scholarly journals Addition of new neurons and the emergence of a local neural circuit for precise timing

2021 ◽  
Vol 17 (3) ◽  
pp. e1008824
Author(s):  
Yevhen Tupikov ◽  
Dezhe Z. Jin
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Extended Period ◽  
Projection Neurons ◽  
Feedforward Network ◽  
Precise Timing ◽  
Self Organized ◽  
Mature Neurons ◽  
Song Development ◽  
Local Brain

During development, neurons arrive at local brain areas in an extended period of time, but how they form local neural circuits is unknown. Here we computationally model the emergence of a network for precise timing in the premotor nucleus HVC in songbird. We show that new projection neurons, added to HVC post hatch at early stages of song development, are recruited to the end of a growing feedforward network. High spontaneous activity of the new neurons makes them the prime targets for recruitment in a self-organized process via synaptic plasticity. Once recruited, the new neurons fire readily at precise times, and they become mature. Neurons that are not recruited become silent and replaced by new immature neurons. Our model incorporates realistic HVC features such as interneurons, spatial distributions of neurons, and distributed axonal delays. The model predicts that the birth order of the projection neurons correlates with their burst timing during the song.

scholarly journals Addition of new neurons and the emergence of a local neural circuit for precise timing

2020 ◽  
Author(s):  
Yevhen Tupikov ◽  
Dezhe Z. Jin
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Extended Period ◽  
Song Learning ◽  
Projection Neurons ◽  
Precise Timing ◽  
Self Organized ◽  
Immature Neurons ◽  
Mature Neurons ◽  
Local Brain

AbstractDuring development, neurons arrive at local brain areas in extended period of time, but how they form local neural circuits is unknown. Here we computationally model the emergence of a network for precise timing in the premotor nucleus HVC in songbird. We show that new motor projection neurons, mostly added to HVC before and during song learning, are recruited to the end of a growing feedforward network. High spontaneous activity of new neurons makes them the prime targets for recruitment in a self-organized process via synaptic plasticity. Once recruited, the new neurons fire readily at precise times, and they become mature. Neurons that are not recruited become silent and replaced by new immature neurons. Our model incorporates realistic HVC features such as interneurons, spatial distributions of neurons, and distributed axonal delays. The model predicts that the birth order of the projection neurons correlates with their burst timing during the song.Significance StatementFunctions of local neural circuits depend on their specific network structures, but how the networks are wired is unknown. We show that such structures can emerge during development through a self-organized process, during which the network is wired by neuron-by-neuron recruitment. This growth is facilitated by steady supply of immature neurons, which are highly excitable and plastic. We suggest that neuron maturation dynamics is an integral part of constructing local neural circuits.

scholarly journals AAV11 permits efficient retrograde targeting of projection neurons

2022 ◽  
Author(s):  
Zengpeng Han ◽  
Nengsong Luo ◽  
Jiaxin Kou ◽  
Lei Li ◽  
Wenyu Ma ◽  
...  
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Brain Area ◽  
Brain Diseases ◽  
Projection Neurons ◽  
Recording Technology ◽  
Neural Connections ◽  
Host Immune Responses ◽  
Promising Tool ◽  
High Level

Viral tracers that permit efficient retrograde targeting of projection neurons are powerful vehicles for structural and functional dissections of the neural circuit and for the treatment of brain diseases. Recombinant adeno-associated viruses (rAAVs) are the most potential candidates because they are low-toxic with high-level transgene expression and minimal host immune responses. Currently, some rAAVs based on capsid engineering for retrograde tracing have been widely used in the analysis and manipulation of neural circuits, but suffer from brain area selectivity and inefficient retrograde transduction in certain neural connections. Here, we discovered that the recombinant adeno-associated virus 11 (rAAV11) exhibits potent retrograde labeling of projection neurons with enhanced efficiency to rAAV2-retro in some neural connections. Combined with calcium recording technology, rAAV11 can be used to monitor neuronal activities by expressing Cre recombinase or calcium-sensitive functional probe. In addition, we further showed the suitability of rAAV11 for astrocyte targeting. These properties make rAAV11 a promising tool for the mapping and manipulation of neural circuits and gene therapy of some neurological and neurodegenerative disorders.

scholarly journals Oscillatory integration windows in neurons

2016 ◽  
Author(s):  
Nitin Gupta ◽  
Swikriti Saran Singh ◽  
Mark Stopfer
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Field Potential ◽  
Coincidence Detection ◽  
Uniform Structure ◽  
Detection Mechanism ◽  
Oscillation Frequencies ◽  
Local Field Potential Lfp ◽  
Oscillatory Cycle

AbstractOscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly tested this idea in the locust olfactory system. We found that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we found that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrated that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking.

scholarly journals Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective

2019 ◽  
Author(s):  
Samantha Hughes ◽  
Tansu Celikel
Keyword(s):  
Motor Neurons ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Sensory Information ◽  
Circuit Complexity ◽  
Inhibitory Circuits ◽  
Invertebrate Species ◽  
Gating Mechanism ◽  
Motor Actions ◽  
Sensorimotor Representations

From single-cell organisms to complex neural networks, all evolved to provide control solutions to generate context and goal-specific actions. Neural circuits performing sensorimotor computation to drive navigation employ inhibitory control as a gating mechanism, as they hierarchically transform (multi)sensory information into motor actions. Here, we focus on this literature to critically discuss the proposition that prominent inhibitory projections form sensorimotor circuits. After reviewing the neural circuits of navigation across various invertebrate species, we argue that with increased neural circuit complexity and the emergence of parallel computations inhibitory circuits acquire new functions. The contribution of inhibitory neurotransmission for navigation goes beyond shaping the communication that drives motor neurons, instead, include encoding of emergent sensorimotor representations. A mechanistic understanding of the neural circuits performing sensorimotor computations in invertebrates will unravel the minimum circuit requirements driving adaptive navigation.

