scholarly journals A neural circuit model for human sensorimotor timing

2019 ◽  
Author(s):  
Seth W. Egger ◽  
Nhat M. Le ◽  
Mehrdad Jazayeri
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Motor Planning ◽  
Time Interval ◽  
Flexible Control ◽  
Interval Reproduction ◽  
Level Model ◽  
Sensory Responses ◽  
Temporal Events ◽  
External Stimuli

ABSTRACTHumans can rapidly and flexibly coordinate their movements with external stimuli. Theoretical considerations suggest that this flexibility can be understood in terms of how sensory responses reconfigure the neural circuits that control movements. However, because external stimuli can occur at unexpected times, it is unclear how the corresponding sensory inputs can be used to exert flexible control over the ongoing activity of recurrent neural circuits. Here, we tackle this problem in the domain of sensorimotor timing and develop a circuit-level model that provides insight into how the brain coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the model’s output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control temporal aspects of behavior.

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 Reaction to a Visual Stimulus: Anticipation with Steady and Dynamic Contractions

2019 ◽  
Vol 69 (1) ◽  
pp. 17-27
Author(s):  
Agostina Casamento-Moran ◽  
Stefan Delmas ◽  
Seoung Hoon Park ◽  
Basma Yacoubi ◽  
Evangelos A. Christou
Keyword(s):  
Reaction Time ◽  
Planning Process ◽  
Dynamic Condition ◽  
Motor Planning ◽  
Reaction Time Task ◽  
Emg Activity ◽  
Time Interval ◽  
Variable Direction ◽  
The Moment ◽  
Study Participants

Abstract Reacting fast to visual stimuli is important for many activities of daily living and sports. It remains unknown whether the strategy used during the anticipatory period influences the speed of the reaction. The purpose of this study was to determine if reaction time (RT) differs following a steady and a dynamic anticipatory strategy. Twenty‐two young adults (21.0 ± 2.2 yrs, 13 women) participated in this study. Participants performed 15 trials of a reaction time task with ankle dorsiflexion using a steady (steady force at 15% MVC) and a dynamic (oscillating force from 10‐20% MVC) anticipatory strategy. We recorded primary agonist muscle (tibialis anterior; TA) electromyographic (EMG) activity. We quantified RT as the time interval from the onset of the stimulus to the onset of force. We found that a dynamic anticipatory strategy, compared to the steady anticipatory strategy, resulted in a longer RT (p = 0.04). We classified trials of the dynamic condition based on the level and direction of anticipatory force at the moment of the response. We found that RT was longer during the middle descending relative to the middle ascending and the steady conditions (p < 0.01). All together, these results suggest that RT is longer when preceded by a dynamic anticipatory strategy. Specifically, the longer RT is a consequence of the variable direction of force at which the response can occur, which challenges the motor planning process.

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 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 Motor planning perturbation: muscle activation and reaction time

2018 ◽  
Vol 120 (4) ◽  
pp. 2059-2065
Author(s):  
Stefan Delmas ◽  
Agostina Casamento-Moran ◽  
Seoung Hoon Park ◽  
Basma Yacoubi ◽  
Evangelos A. Christou
Keyword(s):  
Reaction Time ◽  
Muscle Activity ◽  
Muscle Activation ◽  
Maximum Voluntary Contraction ◽  
Motor Planning ◽  
Reaction Time Task ◽  
Voluntary Contraction ◽  
Voluntary Activation ◽  
Time Interval ◽  
Voluntary Activity

Reaction time (RT) is the time interval between the appearance of a stimulus and initiation of a motor response. Within RT, two processes occur, selection of motor goals and motor planning. An unresolved question is whether perturbation to the motor planning component of RT slows the response and alters the voluntary activation of muscle. The purpose of this study was to determine how the modulation of muscle activity during an RT response changes with motor plan perturbation. Twenty-four young adults (20.5 ±1.1 yr, 13 women) performed 15 trials of an isometric RT task with ankle dorsiflexion using a sinusoidal anticipatory strategy (10–20% maximum voluntary contraction). We compared the processing part of the RT and modulation of muscle activity from 10 to 60 Hz of the tibialis anterior (primary agonist) when the stimulus appeared at the trough or at the peak of the sinusoidal task. We found that RT ( P = 0.003) was longer when the stimulus occurred at the peak compared with the trough. During the time of the reaction, the electromyography (EMG) power from 10 to 35 Hz was less at the peak than the trough ( P = 0.019), whereas the EMG power from 35 to 60 Hz was similar between the peak and trough ( P = 0.92). These results suggest that perturbation to motor planning lengthens the processing part of RT and alters the voluntary activation of the muscle by decreasing the relative amount of power from 10 to 35 Hz. NEW & NOTEWORTHY We aimed to determine whether perturbation to motor planning would alter the speed and muscle activity of the response. We compared trials when a stimulus appeared at the peak or trough of an oscillatory reaction time task. When the stimulus occurred at the trough, participants responded faster, with greater force, and less EMG power from 10-35 Hz. We provide evidence that motor planning perturbation slows the response and alters the voluntary activity of the muscle.

scholarly journals Central tendency effects in time interval reproduction in autism

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Themelis Karaminis ◽  
Guido Marco Cicchini ◽  
Louise Neil ◽  
Giulia Cappagli ◽  
David Aagten-Murphy ◽  
...  
Keyword(s):  
Time Interval ◽  
Central Tendency ◽  
Interval Reproduction

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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