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In recent years, parallel developments in disparate disciplines have focused on what has come to be termed connectivity ; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a ‘common toolbox’ underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.

The large multicomponent K-complex (KC) and the rhythmic spindle are the hallmarks of non-rapid eye movement (NREM)-2 sleep stage. We studied with magnetoencephalography (MEG) the progress of light sleep (NREM-1 and NREM-2) and emergence of KCs and spindles. Seven periods of interest (POI) were analyzed: wakefulness, the two quiet \"core\" periods of light sleep (periods free from any prominent phasic or oscillatory events) and four periods before and during spindles and KCs. For each POI, eight 2-s (1250 time slices) segments were used. We employed magnetic field tomography (MFT) to extract an independent tomographic estimate of brain activity from each MEG data sample. The spectral power was then computed for each voxel in the brain for each segment of each POI. The sets of eight maps from two POIs were contrasted using a voxel-by-voxel -test. Only increased spectral power was identified in the four key contrasts between POIs before and during spindles and KCs versus the NREM2 core. Common increases were identified for all four subjects, especially within and close to the anterior cingulate cortex (ACC). These common increases were widespread for low frequencies, while for higher frequencies they were focal, confined to specific brain areas. For the pre-KC POI, only one prominent increase was identified, confined to the theta/alpha bands in a small area in the dorsal caudal part of ACC (dcACC). During KCs, the activity in this area grows in intensity and extent (in space and frequency), filling the space between the areas that expanded their low frequency activity (in the delta band) during NREM2 compared to NREM1. Our main finding is that prominent spectral power increases before NREM2 graphoelements are confined to the dcACC, and only for KCs, sharing common features with changes of activity in dcACC of the well-studied error related negativity (ERN). ERN is seen in awake state, in perceptual conflict and situations where there is a difference between expected and actual environmental or internal events. These results suggest that a KC is the sleep side of the awake state ERN, both serving their putative sentinel roles in the frame of the saliency network.

We used tomographic analysis of MEG signals to characterize regional spectral changes in the brain at sleep onset and during light sleep. We identified two key processes that may causally link to loss of consciousness during the quiet or \"core\" periods of NREM1. First, active inhibition in the frontal lobe leads to delta and theta spectral power increases. Second, activation suppression leads to sharp drop of spectral power in alpha and higher frequencies in posterior parietal cortex. During NREM2 core periods, the changes identified in NREM1 become more widespread, but focal increases also emerge in alpha and low sigma band power in frontal midline cortical structures, suggesting reemergence of some monitoring of internal and external environment. Just before spindles and K-complexes (KCs), the hallmarks of NREM2, we identified focal spectral power changes in pre-frontal cortex, mid cingulate, and areas involved in environmental and internal monitoring, i.e., the rostral and sub-genual anterior cingulate. During both spindles and KCs, alpha and low sigma bands increases. Spindles emerge after further active inhibition (increase in delta power) of the frontal areas responsible for environmental monitoring, while in posterior parietal cortex, power increases in low and high sigma bands. KCs are correlated with increase in alpha power in the monitoring areas. These specific regional changes suggest strong and varied vigilance changes for KCs, but vigilance suppression and sharpening of cognitive processing for spindles. This is consistent with processes designed to ensure accurate and uncorrupted memory consolidation. The changes during KCs suggest a sentinel role: evaluation of the salience of provoking events to decide whether to increase processing and possibly wake up, or to actively inhibit further processing of intruding influences. The regional spectral patterns of NREM1, NREM2, and their dynamic changes just before spindles and KCs reveal an edge effect facilitating the emergence of spindles and KCs and defining the precise loci where they might emerge. In the time domain, the spindles are seen in widespread areas of the cortex just as reported from analysis of intracranial data, consistent with the emerging consensus of a differential topography that depends on the kind of memory stored.

It is now apparent that the visual system reacts to stimuli very fast, with many brain areas activated within 100 ms. It is, however, unclear how much detail is extracted about stimulus properties in the early stages of visual processing. Here, using magnetoencephalography we show that the visual system separates different facial expressions of emotion well within 100 ms after image onset, and that this separation is processed differently depending on where in the visual field the stimulus is presented. Seven right-handed males participated in a face affect recognition experiment in which they viewed happy, fearful and neutral faces. Blocks of images were shown either at the center or in one of the four quadrants of the visual field. For centrally presented faces, the emotions were separated fast, first in the right superior temporal sulcus (STS; 35-48 ms), followed by the right amygdala (57-64 ms) and medial pre-frontal cortex (83-96 ms). For faces presented in the periphery, the emotions were separated first in the ipsilateral amygdala and contralateral STS. We conclude that amygdala and STS likely play a different role in early visual processing, recruiting distinct neural networks for action: the amygdala alerts sub-cortical centers for appropriate autonomic system response for fight or flight decisions, while the STS facilitates more cognitive appraisal of situations and links appropriate cortical sites together. It is then likely that different problems may arise when either network fails to initiate or function properly.

