The Underlying Social Dynamics of Paradigm Shifts

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.     

Dynamics of Social Behavior in Fruit Fly Larvae

We quantified the extent and dynamics of social interactions among fruit fly larvae over time. Both a wild-type laboratory population and a recently-caught strain of larvae spontaneously formed social foraging groups. Levels of aggregation initially increased during larval development and then declined with the wandering stage before pupation. We show that larvae aggregated more on hard than soft food, and more at sites where we had previously broken the surface of the food. Groups of larvae initiated burrowing sooner than solitary individuals, indicating that one potential benefit of larval aggregations is an improved ability to dig and burrow into the food substrate. We also show that two closely related species, D. melanogaster and D. simulans, differ in their tendency to aggregate, which may reflect different evolutionary histories. Our protocol for quantifying social behavior in larvae uncovered robust social aggregations in this simple model, which is highly amenable to neurogenetic analyses, and can serve for future research into the mechanisms and evolution of social behavior.     

Exploring the Social Dynamics of Proenvironmental Behavior Change

This article explores the intrinsic role of context in shaping the course and outcomes of interventions aimed at changing environmentally significant behavior in home and workplace settings. Drawing on sociological theories of symbolic interactionism, we evaluate the social dynamics and mechanisms of two similar, team-based behavior change interventions at work (Environment Champions) and at home (EcoTeams). The analysis shows that the interventions open up different levels of opportunity for reviewing and renegotiating new environmentally friendly behaviors against the reactions and expectations of the immediate peer group, existing workplace or domestic roles, and the situation-specific definitions of what counts as appropriate behavior in the home and the workplace. We argue that policy studies should pay greater attention to the processes of behavior change, or the contextually sensitive relationship between interventions and outcomes, as a step toward refining or streamlining interventions aimed at changing environmentally significant behavior.     

Neural Mechanisms Underlying Breathing Complexity

Breathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD). COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI), we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL) medulla (pre-Bötzinger complex) and the caudal VL pons (parafacial group). fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in neurons can contribute to chaos in airflow and reproduces key experimental fMRI findings.     

Mechanisms Underlying Microbial-Mediated Changes in Social Behavior in Mouse Models of Autism Spectrum Disorder

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Stochastic Dynamics Underlying Cognitive Stability and Flexibility

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences.     

Collective Dynamics Underlying Allosteric Transitions in Hemoglobin

Hemoglobin is the prototypic allosteric protein. Still, its molecular allosteric mechanism is not fully understood. To elucidate the mechanism of cooperativity on an atomistic level, we developed a novel computational technique to analyse the coupling of tertiary and quaternary motions. From Molecular Dynamics simulations showing spontaneous quaternary transitions, we separated the transition trajectories into two orthogonal sets of motions: one consisting of intra-chain motions only (referred to as tertiary-only) and one consisting of global inter-chain motions only (referred to as quaternary-only). The two underlying subspaces are orthogonal by construction and their direct sum is the space of full motions. Using Functional Mode Analysis, we were able to identify a collective coordinate within the tertiary-only subspace that is correlated to the most dominant motion within the quaternary-only motions, hence providing direct insight into the allosteric coupling mechanism between tertiary and quaternary conformation changes. This coupling-motion is substantially different from tertiary structure changes between the crystallographic structures of the T- and R-state. We found that hemoglobin''s allosteric mechanism of communication between subunits is equally based on hydrogen bonds and steric interactions. In addition, we were able to affect the T-to-R transition rates by choosing different histidine protonation states, thereby providing a possible atomistic explanation for the Bohr effect.     

Genetic Variation Underlying Sexual Behavior and Reproduction

Selection depletes additive genetic variation underlying traitsimportant in fitness. Intense mating competition and femalechoice may result in negligible heritability in males. Femalesoften appear to choose mates, however, suggesting genetic variationin males which is important to females. Evidence is reviewedon allelic substitutions, karyotypic variation, and especiallythe heritable variation of continuous traits involved in sexualbehavior and reproduction. Phenotypic variation in male matingspeed and courtship intensity, female mating and ovipositionbehavior, egg size and number, body size, parthenogenesis, andthe sex ratio generally have heritable variation. The maintenanceof genetic variation, and the meaning of heritability estimatesfor natural populations is considered.     

