Multiscale energy reallocation during low‐frequency steady‐state brain response

Traditional task‐evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low‐frequency steady‐state brain response (lfSSBR) reflects frequency‐tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra‐slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain–behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency‐specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks.     

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): Proof of concept in the human

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 13–35 Hz (“beta band”) oscillatory dynamics in the manifestation of Parkinson's disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulses with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequency-specific (16–22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.     

Neuronal dynamics enable the functional differentiation of resting state networks in the human brain

Intrinsic brain activity is organized in spatial–temporal patterns, called resting‐state networks (RSNs), exhibiting specific structural–functional architecture. These networks presumably reflect complex neurophysiological processes and have a central role in distinct perceptual and cognitive functions. In this work, we propose an innovative approach for characterizing RSNs according to their underlying neural oscillations. We investigated specific electrophysiological properties, including spectral features, fractal dimension, and entropy, associated with eight core RSNs derived from high‐density electroencephalography (EEG) source‐reconstructed signals. Specifically, we found higher synchronization of the gamma‐band activity and higher fractal dimension values in perceptual (PNs) compared with higher cognitive (HCNs) networks. The inspection of this underlying rapid activity becomes of utmost importance for assessing possible alterations related to specific brain disorders. The disruption of the coordinated activity of RSNs may result in altered behavioral and perceptual states. Thus, this approach could potentially be used for the early detection and treatment of neurological disorders.     

Parcellation influence on the connectivity‐based structure–function relationship in the human brain

One of the fundamental questions in neuroscience is how brain structure and function are intertwined. MRI‐based studies have demonstrated a close relationship between the physical wiring of the brain (structural connectivity) and the associated patterns of synchronization (functional connectivity). However, little is known about the spatial consistency of such a relationship and notably its potential dependence on brain parcellations. In the present study, we performed a comparison of a set of state‐of‐the‐art group‐wise brain atlases, with various spatial resolutions, to relate structural and functional connectivity derived from high quality MRI data. We aim to investigate if the definition of brain areas influences the relationship between structural and functional connectivity. We observed that there is a significant effect of brain parcellations, which is mainly driven by the number of areas; there are mixed differences in the SC–FC relationship when compared to purely random parcellations; the influence of the number of areas cannot be attributed solely to the reliability of the connectivity estimates; and beyond the influence of the number of regions, the spatial embedding of the brain (distance effect) can explain a large portion of the observed relationship. As such the choice of a brain parcellation for connectivity analyses remains most likely a matter of convenience.     

Alpha Oscillations Shape Sensory Representation and Perceptual Sensitivity

Alpha activity (8–14 Hz) is the dominant rhythm in the awake brain and is thought to play an important role in setting the internal state of the brain. Previous work has associated states of decreased alpha power with enhanced neural excitability. However, evidence is mixed on whether and how such excitability enhancement modulates sensory signals of interest versus noise differently, and what, if any, are the consequences for subsequent perception. Here, human subjects (male and female) performed a visual detection task in which we manipulated their decision criteria in a blockwise manner. Although our manipulation led to substantial criterion shifts, these shifts were not reflected in prestimulus alpha band changes. Rather, lower prestimulus alpha power in occipital-parietal areas improved perceptual sensitivity and enhanced information content decodable from neural activity patterns. Additionally, oscillatory alpha phase immediately before stimulus presentation modulated accuracy. Together, our results suggest that alpha band dynamics modulate sensory signals of interest more strongly than noise.SIGNIFICANCE STATEMENT The internal state of our brain fluctuates, giving rise to variability in perception and action. Neural oscillations, most prominently in the alpha band, have been suggested to play a role in setting this internal state. Here, we show that ongoing alpha band activity in occipital-parietal regions predicts the quality of visual information decodable in neural activity patterns and subsequently the human observer''s sensitivity in a visual detection task. Our results provide comprehensive evidence that visual representation is modulated by ongoing alpha band activity and advance our understanding on how, when faced with unchanging external stimuli, internal neural fluctuations influence perception and behavior.     

