Framing deductive reasoning with emotional content: an fMRI study.

In the literature concerning the study of emotional effect on cognition, several researches highlight the mechanisms of reasoning ability and the influence of emotions on this ability. However, up to now, no neuroimaging study was specifically devised to directly compare the influence on reasoning performance of visual task-unrelated with semantic task-related emotional information. In the present functional fMRI study, we devised a novel paradigm in which emotionally negative vs. neutral visual stimuli (context) were used as primes, followed by syllogisms composed of propositions with emotionally negative vs. neutral contents respectively. Participants, in the MR scanner, were asked to assess the logical validity of the syllogisms. We have therefore manipulated the emotional state and arousal induced by the visual prime as well as the emotional interference exerted by the syllogism content. fMRI data indicated a medial prefrontal cortex deactivation and lateral/dorsolateral prefrontal cortex activation in conditions with negative context. Furthermore, a lateral/dorsolateral prefrontal cortex modulation caused by syllogism content was observed. Finally, behavioral data confirmed the influence of emotional task-related stimuli on reasoning ability, since the performance was worse in conditions with syllogisms involving negative emotions. Therefore, on the basis of these data, we conclude that emotional states can impair the performance in reasoning tasks by means of the delayed general reactivity, whereas the emotional content of the target may require a larger amount of top-down resources to be processed.

Pharmacological functional MRI assessment of the effect of ibuprofen-arginine in painful conditions.

Pharmacological functional magnetic resonance imaging (phMRI) is a valuable tool for the investigation of pharmacological effects of a drug on pain processing. We hypothesized that the ibuprofen-arginine combination, in line with its characteristic analgesic properties, may influence the phMRI response at the central level, as compared to placebo. Ten healthy subjects underwent a double-blind, placebo-controlled, randomized, cross-over phFMRI study with somatosensory painful stimulation of the right median nerve. We measured the blood oxygen level dependent (BOLD) signal variations induced in conditions of pain after oral administration of either ibuprofen-arginine or placebo formulations. Independent component analysis (ICA) was used for the analysis of the fMRI data, without assuming a specific hemodynamic response function (HRF), which may be altered by drug administration. Median nerve electrical painful stimulation mainly activated the primary contralateral and the secondary somatosensory cortices, the insula, the supplementary motor area, and the middle frontal gyrus. Placebo and ibuprofen-arginine administration induced activation bilaterally in the premotor cortex, and an overall reduction in the other pain-related areas, which was more prominent in the left hemisphere. A task-related increase of BOLD signal between drug and placebo was observed bilaterally in the primary somatosensory area and the middle frontal gyrus without any changes in subjective pain scores. Overall, our findings show that ibuprofen-arginine, in line with the characteristic analgesic properties of ibuprofen, influences the BOLD response in specific pain-related brain areas with respect to placebo, with a vasoactive effect possibly due to arginine.

Elevated response of human amygdala to neutral stimuli in mild post traumatic stress disorder: neural correlates of generalized emotional response.

Previous evidence from functional magnetic resonance imaging (fMRI) studies has shown that amygdala responses to emotionally neutral pictures are exaggerated at a group level in patients with severe post-traumatic stress disorder (PTSD) [Hendler T, Rotshtein P, Yeshurun Y, Weizmann T, Kahn I, Ben-Bashat D, Malach R, Bleich A (2003) Neuroimage 19(3):587-600]. The present fMRI study tested the hypothesis that amygdala responses are elevated not only in response to negative pictures but also to neutral pictures as a function of disease severity in patients with mild symptoms and in subjects who did not develop symptoms. To this end, fMRI scans were performed in 10 patients with mild PTSD and 10 healthy controls (both victims of a bank robbery), during the execution of a visuo-attentional task in which they were asked to observe emotionally negative or neutral pictures. Control subjects showed enhanced amygdala responses to emotionally negative stimuli compared to neutral stimuli. On the contrary, PTSD patients were characterized by high amygdala responses to both neutral and emotional pictures, with no statistically significant difference between the two classes of stimuli. In the entire group, we found correlations among the severity of the PTSD symptoms, task performance, and amygdala activation during the processing of neutral stimuli. Results of this study suggest that amygdala responses and the selectivity of the emotional response to neutral stimuli are elevated as a function of disease severity in PTSD patients with mild symptoms.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks.

