy.
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Project description:Analysis of FDG-PET imaging commonly shows that hypometabolism extends into extra-epileptogenic zones (extra-EZ). This study investigates the distribution patterns of hypometabolism in frontal lobe epilepsy (FLE) originating in different frontal regions. Sixty-four patients with FLE were grouped by EZ localization according to Brodmann areas (BAs): Group 1 (the frontal motor and premotor area), BAs 4, 6, and 8; Group 2 (the inferior frontal gyrus and opercular area), BAs 44, 45, and 47; Group 3 (the dorsal prefrontal area), BAs 9, 10, 11, and 46; and Group 4 (the medial frontal and anterior cingulate gyrus), BAs 32 and 24. Regions of extra-EZ hypometabolism were statistically analyzed between FLE groups and healthy controls. Correlation analysis was performed to identify relationships between the intensity of hypometabolism and clinical characteristics. Significant hypometabolism in the ipsilateral (Groups 1 and 4) or bilateral (Groups 2 and 3) anterior insulae was found. Groups 1 and 4 presented with limited distribution of extra-EZ hypometabolism, whereas Groups 2 and 3 showed widely distributed extra-EZ hypometabolism in the rectus gyrus, cingulate gyrus, and other regions. Additionally, the intensity of hypometabolism was correlated with epilepsy duration in Groups 2 and 3. All FLE groups showed hypometabolism in the anterior insula. In addition, distinct patterns of extra-EZ hypometabolism were identified for each FLE group. This quantitative FDG-PET analysis expanded our understanding of the topography of epileptic networks and can guide EZ localization in the future.
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