BOLD correlates of edge detection in human auditory cortex

Edges are important cues defining coherent auditory objects. As a model of auditory edges, sound on- and offset are particularly suitable to study their neural underpinnings because they contrast a specific physical input against no physical input. Change from silence to sound, that is onset, has extensively been studied and elicits transient neural responses bilaterally in auditory cortex. However, neural activity associated with sound onset is not only related to edge detection but also to novel afferent inputs. Edges at the change from sound to silence, that is offset, are not confounded by novel physical input and thus allow to examine neural activity associated with sound edges per se. In the first experiment, we used silent acquisition functional magnetic resonance imaging and found that the offset of pulsed sound activates planum temporale, superior temporal sulcus and planum polare of the right hemisphere. In the planum temporale and the superior temporal sulcus, offset response amplitudes were related to the pulse repetition rate of the preceding stimulation. In the second experiment, we found that these offset-responsive regions were also activated by single sound pulses, onset of sound pulse sequences and single sound pulse omissions within sound pulse sequences. However, they were not active during sustained sound presentation. Thus, our data show that circumscribed areas in right temporal cortex are specifically involved in identifying auditory edges. This operation is crucial for translating acoustic signal time series into coherent auditory objects.

Facial affect recognition training in autism: can we animate the fusiform gyrus?

One of the most consistent findings in the neuroscience of autism is hypoactivation of the fusiform gyrus (FG) during face processing. In this study the authors examined whether successful facial affect recognition training is associated with an increased activation of the FG in autism. The effect of a computer-based program to teach facial affect identification was examined in 10 individuals with high-functioning autism. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) changes in the FG and other regions of interest, as well as behavioral facial affect recognition measures, were assessed pre- and posttraining. No significant activation changes in the FG were observed. Trained participants showed behavioral improvements, which were accompanied by higher BOLD fMRI signals in the superior parietal lobule and maintained activation in the right medial occipital gyrus.

Neural correlates of antinociception in borderline personality disorder

CONTEXT: A characteristic feature of borderline personality disorder (BPD) is self-injurious behavior in conjunction with stress-induced reduction of pain perception. Reduced pain sensitivity has been experimentally confirmed in patients with BPD, but the neural correlates of antinociceptive mechanisms in BPD are unknown. We predicted that heat stimuli in patients with BPD would activate brain areas concerned with cognitive and emotional evaluation of pain. OBJECTIVE: To assess the psychophysical properties and neural correlates of altered pain processing in patients with BPD. DESIGN: Case-control study. SETTING: A university hospital. PARTICIPANTS: Twelve women with BPD and self-injurious behavior and 12 age-matched control subjects. INTERVENTIONS: Psychophysical assessment and blood oxygen level-dependent functional magnetic resonance imaging during heat stimulation with fixed-temperature heat stimuli and individual-temperature stimuli adjusted for equal subjective pain in all the participants. MAIN OUTCOME MEASURE: Blood oxygen level-dependent functional magnetic resonance imaging signal changes during heat pain stimulation. RESULTS: Patients with BPD had higher pain thresholds and smaller overall volumes of activity than controls in response to identical heat stimuli. When the stimulus temperature was individually adjusted for equal subjective pain level, overall volumes of activity were similar, although regional patterns differed significantly. Patient response was greater in the dorsolateral prefrontal cortex and smaller in the posterior parietal cortex. Pain also produced neural deactivation in the perigenual anterior cingulate gyrus and the amygdala in patients with BPD. CONCLUSION: The interaction between increased pain-induced response in the dorsolateral prefrontal cortex and deactivation in the anterior cingulate and the amygdala is associated with an antinociceptive mechanism in patients with BPD.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Tracking the subprocesses of decision-based action in the human frontal lobes

Situationally adaptive behavior relies on the identification of relevant target stimuli, the evaluation of these with respect to the current context and the selection of an appropriate action. We used functional magnetic resonance imaging (fMRI) to disentangle the neural networks underlying these processes within a single task. Our results show that activation of mid-ventrolateral prefrontal cortex (PFC) reflects the perceived presence of a target stimulus regardless of context, whereas context-appropriate evaluation is subserved by mid-dorsolateral PFC. Enhancing demands on response selection by means of response conflict activated a network of regions, all of which are directly connected to motor areas. On the midline, rostral anterior paracingulate cortex was found to link target detection and response selection by monitoring for the presence of behaviorally significant conditions. In summary, we provide new evidence for process-specific functional dissociations in the frontal lobes. In target-centered processing, target detection in the VLPFC is separable from contextual evaluation in the DLPFC. Response-centered processing in motor-associated regions occurs partly in parallel to these processes, which may enhance behavioral efficiency, but it may also lead to reaction time increases when an irrelevant response tendency is elicited.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

