The posterior cingulate BOLD duty cycle during meditation predicts attentional skills

Introduction: Recent findings about the human brain's wakeful resting state suggest a link between the spontaneous generation of task-unrelated thoughts (mind-wandering), and the slow fluctuations of activity in the 'default mode network' (DMN), a consistent set of brain regions with a major hub in the posterior cingulate cortex (PCC). Meta-awareness and regulation of mind-wandering are core cognitive components of many meditation practices, and to study their relationship to the DMN activity we collected fMRI data from a cohort of experienced Zen meditators and meditation-naive controls engaging in a simple meditative protocol, along with their performance on a computerized sustained attention task. By introducing a simple duty cycle measure for the fMRI BOLD signal from the PCC, we hypothesized that this could be taken as an endophenotype5 of the individual capacity to regulate mind-wandering and would thus correlate with performance in the sustained attention task. Methods: Subjects: 12 Zen meditators with > 3 years of daily practice and 12 control subjects, matched for age and education level. Meditative task: subjects were asked to maintain their attention on their breathing throughout the scan and gently redirect attention to breathing every time they found themselves distracted or mind-wandering. MRI acquisition: a single series of gradient-echo EPI volumes (200 scans, TR=2.35s, 35 3x3x3mm axial slices) and a T1-weighted hi-res volume (MPRAGE, 176 1x1x1 mm sagittal slices) were acquired on a 3.0 Tesla Siemens Magnetom Trio scanner. Imaging analysis: The EPI series were corrected for slice-timing and head motion, and warped to MNI space using the T1-weighted image to estimate the warping parameters. The time series were then band-pass filtered (0.01-0.1 Hz), along with least-square removal of the global signal and estimated motion parameters. The average processed BOLD time courses from a PCC region of interest (center-of-mass MNI coordinates: -6, -56, 22; size=82 voxels), identified by a previous study on the same subject sample using a conceptual processing task 6, were extracted and a duty cycle measure was computed as the ratio of the cumulative time that the signal lay above its temporal mean and the total scanning time. Sustained attention task: each subject completed the Rapid Visual Information Processing (RVIP) task from the CANTAB neuropsychological computerized battery 7. Performance was assessed in terms of reaction times (RT) and A-prime, a nonparametric sensitivity index ranging from 0 to 1 based on the number of hits and false alarms (1=perfect performance). Correlation analysis: Pearson's correlation tests were computed between individual scores in the RVIP task (RT and A-prime) and the PCC duty cycle values. Image processing and statistics were performed with the software packages AFNI, SPM5, and R. Results: We observed a significant correlation between the values of the PCC BOLD duty cycle during the meditative procedure and the individual scores in the RVIP task (A-prime: r=-0.64, p= 0.0007; RT: r=+0.58, p=0.003): subjects with a lower PCC duty cycle tended to respond faster and more accurately on the sustained attention task (see Figure). Conclusions: Although these findings need to be confirmed by a larger study, they support the notion that individual capacity for top-down attentional control and resistance to mind-wandering is inversely related to the relative abundance of high levels of activity of the central DMN node, the PCC, when such activity is mobilized by the processes of meta-awareness and regulation of spontaneous mentation that characterize the meditative exercise. The simple time-domain measure of the PCC BOLD activity proposed here, i.e. its duty cycle while subjects attempt to keep their attention on their breathing, appears as a promising candidate for an endophenotype of individual attentional skills

Remembrance of things to come: a conversation between Zen and neuroscience on the predictive nature of the mind

The notion of the brain as a predictive organ following Bayesian principles has been steadily gaining favor in neuroscience. This perspective, which has broad theoretical and applicative consequences, suggests also a novel way to look at the mind-body processes mobilized by meditative practices. In this article, the topic is introduced and subsequently explored as a conversation between a neuroscientist (GP) and the abbot of a Zen Sōtō monastery (FTG). We believe that such ‘mutual perturbations’ between the third-person descriptions provided by scientific research and the phenomenological depth of Buddhist lore have a great potential for advancing our understanding of both brain function and meditation

Network-based characterization of brain functional connectivity in Zen practitioners

In the last decade, a number of neuroimaging studies have investigated the neurophysiological effects associated with contemplative practices. Meditation-related changes in resting state functional connectivity (rsFC) have been previously reported, particularly in the default mode network, frontoparietal attentional circuits, saliency-related regions, and primary sensory cortices. We collected functional magnetic resonance imaging data from a sample of 12 experienced Zen meditators and 12 meditation-naïve matched controls during a basic attention-to-breathing protocol, together with behavioral performance outside the scanner on a set of computerized neuropsychological tests. We adopted a network system of 209 nodes, classified into nine functional modules, and a multi-stage approach to identify rsFC differences in meditators and controls. Between-group comparisons of modulewise FC, summarized by the first principal component of the relevant set of edges, revealed important connections of frontoparietal circuits with early visual and executive control areas. We also identified several group differences in positive and negative edgewise FC, often involving the visual, or frontoparietal regions. Multivariate pattern analysis of modulewise FC, using support vector machine (SVM), classified meditators, and controls with 79% accuracy and selected 10 modulewise connections that were jointly prominent in distinguishing meditators and controls; a similar SVM procedure based on the subjects' scores on the neuropsychological battery yielded a slightly weaker accuracy (75%). Finally, we observed a good correlation between the across-subject variation in strength of modulewise connections among frontoparietal, executive, and visual circuits, on the one hand, and in the performance on a rapid visual information processing test of sustained attention, on the other. Taken together, these findings highlight the usefulness of employing network analysis techniques in investigating the neural correlates of contemplative practices