Cross-modal activity in visual cortex of blind subjects has been reported during performance of variety of non-visual tasks. A key unanswered question is through which pathways non-visual inputs are funneled to the visual cortex. Here we used tomographic analysis of single trial magnetoencephalography (MEG) data recorded from one congenitally blind and two sighted subjects after stimulation of the left and right median nerves at three intensities: below sensory threshold, above sensory threshold and above motor threshold; the last sufficient to produce thumb twitching. We identified reproducible brain responses in the primary somatosensory (S1) and motor (M1) cortices at around 20 ms post-stimulus, which were very similar in sighted and blind subjects. Time-frequency analysis revealed strong 45-70 Hz activity at latencies of 20-50 ms in S1 and M1, and posterior parietal cortex Brodmann areas (BA) 7 and 40, which compared to lower frequencies, were substantially more pronounced in the blind than the sighted subjects. Critically, at frequencies from α-band up to 100 Hz we found clear, strong, and widespread responses in the visual cortex of the blind subject, which increased with the intensity of the somatosensory stimuli. Time-delayed mutual information (MI) revealed that in blind subject the stimulus information is funneled from the early somatosensory to visual cortex through posterior parietal BA 7 and 40, projecting first to visual areas V5 and V3, and eventually V1. The flow of information through this pathway occurred in stages characterized by convergence of activations into specific cortical regions. In sighted subjects, no linked activity was found that led from the somatosensory to the visual cortex through any of the studied brain regions. These results provide the first evidence from MEG that in blind subjects, tactile information is routed from primary somatosensory to occipital cortex via the posterior parietal cortex.

In an earlier experiment, we have used the BTi twin MAGNES system (2 x 37 channels) to record the evoked magnetic field from five healthy right-handed male volunteers using two tasks: visual recognition of complex objects including faces and facial expressions of emotion. We have repeated the experiment with one of the five subjects using the BTi whole head system (148 channels). Magnetic field tomography (MFT) was used to extract 3D estimates of brain activity millisecond by millisecond from the recorded magnetoencephalographic (MEG) signals. Results from the MFT analysis of the average signals of the five subjects have been reported elsewhere (Streit et al. 1997; Streit et al. 1999). In this paper, we present results of the detailed single trial analysis for the subject recorded from the whole head system. We found activations in areas extending from the occipital pole to anterior areas. Regions of interest (ROIs) were defined entirely on functional criteria and confirmed independently by the location of the maximum activity on the MRI. Activation curves for each ROI were computed and objective statistical measures (Kolmogorov-Smirnov test) were then used to identify time segments for which the ROI activity showed significant differences both within the same and across different object/emotion categories. Emphasis is placed on the quantification of the activity from two ROIs, fusiform gyrus (FG) and amygdala (AM), which have been best studied in the context of processing of faces and facial expressions of emotion, respectively. We found no face-specific area as such, but instead areas like the FG was activated by all complex objects at roughly similar latencies and varying strengths. The amygdala activity was significantly different between 150 and 180 ms for fearful expression, and even earlier for happy expression.

Most neuroimaging studies on face processing used centrally presented images with a relatively large visual field. Images presented in this way activate widespread striate and extrastriate areas and make it difficult to study spatiotemporal dynamics and connectivity pattern differences from various parts of the visual field. Here we studied magnetoencephalographic responses in humans to centrally and peripherally presented faces for testing the hypothesis that processing of visual stimuli with facial expressions of emotions depends on where the stimuli are presented in the visual field. Using our tomographic and statistical parametric mapping analyses, we identified occipitotemporal areas activated by face stimuli more than by control conditions. V1/V2 activity was significantly stronger for lower than central and upper visual field presentation. Fusiform activity, however, was significantly stronger for central than for peripheral presentation. Both the V1/V2 and fusiform areas activated earlier for peripheral than for central presentation. Fast responses in the fusiform were found at 70–80 ms after image onset, as well as a response at 130–160 ms. For peripheral presentation, contralateral V1/V2 and fusiform activated earlier (10 ms and 23 ms, respectively) and significantly stronger than their ipsilateral counterparts. Mutual information analysis further showed linked activity from bilateral V1/V2 to fusiform for central presentation and from contralateral V1/V2 to fusiform for lower visual field presentation. In the upper visual field, the linkage was from fusiform to V1/V2. Our results showed that face stimuli are processed predominantly in the hemisphere contralateral to the stimulation and demonstrated for the first time early fusiform activation leading V1/V2 activation for upper visual field stimulation.

All sleep stages contain epochs with high-amplitude electrophysiological phasic events, alternating with quieter “core periods.” High-amplitude and core state properties cannot be disentangled with PET and fMRI. Here from high temporal resolution magnetoencephalography data, regional changes in neuronal activity were extracted during core periods in different frequency bands for each sleep stage and waking. We found that gamma-band activity increases in precuneus during light sleep (stages 1/2) and in the left dorso–medial prefrontal cortex (L-DMPFC) during deep sleep (stages 3/4). The L-DMPFC activated area expands laterally during rapid eye movement (REM) sleep, into a volume of about 5 cm 3 bounded by regions attributed to Theory of Mind (ToM) and default systems, both involved in introspection. Gamma band activity in this area was higher during REM sleep than other sleep stages and active wakefulness. There is a tantalizing correspondence between increased wide-band activity (dominated by low frequencies) in early non-REM (NREM) sleep stages and increases in gamma-band activity in late NREM and REM periods that we attribute to a lateral disinhibition mechanism. The results provide a description of regional electrophysiological changes in awake state, light and deep sleep, and REM sleep. These changes are most pronounced in the L-DMPFC and the other areas around the dorsal midline that are close to, but do not overlap with areas of the default and ToM systems, suggesting that the DMPFC, particularly in the left hemisphere, plays an important role in late NREM stages, in REM and possibly in dreaming.