Matthew Hartley

Local chromatin environment of a Polycomb target gene instructs its own epigenetic inheritance

Inheritance of gene expression states is fundamental for cells to ‘remember’ past events, such as environmental or developmental cues. The conserved Polycomb Repressive Complex 2 (PRC2) maintains epigenetic repression of many genes in animals and plants and modifies chromatin at its targets. Histones modified by PRC2 can be inherited through cell division. However, it remains unclear whether this inheritance can direct long-term memory of individual gene expression states (cis memory) or instead if local chromatin states are dictated by the concentrations of diffusible factors (trans memory). By monitoring the expression of two copies of the Arabidopsis Polycomb target gene FLOWERING LOCUS C (FLC) in the same plants, we show that one copy can be repressed while the other is active. Furthermore, this ‘mixed’ expression state is inherited through many cell divisions as plants develop. These data demonstrate that epigenetic memory of FLC expression is stored not in trans but in cis. DOI: http://dx.doi.org/10.7554/eLife.07205.001

2006 Special Issue: Attention as a controller

We investigate, by constructing suitable models, the manner in which attention and executive function are observed to interact, including some aspects of the influence of value/emotion on this interaction. Attention is modelled using the recent engineering control model (Corollary Discharge of Attention Movement, CODAM), which includes suitable working memory components. We extend this model to take account of various executive functions performed in working memory under attention control, such as rehearsal, substitution and transformation of buffered activity. How these are achieved is specified in suitable extension of CODAM. Further extensions are then made to include emotional values of stimuli. All of these extensions are supported by recent experimental brain imaging data on various working memory tasks, which are simulated with reasonable accuracy. We conclude our analysis by a discussion on the nature of cognition as seen in terms of the resulting extended attention model framework.

Distinct phases of Polycomb silencing to hold epigenetic memory of cold in Arabidopsis

A multifactorial strategy establishes and maintains repressive chromatin marks in plants in response to environmental signals. Managing gene silencing through replication Vernalization is the process in plants by which wintertime chill stimulates springtime flowering. Yang et al. and Jiang et al. show how chill is recorded in Arabidopsis epigenetically by methylation of histones. Specialized components of the Polycomb group of proteins remodel DNA to establish the methylation marks and are linked to DNA replication. Long-term stable epigenetic status follows rapid establishment of metastable epigenetic marks. This epigenetic strategy may be key to the developmental requirement of both secure and nimble fate decisions, allowing plant cells to change fates. Science, this issue p. 1142 and p. 1146 Gene silencing by Polycomb complexes is central to eukaryotic development. Cold-induced epigenetic repression of FLOWERING LOCUS C (FLC) in the plant Arabidopsis provides an opportunity to study initiation and maintenance of Polycomb silencing. Here, we show that a subset of Polycomb repressive complex 2 factors nucleate silencing in a small region within FLC, locally increasing H3K27me3 levels. This nucleation confers a silenced state that is metastably inherited, with memory held in the local chromatin. Metastable memory is then converted to stable epigenetic silencing through separate Polycomb factors, which spread across the locus after cold to enlarge the domain that contains H3K27me3. Polycomb silencing at FLC thus has mechanistically distinct phases, which involve specialization of distinct Polycomb components to deliver first metastable then long-term epigenetic silencing.

Occlusion, attention and object representations

Occlusion is currently at the centre of analysis in machine vision. We present an approach to it that uses attention feedback to an occluded object to obtain its correct recognition. Various simulations are performed using a hierarchical visual attention feedback system, based on contrast gain (which we discuss as to its relation to possible hallucinations that could be caused by feedback). We then discuss implications of our results for object representations per se.

Understanding spike-time-dependent plasticity: A biologically motivated computational model

Abstract Long-term synaptic plasticity underlies many important learning processes in the brain. Recent physiological data have shown that the precise relative timings of pre- and post-synaptic neuron firings at a synapse determine both the direction of certain types of modification (potentiation or depression), and magnitude of this modification. We propose a neurophysiological mechanism by which this spike-time-dependent plasticity (STDP) could arise, and support this hypothesis using a model involving calcium dynamics. We show that, in addition to reproducing experimental data for paired spikes, the model can explain differences in experimentally observed STDP forms. We also demonstrate that the model provides a good match to recent data for the triplet and quadruplet paradigms, and that a simulated network of reciprocally connected neurons using this learning rule can store and recall a simple temporal sequence. In conclusion we make predictions from the model both on the plasticity effects of quadruple spike interactions and manipulations of concentrations of components involved at the synapse.

A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning

We present a neural network software architecture, guided by that of the human and more generally primate brain, for the construction of an autonomous cognitive system (which we have named GNOSYS). GNOSYS is created so as to be able to attend to stimuli, to conceptualise them, to learn their predicted reward value and reason about them so as to attain those stimuli in the environment with greatest predicted value. We apply this software system to an embodied version in a robot, and describe the activities in the various component modules of GNOSYS, as well as the overall results. We briefly compare our system with some others proposed to have cognitive powers, and finish by discussion of future developments we propose for our system, as well as expanding on the arguments for and against our approach to creating such a software system.

A method for detecting single mRNA molecules in Arabidopsis thaliana

BackgroundDespite advances in other model organisms, there are currently no techniques to explore cell-to-cell variation and sub-cellular localization of RNA molecules at the single-cell level in plants.ResultsHere we describe a method for imaging individual mRNA molecules in Arabidopsis thaliana root cells using multiple singly labeled oligonucleotide probes. We demonstrate detection of both mRNA and nascent transcripts of the housekeeping gene Protein Phosphatase 2A. Our image analysis pipeline also enables quantification of mRNAs that reveals the frequency distribution of transcripts per cell underlying the population mean.ConclusionThis method allows single molecule RNA in situ to be exploited as a powerful tool for studying gene regulation in plants.

Attention as sigma-pi controlled ACh-based feedback

We analyse experimental data on attention to indicate that any attention feedback control signals to lower order cortical sites will lead to a quadratic sigma-pi form of output in its dependence on the lower-order input and the feedback signal. The manner by which this structure works is shown by a brief simulation. We then discuss how such a structure could arise from the action of diffuse acetylcholine signals from the NBM, especially involving nicotinic receptors. We deduce certain structural regularities which should be expected both at local-and at micro-circuit level, mainly in cortical layer V (the output layer).

Coding of objects in low-level visual cortical areas

We develop a neural network architecture to help model the creation of visual temporal object representations. We take visual input to be hard-wired up to and including V1 (as an orientation-filtering system). We then develop architectures for afferents to V2 and thence to V4, both of which are trained by a causal Hebbian law. We use an incremental approach, using sequences of increasingly complex stimuli at an increasing level of the hierarchy. The V2 representations are shown to encode angles, and V4 is found sensitive to shapes embedded in figures. These results are compared to recent experimental data, supporting the incremental training scheme and associated architecture.

jicbioimage: a tool for automated and reproducible bioimage analysis

There has been steady improvement in methods for capturing bioimages. However analysing these images still remains a challenge. The Python programming language provides a powerful and flexible environment for scientific computation. It has a wide range of supporting libraries for image processing but lacks native support for common bioimage formats, and requires specific code to be written to ensure that suitable audit trails are generated and analyses are reproducible. Here we describe the development of a Python tool that: (1) allows users to quickly view and explore microscopy data; (2) generate reproducible analyses, encoding a complete history of image transformations from raw data to final result; and (3) scale up analyses from initial exploration to high throughput processing pipelines, with a minimal amount of extra effort. The tool, jicbioimage, is open source and freely available online at http://jicbioimage.readthedocs.io.