Evoked brain responses are generated by feedback loops

Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, United Kingdom.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 01/2008; 104(52):20961-6. DOI: 10.1073/pnas.0706274105
Source: PubMed

ABSTRACT Neuronal responses to stimuli, measured electrophysiologically, unfold over several hundred milliseconds. Typically, they show characteristic waveforms with early and late components. It is thought that early or exogenous components reflect a perturbation of neuronal dynamics by sensory input bottom-up processing. Conversely, later, endogenous components have been ascribed to recurrent dynamics among hierarchically disposed cortical processing levels, top-down effects. Here, we show that evoked brain responses are generated by recurrent dynamics in cortical networks, and late components of event-related responses are mediated by backward connections. This evidence is furnished by dynamic causal modeling of mismatch responses, elicited in an oddball paradigm. We used the evidence for models with and without backward connections to assess their likelihood as a function of peristimulus time and show that backward connections are necessary to explain late components. Furthermore, we were able to quantify the contribution of backward connections to evoked responses and to source activity, again as a function of peristimulus time. These results link a generic feature of brain responses to changes in the sensorium and a key architectural component of functional anatomy; namely, backward connections are necessary for recurrent interactions among levels of cortical hierarchies. This is the theoretical cornerstone of most modern theories of perceptual inference and learning.

Download full-text


Available from: Marta I Garrido, Aug 22, 2015
  • Source
    • "This finding contrasts with the interpretation of these potentials as objective pain intensity markers, suggesting that the magnitude of the N2 response cannot be considered a direct read-out of pain intensity (Bromm and Lorenz, 1998), but rather reflects a complex pain-related process integrating stimulus salience and cognitive expectations (e.g., Legrain et al., 2011). This pattern of N2 potentials fits with recent evidence that both sensory prediction errors conveyed by forward connections and top-down predictions conveyed by backward connections are implicated in the generation of late cortical ERPs (N100 ms) (Garrido et al., 2007). For example, when a subject expects to have less pain (inhibitory mental imagery), but actually receive a painful stimulus, this would produce a net positive pain prediction error. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Mental imagery has the potential to influence perception by directly altering sensory, cognitive, and affective brain activity associated with imagined content. While it is well established that mental imagery can both exacerbate and alleviate acute and chronic pain, it is currently unknown how imagery mechanisms regulate pain perception. For example, studies to date have been unable to determine whether imagery effects depend upon a general redirection of attention away from pain or related focused attentional mechanisms. To address these issues, we recorded subjective, behavioral and ERP responses using 64-channel EEG while healthy human participants applied a mental imagery strategy to decrease or increase pain sensations. When imagining a glove covering the forearm, participants reported decreased perceived intensity and unpleasantness, classified fewer high-intensity stimuli as painful, and showed a more conservative response bias. In contrast, when imagining a lesion on the forearm, participants reported increased pain intensity and unpleasantness, classified more low-intensity stimuli as painful, and displayed a more liberal response bias. Using a mass-univariate approach, we further showed differential modulation of the N2 potentials across conditions, with inhibition and facilitation respectively increasing and decreasing N2 amplitudes between 122 and 180 ms. Within this time window, source localization associated inhibiting vs. facilitating pain with neural activity in cortical regions involved in cognitive inhibitory control and in the retrieval of semantic information (i.e., right inferior frontal and temporal regions). In contrast, the main sources of neural activity associated with facilitating vs. inhibiting pain were identified in cortical regions typically implicated in salience processing and emotion regulation (i.e., left insular, inferior-middle frontal, supplementary motor and precentral regions). Overall, these findings suggest that the content of a mental image directly alters pain-related decision and evaluative processing to flexibly produce hypoalgesic and hyperalgesic outcomes. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 07/2015; DOI:10.1016/j.neuroimage.2015.07.008 · 6.36 Impact Factor
  • Source
    • "Following the initial paper by Garrido et al. (2007a, 2007b), and confirmed by our identified localised sources (Youssofzadeh et al., 2013), we constructed a DCM network of five interconnected units (sources) consisting of right/left primary auditory cortex (r/lA1), right/left superior temporal gyrus (r/lSTG), and right inferior frontal gyrus (rIFG). Informed by the Montreal Neurological Institute (MNI) coordinates, the sources were set to be modelled using equivalent current dipoles (Kiebel et al., 2008a). "
    [Show description] [Hide description]
    DESCRIPTION: In this work, we provide an extension to commonly used neural mass models (NMMs) by incorporating self-feedback connections within three main neuronal populations, including our proposed NMM with full self-feedback (FSM). Compared to a commonly used NMM (Jansen and Ritt model), dynamical system analysis and spectral representations show FSM to be capable of robustly generating all EEG rhythms over a wide range of frequencies. Under Bayesian inversion approach, we validate the NMMs fitted outputs with ERP data, and found that FSM best replicates all the individual channel data. Moreover, posterior correlation of interdependencies among model parameters shows that self-feedback within deep-layer excitatory neuronal population does not contribute much to the generated evoked response. Next, we incorporate inter-areal connectivity to the NMMs using dynamic causal modelling approach. Our results show a reasonable match with experimental recordings for both single and multi-unit channel data. Interestingly, we also found the multi-area Jansen-Rit model to perform as well as the FSM.
  • Source
    • "where the term k ij = 1 for area-to-area feedforward connections of W ee and k ij = À1 for feedback connections. This was implemented due to evidence showing that feedback activity contributes to responses that have a polarity opposite to that of the N1m (Garrido et al., 2007). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Incoming sounds are represented in the context of preceding events, and this requires a memory mechanism that integrates information over time. Here, it was demonstrated that response adaptation, the suppression of neural responses due to stimulus repetition, might reflect a computational solution that auditory cortex uses for temporal integration. Adaptation is observed in single-unit measurements as two-tone forward masking effects and as stimulus-specific adaptation (SSA). In non-invasive observations, the amplitude of the auditory N1m response adapts strongly with stimulus repetition, and it is followed by response recovery (the so-called mismatch response) to rare deviant events. The current computational simulations described the serial core-belt-parabelt structure of auditory cortex, and included synaptic adaptation, the short-term, activity-dependent depression of excitatory corticocortical connections. It was found that synaptic adaptation is sufficient for columns to respond selectively to tone pairs and complex tone sequences. These responses were defined as combination sensitive, thus reflecting temporal integration, when a strong response to a stimulus sequence was coupled with weaker responses both to the time-reversed sequence and to the isolated sequence elements. The temporal complexity of the stimulus seemed to be reflected in the proportion of combination-sensitive columns across the different regions of the model. Our results suggest that while synaptic adaptation produces facilitation and suppression effects, including SSA and the modulation of the N1m response, its functional significance may actually be in its contribution to temporal integration. This integration seems to benefit from the serial structure of auditory cortex. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
    European Journal of Neuroscience 03/2015; 41(5):615-30. DOI:10.1111/ejn.12820 · 3.67 Impact Factor
Show more