Lessons From Spontaneous Neural Noise Genesis on Neuromorphic Engineering [Further Thoughts]

2014 ◽  
Vol 102 (4) ◽  
pp. 513-513
Author(s):  
Tomoki Fukai ◽  
Jun-nosuke Teramae
Keyword(s):  
Neuromorphic Engineering ◽  
Neural Noise

scholarly journals On the interrelation of 1/f neural noise and norepinephrine system activity during motor response inhibition

2019 ◽  
Vol 121 (5) ◽  
pp. 1633-1643 ◽  
Author(s):  
Maik Pertermann ◽  
Moritz Mückschel ◽  
Nico Adelhöfer ◽  
Tjalf Ziemssen ◽  
Christian Beste
Keyword(s):  
Information Processing ◽  
Cognitive Control ◽  
Inhibitory Control ◽  
Response Inhibition ◽  
Pupil Diameter ◽  
Human Information Processing ◽  
System Activity ◽  
Neural Noise ◽  
Control Processes ◽  
Norepinephrine System

Several lines of evidence suggest that there is a close interrelation between the degree of noise in neural circuits and the activity of the norepinephrine (NE) system, yet the precise nexus between these aspects is far from being understood during human information processing and cognitive control in particular. We examine this nexus during response inhibition in n = 47 healthy participants. Using high-density EEG recordings, we estimate neural noise by calculating “1/ f noise” of those data and integrate these EEG parameters with pupil diameter data as an established indirect index of NE system activity. We show that neural noise is reduced when cognitive control processes to inhibit a prepotent/automated response are exerted. These neural noise variations were confined to the theta frequency band, which has also been shown to play a central role during response inhibition and cognitive control. There were strong positive correlations between the 1 /f neural noise parameter and the pupil diameter data within the first 250 ms after the Nogo stimulus presentation at centro-parietal electrode sites. No such correlations were evident during automated responding on Go trials. Source localization analyses using standardized low-resolution brain electromagnetic tomography show that inferior parietal areas are activated in this time period in Nogo trials. The data suggest an interrelation of NE system activity and neural noise within early stages of information processing associated with inferior parietal areas when cognitive control processes are required. The data provide the first direct evidence for the nexus between NE system activity and the modulation of neural noise during inhibitory control in humans. NEW & NOTEWORTHY This is the first study showing that there is a nexus between norepinephrine system activity and the modulation of neural noise or scale-free neural activity during inhibitory control in humans. It does so by integrating pupil diameter data with analysis of EEG neural noise.

Mechanistic modeling of vertebrate spatial contrast sensitivity and acuity at low luminance

2012 ◽  
Vol 29 (3) ◽  
pp. 169-181 ◽  
Author(s):  
JOHN R. JARVIS ◽  
CHRISTOPHER M. WATHES
Keyword(s):  
Contrast Sensitivity ◽  
Mechanistic Modeling ◽  
Spatial Integration ◽  
Modulation Transfer ◽  
Neural Noise ◽  
Light Levels ◽  
Low Luminance ◽  
Spatial Contrast Sensitivity ◽  
Neural Factors ◽  
Experimental Values

AbstractThe validity of the Barten theoretical model for describing the vertebrate spatial contrast sensitivity function (CSF) and acuity at scotopic light levels has been examined. Although this model (which has its basis in signal modulation transfer theory) can successfully describe vertebrate CSF, and its relation to underlying visual neurophysiology at photopic light levels, significant discrepancies between theory and experimental data have been found at scotopic levels. It is shown that in order to describe scotopic CSF, the theory must be modified to account for important mechanistic changes, which occur as cone vision switches to rod vision. These changes are divided into photon management factors [changes in optical performance (for a dilated pupil), quantum efficiency, receptor sampling] and neural factors (changes in spatial integration area, neural noise, and lateral inhibition in the retina). Predictions of both scotopic CSF and acuity obtained from the modified theory were found to be in good agreement with experimental values obtained from the human, macaque, cat, and owl monkey. The last two species have rod densities particularly suited for scotopic conditions.

Neuromorphic Engineering

2017 ◽  
pp. 3-26
Author(s):  
Paul R. Prucnal ◽  
Bhavin J. Shastri ◽  
Malvin Carl Teich
Keyword(s):  
Neuromorphic Engineering

Exact Event-Driven Implementation for Recurrent Networks of Stochastic Perfect Integrate-and-Fire Neurons

2012 ◽  
Vol 24 (12) ◽  
pp. 3145-3180 ◽  
Author(s):  
Thibaud Taillefumier ◽  
Jonathan Touboul ◽  
Marcelo Magnasco
Keyword(s):  
Intrinsic Noise ◽  
Spike Timing ◽  
Temporal Coding ◽  
Recurrent Networks ◽  
Neural Noise ◽  
Integrate And Fire ◽  
Discretization Schemes ◽  
Event Driven ◽  
Random Variability

In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks’ dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.

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