Morten Joensson

Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations

Spontaneous (or resting-state) brain activity has attracted a growing body of neuroimaging research over the last decades. Whole-brain network models have proved helpful to investigate the source of slow (<0.1 Hz) correlated hemodynamic fluctuations revealed in fMRI during rest. However, the mechanisms mediating resting-state long-distance correlations and the relationship with the faster neural activity remain unclear. Novel insights coming from MEG studies have shown that the amplitude envelopes of alpha- and beta-frequency oscillations (~8-30 Hz) display similar correlation patterns as the fMRI signals. In this work, we combine experimental and theoretical work to investigate the mechanisms of spontaneous MEG functional connectivity. Using a simple model of coupled oscillators adapted to incorporate realistic whole-brain connectivity and conduction delays, we explore how slow and structured amplitude envelopes of band-pass filtered signals - fairly reproducing MEG data collected from 10 healthy subjects at rest - are generated spontaneously in the space-time structure of the brain network. Our simulation results show that the large-scale neuroanatomical connectivity provides an optimal network structure to support a regime with metastable synchronization. In this regime, different subsystems may temporarily synchronize at reduced collective frequencies (falling in the 8-30 Hz range due to the delays) while the global system never fully synchronizes. This mechanism modulates the frequency of the oscillators on a slow time-scale (<0.1 Hz) leading to structured amplitude fluctuations of band-pass filtered signals. Taken overall, our results reveal that the structured amplitude envelope fluctuations observed in resting-state MEG data may originate from spontaneous synchronization mechanisms naturally occurring in the space-time structure of the brain.

Minor structural abnormalities in the infant face disrupt neural processing: a unique window into early caregiving responses.

Infant faces elicit early, specific activity in the orbitofrontal cortex (OFC), a key cortical region for reward and affective processing. A test of the causal relationship between infant facial configuration and OFC activity is provided by naturally occurring disruptions to the face structure. One such disruption is cleft lip, a small change to one facial feature, shown to disrupt parenting. Using magnetoencephalography, we investigated neural responses to infant faces with cleft lip compared with typical infant and adult faces. We found activity in the right OFC at 140 ms in response to typical infant faces but diminished activity to infant faces with cleft lip or adult faces. Activity in the right fusiform face area was of similar magnitude for typical adult and infant faces but was significantly lower for infant faces with cleft lip. This is the first evidence that a minor change to the infant face can disrupt neural activity potentially implicated in caregiving.

Altered paralimbic interaction in behavioral addiction

The introduction of magnetoencephalography has made it possible to study electromagnetic signaling in deeper, paralimbic cortical structures such as the medial prefrontal/anterior cingulate (ACC) and medial parietal/posterior cingulate (PCC) cortices. Self-awareness and self-control have been attributed to these regions. To test the hypothesis that they are dysfunctional in pathological gambling with poor self-control, we studied gamblers with and without previous stimulant abuse and age- and sex-matched controls. We found that pathological gamblers were more impulsive than controls in a stop-signal task and attributed this to changes in the activity of the paralimbic network: Pathological gamblers had reduced synchronization at rest in the high gamma range (55–100 Hz) compared with controls and failed to show an increase in gamma synchronization during rest compared with the task, as observed in controls. Subgroup analysis revealed that pathological gamblers without a history of stimulant abuse had lower PCC power during the stop-signal task compared with controls and gamblers with previous stimulant abuse. Furthermore, gamblers with a history of stimulant abuse had up to four times higher power at the ACC site during rest and the task compared with controls. In conclusion, pathological gamblers had higher impulsivity and functional paralimbic abnormalities, which could not be explained by a history of stimulant abuse. In addition, previous stimulant abuse had a marked effect on the amplitude of oscillatory brain activity in the ACC and PCC, suggesting long-term deleterious effects of repeated dopaminergic drug exposure. These consequences should be investigated in more detail in longitudinal studies.

Ready for action: a role for the human midbrain in responding to infant vocalizations

Infant vocalizations are among the most biologically salient sounds in the environment and can draw the listener to the infant rapidly in both times of distress and joy. A region of the midbrain, the periaqueductal gray (PAG), has long been implicated in the control of urgent, survival-related behaviours. To test for PAG involvement in the processing of infant vocalizations, we recorded local field potentials from macroelectrodes implanted in this region in four adults who had undergone deep brain stimulation. We found a significant difference occurring as early as 49 ms after hearing a sound in activity recorded from the PAG in response to infant vocalizations compared with constructed control sounds and adult and animal affective vocalizations. This difference was not present in recordings from thalamic electrodes implanted in three of the patients. Time frequency analyses revealed distinct patterns of activity in the PAG for infant vocalisations, constructed control sounds and adult and animal vocalisations. These results suggest that human infant vocalizations can be discriminated from other emotional or acoustically similar sounds early in the auditory pathway. We propose that this specific, rapid activity in response to infant vocalizations may reflect the initiation of a state of heightened alertness necessary to instigate protective caregiving.

