993 resultados para Brain Mapping


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Introduction: Discrimination of species-specific vocalizations is fundamental for survival and social interactions. Its unique behavioral relevance has encouraged the identification of circumscribed brain regions exhibiting selective responses (Belin et al., 2004), while the role of network dynamics has received less attention. Those studies that have examined the brain dynamics of vocalization discrimination leave unresolved the timing and the inter-relationship between general categorization, attention, and speech-related processes (Levy et al., 2001, 2003; Charest et al., 2009). Given these discrepancies and the presence of several confounding factors, electrical neuroimaging analyses were applied to auditory evoked-potential (AEPs) to acoustically and psychophysically controlled non-verbal human and animal vocalizations. This revealed which region(s) exhibit voice-sensitive responses and in which sequence. Methods: Subjects (N=10) performed a living vs. man-made 'oddball' auditory discrimination task, such that on a given block of trials 'target' stimuli occurred 10% of the time. Stimuli were complex, meaningful sounds of 500ms duration. There were 120 different sound files in total, 60 of which represented sounds of living objects and 60 man-made objects. The stimuli that were the focus of the present investigation were restricted to those of living objects within blocks where no response was required. These stimuli were further sorted between human non-verbal vocalizations and animal vocalizations. They were also controlled in terms of their spectrograms and formant distributions. Continuous 64-channel EEG was acquired through Neuroscan Synamps referenced to the nose, band-pass filtered 0.05-200Hz, and digitized at 1000Hz. Peri-stimulus epochs of continuous EEG (-100ms to 900ms) were visually inspected for artifacts, 40Hz low-passed filtered and baseline corrected using the pre-stimulus period . Averages were computed from each subject separately. AEPs in response to animal and human vocalizations were analyzed with respect to differences of Global Field Power (GFP) and with respect to changes of the voltage configurations at the scalp (reviewed in Murray et al., 2008). The former provides a measure of the strength of the electric field irrespective of topographic differences; the latter identifies changes in spatial configurations of the underlying sources independently of the response strength. In addition, we utilized the local auto-regressive average distributed linear inverse solution (LAURA; Grave de Peralta Menendez et al., 2001) to visualize and statistically contrast the likely underlying sources of effects identified in the preceding analysis steps. Results: We found differential activity in response to human vocalizations over three periods in the post-stimulus interval, and this response was always stronger than that to animal vocalizations. The first differential response (169-219ms) was a consequence of a modulation in strength of a common brain network localized into the right superior temporal sulcus (STS; Brodmann's Area (BA) 22) and extending into the superior temporal gyrus (STG; BA 41). A second difference (291-357ms) also followed from strength modulations of a common network with statistical differences localized to the left inferior precentral and prefrontal gyrus (BA 6/45). These two first strength modulations correlated (Spearman's rho(8)=0.770; p=0.009) indicative of functional coupling between temporally segregated stages of vocalization discrimination. A third difference (389-667ms) followed from strength and topographic modulations and was localized to the left superior frontal gyrus (BA10) although this third difference did not reach our spatial criterion of 12 continuous voxels. Conclusions: We show that voice discrimination unfolds over multiple temporal stages, involving a wide network of brain regions. The initial stages of vocalization discrimination are based on modulations in response strength within a common brain network with no evidence for a voice-selective module. The latency of this effect parallels that of face discrimination (Bentin et al., 2007), supporting the possibility that voice and face processes can mutually inform one another. Putative underlying sources (localized in the right STS; BA 22) are consistent with prior hemodynamic imaging evidence in humans (Belin et al., 2004). Our effect over the 291-357ms post-stimulus period overlaps the 'voice-specific-response' reported by Levy et al. (Levy et al., 2001) and the estimated underlying sources (left BA6/45) were in agreement with previous findings in humans (Fecteau et al., 2005). These results challenge the idea that circumscribed and selective areas subserve con-specific vocalization processing.

