The Influence of Markov Decision Process Structure on the Possible Strategic Use of Working Memory and Episodic Memory

Researchers use a variety of behavioral tasks to analyze the effect of biological manipulations on memory function. This research will benefit from a systematic mathematical method for analyzing memory demands in behavioral tasks. In the framework of reinforcement learning theory, these tasks can be mathematically described as partially-observable Markov decision processes. While a wealth of evidence collected over the past 15 years relates the basal ganglia to the reinforcement learning framework, only recently has much attention been paid to including psychological concepts such as working memory or episodic memory in these models. This paper presents an analysis that provides a quantitative description of memory states sufficient for correct choices at specific decision points. Using information from the mathematical structure of the task descriptions, we derive measures that indicate whether working memory (for one or more cues) or episodic memory can provide strategically useful information to an agent. In particular, the analysis determines which observed states must be maintained in or retrieved from memory to perform these specific tasks. We demonstrate the analysis on three simplified tasks as well as eight more complex memory tasks drawn from the animal and human literature (two alternation tasks, two sequence disambiguation tasks, two non-matching tasks, the 2-back task, and the 1-2-AX task). The results of these analyses agree with results from quantitative simulations of the task reported in previous publications and provide simple indications of the memory demands of the tasks which can require far less computation than a full simulation of the task. This may provide a basis for a quantitative behavioral stoichiometry of memory tasks

The Workshop on Animal Botulism in Europe

A workshop on animal botulism was held in Uppsala, Sweden, in June 2012. Its purpose was to explore the current status of the disease in Europe by gathering the European experts in animal botulism and to raise awareness of the disease among veterinarians and others involved in biopreparedness. Animal botulism is underreported and underdiagnosed, but an increasing number of reports, as well as the information gathered from this workshop, show that it is an emerging problem in Europe. The workshop was divided into 4 sessions: animal botulism in Europe, the bacteria behind the disease, detection and diagnostics, and European collaboration and surveillance. An electronic survey was conducted before the workshop to identify the 3 most needed discussion points, which were: prevention, preparedness and outbreak response; detection and diagnostics; and European collaboration and surveillance. The main conclusions drawn from these discussions were that there is an urgent need to replace the mouse bioassay for botulinum toxin detection with an in vitro test and that there is a need for a European network to function as a reference laboratory, which could also organize a European supply of botulinum antitoxin and vaccines. The foundation of such a network was discussed, and the proposals are presented here along with the outcome of discussions and a summary of the workshop itself

Shaping Embodied Neural Networks for Adaptive Goal-directed Behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves

NetMets: software for quantifying and visualizing errors in biological network segmentation

One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization

Functional Differences in the Backward Shifts of CA1 and CA3 Place Fields in Novel and Familiar Environments

Insight into the processing dynamics and other neurophysiological properties of different hippocampal subfields is critically important for understanding hippocampal function. In this study, we compared shifts in the center of mass (COM) of CA3 and CA1 place fields in a familiar and completely novel environment. Place fields in CA1 and CA3 were simultaneously recorded as rats ran along a closed loop track in a familiar room followed by a session in a completely novel room. This process was repeated each day over a 4-day period. CA3 place fields shifted backward (opposite to the direction of motion of the rat) only in novel environments. This backward shift gradually diminished across days, as the novel environment became more familiar with repeated exposures. Conversely, CA1 place fields shifted backward across all days in both familiar and novel environments. Prior studies demonstrated that CA1 place fields on average do not exhibit a backward shift during the first exposure to an environment in which the familiar cues are rearranged into a novel configuration, although CA3 place fields showed a strong backward shift. Under the completely novel conditions of the present study, no dissociation was observed between CA3 and CA1 during the first novel session (although a strong dissociation was observed in the familiar sessions and the later novel sessions). In summary, this is the first study to use simultaneous recordings in CA1 and CA3 to compare place field COM shift and other associated properties in truly novel and familiar environments. This study further demonstrates functional differentiation between CA1 and CA3 as the plasticity of CA1 place fields is affected differently by exposure to a completely novel environment in comparison to an altered, familiar environment, whereas the plasticity of CA3 place fields is affected similarly during both types of environmental novelty

