For things needing your attention: the role of neocortical gamma in sensory perception

Entrainment by transcranial alternating current stimulation: Insights from models of cortical oscillations and dynamical systems theory

Signature of neuronal oscillations can be found in nearly every brain function. However, abnormal oscillatory activity is linked with several brain disorders. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that can potentially modulate neuronal oscillations and influence behavior both in health and disease. Yet, a complete understanding of how interacting networks of neurons are affected by tACS remains elusive. Entrainment effects by which tACS synchronizes neuronal oscillations is one of the main hypothesized mechanisms, as evidenced in animals and humans. Computational models of cortical oscillations may shed light on the entrainment effects of tACS, but current modeling studies lack specific guidelines to inform experimental investigations. This study addresses the existing gap in understanding the mechanisms of tACS effects on rhythmogenesis within the brain by providing a comprehensive overview of both theoretical and experimental perspectives. We explore the intricate interactions between oscillators and periodic stimulation through the lens of dynamical systems theory. Subsequently, we present a synthesis of experimental findings that demonstrate the effects of tACS on both individual neurons and collective oscillatory patterns in animal models and humans. Our review extends to computational investigations that elucidate the interplay between tACS and neuronal dynamics across diverse cortical network models. To illustrate these concepts, we conclude with a simple oscillatory neuron model, showcasing how fundamental theories of oscillatory behavior derived from dynamical systems, such as phase response of neurons to external perturbation, can account for the entrainment effects observed with tACS. Studies reviewed here render the necessity of integrated experimental and computational approaches for effective neuromodulation by tACS in health and disease.

Arousal effects on oscillatory dynamics in the non-human primate brain

Arousal states are thought to influence many aspects of cognition and behavior by broadly modulating neural activity. Many studies have observed arousal-related modulations of alpha (~8 to 15 Hz) and gamma (~30 to 50 Hz) power and coherence in local field potentials across relatively small groups of brain regions. However, the global pattern of arousal-related oscillatory modulation in local field potentials is yet to be fully elucidated. We simultaneously recorded local field potentials in numerous cortical and subcortical regions in the primate brain and assessed oscillatory activity and inter-regional coherence associated with arousal state. In high arousal states, we found a uniquely strong and coherent gamma oscillation between the amygdala and basal forebrain. In low arousal rest-like states, a relative increase in coherence at alpha frequencies was present across sampled brain regions, with the notable exception of the medial temporal lobe. We consider how these patterns of activity may index arousal-related brain states that support the processing of incoming sensory stimuli during high arousal states and memory-related functions during rest.

Mindfulness meditation is associated with global EEG spectral changes in theta, alpha, and beta amplitudes

Mindfulness meditation is linked to a broad range of psychological and physical health benefits, potentially mediated by changes in neural oscillations. This study explored changes in neural oscillations associated with both immediate and regular mindfulness meditation practice. Electroencephalographic (EEG) data were collected from 40 healthy young adults (Mage = 20.8, 24 females) during eyes-closed resting and mindfulness meditation states in two separate recording sessions, six weeks apart. Participants were novice meditators, and following the first recording session, were randomly assigned to either a daily mindfulness meditation practice or classical music listening as an active control, which they completed until the second recording session. Traditional bands of delta (1.0-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), beta (13.5-30.0 Hz), and gamma (30.5-45.0 Hz) were used to explore changes in global EEG spectral amplitude. A significant increase in theta between sessions was observed in both groups and states. Alpha decreased significantly during meditation compared with rest, and a three-way interaction indicated a smaller reduction during meditation between sessions in the mindfulness group. There was a similar interaction in beta, which remained stable between sessions during both rest and meditation in the mindfulness group while varying in the classical music listening group. No significant effects were observed in global delta or gamma amplitudes. These findings suggest that changes in neural oscillations associated with breath-focused mindfulness meditation may be related to processes underlying attention and awareness. Further research is necessary to consolidate these findings, particularly in relation to the associated health benefits.

