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: 9.67). 01/2008; 104(52):20961-6. DOI: 10.1073/pnas.0706274105
Source: PubMed


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.

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    • "r/lA1, r/lSTG and rIFG) that are significantly involved in the MMN process. This is also in agreement with the results of a modelling study in which the best estimation of MMN response was achieved using a hierarchical interconnected model composed of similar ROIs (Garrido, et al. 2007b). Moreover, we have found strong causal effects in some other areas. "
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    ABSTRACT: Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250-300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modelling.
    Neuroinformatics 10/2015; DOI:10.1007/s12021-015-9281-6 · 2.83 Impact Factor
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    • "Here, we test sensitivity and specificity of the synaptic ion channel inferences available through electrophysiological DCM, utilizing data from two cases of single-gene mutation channelopathies. In order to test these particular patients we augmented a conductance-based neural mass model (Moran et al., 2011c) of regionally specific sources (Garrido et al., 2007) to include ligand-gated sodium, calcium, and chloride channels — as well as voltage-gated potassium and calcium channels (Fig. 1). This augmented model was used to explain auditoryevoked ERFs produced by 94 healthy control participants and 2 patients with known mutations causing loss-of-function in the inward-rectifying potassium channel gene KCNJ2 and in the voltage-gated presynaptic calcium channel gene CACNA1A. "
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    ABSTRACT: Clinical assessments of brain function rely upon visual inspection of electroencephalographic waveform abnormalities in tandem with functional magnetic resonance imaging. However, no current technology proffers in vivo assessments of activity at synapses, receptors and ion-channels, the basis of neuronal communication. Using dynamic causal modeling we compared electrophysiological responses from two patients with distinct monogenic ion channelopathies and a large cohort of healthy controls to demonstrate the feasibility of assaying synaptic-level channel communication non-invasively. Synaptic channel abnormality was identified in both patients (100% sensitivity) with assay specificity above 89%, furnishing estimates of neurotransmitter and voltage-gated ion throughput of sodium, calcium, chloride and potassium. This performance indicates a potential novel application as an adjunct for clinical assessments in neurological and psychiatric settings. More broadly, these findings indicate that biophysical models of synaptic channels can be estimated non-invasively, having important implications for advancing human neuroimaging to the level of non-invasive ion channel assays. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 09/2015; 124. DOI:10.1016/j.neuroimage.2015.08.057 · 6.36 Impact Factor
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    • "However, this more sophisticated approach is based upon the reconstruction of source activity underlying ERP components: if the P3 does not count as an NCC because it can also be elicited by subliminal stimuli (Reuter et al. 1989; Shevrin 2001), then it would seem that its DCM source and connectivity reconstruction (i.e., a mathematical transformation of the same data, plus several assumptions) cannot be an NCC either. This holds as well for ERP responses later than the P3, including the N400 modulated by semantic priming (Kiefer 2002; more below), that are predicted by Garrido et al. (2007) to involve top-down processing. Suppose, however, one could remove ERPs from the picture. "
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    DESCRIPTION: Recently, a number of neuroimaging studies have been conducted, aimed at detecting signs of consciousness in patients with a diagnosis of vegetative or minimally conscious state. The contributions appeared during an ongoing international ethical and socio-legal debate, on the admissibility of decisions to withdraw artificial nutrition from vegetative patients, thereby allowing them to die. We argue that neuroimaging is more likely to contribute to medical diagnosis and decision making if two requirements are met. First, those studies inferred awareness from the neural correlates of cognitive processes that are assumed to involve consciousness. However, neural correlates of consciousness proper, as defined by current philosophy and neuroscience, are the only admissible non-behavioral signs of awareness. Second, in those studies patients attempted to answer medically irrelevant questions by modulating their cortical activity in imagery tasks. We suggest patients should instead be queried on matters relevant to their clinical condition and quality of life.
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