Noise in the nervous system

Faisal, A. Aldo; Selen, Luc P. J.; Wolpert, Daniel M.

doi:10.1038/nrn2258

Cited by 2,323 publications

(1,998 citation statements)

References 191 publications

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“…Any comprehensive understanding of coding in stimulus-evoked spike trains of neurons requires a characterization of neural discharge components that are directly associated with the stimulus (signal) and those that are not (noise) (Roddey et al 2000;Stein et al 2005;Faisal et al 2008). In neurons that display high resting (i.e.…”

Section: Effects Of Isi Correlations On Information Transmission: Noimentioning

confidence: 99%

Nonrenewal spike train statistics: causes and functional consequences on neural coding

Ávila-Ǻkerberg

Chacron

2011

Exp Brain Res

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Many neurons display significant patterning in their spike trains (e.g. oscillations, bursting), and there is accumulating evidence that information is contained in these patterns. In many cases, this patterning is caused by intrinsic mechanisms rather than external signals. In this review, we focus on spiking activity that displays nonrenewal statistics (i.e. memory that persists from one firing to the next). Such statistics are seen in both peripheral and central neurons and appear to be ubiquitous in the CNS. We review the principal mechanisms that can give rise to nonrenewal spike train statistics. These are separated into intrinsic mechanisms such as relative refractoriness and network mechanisms such as coupling with delayed inhibitory feedback. Next, we focus on the functional roles for nonrenewal spike train statistics. These can either increase or decrease information transmission. We also focus on how such statistics can give rise to an optimal integration timescale at which spike train variability is minimal and how this might be exploited by sensory systems to maximize the detection of weak signals. We finish by pointing out some interesting future directions for research in this area. In particular, we explore the interesting possibility that synaptic dynamics might be matched with the nonrenewal spiking statistics of presynaptic spike trains in order to further improve information transmission.

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Section: Effects Of Isi Correlations On Information Transmission: Noimentioning

confidence: 99%

Nonrenewal spike train statistics: causes and functional consequences on neural coding

Ávila-Ǻkerberg

Chacron

2011

Exp Brain Res

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“…There are further factors that influence veering, which cannot be captured directly by the model. For example, Kallie et al [17] report that asymmetries in the motor noise [18][19][20][21] can also lead to walking in circles. In addition, distraction [22], sex [23], drugs [24,25] and deviations in stepping frequency [26] have been reported to have significant influence on veering.…”

Section: Discussionmentioning

confidence: 99%

Walking in circles: a modelling approach

Maus

Seyfarth

2014

J. R. Soc. Interface.

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Blindfolded or disoriented people have the tendency to walk in circles rather than on a straight line even if they wanted to. Here, we use a minimalistic walking model to examine this phenomenon. The bipedal spring-loaded inverted pendulum exhibits asymptotically stable gaits with centre of mass (CoM) dynamics and ground reaction forces similar to human walking in the sagittal plane. We extend this model into three dimensions, and show that stable walking patterns persist if the leg is aligned with respect to the body (here: CoM velocity) instead of a world reference frame. Further, we demonstrate that asymmetric leg configurations, which are common in humans, will typically lead to walking in circles. The diameter of these circles depends strongly on parameter configuration, but is in line with empirical data from human walkers. Simulation results suggest that walking radius and especially direction of rotation are highly dependent on leg configuration and walking velocity, which explains inconsistent veering behaviour in repeated trials in human data. Finally, we discuss the relation between findings in the model and implications for human walking.

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“…The use of fMRI to study brain function has relied primarily on assessing average brain activation patterns. Nevertheless, brain activity is inherently variable, and several lines of research have shown that our ability to understand important aspects of brain function is enhanced by considering the variability of brain signals [221][222][223] . In particular, networks that are more variable may be more robust to disruption and may explore more neural states, thus enhancing learning and promoting optimal performance 221,222,224,225 .…”

Section: Box 2 Assessing Behavioral and Brain Trajectories Over The Lmentioning

confidence: 99%

The cognitive neuroscience of ageing

2012

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PrefaceThe availability of neuroimaging technology has spurred a marked increase in the human cognitive neuroscience literature, including the study of cognitive aging. Although there is a growing consensus that the aging brain retains considerable plasticity of function, currently measured primarily by means of functional magnetic resonance imaging, it is less clear how age differences in brain activity relate to cognitive performance. The field also is hampered by the complexity of the aging process itself and the large number of factors that are influenced by age. In this review, current trends and unresolved issues in the cognitive neuroscience of aging are discussed.

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Noise in the nervous system

Cited by 2,323 publications

References 191 publications

Nonrenewal spike train statistics: causes and functional consequences on neural coding

Nonrenewal spike train statistics: causes and functional consequences on neural coding

Walking in circles: a modelling approach

The cognitive neuroscience of ageing

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