Resting-state frontal electroencephalography (EEG) biomarkers for detecting the severity of chronic neuropathic pain

Increasing evidence is present to enable pain measurement by using frontal channel EEG-based signals with spectral analysis and phase-amplitude coupling. To identify frontal channel EEG-based biomarkers for quantifying pain severity, we investigated band-power features to more complex features and employed various machine learning algorithms to assess the viability of these features. We utilized a public EEG dataset obtained from 36 patients with chronic pain during an eyes-open resting state and performed correlation analysis between clinically labelled pain scores and EEG features from Fp1 and Fp2 channels (EEG band-powers, phase-amplitude couplings (PAC), and its asymmetry features). We also conducted regression analysis with various machine learning models to predict patients' pain intensity. All the possible feature sets combined with five machine learning models (Linear Regression, random forest and support vector regression with linear, non-linear and polynomial kernels) were intensively checked, and regression performances were measured by adjusted R-squared value. We found significant correlations between beta power asymmetry (r = -0.375), gamma power asymmetry (r = -0.433) and low beta to low gamma coupling (r = -0.397) with pain scores while band power features did not show meaningful results. In the regression analysis, Support Vector Regression with a polynomial kernel showed the best performance (R squared value = 0.655), enabling the regression of pain intensity within a clinically usable error range. We identified the four most selected features (gamma power asymmetry, PAC asymmetry of theta to low gamma, low beta to low/high gamma). This study addressed the importance of complex features such as asymmetry and phase-amplitude coupling in pain research and demonstrated the feasibility of objectively observing pain intensity using the frontal channel-based EEG, that are clinically crucial for early intervention.

Neocortical inhibitory imbalance predicts successful sensory detection

Perceptual success depends on fast-spiking, parvalbumin-positive interneurons (FS/PVs). However, competing theories of optimal rate and correlation in pyramidal (PYR) firing make opposing predictions regarding the underlying FS/PV dynamics. We addressed this with population calcium imaging of FS/PVs and putative PYR neurons during threshold detection. In primary somatosensory and visual neocortex, a distinct PYR subset shows increased rate and spike-count correlations on detected trials ("hits"), while most show no rate change and decreased correlations. A larger fraction of FS/PVs predicts hits with either rate increases or decreases. Using computational modeling, we found that inhibitory imbalance, created by excitatory "feedback" and interactions between FS/PV pools, can account for the data. Rate-decreasing FS/PVs increase rate and correlation in a PYR subset, while rate-increasing FS/PVs reduce correlations and offset enhanced excitation in PYR neurons. These findings indicate that selection of informative PYR ensembles, through transient inhibitory imbalance, is a common motif of optimal neocortical processing.

A Novel Approach to Study Coherent γ-Band Oscillations in Hippocampal Brain Sections

γ-Band oscillations (GBOs) are generated by fast-spiking interneurons (FSIs) and are critical for cognitive functions. Abnormalities in GBOs are frequently observed in schizophrenia and bipolar disorder and are strongly correlated with cognitive impairment. However, the underlying mechanisms are poorly understood. Studying GBOs in ex vivo preparations is challenging because of high energy demands and the need for continuous oxygen delivery to the tissue. As a result, GBOs are typically studied in brain tissue from very young animals or in experimental setups that maximize oxygen supply but compromise spatial resolution. Thus, there is a limited understanding of how GBOs interact within and between different brain structures and in brain tissue from mature animals. To address these limitations, we have developed a novel approach for studying GBOs in ex vivo hippocampal slices from mature animals, using 60-channel, perforated microelectrode arrays (pMEAs). pMEAs enhance oxygen delivery and increase spatial resolution in electrophysiological recordings, enabling comprehensive analyses of GBO synchronization within discrete brain structures. We found that transecting the Schaffer collaterals, a neural pathway within the hippocampus, impairs GBO coherence between CA1 and CA3 subfields. Furthermore, we validated our approach by studying GBO coherence in an Ank3 mutant mouse model exhibiting inhibitory synaptic dysfunction. We discovered that GBO coherence remains intact in the CA3 subfield of these mutant mice but is impaired within and between the CA1 subfield. Overall, our approach offers significant potential to characterize GBOs in ex vivo brain sections of animal models, enhancing our understanding of network dysfunction in psychiatric disorders.