Movement‐related neuromagnetic fields in preschool age children

We examined sensorimotor brain activity associated with voluntary movements in preschool children using a customized pediatric magnetoencephalographic system. A videogame‐like task was used to generate self‐initiated right or left index finger movements in 17 healthy right‐handed subjects (8 females, ages 3.2–4.8 years). We successfully identified spatiotemporal patterns of movement‐related brain activity in 15/17 children using beamformer source analysis and surrogate MRI spatial normalization. Readiness fields in the contralateral sensorimotor cortex began ～0.5 s prior to movement onset (motor field, MF), followed by transient movement‐evoked fields (MEFs), similar to that observed during self‐paced movements in adults, but slightly delayed and with inverted source polarities. We also observed modulation of mu (8–12 Hz) and beta (15–30 Hz) oscillations in sensorimotor cortex with movement, but with different timing and a stronger frequency band coupling compared to that observed in adults. Adult‐like high‐frequency (70–80 Hz) gamma bursts were detected at movement onset. All children showed activation of the right superior temporal gyrus that was independent of the side of movement, a response that has not been reported in adults. These results provide new insights into the development of movement‐related brain function, for an age group in which no previous data exist. The results show that children under 5 years of age have markedly different patterns of movement‐related brain activity in comparison to older children and adults, and indicate that significant maturational changes occur in the sensorimotor system between the preschool years and later childhood. Hum Brain Mapp 35:4858–4875, 2014. © 2014 Wiley Periodicals, Inc .     

Effects of scopolamine on MEG spectral power and coherence in elderly subjects

Objective: Scopolamine, a muscarinic receptor antagonist, can produce temporary cognitive impairments as well as electroencephalographic changes that partially resemble those observed in Alzheimer's disease. In order to test the sensitivity of spectral power and hemispheric coherence to changes in cholinergic transmission, we evaluated quantitative magnetoencephalogram (MEG) after intravenous injection of scopolamine.Methods: MEG of 8 elderly healthy subjects (59–80 years) were measured with a whole-head magnetometer after intravenous injection of scopolamine. An injection of glycopyrrolate, a peripheral muscarinic antagonist, was used as the placebo in a double-blind, randomized, cross-over design. Spectral power and coherence were computed over 7 brain regions in 3 frequency bands.Results: Scopolamine administration increased theta activity (4–8 Hz) and resulted in the abnormal pattern of MEG desynchronization in eyes-open vs. eyes-closed conditions in the alpha band (8–13 Hz). These effects were most prominent over the posterior regions. Interhemispheric and left intrahemispheric coherence was significantly decreased in the theta band (4–8 Hz).Conclusions: Spontaneous cortical activity at the theta and alpha range and functional coupling in the theta band are modulated by the cholinergic system. MEG may provide a tool for monitoring brain dynamics in neurological disorders associated with cholinergic abnormalities.     

tDCS modulates behavioral performance and the neural oscillatory dynamics serving visual selective attention

Transcranial direct‐current stimulation (tDCS) is a noninvasive method for modulating human brain activity. Although there are several hypotheses about the net effects of tDCS on brain function, the field's understanding remains incomplete and this is especially true for neural oscillatory activity during cognitive task performance. In this study, we examined whether different polarities of occipital tDCS differentially alter flanker task performance and the underlying neural dynamics. To this end, 48 healthy adults underwent 20 min of anodal, cathodal, or sham occipital tDCS, and then completed a visual flanker task during high‐density magnetoencephalography (MEG). The resulting oscillatory responses were imaged in the time‐frequency domain using beamforming, and the effects of tDCS on task‐related oscillations and spontaneous neural activity were assessed. The results indicated that anodal tDCS of the occipital cortices inhibited flanker task performance as measured by reaction time, elevated spontaneous activity in the theta (4–7 Hz) and alpha (9–14 Hz) bands in prefrontal and occipital cortices, respectively, and reduced task‐related theta oscillatory activity in prefrontal cortices during task performance. Cathodal tDCS of the occipital cortices did not significantly affect behavior or any of these neuronal parameters in any brain region. Lastly, the power of theta oscillations in the prefrontal cortices was inversely correlated with reaction time. In conclusion, anodal tDCS modulated task‐related oscillations and spontaneous activity across multiple cortical areas, both near the electrode and in distant sites that were putatively connected to the targeted regions.     

