Thickness of Deep Layers in the Fusiform Face Area Predicts Face Recognition.
- 作者列表："McGugin RW","Newton AT","Tamber-Rosenau B","Tomarken A","Gauthier I
:People with superior face recognition have relatively thin cortex in face-selective brain areas, whereas those with superior vehicle recognition have relatively thick cortex in the same areas. We suggest that these opposite correlations reflect distinct mechanisms influencing cortical thickness (CT) as abilities are acquired at different points in development. We explore a new prediction regarding the specificity of these effects through the depth of the cortex: that face recognition selectively and negatively correlates with thickness of the deepest laminar subdivision in face-selective areas. With ultrahigh resolution MRI at 7T, we estimated the thickness of three laminar subdivisions, which we term "MR layers," in the right fusiform face area (FFA) in 14 adult male humans. Face recognition was negatively associated with the thickness of deep MR layers, whereas vehicle recognition was positively related to the thickness of all layers. Regression model comparisons provided overwhelming support for a model specifying that the magnitude of the association between face recognition and CT differs across MR layers (deep vs. superficial/middle) whereas the magnitude of the association between vehicle recognition and CT is invariant across layers. The total CT of right FFA accounted for 69% of the variance in face recognition, and thickness of the deep layer alone accounted for 84% of this variance. Our findings demonstrate the functional validity of MR laminar estimates in FFA. Studying the structural basis of individual differences for multiple abilities in the same cortical area can reveal effects of distinct mechanisms that are not apparent when studying average variation or development.
: 面部识别优势的人在面部选择性脑区的皮层相对较薄，而车辆识别优势的人在相同区域的皮层相对较厚。我们认为，这些相反的相关性反映了影响皮质厚度 (CT) 的不同机制，因为能力是在发育的不同点获得的。我们通过皮层深度探索了关于这些效应特异性的新预测: 面部识别与面部选择性区域最深层流细分的厚度有选择性和负相关。采用 7 T 超高分辨率 MRI，我们估计了 14 例成年男性右侧梭形面部 (FFA) 三个椎板亚区的厚度，我们称之为 “MR 层”。人脸识别与深层 MR 层的厚度呈负相关，而车辆识别与所有层的厚度呈正相关。回归模型比较为一个模型提供了压倒性的支持，该模型指定了人脸识别和 CT 之间的关联程度在 MR 层中不同 (深与浅/中) 而车辆识别和 CT 之间的关联大小跨层不变。右侧 FFA 的总 CT 占人脸识别方差的 69%，仅深层厚度占该方差的 84%。我们的研究结果证明了 FFA 中 MR 层流估计的功能有效性。研究同一皮质区域多种能力的个体差异的结构基础，可以揭示在研究平均变异或发育时不明显的不同机制的影响。
METHODS::In recent years, transcranial electrical stimulation (tES) has been used to improve cognitive and perceptual abilities and to boost learning. In the visual domain, transcranial random noise stimulation (tRNS), a type of tES in which electric current is randomly alternating in between two electrodes at high frequency, has shown potential in inducing long lasting perceptual improvements when coupled with tasks such as contrast detection. However, its cortical mechanisms and online effects have not been fully understood yet, and it is still unclear whether these long-term improvements are due to early-stage perceptual enhancements of contrast sensitivity or later stage mechanisms such as learning consolidation. Here we tested tRNS effects on multiple spatial frequencies and orientation, showing that tRNS enhances detection of a low contrast Gabor, but only for oblique orientation and high spatial frequency (12 cycles per degree of visual angle). No improvement was observed for low contrast and vertical stimuli. These results indicate that tRNS can enhance contrast sensitivity already after one training session, however this early onset is dependent on characteristics of the stimulus such as spatial frequency and orientation. In particular, the shallow depth of tRNS is likely to affect superficial layers of the visual cortex where neurons have higher preferred spatial frequencies than cells in further layers, while the lack of effect on vertical stimuli might reflect the optimization of the visual system to see cardinally oriented low contrast stimuli, leaving little room for short-term improvement. Taken together, these results suggest that online tRNS effects on visual perception are the result of a complex interaction between stimulus intensity and cortical anatomy, consistent with previous literature on brain stimulation.
METHODS:OBJECTIVE:There is growing interest in treating diseases by electrical stimulation and block of peripheral autonomic nerves, but a paucity of studies on excitation and block of small diameter autonomic axons. We conducted in vivo quantification of the strength-duration properties, activity-dependent slowing (ADS), and responses to kilohertz frequency (KHF) signals for the rat vagus nerve (VN). APPROACH:We conducted acute in vivo experiments in urethane-anesthetised rats. We placed two cuff electrodes on the left cervical VN and one cuff electrode on the anterior subdiaphragmatic VN. The rostral cervical cuff was used to deliver pulses to quantify recruitment and ADS. The caudal cervical cuff was used to deliver KHF signals. The subdiaphragmatic cuff was used to record compound action potentials (CAPs). MAIN RESULTS:We quantified the input-output recruitment and strength-duration curves. Fits to the data using standard strength-duration equations were qualitatively similar, but the resulting chronaxie and rheobase estimates varied substantially. We measured larger thresholds for the slowest fibres (0.5 to 1 m/s), especially at shorter pulse widths. Using a novel cross-correlation CAP-based analysis, we measured ADS of ~2.3% after 3 min of 2 Hz stimulation, which is comparable to ADS reported for sympathetic efferents in somatic nerves, but much smaller than ADS in cutaneous nociceptors. We found greater ADS with higher stimulation frequency and non-monotonic changes in CV in select cases. We found monotonically increasing block thresholds across frequencies from 10 to 80 kHz for both fast and slow fibres. Further, following 25 s of KHF signal, neural conduction could require tens of seconds to recover. SIGNIFICANCE:The quantification of mammalian autonomic nerve responses to conventional and KHF signals provides essential information for development of peripheral nerve stimulation therapies and for understanding their mechanisms of action.
METHODS:BACKGROUND:Early accounts of forced thought were reported at the onset of a focal seizure, and characterized as vague, repetitive, and involuntary intellectual auras distinct from perceptual or psychic hallucinations or illusions. Here, we examine the neural underpinnings involved in conceptual thought by presenting a series of 3 patients with epilepsy reporting intrusive thoughts during electrical stimulation of the left lateral prefrontal cortex (PFC) during invasive surgical evaluation. We illustrate the widespread networks involved through two independent brain imaging modalities: resting state functional magnetic resonance imaging (fMRI) (rs-fMRI) and task-based meta-analytic connectivity modeling (MACM). METHODS:We report the clinical and stimulation characteristics of three patients with left hemispheric language dominance who demonstrate forced thought with functional mapping. To examine the brain networks underlying this phenomenon, we used the regions of interest (ROI) centered at the active electrode pairs. We modeled functional networks using two approaches: (1) rs-fMRI functional connectivity analysis, representing 81 healthy controls and (2) meta-analytic connectivity modeling (MACM), representing 8260 healthy subjects. We also determined the overlapping regions between these three subjects' rs-fMRI and MACM networks through a conjunction analysis. RESULTS:We identified that left PFC was associated with a large-scale functional network including frontal, temporal, and parietal regions, a network that has been associated with multiple cognitive functions including semantics, speech, attention, working memory, and explicit memory. CONCLUSIONS:We illustrate the neural networks involved in conceptual thought through a unique patient population and argue that PFC supports this function through activation of a widespread network.