Biology subjects

Stasiak, A.

Publications and source records attributed to Stasiak, A..

6 recordsLinked to original sources

bioRxiv2023

Dopamine signals encode internally determined subjective value regardless of externally indicated reward attributes

The dopamine reward prediction error signal is known to be subjective but has so far only been assessed in aggregate choices. However, personal choices fluctuate across trials and thus reflect the instantaneous subjective reward value. In the well-established Becker-DeGroot-Marschak (BDM) auction-like mechanism, participants are encouraged to place bids that accurately reveal their instantaneous subjective reward value; inaccurate bidding results in suboptimal reward ( incentive compatibility). In our experiment, male rhesus monkeys became experienced over several years to place accurate BDM bids for juice rewards without specific external constraints. Their bids for physically identical rewards varied trial by trial and increased overall for larger rewards. In these highly experienced animals, responses of midbrain dopamine neurons followed the trial-by-trial variations of bids despite constant, explicitly predicted reward amounts. Inversely, dopamine responses were similar with similar bids for different physical reward amounts. Support Vector Regression demonstrated accurate prediction of the animals bids by as few as twenty dopamine neurons. Thus, the phasic dopamine reward signal reflects instantaneous subjective reward value.

neuroscience↗

bioRxiv2020

Reduced neuronal value signals in monkey orbitofrontal cortex during relative reward-specific satiety

Sensitivity to satiety constitutes a basic requirement for neuronal coding of subjective reward value. Satiety from natural on-going consumption affects reward functions in learning and approach behavior. More specifically, satiety reduces the subjective economic value of individual rewards during choice between options that typically contain multiple reward components. The unconfounded assessment of economic reward value requires tests at choice indifference between two options, which is difficult to achieve with sated rewards. By conceptualizing choices between options with multiple reward components ( bundles), Revealed Preference Theory may offer a solution. Despite satiety, choices against an unaltered reference bundle may remain indifferent when the reduced value of a sated bundle reward is compensated by larger amounts of an unsated reward of the same bundle; then the value loss of the sated reward is indicated by the amount of the added unsated reward. Here we show psychophysically titrated choice indifference in monkeys between bundles of differently sated rewards. Neuronal chosen value signals in orbitofrontal cortex (OFC) followed closely the subjective value change within recording periods of individual neurons. A neuronal classifier distinguishing the bundles and predicting choice substantiated the subjective value change. Choice between conventional single rewards confirmed the neuronal changes seen with two-reward bundles. Thus, reward-specific satiety reduces subjective reward value signals in OFC. With satiety being an important factor of subjective reward value, these results extend the notion of subjective economic reward value coding in OFC neurons. SignificanceOn-going consumption reduces the subjective value of rewards to different degrees depending on their individual properties, a phenomenon referred to as sensory-specific satiety. Such value change should be manifested in economic choices, and neuronal signals for subjective economic reward value should be sensitive to reward-specific satiety. We tested monkeys during choice between two options that each contained two different rewards ( bundles); the two rewards were prone to different degrees of satiety. On-going reward consumption affected choices in a way that indicated satiety-induced reward-specific change of subjective economic value. Neuronal responses in the monkey orbitofrontal cortex (OFC) followed the differential reduction of subjective economic value. These results satisfy a crucial requirement for subjective reward value coding in OFC neurons.

neuroscience↗

bioRxiv2020

Scalar human brain responses to vectorial economic choice options: a concept-driven approach

Rewarding choice options typically contain multiple components, but neural signals in single brain voxels are scalar and primarily vary up or down. In a previous study, we had designed reward bundles that contained the same two milkshakes with independently set amounts; we had used psychophysics and rigorous economic concepts to estimate two-dimensional choice indifference curves (IC) that represented revealed stochastic preferences for these bundles in a systematic, integrated manner. All bundles on the same ICs were equally revealed preferred (and thus had same utility, as inferred from choice indifference); bundles on higher ICs (higher utility) were preferred to bundles on lower ICs (lower utility). In the current study, we used the established behavior for testing with functional magnetic resonance imaging (fMRI). We now demonstrate neural responses in reward-related brain structures of human female and male participants, including striatum, midbrain and medial orbitofrontal cortex that followed the characteristic pattern of ICs: similar responses along ICs (same utility despite different bundle composition), but monotonic change across ICs (different utility). Thus, these brain structures integrated multiple reward components into a scalar signal, well beyond the known subjective value coding of single-component rewards. Significance StatementRewards have several components, like the taste and size of an apple, but it is unclear how each component contributes to the overall value of the reward. While choice indifference curves of economic theory provide behavioural approaches to this question, it is unclear whether brain responses capture the preference and utility integrated from multiple components. We report activations in striatum, midbrain and orbitofrontal cortex that follow choice indifference curves representing behavioral preferences over and above variations of individual reward components. In addition, the concept-driven approach encourages future studies on natural, multi-component rewards that are prone to irrational choice of normal and brain-damaged individuals.