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli, respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes.

An fMRI investigation on image generation in different sensory modalities: the influence of vividness.

In the present fMRI study the issue of the specific cortices activation during imagery generation in different sensory modalities is addressed. In particular, we tested whether the vividness variability of imagery was reflected in the BOLD signal within specific sensory cortices. Subjects were asked to generate a mental image for each auditory presented sentence. Each imagery modality was contrasted with an abstract sentence condition. In addition, subjects were asked to fill the Italian version of the Questionnaire Upon Mental Imagery (QMI) prior to each neuroimaging session. In general, greater involvement of sensory specific cortices in high-vivid versus low-vivid subjects was found for visual (occipital), gustatory (anterior insula), kinaesthetic (pre-motor), and tactile and for somatic (post-central parietal) imagery modalities. These results support the hypothesis that vividness is related to image format: high-vivid subjects would create more analogical representations relying on the same specific neural substrates active during perception with respect to low-vivid subjects. Results are also discussed according to the simulation perspective.

Hypothalamus, sexual arousal and psychosexual identity in human males: a functional magnetic resonance imaging study.

In a recent functional magnetic resonance imaging study, a complex neural circuit was shown to be involved in human males during sexual arousal [A. Ferretti et al. (2005) Neuroimage, 26, 1086]. At group level, there was a specific correlation between penile erection and activations in anterior cingulate, insula, amygdala, hypothalamus and secondary somatosensory regions. However, it is well known that there are remarkable inter-individual differences in the psychological view and attitude to sex of human males. Therefore, a crucial issue is the relationship among cerebral responses, sexual arousal and psychosexual identity at individual level. To address this issue, 18 healthy male subjects were recruited. Their deep sexual identity (DSI) was assessed following the construct revalidation by M. Olivetti Belardinelli [(1994) Sci. Contrib. Gen. Psychol., 11, 131] of the Franck drawing completion test, a projective test providing, according to this revalidation, quantitative scores on 'accordance/non-accordance' between self-reported and psychological sexual identity. Cerebral activity was evaluated by means of functional magnetic resonance imaging during hard-core erotic movies and sport movies. Results showed a statistically significant positive correlation between the blood oxygen level-dependent signal in bilateral hypothalamus and the Franck drawing completion test score during erotic movies. The higher the blood oxygen level-dependent activation in bilateral hypothalamus, the higher the male DSI profile. These results suggest that, in male subjects, inter-individual differences in the DSI are strongly correlated with blood flow to the bilateral hypothalamus, a dimorphic brain region deeply implicated in instinctual drives including reproduction.

Empirical Markov Chain Monte Carlo Bayesian analysis of fMRI data.

In this work an Empirical Markov Chain Monte Carlo Bayesian approach to analyse fMRI data is proposed. The Bayesian framework is appealing since complex models can be adopted in the analysis both for the image and noise model. Here, the noise autocorrelation is taken into account by adopting an AutoRegressive model of order one and a versatile non-linear model is assumed for the task-related activation. Model parameters include the noise variance and autocorrelation, activation amplitudes and the hemodynamic response function parameters. These are estimated at each voxel from samples of the Posterior Distribution. Prior information is included by means of a 4D spatio-temporal model for the interaction between neighbouring voxels in space and time. The results show that this model can provide smooth estimates from low SNR data while important spatial structures in the data can be preserved. A simulation study is presented in which the accuracy and bias of the estimates are addressed. Furthermore, some results on convergence diagnostic of the adopted algorithm are presented. To validate the proposed approach a comparison of the results with those from a standard GLM analysis, spatial filtering techniques and a Variational Bayes approach is provided. This comparison shows that our approach outperforms the classical analysis and is consistent with other Bayesian techniques. This is investigated further by means of the Bayes Factors and the analysis of the residuals. The proposed approach applied to Blocked Design and Event Related datasets produced reliable maps of activation.

Trigeminal activation using chemical, electrical, and mechanical stimuli.

