Resting State Network Connectivity is attenuated by fMRI acoustic noise

Reliable measurement of auditory-driven gamma synchrony with a single EEG electrode: A simultaneous EEG-MEG study

OBJECTIVE

Auditory-driven gamma synchrony (GS) is linked to the function of a specific cortical circuit based on a parvalbumin+ and pyramidal neuron loop. This circuit is impaired in neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.) and its relevance in clinical practice is increasingly being recognized. Auditory stimulation at a typical gamma frequency of 40 Hz can be applied as a 'stress test' of excitation/inhibition (E/I) of the entire cerebral cortex, to drive GS and record it with magnetoencephalography (MEG) or high-density electroencephalography (EEG). However, these two techniques are costly and not widely available. Therefore, we assessed whether a single EEG electrode is sufficient to provide an accurate estimate of the auditory-driven GS level of the entire cortical surface while expecting the highest correspondence in the auditory and somatosensory cortices.

METHODS

We measured simultaneous EEG-MEG in 29 healthy subjects, utilizing 3 EEG electrodes (C4, F4, O2) and a full MEG setup. Recordings were performed during binaural exposure to auditory gamma stimulation and during silence. We compared GS measurement of each of the three EEG electrodes separately against full MEG mapping. Time-resolved phase locking value (PLVt) was computed between EEG signals and cortex reconstructed MEG signals.

RESULTS

During auditory stimulation, but not at rest, EEG captures a significant amount of GS, especially from both auditory cortices and motor-premotor regions. This was especially true for frontal (C4) and central electrodes (F4).

DISCUSSION AND CONCLUSIONS

While hd-EEG and MEG are necessary for accurate spatial mapping of GS at rest and during auditory stimulation, a single EEG channel is sufficient to detect the global level of GS. These results have great translational potential for mapping GS in standard clinical settings.

Methodological Choices Matter: A Systematic Comparison of TMS-EEG Studies Targeting the Primary Motor Cortex

Transcranial magnetic stimulation (TMS) triggers time-locked cortical activity that can be recorded with electroencephalography (EEG). Transcranial evoked potentials (TEPs) are widely used to probe brain responses to TMS. Here, we systematically reviewed 137 published experiments that studied TEPs elicited from TMS to the human primary motor cortex (M1) in healthy individuals to investigate the impact of methodological choices. We scrutinized prevalent methodological choices and assessed how consistently they were reported in published papers. We extracted amplitudes and latencies from reported TEPs and compared specific TEP peaks and components between studies using distinct methods. Reporting of methodological details was overall sufficient, but some relevant information regarding the TMS settings and the recording and preprocessing of EEG data were missing in more than 25% of the included experiments. The published TEP latencies and amplitudes confirm the "prototypical" TEP waveform following stimulation of M1, comprising distinct N15, P30, N45, P60, N100, and P180 peaks. However, variations in amplitude were evident across studies. Higher stimulation intensities were associated with overall larger TEP amplitudes. Active noise masking during TMS generally resulted in lower TEP amplitudes compared to no or passive masking but did not specifically impact those TEP peaks linked to long-latency sensory processing. Studies implementing independent component analysis (ICA) for artifact removal generally reported lower TEP magnitudes. In summary, some aspects of reporting practices could be improved in future TEP studies to enable replication. Methodological choices, including TMS intensity and the use of noise masking or ICA, introduce systematic differences in reported TEP amplitudes. Further investigation into the significance of these and other methodological factors and their interactions is warranted.

