Neural variability: friend or foe?

doi:10.1016/j.tics.2015.04.005

Trends in Cognitive Sciences

Volume 19, Issue 6, June 2015, Pages 322-328

https://doi.org/10.1016/j.tics.2015.04.005 Get rights and content

Highlights

•
Trial-to-trial neural and behavioral variability differs across individuals.
•
Does excessive neural variability have cognitive/perceptual/clinical consequences?
•
Several types of neural variability can be measured in humans using neuroimaging.
•
Excessive neural variability is apparent in autism and other disorders.

Although we may not realize it, our brain function varies markedly from moment to moment such that our brain responses exhibit substantial variability across trials even in response to a simple repeating stimulus. Should we care about such within-subject variability? Are there developmental, cognitive, and clinical consequences to having a brain that is more or less variable/noisy? Although neural variability seems to be beneficial for learning, excessive levels of neural variability are apparent in individuals with different clinical disorders. We propose that measuring distinct types of neural variability in autism and other disorders is likely to reveal crucial insights regarding their neuropathology. We further discuss the importance of studying neural variability more generally across development and aging in humans.

Section snippets

Sources of neural variability

Moment-to-moment neural variability is generated by many neurophysiological mechanisms. At the single cell level, these include the noisy response characteristics of peripheral sensors [1], the stochastic nature of synaptic transmission [2], and the dynamic changes caused by neural adaptation [3] and synaptic plasticity [4]. At the neural network level, additional variability is generated by adjustments of the excitation/inhibition balance [5], changes in attention and arousal levels [6],

Excessive neural variability in autism

Autism is a developmental disorder which is diagnosed based on the presence of specific behavioral symptoms that include social communication difficulties, abnormal sensory sensitivities, and repetitive behaviors [14]. Prominent hypotheses about autism posit that it may result from excitation–inhibition imbalances 15, 16, 17, abnormalities in genes that govern neural migration and proliferation 18, 19, and synaptic maturation and transmission 20, 21. Such fundamental neural alterations are

Variability in other clinical disorders

Is excessive neural variability unique to autism? Several studies have reported that excessive neural variability is also apparent in other disorders, but suggest that different disorders exhibit distinct types of neural variability. For example, individuals with dyslexia exhibit abnormally large trial-to-trial variability in auditory brain stem EEG responses to single syllables [60]. By contrast, individuals with attention deficit hyperactivity disorder (ADHD) exhibit abnormally variable P3b

Cognition and perception

Might specific measures of neural variability indicate anything about an individual's cognitive or perceptual abilities? An extensive body of behavioral research has shown that larger trial-to-trial behavioral variability is apparent in individuals with different cognitive impairments [67]. These include reports of increased reaction time (RT) variability in individuals with dementia [68], traumatic brain injury [69], schizophrenia [70], autism 37, 38, and ADHD 71, 72, 73 across a wide range of

Variability in motor learning and typical development

Although excessive neural and behavioral variability may be indicators of impaired cognitive function and pathophysiology, a degree of neural and behavioral variability is essential for learning and proper development. Variability is a central component of many motor control models that explain how the motor system balances the need for accuracy and the need for flexibility [81]. Performing accurate actions in an ever-changing world means that the motor system constantly needs to adapt to both

Concluding remarks and future directions

The human brain seems to balance the need to perform tasks accurately and respond to stimuli reliably (on a single-trial basis) with the need to maintain flexibility, explore novel solutions and outcomes, and adapt to ever-changing environmental conditions. Neural variability is likely maladaptive for optimizing performance accuracy on single trials, but it seems to be important for enabling exploration, plasticity, and learning. Although many studies have examined behavioral trial-to-trial

Acknowledgments

The research described here was supported by grants from the Simons Foundation Autism Research Initiative (177638 and 298640) to D.H. and M.B.

