scholarly journals Theta-burst TMS to the posterior superior temporal sulcus decreases resting-state fMRI connectivity across the face processing network

2020 ◽  
Vol 4 (3) ◽  
pp. 746-760 ◽  
Author(s):  
Daniel A. Handwerker ◽  
Geena Ianni ◽  
Benjamin Gutierrez ◽  
Vinai Roopchansingh ◽  
Javier Gonzalez-Castillo ◽  
...  

Humans process faces by using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. We approximated the effects of damage to the face network in neurologically normal human participants by using theta burst transcranial magnetic stimulation (TBS). Multi-echo functional magnetic resonance imaging (fMRI) resting-state data were collected pre- and post-TBS delivery over the face-selective right superior temporal sulcus (rpSTS), or a control site in the right motor cortex. Results showed that TBS delivered over the rpSTS reduced resting-state connectivity across the extended face processing network. This connectivity reduction was observed not only between the rpSTS and other face-selective areas, but also between nonstimulated face-selective areas across the ventral, medial, and lateral brain surfaces (e.g., between the right amygdala and bilateral fusiform face areas and occipital face areas). TBS delivered over the motor cortex did not produce significant changes in resting-state connectivity across the face processing network. These results demonstrate that, even without task-induced fMRI signal changes, disrupting a single node in a brain network can decrease the functional connectivity between nodes in that network that have not been directly stimulated.

2019 ◽  
Author(s):  
Daniel A Handwerker ◽  
Geena Ianni ◽  
Benjamin Gutierrez ◽  
Vinai Roopchansingh ◽  
Javier Gonzalez-Castillo ◽  
...  

AbstractHumans process faces using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. We approximated the effects of damage to the face network in neurologically normal human participants using thetaburst transcranial magnetic stimulation (TBS). Multi-echo functional magnetic resonance imaging (fMRI) resting-state data were collected pre- and post-TBS delivery over the face-selective right superior temporal sulcus (rpSTS), or a control site in the right motor cortex. Results showed that TBS delivered over the rpSTS reduced resting-state connectivity across the extended face-processing network. This connectivity reduction was observed not only between the rpSTS and other face-selective areas, but also between non-stimulated face-selective areas across the ventral, medial and lateral brain surfaces (e.g. between the right amygdala and bilateral fusiform face areas and occipital face areas). TBS delivered over the motor cortex did not produce significant changes in resting-state connectivity across the face-processing network. These results demonstrate that, even without task-induced fMRI signal changes, disrupting a single node in a brain network can decrease the functional connectivity between nodes in that network that have not been directly stimulated.Author SummaryHuman behavior is dependent on brain networks that perform different cognitive functions. We combined thetaburst transcranial magnetic stimulation (TBS) with resting-state fMRI to study the face processing network. Disruption of the face-selective right posterior superior temporal sulcus (rpSTS) reduced fMRI connectivity across the face network. This impairment in connectivity was observed not only between the rpSTS and other face-selective areas, but also between non-stimulated face-selective areas on the ventral and medial brain surfaces (e.g. between the right amygdala and bilateral fusiform face areas and occipital face areas). Thus, combined TBS/fMRI can be used to approximate and measure the effects of focal brain damage on brain networks, and suggests such an approach may be useful for mapping intrinsic network organization.Technical TermsTBS vs TMSTranscranial magnetic stimulation (TMS) is a method that induces current in neural tissue by using a rapidly changing magnetic field. The pattern of magnetic field changes can vary. Thetaburst TMS (TBS) is a type of TMS where the same stimulation pattern fluctuates at around a 5Hz cycle.Multi-echo fMRIDuring typical fMRI, protons are excited and there is a delay, the echo time, before data are collected. That delay is typically designed to result in a high contrast for blood oxygenation differences. In multi-echo fMRI, data are collected at several echo times each time protons are excited. This results in data that have different levels of contrast for blood oxygenation differences. This added information can be used to empirically decrease noise.Face networkA group of brain regions that show significant activity changes in response to visual face stimuli. While these regions have been defined using univariate analyses with task-based fMRI, they often significantly correlate with each other at rest. In this manuscript, the following regions were a priori defined as part of the face network: posterior superior temporal sulcus (pSTS), amygdala, fusiform face area (FFA), and occipital face area (OFA).Matrix based analysis (MBA)A recent approach that uses a Bayesian multilevel modeling framework to identify pairs of ROIs where a decrease in correlation magnitude was larger than expected along with a measure of statistical evidence. With this approach, correlations between all pairs of ROIs are assessed as part of a single model rather than many independent statistical tests.