Aberrant thalamocortical connectivity and shifts between the resting state and task state in patients with schizophrenia

Prominent pathological hypotheses for schizophrenia include auditory processing deficits and dysconnectivity within cerebral networks. However, most neuroimaging studies have focused on impairments in either resting-state or task-related functional connectivity in patients with schizophrenia. The aims of our study were to examine (1) blood oxygen level-dependent (BOLD) signals during auditory steady-state response (ASSR) tasks, (2) functional connectivity during the resting-state and ASSR tasks and (3) state shifts between the resting-state and ASSR tasks in patients with schizophrenia. To reduce the functional consequences of scanner noise, we employed resting-state and sparse sampling auditory fMRI paradigms in 25 schizophrenia patients and 25 healthy controls. Auditory stimuli were binaural click trains at frequencies of 20, 30, 40 and 80 Hz. Based on the detected ASSR-evoked BOLD signals, we examined the functional connectivity between the thalamus and bilateral auditory cortex during both the resting state and ASSR task state, as well as their alterations. The schizophrenia group exhibited significantly diminished BOLD signals in the bilateral auditory cortex and thalamus during the 80 Hz ASSR task (corrected p < 0.05). We observed a significant inverse relationship between the resting state and ASSR task state in altered functional connectivity within the thalamo-auditory network in schizophrenia patients. Specifically, our findings demonstrated stronger functional connectivity in the resting state (p < 0.004) and reduced functional connectivity during the ASSR task (p = 0.048), which was mediated by abnormal state shifts, within the schizophrenia group. These results highlight the presence of abnormal thalamocortical connectivity associated with deficits in the shift between resting and task states in patients with schizophrenia.

Beyond boundaries: investigating shared and divergent connectivity in the pre-/postcentral gyri and supplementary motor area

OBJECTIVE

This study aimed to comprehensively investigate the functional connectivity of key brain regions involved in motor and sensory functions, namely the precentral gyrus, postcentral gyrus and supplementary motor area (SMA). Using advanced MRI, the objective was to understand the neurophysiological integrative characterizations of these regions by examining their connectivity with eight distinct functional brain networks. The goal was to uncover their roles beyond conventional motor and sensory functions, contributing to a more holistic understanding of brain functioning.

METHODS

The study involved 198 healthy volunteers, with the primary methodology being functional connectivity analysis using advanced MRI techniques. The bilateral precentral gyrus, postcentral gyrus and SMA served as seed regions, and their connectivity with eight distinct brain regional functional networks was investigated. This approach allowed for the exploration of synchronized activity between these critical brain areas, shedding light on their integrated functioning and relationships with other brain networks.

RESULTS

The study revealed a nuanced landscape of functional connectivity for the precentral gyrus, postcentral gyrus and SMA with the main functional brain networks. Despite their high functional connectedness, these regions displayed diverse functional integrations with other networks, particularly in the salience, visual, cerebellar and language networks. Specific data and statistical significance were not provided in the abstract, but the results suggested unique and distinct roles for each brain area in sophisticated cognitive tasks beyond their conventional motor and sensory functions.

CONCLUSION

The study emphasized the multifaceted roles of the precentral gyrus, postcentral gyrus and SMA. Beyond their crucial involvement in motor and sensory functions, these regions exhibited varied functional integrations with different brain networks. The observed disparities, especially in the salience, visual, cerebellar and language networks, indicated a nuanced and specialized involvement of these regions in diverse cognitive functions. The study underscores the importance of considering the broader neurophysiological landscape to comprehend the intricate roles of these brain areas, contributing to ongoing efforts in unraveling the complexities of brain function.

Assessing cortical excitability with electroencephalography: A pilot study with EEG-iTBS

BACKGROUND

Cortical excitability measures neural reactivity to stimuli, usually delivered via Transcranial Magnetic Stimulation (TMS). Excitation/inhibition balance (E/I) is the ongoing equilibrium between excitatory and inhibitory activity of neural circuits. According to some studies, E/I could be estimated in-vivo and non-invasively through the modeling of electroencephalography (EEG) signals and termed 'intrinsic excitability' measures. Several measures have been proposed (phase consistency in the gamma band, sample entropy, exponent of the power spectral density 1/f curve, E/I index extracted from detrend fluctuation analysis, and alpha power). Intermittent theta burst stimulation (iTBS) of the primary motor cortex (M1) is a non-invasive neuromodulation technique allowing controlled and focal enhancement of TMS cortical excitability and E/I of the stimulated hemisphere.

OBJECTIVE

Investigating to what extent E/I estimates scale with TMS excitability and how they relate to each other.

METHODS

M1 excitability (TMS) and several E/I estimates extracted from resting state EEG recordings were assessed before and after iTBS in a cohort of healthy subjects.

RESULTS

Enhancement of TMS M1 excitability, as measured through motor-evoked potentials (MEPs), and phase consistency of the cortex in high gamma band correlated with each other. Other measures of E/I showed some expected results, but no correlation with TMS excitability measures or strong consistency with each other.

CONCLUSIONS

EEG E/I estimates offer an intriguing opportunity to map cortical excitability non-invasively, with high spatio-temporal resolution and with a stimulus independent approach. While different EEG E/I estimates may reflect the activity of diverse excitatory-inhibitory circuits, spatial phase synchrony in the gamma band is the measure that best captures excitability changes in the primary motor cortex.

Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test-Retest Reliability

Transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) provide unique insights into cortical excitability and connectivity. However, confounding EEG signals from auditory and somatosensory co-stimulation complicate TEP interpretation. Our optimized sham procedure established with TMS of primary motor cortex (Gordon in JAMA 245:118708, 2021) differentiates direct cortical EEG responses to TMS from those caused by peripheral sensory inputs. Using this approach, this study aimed to investigate TEPs and their test-retest reliability when targeting regions outside the primary motor cortex, specifically the left angular gyrus, supplementary motor area, and medial prefrontal cortex. We conducted three identical TMS-EEG sessions one week apart involving 24 healthy participants. In each session, we targeted the three areas separately using a figure-of-eight TMS coil for active TMS, while a second coil away from the head produced auditory input for sham TMS. Masking noise and electric scalp stimulation were applied in both conditions to achieve matched EEG responses to peripheral sensory inputs. High test-retest reliability was observed in both conditions. However, reliability declined for the 'cleaned' TEPs, resulting from the subtraction of evoked EEG response to the sham TMS from those to the active, particularly for latencies > 100 ms following the TMS pulse. Significant EEG differences were found between active and sham TMS at latencies < 90 ms for all targeted areas, exhibiting distinct spatiotemporal characteristics specific to each target. In conclusion, our optimized sham procedure effectively reveals EEG responses to direct cortical activation by TMS in brain areas outside primary motor cortex. Moreover, we demonstrate the impact of peripheral sensory inputs on test-retest reliability of TMS-EEG responses.

The Benefit of Hearing Aids as Measured by Listening Accuracy, Subjective Listening Effort, and Functional Near Infrared Spectroscopy

There is broad consensus that listening effort is an important outcome for measuring hearing performance. However, there remains debate on the best ways to measure listening effort. This study sought to measure neural correlates of listening effort using functional near-infrared spectroscopy (fNIRS) in experienced adult hearing aid users. The study evaluated impacts of amplification and signal-to-noise ratio (SNR) on cerebral blood oxygenation, with the expectation that easier listening conditions would be associated with less oxygenation in the prefrontal cortex. Thirty experienced adult hearing aid users repeated sentence-final words from low-context Revised Speech Perception in Noise Test sentences. Participants repeated words at a hard SNR (individual SNR-50) or easy SNR (individual SNR-50 + 10 dB), while wearing hearing aids fit to prescriptive targets or without wearing hearing aids. In addition to assessing listening accuracy and subjective listening effort, prefrontal blood oxygenation was measured using fNIRS. As expected, easier listening conditions (i.e., easy SNR, with hearing aids) led to better listening accuracy, lower subjective listening effort, and lower oxygenation across the entire prefrontal cortex compared to harder listening conditions. Listening accuracy and subjective listening effort were also significant predictors of oxygenation.