Dynamic attention signalling in V4: Relation to fast-spiking/non-fast-spiking cell class and population coupling

The computational role of a neuron during attention depends on its firing properties, neurotransmitter expression and functional connectivity. Neurons in the visual cortical area V4 are reliably engaged by selective attention but exhibit diversity in the effect of attention on firing rates and correlated variability. It remains unclear what specific neuronal properties shape these attention effects. In this study, we quantitatively characterised the distribution of attention modulation of firing rates across populations of V4 neurons. Neurons exhibited a continuum of time-varying attention effects. At one end of the continuum, neurons' spontaneous firing rates were slightly depressed with attention (compared to when unattended), whereas their stimulus responses were enhanced with attention. The other end of the continuum showed the converse pattern: attention depressed stimulus responses but increased spontaneous activity. We tested whether the particular pattern of time-varying attention effects that a neuron exhibited was related to the shape of their actions potentials (so-called 'fast-spiking' [FS] neurons have been linked to inhibition) and the strength of their coupling to the overall population. We found an interdependence among neural attention effects, neuron type and population coupling. In particular, we found neurons for which attention enhanced spontaneous activity but suppressed stimulus responses were less likely to be fast-spiking (more likely to be non-fast-spiking) and tended to have stronger population coupling, compared to neurons with other types of attention effects. These results add important information to our understanding of visual attention circuits at the cellular level.

Layer- and cell-type-specific differences in neural activity in mouse barrel cortex during a whisker detection task

To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.

Effects of optogenetic inhibition of a small fraction of parvalbumin-positive interneurons on the representation of sensory stimuli in mouse barrel cortex

Inhibitory interneurons play central roles in the modulation of spontaneous network activity and in processing of neuronal information. In sensory neocortical areas, parvalbumin-positive (PV+) GABAergic interneurons control the representation and processing of peripheral sensory inputs. We studied the functional role of PV+ interneurons in the barrel cortex of anesthetized adult PVCre mice by combining extracellular multi-electrode recordings with optogenetic silencing of a small fraction of PV+ interneurons. In all cortical layers, optogenetic inhibition caused an increase in spontaneous network activity from theta to gamma frequencies. The spatio-temporal representation of sensory inputs was studied by stimulating one or two whiskers at different intervals and analyzing the resulting local field potential (LFP) and single unit (SU) response. Silencing PV+ interneurons caused an increase in LFP response to sensory stimulation and a decrease in temporal discrimination of consecutive whisker deflections. The combined effect of whisker deflection and optogenetic inhibition was highly similar to the linear sum of the individual effects of these two manipulations. SU recordings revealed that optogenetic silencing reduced stimulus detectability by increasing stimulus-evoked firing rate by a constant offset, suggesting that PV+ interneurons improve signal-to-noise ratio by reducing ongoing spiking activity, thereby sharpening the spatio-temporal representation of sensory stimuli.

Synaptic alterations in visual cortex reshape contrast-dependent gamma oscillations and inhibition-excitation ratio in a genetic mouse model of migraine

Background

Migraine affects a significant fraction of the world population, yet its etiology is not completely understood. In vitro results highlighted thalamocortical and intra-cortical glutamatergic synaptic gain-of-function associated with a monogenic form of migraine (familial-hemiplegic-migraine-type-1: FHM1). However, how these alterations reverberate on cortical activity remains unclear. As altered responsivity to visual stimuli and abnormal processing of visual sensory information are common hallmarks of migraine, herein we investigated the effects of FHM1-driven synaptic alterations in the visual cortex of awake mice.

Methods

We recorded extracellular field potentials from the primary visual cortex (V1) of head-fixed awake FHM1 knock-in (n = 12) and wild type (n = 12) mice in response to square-wave gratings with different visual contrasts. Additionally, we reproduced in silico the obtained experimental results with a novel spiking neurons network model of mouse V1, by implementing in the model both the synaptic alterations characterizing the FHM1 genetic mouse model adopted.

Results

FHM1 mice displayed similar amplitude but slower temporal evolution of visual evoked potentials. Visual contrast stimuli induced a lower increase of multi-unit activity in FHM1 mice, while the amount of information content about contrast level remained, however, similar to WT.

Spectral analysis of the local field potentials revealed an increase in the β/low γ range of WT mice following the abrupt reversal of contrast gratings. Such frequency range transitioned to the high γ range in FHM1 mice. Despite this change in the encoding channel, these oscillations preserved the amount of information conveyed about visual contrast. The computational model showed how these network effects may arise from a combination of changes in thalamocortical and intra-cortical synaptic transmission, with the former inducing a lower cortical activity and the latter inducing the higher frequencies ɣ oscillations.

Conclusions

Contrast-driven ɣ modulation in V1 activity occurs at a much higher frequency in FHM1. This is likely to play a role in the altered processing of visual information. Computational studies suggest that this shift is specifically due to enhanced cortical excitatory transmission. Our network model can help to shed light on the relationship between cellular and network levels of migraine neural alterations.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-022-01495-9.

Upstream γ-synchronization enhances odor processing in downstream neurons

γ-oscillatory activity is ubiquitous across brain areas. Numerous studies have suggested that γ-synchrony is likely to enhance the transmission of sensory information. However, direct causal evidence is still lacking. Here, we test this hypothesis in the mouse olfactory system, where local GABAergic granule cells (GCs) in the olfactory bulb shape mitral/tufted cell (MTC) excitatory output from the olfactory bulb. By optogenetically modulating GC activity, we successfully dissociate MTC γ-synchronization from its firing rates. Recording of odor responses in downstream piriform cortex neurons shows that increasing MTC γ-synchronization enhances cortical neuron odor-evoked firing rates, reduces response variability, and improves odor ensemble representation. These gains occur despite a reduction in MTC firing rates. Furthermore, reducing MTC γ-synchronization without changing the MTC firing rates, by suppressing GC activity, degrades piriform cortex odor-evoked responses. These findings provide causal evidence that increased γ-synchronization enhances the transmission of sensory information between two brain regions.

Neuronal oscillations and the mouse prefrontal cortex

The mouse prefrontal cortex (PFC) encompasses a collection of agranual brain regions in the rostral neocortex and is considered to be critically involved in the neuronal computations underlying intentional behaviors. Flexible behavioral responses demand coordinated integration of sensory inputs with state, goal and memory information in brain-wide neuronal networks. Neuronal oscillations are proposed to provide a temporal scaffold for coordination of neuronal network activity and routing of information. In the present book chapter, we review findings on the role neuronal oscillations in prefrontal functioning, with a specific focus on research in mice. We discuss discoveries pertaining to local prefrontal processing, as well to interactions with other brain regions. We also discuss how the recent discovery of brain-wide respiration-entrained rhythms (RR) warrant re-evaluation of certain findings on slow oscillations (<10Hz) in prefrontal functioning.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback

This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

Persistent Gamma Spiking in SI Nonsensory Fast Spiking Cells Predicts Perceptual Success

Gamma oscillations (30-55 Hz) are hypothesized to temporally coordinate sensory encoding, enabling perception. However, fast spiking interneurons (FS), key gamma generators, can be highly sensory responsive, as is the gamma band local field potential (LFP). How can FS-mediated gamma act as an impartial temporal reference for sensory encoding, when the sensory drive itself presumably perturbs the pre-established rhythm? Combining tetrode recording in SI barrel cortex with controlled psychophysics, we found a unique FS subtype that was not sensory responsive and spiked regularly at gamma range intervals (gamma regular nonsensory FS [grnsFS]). Successful detection was predicted by a further increase in gamma regular spiking of grnsFS, persisting from before to after sensory onset. In contrast, broadband LFP power, including gamma, negatively predicted detection and did not cohere with gamma band spiking by grnsFS. These results suggest that a distinct FS subtype mediates perceptually relevant oscillations, independent of the LFP and sensory drive.

LTD-like plasticity of the human primary motor cortex can be reversed by γ-tACS

BACKGROUND

Cortical oscillatory activities play a role in regulating several brain functions in humans. However, whether motor resonant oscillations (i.e. β and γ) modulate long-term depression (LTD)-like plasticity of the primary motor cortex (M1) is still unclear.

OBJECTIVE

To address this issue, we combined transcranial alternating current stimulation (tACS), a technique able to entrain cortical oscillations, with continuous theta burst stimulation (cTBS), a transcranial magnetic stimulation (TMS) protocol commonly used to induce LTD-like plasticity in M1.

METHODS

Motor evoked potentials (MEPs) elicited by single-pulse TMS, short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) were evaluated before and 5, 15 and 30 min after cTBS alone or cTBS delivered during β-tACS (cTBS-β) or γ-tACS (cTBS-γ). Moreover, we tested the effects of β-tACS (alone) on short-latency afferent inhibition (SAI) and γ-tACS on SICI in order to verify whether tACS-related interneuronal modulation contributes to the effects of tACS-cTBS co-stimulation.