Neurofeedback: Principles,appraisal, and outstanding issues

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last 20 years, neurofeedback has been used to treat various neurological and psychiatric conditions, and to improve cognitive function in various contexts. However, in spite of a growing popularity, neurofeedback protocols typically make (often covert) assumptions on what aspects of brain activity to target, where in the brain to act and how, which have far‐reaching implications for the assessment of its potential and efficacy. Here we critically examine some conceptual and methodological issues associated with the way neurofeedback's general objectives and neural targets are defined. The neural mechanisms through which neurofeedback may act at various spatial and temporal scales, and the way its efficacy is appraised are reviewed, and the extent to which neurofeedback may be used to control functional brain activity discussed. Finally, it is proposed that gauging neurofeedback's potential, as well as assessing and improving its efficacy will require better understanding of various fundamental aspects of brain dynamics and a more precise definition of functional brain activity and brain‐behaviour relationships.     

On the relation between brain images and brain neural networks

The relationship between brain images observed by PET and fMRI and the underlying neural activity is analysed using recent results on the detailed nature of averaged and synchronised activity of coupled neural networks and on a simplifying model of the level of blood flow caused by neural activity. The conditions on the coupled neural systems are specified that lead to structural equation models, giving support to analysis of the covariance structural equation modelling of brain imaging data. The relation between the resulting models and possible neural codes are analysed. Furthermore, a new form of structural equation model is derived, in which all neuronal activity arises as hidden variables. We discuss how the results of such analyses can be transported back to the domain of coupled temporally dynamic neural systems in the brain appropriate to EEG and MEG observations.     

Fast periodic visual stimulation to highlight the relationship between human intracerebral recordings and scalp electroencephalography

Despite being of primary importance for fundamental research and clinical studies, the relationship between local neural population activity and scalp electroencephalography (EEG) in humans remains largely unknown. Here we report simultaneous scalp and intracerebral EEG responses to face stimuli in a unique epileptic patient implanted with 27 intracerebral recording contacts in the right occipitotemporal cortex. The patient was shown images of faces appearing at a frequency of 6 Hz, which elicits neural responses at this exact frequency. Response quantification at this frequency allowed to objectively relate the neural activity measured inside and outside the brain. The patient exhibited typical 6 Hz responses on the scalp at the right occipitotemporal sites. Moreover, there was a clear spatial correspondence between these scalp responses and intracerebral signals in the right lateral inferior occipital gyrus, both in amplitude and in phase. Nevertheless, the signal measured on the scalp and inside the brain at nearby locations showed a 10‐fold difference in amplitude due to electrical insulation from the head. To further quantify the relationship between the scalp and intracerebral recordings, we used an approach correlating time‐varying signals at the stimulation frequency across scalp and intracerebral channels. This analysis revealed a focused and right‐lateralized correspondence between the scalp and intracerebral recordings that were specific to the face stimulation is more broadly distributed in various control situations. These results demonstrate the interest of a frequency tagging approach in characterizing the electrical propagation from brain sources to scalp EEG sensors and in identifying the cortical sources of brain functions from these recordings.     