Cleaning up the Brickyard: How Theory and Methodology Shape Experiments in Cognitive Neuroscience of Language

The capacity for language is a defining property of our species, yet despite decades of research, evidence on its neural basis is still mixed and a generalized consensus is difficult to achieve. We suggest that this is partly caused by researchers defining "language" in different ways, with focus on a wide range of phenomena, properties, and levels of investigation. Accordingly, there is very little agreement among cognitive neuroscientists of language on the operationalization of fundamental concepts to be investigated in neuroscientific experiments. Here, we review chains of derivation in the cognitive neuroscience of language, focusing on how the hypothesis under consideration is defined by a combination of theoretical and methodological assumptions. We first attempt to disentangle the complex relationship between linguistics, psychology, and neuroscience in the field. Next, we focus on how conclusions that can be drawn from any experiment are inherently constrained by auxiliary assumptions, both theoretical and methodological, on which the validity of conclusions drawn rests. These issues are discussed in the context of classical experimental manipulations as well as study designs that employ novel approaches such as naturalistic stimuli and computational modeling. We conclude by proposing that a highly interdisciplinary field such as the cognitive neuroscience of language requires researchers to form explicit statements concerning the theoretical definitions, methodological choices, and other constraining factors involved in their work.

Functional ultrasound reveals effects of MRI acoustic noise on brain function

Loud acoustic noise from the scanner during functional magnetic resonance imaging (fMRI) can affect functional connectivity (FC) observed in the resting state, but the exact effect of the MRI acoustic noise on resting state FC is not well understood. Functional ultrasound (fUS) is a neuroimaging method that visualizes brain activity based on relative cerebral blood volume (rCBV), a similar neurovascular coupling response to that measured by fMRI, but without the audible acoustic noise. In this study, we investigated the effects of different acoustic noise levels (silent, 80 dB, and 110 dB) on FC by measuring resting state fUS (rsfUS) in awake mice in an environment similar to fMRI measurement. Then, we compared the results to those of resting state fMRI (rsfMRI) conducted using an 11.7 Tesla scanner. RsfUS experiments revealed a significant reduction in FC between the retrosplenial dysgranular and auditory cortexes (0.56 ± 0.07 at silence vs 0.05 ± 0.05 at 110 dB, p=.01) and a significant increase in FC anticorrelation between the infralimbic and motor cortexes (-0.21 ± 0.08 at silence vs -0.47 ± 0.04 at 110 dB, p=.017) as acoustic noise increased from silence to 80 dB and 110 dB, with increased consistency of FC patterns between rsfUS and rsfMRI being found with the louder noise conditions. Event-related auditory stimulation experiments using fUS showed strong positive rCBV changes (16.5% ± 2.9% at 110 dB) in the auditory cortex, and negative rCBV changes (-6.7% ± 0.8% at 110 dB) in the motor cortex, both being constituents of the brain network that was altered by the presence of acoustic noise in the resting state experiments. Anticorrelation between constituent brain regions of the default mode network (such as the infralimbic cortex) and those of task-positive sensorimotor networks (such as the motor cortex) is known to be an important feature of brain network antagonism, and has been studied as a biological marker of brain disfunction and disease. This study suggests that attention should be paid to the acoustic noise level when using rsfMRI to evaluate the anticorrelation between the default mode network and task-positive sensorimotor network.

The impact of ROI extraction method for MEG connectivity estimation: practical recommendations for the study of resting state data