RESULTS

cTBS-γ turned the expected after-effects of cTBS from inhibition to facilitation. By contrast, responses to cTBS-β were similar to those induced by cTBS alone. β- and γ-tACS did not change MEPs evoked by single-pulse TMS. β-tACS reduced SAI and γ-tACS reduced SICI. However, the degree of γ-tACS-induced modulation of SICI did not correlate with the effects of cTBS-γ.

CONCLUSION

γ-tACS reverses cTBS-induced plasticity of the human M1. γ-oscillations may therefore regulate LTD-like plasticity mechanisms.

Gamma oscillations in somatosensory cortex recruit prefrontal and descending serotonergic pathways in aversion and nociception

In humans, gamma-band oscillations in the primary somatosensory cortex (S1) correlate with subjective pain perception. However, functional contributions to pain and the nature of underlying circuits are unclear. Here we report that gamma oscillations, but not other rhythms, are specifically strengthened independently of any motor component in the S1 cortex of mice during nociception. Moreover, mice with inflammatory pain show elevated resting gamma and alpha activity and increased gamma power in response to sub-threshold stimuli, in association with behavioral nociceptive hypersensitivity. Inducing gamma oscillations via optogenetic activation of parvalbumin-expressing inhibitory interneurons in the S1 cortex enhances nociceptive sensitivity and induces aversive avoidance behavior. Activity mapping identified a network of prefrontal cortical and subcortical centers whilst morphological tracing and pharmacological studies demonstrate the requirement of descending serotonergic facilitatory pathways in these pain-related behaviors. This study thus describes a mechanistic framework for modulation of pain by specific activity patterns in the S1 cortex.

Gamma oscillations in somatosensory areas in humans correlate with pain perception and pain stimulus intensity, but could also reflect cognitive processes such as attention. Here the authors provide evidence in mice that these oscillations causally contribute to pain perception.

High efficiency two-photon uncaging coupled by the correction of spontaneous hydrolysis

Two-photon (TP) uncaging of neurotransmitter molecules is the method of choice to mimic and study the subtleties of neuronal communication either in the intact brain or in slice preparations. However, the currently available caged materials are just at the limit of their usability and have several drawbacks. The local and focal nature of their use may for example be jeopardized by a high spontaneous hydrolysis rate of the commercially available compounds with increased photochemical release rate. Here, using quantum chemical modelling we show the mechanisms of hydrolysis and two-photon activation, and synthesized more effective caged compounds. Furthermore, we have developed a new enzymatic elimination method removing neurotransmitters inadvertently escaping from their compound during experiment. This method, usable both in one and two-photon experiments, allows for the use of materials with an increased rate of photochemical release. The efficiency of the new compound and the enzymatic method and of the new compound are demonstrated in neurophysiological experiments.

Do Brain Oscillations Orchestrate Memory?

Rhythmicity and oscillations are common features in nature, and can be seen in phenomena such as seasons, breathing, and brain activity. Despite the fact that a single neuron transmits its activity to its neighbor through a transient pulse, rhythmic activity emerges from large population-wide activity in the brain, and such rhythms are strongly coupled with the state and cognitive functions of the brain. However, it is still debated whether the oscillations of brain activity actually carry information. Here, we briefly introduce the biological findings of brain oscillations, and summarize the recent progress in understanding how oscillations mediate brain function. Finally, we examine the possible relationship between brain cognitive function and oscillation, focusing on how oscillation is related to memory, particularly with respect to state-dependent memory formation and memory retrieval under specific brain waves. We propose that oscillatory waves in the neocortex contribute to the synchronization and activation of specific memory trace ensembles in the neocortex by promoting long-range neural communication.

