scholarly journals Motor control by precisely timed spike patterns

2016 ◽  
Author(s):  
Kyle H. Srivastava ◽  
Caroline M. Holmes ◽  
Michiel Vellema ◽  
Andrea Pack ◽  
Coen P. H. Elemans ◽  
...  

SummaryA fundamental problem in neuroscience is to understand how sequences of action potentials (“spikes”) encode information about sensory signals and motor outputs. Although traditional theories of neural coding assume that information is conveyed by the total number of spikes fired (spike rate), recent studies of sensory [1–5] and motor [6] activity have shown that far more information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear whether the information carried by spike timing actually plays a causal role in brain function [1]. Here we demonstrate how a precise spike timing code is read out downstream by the muscles to control behavior. We provide both correlative and causal evidence to show that the nervous system uses millisecond-scale variations in the timing of spikes within multi-spike patterns to regulate a relatively simple behavior – respiration in the Bengalese finch, a songbird. These findings suggest that a fundamental assumption of current theories of motor coding requires revision, and that significant improvements in applications, such as neural prosthetic devices, can be achieved by using precise spike timing information.


2017 ◽  
Vol 114 (5) ◽  
pp. 1171-1176 ◽  
Author(s):  
Kyle H. Srivastava ◽  
Caroline M. Holmes ◽  
Michiel Vellema ◽  
Andrea R. Pack ◽  
Coen P. H. Elemans ◽  
...  

A fundamental problem in neuroscience is understanding how sequences of action potentials (“spikes”) encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence that the nervous system uses millisecond-scale variations in the timing of spikes within multispike patterns to control a vertebrate behavior—namely, respiration in the Bengalese finch, a songbird. These findings suggest that a fundamental assumption of current theories of motor coding requires revision.



2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Sumedha Gandharava Dahl ◽  
Robert C. Ivans ◽  
Kurtis D. Cantley

AbstractThis study uses advanced modeling and simulation to explore the effects of external events such as radiation interactions on the synaptic devices in an electronic spiking neural network. Specifically, the networks are trained using the spike-timing-dependent plasticity (STDP) learning rule to recognize spatio-temporal patterns (STPs) representing 25 and 100-pixel characters. Memristive synapses based on a TiO2 non-linear drift model designed in Verilog-A are utilized, with STDP learning behavior achieved through bi-phasic pre- and post-synaptic action potentials. The models are modified to include experimentally observed state-altering and ionizing radiation effects on the device. It is found that radiation interactions tend to make the connection between afferents stronger by increasing the conductance of synapses overall, subsequently distorting the STDP learning curve. In the absence of consistent STPs, these effects accumulate over time and make the synaptic weight evolutions unstable. With STPs at lower flux intensities, the network can recover and relearn with constant training. However, higher flux can overwhelm the leaky integrate-and-fire post-synaptic neuron circuits and reduce stability of the network.



2001 ◽  
Vol 13 (10) ◽  
pp. 2221-2237 ◽  
Author(s):  
Rajesh P. N. Rao ◽  
Terrence J. Sejnowski

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are potentiated, while those that are activated a few milliseconds after are depressed. We show that such a mechanism can implement a form of temporal difference learning for prediction of input sequences. Using a biophysical model of a cortical neuron, we show that a temporal difference rule used in conjunction with dendritic backpropagating action potentials reproduces the temporally asymmetric window of Hebbian plasticity observed physiologically. Furthermore, the size and shape of the window vary with the distance of the synapse from the soma. Using a simple example, we show how a spike-timing-based temporal difference learning rule can allow a network of neocortical neurons to predict an input a few milliseconds before the input's expected arrival.



2002 ◽  
Vol 87 (4) ◽  
pp. 1749-1762 ◽  
Author(s):  
Shigeto Furukawa ◽  
John C. Middlebrooks