Tactile, proprioceptive, and nociceptive information, including also chemosensory functions are expressed in the trigeminal nerve sensory response. To study differences in the processing of different stimulus qualities, we performed a study based on functional magnetic resonance imaging. The first trigeminal branch (ophthalmic nerve) was activated by (a) intranasal chemical stimulation with gaseous CO2 which produces stinging and burning sensations, but is virtually odorless, (b) painful, but not nociceptive specific cutaneous electrical stimulation, and (c) cutaneous mechanical stimulation using air puffs. Eighteen healthy subjects participated (eight men, 10 women, mean age 31 years). Painful stimuli produced patterns of activation similar to what has been reported for other noxious stimuli, namely activation in the primary and secondary somatosensory cortices, anterior cingulate cortex, insular cortex, and thalamus. In addition, analyses indicated intensity-related activation in the prefrontal cortex which was specifically involved in the evaluation of stimulus intensity. Importantly, the results also indicated similarities between activation patterns after intranasal chemosensory trigeminal stimulation and patterns usually found following intranasal odorous stimulation, indicating the intimate connection between these two systems in the processing of sensory information.

A frontoparietal network for spatial attention reorienting in the auditory domain: a human fMRI/MEG study of functional and temporal dynamics.

Several studies have identified a supramodal network critical to the reorienting of attention toward stimuli at novel locations and which involves the right temporoparietal junction and the inferior frontal areas. The present functional magnetic resonance imaging (fMRI)\magnetoencephalography (MEG) study investigates: 1) the cerebral circuit underlying attentional reorienting to spatially varying sound locations; 2) the circuit related to the regular change of sound location in the same hemifield, the change of sound location across hemifields, or sounds presented randomly at different locations on the azimuth plane; 3) functional temporal dynamics of the observed cortical areas exploiting the complementary characteristics of the fMRI and MEG paradigms. fMRI results suggest 3 distinct roles: the supratemporal plane appears modulated by variations of sound location; the inferior parietal lobule is modulated by the cross-meridian effect; and the inferior frontal cortex is engaged by the inhibition of a motor response. MEG data help to elucidate the temporal dynamics of this network by providing high-resolution time series with which to measure latency of neural activation manipulated by the reorienting of attention.

Electrophysiological signatures of resting state networks in the human brain.

Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.

Brain network for passive word listening as evaluated with ICA and Granger causality.

Brain network modeling is probably the biggest challenge in fMRI data analysis. Higher cognitive processes in fact, rely on complex dynamics of temporally and spatially segregated brain activities. A number of different techniques, mostly derived from paradigmatic hypothesis-driven methods, have been successfully applied for such purpose. This paper instead, presents a new data-driven analysis approach that applies both independent components analysis (ICA) and the Granger causality (GC). The method includes two steps: (1) ICA is used to extract the independent functional activities; (2) the GC is applied to the independent component (IC) most correlated with the stimuli, to indicate its functional relation with other ICs. This new method is applied to the analysis of fMRI study of listening to high-frequency trisyllabic words, non-words and reversed words. As expected, activity was found in the primary and secondary auditory cortices. Additionally, a parieto-frontal network of activations, supported by temporal and causality relationships, was found. This network is modulated by experimental conditions in agreement with the most recent models presented for word perception. The results have confirmed the validity of the proposed method, and seem promising for the detection of cognitive causal relationships in neuroimaging data.

The use of standardized infinity reference in EEG coherency studies.

The study of large scale interactions in the brain from EEG signals is a promising method for the identification of functional networks. However, the validity of a large scale parameter is limited by two factors: the use of a non-neutral reference and the artifactual self-interactions between the measured EEG signals introduced by volume conduction. In this paper, we propose an approach to study large scale EEG coherency in which these factors are eliminated. Artifactual self-interaction by volume conduction is eliminated by using the imaginary part of the complex coherency as a measure of interaction and the Reference Electrode Standardization Technique (REST) is used for the approximate standardization of the reference of scalp EEG recordings to a point at infinity that, being far from all possible neural sources, acts like a neutral virtual reference. The application of our approach to simulated and real EEG data shows that the detection of interaction, as opposed to artifacts due to reference and volume conduction, is a goal that can be achieved from the study of a large scale parameter.

Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis.