Attention modulates beta oscillations during prolonged tactile stimulation

The inter‐play between changes in beta‐band (14–30‐Hz) cortical rhythms and attention during somatosensation informs us about where and when relevant processes occur in the brain. As such, we investigated the effects of attention on somatosensory evoked and induced responses using vibrotactile stimulation and magnetoencephalographic recording. Subjects received trains of vibration at 23 Hz to the right index finger while watching a movie and ignoring the somatosensory stimuli or paying attention to the stimuli to detect a change in the duration of the stimulus. The amplitude of the evoked 23‐Hz steady‐state response in the contralateral primary somatosensory cortex (SI) was enhanced by attention and the underlying dipole source was located 2 mm more medially, indicating top‐down recruitment of additional neuronal populations for the functionally relevant stimulus. Attentional modulation of the somatosensory evoked response indicates facilitation of early processing of the tactile stimulus. Beta‐band activity increased after vibration offset in the contralateral primary motor cortex (MI) [event‐related synchronization (ERS)] and this increase was larger for attended than ignored stimuli. Beta‐band activity decreased in the ipsilateral SI prior to stimulus offset [event‐related desynchronization (ERD)] for attended stimuli only. Whereas attention modulation of the evoked response was confined to the contralateral SI, event‐related changes of beta‐band activity involved contralateral SI–MI and inter‐hemispheric SI–SI connections. Modulation of neural activity in such a large sensorimotor network indicates a role for beta activity in higher‐order processing.     

Cortex-Wide Dynamics of Intrinsic Electrical Activities: Propagating Waves and Their Interactions

Cortical circuits generate patterned activities that reflect intrinsic brain dynamics that lay the foundation for any, including stimuli-evoked, cognition and behavior. However, the spatiotemporal organization properties and principles of this intrinsic activity have only been partially elucidated because of previous poor resolution of experimental data and limited analysis methods. Here we investigated continuous wave patterns in the 0.5–4 Hz (delta band) frequency range on data from high-spatiotemporal resolution optical voltage imaging of the upper cortical layers in anesthetized mice. Waves of population activities propagate in heterogeneous directions to coordinate neuronal activities between different brain regions. The complex wave patterns show characteristics of both stereotypy and variety. The location and type of wave patterns determine the dynamical evolution when different waves interact with each other. Local wave patterns of source, sink, or saddle emerge at preferred spatial locations. Specifically, “source” patterns are predominantly found in cortical regions with low multimodal hierarchy such as the primary somatosensory cortex. Our findings reveal principles that govern the spatiotemporal dynamics of spontaneous cortical activities and associate them with the structural architecture across the cortex.SIGNIFICANCE STATEMENT Intrinsic brain activities, as opposed to external stimulus-evoked responses, have increasingly gained attention, but it remains unclear how these intrinsic activities are spatiotemporally organized at the cortex-wide scale. By taking advantage of the high spatiotemporal resolution of optical voltage imaging, we identified five wave pattern types, and revealed the organization properties of different wave patterns and the dynamical mechanisms when they interact with each other. Moreover, we found a relationship between the emergence probability of local wave patterns and the multimodal structure hierarchy across cortical areas. Our findings reveal the principles of spatiotemporal wave dynamics of spontaneous activities and associate them with the underlying hierarchical architecture across the cortex.     

Neural complexity and the spectral slope characterise auditory processing in wakefulness and sleep

Auditory processing and the complexity of neural activity can both indicate residual consciousness levels and differentiate states of arousal. However, how measures of neural signal complexity manifest in neural activity following environmental stimulation and, more generally, how the electrophysiological characteristics of auditory responses change in states of reduced consciousness remain under-explored. Here, we tested the hypothesis that measures of neural complexity and the spectral slope would discriminate stages of sleep and wakefulness not only in baseline electroencephalography (EEG) activity but also in EEG signals following auditory stimulation. High-density EEG was recorded in 21 participants to determine the spatial relationship between these measures and between EEG recorded pre- and post-auditory stimulation. Results showed that the complexity and the spectral slope in the 2–20 Hz range discriminated between sleep stages and had a high correlation in sleep. In wakefulness, complexity was strongly correlated to the 20–40 Hz spectral slope. Auditory stimulation resulted in reduced complexity in sleep compared to the pre-stimulation EEG activity and modulated the spectral slope in wakefulness. These findings confirm our hypothesis that electrophysiological markers of arousal are sensitive to sleep/wake states in EEG activity during baseline and following auditory stimulation. Our results have direct applications to studies using auditory stimulation to probe neural functions in states of reduced consciousness.     

