The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor.
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ABSTRACT:
SUBMITTER: Turner-Evans DB
PROVIDER: S-EPMC8356802 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Neural representations of head direction (HD) have been discovered in many species. Theoretical work has proposed that the dynamics associated with these representations are generated, maintained, and updated by recurrent network structures called ring attractors. We evaluated this theorized structure-function relationship by performing electron microscopy-based circuit reconstruction and RNA profiling of identified cell types in the HD system of Drosophila melanogaster. We identified motifs that have been hypothesized to maintain the HD representation in darkness, update it when the animal turns, and tether it to visual cues. Functional studies provided support for the proposed roles of individual excitatory or inhibitory circuit elements in shaping activity. We also discovered recurrent connections between neuronal arbors with mixed pre- and post-synaptic specializations. Our results confirm that the Drosophila HD network contains the core components of a ring attractor while also revealing unpredicted structural features that might enhance the network’s computational power.
2020-09-14 | GSE155329 | GEO
Project description:The neuroanatomical ultrastructure and function of a biological ring attractor
| PRJNA649419 | ENA
Project description:Effective cue integration is essential for an animal's survival. The ring attractor network has emerged as a powerful framework for understanding how animals seamlessly integrate various cues. This network not only elucidates neural dynamics within the brain, especially in spatial encoding systems like the heading direction (HD) system, but also sheds light on cue integration within decision-making processes. Yet, many significant phenomena across different fields lack clear explanations. For instance, in physiology, the integration mechanism of Drosophila's compass neuron when confronted with conflicting self-motion cues and external sensory cues with varying gain control settings is not well elucidated. Similarly, in ethology, the decision-making system shows Bayesian integration (BI) under minimal cue conflicts, but shifts to a winner-take-all (WTA) mode as conflicts surpass a certain threshold. To address these gaps, we introduce a ring attractor network with asymmetrical neural connections and synaptic dynamics in this paper. A thorough series of simulations has been conducted to assess its ability to track external cues and integrate conflicting cues. The results from these simulations demonstrate that the proposed model replicates observed neural dynamics and offers a framework for modeling biologically plausible cue integration behaviors. Furthermore, our findings yield several testable predictions that could inform future neuroethological research, providing insights into the role of ring attractor dynamics in the animal brain.
| S-EPMC11365315 | biostudies-literature
Project description:Structural MRI allows unparalleled in vivo study of the anatomy of the developing human brain. For more than two decades, MRI research has revealed many new aspects of this multifaceted maturation process, significantly augmenting scientific knowledge gathered from postmortem studies. Postnatal brain development is notably protracted and involves considerable changes in cerebral cortical, subcortical, and cerebellar structures, as well as significant architectural changes in white matter fiber tracts (see [12]). Although much work has described isolated features of neuroanatomical development, it remains a critical challenge to characterize the multidimensional nature of brain anatomy, capturing different phases of development among individuals. Capitalizing on key advances in multisite, multimodal MRI, and using cross-validated nonlinear modeling, we demonstrate that developmental brain phase can be assessed with much greater precision than has been possible using other biological measures, accounting for more than 92% of the variance in age. Further, our composite metric of morphology, diffusivity, and signal intensity shows that the average difference in phase among children of the same age is only about 1 year, revealing for the first time a latent phenotype in the human brain for which maturation timing is tightly controlled.
| S-EPMC3461087 | biostudies-literature
Project description: Not available
| S-EPMC10501606 | biostudies-literature
Project description:Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading in flies, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.
| S-EPMC9286743 | biostudies-literature
Project description:Decreased insulin availability and high blood glucose levels, the hallmark features of poorly controlled diabetes, drive disease progression and are associated with decreased skeletal muscle mass. We have shown that mice with -cell dysfunction and normal insulin sensitivity have decreased skeletal muscle mass. This project asks how insulin deficiency impacts on the structure and function of the remaining skeletal muscle in these animals. Methods: Skeletal muscle function was determined by measuring exercise capacity and specific muscle strength prior to and after insulin supplementation for 28 days in 12-week-old mice with conditional -cell deletion of the ATP binding cassette transporters ABCA1 and ABCG1 (β-DKO mice). Abca1 and Abcg1 floxed (fl/fl) mice were used as controls. RNAseq was used to quantify changes in transcripts in soleus and extensor digitorum longus muscles. Skeletal muscle and mitochondrial morphology were assessed by transmission electron microscopy. Myofibrillar Ca2+ sensitivity and maximum isometric single muscle fibre force were assessed using MyoRobot biomechatronics technology. Results: RNA transcripts were significantly altered in β-DKO mice compared to fl/fl controls (32 in extensor digitorum longus and 412 in soleus). Exercise capacity and muscle strength were significantly decreased in β-DKO mice compared to fl/fl controls (p = 0.012), and a loss of structural integrity was also observed in skeletal muscle from the β-DKO mice. Supplementation of β-DKO mice with insulin restored muscle integrity, strength and expression of 13 and 16 of the dysregulated transcripts in and extensor digitorum longus and soleus muscles, respectively. Conclusions: Insulin insufficiency due to -cell dysfunction perturbs the structure and function of skeletal muscle. These adverse effects are rectified by insulin supplementation.
2023-09-26 | E-MTAB-13315 | biostudies-arrayexpress
Project description:The autoassociative memory model of hippocampal field CA3 postulates that Hebbian associations among external input features produce attractor states embedded in a recurrent synaptic matrix. In contrast, the attractor-map model postulates that a two-dimensional continuum of attractor states is preconfigured in the network during development and that transitions among these states are governed primarily by self-motion information ("path-integration"), giving rise to the strong spatial characteristic of hippocampal activity. In this model, learned associations between "coordinates" on the attractor map and external cues can result in abrupt jumps between states, in the case of mismatches between the current input and previous associations between internal coordinates and external landmarks. Both models predict attractor dynamics, but for fundamentally different reasons; however, the two models are not a priori mutually exclusive. We contrasted these two models by comparing the dynamics of state transitions when two previously learned environmental shapes were morphed between their endpoints, in animals that had first experienced the environments either at the same location, or at two different locations, connected by a passageway through which they walked. As predicted from attractor-map theory, the latter animals expressed abrupt transitions between representations at the midpoint of the morph series. Contrary to the predictions of autoassociation theory, the former group expressed no evidence of attractor dynamics during the morph series; there was only a gradual transition between endpoints. The results of this critical test thus cast the autoassociator theory for CA3 into doubt and indicate the need for a new theory for this structure.
| S-EPMC2904215 | biostudies-literature
Project description:BackgroundThe experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity.Methodology/principal findingsIn order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network.Conclusions/significanceWe have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed.
| S-EPMC3598861 | biostudies-literature
Project description:Ralstonia solanacearum is the causal agent of bacterial wilt. Arabidopsis thaliana monogenic resistance to the strain GMI1000 is conferred by the RRS1-R gene, present in the resistant ecotype ND-1 and absent in the susceptible ecotype Col-0. The corresponding protein is recognized by the avirulence protein PopP2 of R. solanacearum. In order to identify the plant proteins involved in the PopP2/RRS1-R perception complex, the screening of a root cDNA library in yeast was performed using PopP2 as bait. One interactor found was called Pip3, and we would like to better understand its biological function. Thereby we choose to compare two RNAi lines with their wild type Nd-1 background, and one KO line with its wild type Col-0 background. Also, two overexpressor lines will be compared with their wilt type Nd-1 background and two with their Col-0 background. 27 samples were used in this experiment.
2009-12-09 | E-GEOD-19273 | biostudies-arrayexpress