Magnetoencephalography and electroencephalography (M/EEG) seed-based connectivity analysis requires the extraction of measures from regions of interest (ROI). M/EEG ROI-derived source activity can be treated in different ways. It is possible, for instance, to average each ROI's time series prior to calculating connectivity measures. Alternatively, one can compute connectivity maps for each element of the ROI prior to dimensionality reduction to obtain a single map. The impact of these different strategies on connectivity results is still unclear. Here, we address this question within a large MEG resting state cohort (N=113) and within simulated data. We consider 68 ROIs (Desikan-Kiliany atlas), two measures of connectivity (phase locking value-PLV, and its imaginary counterpart- ciPLV), and three frequency bands (theta 4-8 Hz, alpha 9-12 Hz, beta 15-30 Hz). We compare four extraction methods: (i) mean, or (ii) PCA of the activity within the seed or ROI before computing connectivity, map of the (iii) average, or (iv) maximum connectivity after computing connectivity for each element of the seed. Hierarchical clustering is then applied to compare connectivity outputs across multiple strategies, followed by direct contrasts across extraction methods. Finally, the results are validated by using a set of realistic simulations. We show that ROI-based connectivity maps vary remarkably across strategies in terms of connectivity magnitude and spatial distribution. Dimensionality reduction procedures conducted after computing connectivity are more similar to each-other, while PCA before approach is the most dissimilar to other approaches. Although differences across methods are consistent across frequency bands, they are influenced by the connectivity metric and ROI size. Greater differences were observed for ciPLV than PLV, and in larger ROIs. Realistic simulations confirmed that after aggregation procedures are generally more accurate but have lower specificity (higher rate of false positive connections). Though computationally demanding, after dimensionality reduction strategies should be preferred when higher sensitivity is desired. Given the remarkable differences across aggregation procedures, caution is warranted in comparing results across studies applying different methods.

Auditory white noise exposure results in intrinsic cortical excitability changes

Cortical excitability is commonly measured by applying magnetic stimulation in combination with measuring behavioral response. This measure has, however, some shortcomings including spatial limitation to the primary motor cortex and not accounting for intrinsic excitability fluctuations. Here, we use a measure for intrinsic excitability based on phase synchronization previously validated for epilepsy. We apply this measure in 30 healthy participants' magnetoencephalography (MEG) recordings during the exposure of auditory white noise, a stimulus that has been suggested to modify cortical excitability. Using cortical parcellation of the MEG source data, we could find a specific pattern of increased and decreased excitability while participants are exposed to white noise vs. silence. Specifically, excitability during white noise exposure decreases in the frontal lobe and increases in the temporal lobe. This study thus adds to the understanding of cortical excitability changes due to specific environmental stimuli as well as the spatial extent of these effects.

Odor-evoked layer-specific fMRI activities in the awake mouse olfactory bulb

Awake rodent fMRI is increasingly common over the use of anesthesia since it permits behavioral paradigms and does not confound normal brain function or neurovascular coupling. It is well established that adequate acclimation to the loud fMRI environment and head fixation reduces stress in the rodents and allows for whole brain imaging with little contamination from motion. However, it is unknown whether high-resolution fMRI with increased susceptibility to motion and lower sensitivity can measure small, but spatially discrete, activations in awake mice. To examine this, we used contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI in the mouse olfactory bulb for its enhanced sensitivity and neural specificity. We determined that activation patterns in the glomerular layer to four different odors were spatially distinct and were consistent with previously established histological patterns. In addition, odor-evoked laminar activations were greatest in superficial layers that decreased with laminar depth, similar to previous observations. Interestingly, the fMRI response strengths in the granule cell layer were greater in awake mice than our previous anesthetized rat studies, suggesting that feedback neural activities were intact with wakefulness. We finally determined that fMRI signal changes to repeated odor exposure (i.e., olfactory adaptation) attenuated relatively more in the feedback granule cell layer compared to the input glomerular layer, which is consistent with prior observations. We, therefore, conclude that high-resolution CBVw fMRI can measure odor-specific activation patterns and distinguish changes in laminar activity of head and body restrained awake mice.

Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas

BACKGROUND

Magnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation.

METHOD

We validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (iEEG) atlas (https://mni-open-ieegatlas.

RESEARCH

mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space by applying a forward model to the MEG-reconstructed source maps, and estimated virtual iEEG (ViEEG) potentials on each iEEG channel location; we finally quantitatively compared those with actual iEEG signals from the atlas for 38 regions of interest in the canonical frequency bands.