Previous studies have demonstrated that the spike patterns of cortical neurons vary systematically as a function of sound-source location such that the response of a single neuron can signal the location of a sound source throughout 360° of azimuth. The present study examined specific features of spike patterns that might transmit information related to sound-source location. Analysis was based on responses of well-isolated single units recorded from cortical area A2 in α-chloralose-anesthetized cats. Stimuli were 80-ms noise bursts presented from loudspeakers in the horizontal plane; source azimuths ranged through 360° in 20° steps. Spike patterns were averaged across samples of eight trials. A competitive artificial neural network (ANN) identified sound-source locations by recognizing spike patterns; the ANN was trained using the learning vector quantization learning rule. The information about stimulus location that was transmitted by spike patterns was computed from joint stimulus-response probability matrices. Spike patterns were manipulated in various ways to isolate particular features. Full-spike patterns, which contained all spike-count information and spike timing with 100-μs precision, transmitted the most stimulus-related information. Transmitted information was sensitive to disruption of spike timing on a scale of more than ∼4 ms and was reduced by an average of ∼35% when spike-timing information was obliterated entirely. In a condition in which all but the first spike in each pattern were eliminated, transmitted information decreased by an average of only ∼11%. In many cases, that condition showed essentially no loss of transmitted information. Three unidimensional features were extracted from spike patterns. Of those features, spike latency transmitted ∼60% more information than that transmitted either by spike count or by a measure of latency dispersion. Information transmission by spike patterns recorded on single trials was substantially reduced compared with the information transmitted by averages of eight trials. In a comparison of averaged and nonaveraged responses, however, the information transmitted by latencies was reduced by only ∼29%, whereas information transmitted by spike counts was reduced by 79%. Spike counts clearly are sensitive to sound-source location and could transmit information about sound-source locations. Nevertheless, the present results demonstrate that the timing of the first poststimulus spike carries a substantial amount, probably the majority, of the location-related information present in spike patterns. The results indicate that any complete model of the cortical representation of auditory space must incorporate the temporal characteristics of neuronal response patterns.



Nano Letters ◽  
2012 ◽  
Vol 12 (7) ◽  
pp. 3391-3398 ◽  
Author(s):  
Huanan Zhang ◽  
Jimmy Shih ◽  
Jian Zhu ◽  
Nicholas A. Kotov


2011 ◽  
pp. 581-619
Author(s):  
Benjamin I. Rapoport ◽  
Rahul Sarpeshkar

Algorithmically and energetically efficient computational architectures that operate in real time are essential for clinically useful neural prosthetic devices. Such architectures decode raw neural data to obtain direct motor control signals for external devices. They can also perform data compression and vastly reduce the bandwidth and consequently power expended in wireless transmission of raw data from implantable brain–machine interfaces. We describe a biomimetic algorithm and micropower analog circuit architecture for decoding neural cell ensemble signals. The decoding algorithm implements a continuous-time artificial neural network, using a bank of adaptive linear filters with kernels that emulate synaptic dynamics. The filters transform neural signal inputs into control-parameter outputs, and can be tuned automatically in an on-line learning process. We demonstrate that the algorithm is suitable for decoding both local field potentials and mean spike rates. We also provide experimental validation of our system, decoding discrete reaching decisions from neuronal activity in the macaque parietal cortex, and decoding continuous head direction trajectories from cell ensemble activity in the rat thalamus. We further describe a method of mapping the algorithm to a highly parallel circuit architecture capable of continuous learning and real-time operation. Circuit simulations of a subthreshold analog CMOS instantiation of the architecture reveal that its performance is comparable to the predicted performance of our decoding algorithm for a system decoding three control parameters from 100 neural input channels at microwatt levels of power consumption. While the algorithm and decoding architecture are suitable for analog or digital implementation, we indicate how a micropower analog system trades some algorithmic programmability for reductions in power and area consumption that could facilitate implantation of a neural decoder within the brain. We also indicate how our system can compress neural data more than 100,000-fold, greatly reducing the power needed for wireless telemetry of neural data.



Micromachines ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 810
Author(s):  
Yan Gong ◽  
Wentai Liu ◽  
Runyu Wang ◽  
Matthew Harris Brauer ◽  
Kristine Zheng ◽  
...  

Reliable packaging for implantable neural prosthetic devices in body fluids is a long-standing challenge for devices’ chronic applications. This work studied the stability of Parylene C (PA), SiO2, and Si3N4 packages and coating strategies on tungsten wires using accelerated, reactive aging tests in three solutions: pH 7.4 phosphate-buffered saline (PBS), PBS + 30 mM H2O2, and PBS + 150 mM H2O2. Different combinations of coating thicknesses and deposition methods were studied at various testing temperatures. Analysis of the preliminary data shows that the pinholes/defects, cracks, and interface delamination are the main attributes of metal erosion and degradation in reactive aging solutions. Failure at the interface of package and metal is the dominating factor in the wire samples with open tips.