2021 ◽  
pp. 1-14
Author(s):  
Jie Huang ◽  
Paul Beach ◽  
Andrea Bozoki ◽  
David C. Zhu

Background: Postmortem studies of brains with Alzheimer’s disease (AD) not only find amyloid-beta (Aβ) and neurofibrillary tangles (NFT) in the visual cortex, but also reveal temporally sequential changes in AD pathology from higher-order association areas to lower-order areas and then primary visual area (V1) with disease progression. Objective: This study investigated the effect of AD severity on visual functional network. Methods: Eight severe AD (SAD) patients, 11 mild/moderate AD (MAD), and 26 healthy senior (HS) controls undertook a resting-state fMRI (rs-fMRI) and a task fMRI of viewing face photos. A resting-state visual functional connectivity (FC) network and a face-evoked visual-processing network were identified for each group. Results: For the HS, the identified group-mean face-evoked visual-processing network in the ventral pathway started from V1 and ended within the fusiform gyrus. In contrast, the resting-state visual FC network was mainly confined within the visual cortex. AD disrupted these two functional networks in a similar severity dependent manner: the more severe the cognitive impairment, the greater reduction in network connectivity. For the face-evoked visual-processing network, MAD disrupted and reduced activation mainly in the higher-order visual association areas, with SAD further disrupting and reducing activation in the lower-order areas. Conclusion: These findings provide a functional corollary to the canonical view of the temporally sequential advancement of AD pathology through visual cortical areas. The association of the disruption of functional networks, especially the face-evoked visual-processing network, with AD severity suggests a potential predictor or biomarker of AD progression.


2014 ◽  
Vol 34 (20) ◽  
pp. 6849-6859 ◽  
Author(s):  
C. Nettekoven ◽  
L. J. Volz ◽  
M. Kutscha ◽  
E.-M. Pool ◽  
A. K. Rehme ◽  
...  

2021 ◽  
Vol 15 ◽  
Author(s):  
Yanling Li ◽  
Xin Dai ◽  
Huawang Wu ◽  
Lijie Wang

Major depressive disorder (MDD) is a severe mental disorder and is lacking in biomarkers for clinical diagnosis. Previous studies have demonstrated that functional abnormalities of the unifying triple networks are the underlying basis of the neuropathology of depression. However, whether the functional properties of the triple network are effective biomarkers for the diagnosis of depression remains unclear. In our study, we used independent component analysis to define the triple networks, and resting-state functional connectivities (RSFCs), effective connectivities (EC) measured with dynamic causal modeling (DCM), and dynamic functional connectivity (dFC) measured with the sliding window method were applied to map the functional interactions between subcomponents of triple networks. Two-sample t-tests with p < 0.05 with Bonferroni correction were used to identify the significant differences between healthy controls (HCs) and MDD. Compared with HCs, the MDD showed significantly increased intrinsic FC between the left central executive network (CEN) and salience network (SAL), increased EC from the right CEN to left CEN, decreased EC from the right CEN to the default mode network (DMN), and decreased dFC between the right CEN and SAL, DMN. Moreover, by fusion of the changed RSFC, EC, and dFC as features, support vector classification could effectively distinguish the MDD from HCs. Our results demonstrated that fusion of the multiple functional connectivities measures of the triple networks is an effective way to reveal functional disruptions for MDD, which may facilitate establishing the clinical diagnosis biomarkers for depression.


2019 ◽  
Vol 31 (10) ◽  
pp. 1573-1588 ◽  
Author(s):  
Eelke de Vries ◽  
Daniel Baldauf

We recorded magnetoencephalography using a neural entrainment paradigm with compound face stimuli that allowed for entraining the processing of various parts of a face (eyes, mouth) as well as changes in facial identity. Our magnetic response image-guided magnetoencephalography analyses revealed that different subnodes of the human face processing network were entrained differentially according to their functional specialization. Whereas the occipital face area was most responsive to the rate at which face parts (e.g., the mouth) changed, and face patches in the STS were mostly entrained by rhythmic changes in the eye region, the fusiform face area was the only subregion that was strongly entrained by the rhythmic changes in facial identity. Furthermore, top–down attention to the mouth, eyes, or identity of the face selectively modulated the neural processing in the respective area (i.e., occipital face area, STS, or fusiform face area), resembling behavioral cue validity effects observed in the participants' RT and detection rate data. Our results show the attentional weighting of the visual processing of different aspects and dimensions of a single face object, at various stages of the involved visual processing hierarchy.


2019 ◽  
Vol 30 (5) ◽  
pp. 2986-2996
Author(s):  
Xue Tian ◽  
Ruosi Wang ◽  
Yuanfang Zhao ◽  
Zonglei Zhen ◽  
Yiying Song ◽  
...  

Abstract Previous studies have shown that individuals with developmental prosopagnosia (DP) show specific deficits in face processing. However, the mechanism underlying the deficits remains largely unknown. One hypothesis suggests that DP shares the same mechanism as normal population, though their faces processing is disproportionally impaired. An alternative hypothesis emphasizes a qualitatively different mechanism of DP processing faces. To test these hypotheses, we instructed DP and normal individuals to perceive faces and objects. Instead of calculating accuracy averaging across stimulus items, we used the discrimination accuracy for each item to construct a multi-item discriminability pattern. We found DP’s discriminability pattern was less similar to that of normal individuals when perceiving faces than perceiving objects, suggesting that DP has qualitatively different mechanism in representing faces. A functional magnetic resonance imaging study was conducted to reveal the neural basis and found that multi-voxel activation patterns for faces in the right fusiform face area and occipital face area of DP were deviated away from the mean activation pattern of normal individuals. Further, the face representation was more heterogeneous in DP, suggesting that deficits of DP may come from multiple sources. In short, our study provides the first direct evidence that DP processes faces qualitatively different from normal population.


Neuron ◽  
2011 ◽  
Vol 70 (2) ◽  
pp. 352-362 ◽  
Author(s):  
Shih-Pi Ku ◽  
Andreas S. Tolias ◽  
Nikos K. Logothetis ◽  
Jozien Goense

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