References (94)

C.W.G. Clifford
Visual adaptation: neural, psychological and computational aspects
Vision Res.
(2007)
A.M.C. Kelly
Competition between functional brain networks mediates behavioral variability
Neuroimage
(2008)
E. Marder
Neuromodulation of neuronal circuits: back to the future
Neuron
(2012)
G.J. Tomko et al.
Neuronal variability: non-stationary responses to identical visual stimuli
Brain Res.
(1974)
M.N. Shadlen et al.
Noise, neural codes and cortical organization
Curr. Opin. Neurobiol.
(1994)
D.R. Simmons
Vision in autism spectrum disorders
Vision Res.
(2009)
S. Dakin et al.
Vagaries of visual perception in autism
Neuron
(2005)
I. Dinstein
Unreliable evoked responses in autism
Neuron
(2012)
I. Dinstein
Normal movement selectivity in autism
Neuron
(2010)
P.M. Weinger
Low-contrast response deficits and increased neural noise in children with autism spectrum disorder
Neuropsychologia
(2014)

E. Pellicano et al.

When the world becomes ‘too real’: a Bayesian explanation of autistic perception

Trends Cogn. Sci.

(2012)

R. Tuchman et al.

Epilepsy in autism

Lancet Neurol.

(2002)

I. Dinstein

Disrupted neural synchronization in toddlers with autism

Neuron

(2011)

M-P. Poulin-Lord

Increased topographical variability of task-related activation in perceptive and motor associative regions in adult autistics

Neuroimage Clin.

(2014)

S.W.S. MacDonald

Intra-individual variability in behavior: links to brain structure, neurotransmission and neuronal activity

Trends Neurosci.

(2006)

L. Tamm

Reaction time variability in ADHD: a review

Neurotherapeutics

(2012)

M.J. Kofler

Reaction time variability in ADHD: a meta-analytic review of 319 studies

Clin. Psychol. Rev.

(2013)

F.X. Castellanos

Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability

Biol. Psychiatry

(2005)

T. Aihara

Internal noise determines external stochastic resonance in visual perception

Vision Res.

(2008)

R.M. Costa

A selectionist account of de novo action learning

Curr. Opin. Neurobiol.

(2011)

R.M. Costa

Rapid alterations in corticostriatal ensemble coordination during acute dopamine-dependent motor dysfunction

Neuron

(2006)

D. Mongeon

Impact of Parkinson's disease and dopaminergic medication on adaptation to explicit and implicit visuomotor perturbations

Brain Cogn.

(2013)

R. West

Lapses of intention and performance variability reveal age-related increases in fluctuations of executive control

Brain Cogn.

(2002)

K.R.A. Van Dijk

The influence of head motion on intrinsic functional connectivity MRI

Neuroimage

(2012)

D.M. Schneeweis et al.

The photovoltage of macaque cone photoreceptors: adaptation, noise, and kinetics

J. Neurosci.

(1999)

C. Ribrault

From the stochasticity of molecular processes to the variability of synaptic transmission

Nat. Rev. Neurosci.

(2011)

D.E. Feldman

Synaptic mechanisms for plasticity in neocortex

Annu. Rev. Neurosci.

(2009)

G. Turrigiano

Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement

Annu. Rev. Neurosci.

(2011)

A. Fontanini et al.

Behavioral states, network states, and sensory response variability

J. Neurophysiol.

(2008)

M. Carandini

Amplification of trial-to-trial response variability by neurons in visual cortex

PLoS Biol.

(2004)

R.L.T. Goris

Partitioning neuronal variability

Nat. Neurosci.

(2014)

M.M. Churchland

Stimulus onset quenches neural variability: a widespread cortical phenomenon

Nat. Neurosci.

(2010)

Diagnostic and Statistical Manual of Mental Disorders

(2013)

J.L.R. Rubenstein et al.

Model of autism: increased ratio of excitation/inhibition in key neural systems

Genes Brain Behav.

(2003)

H. Markram

The intense world syndrome – an alternative hypothesis for autism

Front. Neurosci.

(2007)

O. Yizhar

Neocortical excitation/inhibition balance in information processing and social dysfunction

Nature

(2011)

R. Stoner

Patches of disorganization in the neocortex of children with autism

N. Engl. J. Med.

(2014)

E.L. Casanova et al.

