Redefining functional models of basal ganglia organisation: Role for the posteroventral pallidum in linguistic processing?

Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

Parameter setting and statistical learning

Three main models of parameter setting have been proposed: the Variational model proposed by Yang (2002; 2004), the Structured Acquisition model endorsed by Baker (2001; 2005), and the Very Early Parameter Setting (VEPS) model advanced by Wexler (1998). The VEPS model contends that parameters are set early. The Variational model supposes that children employ statistical learning mechanisms to decide among competing parameter values, so this model anticipates delays in parameter setting when critical input is sparse, and gradual setting of parameters. On the Structured Acquisition model, delays occur because parameters form a hierarchy, with higher-level parameters set before lower-level parameters. Assuming that children freely choose the initial value, children sometimes will miss-set parameters. However when that happens, the input is expected to trigger a precipitous rise in one parameter value and a corresponding decline in the other value. We will point to the kind of child language data that is needed in order to adjudicate among these competing models.

Geographic variation and positive selection on M7 lysin, an acrosomal sperm protein in mussels (Mytilus spp.)

Successful fertilization in free-spawning marine organisms depends on the interactions between genes expressed on the surfaces of eggs and sperm. Positive selection frequently characterizes the molecular evolution of such genes, raising the possibility that some common deterministic process drives the evolution of gamete recognition genes and may even be important for understanding the evolution of prezygotic isolation and speciation in the marine realm. One hypothesis is that gamete recognition genes are subject to selection for prezygotic isolation, namely reinforcement. In a previous study, positive selection on the gene coding for the acrosomal sperm protein M7 lysin was demonstrated among allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). Here, we expand sampling to include M7 lysin haplotypes from populations where mussel species are sympatric and hybridize to determine whether there is a pattern of reproductive character displacement, which would be consistent with reinforcement driving selection on this gene. We do not detect a strong pattern of reproductive character displacement; there are no unique haplotypes in sympatry nor is there consistently greater population structure in comparisons involving sympatric populations. One distinct group of haplotypes, however, is strongly affected by natural selection and this group of haplotypes is found within M. galloprovincialis populations throughout the Northern Hemisphere concurrent with haplotypes common to M. galloprovincialis and M. edulis. We suggest that balancing selection, perhaps resulting from sexual conflicts between sperm and eggs, maintains old allelic diversity within M. galloprovincialis.

A two-phase strategy for detecting recombination in nucleotide sequences

Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. Delineating recombination events is important in the study of molecular evolution, as inference of such events provides a clearer picture of the phylogenetic relationships among different gene sequences or genomes. Nevertheless, detecting recombination events can be a daunting task, as the performance of different recombination-detecting approaches can vary, depending on evolutionary events that take place after recombination. We previously evaluated the effects of post-recombination events on the prediction accuracy of recombination-detecting approaches using simulated nucleotide sequence data. The main conclusion, supported by other studies, is that one should not depend on a single method when searching for recombination events. In this paper, we introduce a two-phase strategy, applying three statistical measures to detect the occurrence of recombination events, and a Bayesian phylogenetic approach to delineate breakpoints of such events in nucleotide sequences. We evaluate the performance of these approaches using simulated data, and demonstrate the applicability of this strategy to empirical data. The two-phase strategy proves to be time-efficient when applied to large datasets, and yields high-confidence results.

Autoimmune Neurological Disease

This book provides a comprehensive and critical overview of the immunological aspects of autoimmune neurological disease. These diseases include common conditions such as multiple sclerosis, the Guillain–Barré syndrome and myasthenia gravis. The introductory chapters on antigen recognition and self–non-self discrimination, and on neuroimmunology, are followed by chapters on specific diseases. These are presented in a standardized format with sections on clinical features, genetics, neuropathology, pathophysiology, immunology and therapy. Each chapter has a concluding section which summarizes key points and suggests directions for future research. Animal models of autoimmune neurological disease are also covered in detail because of their importance in understanding the human diseases. The book is suitable for clinicians and neurologists managing patients with these diseases, and for immunologists, neuroscientists and neurologists investigating the pathogenesis and pathophysiology of these disorders.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Concordance between dispersal and mitochondrial gene flow: isolation by distance in a tropical teleost, Lates calcarifer (Australian barramundi)

Patterns of population subdivision and the relationship between gene flow and geographical distance in the tropical estuarine fish Lares calcarifer (Centropomidae) were investigated using mtDNA control region sequences. Sixty-three putative haplotypes were resolved from a total of 270 individuals from nine localities within three geographical regions spanning the north Australian coastline. Despite a continuous estuarine distribution throughout the sampled range, no haplotypes were shared among regions. However, within regions, common haplotypes were often shared among localities. Both sequence-based (average Phi(ST)=0.328) and haplotype-based (average Phi(ST)=0.182) population subdivision analyses indicated strong geographical structuring. Depending on the method of calculation, geographical distance explained either 79 per cent (sequence-based) or 23 per cent (haplotype-based) of the variation in mitochondrial gene flow. Such relationships suggest that genetic differentiation of L. calcarifer has been generated via isolation-by-distance, possibly in a stepping-stone fashion. This pattern of genetic structure is concordant with expectations based on the life history of L. calcarifer and direct studies of its dispersal patterns. Mitochondrial DNA variation, although generally in agreement with patterns of allozyme variation, detected population subdivision at smaller spatial scales. Our analysis of mtDNA variation in L. calcarifer confirms that population genetic models can detect population structure of not only evolutionary significance but also of demographic significance. Further, it demonstrates the power of inferring such structure from hypervariable markers, which correspond to small effective population sizes.

Building better wildlife-habitat models

Wildlife-habitat models are an important tool in wildlife management toda?, and by far the majority of these predict aspects of species distribution (abundance or presence) as a proxy measure of habitat quality. Unfortunately, few are tested on independent data, and of those that are, few show useful predictive st;ill. We demonstrate that six critical assumptions underlie distribution based wildlife-habitat models, all of which must be valid for the model to predict habitat quality. We outline these assumptions in a mete-model, and discuss methods for their validation. Even where all sis assumptions show a high level of validity, there is still a strong likelihood that the model will not predict habitat quality. However, the meta-model does suggest habitat quality can be predicted more accurately if distributional data are ignored, and variables more indicative of habitat quality are modelled instead.

Sustained gene expression in transplanted skin fibroblasts in rats

Retrovirus-mediated gene transfer into adult skin fibroblasts has provided measurable amounts of therapeutic proteins in animal models. However, the major problem emerging from these experiments was a limited time of vector encoded gene expression once transduced cells were engrafted We hypothesized that sustained transduced gene expression in quiescent fibroblasts in vivo might be obtained by using a fibronectin (Fn) promoter. Fibronectin plays a key role in cell adhesion, migration and wound healing and is up-regulated in quiescent fibroblasts. Retroviral vectors containing human adenosine deaminase (ADA) cDNA linked to rat fibronectin promoter (LNFnA) or viral LTR promoter (LASN) were compared for their ability to express ADA from transduced primary rat skin fibroblasts in vivo. Skin grafts formed from fibroblasts transduced with LNFnA showed strong human ADA enzyme activity from 1 week to 3 months. In contrast, skin grafts containing LASN-transduced fibroblasts tested positive for human ADA for weeks 1 and 2, were faintly positive at week 3 and showed no human ADA expression at 1, 2 and 3 months. Thus, a fibronectin promoter provided sustained transduced gene expression at high levels for at least 3 months in transplanted rat skin fibroblasts, perhaps permitting the targeting of this tissue for human gene therapy.