Biology subjects

Lee, S. W.

Publications and source records attributed to Lee, S. W..

5 recordsLinked to original sources

bioRxiv2018

Task complexity interacts with state-space uncertainty in the arbitration process between model-based and model-free reinforcement-learning at both behavioral and neural levels

A major open question concerns how the brain governs the allocation of control between two distinct strategies for learning from reinforcement: model-based and model-free reinforcement learning. While there is evidence to suggest that the reliability of the predictions of the two systems is a key variable responsible for the arbitration process, another key variable has remained relatively unexplored: the role of task complexity. By using a combination of novel task design, computational modeling, and model-based fMRI analysis, we examined the role of task complexity alongside state-space uncertainty in the arbitration process between model-based and model-free RL. We found evidence to suggest that task complexity plays a role in influencing the arbitration process alongside state-space uncertainty. Participants tended to increase model-based RL control in response to increasing task complexity. However, they resorted to model-free RL when both uncertainty and task complexity were high, suggesting that these two variables interact during the arbitration process. Computational fMRI revealed that task complexity interacts with neural representations of the reliability of the two systems in the inferior prefrontal cortex bilaterally. These findings provide insight into how the inferior prefrontal cortex negotiates the trade-off between model-based and model-free RL in the presence of uncertainty and complexity, and more generally, illustrates how the brain resolves uncertainty and complexity in dynamically changing environments.\n\nSUMMARY OF FINDINGS- Elucidated the role of state-space uncertainty and complexity in model-based and model-free RL.\n\n- Found behavioral and neural evidence for complexity-sensitive prefrontal arbitration.\n\n- High task complexity induces explorative model-based RL.

neuroscience↗

bioRxiv2018

Decoupling between causal understanding and awareness during learning and inference

Causal reasoning is a principal higher-cognitive ability of humans, however, much remains unknown, including (a) the type (systematic versus intermixed) and order (inductive-then-deductive or vice versa) of experience that best achieves causal-chain extraction; (b) how inferences generalize to novel problems, especially with one-shot experience; and (c) how metacognition, reflected in uncertainty of ones knowledge, relates to actual knowledge. We tested people on a realistic cancer biology task (e.g., seroc chemicals inducing tumors with subsequent effects). Systematic experience was superior, with some evidence that the inductive-then-deductive order promoted stronger one-shot generalization. Notably, uncertainty was decoupled from actual knowledge, with the deductive-then-inductive group being overconfident, likely reflecting lack of awareness of the inductive component; while those with successful one-shot generalization held lower confidence, reflecting generalization with minimal experience, while remaining skeptical. Our findings clarify processes underlying causal reasoning, and reveal a complex relationship between causal reasoning and metacognitive awareness of it.

neuroscience↗

bioRxiv2018

Effects of depression on prefrontal striatal goal directed and habitual control

Depression is characterized by deficits in the reinforcement learning (RL) process. Although many computational and neural studies have extended our knowledge of the impact of depression on RL, most focus on habitual control (model-free RL), yielding a relatively poor understanding of goal-directed control (model-based RL) and arbitration control to find a balance between the two. We investigate the effects of depression on goal-directed and habitual control in the prefrontal-striatal circuitry. We find that depression is associated with attenuated state and reward prediction error representation in the insula and caudate, a disruption of arbitration control in the predominantly inferior lateral prefrontal cortex and frontopolar cortex, and suboptimal value-action conversion. These findings fully characterize how depression influences different levels of RL, challenging previous conflicting views that depression simply influences either habitual or goal-directed control. Our study creates possibilities for various clinical applications, such as early diagnosis and behavioral therapy design.

neuroscience↗

bioRxiv2018

The tumor suppressor p53 promotes carcinoma invasion and collective cellular migration

SummaryLoss of function of the tumor suppressor p53 is generally thought to increase cell motility and invasiveness. Using 2-D confluent and 3-D spheroidal cell motility assays with bladder carcinoma cells and colorectal carcinoma cells, we report, to the contrary, that loss of p53 can decrease cell motility and invasion.\n\nAbstractFor migration of the single cell studied in isolation, loss of function of the tumor suppressor p53 is thought to increase cell motility. Here by contrast we used the 2-D confluent cell layer and the 3-D multicellular spheroid to investigate how p53 impacts dissemination and invasion of cellular collectives. We used two human carcinoma cell lines, the bladder carcinoma EJ and the colorectal carcinoma HCT116. We began by replicating single cell invasion in the traditional Boyden chamber assay, and found that the number of invading cells increased with loss of p53, as expected. In the confluent 2-D cell layer, however, for both EJ and HCT, speeds and effective diffusion coefficients for the p53 null types compared to their p53 expressing counterparts were significantly smaller. Compared to p53 expressers, p53 null cells exhibited more organized cortical actin rings together with reduced front-rear cell polarity. Furthermore, loss of p53 caused cells to exert smaller traction forces upon their substrates, and reduced formation of cryptic lamellipodia. In a 3-D collagen matrix, p53 consistently promoted invasion of the multicellular spheroids into surrounding matrix. Together, these results show that p53 expression in these carcinoma model systems increases collective cellular migration and invasion. As such, these studies point to paradoxical contributions of p53 in single cell versus collective cellular migration.

cancer biology↗

bioRxiv2018

Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains

Bacteriocins are ribosomally produced antimicrobial peptides that represent an untapped source of promising antibiotic alternatives. However, inherent challenges in isolation and identification of natural bacteriocins in substantial yield have limited their potential use as viable antimicrobial compounds. In this study, we have developed an overall pipeline for bacteriocin-derived compound design and testing that combines sequence-free prediction of bacteriocins using a machine-learning algorithm and a simple biophysical trait filter to generate minimal 20 amino acid peptide candidates that can be readily synthesized and evaluated for activity. We generated 28,895 total 20-mer peptides and scored them for charge, -helicity, and hydrophobic moment, allowing us to identify putative peptide sequences with the highest potential for interaction and activity against bacterial membranes. Of those, we selected sixteen sequences for synthesis and further study, and evaluated their antimicrobial, cytotoxicity, and hemolytic activities. We show that bacteriocin-based peptides with the overall highest scores for our biophysical parameters exhibited significant antimicrobial activity against E. coli and P. aeruginosa. Our combined method incorporates machine learning and biophysical-based minimal region determination, to create an original approach to rapidly discover novel bacteriocin candidates amenable to rapid synthesis and evaluation for therapeutic use.

microbiology↗