Although the electrophysiological event-related potential in face processing (e.g. N170) is widely accepted as a face-sensitivity biomarker that is deficient in children with autism spectrum disorders, the time-varying brain networks during face recognition are still awaiting further investigation. To explore the social deficits in autism spectrum disorder, especially the time-varying brain networks during face recognition, the current study analyzed the N170, cortical activity, and time-varying networks under 3 tasks (face-upright, face-inverted, and house-upright) in autism spectrum disorder and typically developing children. The results revealed a smaller N170 amplitude in autism spectrum disorder compared with typically developing, along with decreased cortical activity mainly in occipitotemporal areas. Concerning the time-varying networks, the atypically stronger information flow and brain network connections across frontal, parietal, and temporal regions in autism spectrum disorder were reported, which reveals greater effort was exerted by autism spectrum disorder to obtain comparable performance to the typically developing children, although the amplitude of N170 was still smaller than that of the typically developing children. Different brain activation states and interaction patterns of brain regions during face processing were discovered between autism spectrum disorder and typically developing. These findings shed light on the face-processing mechanisms in children with autism spectrum disorder and provide new insight for understanding the social dysfunction of autism spectrum disorder.

Structural alterations of the basal ganglia occur in patients with Huntington's disease (HD). The aim of this exploratory study was to assess auditory processing mechanisms by functional MRI (fMRI) in patients with premanifest (pHD) and manifest HD to gain more insight in possible alterations in basal ganglia-thalamic circuits. Sixteen HD and 18 pHD as well as corresponding age- and gender-matched controls were included. The pHD group was divided into two subgroups close (cpHD; <10 years) and far pHD (fcHP; >10 years), according to their estimated age of disease onset (eAO). Tone perception and processing were visualized by 3T fMRI by employing repeated tone stimulation through digitally generated pulsed (nu=5Hz) 800-Hz sine tones. We found altered activation in basal ganglia-thalamic circuits in HD and/or pHD compared to controls. (i) The cpHD group presented predominantly down-regulated processes compared to fpHD and HD. (ii) HD presented stronger bilateral activation of the putamen and (iii) fpHD presented stronger bilateral activation of the thalamus and also right caudatum. (iv) Depending on the progress of the disease, a shift towards the activation of more right hemispherical areas can be observed. Our findings seem to reflect an altered activation pattern to auditory stimulation depending on the progression of neuronal dysfunction in HD and pHD. They also stress the involvement of the basal ganglia-thalamic circuits in the processing of sensory auditory stimuli.

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.

This study examined the effects of total sleep deprivation (TSD) on cerebral responses to a verbal learning task with two levels of word difficulty. A total of 32 subjects were studied with functional magnetic resonance imaging (FMRI) after normal sleep and following 36 h of TSD. Cerebral responses to EASY words were identical on both nights, but several brain regions showed increased activation to HARD words following TSD compared with following a normal night of sleep (NORM). These regions included bilateral inferior frontal gyrus, bilateral dorsolateral prefrontal cortex, and bilateral inferior parietal lobe. Better free recall performance on the HARD words after TSD was related to increased cerebral responses within the left inferior and superior parietal lobes and left inferior frontal gyrus. Recall was negatively related to activation within the right inferior frontal gyrus. Overall, the findings support the predictions of the compensatory recruitment hypothesis that task demands influence both the likelihood and location of increased cerebral activation during task performance following TSD, and refine that hypothesis by identifying a specific task demand that plays a role. The performance relationships suggest increased activation may be both beneficial (compensatory) and interfere with task performance, depending on the brain regions involved.

This paper presents a fast method for delineation of activated areas of the brain from functional magnetic resonance imaging (fMRI) time series data. The steps of the work accomplished are as follows. 1) It is shown that the detection performance evaluated by the area under the receiver operating characteristic curve is directly related to the signal-to-noise ratio (SNR) of the composite image generated in the detection process. 2) Detection and segmentation of activated areas are formulated in a vector space framework. In this formulation, a linear transformation (image combination method) is shown to be desirable to maximize the SNR of the activated areas subject to the constraint of removing inactive areas. 3) An analytical solution for the problem is found. 4) Image pixel vectors and expected time series pattern (signature) for inactive pixels are used to calculate weighting vector and identify activated regions. 5) Signatures of the activated regions are used to segment different activities. 6) Segmented images by the proposed method are compared with those generated by the conventional methods (correlation, t-statistic, and z statistic). Detection performance and SNRs of the images are compared. The proposed approach outperforms the conventional methods of fMRI analysis. In addition, it is model-independent and does not require a priori knowledge of the fMRI response to the paradigm. Since the method is linear and most of the work is done analytically, numerical implementation and execution of the method are much faster than the conventional methods.

Brain imaging based on functional magnetic resonance imaging (fMRI) provides a useful tool to examine neural networks and cerebral structures subserving visuospatial function. It allows not only the qualitative determination of which areas are active during task processing, but also estimates the quantitative contribution of involved brain regions to different aspects of spatial processing. In this study, we investigated in 10 healthy subjects how the amount of task (computational) demand in an angle discrimination task was related to neural activity as measured with event-related fMRI. Task demand, indicated by behavioral performance, was modulated by presenting clocks with different angular disparity and length of hands. Significant activations were found in the cortical network subserving the visual and visuospatial processing, including the right and left superior parietal lobules (SPL), striate visual areas, and sensorimotor areas. Both blood oxygenation level-dependent (BOLD) signal strength and spatial extent of activation in right as well as left SPL increased with task demand. By contrast, no significant correlation or a very weak correlation was found between the task demand and the BOLD signal as well as between task demand and spatial extent of activations in the striate visual areas and in the sensorimotor areas. These results support the hypothesis that increased computational demand requires more brain resources. The brain regions that are most specialized for the execution of the visuospatial task can be assessed by relating the imposed task demand to the functional activation measured.

This study examined the effects of Huntington's disease (HD) on neural activity during performance of the Porteus maze task. fMRI data were acquired from three HD patients and three controls. Reduced fMRI signal was observed in the patients relative to the controls in occipital, parietal and somato-motor cortex and in the caudate, while increased signal was found in HD in the left postcentral and right middle frontal gyri. The altered fMRI responses in HD patients may result from neural, metabolic, neurovascular coupling and/or hemodynamic differences associated with this disorder.