Neural correlates of emotional valence for faces and words

: Stimuli with negative emotional valence are especially apt to influence perception and action because of their crucial role in survival, a property that may not be precisely mirrored by positive emotional stimuli of equal intensity. The aim of this study was to identify the neural circuits differentially coding for positive and negative valence in the implicit processing of facial expressions and words, which are among the main ways human beings use to express emotions. Thirty-six healthy subjects took part in an event-related fMRI experiment. We used an implicit emotional processing task with the visual presentation of negative, positive, and neutral faces and words, as primary stimuli. Dynamic Causal Modeling (DCM) of the fMRI data was used to test effective brain connectivity within two different anatomo-functional models, for the processing of words and faces, respectively. In our models, the only areas showing a significant differential response to negative and positive valence across both face and word stimuli were early visual cortices, with faces eliciting stronger activations. For faces, DCM revealed that this effect was mediated by a facilitation of activity in the amygdala by positive faces and in the fusiform face area by negative faces; for words, the effect was mainly imputable to a facilitation of activity in the primary visual cortex by positive words. These findings support a role of early sensory cortices in discriminating the emotional valence of both faces and words, where the effect may be mediated chiefly by the subcortical/limbic visual route for faces, and rely more on the direct thalamic pathway to primary visual cortex for words

Structural and functional cerebral correlates of hypnotic suggestibility

Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity

Brain Activation in Primary Motor and Somatosensory Cortices during Motor Imagery Correlates with Motor Imagery Ability in Stroke Patients

Aims. While studies on healthy subjects have shown a partial overlap between the motor execution and motor imagery neural circuits, few have investigated brain activity during motor imagery in stroke patients with hemiparesis. This work is aimed at examining similarities between motor imagery and execution in a group of stroke patients. Materials and Methods. Eleven patients were asked to perform a visuomotor tracking task by either physically or mentally tracking a sine wave force target using their thumb and index finger during fMRI scanning. MIQ-RS questionnaire has been administered. Results and Conclusion. Whole-brain analyses confirmed shared neural substrates between motor imagery and motor execution in bilateral premotor cortex, SMA, and in the contralesional inferior parietal lobule. Additional region of interest-based analyses revealed a negative correlation between kinaesthetic imagery ability and percentage BOLD change in areas 4p and 3a; higher imagery ability was associated with negative and lower percentage BOLD change in primary sensorimotor areas during motor imagery

Resting-state networks and anosognosia in Alzheimer’s disease

Background: Recent evidence suggests that anosognosia or unawareness of cognitive impairment in Alzheimer’s Disease (AD) may be explained by a disconnection between brain regions involved in accessing and monitoring information regarding self and others. It has been demonstrated that AD patients with anosognosia have reduced connectivity within the default mode network (DMN) and that anosognosia in people with prodromal AD is positively associated with bilateral anterior cingulate cortex (ACC), suggesting a possible role of this region in mechanisms of awareness in the early phase of disease. We hypothesized that anosognosia in AD is associated with an imbalance between the activity of large-scale resting-state functional magnetic resonance imaging (fMRI) networks, in particular the DMN, the salience network (SN), and the frontoparietal network (FPN). Methods: Sixty patients with MCI and AD dementia underwent fMRI and neuropsychological assessment including the Anosognosia Questionnaire Dementia (AQ-D), a measure of anosognosia based on a discrepancy score between patient’s and carer’s judgments. After having applied Independent Component Analysis (ICA) to resting fMRI data we performed: (i) correlations between the AQ-D score and functional connectivity in the DMN, SN, and FPN, and (ii) comparisons between aware and unaware patients of the DMN, SN, and FPN functional connectivity. Results: We found that anosognosia was associated with (i) weak functional connectivity within the DMN, in posterior and middle cingulate cortex particularly, (ii) strong functional connectivity within the SN in ACC, and between the SN and basal ganglia, and (iii) a heterogenous effect concerning the functional connectivity of the FPN, with a weak connectivity between the FPN and PCC, and a strong connectivity between the FPN and ACC. The observed effects were controlled for differences in severity of cognitive impairment and age. Conclusion: Anosognosia in the AD continuum is associated with a dysregulation of the functional connectivity of three large-scale networks, namely the DMN, SN, and FPN

Emergence of associative learning in a neuromorphic inference network

OBJECTIVE: In the theoretical framework of predictive coding and active inference, the brain can be viewed as instantiating a rich generative model of the world that predicts incoming sensory data while continuously updating its parameters via minimization of prediction errors. While this theory has been successfully applied to cognitive processes - by modelling the activity of functional neural networks at a mesoscopic scale - the validity of the approach when modelling neurons as an ensemble of inferring agents, in a biologically plausible architecture, remained to be explored. APPROACH: We modelled a simplified cerebellar circuit with individual neurons acting as Bayesian agents to simulate the classical delayed eyeblink conditioning protocol. Neurons and synapses adjusted their activity to minimize their prediction error, which was used as the network cost function. This cerebellar network was then implemented in hardware by replicating digital neuronal elements via a low-power microcontroller. MAIN RESULTS: Persistent changes of synaptic strength - that mirrored neurophysiological observations - emerged via local (neurocentric) prediction error minimization, leading to the expression of associative learning. The same paradigm was effectively emulated in low-power hardware showing remarkably efficient performance compared to conventional neuromorphic architectures. SIGNIFICANCE: These findings show that: i) an ensemble of free energy minimizing neurons - organized in a biological plausible architecture - can recapitulate functional self-organization observed in nature, such as associative plasticity, and ii) a neuromorphic network of inference units can learn unsupervised tasks without embedding predefined learning rules in the circuit, thus providing a potential avenue to a novel form of brain-inspired artificial intelligence