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Dystonia is associated with impaired somatosensory ability. The electrophysiological method of repetitive transcranial magnetic stimulation (rTMS) can be used for noninvasive stimulation of the human cortex and can alter cortical excitability and associated behavior. Among others, rTMS can alter/improve somatosensory discrimation abilities, as shown in healthy controls. We applied 5Hz-rTMS over the left primary somatosensory cortex (S1) in 5 patients with right-sided writer's dystonia and 5 controls. We studied rTMS effects on tactile discrimination accuracy and concomitant rTMS-induced changes in hemodynamic activity measured by functional magnetic resonance imaging (fMRI). Before rTMS, patients performed worse on the discrimination task than controls even though fMRI showed greater task-related activation bilaterally in the basal ganglia (BG). In controls, rTMS led to improved discrimination; fMRI revealed this was associated with increased activity of the stimulated S1, bilateral premotor cortex and BG. In dystonia patients, rTMS had no effect on discrimination; fMRI showed similar cortical effects to controls except for no effects in BG. Improved discrimination after rTMS in controls is linked to enhanced activation of S1 and BG. Failure of rTMS to increase BG activation in dystonia may be associated with the lack of effect on sensory discrimination in this group and may reflect impaired processing in BG-S1 connections. Alternatively, the increased BG activation seen in the baseline state without rTMS may reflect a compensatory strategy that saturates a BG contribution to this task.

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Neurons projecting transitorily into the corpus callosum from area 17 of the cat were retrogradely labeled by the fluorescent tracer Fast Blue (FB) injected into contralateral areas 17 and 18 on postnatal days 1-5. During the second postnatal month these neurons were still labeled by the early injection, although they had eliminated their callosal axon. At this time, 15-20% of these neurons could be retrogradely relabeled by injections of Diamidino Yellow (DY) into ipsilateral areas 17 and 18, but few or none by similar injections in the other areas that receive from area 17 (19, 21a, PMLS, 20a, 20b, DLS). Similarly, area 17 neurons projecting transitorily to contralateral area PMLS during the first postnatal week could be relabeled by DY injections in ipsilateral areas 17 and 18 but not in PMLS. Already around birth, many transitorily callosal neurons in area 17 send bifurcating axons both to contralateral areas 17 and 18 and ipsilateral area 18. It is probable that during postnatal development some of these neurons selectively eliminate their callosal axon collaterals and maintain the projection to ipsilateral area 18. In fact, some transitorily callosal neurons in area 17 can be double-labeled by simultaneous perinatal injections of FB in contralateral areas 17 and 18 and of a new long-lasting retrograde tracer, rhodamine-conjugated latex microspheres, in ipsilateral area 18. The same neurons can then be relabeled by reinjecting ipsilateral area 18 with DY during the second postnatal month. This finding, however, does not exclude the possibility that some transitorily callosal neurons send an axon to ipsilateral area 18 after eliminating their callosal axon. In conclusion, area 17 neurons that project transitorily through the corpus callosum later participate, probably permanently, in ipsilateral corticocortical projections but selectively to areas 17-18. The mechanism responsible for this selectivity is unknown, but it may be related to the differential radial distribution (i.e., to birth date) of area 17 neurons engaged in the various corticocortical projections. The problems raised by the use of long-lasting retrograde fluorescent tracers in neurodevelopmental studies and by the quantification of results of double- and triple-labeling paradigms are also discussed.

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Introduction : Driving is a complex everyday task requiring mechanisms of perception, attention, learning, memory, decision making and action control, thus indicating that involves numerous and varied brain networks. If many data have been accumulated over time about the effects of alcohol consumption on driving capability, much less is known about the role of other psychoactive substances, such as cannabis (Chang et al.2007, Ramaekers et al, 2006). Indeed, the solicited brain areas during safe driving which could be affected by cannabis exposure have not yet been clearly identified. Our aim is to study these brain regions during a tracking task related to driving skills and to evaluate the modulation due to the tolerance of cannabis effects. Methods : Eight non-smoker control subjects participated to an fMRI experiment based on a visuo-motor tracking task, alternating active tracking blocks with passive tracking viewing and rest condition. Half of the active tracking conditions included randomly presented traffic lights as distractors. Subjects were asked to track with a joystick with their right hand and to press a button with their left index at each appearance of a distractor. Four smoking subjects participated to the same fMRI sessions once before and once after smoking cannabis and a placebo in two independent cross-over experiments. We quantified the performance of the subjects by measuring the precision of the behavioural responses (i.e. percentage of time of correct tracking and reaction times to distractors). Functional MRI data were acquired using on a 3.0T Siemens Trio system equipped with a 32-channel head coil. BOLD signals will be obtained with a gradient-echo EPI sequence (TR=2s, TE=30ms, FoV=216mm, FA=90°, matrix size 72×72, 32 slices, thickness 3mm). Preprocessing, single subject analysis and group statistics were conducted on SPM8b. Results were thresholded at p<0.05 (FWE corrected) and at k>30 for spatial extent. Results : Behavioural results showed a significant impairment in task and cognitive test performance of the subjects after cannabis inhalation when comparing their tracking accuracy either to the controls subjects or to their performances before the inhalation or after the placebo inhalation (p<0.001 corrected). In controls, fMRI BOLD analysis of the active tracking condition compared to the passive one revealed networks of polymodal areas in superior frontal and parietal cortex dealing with attention and visuo-spatial coordination. In accordance to what is known of the visual and sensory motor networks we found activations in V4, frontal eye-field, right middle frontal gyrus, intra-parietal sulcus, temporo-parietal junction, premotor and sensory-motor cortex. The presence of distractors added a significant activation in the precuneus. Preliminary results on cannabis smokers in the acute phase, compared either to themselves before the cannabis inhalation or to control subjects, showed a decreased activation in large portions of the frontal and parietal attention network during the simple tracking task, but greater involvement of precuneus, of the superior part of intraparietal sulcus and middle frontal gyrus bilaterally when distractors were present in the task. Conclusions : Our preliminary results suggest that acute cannabis smoking alters performances and brain activity during active tracking tasks, partly reorganizing the recruitment of brain areas of the attention network.

