Variability in the human response to pain

Intrinsic variability in the human response to pain is assembled from multiple, dynamic brain processes – ScienceDirect – July 2013

The stimulus-evoked response is the principle measure used to elucidate the timing and spatial location of human brain activity.

Brain and behavioural responses to pain

  • are influenced by multiple intrinsic and extrinsic factors and
  • display considerable, natural trial-by-trial variability.  

However, because the neuronal sources of this variability are poorly understood the functional information it contains is under-exploited for understanding the relationship between brain function and behaviour.

We recorded simultaneous EEG–fMRI during rest and noxious thermal stimulation to characterise the relationship between natural fluctuations in behavioural pain-ratings, the spatiotemporal dynamics of brain network responses and intrinsic connectivity.

We demonstrate that fMRI response variability in the pain network is:

  • dependent upon its resting-state functional connectivity;
  • modulated by behaviour; and
  • correlated with EEG evoked-potential amplitude.

The pre-stimulus default-mode network (DMN) fMRI signal predicts the subsequent magnitude of pain ratings, evoked-potentials and pain network BOLD responses.

Additionally, the power of the ongoing EEG alpha oscillation, an index of cortical excitability, modulates the DMN fMRI response to pain.

The complex interaction between alpha-power, DMN activity and both the behavioural report of pain and the brain’s response to pain demonstrates the neurobiological significance of trial-by-trial variability.

Furthermore, we show that multiple, interconnected factors contribute to both the brain’s response to stimulation and the psychophysiological emergence of the subjective experience of pain.

Introduction

In the course of everyday life the human brain is continually bombarded by sensory information and generates a behavioural response proportionate to the varying intensity and saliency of each event.

Functional neuroimaging experiments simulate a constrained version of this scenario in a laboratory environment and primarily use the signal change evoked in response to a stimulus event to elucidate the timing, intensity and spatial location of the underlying brain activity.

Conventional fMRI and EEG analyses assume that the brain’s response is standardised and consistent across repeated stimulus presentations.

However, studies ranging from single-neuron recordings to macroscale neuroimaging indicate that not only is response variability intrinsic to brain function but that it contains perceptually relevant information (Debener et al., 2006; Scaglione et al., 2011; Scheibe et al., 2010).

The functional and behavioural significance of this variability and the neural substrates underlying it remain poorly understood.

Human pain is a conscious, subjective interpretation of nociceptive input influenced by cognitive, neurophysiological and environmental factors (Legrain et al., 2002; Tracey and Mantyh, 2007).

Consequently, both the perceptual and the brain responses evoked by pain exhibit considerable natural variability both between individuals and across multiple experimental trials (Coghill et al., 2003; Nielsen et al., 2009; Stancak et al., 2011).

The perception of pain from nociception is generated by a spatially-distributed network of brain regions (Apkarian et al., 2005; Peyron et al., 2000) and recent fMRI studies have highlighted the importance of studying network dynamics for understanding the emergence of pain (Boly et al., 2007; Ploner et al., 2010).

Such work reflects a conceptual shift towards an appreciation of the importance of understanding the functional architecture of the brain as represented by intrinsically connected networks (ICNs), whose regional activity is correlated during the resting-state, and modulated by external inputs (Smith et al., 2009).

The importance of brain network dynamics in supporting cognitive function is becoming increasingly clear (Bressler and Menon, 2010).

We broadly summarise the contribution of ICN dynamics to task performance and behavioural outcomes at three spatio-temporal scales as:

1) (Ongoing) facilitating short-term, network response priming such that pre-stimulus ICN activity influences the behavioural and/or brain response to a subsequent stimulus (Becker et al., 2011; Sadaghiani et al., 2009);

2) (Concurrent) providing an active contribution through signalling occurring during task performance (Fox et al., 2007; Kelly et al., 2008);

3) (Intrinsic) defining core properties of ICNs, such as resting-state signal coherence, that determine parameters of behavioural (Mennes et al., 2011) or brain responses (Kannurpatti et al., 2012; Keller et al., 2011).