The simultaneous recording of EEG and fMRI is a promising method for combining the electrophysiological and hemodynamic information on cerebral dynamics. However, EEG recordings performed in the MRI scanner are contaminated by imaging, ballistocardiographic (BCG) and ocular artifacts. A number of processing techniques for the cancellation of fMRI environment disturbances exist: the most popular is averaged artifact subtraction (AAS), which performs well for the imaging artifact, but has some limitations in removing the BCG artifact, due to the variability in cardiac wave duration and shape; furthermore, no processing method to attenuate ocular artifact is currently used in EEG/fMRI, and contaminated epochs are simply rejected before signal analysis. In this work, we present a comprehensive method based on independent component analysis (ICA) for simultaneously removing BCG and ocular artifacts from the EEG recordings, as well as residual MRI contamination left by AAS. The ICA method has been tested on event-related potentials (ERPs) obtained from a visual oddball paradigm: it is very effective in attenuating artifacts in order to reconstruct clear brain signals from EEG acquired in the MRI scanner. It performs significantly better than the AAS method in removing the BCG artifact. Furthermore, since ocular artifacts can be completely suppressed, a larger number of trials is available for analysis. A comparison of ERPs inside the magnetic environment with those obtained out of the MRI scanner confirms that no systematic bias in the ERP waveform is produced by the ICA method.

"What" versus "where" in the audiovisual domain: an fMRI study.

Similar "what/where" functional segregations have been proposed for both visual and auditory cortical processing. In this fMRI study, we investigated if the same segregation exists in the crossmodal domain, when visual and auditory stimuli have to be matched in order to perform either a recognition or a localization task. Recent neuroimaging research highlighted the contribution of different heteromodal cortical regions during various forms of crossmodal binding. Interestingly, crossmodal effects during audiovisual speech and object recognition have been found in the superior temporal sulcus, while crossmodal effects during the execution of spatial tasks have been found over the intraparietal sulcus, suggesting an underlying "what/where" segregation. In order to directly compare the specific involvement of these two heteromodal regions, we scanned ten male right-handed subjects during the execution of two crossmodal matching tasks. Participants were simultaneously presented with a picture and an environmental sound, coming from either the same or the opposite hemifield and representing either the same or a different object. The two tasks required a manual YES/NO response respectively about location or semantic matching of the presented stimuli. Both group and individual subject analysis were performed. Task-related differences in BOLD response were observed in the right intraparietal sulcus and in the left superior temporal sulcus, providing a direct confirmation of the "what-where" functional segregation in the crossmodal audiovisual domain.

Somatotopy of anterior cingulate cortex (ACC) and supplementary motor area (SMA) for electric stimulation of the median and tibial nerves: an fMRI study.

In this study, we tested whether there is a somatotopic sensory organization in human anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in 15 normal young adults during nonpainful and painful electric stimulation of median nerve at the wrist and tibial nerve at the medial malleolus. Results showed that the representation of median nerve area was more anterior in the ACC and more inferior in the SMA than the one of tibial nerve area. This was true for both nonpainful and painful stimulation intensities. These results point to a somatotopic sensory organization of human ACC and SMA.

Localizing complex neural circuits with MEG data.

During cognitive processing, the various cortical areas, with specialized functions, supply for different tasks. In most cases then, the information flows are processed in a parallel way by brain networks which work together integrating the single performances for a common goal. Such a step is generally performed at higher processing levels in the associative areas. The frequency range at which neuronal pools oscillate is generally wider than the one which is detectable by bold changes in fMRI studies. A high time resolution technique like magnetoencephalography or electroencephalography is therefore required as well as new data processing algorithms for detecting different coherent brain areas cooperating for one cognitive task. Our experiments show that no algorithm for the inverse problem solution is immune from bias. We propose therefore, as a possible solution, our software LOCANTO (LOcalization and Coherence ANalysis TOol). This new package features a set of tools for the detection of coherent areas. For such a task, as a default, it employs the algorithm with best performances for the neural landscape to be detected. If the neural landscape under attention involves more than two interacting areas the SLoreta algorithm is used. Our study shows in fact that SLoreta performance is not biased when the correlation among multiple sources is high. On the other hand, the Beamforming algorithm is more precise than SLoreta at localizing single or double sources but it gets a relevant localization bias when the sources are more than three and are highly correlated.

Human brain activation during passive listening to sounds from different locations: an fMRI and MEG study.

