Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

Investigating predictive coding in younger and older children using MEG and a multi-feature auditory oddball paradigm.

There is mounting evidence for predictive coding theory from computational, neuroimaging, and psychological research. However, there remains a lack of research exploring how predictive brain function develops across childhood. To address this gap, we used pediatric magnetoencephalography to record the evoked magnetic fields of 18 younger children (M = 4.1 years) and 19 older children (M = 6.2 years) as they listened to a 12-min auditory oddball paradigm. For each child, we computed a mismatch field "MMF": an electrophysiological component that is widely interpreted as a neural signature of predictive coding. At the sensor level, the older children showed significantly larger MMF amplitudes relative to the younger children. At the source level, the older children showed a significantly larger MMF amplitude in the right inferior frontal gyrus relative to the younger children, P < 0.05. No differences were found in 2 other key regions (right primary auditory cortex and right superior temporal gyrus) thought to be involved in mismatch generation. These findings support the idea that predictive brain function develops during childhood, with increasing involvement of the frontal cortex in response to prediction errors. These findings contribute to a deeper understanding of the brain function underpinning child cognitive development.

Natural vs forced language switching: Free selection and consistent language use eliminate significant performance costs and cognitive demands in the brain.

Bilinguals are known to switch language spontaneously in everyday conversations, even if there are no external requirements to do so. However, in the laboratory setting, language control is often investigated using forced switching tasks, which result in significant performance costs. The present study assessed whether switching would be less costly when performed in a more natural fashion, and what factors might account for this. Mandarin-English bilinguals engaged in language switching under three different contexts with varied task demands. We examined two factors which may be characteristic of natural switching: (i) freedom of language selection; (ii) consistency of language used to name each item. Participants' brain activities were recorded using magnetoencephalography (MEG), along with behavioural measures of reaction speed and accuracy. The natural context (with both free selection and consistent language use for each item) produced better performance overall, showing reduced mixing cost and no significant switch cost. The neural effect of language mixing was also reversed in this context, suggesting that freely mixing two languages was easier than staying in a single language. Further, while switching in the forced context elicited increased brain activity in the right inferior frontal gyrus, this switch effect disappeared when the language used to name each item was consistent. Together, these findings demonstrate that the two factors above conjointly contribute to eliminating significant performance costs and cognitive demands associated with language switching and mixing. Such evidence aligns with lexical selection models which do not assume bilingual production to be inherently effortful.

Comprehensive behavioural intervention for tics: a neurophysiological intervention.

BACKGROUND: Gilles de la Tourette Syndrome (GTS) is a childhood-onset neuropsychiatric disorder characterised by motor and vocal tics. While Comprehensive Behavioural Intervention for Tics (CBIT) is an effective, non-pharmacological treatment for patients with GTS, the underlying neurophysiological basis of this intervention has not been investigated. METHODS: To investigate the clinical effectiveness of CBIT in reducing tic severity in young people with GTS and explore neurophysiological mechanisms associated with clinical change. RESULTS: There was a significant overall improvement in tic severity of large effect size. The Cortical Silent Period (CSP) to motor evoked potential (MEP) ratio (CSP/MEP ratio) increased after the intervention with a small effect size. Other neurophysiological measures of inhibition were not significantly related to the change in tic severity. CONCLUSIONS: Alongside significant clinical improvements, these results suggest a role for motor cortical Gamma-aminobutyric acid (GABA)-ergic inhibitory circuitry in the neurophysiological changes underlying CBIT treatment. These findings need to be replicated in larger studies using control samples.

A Guided Tutorial on Modelling Human Event-Related Potentials with Recurrent Neural Networks.

In cognitive neuroscience research, computational models of event-related potentials (ERP) can provide a means of developing explanatory hypotheses for the observed waveforms. However, researchers trained in cognitive neurosciences may face technical challenges in implementing these models. This paper provides a tutorial on developing recurrent neural network (RNN) models of ERP waveforms in order to facilitate broader use of computational models in ERP research. To exemplify the RNN model usage, the P3 component evoked by target and non-target visual events, measured at channel Pz, is examined. Input representations of experimental events and corresponding ERP labels are used to optimize the RNN in a supervised learning paradigm. Linking one input representation with multiple ERP waveform labels, then optimizing the RNN to minimize mean-squared-error loss, causes the RNN output to approximate the grand-average ERP waveform. Behavior of the RNN can then be evaluated as a model of the computational principles underlying ERP generation. Aside from fitting such a model, the current tutorial will also demonstrate how to classify hidden units of the RNN by their temporal responses and characterize them using principal component analysis. Statistical hypothesis testing can also be applied to these data. This paper focuses on presenting the modelling approach and subsequent analysis of model outputs in a how-to format, using publicly available data and shared code. While relatively less emphasis is placed on specific interpretations of P3 response generation, the results initiate some interesting discussion points.