RESULTS

The MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the ViEEG than in the iEEG were more accurately recovered. In the deep regions, MEG-estimated amplitudes were largely underestimated and the spectra were poorly recovered. Overall, our wMEM results were similar to those obtained with minimum norm or beamformer source localization. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of iEEG but detected by MEG. Importantly, we found that MEG-estimated spectra were more comparable to spectra from the iEEG atlas after the aperiodic components were removed.

CONCLUSION

This study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.

Reduced connectivity of primary auditory and motor cortices during exposure to auditory white noise

Auditory white noise (WN) is widely used in daily life for inducing sleep, and in neuroscience to mask unwanted environmental noise and cues. However, WN was recently reported to influence corticospinal excitability and behavioral performance. Here, we expand previous preliminary findings on the influence of WN exposure on cortical functioning, and we hypothesize that it may modulate cortical connectivity. We tested our hypothesis by performing magnetoencephalography in 20 healthy subjects. WN reduces cortical connectivity of the primary auditory and motor regions with very distant cortical areas, showing a right lateralized connectivity reduction for primary motor cortex. The present results, together with previous finding concerning WN impact on corticospinal excitability and behavioral performance, further support the role of WN as a modulator of cortical function. This suggest avoiding its unrestricted use as a masking tool, while purposely designed and controlled WN application could be exploited to harness brain function and to treat neuropsychiatric conditions.

Functional connectivity of sub-cortical brain regions: disparities and similarities

Sub-cortical grey matter structures, such as the putamen, pallidum, caudate, thalamus, amygdala and hippocampus, play substantial roles in both simple and complex brain functions, including regulation of pleasure and emotions; control of movements; learning; decision-making; language development; and sensory, cognitive, social and other higher-order functions. Most of these regions act as information hubs for the nervous system, relaying and controlling the flow of information to various portions of the brain. To further understand the complex neurophysiological characteristics of sub-cortical areas, the aim of this study was to investigate the functional integrations of six sub-cortical areas to different major functional brain networks. One hundred ninety-eight healthy individuals were examined using resting-state functional MRI. The seeds identified in this study were six sub-cortical deep grey matter regions, namely putamen, pallidum, caudate, thalamus, amygdala and hippocampus. The analysis indicated that the link between the sub-cortical regions and some functional brain networks was similar in some aspects, but there were disparities in the mechanism underlying such a link and in the existence of functional connections between these regions and networks. Despite the substantial functional connectivity linkages between the sub-cortical regions, discrepancies were still noted. On the basis of the connections to the majority of the major brain networks, this study demonstrated the essential functional roles and involvements of the sub-cortical regions. This finding is consistent with an earlier report that revealed a substantial role of the sub-cortical regions in several brain functions.

TMS combined with EEG: Recommendations and open issues for data collection and analysis

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS-EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS-EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS-EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS-EEG covered all aspects that should be considered in TMS-EEG experiments, providing methodological recommendations (when possible) for effective TMS-EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS-EEG methodology and thus may promote standardization of experimental and computational procedures across groups.

State-dependent tDCS modulation of the somatomotor network: A MEG study

OBJECTIVE

Transcranial direct current stimulation (tDCS) is a non-invasive technique widely used to investigate brain excitability and activity. However, the variability in both brain and behavioral responses to tDCS limits its application for clinical purposes. This study aims to shed light on state-dependency, a phenomenon that contributes to the variability of tDCS.

METHODS

To this aim, we investigated changes in spectral activity and functional connectivity in somatomotor regions after Real and Sham tDCS using generalized additive mixed models (GAMMs), which allowed us to investigate how modulation depends on the initial state of the brain.

RESULTS

Results showed that changes in spectral activity, but not connectivity, in the somatomotor regions depend on the initial state of the brain, confirming state-dependent effects. Specifically, we found a non-linear interaction between stimulation conditions (Real vs Sham) and initial state: a reduction of alpha and beta power was observed only in participants that had higher alpha and beta power before Real tDCS.

CONCLUSIONS

This study highlights the importance of considering state-dependency to tDCS and shows how it can be taken into account with appropriate statistical models.