MODIFIED TEST STATISTICS BY INTER-VOXEL VARIANCE SHRINKAGE WITH AN APPLICATION TO fMRI

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

Reduced neuronal efficacy in progressive mild cognitive impairment: a prospective fMRI study on visuospatial processing

Mild cognitive impairment (MCI) often refers to the preclinical stage of dementia, where the majority develop Alzheimer's disease (AD). Given that neurodegenerative burden and compensatory mechanisms might exist before accepted clinical symptoms of AD are noticeable, the current prospective study aimed to investigate the functioning of brain regions in the visuospatial networks responsible for preclinical symptoms in AD using event-related functional magnetic resonance imaging (fMRI). Eighteen MCI patients were evaluated and clinically followed for approximately 3 years. Five progressed to AD (PMCI) and eight remained stable (SMCI). Thirteen age-, gender- and education-matched controls also participated. An angle discrimination task with varying task demands was used. Brain activation patterns as well as task demand-dependent and -independent signal changes between the groups were investigated by using an extended general linear model including individual performance (reaction time [RT]) of each single trial. Similar behavioral (RT and accuracy) responses were observed between MCI patients and controls. A network of bilateral activations, e.g. dorsal pathway, which increased linearly with increasing task demand, was engaged in all subjects. Compared with SMCI patients and controls, PMCI patients showed a stronger relation between task demand and brain activity in left superior parietal lobules (SPL) as well as a general task demand-independent increased activation in left precuneus. Altered brain function can be detected at a group level in individuals that progress to AD before changes occur at the behavioral level. Increased parietal activation in PMCI could reflect a reduced neuronal efficacy due to accumulating AD pathology and might predict future clinical decline in patients with MCI.

Processing of temporal unpredictability in human and animal amygdala

The amygdala has been studied extensively for its critical role in associative fear conditioning in animals and humans. Noxious stimuli, such as those used for fear conditioning, are most effective in eliciting behavioral responses and amygdala activation when experienced in an unpredictable manner. Here, we show, using a translational approach in mice and humans, that unpredictability per se without interaction with motivational information is sufficient to induce sustained neural activity in the amygdala and to elicit anxiety-like behavior. Exposing mice to mere temporal unpredictability within a time series of neutral sound pulses in an otherwise neutral sensory environment increased expression of the immediate-early gene c-fos and prevented rapid habituation of single neuron activity in the basolateral amygdala. At the behavioral level, unpredictable, but not predictable, auditory stimulation induced avoidance and anxiety-like behavior. In humans, functional magnetic resonance imaging revealed that temporal unpredictably causes sustained neural activity in amygdala and anxiety-like behavior as quantified by enhanced attention toward emotional faces. Our findings show that unpredictability per se is an important feature of the sensory environment influencing habituation of neuronal activity in amygdala and emotional behavior and indicate that regulation of amygdala habituation represents an evolutionary-conserved mechanism for adapting behavior in anticipation of temporally unpredictable events.

Brain responses to auditory and visual stimulus offset: Shared representations of temporal edges

Edges are crucial for the formation of coherent objects from sequential sensory inputs within a single modality. Moreover, temporally coincident boundaries of perceptual objects across different sensory modalities facilitate crossmodal integration. Here, we used functional magnetic resonance imaging in order to examine the neural basis of temporal edge detection across modalities. Onsets of sensory inputs are not only related to the detection of an edge but also to the processing of novel sensory inputs. Thus, we used transitions from input to rest (offsets) as convenient stimuli for studying the neural underpinnings of visual and acoustic edge detection per se. We found, besides modality-specific patterns, shared visual and auditory offset-related activity in the superior temporal sulcus and insula of the right hemisphere. Our data suggest that right hemispheric regions known to be involved in multisensory processing are crucial for detection of edges in the temporal domain across both visual and auditory modalities. This operation is likely to facilitate cross-modal object feature binding based on temporal coincidence. Hum Brain Mapp, 2008. (c) 2008 Wiley-Liss, Inc.

