scholarly journals Neural circuit function redundancy in brain disorders

2021 ◽  
Vol 70 ◽  
pp. 74-80
Author(s):  
Beatriz E.P. Mizusaki ◽  
Cian O'Donnell
2016 ◽  
Author(s):  
Cian O’Donnell ◽  
J. Tiago Gonçalves ◽  
Carlos Portera-Cailliau ◽  
Terrence J. Sejnowski

AbstractA leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this onedimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here we combined computational simulations with analysis of in vivo 2-photon Ca2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: 1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; 2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; 3) The direction of circuit alterations in Fmr1 KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher-dimensional models that can better capture the multidimensional computational functions of neural circuits.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Cian O'Donnell ◽  
J Tiago Gonçalves ◽  
Carlos Portera-Cailliau ◽  
Terrence J Sejnowski

A leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this one-dimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here, we combined computational simulations with analysis of in vivo two-photon Ca2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: (1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; (2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; (3) The direction of circuit alterations in Fmr1 KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher dimensional models that can better capture the multidimensional computational functions of neural circuits.


2019 ◽  
Author(s):  
Manxiu Ma ◽  
Alexandro D. Ramirez ◽  
Tong Wang ◽  
Rachel L. Roberts ◽  
Katherine E. Harmon ◽  
...  

AbstractDown Syndrome Cell Adhesion Molecules (dscam and dscaml1) are essential regulators of neural circuit assembly, but their roles in vertebrate neural circuit function are still mostly unexplored. We investigated the role of dscaml1 in the zebrafish oculomotor system, where behavior, circuit function, and neuronal activity can be precisely quantified. Loss of zebrafish dscaml1 resulted in deficits in retinal patterning and light adaptation, consistent with its known roles in mammals. Oculomotor analyses showed that mutants have abnormal gaze stabilization, impaired fixation, disconjugation, and faster fatigue. Notably, the saccade and fatigue phenotypes in dscaml1 mutants are reminiscent of human ocular motor apraxia, for which no animal model exists. Two-photon calcium imaging showed that loss of dscaml1 leads to impairment in the saccadic premotor pathway but not the pretectum-vestibular premotor pathway, indicating a subcircuit requirement for dscaml1. Together, we show that dscaml1 has both broad and specific roles in oculomotor circuit function, providing a new animal model to investigate the development of premotor pathways and their associated human ocular disorders.


2018 ◽  
Author(s):  
Dika A. Kuljis ◽  
Khaled Zemoura ◽  
Cheryl A. Telmer ◽  
Jiseok Lee ◽  
Eunsol Park ◽  
...  

AbstractAnatomical methods for determining cell-type specific connectivity are essential to inspire and constrain our understanding of neural circuit function. We developed new genetically-encoded reagents for fluorescence-synapse labeling and connectivity analysis in brain tissue, using a fluorogen-activating protein (FAP)-or YFP-coupled, postsynaptically-localized neuroligin-1 targeting sequence (FAP/YFPpost). Sparse viral expression of FAP/YFPpost with the cell-filling, red fluorophore dTomato (dTom) enabled high-throughput, compartment-specific localization of synapses across diverse neuron types in mouse somatosensory cortex. High-resolution confocal image stacks of virally-transduced neurons were used for 3D reconstructions of postsynaptic cells and automated detection of synaptic puncta. We took advantage of the bright, far-red emission of FAPpost puncta for multichannel fluorescence alignment of dendrites, synapses, and presynaptic neurites to assess subtype-specific inhibitory connectivity onto L2 neocortical pyramidal (Pyr) neurons. Quantitative and compartment-specific comparisons show that PV inputs are the dominant source of inhibition at both the soma and across all dendritic branches examined and were particularly concentrated at the primary apical dendrite, a previously unrecognized compartment of L2 Pyr neurons. Our fluorescence-based synapse labeling reagents will facilitate large-scale and cell-type specific quantitation of changes in synaptic connectivity across development, learning, and disease states.