Recent animal and human studies indicate the existence of a neural pathway for sound localization, which is similar to the "where" pathway of the visual system and distinct from the sound identification pathway. This study sought to highlight this pathway using a passive listening protocol. We employed fMRI to study cortical areas, activated during the processing of sounds coming from different locations, and MEG to disclose the temporal dynamics of these areas. In addition, the hypothesis of different activation levels in the right and in the left hemispheres, due to hemispheric specialization of the human brain, was investigated. The fMRI results indicate that the processing of sound, coming from different locations, activates a complex neuronal circuit, similar to the sound localization system described in monkeys known as the auditory "where" pathway. This system includes Heschl's gyrus, the superior temporal gyrus, the supramarginal gyrus, and the inferior and middle frontal lobe. The MEG analysis allowed assessment of the timing of this circuit: the activation of Heschl's gyrus was observed 139 ms after the auditory stimulus, the peak latency of the source located in the superior temporal gyrus was at 156 ms, and the inferior parietal lobule and the supramarginal gyrus peaked at 162 ms. Both hemispheres were found to be involved in the processing of sounds coming from different locations, but a stronger activation was observed in the right hemisphere.

Nociceptive and non-nociceptive sub-regions in the human secondary somatosensory cortex: an MEG study using fMRI constraints.

Previous evidence from functional magnetic resonance imaging (fMRI) has shown that a painful galvanic stimulation mainly activates a posterior sub-region in the secondary somatosensory cortex (SII), whereas a non-painful sensory stimulation mainly activates an anterior sub-region of SII [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. The present study, combining fMRI with magnetoencephalographic (MEG) findings, assessed the working hypothesis that the activity of such a posterior SII sub-region is characterized by an amplitude and temporal evolution in line with the bilateral functional organization of nociceptive systems. Somatosensory evoked magnetic fields (SEFs) recordings after alvanic median nerve stimulation were obtained from the same sample of subjects previously examined with fMRI [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. Constraints for dipole source localizations obtained from MEG recordings were applied according to fMRI activations, namely, at the posterior and the anterior SII sub-regions. It was shown that, after painful stimulation, the two posterior SII sub-regions of the contralateral and ipsilateral hemispheres were characterized by dipole sources with similar amplitudes and latencies. In contrast, the activity of anterior SII sub-regions showed statistically significant differences in amplitude and latency during both non-painful and painful stimulation conditions. In the contralateral hemisphere, the source activity was greater in amplitude and shorter in latency with respect to the ipsilateral. Finally, painful stimuli evoked a response from the posterior sub-regions peaking significantly earlier than from the anterior sub-regions. These results suggested that both ipsi and contra posterior SII sub-regions process painful stimuli in parallel, while the anterior SII sub-regions might play an integrative role in the processing of somatosensory stimuli.

Functional imaging with MEG and fMRI.

The possibility of integrating functional data from magnetoencephalografic (MEG) measurements and functional Magnetic Resonance Imaging (fMRI) offers new insight on the brain organization. In fact, MEG and fMRI integration can provide accurate identification of active brain areas as well as a precise identification of the timing of brain response. In this paper two examples will be discussed: the first aiming at the characterization of the human primary (SI) and secondary (SII) somatosensory cortices, the second concerning how brain reacts to sound coming from different spatial directions.

Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics?

The relationship between neurophysiological and cerebrovascular-metabolic findings in patients affected by severe cerebrovascular deficits was investigated by comparing magnetoencephalographic (MEG-evoked fields) and blood oxygen level-dependent functional MRI (BOLD fMRI) responses to median nerve electric stimulation. Despite the use of identical stimuli, the two techniques elicited always-detectable responses in the control group (10 subjects), but demonstrated uncorrelated activation properties in our patient sample (10 subjects). All patients showed clear MEG signals in both the affected and unaffected hemispheres, indicating well synchronized, stimulus-locked firing of neurons in the primary sensorimotor cortex, but some patients showed no fMRI activation in either the affected or the unaffected hemisphere. In order to clarify the origin of this uncoupling, we investigated the possible role of lesion site, white matter hyperintensities, current medication, risk factors, anatomy of the neck vessels, and cerebral vasomotor reactivity (VMR) as measured by transcranial Doppler (TCD) during CO2 inhalation. Neither neuronal activation properties nor any of the considered factors were related to the lack of fMRI activation, with the exception of altered vasomotor reactivity, which was, on the contrary, strongly related. Preserved VMR was paired with absent BOLD bilaterally in the only patient affected by microangiopathy. This finding suggests that BOLD contrast could be more sensitive than TCD to chronic microvascular impairments, measuring small- rather than large- vessel reactivity.