Rates of false positive outcomes on the A-WPTAS picture items in a sample of non-concussed athletes.

Accurate diagnosis of sports related concussion ensures that athletes are removed from play if concussed and prevents incorrect removal when a concussion has not occurred. Although various screening tools are currently in use, there is no gold standard measure with which to diagnose sports related concussion.Objective: The current study aimed to investigate the diagnostic accuracy of the Abbreviated Westmead Post Traumatic Amnesia Scale (A-WPTAS) picture task, a neurocognitive measure used to assess mild traumatic brain injury. The incidence of false positive classifications and the potential confounding effect of exercise on scores on the A-WPTAS picture items were examined.Methods: The study included an athlete group comprising 33 players and a control group comprising 37 subjects. The A-WPTAS picture task was completed on three testing occasions, separated by three week intervals.Results: Results revealed that the A-WPTAS picture task was highly accurate (>95%) in correctly classifying participants with no concussion across all three testing occasions. There was no significant difference between the two groups in relation to false positive outcomes on any testing occasion, suggesting that exercise was not a confounding factor.Conclusions: Findings provide preliminary evidence to support the use of the A-WPTAS picture task in a sporting context.

The expected oddball: effects of implicit and explicit positional expectation on duration perception.

The oddball duration effect describes how a rare stimulus amongst a string of standard stimuli is perceived to have a longer duration than the standards, even if they are of the same objective duration. Several theories have been proposed to explain this phenomenon. In order to adjudicate between opposing explanations, we have borrowed three extensively studied paradigms from the variable foreperiod literature: the sequential foreperiod, temporal cueing and a skewed foreperiod distribution. This approach allowed us to examine the effects of positional expectation on perceived oddball duration, while avoiding confounds from first-order positioning of the oddball in a sequence of standards. Through these three experiments, we demonstrate a clear role of positional expectation in the lengthening of the perceived duration of an oddball. We show that this expectation effect is separable from other drivers of the oddball duration illusion.

Increased segregation of functional networks in developing brains.

A growing literature conceptualises typical brain development from a network perspective. However, largely due to technical and methodological challenges inherent in paediatric functional neuroimaging, there remains an important gap in our knowledge regarding the typical development of functional brain networks in "preschool" childhood (i.e., children younger than 6 years of age). In this study, we recorded brain oscillatory activity using age-appropriate magnetoencephalography in 24 children, including 14 preschool children aged from 4 to 6 years and 10 school children aged from 7 to 12 years. We compared the topology of the resting-state brain networks in these children, estimated using minimum spanning tree (MST) constructed from phase synchrony between beamformer-reconstructed time-series, with that of 24 adults. Our results show that during childhood the MST topology shifts from a star-like (centralised) toward a more line-like (de-centralised) configuration, indicating the functional brain networks become increasingly segregated. In addition, the increasing global network segregation is frequency-independent and accompanied by decreases in centrality (or connectedness) of cortical regions with age, especially in areas of the default mode network. We propose a heuristic MST model of "network space", which posits a clear developmental trajectory for the emergence of complex brain networks. Our results not only revealed topological reorganisation of functional networks across multiple temporal and spatial scales in childhood, but also fill a gap in the literature regarding neurophysiological mechanisms of functional brain maturation during the preschool years of childhood.

Adaptive Motor Imagery: A Multimodal Study of Immobilization-Induced Brain Plasticity.