Yoga Lessons for Consciousness Research: A Paralimbic Network Balancing Brain Resource Allocation

Consciousness has been proposed to play a key role in shaping flexible learning and as such is thought to confer an evolutionary advantage. Attention and awareness are the perhaps most important underlying processes, yet their precise relationship is presently unclear. Both of these processes must, however, serve the evolutionary imperatives of survival and procreation. They are thus intimately bound by reward and emotion to help to prioritize efficient brain resource allocation in order to predict and optimize behavior. Here we show how this process is served by a paralimbic network consisting primarily of regions located on the midline of the human brain. Using many different techniques, experiments have demonstrated that this network is effective and specific for self-awareness and contributes to the sense of unity of consciousness by acting as a common neural path for a wide variety of conscious experiences. Interestingly, hemodynamic activity in the network decreases with focusing on external stimuli, which has led to the idea of a default mode network. This network is one of many networks that wax and vane as resources are allocated to accommodate the different cyclical needs of the organism primarily related to the fundamental pleasures afforded by evolution: food, sex, and conspecifics. Here we hypothesize, however, that the paralimbic network serves a crucial role in balancing and regulating brain resource allocation, and discuss how it can be thought of as a link between current theories of so-called “default mode,” “resting state networks,” and “global workspace.” We show how major developmental disorders of self-awareness and self-control can arise from problems in the paralimbic network as demonstrated here by the example of Asperger syndrome. We conclude that attention, awareness, and emotion are integrated by a paralimbic network that helps to efficiently allocate brain resources to optimize behavior and help survival.

Role of white-matter pathways in coordinating alpha oscillations in resting visual cortex.

In the absence of cognitive tasks and external stimuli, strong rhythmic fluctuations with a frequency ≈ 10 Hz emerge from posterior regions of human neocortex. These posterior α-oscillations can be recorded throughout the visual cortex and are particularly strong in the calcarine sulcus, where the primary visual cortex is located. The mechanisms and anatomical pathways through which local \alpha-oscillations are coordinated however, are not fully understood. In this study, we used a combination of magnetoencephalography (MEG), diffusion tensor imaging (DTI), and biophysical modeling to assess the role of white-matter pathways in coordinating cortical α-oscillations. Our findings suggest that primary visual cortex plays a special role in coordinating α-oscillations in higher-order visual regions. Specifically, the amplitudes of α-sources throughout visual cortex could be explained by propagation of α-oscillations from primary visual cortex through white-matter pathways. In particular, α-amplitudes within visual cortex correlated with both the anatomical and functional connection strengths to primary visual cortex. These findings reinforce the notion of posterior α-oscillations as intrinsic oscillations of the visual system. We speculate that they might reflect a default-mode of the visual system during which higher-order visual regions are rhythmically primed for expected visual stimuli by α-oscillations in primary visual cortex.

Making sense: dopamine activates conscious self-monitoring through medial prefrontal cortex

When experiences become meaningful to the self, they are linked to synchronous activity in a paralimbic network of self‐awareness and dopaminergic activity. This network includes medial prefrontal and medial parietal/posterior cingulate cortices, where transcranial magnetic stimulation may transiently impair self‐awareness. Conversely, we hypothesize that dopaminergic stimulation may improve self‐awareness and metacognition (i.e., the ability of the brain to consciously monitor its own cognitive processes). Here, we demonstrate improved noetic (conscious) metacognition by oral administration of 100 mg dopamine in minimal self‐awareness. In a separate experiment with extended self‐awareness dopamine improved the retrieval accuracy of memories of self‐judgment (autonoetic, i.e., explicitly self‐conscious) metacognition. Concomitantly, magnetoencephalography (MEG) showed increased amplitudes of oscillations (power) preferentially in the medial prefrontal cortex. Given that electromagnetic activity in this region is instrumental in self‐awareness, this explains the specific effect of dopamine on explicit self‐awareness and autonoetic metacognition. Hum Brain Mapp 36:1866–1877, 2015.

