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A Simple Reservoir Model of Working Memory with Real Values

International audiencePrefrontal cortex is known to be involved in many high-level cognitive functions, in particular working memory. Here, we study to what extent a group of randomly connected units can store and maintain (as output) an arbitrary real value from a streamed input, i.e. how such system act as a sustained working memory module without being distracted by the input stream. Furthermore, we explore to what extent such an architecture can take advantage of the stored value in order to produce non-linear computations. Systematic comparison between different architectures (with and without feedback, with and without a working memory unit) shows that explicit memory is required. With Principal Component Analyses (PCA) we show that the reservoir state is encoding time and the memorized value in different ways depending if a supplementary task is required. Moreover, theses memory states are similar to attractors in an input-driven system [3], and in particular, similar to a noisy line attractor [6]. In this study, we did not try to find the optimal number of reservoir units needed for each task. Conversely, we voluntary limited the size of the reservoir to 100 neurons in order to see if such rather small reservoirs were sufficiently competitive

Latent space exploration and functionalization of a gated working memory model using conceptors

International audienceIntroduction. Working memory is the ability to maintain and manipulate information. We introduce a method based on conceptors that allows us to manipulate information stored in the dynamics (latent space) of a gated working memory model. Methods. This latter model is based on a reservoir: a random recurrent network with trainable readouts. It is trained to hold a value in memory given an input stream when a gate signal is on and to maintain this information when the gate is off. The memorized information results in complex dynamics inside the reservoir that can be faithfully captured by a conceptor.Results. Such conceptors allow us to explicitly manipulate this information in order to perform various, but not arbitrary, operations. In this work, we show how working memory can be stabilized or discretized using such conceptors, how such conceptors can be linearly combined to form new memories, and how these conceptors can be extended to a functional role. Conclusion. These preliminary results suggest that conceptors can be used to manipulate the latent space of the working memory even though several results we introduce are not as intuitive as one would expect

Future roots for future soils

Mechanical impedance constrains root growth in most soils. Crop cultivation changed the impedance characteristics of native soils, through topsoil erosion, loss of organic matter, disruption of soil structure and loss of biopores. Increasing adoption of Conservation Agriculture in high-input agroecosystems is returning cultivated soils to the soil impedance characteristics of native soils, but in the low-input agroecosystems characteristic of developing nations, ongoing soil degradation is generating more challenging environments for root growth. We propose that root phenotypes have evolved to adapt to the altered impedance characteristics of cultivated soil during crop domestication. The diverging trajectories of soils under Conservation Agriculture and low-input agroecosystems have implications for strategies to develop crops to meet global needs under climate change. We present several root ideotypes as breeding targets under the impedance regimes of both high-input and low-input agroecosystems, as well as a set of root phenotypes that should be useful in both scenarios. We argue that a ‘whole plant in whole soil’ perspective will be useful in guiding the development of future crops for future soils

RGS12 Interacts with the SNARE-binding Region of the Ca v 2.2 Calcium Channel

Activation of GABAB receptors in chick dorsal root ganglion (DRG) neurons inhibits the Cav2.2 calcium channel in both a voltage-dependent and voltage-independent manner. The voltage-independent inhibition requires activation of a tyrosine kinase that phosphorylates the alpha1 subunit of the channel and thereby recruits RGS12, a member of the "regulator of G protein signaling" (RGS) proteins. Here we report that RGS12 binds to the SNARE-binding or "synprint" region (amino acids 726-985) in loop II-III of the calcium channel alpha1 subunit. A recombinant protein encompassing the N-terminal PTB domain of RGS12 binds to the synprint region in protein overlay and surface plasmon resonance binding assays; this interaction is dependent on tyrosine phosphorylation and yet is within a sequence that differs from the canonical NPXY motif targeted by other PTB domains. In electrophysiological experiments, microinjection of DRG neurons with synprint-derived peptides containing the tyrosine residue Tyr-804 altered the rate of desensitization of neurotransmitter-mediated inhibition of the Cav2.2 calcium channel, whereas peptides centered about a second tyrosine residue, Tyr-815, were without effect. RGS12 from a DRG neuron lysate was precipitated using synprint peptides containing phosphorylated Tyr-804. The high degree of conservation of Tyr-804 in the SNARE-binding region of Cav2.1 and Cav2.2 calcium channels suggests that this region, in addition to the binding of SNARE proteins, is also important for determining the time course of the modulation of calcium current via tyrosine phosphorylation

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions