Crossmodal Phase Reset and Evoked Responses Provide Complementary Mechanisms for the Influence of Visual Speech in Auditory Cortex

Natural conversation is multisensory: when we can see the speaker's face, visual speech cues improve our comprehension. The neuronal mechanisms underlying this phenomenon remain unclear. The two main alternatives are visually mediated phase modulation of neuronal oscillations (excitability fluctuations) in auditory neurons and visual input-evoked responses in auditory neurons. Investigating this question using naturalistic audiovisual speech with intracranial recordings in humans of both sexes, we find evidence for both mechanisms. Remarkably, auditory cortical neurons track the temporal dynamics of purely visual speech using the phase of their slow oscillations and phase-related modulations in broadband high-frequency activity. Consistent with known perceptual enhancement effects, the visual phase reset amplifies the cortical representation of concomitant auditory speech. In contrast to this, and in line with earlier reports, visual input reduces the amplitude of evoked responses to concomitant auditory input. We interpret the combination of improved phase tracking and reduced response amplitude as evidence for more efficient and reliable stimulus processing in the presence of congruent auditory and visual speech inputs.SIGNIFICANCE STATEMENT Watching the speaker can facilitate our understanding of what is being said. The mechanisms responsible for this influence of visual cues on the processing of speech remain incompletely understood. We studied these mechanisms by recording the electrical activity of the human brain through electrodes implanted surgically inside the brain. We found that visual inputs can operate by directly activating auditory cortical areas, and also indirectly by modulating the strength of cortical responses to auditory input. Our results help to understand the mechanisms by which the brain merges auditory and visual speech into a unitary perception.

Relationships Between Neuronal Oscillatory Amplitude and Dynamic Functional Connectivity

Event-related fluctuations of neural oscillatory amplitude are reported widely in the context of cognitive processing and are typically interpreted as a marker of brain "activity". However, the precise nature of these effects remains unclear; in particular, whether such fluctuations reflect local dynamics, integration between regions, or both, is unknown. Here, using magnetoencephalography, we show that movement induced oscillatory modulation is associated with transient connectivity between sensorimotor regions. Further, in resting-state data, we demonstrate a significant association between oscillatory modulation and dynamic connectivity. A confound with such empirical measurements is that increased amplitude necessarily means increased signal-to-noise ratio (SNR): this means that the question of whether amplitude and connectivity are genuinely coupled, or whether increased connectivity is observed purely due to increased SNR is unanswered. Here, we counter this problem by analogy with computational models which show that, in the presence of global network coupling and local multistability, the link between oscillatory modulation and long-range connectivity is a natural consequence of neural networks. Our results provide evidence for the notion that connectivity is mediated by neural oscillations, and suggest that time-frequency spectrograms are not merely a description of local synchrony but also reflect fluctuations in long-range connectivity.

Interindividual differences in memory system local field potential activity predict behavioral strategy on a dual-solution T-maze

Individuals can use diverse behavioral strategies to navigate their environment including hippocampal-dependent place strategies reliant upon cognitive maps and striatal-dependent response strategies reliant upon egocentric body turns. The existence of multiple memory systems appears to facilitate successful navigation across a wide range of environmental and physiological conditions. The mechanisms by which these systems interact to ultimately generate a unitary behavioral response, however, remain unclear. We trained 20 male, Sprague-Dawley rats on a dual-solution T-maze while simultaneously recording local field potentials that were targeted to the dorsolateral striatum and dorsal hippocampus. Eight rats spontaneously exhibited a place strategy while the remaining 12 rats exhibited a response strategy. Interindividual differences in behavioral strategy were associated with distinct patterns of LFP activity between the dorsolateral striatum and dorsal hippocampus. Specifically, striatal-hippocampal theta activity was in-phase in response rats and out-of-phase in place rats and response rats exhibited elevated striatal-hippocampal coherence across a wide range of frequency bands. These contrasting striatal-hippocampal activity regimes were (a) present during both maze-learning and a 30 min premaze habituation period and (b) could be used to train support vector machines to reliably predict behavioral strategy. Distinct patterns of neuronal activity across multiple memory systems, therefore, appear to bias behavioral strategy selection and thereby contribute to interindividual differences in behavior.

Dynamic Modulation of Cortical Excitability during Visual Active Sensing

Visual physiology is traditionally investigated by presenting stimuli with gaze held constant. However, during active viewing of a scene, information is actively acquired using systematic patterns of fixations and saccades. Prior studies suggest that during such active viewing, both nonretinal, saccade-related signals and “extra-classical” receptive field inputs modulate visual processing. This study used a set of active viewing tasks that allowed us to compare visual responses with and without direct foveal input, thus isolating the contextual eye movement-related influences. Studying nonhuman primates, we find strong contextual modulation in primary visual cortex (V1): excitability and response amplification immediately after fixation onset, transiting to suppression leading up to the next saccade. Time-frequency decomposition suggests that this amplification and suppression cycle stems from a phase reset of ongoing neuronal oscillatory activity. The impact of saccade-related contextual modulation on stimulus processing makes active visual sensing fundamentally different from the more passive processes investigated in traditional paradigms.

By isolating contextual eye movement-related influences during active vision, Barczak et al. show that eye movements affect excitability in V1 such that responses are amplified immediately after fixation onset and suppressed as the next saccade approaches. This amplification and suppression cycle stems from a phase reset of ambient oscillatory activity in V1.

Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales

Classical and modern ethological studies suggest that animal behavior is organized hierarchically across timescales, such that longer-timescale behaviors are composed of specific shorter-timescale actions. Despite progress relating neuronal dynamics to single-timescale behavior, it remains unclear how different timescale dynamics interact to give rise to such higher-order behavioral organization. Here, we show, in the nematode Caenorhabditis elegans, that a behavioral hierarchy spanning three timescales is implemented by nested neuronal dynamics. At the uppermost hierarchical level, slow neuronal population dynamics spanning brain and motor periphery control two faster motor neuron oscillations, toggling them between different activity states and functional roles. At lower hierarchical levels, these faster oscillations are further nested in a manner that enables flexible behavioral control in an otherwise rigid hierarchical framework. Our findings establish nested neuronal activity patterns as a repeated dynamical motif of the C. elegans nervous system, which together implement a controllable hierarchical organization of behavior.

•

Slow dynamics across brain and motor circuits drive upper-hierarchy motor states

•

Fast dynamics in motor circuits drive lower-hierarchy movements within these states

•

Slower dynamics tightly constrain the state and function of faster ones

•

This rigid hierarchy nevertheless enables flexible behavioral control

Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans

Pain is a complex phenomenon that is served by neural oscillations and connectivity involving different brain areas and frequencies. Here, we aimed to systematically and comprehensively assess the pattern of neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. To this end, we applied 10-min heat pain stimuli consecutively to the right and left hand of 39 healthy participants and recorded electroencephalography. We systematically analyzed global and local measures of oscillatory brain activity, connectivity, and graph theory-based network measures during tonic pain and compared them to a nonpainful control condition. Local measures showed suppressions of oscillatory activity at alpha frequencies together with stronger connectivity at alpha and beta frequencies in sensorimotor areas during tonic pain. Furthermore, sensorimotor areas contralateral to stimulation showed significantly increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies. Together, these observations indicate that the state of tonic experimental pain is associated with a sensorimotor-prefrontal network connected at alpha frequencies. These findings represent a step further toward understanding the brain mechanisms underlying long-lasting pain states in health and disease.

Cellular and Synaptic Dysfunctions in Parkinson's Disease: Stepping out of the Striatum

The basal ganglia (BG) are a collection of interconnected subcortical nuclei that participate in a great variety of functions, ranging from motor programming and execution to procedural learning, cognition, and emotions. This network is also the region primarily affected by the degeneration of midbrain dopaminergic neurons localized in the substantia nigra pars compacta (SNc). This degeneration causes cellular and synaptic dysfunctions in the BG network, which are responsible for the appearance of the motor symptoms of Parkinson’s disease. Dopamine (DA) modulation and the consequences of its loss on the striatal microcircuit have been extensively studied, and because of the discrete nature of DA innervation of other BG nuclei, its action outside the striatum has been considered negligible. However, there is a growing body of evidence supporting functional extrastriatal DA modulation of both cellular excitability and synaptic transmission. In this review, the functional relevance of DA modulation outside the striatum in both normal and pathological conditions will be discussed.

Exploring the Phase-Locking Mechanisms Yielding Delayed and Anticipated Synchronization in Neuronal Circuits

Synchronization is one of the brain mechanisms allowing the coordination of neuronal activity required in many cognitive tasks. Anticipated Synchronization (AS) is a specific type of out-of-phase synchronization that occurs when two systems are unidirectionally coupled and, consequently, the information is transmitted from the sender to the receiver, but the receiver leads the sender in time. It has been shown that the primate cortex could operate in a regime of AS as part of normal neurocognitive function. However it is still unclear what is the mechanism that gives rise to anticipated synchronization in neuronal motifs. Here, we investigate the synchronization properties of cortical motifs on multiple scales and show that the internal dynamics of the receiver, which is related to its free running frequency in the uncoupled situation, is the main ingredient for AS to occur. For biologically plausible parameters, including excitation/inhibition balance, we found that the phase difference between the sender and the receiver decreases when the free running frequency of the receiver increases. As a consequence, the system switches from the usual delayed synchronization (DS) regime to an AS regime. We show that at three different scales, neuronal microcircuits, spiking neuronal populations and neural mass models, both the inhibitory loop and the external current acting on the receiver mediate the DS-AS transition for the sender-receiver configuration by changing the free running frequency of the receiver. Therefore, we propose that a faster internal dynamics of the receiver system is the main mechanism underlying anticipated synchronization in brain circuits.

Longitudinal Recordings Reveal Transient Increase of Alpha/Low-Beta Power in the Subthalamic Nucleus Associated With the Onset of Parkinsonian Rest Tremor

Functional magnetic resonance imaging studies suggest that different subcortico-cortical circuits control different aspects of Parkinsonian rest tremor. The basal ganglia were proposed to drive tremor onset, and the cerebellum was suggested to be responsible for tremor maintenance (“dimmer-switch” hypothesis). Although several electrophysiological correlates of tremor have been described, it is currently unclear whether any of these is specific to tremor onset or maintenance. In this study, we present data from a single patient measured repeatedly within 2 years after implantation of a deep brain stimulation (DBS) system capable of recording brain activity from the target. Local field potentials (LFPs) from the subthalamic nucleus and the scalp electroencephalogram were recorded 1 week, 3 months, 6 months, 1 year, and 2 years after surgery. Importantly, the patient suffered from severe rest tremor of the lower limbs, which could be interrupted voluntarily by repositioning the feet. This provided the unique opportunity to record many tremor onsets in succession. We found that tremor onset and tremor maintenance were characterized by distinct modulations of subthalamic oscillations. Alpha/low-beta power increased transiently immediately after tremor onset. In contrast, beta power was continuously suppressed during tremor maintenance. Tremor maintenance was additionally associated with subthalamic and cortical power increases around individual tremor frequency. To our knowledge, this is the first evidence of distinct subthalamic LFP modulations in tremor onset and tremor maintenance. Our observations suggest the existence of an acceleration signal for Parkinsonian rest tremor in the basal ganglia, in line with the “dimmer-switch” hypothesis.

Toward direct MRI of neuro-electro-magnetic oscillations in the human brain

PURPOSE

Neuroimaging techniques are widely used to investigate the function of the human brain, but none are currently able to accurately localize neuronal activity with both high spatial and temporal specificity. Here, a new in vivo MRI acquisition and analysis technique based on the spin-lock mechanism is developed to noninvasively image local magnetic field oscillations resulting from neuroelectric activity in specifiable frequency bands.

METHODS

Simulations, phantom experiments, and in vivo experiments using an eyes-open/eyes-closed task in 8 healthy volunteers were performed to demonstrate its sensitivity and specificity for detecting oscillatory neuroelectric activity in the alpha-band (8-12 Hz). A comprehensive postprocessing procedure was designed to enhance the neuroelectric signal, while minimizing any residual hemodynamic and physiological confounds.

RESULTS

The phantom results show that this technique can detect 0.06-nT magnetic field oscillations, while the in vivo results demonstrate that it can image task-based modulations of neuroelectric oscillatory activity in the alpha-band. Multiple control experiments and a comparison with conventional BOLD functional MRI suggest that the activation was likely not due to any residual hemodynamic or physiological confounds.

CONCLUSION

These initial results provide evidence suggesting that this new technique has the potential to noninvasively and directly image neuroelectric activity in the human brain in vivo. With further development, this approach offers the promise of being able to do so with a combination of spatial and temporal specificity that is beyond what can be achieved with existing neuroimaging methods, which can advance our ability to study the functions and dysfunctions of the human brain.

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.

Mice With Decreased Number of Interneurons Exhibit Aberrant Spontaneous and Oscillatory Activity in the Cortex

GABAergic (γ-aminobutyric acid) neurons are inhibitory neurons and protect neural tissue from excessive excitation. Cortical GABAergic neurons play a pivotal role for the generation of synchronized cortical network oscillations. Imbalance between excitatory and inhibitory mechanisms underlies many neuropsychiatric disorders and is correlated with abnormalities in oscillatory activity, especially in the gamma frequency range (30–80 Hz). We investigated the functional changes in cortical network activity in response to developmentally reduced inhibition in the adult mouse barrel cortex (BC). We used a mouse model that displays ∼50% fewer cortical interneurons due to the loss of Rac1 protein from Nkx2.1/Cre-expressing cells [Rac1 conditional knockout (cKO) mice], to examine how this developmental loss of cortical interneurons may affect basal synaptic transmission, synaptic plasticity, spontaneous activity, and neuronal oscillations in the adult BC. The decrease in the number of interneurons increased basal synaptic transmission, as examined by recording field excitatory postsynaptic potentials (fEPSPs) from layer II networks in the Rac1 cKO mouse cortex, decreased long-term potentiation (LTP) in response to tetanic stimulation but did not alter the pair-pulse ratio (PPR). Furthermore, under spontaneous recording conditions, Rac1 cKO brain slices exhibit enhanced sensitivity and susceptibility to emergent spontaneous activity. We also find that this developmental decrease in the number of cortical interneurons results in local neuronal networks with alterations in neuronal oscillations, exhibiting decreased power in low frequencies (delta, theta, alpha) and gamma frequency range (30–80 Hz) with an extra aberrant peak in high gamma frequency range (80–150 Hz). Therefore, our data show that disruption in GABAergic inhibition alters synaptic properties and plasticity, while it additionally disrupts the cortical neuronal synchronization in the adult BC.

State-Dependent Memory: Neurobiological Advances and Prospects for Translation to Dissociative Amnesia

In susceptible individuals, overwhelming traumatic stress often results in severe abnormalities of memory processing, manifested either as the uncontrollable emergence of memories (flashbacks) or as an inability to remember events (dissociative amnesia, DA) that are usually, but not necessarily, related to the stressful experience. These memory abnormalities are often the source of debilitating psychopathologies such as anxiety, depression and social dysfunction. The question of why memory for some traumatic experiences is compromised while other comparably traumatic experiences are remembered perfectly well, both within and across individuals, has puzzled clinicians for decades. In this article, we present clinical, cognitive, and neurobiological perspectives on memory research relevant to DA. In particular, we examine the role of state dependent memory (wherein memories are difficult to recall unless the conditions at encoding and recall are similar), and discuss how advances in the neurobiology of state-dependent memory (SDM) gleaned from animal studies might be translated to humans.

Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance

Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift toward the less volatile sub-critical state. To test these ideas, we recorded electroencephalography (EEG) from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that 'resting-state criticality' of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity.

Nucleus Basalis of Meynert Stimulation for Dementia: Theoretical and Technical Considerations

Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation's effectiveness in real time. In this article, we propose a methodology to address these issues in an effort to effectively interface with this powerful cognitive nucleus for the treatment of dementia. Specifically, we propose the use of diffusion tensor imaging to identify the nucleus and its tracts, quantitative electroencephalography (QEEG) to identify the physiologic response to stimulation during programming, and investigation of stimulation parameters that incorporate the phase locking and cross frequency coupling of gamma and slower oscillations characteristic of the NBM's innate physiology. We propose that modulating the baseline gamma burst stimulation frequency, specifically with a slower rhythm such as theta or delta will pose more effective coupling between NBM and different cortical regions involved in many learning processes.

Oscillatory Activity in the Cortex, Motor Thalamus and Nucleus Reticularis Thalami in Acute TTX and Chronic 6-OHDA Dopamine-Depleted Animals

The motor thalamus (MTh) and the nucleus reticularis thalami (NRT) have been largely neglected in Parkinson's disease (PD) research, despite their key role as interface between basal ganglia (BG) and cortex (Cx). In the present study, we investigated the oscillatory activity within the Cx, MTh, and NRT, in normal and different dopamine (DA)-deficient states. We performed our experiments in both acute and chronic DA-denervated rats by injecting into the medial forebrain bundle (MFB) tetrodotoxin (TTX) or 6-hydroxydopamine (6-OHDA), respectively. Interestingly, almost all the electroencephalogram (EEG) frequency bands changed in acute and/or chronic DA depletion, suggesting alteration of all oscillatory activities and not of a specific band. Overall, δ (2-4 Hz) and θ (4-8 Hz) band decreased in NRT and Cx in acute and chronic state, whilst, α (8-13 Hz) band decreased in acute and chronic states in the MTh and NRT but not in the Cx. The β (13-40 Hz) and γ (60-90 Hz) bands were enhanced in the Cx. In the NRT the β bands decreased, except for high-β (Hβ, 25-30 Hz) that increased in acute state. In the MTh, Lβ and Hβ decreased in acute DA depletion state and γ decreased in both TTX and 6-OHDA-treated animals. These results confirm that abnormal cortical β band are present in the established DA deficiency and it might be considered a hallmark of PD. The abnormal oscillatory activity in frequency interval of other bands, in particular the dampening of low frequencies in thalamic stations, in both states of DA depletion might also underlie PD motor and non-motor symptoms. Our data highlighted the effects of acute depletion of DA and the strict interplay in the oscillatory activity between the MTh and NRT in both acute and chronic stage of DA depletion. Moreover, our findings emphasize early alterations in the NRT, a crucial station for thalamic information processing.

Transcranial alternating current stimulation modulates auditory temporal resolution in elderly people

Recent research provides evidence for a functional role of brain oscillations for perception. For example, auditory temporal resolution seems to be linked to individual gamma frequency of auditory cortex. Individual gamma frequency not only correlates with performance in between-channel gap detection tasks but can be modulated via auditory transcranial alternating current stimulation. Modulation of individual gamma frequency is accompanied by an improvement in gap detection performance. Aging changes electrophysiological frequency components and sensory processing mechanisms. Therefore, we conducted a study to investigate the link between individual gamma frequency and gap detection performance in elderly people using auditory transcranial alternating current stimulation. In a within-subject design, twelve participants were electrically stimulated with two individualized transcranial alternating current stimulation frequencies: 3 Hz above their individual gamma frequency (experimental condition) and 4 Hz below their individual gamma frequency (control condition), while they were performing a between-channel gap detection task. As expected, individual gamma frequencies correlated significantly with gap detection performance at baseline and in the experimental condition, transcranial alternating current stimulation modulated gap detection performance. In the control condition, stimulation did not modulate gap detection performance. In addition, in elderly, the effect of transcranial alternating current stimulation on auditory temporal resolution seems to be dependent on endogenous frequencies in auditory cortex: Elderlies with slower individual gamma frequencies and lower auditory temporal resolution profit from auditory transcranial alternating current stimulation and show increased gap detection performance during stimulation. Our results strongly suggest individualized transcranial alternating current stimulation protocols for successful modulation of performance.

Time Course of Brain Network Reconfiguration Supporting Inhibitory Control

Hemodynamic research has recently clarified key nodes and links in brain networks implementing inhibitory control. Although fMRI methods are optimized for identifying the structure of brain networks, the relatively slow temporal course of fMRI limits the ability to characterize network operation. The latter is crucial for developing a mechanistic understanding of how brain networks shift dynamically to support inhibitory control. To address this critical gap, we applied spectrally resolved Granger causality (GC) and random forest machine learning tools to human EEG data in two large samples of adults (test sample n = 96, replication sample n = 237, total N = 333, both sexes) who performed a color-word Stroop task. Time-frequency analysis confirmed that recruitment of inhibitory control accompanied by slower behavioral responses was related to changes in theta and alpha/beta power. GC analyses revealed directionally asymmetric exchanges within frontal and between frontal and parietal brain areas: top-down influence of superior frontal gyrus (SFG) over both dorsal ACC (dACC) and inferior frontal gyrus (IFG), dACC control over middle frontal gyrus (MFG), and frontal-parietal exchanges (IFG, precuneus, MFG). Predictive analytics confirmed a combination of behavioral and brain-derived variables as the best set of predictors of inhibitory control demands, with SFG theta bearing higher classification importance than dACC theta and posterior beta tracking the onset of behavioral response. The present results provide mechanistic insight into the biological implementation of a psychological phenomenon: inhibitory control is implemented by dynamic routing processes during which the target response is upregulated via theta-mediated effective connectivity within key PFC nodes and via beta-mediated motor preparation.SIGNIFICANCE STATEMENT Hemodynamic neuroimaging research has recently clarified regional structures in brain networks supporting inhibitory control. However, due to inherent methodological constraints, much of this research has been unable to characterize the temporal dynamics of such networks (e.g., direction of information flow between nodes). Guided by fMRI research identifying the structure of brain networks supporting inhibitory control, results of EEG source analysis in a test sample (n = 96) and replication sample (n = 237) using effective connectivity and predictive analytics strategies advance a model of inhibitory control by characterizing the precise temporal dynamics by which this network operates and exemplify an approach by which mechanistic models can be developed for other key psychological processes.

The Subthalamic Nucleus: Unravelling New Roles and Mechanisms in the Control of Action

How do we decide what we do? This is the essence of action control, the process of selecting the most appropriate response among multiple possible choices. Suboptimal action control can involve a failure to initiate or adapt actions, or conversely it can involve making actions impulsively. There has been an increasing focus on the specific role of the subthalamic nucleus (STN) in action control. This has been fueled by the clinical relevance of this basal ganglia nucleus as a target for deep brain stimulation (DBS), primarily in Parkinson's disease but also in obsessive-compulsive disorder. The context of DBS has opened windows to study STN function in ways that link neuroscientific and clinical fields closely together, contributing to an exceptionally high level of two-way translation. In this review, we first outline the role of the STN in both motor and nonmotor action control, and then discuss how these functions might be implemented by neuronal activity in the STN. Gaining a better understanding of these topics will not only provide important insights into the neurophysiology of action control but also the pathophysiological mechanisms relevant for several brain disorders and their therapies.

Targeting Heterogeneous Findings in Neuronal Oscillations in Tinnitus: Analyzing MEG Novices and Mental Health Comorbidities

Tinnitus is a prevalent phenomenon and bothersome for people affected by it. Its occurrence and maintenance have a clear neuroscientific tie and one aspect are differences in the neuronal oscillatory pattern, especially in auditory cortical areas. As studies in this field come to different results, the aim of this study was to analyze a large number of participants to achieve more stable results. Furthermore, we expanded our analysis to two variables of potential influence, namely being a novice to neuroscientific measurements and the exclusion of psychological comorbidities. Oscillatory brain activity of 88 subjects (46 with a chronic tinnitus percept, 42 without) measured in resting state by MEG was investigated. In the analysis based on the whole group, in sensor space increased activity in the delta frequency band was found in tinnitus patients. Analyzing the subgroup of novices, a significant difference in the theta band emerged additionally to the delta band difference (sensor space). Localizing the origin of the activity, we found a difference in theta and gamma band for the auditory regions for the whole group and the same significant difference in the subgroup of novices. However, no differences in oscillatory activity were observed between tinnitus and control groups once subjects with mental health comorbidity were excluded. Against the background of previous studies, the study at hand underlines the fragility of the results in the field of neuronal cortical oscillations in tinnitus. It supports the body of research arguing for low frequency oscillations and gamma band activity as markers associated with tinnitus.

Neuronal oscillations on an ultra-slow timescale: daily rhythms in electrical activity and gene expression in the mammalian master circadian clockwork

Neuronal oscillations of the brain, such as those observed in the cortices and hippocampi of behaving animals and humans, span across wide frequency bands, from slow delta waves (0.1 Hz) to ultra-fast ripples (600 Hz). Here, we focus on ultra-slow neuronal oscillators in the hypothalamic suprachiasmatic nuclei (SCN), the master daily clock that operates on interlocking transcription-translation feedback loops to produce circadian rhythms in clock gene expression with a period of near 24 h (< 0.001 Hz). This intracellular molecular clock interacts with the cell's membrane through poorly understood mechanisms to drive the daily pattern in the electrical excitability of SCN neurons, exhibiting an up-state during the day and a down-state at night. In turn, the membrane activity feeds back to regulate the oscillatory activity of clock gene programs. In this review, we emphasise the circadian processes that drive daily electrical oscillations in SCN neurons, and highlight how mathematical modelling contributes to our increasing understanding of circadian rhythm generation, synchronisation and communication within this hypothalamic region and across other brain circuits.

Oscillatory Brain Responses Reflect Anticipation during Comprehension of Speech Acts in Spoken Dialog

Everyday conversation requires listeners to quickly recognize verbal actions, so-called speech acts, from the underspecified linguistic code and prepare a relevant response within the tight time constraints of turn-taking. The goal of this study was to determine the time-course of speech act recognition by investigating oscillatory EEG activity during comprehension of spoken dialog. Participants listened to short, spoken dialogs with target utterances that delivered three distinct speech acts (Answers, Declinations, Pre-offers). The targets were identical across conditions at lexico-syntactic and phonetic/prosodic levels but differed in the pragmatic interpretation of the speech act performed. Speech act comprehension was associated with reduced power in the alpha/beta bands just prior to Declination speech acts, relative to Answers and Pre-offers. In addition, we observed reduced power in the theta band during the beginning of Declinations, relative to Answers. Based on the role of alpha and beta desynchronization in anticipatory processes, the results are taken to indicate that anticipation plays a role in speech act recognition. Anticipation of speech acts could be critical for efficient turn-taking, allowing interactants to quickly recognize speech acts and respond within the tight time frame characteristic of conversation. The results show that anticipatory processes can be triggered by the characteristics of the interaction, including the speech act type.

Sleep-Dependent Memory Consolidation and Incremental Sentence Comprehension: Computational Dependencies during Language Learning as Revealed by Neuronal Oscillations

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when) and the establishment of semantic schemas of unordered items (the what) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain.

Disparate Effects of Lithium and a GSK-3 Inhibitor on Neuronal Oscillatory Activity in Prefrontal Cortex and Hippocampus

Glycogen synthase kinase-3 (GSK-3) plays a critical role in cognitive dysfunction associated with Alzheimer’s disease (AD), yet the mechanism by which GSK-3 alters cognitive processes in other disorders, such as schizophrenia, remains unknown. In the present study, we demonstrated a role for GSK-3 in the direct regulation of neuronal oscillations in hippocampus (HIP) and prelimbic cortex (PL). A comparison of the GSK-3 inhibitors SB 216763 and lithium demonstrated disparate effects of the drugs on spatial memory and neural oscillatory activity in HIP and PL. SB 216763 administration improved spatial memory whereas lithium treatment had no effect. Analysis of neuronal local field potentials in anesthetized animals revealed that whereas both repeated SB 216763 (2.5 mg/kg) and lithium (100 mg/kg) induced a theta frequency spike in HIP at approximately 10 Hz, only SB 216763 treatment induced an overall increase in theta power (4–12 Hz) compared to vehicle. Acute administration of either drug suppressed slow (32–59 Hz) and fast (61–100 Hz) gamma power. In PL, both drugs induced an increase in theta power. Repeated SB 216763 increased HIP–PL coherence across all frequencies except delta, whereas lithium selectively suppressed delta coherence. These findings demonstrate that GSK-3 plays a direct role in the regulation of theta oscillations in regions critically involved in cognition, and highlight a potential mechanism by which GSK-3 may contribute to cognitive decline in disorders of cognitive dysfunction.

Mnemonic and attentional roles for states of attenuated alpha oscillations in perceptual working memory: a review

Alpha oscillations are often reported to be amplified during working memory (WM) retention, serving to disengage sensory areas to protect internal representations from external interference. At the same time, contemporary views of WM postulate that sensory areas may often also be recruited for retention. I here review recent evidence that during such 'perceptual' WM, alpha oscillations in mnemonically relevant sensory areas are not amplified but attenuated instead. I will argue that such attenuated alpha states serve a mnemonic role and, further, that larger attenuation may support item-specific attentional prioritisation within perceptual WM. In critically evaluating this role, I also consider (and argue against) four alternatives to a strictly mnemonic account of the available data that may also prove useful to consider in future research. Finally, I highlight key implications of these data for the study of WM and for our understanding of the functional roles of states of attenuated alpha oscillations in cognition.