Identifying control ensembles for information processing within the cortico-basal ganglia-thalamic circuit

In situations featuring uncertainty about action-reward contingencies, mammals can flexibly adopt strategies for decision-making that are tuned in response to environmental changes. Although the cortico-basal ganglia thalamic (CBGT) network has been identified as contributing to the decision-making process, it features a complex synaptic architecture, comprised of multiple feed-forward, reciprocal, and feedback pathways, that complicate efforts to elucidate the roles of specific CBGT populations in the process by which evidence is accumulated and influences behavior. In this paper we apply a strategic sampling approach, based on Latin hypercube sampling, to explore how variations in CBGT network properties, including subpopulation firing rates and synaptic weights, map to variability of parameters in a normative drift diffusion model (DDM), representing algorithmic aspects of information processing during decision-making. Through the application of canonical correlation analysis, we find that this relationship can be characterized in terms of three low-dimensional control ensembles within the CBGT network that impact specific qualities of the emergent decision policy: responsiveness (a measure of how quickly evidence evaluation gets underway, associated with overall activity in corticothalamic and direct pathways), pliancy (a measure of the standard of evidence needed to commit to a decision, associated largely with overall activity in components of the indirect pathway of the basal ganglia), and choice (a measure of commitment toward one available option, associated with differences in direct and indirect pathways across action channels). These analyses provide mechanistic predictions about the roles of specific CBGT network elements in tuning the way that information is accumulated and translated into decision-related behavior.     

Developmental shifts in computations used to detect environmental controllability

Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior—exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8–25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants’ controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one’s benefit.     

Using all Gene Families Vastly Expands Data Available for Phylogenomic Inference

Traditionally, single-copy orthologs have been the gold standard in phylogenomics. Most phylogenomic studies identify putative single-copy orthologs using clustering approaches and retain families with a single sequence per species. This limits the amount of data available by excluding larger families. Recent advances have suggested several ways to include data from larger families. For instance, tree-based decomposition methods facilitate the extraction of orthologs from large families. Additionally, several methods for species tree inference are robust to the inclusion of paralogs and could use all of the data from larger families. Here, we explore the effects of using all families for phylogenetic inference by examining relationships among 26 primate species in detail and by analyzing five additional data sets. We compare single-copy families, orthologs extracted using tree-based decomposition approaches, and all families with all data. We explore several species tree inference methods, finding that identical trees are returned across nearly all subsets of the data and methods for primates. The relationships among Platyrrhini remain contentious; however, the species tree inference method matters more than the subset of data used. Using data from larger gene families drastically increases the number of genes available and leads to consistent estimates of branch lengths, nodal certainty and concordance, and inferences of introgression in primates. For the other data sets, topological inferences are consistent whether single-copy families or orthologs extracted using decomposition approaches are analyzed. Using larger gene families is a promising approach to include more data in phylogenomics without sacrificing accuracy, at least when high-quality genomes are available.     

Diversity of anaerobic gut fungal populations analysed using ribosomal ITS1 sequences in faeces of wild and domesticated herbivores

Gut fungal-specific PCR primers have been used to selectively amplify the ITS1 region of gut fungal rDNA recovered from faeces of domestic and wild animals to investigate population diversity. Two different gel-based methods are described for separating populations of gut fungal rDNA amplicons, namely (1) denaturing gradient gel electrophoresis (DGGE) and (2) separation according to small size differences using Spreadex, a proprietary matrix for electrophoresis. Gut fungal populations were characterised by analysis of rDNA in faeces of seventeen domesticated and ten wild herbivores. Sequences derived from these gel-based characterisations were analysed and classified using a hidden Markov model-based fingerprint matching algorithm. Faecal samples contained a broad spectrum of fungi and sequences from five of the six recognised genera were identified, including Cyllamyces, the most recently described gut fungal genus, which was found to be widely distributed in the samples. Furthermore, four other novel groupings of gut fungal sequences were identified that did not cluster with sequences from any of the previously described genera. Both gel- and sequence- based profiles for gut fungal populations suggested a lack of geographical restriction on occurrence of any individual fungal type.     

Zinc finger nucleases: custom-designed molecular scissors for genome engineering of plant and mammalian cells

Custom-designed zinc finger nucleases (ZFNs), proteins designed to cut at specific DNA sequences, are becoming powerful tools in gene targeting—the process of replacing a gene within a genome by homologous recombination (HR). ZFNs that combine the non-specific cleavage domain (N) of FokI endonuclease with zinc finger proteins (ZFPs) offer a general way to deliver a site-specific double-strand break (DSB) to the genome. The development of ZFN-mediated gene targeting provides molecular biologists with the ability to site-specifically and permanently modify plant and mammalian genomes including the human genome via homology-directed repair of a targeted genomic DSB. The creation of designer ZFNs that cleave DNA at a pre-determined site depends on the reliable creation of ZFPs that can specifically recognize the chosen target site within a genome. The (Cys₂His₂) ZFPs offer the best framework for developing custom ZFN molecules with new sequence-specificities. Here, we explore the different approaches for generating the desired custom ZFNs with high sequence-specificity and affinity. We also discuss the potential of ZFN-mediated gene targeting for ‘directed mutagenesis’ and targeted ‘gene editing’ of the plant and mammalian genome as well as the potential of ZFN-based strategies as a form of gene therapy for human therapeutics in the future.