The consequences of losing the ability to move a limb are traumatic. One approach that examines the impact of pathological limb nonuse on the brain involves temporary immobilization of a healthy limb. Here, we investigated immobilization-induced plasticity in the motor imagery (MI) circuitry during hand immobilization. We assessed these changes with a multimodal paradigm, using functional magnetic resonance imaging (fMRI) to measure neural activation, magnetoencephalography (MEG) to track neuronal oscillatory dynamics, and transcranial magnetic stimulation (TMS) to assess corticospinal excitability. fMRI results show a significant decrease in neural activation for MI of the constrained hand, localized to sensorimotor areas contralateral to the immobilized hand. MEG results show a significant decrease in beta desynchronization and faster resynchronization in sensorimotor areas contralateral to the immobilized hand. TMS results show a significant increase in resting motor threshold in motor cortex contralateral to the constrained hand, suggesting a decrease in corticospinal excitability in the projections to the constrained hand. These results demonstrate a direct and rapid effect of immobilization on MI processes of the constrained hand, suggesting that limb nonuse may not only affect motor execution, as evidenced by previous studies, but also MI. These findings have important implications for the effectiveness of therapeutic approaches that use MI as a rehabilitation tool to ameliorate the negative effects of limb nonuse.

Abnormal time course of low beta modulation in non-fluent preschool children: A magnetoencephalographic study of rhythm tracking.

Stuttering is a disorder of speech affecting millions of people around the world. Whilst the exact aetiology of stuttering remains unknown, it has been hypothesised that it is a disorder of the neural mechanisms that support speech timing. In this article, we used magnetoencephalography (MEG) to examine activity from auditory regions of the brain in stuttering and non-stuttering children aged 3-9years. For typically developing children, we found that MEG oscillations in the beta band responded to rhythmic sounds with a peak near the time of stimulus onset. In contrast, stuttering children showed an opposite phase of beta band envelope, with a trough of activity at stimulus onset. These results suggest that stuttering may result from abnormalities in predictive brain responses which are reflected in abnormal entrainment of the beta band envelope to rhythmic sounds.

Event-related fields evoked by vocal response inhibition: a comparison of younger and older adults.

The current study examined event-related fields (ERFs) evoked by vocal response inhibition in a stimulus-selective stop-signal task. We compared inhibition-related ERFs across a younger and an older group of adults. Behavioural results revealed that stop-signal reaction times (RTs), go-RTs, ignore-stop RTs and failed stop RTs were longer in the older, relative to the younger group by 38, 123, 149 and 116 ms, respectively. The amplitude of the ERF M2 peak (approximately 200 ms after the stop signal) evoked on successful stop trials was larger compared to that evoked on both failed stop and ignore-stop trials. The M4 peak (approximately 450 ms after stop signal) was of larger amplitude in both successful and failed stops compared to ignore-stop trials. In the older group, the M2, M3 and M4 peaks were smaller in amplitude and peaked later in time (by 24, 50 and 76 ms, respectively). We demonstrate that vocal response inhibition-related ERFs exhibit a similar temporal evolution to those previously described for manual response inhibition: an early peak at 200 ms (i.e. M2) that differentiates successful from failed stopping, and a later peak (i.e. M4) that is consistent with a neural marker of response checking and error processing. Across groups, our data support a more general decline of stimulus processing speed with age.

Vocal response inhibition is enhanced by anodal tDCS over the right prefrontal cortex.

Stopping outright (reactive inhibition) and slowing down (proactive inhibition) are types of response inhibition which have mainly been investigated in the manual effector system. This study compared reactive inhibition across manual and vocal effector systems, examined the effects of excitatory anodal transcranial direct current stimulation (anodal tDCS) over the right prefrontal cortex (right-PFC) and looked at the relationship between reactive and proactive inhibition. We hypothesised (1) that vocal reactive inhibition would be less effective than manual reactive inhibition as evidenced by longer stop signal reaction times; (2) that anodal tDCS would enhance both vocal and manual reactive inhibitions and (3) that proactive and reactive inhibitions would be positively related. We tested 14 participants over two sessions (one session with anodal tDCS and one session with sham stimulation) and applied stimulation protocol in the middle of the session, i.e. only during the second of three phases. We used a stop signal task across two stop conditions: relevant and irrelevant stop conditions in which stopping was required or ignored, respectively. We found that reactive inhibition was faster during and immediately after anodal tDCS relative to sham. We also found that greater level of proactive inhibition enhanced reactive inhibition (indexed by shorter stop signal reaction times). These results support the hypothesis that the right-PFC is part of a core network for reactive inhibition and supports previous contention that proactive inhibition is possibly modulated via preactivating the reactive inhibition network.