The spatiotemporal pattern of auditory cortical responses during verbal hallucinations

Functional magnetic resonance imaging (fMRI) studies can provide insight into the neural correlates of hallucinations. Commonly, such studies require self-reports about the timing of the hallucination events. While many studies have found activity in higher-order sensory cortical areas, only a few have demonstrated activity of the primary auditory cortex during auditory verbal hallucinations. In this case, using self-reports as a model of brain activity may not be sensitive enough to capture all neurophysiological signals related to hallucinations. We used spatial independent component analysis (sICA) to extract the activity patterns associated with auditory verbal hallucinations in six schizophrenia patients. SICA decomposes the functional data set into a set of spatial maps without the use of any input function. The resulting activity patterns from auditory and sensorimotor components were further analyzed in a single-subject fashion using a visualization tool that allows for easy inspection of the variability of regional brain responses. We found bilateral auditory cortex activity, including Heschl's gyrus, during hallucinations of one patient, and unilateral auditory cortex activity in two more patients. The associated time courses showed a large variability in the shape, amplitude, and time of onset relative to the self-reports. However, the average of the time courses during hallucinations showed a clear association with this clinical phenomenon. We suggest that detection of this activity may be facilitated by examining hallucination epochs of sufficient length, in combination with a data-driven approach.

The neurophysiological time pattern of illusionary visual perceptual transitions: a simultaneous EEG and fMRI study

Several divergent cortical mechanisms generating multistability in visual perception have been suggested. Here, we investigated the neurophysiologic time pattern of multistable perceptual changes by means of a simultaneous recording with electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Volunteers responded to the subjective perception of a sudden change between stable patterns of illusionary motion (multistable transition) during a stroboscopic paradigm. We found a global deceleration of the EEG frequency prior to a transition and an occipital-accentuated acceleration after a transition, as obtained by low-resolution electromagnetic tomography analysis (LORETA) analysis. A decrease in BOLD response was found in the prefrontal cortex before, and an increase after the transitions was observed in the right anterior insula, the MT/V5 regions and the SMA. The thalamus and left superior temporal gyrus showed a pattern of decrease before and increase after transitions. No such temporal course was found in the control condition. The multimodal approach of data acquisition allows us to argue that the top-down control of illusionary visual perception depends on selective attention, and that a diminution of vigilance reduces selective attention. These are necessary conditions to allow for the occurrence of a perception discontinuity in absence of a physical change of the stimulus.

Dissociation between overt and unconscious face processing in fusiform face area

The precise role of the fusiform face area (FFA) in face processing remains controversial. In this study, we investigated to what degree FFA activation reflects additional functions beyond face perception. Seven volunteers underwent rapid event-related functional magnetic resonance imaging while they performed a face-encoding and a face-recognition task. During face encoding, activity in the FFA for individual faces predicted whether the individual face was subsequently remembered or forgotten. However, during face recognition, no difference in FFA activity between consciously remembered and forgotten faces was observed, but the activity of FFA differentiated if a face had been seen previously or not. This demonstrated a dissociation between overt recognition and unconscious discrimination of stimuli, suggesting that physiological processes of face recognition can take place, even if not all of its operations are made available to consciousness.

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

Differential effect of side of temporal lobe epilepsy on lateralization of hippocampal, temporolateral, and inferior frontal activation patterns during a verbal episodic memory task

The encoding of verbal stimuli elicits left-lateralized activation patterns within the medial temporal lobes in healthy adults. In our study, patients with left- and right-sided temporal lobe epilepsy (LTLE, RTLE) were investigated during the encoding and retrieval of word-pair associates using functional magnetic resonance imaging. Functional asymmetry of activation patterns in hippocampal, inferior frontal, and temporolateral neocortical areas associated with language functions was analyzed. Hippocampal activation patterns in patients with LTLE were more right-lateralized than those in patients with RTLE (P<0.05). There were no group differences with respect to lateralization in frontal or temporolateral regions of interest (ROIs). For both groups, frontal cortical activation patterns were significantly more left-lateralized than hippocampal patterns (P<0.05). For patients with LTLE, there was a strong trend toward a difference in functional asymmetry between the temporolateral and hippocampal ROIs (P=0.059). A graded effect of epileptic activity on laterality of the different regional activation patterns is discussed.