Introduction. Modelling natural action selection

Action selection is the task of resolving conflicts between competing behavioural alternatives. This theme issue is dedicated to advancing our understanding of the behavioural patterns and neural substrates supporting action selection in animals, including humans. The scope of problems investigated includes: (i) whether biological action selection is optimal (and, if so, what is optimized), (ii) the neural substrates for action selection in the vertebrate brain, (iii) the role of perceptual selection in decision-making, and (iv) the interaction of group and individual action selection. A second aim of this issue is to advance methodological practice with respect to modelling natural action section. A wide variety of computational modelling techniques are therefore employed ranging from formal mathematical approaches through to computational neuroscience, connectionism and agent-based modelling. The research described has broad implications for both natural and artificial sciences. One example, highlighted here, is its application to medical science where models of the neural substrates for action selection are contributing to the understanding of brain disorders such as Parkinson's disease, schizophrenia and attention deficit/hyperactivity disorder.     

Cortical mechanisms of action selection: the affordance competition hypothesis

At every moment, the natural world presents animals with two fundamental pragmatic problems: selection between actions that are currently possible and specification of the parameters or metrics of those actions. It is commonly suggested that the brain addresses these by first constructing representations of the world on which to build knowledge and make a decision, and then by computing and executing an action plan. However, neurophysiological data argue against this serial viewpoint. In contrast, it is proposed here that the brain processes sensory information to specify, in parallel, several potential actions that are currently available. These potential actions compete against each other for further processing, while information is collected to bias this competition until a single response is selected. The hypothesis suggests that the dorsal visual system specifies actions which compete against each other within the fronto-parietal cortex, while a variety of biasing influences are provided by prefrontal regions and the basal ganglia. A computational model is described, which illustrates how this competition may take place in the cerebral cortex. Simulations of the model capture qualitative features of neurophysiological data and reproduce various behavioural phenomena.     

Biologically constrained action selection improves cognitive control in a model of the Stroop task

The Stroop task is a paradigmatic psychological task for investigating stimulus conflict and the effect this has on response selection. The model of Cohen et al. (Cohen et al. 1990 Psychol. Rev. 97, 332-361) has hitherto provided the best account of performance in the Stroop task, but there remains certain key data that it fails to match. We show that this failure is due to the mechanism used to perform final response selection-one based on the diffusion model of choice behaviour (Ratcliff 1978 Psychol. Rev. 85, 59-108). We adapt the model to use a selection mechanism which is based on the putative human locus of final response selection, the basal ganglia/thalamo-cortical complex (Redgrave et al. 1999 Neuroscience 89, 1009-1023). This improves the match to the core human data and, additionally, makes it possible for the model to accommodate, in a principled way, additional mechanisms of cognitive control that enable better fits to the data. This work prompts a critique of the diffusion model as a mechanism of response selection, and the features that any response mechanism must possess to provide adaptive action selection. We conclude that the consideration of biologically constrained solutions to the action selection problem is vital to the understanding and improvement of cognitive models of response selection.     

Transmission of the Subthalamic Nucleus Oscillatory Activity to the Cortex: A Computational Approach

Parkinsonian tremor is most likely due to oscillatory neuronal activities of central oscillators such as the subthalamic nucleus (STN)-external segment of the globus pallidus (GPe) pacemaker within the basal ganglia (BG). Activity from the central oscillator is proposed to be transmitted via transcortical pathways to the periphery. A computational model of the BG is proposed for simulating the transmission of the STN oscillatory activity to the cortex, based closely on known anatomy and physiology of the BG. According to the results of the simulation, for transmission of the STN oscillatory activity to the cortex, the STN oscillatory activity has to be transmitted simultaneously to the thalamus via STN-internal segment of the globus pallidus (GPi)-thalamus and STN-GPe-GPi-thalamus pathways. This transmission is controlled by the various factors such as the phase between the STN and GPe oscillatory activities, the STN oscillatory activity frequency, the low-threshold calcium spike bursts of the thalamus and the GPi spontaneous activity.     

Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system

The prefrontal cortex (PFC) has long been thought to serve as an 'executive' that controls the selection of actions and cognitive functions more generally. However, the mechanistic basis of this executive function has not been clearly specified often amounting to a homunculus. This paper reviews recent attempts to deconstruct this homunculus by elucidating the precise computational and neural mechanisms underlying the executive functions of the PFC. The overall approach builds upon existing mechanistic models of the basal ganglia (BG) and frontal systems known to play a critical role in motor control and action selection, where the BG provide a 'Go' versus 'NoGo' modulation of frontal action representations. In our model, the BG modulate working memory representations in prefrontal areas to support more abstract executive functions. We have developed a computational model of this system that is capable of developing human-like performance on working memory and executive control tasks through trial-and-error learning. This learning is based on reinforcement learning mechanisms associated with the midbrain dopaminergic system and its activation via the BG and amygdala. Finally, we briefly describe various empirical tests of this framework.     

Population genetic simulation: Benchmarking frameworks for non-standard models of natural selection

Population genetic simulation has emerged as a common tool for investigating increasingly complex evolutionary and demographic models. Software capable of handling high-level model complexity has recently been developed, and the advancement of tree sequence recording now allows simulations to merge the efficiency and genealogical insight of coalescent simulations with the flexibility of forward simulations. However, frameworks utilizing these features have not yet been compared and benchmarked. Here, we evaluate various simulation workflows using the coalescent simulator msprime and the forward simulator SLiM, to assess resource efficiency and determine an optimal simulation framework. Three aspects were evaluated: (1) the burn-in, to establish an equilibrium level of neutral diversity in the population; (2) the forward simulation, in which temporally fluctuating selection is acting; and (3) the final computation of summary statistics. We provide typical memory and computation time requirements for each step. We find that the fastest framework, a combination of coalescent and forward simulation with tree sequence recording, increases simulation speed by over twenty times compared to classical forward simulations without tree sequence recording, although it does require six times more memory. Overall, using efficient simulation workflows can lead to a substantial improvement when modelling complex evolutionary scenarios—although the optimal framework ultimately depends on the available computational resources.     

Coexistence and error propagation in pre-biotic vesicle models: a group selection approach

Compartmentalization of unlinked, competing templates is widely accepted as a necessary step towards the evolution of complex organisms. However, preservation of information by templates confined to isolated vesicles of finite size faces much harder obstacles than by free templates: random drift allied to mutation pressure wipe out any template that does not replicate perfectly, no matter how small the error probability might be. In addition, drift alone hinders the coexistence of distinct templates in a same compartment. Here, we investigate the conditions for group selection to prevail over drift and mutation and hence to guarantee the maintenance and coexistence of distinct templates in a vesicle. Group selection is implemented through a vesicle survival probability that depends on the template composition. By considering the limit case of an infinite number of vesicles, each one carrying a finite number of templates, we were able to derive a set of recursion equations for the frequencies of vesicles with different template compositions. Numerical iteration of these recursions allows the exact characterization of the steady state of the vesicle population-a quasispecies of vesicles-thus revealing the values of the mutation and group selection intensities for which template coexistence is possible. Within the main assumption of the model-a fixed, finite or infinite, number of vesicles-we find no fundamental impediment to the coexistence of an arbitrary number of template types with the same replication rate inside a vesicle, except of course for the vesicle capacity. Group selection in the form of vesicle selection is a must for compartmentalized primordial genetic systems even in the absence of intra-genomic competition of different templates.     

Variable selection in joint frailty models of recurrent and terminal events

Recurrent event data are commonly encountered in biomedical studies. In many situations, they are subject to an informative terminal event, for example, death. Joint modeling of recurrent and terminal events has attracted substantial recent research interests. On the other hand, there may exist a large number of covariates in such data. How to conduct variable selection for joint frailty proportional hazards models has become a challenge in practical data analysis. We tackle this issue on the basis of the “minimum approximated information criterion” method. The proposed method can be conveniently implemented in SAS Proc NLMIXED for commonly used frailty distributions. Its finite-sample behavior is evaluated through simulation studies. We apply the proposed method to model recurrent opportunistic diseases in the presence of death in an AIDS study.     