Development of effective connectivity in the core network for face perception.

This study measured effective connectivity within the core face network in young children using a paediatric magnetoencephalograph (MEG). Dynamic casual modeling (DCM) of brain responses was performed in a group of adults (N = 14) and a group of young children aged from 3 to 6 years (N = 15). Three candidate DCM models were tested, and the fits of the MEG data to the three models were compared at both individual and group levels. The results show that the connectivity structure of the core face network differs significantly between adults and children. Further, the relative strengths of face network connections were differentially modulated by experimental conditions in the two groups. These results support the interpretation that the core face network undergoes significant structural configuration and functional specialization between four years of age and adulthood.

Cortical activity differs between position- and force-control knee extension tasks.

Neural control differs between position- and force-control tasks as evident from divergent effects of fatigue and pain. Unlike force-control tasks, position-control tasks focus on a postural goal to maintain a joint angle. Cortical involvement is suggested to be less during postural control, but whether this differs between position- and force-control paradigms remains unclear. Coherence estimates the functional communication between spatially distinct active regions within the cortex (cortico-cortical coherence; CCC) and between the cortex and muscles (corticomuscular coherence; CMC). We investigated whether cortical involvement differed between force-control and more posturally focused, position-control tasks. Seventeen adults performed position- and force-control knee extensor efforts at a submaximal load (10 % maximum voluntary contraction). Surface electromyography was recorded from the right knee extensor and flexor muscles and brain activity using electroencephalography (EEG). CCC and CMC in the beta (13-30 Hz) and gamma (30-45 Hz) frequency bands were calculated between combinations of intra- and inter-hemispheric pairs of electrodes, and between four EEG electrodes that approximated the left motor cortical area, and right knee extensor EMG, respectively. Differences in EEG power and muscle activity were also calculated. CCC was greater across distributed regions in the force-control task. Beta EEG power in the left hemisphere was higher for the position-control task. Although averaged CMC data differed between tasks, there was no task difference for individual CMC data. Muscle activity and force did not differ between tasks. The results demonstrate differential cortical contributions to control force- versus position-control tasks. This might contribute to differences in performance outcomes of these tasks that have been shown previously.

A conceptual lemon: theta burst stimulation to the left anterior temporal lobe untangles object representation and its canonical color.

Object recognition benefits greatly from our knowledge of typical color (e.g., a lemon is usually yellow). Most research on object color knowledge focuses on whether both knowledge and perception of object color recruit the well-established neural substrates of color vision (the V4 complex). Compared with the intensive investigation of the V4 complex, we know little about where and how neural mechanisms beyond V4 contribute to color knowledge. The anterior temporal lobe (ATL) is thought to act as a "hub" that supports semantic memory by integrating different modality-specific contents into a meaningful entity at a supramodal conceptual level, making it a good candidate zone for mediating the mappings between object attributes. Here, we explore whether the ATL is critical for integrating typical color with other object attributes (object shape and name), akin to its role in combining nonperceptual semantic representations. In separate experimental sessions, we applied TMS to disrupt neural processing in the left ATL and a control site (the occipital pole). Participants performed an object naming task that probes color knowledge and elicits a reliable color congruency effect as well as a control quantity naming task that also elicits a cognitive congruency effect but involves no conceptual integration. Critically, ATL stimulation eliminated the otherwise robust color congruency effect but had no impact on the numerical congruency effect, indicating a selective disruption of object color knowledge. Neither color nor numerical congruency effects were affected by stimulation at the control occipital site, ruling out nonspecific effects of cortical stimulation. Our findings suggest that the ATL is involved in the representation of object concepts that include their canonical colors.

Examining predictive coding accounts of typical and autistic neurocognitive development.

Predictive coding has emerged as a prominent theoretical framework for understanding perception and its neural underpinnings. There has been a recent surge of interest in the predictive coding framework across the mind sciences. However, comparatively little of the research in this field has investigated the neural underpinnings of predictive coding in young neurotypical and autistic children. This paper provides an overview of predictive coding accounts of typical and autistic neurocognitive development and includes a review of the current electrophysiological evidence supporting these accounts. Based on the current evidence, it is clear that more research in pediatrics is needed to evaluate predictive coding accounts of neurocognitive development fully. If supported, these accounts could have wide-ranging practical implications for pedagogy, parenting, artificial intelligence, and clinical approaches to helping autistic children manage the barrage of everyday sensory information.

