Biology subjects

Bang, D.

Publications and source records attributed to Bang, D..

6 recordsLinked to original sources

bioRxiv2018

Group decision-making is optimal in adolescence

Group decision-making is required in early life in educational settings and central to a well-functioning society. However, there is little research on group decision-making in adolescence, despite the significant neuro-cognitive changes during this period. Researchers have studied adolescent decision-making in static social contexts, such as risk-taking in the presence of peers, and largely deemed adolescent decision-making sub-optimal. It is not clear whether these findings generalise to more dynamic social contexts, such as the discussions required to reach a group decision. Here we test the optimality of group decision-making at different stages of adolescence. Pairs of male pre-to-early adolescents (8 to 13 years of age) and mid-to-late adolescents (14 to 17 years of age) together performed a low-level, perceptual decision-making task. Whenever their individual decisions differed, they were required to negotiate a joint decision. While there were developmental differences in individual performance, the joint performance of both adolescent groups was at adult levels (data obtained from a previous study). Both adolescent groups achieved a level of joint performance expected under optimal integration of their individual information into a joint decision. Young adolescents joint, but not individual, performance deteriorated over time. The results are consistent with recent findings attesting to the competencies, rather than the shortcomings, of adolescent social behaviour.

neuroscience↗

bioRxiv2018

TnClone: high-throughput clonal analysis usingTn5-mediated library construction and de novo assembly

A typical molecular cloning procedure requires Sanger sequencing for validation, which becomes cost-prohibitive and labour-intensive for large-scale clonal analysis of genotype-phenotype studies. Here we present a Tn5-mediated clonal analysis platform TnClone, which uses next-generation sequencing (NGS) to rapidly and cost-effectively analyze a large number of clones. We also developed a user-friendly graphical user interface and have provided general guidelines for conducting validation experiments. Using TnClone, we achieved more than 20-fold cost reduction compared with the cost incurred using conventional Sanger sequencing and detected low-frequency mutant clones (~10%) in mixed samples. We tested our programme and achieved 99.4% sensitivity. Our platform provides rapid turnaround with minimal hands-on time for secondary evaluation as NGS technology continues to evolve.

synthetic biology↗

bioRxiv2018

Lineage tracing using a Cas9-deaminase barcoding system targeting endogenous L1 elements

Determining cell lineage and function is critical to understanding human physiology and pathology. Although advances in lineage tracing methods have provided new insight into cell fate, defining cellular diversity at the mammalian level remains a challenge. Here, we developed a genome editing strategy using a cytidine deaminase fused with inactive Cas9 (dCas9) to specifically target endogenous interspersed repeat regions in mammalian cells. The resulting mutation patterns served as a genetic barcode, which was induced by targeted mutagenesis with single-guide RNA (sgRNA), leveraging substitution events, and subsequent read out by a single primer pair. By analyzing interspersed mutation signatures, we show the accurate reconstruction of cell lineage using both bulk cell and single-cell data. We envision that our genetic barcode system will enable fine-resolution mapping of organismal development in healthy and diseased mammalian states.

bioengineering↗

bioRxiv2018

Multiplexed single-cell RNA-seq via transient barcoding for drug screening

To simultaneously analyze multiple samples of various conditions with scRNA-seq, we developed a universal sample barcoding method through transient transfection of SBOs. A 48-plex drug treatment experiment of pooled samples analyzed by a single run of Drop-Seq revealed a unique transcriptome response for each drug and target-specific gene expression signatures at the single-cell level. Our cost-effective method is widely applicable for single-cell profiling of multiple experimental conditions.

genomics↗

bioRxiv2018

Human noise blindness drives suboptimal cognitive inference

Humans typically make near-optimal sensorimotor judgments but show systematic biases when making more cognitive judgments. Here we test the hypothesis that, while humans are sensitive to the noise present during early sensory processing, the \"optimality gap\" arises because they are blind to noise introduced by later cognitive integration of variable or discordant pieces of information. In six psychophysical experiments, human observers judged the average orientation of an array of contrast gratings. We varied the stimulus contrast (encoding noise) and orientation variability (integration noise) of the array. Participants adapted near-optimally to changes in encoding noise, but, under increased integration noise, displayed a range of suboptimal behaviours: they ignored stimulus base rates, reported excessive confidence in their choices, and refrained from opting out of objectively difficult trials. These overconfident behaviours were captured by a Bayesian model which is blind to integration noise. Our study provides a computationally grounded explanation of suboptimal cognitive inferences.

neuroscience↗

bioRxiv2018

Dissociating decision confidence from evidence reliability in the human brain

Our confidence in a choice and the evidence pertaining to a choice appear to be inseparable. An emerging computational consensus is, however, that the brain should maintain separate estimates of these quantities for adaptive behavioural control. Here we devised a psychophysical task to decouple confidence in a perceptual decision from both the reliability of sensory evidence and the relation of such evidence with respect to a choice boundary. Using human fMRI, we found that an area in medial prefrontal cortex (perigenual anterior cingulate cortex, pgACC) tracked expected performance, an aggregate signature of decision confidence, whereas neural areas previously proposed to encode decision confidence instead tracked sensory reliability (posterior parietal cortex and ventral striatum) or boundary distance (pre-supplementary motor area). Supporting that information encoded by pgACC is central to a subjective sense of decision confidence, we show that pgACC activity does not simply co-vary with expected performance but is also linked to within-subject and between-subject variation in explicit confidence estimates. Our study is consistent with the proposal that the brain maintains choice-dependent and choice-independent estimates of certainty, and sheds light on why dysfunctional confidence often emerges following prefrontal lesions and/or degeneration.\n\nSignificance StatementRecent computational models propose that our sense of confidence in a choice reflects an estimate of the probability that the choice is correct. However, it has proven difficult to experimentally separate decision confidence from its component parts, such as our certainty about perceptual evidence or choice requirements. Here we devised a task to dissociate these quantities and isolate a distinct encoding of decision confidence in the medial prefrontal cortex of the human brain. We show that activity in this area not only tracks expected performance on a task but is also related to both within-subject and between-subject variation in a subjective sense of confidence. Our study illuminates why dysfunctional confidence often emerges following damage to prefrontal cortex.

neuroscience↗