Impact of Emotion on Consciousness: Positive Stimuli Enhance Conscious Reportability

Emotion and reward have been proposed to be closely linked to conscious experience, but empirical data are lacking. The anterior cingulate cortex (ACC) plays a central role in the hedonic dimension of conscious experience; thus potentially a key region in interactions between emotion and consciousness. Here we tested the impact of emotion on conscious experience, and directly investigated the role of the ACC. We used a masked paradigm that measures conscious reportability in terms of subjective confidence and objective accuracy in identifying the briefly presented stimulus in a forced-choice test. By manipulating the emotional valence (positive, neutral, negative) and the presentation time (16 ms, 32 ms, 80 ms) we measured the impact of these variables on conscious and subliminal (i.e. below threshold) processing. First, we tested normal participants using face and word stimuli. Results showed that participants were more confident and accurate when consciously seeing happy versus sad/neutral faces and words. When stimuli were presented subliminally, we found no effect of emotion. To investigate the neural basis of this impact of emotion, we recorded local field potentials (LFPs) directly in the ACC in a chronic pain patient. Behavioural findings were replicated: the patient was more confident and accurate when (consciously) seeing happy versus sad faces, while no effect was seen in subliminal trials. Mirroring behavioural findings, we found significant differences in the LFPs after around 500 ms (lasting 30 ms) in conscious trials between happy and sad faces, while no effect was found in subliminal trials. We thus demonstrate a striking impact of emotion on conscious experience, with positive emotional stimuli enhancing conscious reportability. In line with previous studies, the data indicate a key role of the ACC, but goes beyond earlier work by providing the first direct evidence of interaction between emotion and conscious experience in the human ACC.

Modeling Alpha-Band Functional Connectivity for MEG Resting State Data: Oscillations and Delays in a Spiking Neuron Model

The study of structural and functional connectivity (SC,FC) and dynamics in spontaneous brain activity is a rapidly growing field of research [1]. The existence of Resting State Networks (RSN) has been well established in fMRI over the past decade, [1] and computational models [2] have successfully captured their connectivity patterns and slow oscillations, but have not been applied to recent MEG findings of coherent RSN [3] yet. Here, we extended a recent neurophysiologically realistic spiking-neuron model of spontaneous fMRI activity [4] to exhibit noisy oscillatory activity in the alpha band (Figure ​(Figure1A,1A, bottom) and studied how connectivity and delays influenced the model fit with the oscillatory MEG FC. The global network was described by a graph of nodes (local populations of excitatory and inhibitory spiking neurons), connected to each other according to a DTI-derived anatomical connectivity matrix, which fixed the relative connectivity and delay/distance structure, but left global scaling factors W (coupling weight) and ps (propagation speed in m/s) as free parameters in the model. FC was measured by correlating the low-pass filtered Power Envelopes of the bandlimited signal. Simulations showed the largest margin of good concordance with empirical FC over W when neurophysiologically realistic delays (5-10 m/s) were included (Figure ​(Figure1C1C). Figure 1 A: Sketch of the global model graph, each node consisting of local populations of spiking neurons. The model is capable of producing alpha oscillations (bottom). B: Empirical and simulated FC are fitted and C: the model best captures the empirical pattern ...

Role of anatomical pathways in shaping posterior alpha oscillations in the resting human brain

Since their discovery almost a century ago, ongoing alpha oscillations as recorded with electroencephalography (EEG) or magnetoencephalography (MEG) have been associated with numerous mental and emotional states and have been hypothesized to play a crucial role in perceptual and cognitive processing [1]. A prominent feature of alpha oscillations recorded in the absence of stimuli or explicit tasks is their dominance over parietal-occipital midline regions [2]. In this study we combine MEG and diffusion spectrum imaging (DSI) to investigate the extent to which the topology of anatomical pathways can explain this dominance. We found that source-projected MEG alpha power correlates with eigenvalue centrality of the DSI-derived structural matrix [3]. In particular, the occipital-parietal dominance could largely be explained by the high density of structural connections within the posterior-medial parts of the structural core [4]. Moreover, more local network characterizations such as clustering coefficient, degree, and node centrality, were unable to explain the posterior dominance, suggesting that alpha power is shaped by global rather than local structural features. To assess the possibility of a causal link between the DSI-derived structural network and the power topography of resting-state alpha oscillations, we constructed a computational model of large-scale brain dynamics. Within the model, alpha oscillations are generated within local circuits [5] and interact through long-range excitatory projections according to the DSI-derived structural topology. We found that, when structurally connected, alpha oscillations indeed dominate over parietal-occipital midline regions. Furthermore, they only did so when the dynamics was in the vicinity of an instability, which is in line with previous modeling work on resting-state BOLD correlations [5]. These findings suggest that the posterior dominance of alpha oscillations could indeed be shaped by the topology of anatomical pathways and that critical dynamics are required. We subsequently investigated which features of the experimentally identified network were crucial in shaping the observed dominance and assessed the role of coherent oscillations. In sum, this study provides experimental and theoretical evidence that alpha oscillations in the human resting brain are structured by the topology of underlying anatomical pathways.