SIGNIFICANCE

Our findings bear insight into tDCS mechanisms, potentially leading to discriminate between tDCS responders and non-responders.

Stimulation with acoustic white noise enhances motor excitability and sensorimotor integration

Auditory white noise (WN) is widely used in neuroscience to mask unwanted environmental noise and cues, e.g. TMS clicks. However, to date there is no research on the influence of WN on corticospinal excitability and potentially associated sensorimotor integration itself. Here we tested the hypothesis, if WN induces M1 excitability changes and improves sensorimotor performance. M1 excitability (spTMS, SICI, ICF, I/O curve) and sensorimotor reaction-time performance were quantified before, during and after WN stimulation in a set of experiments performed in a cohort of 61 healthy subjects. WN enhanced M1 corticospinal excitability, not just during exposure, but also during silence periods intermingled with WN, and up to several minutes after the end of exposure. Two independent behavioural experiments highlighted that WN improved multimodal sensorimotor performance. The enduring excitability modulation combined with the effects on behaviour suggest that WN might induce neural plasticity. WN is thus a relevant modulator of corticospinal function; its neurobiological effects should not be neglected and could in fact be exploited in research applications.

Auditory driven gamma synchrony is associated with cortical thickness in widespread cortical areas

OBJECTIVE

Gamma synchrony is a fundamental functional property of the cerebral cortex, impaired in multiple neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.). Auditory stimulation in the gamma range allows to drive gamma synchrony of the entire cortical mantle and to estimate the efficiency of the mechanisms sustaining it. As gamma synchrony depends strongly on the interplay between parvalbumin-positive interneurons and pyramidal neurons, we hypothesize an association between cortical thickness and gamma synchrony. To test this hypothesis, we employed a combined magnetoencephalography (MEG) - Magnetic Resonance Imaging (MRI) study.

METHODS

Cortical thickness was estimated from anatomical MRI scans. MEG measurements related to exposure of 40 Hz amplitude modulated tones were projected onto the cortical surface. Two measures of cortical synchrony were considered: (a) inter-trial phase consistency at 40 Hz, providing a vertex-wise estimation of gamma synchronization, and (b) phase-locking values between primary auditory cortices and whole cortical mantle, providing a measure of long-range cortical synchrony. A correlation between cortical thickness and synchronization measures was then calculated for 72 MRI-MEG scans.

RESULTS

Both inter-trial phase consistency and phase locking values showed a significant positive correlation with cortical thickness. For inter-trial phase consistency, clusters of strong associations were found in the temporal and frontal lobes, especially in the bilateral auditory and pre-motor cortices. Higher phase-locking values corresponded to higher cortical thickness in the frontal, temporal, occipital and parietal lobes.

DISCUSSION AND CONCLUSIONS

In healthy subjects, a thicker cortex corresponds to higher gamma synchrony and connectivity in the primary auditory cortex and beyond, likely reflecting underlying cell density involved in gamma circuitries. This result hints towards an involvement of gamma synchrony together with underlying brain structure in brain areas for higher order cognitive functions. This study contributes to the understanding of inherent cortical functional and structural brain properties, which might in turn constitute the basis for the definition of useful biomarkers in patients showing aberrant gamma synchronization.

Altered resting-state functional connectivity of medial frontal cortex in overweight individuals: Link to food-specific intentional inhibition and weight gain

