From genes to behavior: placing cognitive models in the context of biological pathways

Sáez, Ignacio; Set, Eric; Hsu, Ming

doi:10.3389/fnins.2014.00336

Cited by 11 publications

(7 citation statements)

References 72 publications

(160 reference statements)

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“…Not only are we interested in developing ML models with high prediction capabilities, but also in being able to interpret the models themselves. Models’ interpretation have also been an active research topic in this area in the last years [ 16 – 18 ]. The interpretation of ML models allows researchers to perform biological and functional analysis based on the genetic signatures found to either confirm already existing knowledge of the studied disease or potentially discover new associations that may be worth to investigate further.…”

Section: Introductionmentioning

confidence: 99%

BLASSO: integration of biological knowledge into a regularized linear model

et al. 2018

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BackgroundIn RNA-Seq gene expression analysis, a genetic signature or biomarker is defined as a subset of genes that is probably involved in a given complex human trait and usually provide predictive capabilities for that trait. The discovery of new genetic signatures is challenging, as it entails the analysis of complex-nature information encoded at gene level. Moreover, biomarkers selection becomes unstable, since high correlation among the thousands of genes included in each sample usually exists, thus obtaining very low overlapping rates between the genetic signatures proposed by different authors. In this sense, this paper proposes BLASSO, a simple and highly interpretable linear model with l1-regularization that incorporates prior biological knowledge to the prediction of breast cancer outcomes. Two different approaches to integrate biological knowledge in BLASSO, Gene-specific and Gene-disease, are proposed to test their predictive performance and biomarker stability on a public RNA-Seq gene expression dataset for breast cancer. The relevance of the genetic signature for the model is inspected by a functional analysis.ResultsBLASSO has been compared with a baseline LASSO model. Using 10-fold cross-validation with 100 repetitions for models’ assessment, average AUC values of 0.7 and 0.69 were obtained for the Gene-specific and the Gene-disease approaches, respectively. These efficacy rates outperform the average AUC of 0.65 obtained with the LASSO. With respect to the stability of the genetic signatures found, BLASSO outperformed the baseline model in terms of the robustness index (RI). The Gene-specific approach gave RI of 0.15±0.03, compared to RI of 0.09±0.03 given by LASSO, thus being 66% times more robust. The functional analysis performed to the genetic signature obtained with the Gene-disease approach showed a significant presence of genes related with cancer, as well as one gene (IFNK) and one pseudogene (PCNAP1) which a priori had not been described to be related with cancer.ConclusionsBLASSO has been shown as a good choice both in terms of predictive efficacy and biomarker stability, when compared to other similar approaches. Further functional analyses of the genetic signatures obtained with BLASSO has not only revealed genes with important roles in cancer, but also genes that should play an unknown or collateral role in the studied disease.

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Section: Introductionmentioning

confidence: 99%

BLASSO: integration of biological knowledge into a regularized linear model

et al. 2018

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“…(Rauss & Pourtois, 2013;Rougier, Noelle, Braver, Cohen, & O'Reilly, 2005). In particular, individuals may formulate hypotheses or models of their surrounding environments and to control learning such that rewards received (or not received) are coded cognitively and incorporated into abstract representations of the surrounding environments (Saez, Set, & Hsu, 2014). These representations are updated continuously to predict future rewards that are contingent on complex stimulus cues and events in the environment.…”

