Parallel Processing of Nociceptive and Non-nociceptive Somatosensory Information in the Human Primary and Secondary Somatosensory Cortices: Evidence from Dynamic Causal Modeling of Functional Magnetic Resonance Imaging Data

Liang, Meng; Mouraux, André; Iannetti, Gian Domenico

doi:10.1523/jneurosci.6207-10.2011

Cited by 82 publications

(85 citation statements)

References 78 publications

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“…Second, our feedforward and recurrent models fitted equally well to early segments of the EEG data, suggesting that the feed- forward connections were sufficient to explain the early data epochs (but see Nicolelis et al, 1998, Liang et al, 2011 for alternative accounts based on parallel processing). It should be noted that, although such evidence does not allow for a conclusion that recurrent activity is absent in short epochs, it indicates that the effects of recurrent activity only contribute to explaining differences in longer EEG segments.…”

Section: Early Feedforward Activationmentioning

confidence: 82%

Recurrent Neural Processing and Somatosensory Awareness

Auksztulewicz¹,

Spitzer²,

Blankenburg³

2012

J. Neurosci.

100

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The neural mechanisms of stimulus detection, despite extensive research, remain elusive. The recurrent processing hypothesis, a prominent theoretical account of perceptual awareness, states that, although stimuli might in principle evoke feedforward activity propagating through the visual cortex, stimuli that become consciously detected are further processed in feedforward-feedback loops established between cortical areas. To test this theory in the tactile modality, we applied dynamic causal modeling to electroencephalography (EEG) data acquired from humans in a somatosensory detection task. In the analysis of stimulation-induced event-related potentials (ERPs), we focused on model-based evidence for feedforward, feedback, and recurrent processing between primary and secondary somatosensory cortices. Bayesian model comparison revealed that, although early EEG components were well explained by both the feedforward and the recurrent models, the recurrent model outperformed the other models when later EEG segments were analyzed. Within the recurrent model, stimulus detection was characterized by a relatively early strength increase of the feedforward connection from primary to secondary somatosensory cortex (Ͼ80 ms). At longer latencies (Ͼ140 ms), also the feedback connection showed a detection-related strength increase. The modeling results on relative evidence between recurrent and feedforward model comparison support the hypothesis that the ERP responses from sensory areas arising after aware stimulus detection can be explained by increased recurrent processing within the somatosensory network in the later stages of stimulus processing.

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Section: Early Feedforward Activationmentioning

confidence: 82%

Recurrent Neural Processing and Somatosensory Awareness

Auksztulewicz¹,

Spitzer²,

Blankenburg³

2012

J. Neurosci.

100

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“…The correlations were given by the mutual regression slopes. The ventral thalamus was chosen as the initial seed region based on its known role as a primary relay of sensory input to the cortex (Ab Aziz and Ahmad, 2006;Liang et al, 2011). The voxels from which activity vs time courses were extracted were taken from the main effect of 'stimulus' in the GLM analysis.…”

Section: Discussionmentioning

confidence: 99%

Brain Mapping-Based Model of Δ9-Tetrahydrocannabinol Effects on Connectivity in the Pain Matrix

Walter

Oertel

Felden

et al. 2015

Neuropsychopharmacol

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Cannabinoids receive increasing interest as analgesic treatments. However, the clinical use of Δ 9 -tetrahydrocannabinol (Δ 9 -THC) has progressed with justified caution, which also owes to the incomplete mechanistic understanding of its analgesic effects, in particular its interference with the processing of sensory or affective components of pain. The present placebo-controlled crossover study therefore focused on the effects of 20 mg oral THC on the connectivity between brain areas of the pain matrix following experimental stimulation of trigeminal nocisensors in 15 non-addicted healthy volunteers. A general linear model (GLM) analysis identified reduced activations in the hippocampus and the anterior insula following THC administration. However, assessment of psychophysiological interaction (PPI) revealed that the effects of THC first consisted in a weakening of the interaction between the thalamus and the secondary somatosensory cortex (S2). From there, dynamic causal modeling (DCM) was employed to infer that THC attenuated the connections to the hippocampus and to the anterior insula, suggesting that the reduced activations in these regions are secondary to a reduction of the connectivity from somatosensory regions by THC. These findings may have consequences for the way THC effects are currently interpreted: as cannabinoids are increasingly considered in pain treatment, present results provide relevant information about how THC interferes with the affective component of pain. Specifically, the present experiment suggests that THC does not selectively affect limbic regions, but rather interferes with sensory processing which in turn reduces sensory-limbic connectivity, leading to deactivation of affective regions.

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“…The assessment of effective connectivity measures provides a unique opportunity to determine whether and how activity in different regions within a specific network influences the activity in other regions during a certain task (actually, DCM has been improved for resting-state fMRI data [58] ). DCM has already been applied successfully to test competing hypotheses in the sensory fields of neuroscience, such as to investigate the interhemispheric integration of visual processing [59] , the suppressive influence of the supplementary motor area on primary motor cortex in motor imagery [60] , and somatosensory information processing in primary and secondary somatosensory cortices [61] . In addition, DCM has been successfully applied to more complex cognitive tasks, such as face perception [62] and the cortical interactions related to reading and speech processing [63] .…”

Section: Task-induced Effective Connectivity Network Asmentioning

confidence: 99%

A review of functional magnetic resonance imaging for Brainnetome

Song

Jiang

2012

Neurosci. Bull.

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Abstract:The functional brain network using blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has revealed the potentials for probing brain architecture, as well as for identifying clinical biomarkers for brain diseases. In the general context of Brainnetome, this review focuses on the development of approaches for modeling and analyzing functional brain networks with BOLD fMRI. The prospects for these approaches are also discussed.

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Parallel Processing of Nociceptive and Non-nociceptive Somatosensory Information in the Human Primary and Secondary Somatosensory Cortices: Evidence from Dynamic Causal Modeling of Functional Magnetic Resonance Imaging Data

Cited by 82 publications

References 78 publications

Recurrent Neural Processing and Somatosensory Awareness

Recurrent Neural Processing and Somatosensory Awareness

Brain Mapping-Based Model of Δ9-Tetrahydrocannabinol Effects on Connectivity in the Pain Matrix

A review of functional magnetic resonance imaging for Brainnetome

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