Erratum to: Analysis of in vitro ADCC and clinical response to trastuzumab: possible relevance of Fc\u3b3RIIIA/Fc\u3b3RIIA gene polymorphisms and HER-2 expression levels on breast cancer cell lines

BACKGROUND: Trastuzumab is a humanized monoclonal antibody (mAb) currently used for the treatment of breast cancer (BC) patients with HER-2 overexpressing tumor subtype. Previous data reported the involvement of FcγRIIIA/IIA gene polymorphisms and/or antibody-dependent cellular cytotoxicity (ADCC) in the therapeutic efficacy of trastuzumab, although results on these issues are still controversial. This study was aimed to evaluate in vitro the functional relationships among FcγRIIIA/IIA polymorphisms, ADCC intensity and HER-2 expression on tumor target cells and to correlate them with response to trastuzumab. PATIENTS AND METHODS: Twenty-five patients with HER-2 overexpressing BC, receiving trastuzumab in a neoadjuvant (NEO) or metastatic (MTS) setting, were genotyped for the FcγRIIIA 158V>F and FcγRIIA 131H>R polymorphisms by a newly developed pyrosequencing assay and by multiplex Tetra-primer-ARMS PCR, respectively. Trastuzumab-mediated ADCC of patients’ peripheral blood mononuclear cells (PBMCs) was evaluated prior to therapy and measured by (51)Chromium release using as targets three human BC cell lines showing different levels of reactivity with trastuzumab. RESULTS: We found that the FcγRIIIA 158F and/or the FcγRIIA 131R variants, commonly reported as unfavorable in BC, may actually behave as ADCC favorable genotypes, in both the NEO (P ranging from 0.009 to 0.039 and from 0.007 to 0.047, respectively) and MTS (P ranging from 0.009 to 0.032 and P = 0.034, respectively) patients. The ADCC intensity was affected by different levels of trastuzumab reactivity with BC target cells. In this context, the MCF-7 cell line, showing the lowest reactivity with trastuzumab, resulted the most suitable cell line for evaluating ADCC and response to trastuzumab. Indeed, we found a statistically significant correlation between an increased frequency of patients showing ADCC of MCF-7 and complete response to trastuzumab in the NEO setting (P = 0.006). CONCLUSIONS: Although this study was performed in a limited number of patients, it would indicate a correlation of FcγR gene polymorphisms to the ADCC extent in combination with the HER-2 expression levels on tumor target cells in BC patients. However, to confirm our findings further experimental evidences obtained from a larger cohort of BC patients are mandatory. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-015-0680-0) contains supplementary material, which is available to authorized users

Sexual Conflict and Sexually Antagonistic Coevolution in an Annual Plant

BACKGROUND: Sexual conflict theory predicts sexually antagonistic coevolution of reproductive traits driven by conflicting evolutionary interests of two reproducing individuals. Most studies of the evolutionary consequences of sexual conflicts have, however, to date collectively investigated only a few species. In this study we used the annual herb Collinsia heterophylla to experimentally test the existence and evolutionary consequences of a potential sexual conflict over onset of stigma receptivity. METHODOLOGY/PRINCIPAL FINDINGS: We conducted crosses within and between four greenhouse-grown populations originating from two regions. Our experimental setup allowed us to investigate male-female interactions at three levels of geographic distances between interacting individuals. Both recipient and pollen donor identity affected onset of stigma receptivity within populations, confirming previous results that some pollen donors can induce stigma receptivity. We also found that donors were generally better at inducing stigma receptivity following pollen deposition on stigmas of recipients from another population than their own, especially within a region. On the other hand, we found that donors did worse at inducing stigma receptivity in crosses between regions. Interestingly, recipient costs in terms of lowered seed number after early fertilisation followed the same pattern: the cost was apparent only if the pollen donor belonged to the same region as the recipient. CONCLUSION/SIGNIFICANCE: Our results indicate that recipients are released from the cost of interacting with local pollen donors when crossed with donors from a more distant location, a pattern consistent with a history of sexually antagonistic coevolution within populations. Accordingly, sexual conflicts may have important evolutionary consequences also in plants

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates

Signaling pathway networks mined from human pituitary adenoma proteomics data

Abstract Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. Conclusions This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.</p