New insights into global biogeography,population structure and natural selection from the genome of the epipelagic copepod Oithona

In the epipelagic ocean, the genus Oithona is considered as one of the most abundant and widespread copepods and plays an important role in the trophic food web. Despite its ecological importance, little is known about Oithona and cyclopoid copepods genomics. Therefore, we sequenced, assembled and annotated the genome of Oithona nana. The comparative genomic analysis integrating available copepod genomes highlighted the expansions of genes related to stress response, cell differentiation and development, including genes coding Lin12‐Notch‐repeat (LNR) domain proteins. The Oithona biogeography based on 28S sequences and metagenomic reads from the Tara Oceans expedition showed the presence of O. nana mostly in the Mediterranean Sea (MS) and confirmed the amphitropical distribution of Oithona similis. The population genomics analyses of O. nana in the Northern MS, integrating the Tara Oceans metagenomic data and the O. nana genome, led to the identification of genetic structure between populations from the MS basins. Furthermore, 20 loci were found to be under positive selection including four missense and eight synonymous variants, harbouring soft or hard selective sweep patterns. One of the missense variants was localized in the LNR domain of the coding region of a male‐specific gene. The variation in the B‐allele frequency with respect to the MS circulation pattern showed the presence of genomic clines between O. nana and another undefined Oithona species possibly imported through Atlantic waters. This study provides new approaches and results in zooplankton population genomics through the integration of metagenomic and oceanographic data.     

Mutation,selection, and ancestry in branching models: a variational approach

We consider the evolution of populations under the joint action of mutation and differential reproduction, or selection. The population is modelled as a finite-type Markov branching process in continuous time, and the associated genealogical tree is viewed both in the forward and the backward direction of time. The stationary type distribution of the reversed process, the so-called ancestral distribution, turns out as a key for the study of mutation–selection balance. This balance can be expressed in the form of a variational principle that quantifies the respective roles of reproduction and mutation for any possible type distribution. It shows that the mean growth rate of the population results from a competition for a maximal long-term growth rate, as given by the difference between the current mean reproduction rate, and an asymptotic decay rate related to the mutation process; this tradeoff is won by the ancestral distribution. We then focus on the case when the type is determined by a sequence of letters (like nucleotides or matches/mismatches relative to a reference sequence), and we ask how much of the above competition can still be seen by observing only the letter composition (as given by the frequencies of the various letters within the sequence). If mutation and reproduction rates can be approximated in a smooth way, the fitness of letter compositions resulting from the interplay of reproduction and mutation is determined in the limit as the number of sequence sites tends to infinity. Our main application is the quasispecies model of sequence evolution with mutation coupled to reproduction but independent across sites, and a fitness function that is invariant under permutation of sites. In this model, the fitness of letter compositions is worked out explicitly. In certain cases, their competition leads to a phase transition.      

Phenotypic selection and response to selection in Lobularia maritima: importance of direct and correlational components of natural selection

By using selection differentials, gradients and structural equation modelling (SEM), I have quantified the phenotypic selection acting on Lobularia maritima (Cruciferae) flower size, display, colour and density, using data on lifetime female fitness. Furthermore, by analysing the resulting F₁ generation in field and greenhouse conditions, I estimated the actual intergenerational change in the value of these traits. Both pollinators preferred plants with many and large flowers. Strong directional selection for increased flower display was found in all years of the study, regardless of the technique used. Indirect selection due to a high significant correlation with flower display occurred on flower colour and size. SEM showed that pollinators played only a minor role in this observed phenotypic selection. The analysis of the phenotypes of F₁ plants showed that flower display actually increased across generations. In addition, white flowers were significantly more frequent in the offspring population than in the parental one, mostly due to the association between flower display and white coloured flowers. This suggests that both direct and indirect selection can play a role in the evolution of correlated traits in this crucifer.     