Artificial Intelligence Based on Biological Neurons

2020 ◽  
pp. 25-53
Author(s):  
Rinat Galiautdinov
Keyword(s):  
Artificial Intelligence ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Next Generation ◽  
New Approach ◽  
Home Based

The chapter describes the new approach in artificial intelligence based on simulated biological neurons and creation of the neural circuits for the sphere of IoT which represent the next generation of artificial intelligence and IoT. Unlike existing technical devices for implementing a neuron based on classical nodes oriented to binary processing, the proposed path is based on simulation of biological neurons, creation of biologically close neural circuits where every device will implement the function of either a sensor or a “muscle” in the frame of the home-based live AI and IoT. The research demonstrates the developed nervous circuit constructor and its usage in building of the AI (neural circuit) for IoT.

scholarly journals Interneuron Diversity: Toward a Better Understanding of Interneuron Development In the Olfactory System

2019 ◽  
Vol 13 ◽  
pp. 117906951982605
Author(s):  
Chi-Jen Yang ◽  
Kuo-Ting Tsai ◽  
Nan-Fu Liou ◽  
Ya-Hui Chou
Keyword(s):  
Olfactory System ◽  
Neural Circuits ◽  
Projection Neurons ◽  
Intrinsic Properties ◽  
Recent Advances ◽  
Local Interneurons ◽  
Olfactory Interneurons ◽  
High Diversity ◽  
Interneuron Development

The Drosophila olfactory system is an attractive model for exploring the wiring logic of complex neural circuits. Remarkably, olfactory local interneurons exhibit high diversity and variability in their morphologies and intrinsic properties. Although olfactory sensory and projection neurons have been extensively studied of development and wiring; the development, mechanisms for establishing diversity, and integration of olfactory local interneurons into the developing circuit remain largely undescribed. In this review, we discuss some challenges and recent advances in the study of Drosophila olfactory interneurons.

scholarly journals A novel device for real-time measurement and manipulation of licking behavior in head-fixed mice

2018 ◽  
Vol 120 (6) ◽  
pp. 2975-2987 ◽  
Author(s):  
Brice Williams ◽  
Anderson Speed ◽  
Bilal Haider
Keyword(s):  
Real Time ◽  
Neural Activity ◽  
Closed Loop ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Visual Behavior ◽  
Sensory Stimuli ◽  
Neural Recordings ◽  
Control Signals ◽  
Sensory Motor

The mouse has become an influential model system for investigating the mammalian nervous system. Technologies in mice enable recording and manipulation of neural circuits during tasks where they respond to sensory stimuli by licking for liquid rewards. Precise monitoring of licking during these tasks provides an accessible metric of sensory-motor processing, particularly when combined with simultaneous neural recordings. There are several challenges in designing and implementing lick detectors during head-fixed neurophysiological experiments in mice. First, mice are small, and licking behaviors are easily perturbed or biased by large sensors. Second, neural recordings during licking are highly sensitive to electrical contact artifacts. Third, submillisecond lick detection latencies are required to generate control signals that manipulate neural activity at appropriate time scales. Here we designed, characterized, and implemented a contactless dual-port device that precisely measures directional licking in head-fixed mice performing visual behavior. We first determined the optimal characteristics of our detector through design iteration and then quantified device performance under ideal conditions. We then tested performance during head-fixed mouse behavior with simultaneous neural recordings in vivo. We finally demonstrate our device’s ability to detect directional licks and generate appropriate control signals in real time to rapidly suppress licking behavior via closed-loop inhibition of neural activity. Our dual-port detector is cost effective and easily replicable, and it should enable a wide variety of applications probing the neural circuit basis of sensory perception, motor action, and learning in normal and transgenic mouse models. NEW & NOTEWORTHY Mice readily learn tasks in which they respond to sensory cues by licking for liquid rewards; tasks that involve multiple licking responses allow study of neural circuits underlying decision making and sensory-motor integration. Here we design, characterize, and implement a novel dual-port lick detector that precisely measures directional licking in head-fixed mice performing visual behavior, enabling simultaneous neural recording and closed-loop manipulation of licking.

scholarly journals The dialectic of Hebb and homeostasis

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160258 ◽  
Author(s):  
Gina G. Turrigiano
Keyword(s):  
Recent Progress ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Homeostatic Plasticity ◽  
Homeostatic Control ◽  
Spatial And Temporal Scales ◽  
Network Function ◽  
Hebbian Plasticity ◽  
Circuit Function ◽  
Hebbian Mechanisms

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’.

scholarly journals Neural architecture: from cells to circuits

2018 ◽  
Vol 120 (2) ◽  
pp. 854-866 ◽  
Author(s):  
Sarah E. V. Richards ◽  
Stephen D. Van Hooser
Keyword(s):  
Nervous System ◽  
Cerebral Cortex ◽  
Structure Function ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Neuronal Morphology ◽  
Neural Architecture ◽  
Synaptic Interactions ◽  
Branching Patterns ◽  
Circuit Function

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.

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