Biology subjects

Bang, D.

Publications and source records attributed to Bang, D..

16 recordsLinked to original sources

bioRxiv2026

Dynamics of dopamine transients in human olfactory epithelium during reward learning

Dopamine signaling is crucial for motivation, movement, and learning, but has remained beyond the reach of measurement in healthy humans. Here, we measured sub-second dopamine in the olfactory epithelium of healthy humans during two reward learning tasks with distinct reward types: liquid reward during a conditioning task and monetary reward during an economic exchange game. In both tasks, as trials progress, peak dopamine transients shift from rewarding outcomes back to reward-predictive cues. In the economic game, this pattern retrains quickly when reward magnitude or reward timing is changed without warning. These findings match the time transfer characteristics and amplitude dependence of temporal difference prediction error signals. The results also establish a new, minimally invasive route for recording fast dopamine signaling in healthy humans: the nose.

neuroscience↗

bioRxiv2026

Dopamine dynamics in human anterior cingulate cortex during Pavlovian-instrumental conflict

Dopamine is believed to modulate not only instrumental learning about the link between states, actions, and outcomes but also reflexive behaviours, such as a Pavlovian bias to approach in rewarding states and freeze in aversive ones. We studied these dual roles in the human brain, by combining intracranial dopamine recordings from the anterior cingulate cortex (ACC)-- a region implicated in behavioural and cognitive control -- with a motivational Go/NoGo task involving conflict between instrumental and Pavlovian action selection. We found evidence that dopamine in the ACC is involved in evaluating whether Pavlovian responding should guide behaviour. This computational motif was observed across multiple task events, including in response to rewards and punishments, and in analyses based on a reinforcement learning model. Our results indicate that dopamine supports learning at the more abstract level of behavioural policies in addition to the more concrete levels of states and actions.

neuroscience↗

bioRxiv2025

Dopamine and serotonin transients predict depressive symptom relief following deep brain stimulation of human subcallosal cingulate cortex

Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depression (TRD) in humans1-3. Monoamines, such as dopamine and serotonin, mediate the effects of pharmacological treatments of depression. However, their roles in recovery following DBS remain elusive, largely due to technical limitations of measuring these neurotransmitters in the living human brain. Here, by leveraging machine learning-enhanced electrochemistry4-7, we show that dopamine and serotonin signaling following DBS to the SCC predicted later depressive symptom relief in humans with TRD. We found that both dopamine and serotonin levels increased following subtherapeutic intraoperative SCC stimulation, with each neurotransmitter showing selective responses to distinct decision-making tasks. Furthermore, acute dopamine increases predicted later mood improvements during a social decision-making task, while serotonin enhancement predicted faster responses during a non-social learning task longitudinally. Critically, changes in dopamine and serotonin levels during the social decision-making task jointly predicted depressive symptom remission at 6-month follow-up. These findings illustrate the contribution of both dopamine and serotonin signaling in predicting behavioral improvement and depressive symptom remission in humans with TRD. Such neurochemical plasticity may serve as potential mechanistic biomarkers for SCC DBS mechanism and TRD treatment response. Significance statementO_LIDopamine and serotonin levels increased following acute DBS to the SCC in humans. C_LIO_LIAcute dopamine and serotonin changes predicted later mood and response speed changes. C_LIO_LISustained TRD recovery was predicted by acute increases in both dopamine and serotonin estimates. C_LI

neuroscience↗

bioRxiv2025

Octopamine and tyramine dynamics predict learning rate phenotypes during associative conditioning in honey bees

Biogenic amines are fundamental for physiological homeostasis and behavioral control in both vertebrates and invertebrates. Monoamine neurotransmitters released in target brain regions conjointly regulate adaptive learning and plasticity. However, our understanding of these multi-analyte mechanisms remains nascent, in part due to limitations in measurement technology. Here, during associative conditioning in honey bees, we concurrently tracked sub-second fluctuations in octopamine, tyramine, dopamine, and serotonin in the antennal lobe, where plasticity influences odorant representations. By repeatedly pairing an odorant with subsequent sucrose delivery, we observed individual differences in the conditioned response to odor, which occurred after a variable number of pairings (learners) or not at all (nonlearners). The distinction between learners and non-learners was reflected in neurotransmitter responses across experimental conditions. Remarkably, the speed of learning - the number of pairings prior to a proboscis extension reflex - could be predicted from monoamine opponent signaling (octopamine-tyramine), from both the first presentation of the odorant alone, prior to any pairing with sucrose, and from the first conditioned response to the odorant, coming after a number of sucrose pairings. These results suggest monoamine signaling phenotypes may relate directly to the now widely-reported socially-relevant genetic differences in honey bee learning.

neuroscience↗

bioRxiv2024

Correcting errors in PCR-derived libraries for rare allele detection by reconstructing parental and daughter strand information