Polymorphism in heterogeneous environments,evolution of habitat selection and sympatric speciation: Soft and hard selection models

Summary The adaptation to a variable environment has been studied within soft and hard selection frameworks. It is shown that an epistatically determined habitat preference, following a Markovian process, always leads to the maintenance of an adaptive polymorphism, in a soft selection context. Although local mating does not alter the conditions for polymorphism maintenance, it is shown that, in that case, habitat selection also leads to the evolution of isolated reproductive units within each available habitat. Habitat selection, however, cannot evolve in the total absence of adaptive polymorphism. This represents a theoretical problem for all models assuming habitat selection to be an initially fixed trait, and means that within a soft selection framework, all the available habitats will be exploited, even the less favourable ones.On the other hand, polymorphism cannot be maintained when selection is hard, even when all individuals select their habitat. Here, the evolution of habitat selection does not need any prerequisite polymorphism, and always leads to the exploitation of only one habitat by the most specialized genotype. It appears then that hard selection can account for the existence of empty habitat and for an easier evolution of habitat specialization.     

The epidermal growth factor receptor and its ligands in female reproduction: insights from rodent models

Recent studies employing molecular, cellular, and whole organism approaches have identified the epidermal growth factor receptor (EGFR) and its ligands as key players in female reproductive functions. Gene expression studies demonstrated that the members of this family are expressed in a timely and spatially coordinated manner in different reproductive tissues. Manipulation of the EGFR system in rodent models by pharmacological or surgical means as well as elimination or overexpression of specific components of the EGFR system in genetically modified mice resulted in aberrant reproductive phenotypes, highlighting the physiological relevance of these molecules. This article summarizes the experimental evidence derived from rodent models, leading to our current understanding of the roles of the EGFR system in key steps of reproduction, such as ovulation, fertilization, embryo implantation, and the attainment of sexual maturity.     

New biomechanical model for clinical evaluation of the upper extremity motion in subjects with neurological disorders: an application case

Cervical spinal cord injury and acquired brain injury commonly imply a reduction in the upper extremity function which complicates, or even constrains, the performance of basic activities of daily living. Neurological rehabilitation in specialised hospitals is a common treatment for patients with neurological disorders. This study presents a practical methodology for the objective and quantitative evaluation of the upper extremity motion during an activity of daily living of those subjects. A new biomechanical model (with 10 rigid segments and 20 degrees of freedom) was defined to carry out kinematic, dynamic and energetic analyses of the upper extremity motion during a reaching task through data acquired by an optoelectronic system. In contrast to previous upper extremity models, the present model includes the analysis of the grasp motion, which is considered as crucial by clinicians. In addition to the model, we describe a processing and analysis methodology designed to present relevant summaries of biomechanical information to rehabilitation specialists. As an application case, the method was tested on a total of four subjects: three healthy subjects and one pathological subject suffering from cervical spinal cord injury. The dedicated kinematic, dynamic and energetic analyses for this particular case are presented. The resulting set of biomechanical measurements provides valuable information for clinicians to achieve a thorough understanding of the upper extremity motion, and allows comparing the motion of healthy and pathological cases.     

A novel mechanism for irregular firing of a neuron in response to periodic stimulation: irregularity in the absence of noise

Irregular firing of action potentials (AP's) is a characteristic feature of neurons in the brain. The variability has been attributed to noise from various sources. This study illustrates an alternative mechanism, namely, deterministic irregularity within a model of ionic conductances. Specifically, a model based on modern measurements of the Na⁺ and K⁺ current components from the squid giant axon fires irregularly in response to a continuous train of near-threshold current pulses. The interspike interval histogram from these simulations is multi-modal, a result which in other systems has been attributed to stochastic resonance. Moreover, the simulations exhibited short burst of spikes followed by relatively long quiescent periods, a result suggestive of patterned input to the model even though the input consisted of a train of regularly spaced current pulses. The variability of firing is attributable to variations in AP parameters, in particular AP amplitude. The action potential for squid giant axons is not all-or-none. Rather, it is fundamentally a continuous function of stimulus amplitude. That is, the membrane lacks a threshold. Variation in AP amplitude, and to a lesser extent, AP duration, can produce variations in the time to a subsequent AP, which represents a paradigm shift for understanding irregular neuronal firing. The emphasis is not as much on events prior to an AP as it is on the AP's themselves.     

Natural selection drives leaf divergence in experimental populations of Senecio lautus under natural conditions

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