Genetics studies indicate that neural induction and early neuronal maturation are disturbed in autism

Front. Cell. Neurosci.

(2014)

J.T. Glessner

Autism genome-wide copy number variation reveals ubiquitin and neuronal genes

Nature

(2009)

B.D. Auerbach

Mutations causing syndromic autism define an axis of synaptic pathophysiology

Nature

(2011)

Minshew, N.J. and Goldstein, G. (1998) Autism as a disorder of complex information processing. 136,...

M.K. Belmonte

Autism as a disorder of neural information processing: directions for research and targets for therapy

Mol. Psychiatry

(2004)

S.M. Haigh

Cortical variability in the sensory-evoked response in autism

J. Autism Dev. Disord.

(2015)

E. Milne

Increased intra-participant variability in children with autistic spectrum disorders: evidence from single-trial analysis of evoked EEG

Front. Psychol.

(2011)

R.P. Lawson

An aberrant precision account of autism

Front. Hum. Neurosci.

(2014)

P. Sinha

Autism as a disorder of prediction

Proc. Natl. Acad. Sci. U.S.A.

(2014)

S. Van de Cruys

Precise minds in uncertain worlds: predictive coding in autism

Psychol. Rev.

(2014)

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View full text

Trends in Cognitive Sciences

OpinionNeural variability: friend or foe?

Highlights

Section snippets

Sources of neural variability

Excessive neural variability in autism

Variability in other clinical disorders

Cognition and perception

Variability in motor learning and typical development

Concluding remarks and future directions

Acknowledgments

Vision Res.

Neuroimage

Neuron

Brain Res.

Curr. Opin. Neurobiol.

Vision Res.

Neuron

Neuron

Neuron

Neuropsychologia

Trends Cogn. Sci.

Lancet Neurol.

Neuron

Neuroimage Clin.

Trends Neurosci.

Neurotherapeutics

Clin. Psychol. Rev.

Biol. Psychiatry

Vision Res.

Curr. Opin. Neurobiol.

Neuron

Brain Cogn.

Brain Cogn.

Neuroimage

The photovoltage of macaque cone photoreceptors: adaptation, noise, and kinetics

J. Neurosci.

From the stochasticity of molecular processes to the variability of synaptic transmission

Nat. Rev. Neurosci.

Synaptic mechanisms for plasticity in neocortex

Annu. Rev. Neurosci.

Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement

Annu. Rev. Neurosci.

Behavioral states, network states, and sensory response variability

J. Neurophysiol.

Amplification of trial-to-trial response variability by neurons in visual cortex

PLoS Biol.

Partitioning neuronal variability

Nat. Neurosci.

Stimulus onset quenches neural variability: a widespread cortical phenomenon

Nat. Neurosci.

Diagnostic and Statistical Manual of Mental Disorders

Model of autism: increased ratio of excitation/inhibition in key neural systems

Genes Brain Behav.

The intense world syndrome – an alternative hypothesis for autism

Front. Neurosci.

Neocortical excitation/inhibition balance in information processing and social dysfunction

Nature

Patches of disorganization in the neocortex of children with autism

N. Engl. J. Med.

Genetics studies indicate that neural induction and early neuronal maturation are disturbed in autism

Front. Cell. Neurosci.

Autism genome-wide copy number variation reveals ubiquitin and neuronal genes

Nature

Mutations causing syndromic autism define an axis of synaptic pathophysiology

Nature

Autism as a disorder of neural information processing: directions for research and targets for therapy

Mol. Psychiatry

Cortical variability in the sensory-evoked response in autism

J. Autism Dev. Disord.

Increased intra-participant variability in children with autistic spectrum disorders: evidence from single-trial analysis of evoked EEG

Front. Psychol.

An aberrant precision account of autism

Front. Hum. Neurosci.

Autism as a disorder of prediction

Proc. Natl. Acad. Sci. U.S.A.

Precise minds in uncertain worlds: predictive coding in autism

Psychol. Rev.

Opinion
Neural variability: friend or foe?