Molecular barcoding methods enable high-sensitivity detection of circulating tumor DNA that is rarely present in liquid biopsy samples. Many methods involve ligation of molecular barcodes to DNA prior to hybridization capture, enabling recovery of starting molecules. Development of polymerase chain reaction (PCR)-based methods could facilitate more cost- and labor- effective detection; however, tracking molecular identity can be difficult, as new barcodes overwrite old barcodes in each cycle. We developed a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. SPIDER-seq detected mutations at frequences as low as 0.125% after only two consecutive general PCR cycles and systematically analyzed the error pattern in the peer-to-peer network. Our method could facilitate the rapid detection of mutations associated with various cancers.

bioinformatics↗

bioRxiv2022

Multi-layer guilt-by-association-based drug repurposing by integrating clinical knowledge on biological heterogeneous networks

Computational drug repurposing attempts to leverage rapidly accumulating high-throughput data to discover new indications for existing drugs, often by clarifying biological mechanisms with relevant genes. Leveraging the Guilt-by-association (GBA), the principle of "similar genes share similar functions," we introduced clinical neighbors of drug and disease entities while learning their mechanisms on the biological network. To overcome the hurdle of connecting drugs and diseases through large and dense gene-gene network and simultaneously realize the concept of "semantic multi-layer GBA", we present a random walk-based algorithm with a novel clinical-knowledge guided teleport. As a result, drug-disease association prediction accuracy increased up to 8.7% compared to existing state-of-the-art models. In addition, exploration of the generated embedding space displays harmony between biological and clinical contexts. Through repurposing case studies for breast carcinoma and Alzheimers disease, we demonstrate the potential power of multi-layer GBA, a novel perspective for predicting clinical-level associations on heterogeneous biomedical networks.

bioinformatics↗

bioRxiv2021

Neurocomputational mechanisms of confidence in self and others

Computing confidence in ones own and others decisions is crucial for success in many social situations. While there has been substantial progress in our understanding of confidence in oneself, little is known about how we form confidence about others. Here, we address this question by asking subjects undergoing fMRI to place bets on perceptual decisions made by themselves or one of three other players of varying ability. We show that subjects compute confidence in another players decisions by combining distinct estimates of player ability and decision difficulty - allowing them to predict that a good player may get a difficult decision wrong and that a bad player may get an easy decision right. We find that this computation is supported by an interaction between brain systems traditionally implicated in decision-making (LIP) and theory of mind (TPJ, dmPFC). These results reveal a neurocomputational interplay between self- and other-related processes during social cognition.

neuroscience↗

bioRxiv2020

Private-public mappings in human prefrontal cortex

A core feature of human cognition is an ability to separate private states of mind - what we think or believe - from public actions - what we say or do. This ability is central to navigating social interactions in which different contexts often require different mappings between private states and public actions in order to minimise conflict and facilitate communication. Here we investigated how the human brain supports private-public mappings, using an interactive task which required subjects to adapt how they communicated their confidence about a perceptual decision to the social context. Univariate and multivariate analysis of fMRI data revealed that a private-public distinction is reflected in a medial-lateral division of prefrontal cortex - with lateral frontal pole (FPl) supporting the context-dependent mapping from a private sense of confidence to a public report. The concept of private-public mappings provides a promising framework for understanding flexible social behaviour.

neuroscience↗

bioRxiv2020

Multiplex generation, tracking, and functional screening of substitution mutants using a CRISPR/retron system

We developed a clustered regularly interspaced short palindromic repeats (CRISPR)/retron system for multiplexed generation of substitution mutations by co-utilization of a retron system that continuously expresses donor DNA and a CRISPR/Cas9 cassette that induces cleavage at target genomic loci. Our system efficiently introduces substitution mutation in the Escherichia coli genome in a high-throughput manner. These substitution mutations can be tracked by analysis of retron plasmid sequences without laborious amplification of individual edited loci. We demonstrated that our CRISPR/retron system can introduce thousands of mutations in a single experiment and be used for screening phenotypes related to chemical responses or fitness changes. We expect that our system could facilitate genome-scale substitution screenings.

bioengineering↗

bioRxiv2019

Single-cell analysis of a mutant library generated using CRISPR-guided deaminase

CRISPR-based screening methods using single-cell RNA sequencing (scRNA-seq) technology enable comprehensive profiling of gene perturbations from knock-out mutations. However, evaluating substitution mutations using scRNA-seq is currently limited. We combined CRISPR RNA-guided deaminase and scRNA-seq technology to develop a platform for introducing mutations in multiple genes and assessing the mutation-associated signatures. Using this platform, we generated a library consisting of 420 sgRNAs, performed sgRNA tracking analysis, and assessed the effect size of the response to vemurafenib in the melanoma cell line, which has been well-studied via knockout-based drop-out screens. However, a substitution mutation library screen has not been applied and transcriptional information for mechanisms of action was not assessed. Our platform permits discrimination of several candidate mutations that function differently from other mutations by integrating sgRNA candidates and gene expression readout. We anticipate that our platform will enable high-throughput analyses of the mechanisms related to a variety of biological events.

bioengineering↗

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↗