Here we use simultaneous EEG–fMRI recordings during rest and fixed-temperature, noxious, thermal stimulation to investigate the contributions of these three mechanisms to the natural variability in behavioural and brain responses.

EEG–fMRI presents a powerful tool to study this phenomenon as:

1) fMRI provides the high spatial resolution whole-brain coverage required to measure the activity of the distributed brain areas that comprise ICNs;

2) EEG records the dynamics of brain activity directly, providing measurements of neuronal response features with high temporal resolution. This allows investigation of how variability in these features correlates with regional haemodynamic response amplitudes;

3) Indices of cortical excitability, such as the 8–13 Hz alpha oscillation which has been shown to modulate subsequent behavioural and brain responses  (Becker et al., 2011; Hanslmayr et al., 2007; Linkenkaer-Hansen et al., 2004), can be measured from EEG and their effect upon simultaneous fMRI signals observed.

It is important to characterise both inter- and intra-subject response variability in order to fully understand the link between the brain’s response to pain and the subjects’ perception of pain.

However, the majority of neuroimaging studies analyse only a subset of potential functional indices which restricts interpretation of the complex and parallel brain processes underlying a given behaviour.

In this study we aim to take a more comprehensive approach, by investigating the influence of multiple ICNs at a range of temporal scales.

The article then provides all the details of the materials and methods used.

Discussion

Delivering a fixed-temperature, noxious stimulus input enabled us to demonstrate that Ongoing, Concurrent and Intrinsic ICN mechanisms all contribute to the natural inter- and intra-individual response variability that forms a fundamental but often overlooked feature of all psychological and neuroimaging studies

We investigated the relationship between

  • subjective ratings of pain intensity,
  • BOLD haemodynamic responses,
  • EEG evoked potentials,
  • EEG alpha-power,
  • pre- and peri-stimulus BOLD signals in multiple ICNs, and
  • resting-state functional connectivity.

Dependent on brain region and time relative to stimulation, all of these factors contributed to the observed response variability.

Evidence for the contribution of the three mechanisms can be summarised as follows:

Ongoing:

1) Pre- and peri-stimulus fMRI signals in the DMN are related to the magnitude of the subsequent pain network BOLD response, CHEPs amplitude and subjective pain ratings.
2) The amplitude of CHEPs and the DMN BOLD response to pain stimulation are modulated by the spontaneous power of the EEG alpha oscillation.

Concurrent:

1) Single-trial pain ratings and evoked-potential amplitudes correlate with the BOLD response in sub-regions of the pain network.
2) BOLD responses to thermal pain stimulation in multiple ICNs are related to the trial-by-trial magnitude of pain ratings and CHEPs

Intrinsic:

The amplitude of the BOLD response to thermal pain stimulation in pain network regions is correlated with the strength of functional connectivity between those same regions during the resting-state.

It must be remembered that considering any of these effects in isolation represents an oversimplification of the functional integration of the brain processes underlying the stimulus response.

we reveal the importance of dynamic functional interactions between brain regions in shaping the subjective experience of pain and demonstrate that contributions of brain processes at multiple spatio-temporal scales should be considered to fully understand cognitive function.

The article goes into detail under the following headings:

  • Contributions to response variability in the pain network
  • Widespread modulation of ICNs by pain stimulation
  • Interaction between EEG alpha power and DMN BOLD response to pain
  • Resting-state connectivity predicts amplitude of task-evoked BOLD response

By exploiting natural inter- and intra-individual variability in behavioural and brain responses to constant intensity thermal pain stimulation we have demonstrated that electrophysiological and haemodynamic ICNs contribute to pain perception via all of the Ongoing, Concurrent and Intrinsic mechanisms suggested above.

Our approach of factoring contributions from multiple, interconnected brain processes is relevant to all studies which attempt to link evoked brain responses with behaviour, and demonstrates that exploiting these interactions leads to a more complete understanding of the brain’s response to stimulation, and the psychophysiological emergence of the experience of pain.

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