neuroscience↗

bioRxiv2019

How we choose multi-component rewards

Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multi-component choice options? Here, we measured how stochastic choices revealed preferences for two-component milkshakes. The preferences were intuitively graphed as indifference curves that represented the orderly integration of the two components as trade-off: parts of one component were given up for obtaining one additional unit of the other component without a change in preference. The well-ordered, non-overlapping curves satisfied leave-one-out tests, followed predictions by machine learning decoders and correlated with single-dimensional Becker-DeGroot-Marschak (BDM) auction-like bids for the two-component rewards. This accuracy suggests a decision process that integrates multiple reward components into single-dimensional estimates in a systematic fashion. In inter-species comparisons, human performance matched that of highly experienced laboratory monkeys, as measured by accuracy of the critical trade-off between bundle components. These data describe the nature of choices of multi-component choice options and attest to the validity of the rigorous economic concepts and their convenient graphic schemes for explaining choices of human and non-human primates. The results encourage formal behavioral and neural investigations of normal, irrational and pathological economic choices.

neuroscience↗

bioRxiv2019

Chromatin is frequently unknotted at the megabase scale

Knots in the human genome would greatly impact diverse cellular processes ranging from transcription to gene regulation. To date, it has not been possible to directly examine the genome in vivo for the presence of knots. Recently, methods for serial fluorescent in situ hybridization have made it possible to measure the 3d position of dozens of consecutive genomic loci, in vivo. However, the determination of whether genomic trajectories are knotted remains challenging, because small errors in the localization of a single locus can transform an unknotted trajectory into a highly-knotted trajectory, and vice versa. Here, we use stochastic closure analysis to determine whether a genomic trajectory is knotted in the setting of experimental noise. We analyse 4727 deposited genomic trajectories of a 2Mb long chromatin interval from chromosome 21. For 243 of these trajectories, their knottedness could be reliably determined despite the possibility of localization errors. Strikingly, in each of these 243 cases, the trajectory was unknotted. We note a potential source of bias, insofar as knotted contours may be more difficult to reliably resolve. Nevertheless, our data is consistent with a model where, at the scales probed, the human genome is often free of knots.

bioinformatics↗

bioRxiv2018

Chromatin-loop extrusion and chromatin unknotting

It has been a puzzle how decondensed interphase chromosomes remain essentially unknotted. The natural expectation is that in the presence of type II DNA topoisomerases that permit passages of double-stranded DNA regions through each other, all chromosomes should reach the state of topological equilibrium. The topological equilibrium in highly crowded interphase chromosomes forming chromosome territories would result in formation of highly knotted chromatin fibres. However, Chromosome Conformation Capture (3C) methods revealed that the decay of contacts with the genomic distance in interphase chromosomes is practically the same as in the crumpled globule state that is formed when long polymers condense without formation of any knots. To remove knots from highly crowded chromatin, one would need an active process that should not only provide the energy to move the system from the state of topological equilibrium but also guide topoisomerase-mediated passages in such a way that knots would be efficiently unknotted instead of making the knots even more complex. We show here that the process of chromatin-loop extrusion is ideally suited to actively unknot chromatin fibres in interphase chromosomes.\n\nSIGNIFICANCE STATEMENTSimilar to earphone cables crammed into a pocket, long and crowded chromatin fibres that form chromosomes in living cells have the natural tendency to get knotted. This is exacerbated by the action of DNA topoisomerases that transiently cut some chromatin fibres and let other to pass through. Yet, the knotting frequency of chromatin fibres is very low and it has been a puzzle how this is achieved. Recently a novel active mechanism known as chromatin loop extrusion has been proposed to be involved in shaping chromosomes by forming sequential arrays of ca 1 Mb large chromatin loops. Using numerical simulations, we show here that chromatin loop extrusion is ideally suited to remove knots from chromatin fibres.

biophysics↗