Statistical Computations Underlying the Dynamics of Memory Updating

Psychophysical and neurophysiological studies have suggested that memory is not simply a carbon copy of our experience: Memories are modified or new memories are formed depending on the dynamic structure of our experience, and specifically, on how gradually or abruptly the world changes. We present a statistical theory of memory formation in a dynamic environment, based on a nonparametric generalization of the switching Kalman filter. We show that this theory can qualitatively account for several psychophysical and neural phenomena, and present results of a new visual memory experiment aimed at testing the theory directly. Our experimental findings suggest that humans can use temporal discontinuities in the structure of the environment to determine when to form new memory traces. The statistical perspective we offer provides a coherent account of the conditions under which new experience is integrated into an old memory versus forming a new memory, and shows that memory formation depends on inferences about the underlying structure of our experience.     

Modeling the Underlying Dynamics of the Spread of Crime

The spread of crime is a complex, dynamic process that calls for a systems level approach. Here, we build and analyze a series of dynamical systems models of the spread of crime, imprisonment and recidivism, using only abstract transition parameters. To find the general patterns among these parameters—patterns that are independent of the underlying particulars—we compute analytic expressions for the equilibria and for the tipping points between high-crime and low-crime equilibria in these models. We use these expressions to examine, in particular, the effects of longer prison terms and of increased incarceration rates on the prevalence of crime, with a follow-up analysis on the effects of a Three-Strike Policy.     

条件化恐惧记忆消退的神经振荡机制

恐惧作为个体应对内外界危险因素形成的自我保护机制的一部分,在生物体的生存中发挥着重要作用.但过度的恐惧不仅对个体生存无益,反而易引发创伤后应激障碍、焦虑等精神疾病,严重影响个体生活质量.临床上通常采用基于行为学研究结果的暴露疗法对恐惧相关疾病进行治疗,然而在患者处于治疗环境之外的时候,上述症状经常会复发.因此,解析恐惧记忆相关神经环路内信息处理的神经机制,对于理解这些疾病的发生发展,寻求切实有效的治疗方案至关重要.大量研究表明与恐惧记忆消退相关的脑区主要涉及杏仁核、内侧前额叶和海马.在恐惧消退的过程中,这3个脑区表现出特定的神经振荡模式,而且这些活动也具有同步性,构成了恐惧记忆成功消退的神经基础.未来可利用基于神经神经振荡的无创性脑刺激手段干预恐惧记忆消退的神经环路,以促进恐惧记忆的消退并避免复发,为恐惧相关障碍的临床治疗提供重要的科学依据.     

Bistable Dynamics Underlying Excitability of Ion Homeostasis in Neuron Models

When neurons fire action potentials, dissipation of free energy is usually not directly considered, because the change in free energy is often negligible compared to the immense reservoir stored in neural transmembrane ion gradients and the long–term energy requirements are met through chemical energy, i.e., metabolism. However, these gradients can temporarily nearly vanish in neurological diseases, such as migraine and stroke, and in traumatic brain injury from concussions to severe injuries. We study biophysical neuron models based on the Hodgkin–Huxley (HH) formalism extended to include time–dependent ion concentrations inside and outside the cell and metabolic energy–driven pumps. We reveal the basic mechanism of a state of free energy–starvation (FES) with bifurcation analyses showing that ion dynamics is for a large range of pump rates bistable without contact to an ion bath. This is interpreted as a threshold reduction of a new fundamental mechanism of ionic excitability that causes a long–lasting but transient FES as observed in pathological states. We can in particular conclude that a coupling of extracellular ion concentrations to a large glial–vascular bath can take a role as an inhibitory mechanism crucial in ion homeostasis, while the pumps alone are insufficient to recover from FES. Our results provide the missing link between the HH formalism and activator–inhibitor models that have been successfully used for modeling migraine phenotypes, and therefore will allow us to validate the hypothesis that migraine symptoms are explained by disturbed function in ion channel subunits, pumps, and other proteins that regulate ion homeostasis.