Spectral signatures of mirror movements in the sensori‐motor connectivity in kallmann syndrome

Mirror movements (MM) might be observed in congenital and acquired neurodegenerative conditions but their anatomic‐functional underpinnings are still largely elusive. This study investigated the spectral changes of resting‐state functional connectivity in Kallmann Syndrome (hypogonadotropic hypogonadism with hypo/anosmia with or without congenital MM) searching for insights into the phenomenon of MM. Forty‐four Kallmann syndrome patients (21 with MM) and 24 healthy control subjects underwent task (finger tapping) and resting‐state functional MRI. The spatial pattern of task‐related activations was used to mask regions and select putative motor networks in a spatially independent component analysis of resting‐state signals. For each resting‐state independent component time‐course power spectrum, we extracted the relative contribution of four separate bands: slow‐5 (0.01–0.027 Hz), slow‐4 (0.027–0.073 Hz), slow‐3 (0.073–0.198 Hz), slow‐2 (0.198–0.25 Hz), and analyzed the variance between groups. For the sensorimotor network, the analysis revealed a significant group by frequency interaction (P = 0.002) pointing to a frequency shift in the spectral content among subgroups with lower slow‐5 band and higher slow‐3 band contribution in Kallmann patients with MM versus controls (P = 0.028) and with lower slow‐5 band contribution between patients with and without MM (P = 0.057). In specific regions, as obtained from hand motor activation task analysis, spectral analyses demonstrated a lower slow‐5 band contribution in Kallmann patients with MM versus both controls and patients without MM (P < 0.05). In Kallmann syndrome, the peculiar phenomenon of bimanual synkinesis is associated at rest with regionally and spectrally selective functional connectivity changes pointing to a distinctive cortical and subcortical functional reorganization. Hum Brain Mapp 39:42–53, 2018. © 2017 Wiley Periodicals, Inc.     

Spectral features of central pattern generation in the in vitro brain stem spinal cord preparation of the newborn rat

In the present investigation, brain stem spinal cord preparations of 0–4-day-old rats were used to determine whether inspiratory-related discharges were modulated by a central pattern generator either during baseline conditions or during conditions of increased chemical drive. Spectral analyses were carried out on pairs of nerve activities during superfusion with normal solutions (pH = 7.4) and during superfusion with acidic solutions (pH = 6.8–7.0). Autopower spectra of nerve discharges in normal pH solution revealed the presence of two peaks: one in the 2–6 Hz band and the other in the 20–39 Hz band. Peaks occurring over both frequency ranges were highly correlated as revealed by coherence spectral analysis. Acidic stimulation produced no systematic changes in spectral features, for example, shifting peaks to other frequency regions, or increasing the values of coherence. The 2–6 Hz peak is most likely due to the arrival of depolarizing inputs from the brain stem that generate a ramp of activity at recording sites. On the other hand, activity in the 20–39 Hz region represents the discharge frequency of inspiratory motoneurons. The fact that coherence is present in this latter band provides evidence for short-time scale (ms) synchronization of functionally and anatomically distinct inspiratory motoneurons by a central pattern generator.     