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MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.

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Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event-related fMRI, in the same group of subjects, to compare reasoning-related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning-related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto-lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro-lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations.

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In schizophrenia patients, glutathione dysregulation at the gene, protein and functional levels, leads to N-methyl-D-aspartate (NMDA) receptor hypofunction. These patients also exhibit deficits in auditory sensory processing that manifests as impaired mismatch negativity (MMN), which is an auditory evoked potential (AEP) component related to NMDA receptor function. N-acetyl-cysteine (NAC), a glutathione precursor, was administered to patients to determine whether increased levels of brain glutathione would improve MMN and by extension NMDA function. A randomized, double-blind, cross-over protocol was conducted, entailing the administration of NAC (2 g/day) for 60 days and then placebo for another 60 days (or vice versa). 128-channel AEPs were recorded during a frequency oddball discrimination task at protocol onset, at the point of cross-over, and at the end of the study. At the onset of the protocol, the MMN of patients was significantly impaired compared to sex- and age- matched healthy controls (p=0.003), without any evidence of concomitant P300 component deficits. Treatment with NAC significantly improved MMN generation compared with placebo (p=0.025) without any measurable effects on the P300 component. MMN improvement was observed in the absence of robust changes in assessments of clinical severity, though the latter was observed in a larger and more prolonged clinical study. This pattern suggests that MMN enhancement may precede changes to indices of clinical severity, highlighting the possible utility AEPs as a biomarker of treatment efficacy. The improvement of this functional marker may indicate an important pathway towards new therapeutic strategies that target glutathione dysregulation in schizophrenia.

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Current models of brain organization include multisensory interactions at early processing stages and within low-level, including primary, cortices. Embracing this model with regard to auditory-visual (AV) interactions in humans remains problematic. Controversy surrounds the application of an additive model to the analysis of event-related potentials (ERPs), and conventional ERP analysis methods have yielded discordant latencies of effects and permitted limited neurophysiologic interpretability. While hemodynamic imaging and transcranial magnetic stimulation studies provide general support for the above model, the precise timing, superadditive/subadditive directionality, topographic stability, and sources remain unresolved. We recorded ERPs in humans to attended, but task-irrelevant stimuli that did not require an overt motor response, thereby circumventing paradigmatic caveats. We applied novel ERP signal analysis methods to provide details concerning the likely bases of AV interactions. First, nonlinear interactions occur at 60-95 ms after stimulus and are the consequence of topographic, rather than pure strength, modulations in the ERP. AV stimuli engage distinct configurations of intracranial generators, rather than simply modulating the amplitude of unisensory responses. Second, source estimations (and statistical analyses thereof) identified primary visual, primary auditory, and posterior superior temporal regions as mediating these effects. Finally, scalar values of current densities in all of these regions exhibited functionally coupled, subadditive nonlinear effects, a pattern increasingly consistent with the mounting evidence in nonhuman primates. In these ways, we demonstrate how neurophysiologic bases of multisensory interactions can be noninvasively identified in humans, allowing for a synthesis across imaging methods on the one hand and species on the other.

