[MEG]PLS: A pipeline for MEG data analysis and partial least squares statistics

Thalamocortical excitability modulation guides human perception under uncertainty

Knowledge about the relevance of environmental features can guide stimulus processing. However, it remains unclear how processing is adjusted when feature relevance is uncertain. We hypothesized that (a) heightened uncertainty would shift cortical networks from a rhythmic, selective processing-oriented state toward an asynchronous ("excited") state that boosts sensitivity to all stimulus features, and that (b) the thalamus provides a subcortical nexus for such uncertainty-related shifts. Here, we had young adults attend to varying numbers of task-relevant features during EEG and fMRI acquisition to test these hypotheses. Behavioral modeling and electrophysiological signatures revealed that greater uncertainty lowered the rate of evidence accumulation for individual stimulus features, shifted the cortex from a rhythmic to an asynchronous/excited regime, and heightened neuromodulatory arousal. Crucially, this unified constellation of within-person effects was dominantly reflected in the uncertainty-driven upregulation of thalamic activity. We argue that neuromodulatory processes involving the thalamus play a central role in how the brain modulates neural excitability in the face of momentary uncertainty.

A controlled clinical crossover trial of exercise training to improve cognition and neural communication in pediatric brain tumor survivors

OBJECTIVE

To assess the efficacy of aerobic exercise training to improve controlled attention, information processing speed and neural communication during increasing task load and rest in pediatric brain tumor survivors (PBTS) treated with cranial radiation.

METHODS

Participants completed visual-motor Go and Go/No-Go tasks during magnetoencephalography recording prior to and following the completion of 12-weeks of exercise training. Exercise-related changes in response accuracy and visual-motor latency were evaluated with Linear Mixed models. The Phase Lag Index (PLI) was used to estimate functional connectivity during task performance and rest. Changes in PLI values after exercise training were assessed using Partial Least Squares analysis.

RESULTS

Exercise training predicted sustained (12-weeks) improvement in response accuracy (p<0.05) during No-Go trials. Altered functional connectivity was detected in theta (4-7Hz) alpha (8-12Hz) and high gamma (60-100Hz) frequency bands (p<0.001) during Go and Go/No-Go trials. Significant changes in response latency and resting state connectivity were not detected.

CONCLUSION

These findings support the efficacy of aerobic exercise to improve controlled attention and enhance functional mechanisms under increasing task load in participants.

SIGNIFICANCE

It may be possible to harness the beneficial effects of exercise as therapy to promote cognitive recovery and enhance brain function in PBTS.

Age-related changes to oscillatory dynamics during maintenance and retrieval in a relational memory task

In aging, structural and/or functional brain changes may precede changes in cognitive performance. We previously showed that despite having hippocampal volumes similar to those of younger adults, older adults showed oscillatory changes during the encoding phase of a short-delay visuospatial memory task that required spatial relations among objects to be bound across time (Rondina et al., 2016). The present work provides a complementary set of analyses to examine age-related changes in oscillatory activity during maintenance and retrieval of those spatial relations in order to provide a comprehensive examination of the neural dynamics that support memory function in aging. Participants were presented with three study objects sequentially. Following a delay (maintenance phase), the objects were re-presented simultaneously and participants had to determine whether the relative spatial relations among the objects had been maintained (retrieval phase). Older adults had similar task accuracy, but slower response times, compared to younger adults. Both groups showed a decrease in theta (2-7Hz), alpha (9-14Hz), and beta (15-30Hz) power during the maintenance phase. During the retrieval phase, younger adults showed theta and beta power increases that predicted greater task accuracy, whereas older adults showed a widespread decrease in each of the three frequency ranges that predicted longer response latencies. Older adults also showed distinct patterns of behaviour-related activity depending on whether the analysis was time-locked to the onset of the stimulus or to the onset of the response during the test phase. These findings suggest that older adults may experience declines in relational binding and/or comparison processes that are reflected in oscillatory changes prior to structural decline.

Partial Least Square Aided Beamforming Algorithm in Magnetoencephalography Source Imaging

Beamforming techniques have played a prominent role in source imaging in neuroimaging and in locating epileptogenic zones. However, existing vector-beamformers are sensitive to noise on localization of epileptogenic zones. In this study, partial least square (PLS) was used to aid the minimum variance beamforming approach for source imaging with magnetoencephalography (MEG) arrays, and verified its effectiveness in simulated data and epilepsy data. First, PLS was employed to extract the components of the MEG arrays by maximizing the covariance between a linear combination of the predictors and the class variable. Noise was then removed by reconstructing the MEG arrays based on those components. The minimum variance beamforming method was used to estimate a source model. Simulations with a realistic head model and varying noise levels indicated that the proposed approach can provide higher spatial accuracy than other well-known beamforming methods. For real MEG recordings in 10 patients with temporal lobe epilepsy, the ratios of the number of spikes localized in the surgical excised region to the total number of spikes using the proposed method were higher than that of the dipole fitting method. These localization results using the proposed method are more consistent with the clinical evaluation. The proposed method may provide a new imaging marker for localization of epileptogenic zones.

Dynamic functional connectivity shapes individual differences in associative learning

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc.

Age-related changes to oscillatory dynamics in hippocampal and neocortical networks

Recent models of hippocampal function have emphasized its role in relational binding - the ability to form lasting representations regarding the relations among distinct elements or items which can support memory performance, even over brief delays (e.g., several seconds). The present study examined the extent to which aging is associated with changes in the recruitment of oscillatory activity within hippocampal and neocortical regions to support relational binding performance on a short delay visuospatial memory task. Structural magnetic resonance imaging and MEG were used to characterize potential age-related changes in hippocampal volume, oscillatory activity, and subsequent memory performance, and the relationships among them. Participants were required to bind the relative visuospatial positions of objects that were presented singly across time. Subsequently, the objects were re-presented simultaneously, and participants were required to indicate whether the relative spatial positions among the objects had been maintained. Older and younger adults demonstrated similar task accuracy, and older adults had preserved hippocampal volumes relative to younger adults. Age-group differences were found in pre-stimulus theta (∼5Hz) and beta (∼20Hz) oscillations, and this pre-stimulus activity was related to hippocampal volumes in younger adults. Age-group differences were also found in the recruitment of oscillatory activity from the pre-stimulus period to the task. Only younger adults showed a task-related change in theta power that was predictive of memory performance. In contrast, older adults demonstrated task-related alpha (∼10Hz) oscillatory power changes that were not observed in younger adults. These findings provide novel evidence for the role of the hippocampus and functionally connected regions in relational binding that is disrupted in aging. The present findings are discussed in the context of current models regarding the cognitive neuroscience of aging.