Localized estimation of event-related neural source activity from simultaneous MEG-EEG with a recurrent neural network.

Estimating intracranial current sources underlying the electromagnetic signals observed from extracranial sensors is a perennial challenge in non-invasive neuroimaging. Established solutions to this inverse problem treat time samples independently without considering the temporal dynamics of event-related brain processes. This paper describes current source estimation from simultaneously recorded magneto- and electro-encephalography (MEEG) using a recurrent neural network (RNN) that learns sequential relationships from neural data. The RNN was trained in two phases: (1) pre-training and (2) transfer learning with L1 regularization applied to the source estimation layer. Performance of using scaled labels derived from MEEG, magnetoencephalography (MEG), or electroencephalography (EEG) were compared, as were results from volumetric source space with free dipole orientation and surface source space with fixed dipole orientation. Exact low-resolution electromagnetic tomography (eLORETA) and mixed-norm L1/L2 (MxNE) source estimation methods were also applied to these data for comparison with the RNN method. The RNN approach outperformed other methods in terms of output signal-to-noise ratio, correlation and mean-squared error metrics evaluated against reference event-related field (ERF) and event-related potential (ERP) waveforms. Using MEEG labels with fixed-orientation surface sources produced the most consistent estimates. To estimate sources of ERF and ERP waveforms, the RNN generates temporal dynamics within its internal computational units, driven by sequential structure in neural data used as training labels. It thus provides a data-driven model of computational transformations from psychophysiological events into corresponding event-related neural signals, which is unique among MEEG source reconstruction solutions.

Neuromagnetic brain activity associated with anticipatory postural adjustments for bimanual load lifting.

During bimanual load lifting, the brain must anticipate the effects of unloading upon the load-bearing arm. Little is currently known about the neural networks that coordinate these anticipatory postural adjustments. We measured neuromagnetic brain activity with whole-head magnetoencephalography while participants performed a bimanual load-lifting task. Anticipatory adjustments were associated with reduction in biceps brachii muscle activity of the load-bearing arm and pre-movement desynchronization of the cortical beta rhythm. Beamforming analyses localized anticipatory brain activity to the precentral gyrus, basal ganglia, supplementary motor area, and thalamus, contralateral to the load-bearing arm. To our knowledge this is the first human neuroimaging study to directly investigate anticipatory postural adjustments and to explicitly partition the anticipatory and volitional aspects of brain activity in bimanual load lifting. These data contribute to our understanding of the neural systems supporting anticipatory postural adjustments in healthy adults.

Multimodal functional imaging of motor imagery using a novel paradigm.

Neuroimaging studies have shown that the neural mechanisms of motor imagery (MI) overlap substantially with the mechanisms of motor execution (ME). Surprisingly, however, the role of several regions of the motor circuitry in MI remains controversial, a variability that may be due to differences in neuroimaging techniques, MI training, instruction types, or tasks used to evoke MI. The objectives of this study were twofold: (i) to design a novel task that reliably invokes MI, provides a reliable behavioral measure of MI performance, and is transferable across imaging modalities; and (ii) to measure the common and differential activations for MI and ME with functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). We present a task in which it is difficult to give accurate responses without the use of either motor execution or motor imagery. The behavioral results demonstrate that participants performed similarly on the task when they imagined vs. executed movements and this performance did not change over time. The fMRI results show a spatial overlap of MI and ME in a number of motor and premotor areas, sensory cortices, cerebellum, inferior frontal gyrus, and ventrolateral thalamus. MI uniquely engaged bilateral occipital areas, left parahippocampus, and other temporal and frontal areas, whereas ME yielded unique activity in motor and sensory areas, cerebellum, precuneus, and putamen. The MEG results show a robust event-related beta band desynchronization in the proximity of primary motor and premotor cortices during both ME and MI. Together, these results further elucidate the neural circuitry of MI and show that our task robustly and reliably invokes motor imagery, and thus may prove useful for interrogating the functional status of the motor circuitry in patients with motor disorders.