Frequency‐specific neuromodulation of local and distant connectivity in aging and episodic memory function

A growing literature has focused on the brain's ability to augment processing in local regions by recruiting distant communities of neurons in response to neural decline or insult. In particular, both younger and older adult populations recruit bilateral prefrontal cortex (PFC) as a means of compensating for increasing neural effort to maintain successful cognitive function. However, it remains unclear how local changes in neural activity affect the recruitment of this adaptive mechanism. To address this problem, we combined graph theoretical measures from functional MRI with diffusion weighted imaging and repetitive transcranial magnetic stimulation (rTMS) to resolve a central hypothesis: how do aged brains flexibly adapt to local changes in cortical activity? Specifically, we applied neuromodulation to increase or decrease local activity in a cortical region supporting successful memory encoding (left dorsolateral PFC or DLPFC) using 5 or 1 Hz rTMS, respectively. We then assessed a region's local within‐module degree, or the distributed between‐module degree (BMD) between distant cortical communities. We predicted that (1) local stimulation‐related deficits may be counteracted by boosting BMD between bilateral PFC, and that this effect should be (2) positively correlated with structural connectivity. Both predictions were confirmed; 5 Hz rTMS increased local success‐related activity and local increases in PFC connectivity, while 1 Hz rTMS decreases local activity and triggered a more distributed pattern of bilateral PFC connectivity to compensate for this local inhibitory effect. These results provide an integrated, causal explanation for the network interactions associated with successful memory encoding in older adults. Hum Brain Mapp 38:5987–6004, 2017 . © 2017 Wiley Periodicals, Inc.     

Posterior Beta and anterior gamma oscillations predict cognitive insight

Pioneering neuroimaging studies on insight have revealed neural correlates of the emotional "Aha!" component of the insight process, but neural substrates of the cognitive component, such as problem restructuring (a key to transformative reasoning), remain a mystery. Here, multivariate electroencephalogram signals were recorded from human participants while they solved verbal puzzles that could create a small-scale experience of cognitive insight. Individuals responded as soon as they reached a solution and provided a rating of subjective insight. For unsolved puzzles, hints were provided after 60 to 90 sec. Spatio-temporal signatures of brain oscillations were analyzed using Morlet wavelet transform followed by exploratory parallel-factor analysis. A consistent reduction in beta power (15-25 Hz) was found over the parieto-occipital and centro-temporal electrode regions on all four conditions-(a) correct (vs. incorrect) solutions, (b) solutions without (vs. with) external hint, (c) successful (vs. unsuccessful) utilization of the external hint, and d) self-reported high (vs. low) insight. Gamma band (30-70 Hz) power was increased in right fronto-central and frontal electrode regions for conditions (a) and (c). The effects occurred several (up to 8) seconds before the behavioral response. Our findings indicate that insight is represented by distinct spectral, spatial, and temporal patterns of neural activity related to presolution cognitive processes that are intrinsic to the problem itself but not exclusively to one's subjective assessment of insight.     

Frequency-specific altered global signal topography in drug-naïve first-episode patients with adolescent-onset schizophrenia

Adolescent-onset schizophrenia (AOS) is a severe neuropsychiatric disease associated with frequency-specific abnormalities across distributed neural systems in a slow rhythm. Recently, functional magnetic resonance imaging (fMRI) studies have determined that the global signal. (GS) is an important source of the local neuronal activity in 0.01–0.1 Hz frequency band. However, it remains unknown whether the effects follow a specific spatially preferential pattern in different frequency bands in schizophrenia. To address this issue, resting-state fMRI data from 39 drug-naïve AOS patients and 31 healthy controls (HCs) were used to assess the changes in GS topography patterns in the slow-4 (0.027–0.073 Hz) and slow-5 bands (0.01–0.027 Hz). Results revealed that GS mainly affects the default mode network (DMN) in slow-4 and sensory regions in the slow-5 band respectively, and GS has a stronger driving effect in the slow-5 band. Moreover, significant frequency-by-group interaction was observed in the frontoparietal network. Compared with HCs, patients with AOS exhibited altered GS topography mainly located in the DMN. Our findings demonstrated that the influence of the GS on brain networks altered in a frequency-specific way in schizophrenia.