2019 ◽  
Vol 116 (47) ◽  
pp. 23783-23789 ◽  
Author(s):  
Igor Delvendahl ◽  
Katarzyna Kita ◽  
Martin Müller

Animal behavior is remarkably robust despite constant changes in neural activity. Homeostatic plasticity stabilizes central nervous system (CNS) function on time scales of hours to days. If and how CNS function is stabilized on more rapid time scales remains unknown. Here, we discovered that mossy fiber synapses in the mouse cerebellum homeostatically control synaptic efficacy within minutes after pharmacological glutamate receptor impairment. This rapid form of homeostatic plasticity is expressed presynaptically. We show that modulations of readily releasable vesicle pool size and release probability normalize synaptic strength in a hierarchical fashion upon acute pharmacological and prolonged genetic receptor perturbation. Presynaptic membrane capacitance measurements directly demonstrate regulation of vesicle pool size upon receptor impairment. Moreover, presynaptic voltage-clamp analysis revealed increased Ca2+-current density under specific experimental conditions. Thus, homeostatic modulation of presynaptic exocytosis through specific mechanisms stabilizes synaptic transmission in a CNS circuit on time scales ranging from minutes to months. Rapid presynaptic homeostatic plasticity may ensure stable neural circuit function in light of rapid activity-dependent plasticity.


Author(s):  
Carolina Gutierrez Herrera ◽  
Antoine Adamantidis ◽  
Feng Zhang ◽  
Karl Deisseroth ◽  
Luis de Lecea

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160258 ◽  
Author(s):  
Gina G. Turrigiano

It has become widely accepted that homeostatic and Hebbian plasticity mechanisms work hand in glove to refine neural circuit function. Nonetheless, our understanding of how these fundamentally distinct forms of plasticity compliment (and under some circumstances interfere with) each other remains rudimentary. Here, I describe some of the recent progress of the field, as well as some of the deep puzzles that remain. These include unravelling the spatial and temporal scales of different homeostatic and Hebbian mechanisms, determining which aspects of network function are under homeostatic control, and understanding when and how homeostatic and Hebbian mechanisms must be segregated within neural circuits to prevent interference. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.


2018 ◽  
Vol 120 (2) ◽  
pp. 854-866 ◽  
Author(s):  
Sarah E. V. Richards ◽  
Stephen D. Van Hooser

Circuit operations are determined jointly by the properties of the circuit elements and the properties of the connections among these elements. In the nervous system, neurons exhibit diverse morphologies and branching patterns, allowing rich compartmentalization within individual cells and complex synaptic interactions among groups of cells. In this review, we summarize work detailing how neuronal morphology impacts neural circuit function. In particular, we consider example neurons in the retina, cerebral cortex, and the stomatogastric ganglion of crustaceans. We also explore molecular coregulators of morphology and circuit function to begin bridging the gap between molecular and systems approaches. By identifying motifs in different systems, we move closer to understanding the structure-function relationships that are present in neural circuits.


2021 ◽  
Author(s):  
Nada Y. Abdelrahman ◽  
Eleni Vasilaki ◽  
Andrew C. Lin

AbstractNeural circuits use homeostatic compensation to achieve consistent behaviour despite variability in underlying intrinsic and network parameters. However, it remains unclear how compensation regulates variability across a population of the same type of neurons within an individual, and what computational benefits might result from such compensation. We address these questions in the Drosophila mushroom body, the fly’s olfactory memory center. In a computational model, we show that memory performance is degraded when the mushroom body’s principal neurons, Kenyon cells (KCs), vary realistically in key parameters governing their excitability, because the resulting inter-KC variability in average activity levels makes odor representations less separable. However, memory performance is rescued while maintaining realistic variability if parameters compensate for each other to equalize KC average activity. Such compensation can be achieved through both activity-dependent and activity-independent mechanisms. Finally, we show that correlations predicted by our model’s compensatory mechanisms appear in the Drosophila hemibrain connectome. These findings reveal compensatory variability in the mushroom body and describe its computational benefits for associative memory.Significance statementHow does variability between neurons affect neural circuit function? How might neurons behave similarly despite having different underlying features? We addressed these questions in neurons called Kenyon cells, which store olfactory memories in flies. Kenyon cells differ among themselves in key features that affect how active they are, and in a model of the fly’s memory circuit, adding this inter-neuronal variability made the model fly worse at learning the values of multiple odors. However, memory performance was rescued if compensation between the variable underlying features allowed Kenyon cells to be equally active on average, and we found the hypothesized compensatory variability in real Kenyon cells’ anatomy. This work reveals the existence and computational benefits of compensatory variability in neural networks.


Sign in / Sign up

Export Citation Format

Share Document