2010 ◽  
Vol 103 (4) ◽  
pp. 2314-2314
Author(s):  
Marco Fuenzalida ◽  
David Fernández de Sevilla ◽  
Alejandro Couve ◽  
Washington Buño


2001 ◽  
Vol 86 (3) ◽  
pp. 1252-1265 ◽  
Author(s):  
Yu-Feng Wang ◽  
Xiao-Bing Gao ◽  
Anthony N. van den Pol

Spikes may play an important role in modulating a number of aspects of brain development. In early hypothalamic development, GABA can either evoke action potentials, or it can shunt other excitatory activity. In both slices and cultures of the mouse hypothalamus, we observed a heterogeneity of spike patterns and frequency in response to GABA. To examine the mechanisms underlying patterns and frequency of GABA-evoked spikes, we used conventional whole cell and gramicidin perforation recordings of neurons ( n = 282) in slices and cultures of developing mouse hypothalamus. Recorded with gramicidin pipettes, GABA application evoked action potentials in hypothalamic neurons in brain slices of postnatal day 2–9( P2- 9) mice. With conventional patch pipettes (containing 29 mM Cl−), action potentials were also elicited by GABA from neurons of 2–13 days in vitro (2–13 DIV) embryonic hypothalamic cultures. Depolarizing responses to GABA could be generally classified into three types: depolarization with no spike, a single spike, or complex patterns of multiple spikes. In parallel experiments in slices, electrical stimulation of GABAergic mediobasal hypothalamic neurons in the presence of glutamate receptor antagonists [10 μM 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX), 100 μM 2-amino-5-phosphonopentanoic acid (AP5)] resulted in the occurrence of spikes that were blocked by bicuculline (20 μM). Blocking ionotropic glutamate receptors with AP5 and CNQX did not block GABA-mediated multiple spikes. Similarly, when synaptic transmission was blocked with Cd2+ (200 μM) and Ni2+(300 μM), GABA still induced multiple spikes, suggesting that the multiple spikes can be an intrinsic membrane property of GABA excitation and were not based on local interneurons. When the pipette [Cl−] was 29 or 45 mM, GABA evoked multiple spikes. In contrast, spikes were not detected with 2 or 10 mM intracellular [Cl−]. With gramicidin pipettes, we found that the mean reversal potential of GABA-evoked current ( E GABA) was positive to the resting membrane potential, suggesting a high intracellular [Cl−] in developing mouse neurons. Varying the holding potential from −80 to 0 mV revealed an inverted U-shaped effect on spike probability. Blocking voltage-dependent Na+ channels with tetrodotoxin eliminated GABA-evoked spikes, but not the GABA-evoked depolarization. Removing Ca2+ from the extracellular solution did not block spikes, indicating GABA-evoked Na+-based spikes. Although E GABA was more positive within 2–5 days in culture, the probability of GABA-evoked spikes was greater in 6- to 9-day cells. Mechanistically, this appears to be due to a greater Na+ current found in the older cells during a period when the E GABA is still positive to the resting membrane potential. GABA evoked similar spike patterns in HEPES and bicarbonate buffers, suggesting that Cl−, not bicarbonate, was primarily responsible for generatingmultiple spikes. GABA evoked either single or multiple spikes; neurons with multiple spikes had a greater Na+ current, a lower conductance, a more negative spike threshold, and a greater difference between the peak of depolarization and the spike threshold. Taken together, the present results indicate that the patterns of multiple action potentials evoked by GABA are an inherent property of the developing hypothalamic neuron.



2017 ◽  
Vol 118 (2) ◽  
pp. 855-873 ◽  
Author(s):  
Charles. J. Wilson

During repetitive firing, the timing of action potentials is determined by the interaction between the input and voltage-sensitive currents throughout the interspike interval. This interaction is encapsulated in the neuron’s phase-resetting curve. The phase-resetting curve predicted spike timing to small sinusoidal currents over a wide range of stimulus frequencies. Firing patterns were most sensitive to oscillatory components near the cell’s own firing rate, even in the presence of noise and other inputs.



Sign in / Sign up

Export Citation Format

Share Document