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Introduction: The interhemispheric asymmetries that originate from connectivity-related structuring of the cerebral cortex are compromised in schizophrenia (SZ). Recently, we have revealed the whole-head topography of EEG synchronization in SZ (Jalili et al. 2007; Knyazeva et al. 2008). Here we extended the analysis to assess the abnormality in the asymmetry of synchronization, which is further motivated by the evidence that the interhemispheric asymmetries suspected to be abnormal in SZ originate from the connectivity-related structuring of the cortex. Methods: Thirteen right-handed SZ patients and thirteen matched controls, participated in this study and the multichannel (128) EEGs were recorded for 3-5 minutes at rest. Then, Laplacian EEG (LEEG) were calculated using a 2-D spline. The LEEGs were analysis through calculating the power spectral density using Welch's average periodogram method. Furthermore, using a state-space based multivariate synchronization measure, S-estimator, we analyzed the correlate of the functional cortico-cortical connectivity in SZ patients compared to the controls. The values of S-estimator were obtained at three different special scales: first-order neighbors for each sensor location, second-order neighbors, and the whole hemisphere. The synchronization measures based on LEEG of alpha and beta bands were applied and tuned to various spatial scales including local, intraregional, and long-distance levels. To assess the between-group differences, we used a permutation version of Hotelling's T2 test. For correlation analysis, Spearman Rank Correlation was calculated. Results: Compared to the controls, who had rightward asymmetry at a local level (LEEG power), rightward anterior and leftward posterior asymmetries at an intraregional level (first- and second-order S-estimator), and rightward global asymmetry (hemispheric S-estimator), SZ patients showed generally attenuated asymmetry, the effect being strongest for intraregional synchronization. This deviation in asymmetry across the anterior-to-posterior axis is consistent with the cerebral form of the so-called Yakovlevian or anticlockwise cerebral torque. Moreover, the negative occipital and positive frontal asymmetry values suggest higher regional synchronization among the left occipital and the right frontal locations relative to their symmetrical counterparts. Correlation analysis linked the posterior intraregional and hemispheric abnormalities to the negative SZ symptoms, whereas the asymmetry of LEEG power appeared to be weakly coupled to clinical ratings. The posterior intraregional abnormalities of asymmetry were shown to increase with the duration of the disease. The tentative links between these findings and gross anatomical asymmetries, including the cerebral torque and gyrification pattern in normal subjects and SZ patients, are discussed. Conclusions: Overall, our findings reveal the abnormalities in the synchronization asymmetry in SZ patients and heavy involvement of the right hemisphere in these abnormalities. These results indicate that anomalous asymmetry of cortico-cortical connections in schizophrenia is amenable to electrophysiological analysis.

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Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

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During the past 20 years, BOLD fMRI has developed towards a central and fundamental tool in neuroscience. It has been shown that the BOLD response provides an indicator of neuronal activity in the brain. Consequently, for an accurate interpretation of findings in BOLD MRI experiments and to draw meaningful conclusions about the temporal evolution of neural events, a deep understanding of the nature of the BOLD contrast has become of essential importance. Since the dynamics of the major direct determinants of the BOLD signal (CBF, CBV and CMRO(2)) range between seconds and minutes, long duration stimulation was an early key strategy needed to study and understand the BOLD characteristics. This paper summarizes and discusses the thoughts and rationales of the long duration stimulation studies.

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OBJECTIVE: To reveal the EEG correlates of resting hypofrontality in schizophrenia (SZ). METHOD: We analyzed the whole-head EEG topography in 14 patients compared to 14 matched controls by applying a new parameterization of the multichannel EEG. We used a combination of power measures tuned for regional surface mapping with power measures that allow evaluation of global effects. RESULTS: The SZ-related EEG abnormalities include i) a global decrease in absolute EEG power robustly manifested in the alpha and beta frequency bands, and ii) a relative increase in the alpha power over the prefrontal brain regions against its reduction over the posterior regions. In the alpha band both effects are linked to the SZ symptoms measured with Positive and Negative Symptom Scales and to chronicity. CONCLUSION: As alpha activity is related to regional deactivation, our findings support the concept of hypofrontality in SZ and expose the alpha rhythm as a sensitive indicator of it.

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Little is known about how human amnesia affects the activation of cortical networks during memory processing. In this study, we recorded high-density evoked potentials in 12 healthy control subjects and 11 amnesic patients with various types of brain damage affecting the medial temporal lobes, diencephalic structures, or both. Subjects performed a continuous recognition task composed of meaningful designs. Using whole-scalp spatiotemporal mapping techniques, we found that, during the first 200 ms following picture presentation, map configuration of amnesics and controls were indistinguishable. Beyond this period, processing significantly differed. Between 200 and 350 ms, amnesic patients expressed different topographical maps than controls in response to new and repeated pictures. From 350 to 550 ms, healthy subjects showed modulation of the same maps in response to new and repeated items. In amnesics, by contrast, presentation of repeated items induced different maps, indicating distinct cortical processing of new and old information. The study indicates that cortical mechanisms underlying memory formation and re-activation in amnesia fundamentally differ from normal memory processing.