Biology subjects

Hori, Y.

Publications and source records attributed to Hori, Y..

3 recordsLinked to original sources

bioRxiv2018

Signaling incentive and drive in the primate ventral pallidum for motivational control of goal-directed action

Processing incentive and drive is essential for control of goal-directed behavior. The limbic part of the basal ganglia has been emphasized in these processes, yet the exact neuronal mechanism has remained elusive. In this study, we examined the neuronal activity of the ventral pallidum (VP) and its upstream area, the rostromedial caudate (rmCD), while two male macaque monkeys performed an instrumental lever-release task, in which a visual cue indicated the forthcoming reward size. We found that the activity of some neurons in VP and rmCD reflected the expected reward-size transiently following the cue. Reward-size coding appeared earlier and stronger in VP than in rmCD. We also found that the activity in these areas was modulated by the satiation level of monkeys, which also occurred more frequently in VP than in rmCD. The information regarding reward-size and satiation-level was independently signaled in the neuronal populations of these areas. The data thus highlighted the neuronal coding of key variables for goal-directed behavior in VP. Furthermore, pharmacological inactivation of VP induced more severe deficit of goal-directed behavior than inactivation of rmCD, which was indicated by abnormal error repetition and diminished satiation effect on the performance. These results suggest that VP encodes incentive value and internal drive, and plays a pivotal role in the control of motivation to promote goal-directed behavior.\n\nSignificance StatementThe limbic part of the basal ganglia has been emphasized in the motivational control of goal-directed action. Here, we investigated how the ventral pallidum (VP) and the rostromedial caudate (rmCD) encode incentive value and internal drive, and control goal-directed behavior. Neuronal recording and subsequent pharmacological inactivation revealed that VP had stronger coding of reward size and satiation level than rmCD. Reward size and satiation level were independently encoded in the neuronal population of these areas. Furthermore, VP inactivation impaired goal-directed behavior more severely than rmCD inactivation. These results highlighted the central role of VP in the motivational control of goal-directed action.

neuroscience↗

bioRxiv2018

Analysing disturbance response of cell-to-cell communication systems: a case study for activator-repressor-diffuser motif

In biomolecular communication networks, bacterial cells communicate with each other using a cell-to-cell communication mechanism mediated by diffusible signaling molecules. The dynamics of molecular concentrations in such systems are approximately modeled by reaction-diffusion equations. In this paper, we analyse the ability of cell-to-cell communication systems to attenuate impulsive disturbances with various spatial frequency profiles by computing the integrated squared concentration of molecules. In particular, we perform in-depth study of disturbance responses for an activator-repressor-diffuser biocircuit in the spatial frequency domain to characterize its spatial frequency gain.

synthetic biology↗

bioRxiv2017

Optimization-based synthesis of stochastic biocircuits with statistical specifications

Model-guided design has become a standard approach to engineering biomolecular circuits in current synthetic biology. However, the stochastic nature of biomolecular reactions is often overlooked in the design process. As a result, cell-cell heterogeneity causes unexpected deviation of biocircuit behaviors from model predictions and requires additional iterations of design-build-test cycles. To enhance the design process of stochastic biocircuits, this paper presents a computational framework to systematically specify the level of intrinsic noise using well-defined metrics of statistics and design highly heterogeneous biocircuits based on the specifications. Specifically, we use descriptive statistics of population distributions as an intuitive specification language of stochastic biocircuits and develop an optimization based computational tool that explores parameter configurations satisfying design requirements. Sensitivity analysis methods are also developed to ensure the robustness of a biocircuit design. These design tools are formulated using convex optimization programs to enable efficient and rigorous quantification of the statistics without approximation, and thus, they are amenable to the synthesis of stochastic biocircuits that require high reliability. We demonstrate these features by designing a stochastic negative feedback biocircuit that satisfies multiple statistical constraints. In particular, we use a rigorously quantified parameter map of feasible design space to perform in-depth study of noise propagation and regulation in negative feedback pathways.

synthetic biology↗