Numerous findings from functional neuroimaging research suggest that overweight may be associated with alterations in reactive inhibition. However, there is a dearth of research investigating the functional connectivity that mediates intentional inhibition in overweight individuals. To explore this issue, 55 overweight and 45 normal-weight adults completed an assessment consisting of a resting-state functional magnetic resonance imaging scan, a behavioural task measuring food-specific intentional inhibition, and a 1-year longitudinal measurement of BMI change. A seed-based approach was employed to examine the group-difference of the resting-state functional connectivity (rsFC) of the medial frontal cortex (MFC) (dorsal fronto-medial cortex [dFMC], pre-supplementary motor area, and premotor cortex) regions involved in intentional inhibition. Compared with normal-weight adults, the overweight individuals exhibited higher rsFC between the MFC seeds and (i) cerebellum, (ii) postcentral gyrus, (iii) middle temporal gyrus, and (iv) posterior cingulate cortex, while lower rsFC strength were observed between MFC seeds and (i) putamen and (ii) insula. The overweight individuals with higher dFMC-cerebellum rsFC strength showed poorer performance in food-specific intentional inhibition and gained more weight a year later than those of normal-weight participants. Results suggested that altered functional connections between MFC and regions associated with reward and maladaptive eating may be key neural mechanisms of food-specific intentional inhibition in overweight status. Therefore, individuals are encouraged to make informed decisions about their health and reduce their consumption of obesogenic foods from the perspective of intentional inhibition.

Exposure to traffic-related air pollution and noise during pregnancy and childhood, and functional brain connectivity in preadolescents

BACKGROUND

The amount of people affected by traffic-related air pollution and noise is continuously increasing, but limited research has been conducted on the association between these environmental exposures and functional brain connectivity in children.

OBJECTIVE

This exploratory study aimed to analyze the associations between the exposure to traffic-related air pollution and noise during pregnancy and childhood, and functional brain connectivity amongst a wide-swath of brain areas in preadolescents from 9 to 12 years of age.

METHODS

We used data of 2,197 children from the Generation R Study. Land use regression models were applied to estimate nitrogen oxides and particulate matter levels at participant's homes for several time periods: pregnancy, birth to 3 years, 3 to 6 years, and 6 years of age to the age at magnetic resonance imaging (MRI) assessment. Existing noise maps were used to estimate road traffic noise exposure at participant's homes for the same time periods. Resting-state functional MRI was obtained at 9-12 years of age. Pair-wise correlation coefficients of the blood-oxygen-level-dependent signals between 380 brain areas were calculated. Linear regressions were run and corrected for multiple testing.

RESULTS

Preadolescents exposed to higher levels of NO₂, NO_x, and PM_2.5 absorbance, from birth to 3 years, and from 3 to 6 years of age showed higher correlation coefficients among several brain regions (e.g. from 0.16 to 0.19 higher correlation coefficient related to PM_2.5 absorbance exposure, depending on the brain connection). Overall, most identified associations were between brain regions of the task positive and task negative networks, and were mainly inter-network (20 of 26). Slightly more than half of the connections were intra-hemispheric (14 of 26), predominantly in the right hemisphere. Road traffic noise was not associated with functional brain connectivity.

CONCLUSIONS

This exploratory study found that exposure to traffic-related air pollution during the first years of life was related to higher functional brain connectivity predominantly in brain areas located in the task positive and task negative networks, in preadolescents from 9 to 12 years of age. These results could be an indicator of differential functional connectivity in children exposed to higher levels of air pollution.

Future Directions for Chemosensory Connectomes: Best Practices and Specific Challenges

Ecological chemosensory stimuli almost always evoke responses in more than one sensory system. Moreover, any sensory processing takes place along a hierarchy of brain regions. So far, the field of chemosensory neuroimaging is dominated by studies that examine the role of brain regions in isolation. However, to completely understand neural processing of chemosensation, we must also examine interactions between regions. In general, the use of connectivity methods has increased in the neuroimaging field, providing important insights to physical sensory processing, such as vision, audition, and touch. A similar trend has been observed in chemosensory neuroimaging, however, these established techniques have largely not been rigorously applied to imaging studies on the chemical senses, leaving network insights overlooked. In this article, we first highlight some recent work in chemosensory connectomics and we summarize different connectomics techniques. Then, we outline specific challenges for chemosensory connectome neuroimaging studies. Finally, we review best practices from the general connectomics and neuroimaging fields. We recommend future studies to develop or use the following methods we perceive as key to improve chemosensory connectomics: (1) optimized study designs, (2) reporting guidelines, (3) consensus on brain parcellations, (4) consortium research, and (5) data sharing.