Section: Reward Processingmentioning

confidence: 99%

DRD4 polymorphisms modulate reward positivity and P3a in a gambling task: Exploring a genetic basis for cultural learning

et al. 2020

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Prior work shows that people respond more plastically to environmental influences, including cultural influences, if they carry the 7 or 2‐repeat (7/2R) allelic variant of the dopamine D4 receptor gene (DRD4). The 7/2R carriers are thus more likely to endorse the norms and values of their culture. So far, however, mechanisms underlying this moderation of cultural acquisition by DRD4 are unclear. To address this gap in knowledge, we tested the hypothesis that DRD4 modulates the processing of reward cues existing in the environment. About 72 young adults, preselected for their DRD4 status, performed a gambling task, while the electroencephalogram was recorded. Principal components of event‐related potentials aligned to the Reward‐Positivity (associated with bottom‐up processing of reward prediction errors) and frontal‐P3 (associated with top‐down attention) were both significantly more positive following gains than following losses. As predicted, the gain‐loss differences were significantly larger for 7/2R carriers than for noncarriers. Also, as predicted, the cultural backgrounds of the participants (East Asian vs. European American) did not moderate the effects of DRD4. Our findings suggest that the 7/2R variant of DRD4 enhances (a) the detection of reward prediction errors and (b) controlled attention that updates the context for the reward, thereby suggesting one possible mechanism underlying the DRD4 × Culture interactions.

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“…The main criticism to this approach is represented by the assumption that the effects of the single variants are considered additive rather than epistatic and with similar magnitude. However, compared to the single gene variant analysis, this strategy allows for a better representation of the effect of biological networks on complex phenotypes, as it is the case with human behavior (Saez et al, 2014 ).…”

Section: Limitations Of the Studymentioning

confidence: 99%

Genetically-Driven Enhancement of Dopaminergic Transmission Affects Moral Acceptability in Females but Not in Males: A Pilot Study

Pellegrini

Palumbo

Iofrida

et al. 2017

Front. Behav. Neurosci.

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Moral behavior has been a key topic of debate for philosophy and psychology for a long time. In recent years, thanks to the development of novel methodologies in cognitive sciences, the question of how we make moral choices has expanded to the study of neurobiological correlates that subtend the mental processes involved in moral behavior. For instance, in vivo brain imaging studies have shown that distinct patterns of brain neural activity, associated with emotional response and cognitive processes, are involved in moral judgment. Moreover, while it is well-known that responses to the same moral dilemmas differ across individuals, to what extent this variability may be rooted in genetics still remains to be understood. As dopamine is a key modulator of neural processes underlying executive functions, we questioned whether genetic polymorphisms associated with decision-making and dopaminergic neurotransmission modulation would contribute to the observed variability in moral judgment. To this aim, we genotyped five genetic variants of the dopaminergic pathway [rs1800955 in the dopamine receptor D4 (DRD4) gene, DRD4 48 bp variable number of tandem repeat (VNTR), solute carrier family 6 member 3 (SLC6A3) 40 bp VNTR, rs4680 in the catechol-O-methyl transferase (COMT) gene, and rs1800497 in the ankyrin repeat and kinase domain containing 1 (ANKK1) gene] in 200 subjects, who were requested to answer 56 moral dilemmas. As these variants are all located in genes belonging to the dopaminergic pathway, they were combined in multilocus genetic profiles for the association analysis. While no individual variant showed any significant effects on moral dilemma responses, the multilocus genetic profile analysis revealed a significant gender-specific influence on human moral acceptability. Specifically, those genotype combinations that improve dopaminergic signaling selectively increased moral acceptability in females, by making their responses to moral dilemmas more similar to those provided by males. As females usually give more emotionally-based answers and engage the “emotional brain” more than males, our results, though preliminary and therefore in need of replication in independent samples, suggest that this increase in dopamine availability enhances the cognitive and reduces the emotional components of moral decision-making in females, thus favoring a more rationally-driven decision process.

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From genes to behavior: placing cognitive models in the context of biological pathways

Cited by 11 publications

References 72 publications

BLASSO: integration of biological knowledge into a regularized linear model

BLASSO: integration of biological knowledge into a regularized linear model

DRD4 polymorphisms modulate reward positivity and P3a in a gambling task: Exploring a genetic basis for cultural learning

Genetically-Driven Enhancement of Dopaminergic Transmission Affects Moral Acceptability in Females but Not in Males: A Pilot Study

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