Optogenetic Modulation of a Minor Fraction of Parvalbumin-Positive Interneurons Specifically Affects Spatiotemporal Dynamics of Spontaneous and Sensory-Evoked Activity in Mouse Somatosensory Cortex in Vivo

Parvalbumin (PV) positive interneurons exert strong effects on the neocortical excitatory network, but it remains unclear how they impact the spatiotemporal dynamics of sensory processing in the somatosensory cortex. Here, we characterized the effects of optogenetic inhibition and activation of PV interneurons on spontaneous and sensory-evoked activity in mouse barrel cortex in vivo. Inhibiting PV interneurons led to a broad-spectrum power increase both in spontaneous and sensory-evoked activity. Whisker-evoked responses were significantly increased within 20 ms after stimulus onset during inhibition of PV interneurons, demonstrating high temporal precision of PV-shaped inhibition. Multiunit activity was strongly enhanced in neighboring cortical columns, but not at the site of transduction, supporting a central and highly specific role of PV interneurons in lateral inhibition. Inversely, activating PV interneurons drastically decreased spontaneous and whisker-evoked activity in the principal column and exerted strong lateral inhibition. Histological assessment of transduced cells combined with quantitative modeling of light distribution and spike sorting revealed that only a minor fraction (~10%) of the local PV population comprising no more than a few hundred neurons is optogenetically modulated, mediating the observed prominent and widespread effects on neocortical processing.

Review of the Neural Oscillations Underlying Meditation

Objective: Meditation is one type of mental training that has been shown to produce many cognitive benefits. Meditation practice is associated with improvement in concentration and reduction of stress, depression, and anxiety symptoms. Furthermore, different forms of meditation training are now being used as interventions for a variety of psychological and somatic illnesses. These benefits are thought to occur as a result of neurophysiologic changes. The most commonly studied specific meditation practices are focused attention (FA), open-monitoring (OM), as well as transcendental meditation (TM), and loving-kindness (LK) meditation. In this review, we compare the neural oscillatory patterns during these forms of meditation.

Method: We performed a systematic review of neural oscillations during FA, OM, TM, and LK meditation practices, comparing meditators to meditation-naïve adults.

Results: FA, OM, TM, and LK meditation are associated with global increases in oscillatory activity in meditators compared to meditation-naïve adults, with larger changes occurring as the length of meditation training increases. While FA and OM are related to increases in anterior theta activity, only FA is associated with changes in posterior theta oscillations. Alpha activity increases in posterior brain regions during both FA and OM. In anterior regions, FA shows a bilateral increase in alpha power, while OM shows a decrease only in left-sided power. Gamma activity in these meditation practices is similar in frontal regions, but increases are variable in parietal and occipital regions.

Conclusions: The current literature suggests distinct differences in neural oscillatory activity among FA, OM, TM, and LK meditation practices. Further characterizing these oscillatory changes may better elucidate the cognitive and therapeutic effects of specific meditation practices, and potentially lead to the development of novel neuromodulation targets to take advantage of their benefits.

A neural circuit for gamma-band coherence across the retinotopic map in mouse visual cortex

Cortical gamma oscillations have been implicated in a variety of cognitive, behavioral, and circuit-level phenomena. However, the circuit mechanisms of gamma-band generation and synchronization across cortical space remain uncertain. Using optogenetic patterned illumination in acute brain slices of mouse visual cortex, we define a circuit composed of layer 2/3 (L2/3) pyramidal cells and somatostatin (SOM) interneurons that phase-locks ensembles across the retinotopic map. The network oscillations generated here emerge from non-periodic stimuli, and are stimulus size-dependent, coherent across cortical space, narrow band (30 Hz), and depend on SOM neuron but not parvalbumin (PV) neuron activity; similar to visually induced gamma oscillations observed in vivo. Gamma oscillations generated in separate cortical locations exhibited high coherence as far apart as 850 μm, and lateral gamma entrainment depended on SOM neuron activity. These data identify a circuit that is sufficient to mediate long-range gamma-band coherence in the primary visual cortex.

Gamma and Beta Oscillations Define a Sequence of Neurocognitive Modes Present in Odor Processing

Olfactory system beta (15-35 Hz) and gamma (40-110 Hz) oscillations of the local field potential in mammals have both been linked to odor learning and discrimination. Gamma oscillations represent the activity of a local network within the olfactory bulb, and beta oscillations represent engagement of a systemwide network. Here, we test whether beta and gamma oscillations represent different cognitive modes using the different demands of go/no-go and two-alternative choice tasks that previously were suggested to favor beta or gamma oscillations, respectively. We reconcile previous studies and show that both beta and gamma oscillations occur in both tasks, with gamma dominating the early odor sampling period (2-4 sniffs) and beta dominating later. The relative power and coherence of both oscillations depend separately on multiple factors within both tasks without categorical differences across tasks. While the early/gamma-associated period occurs in all trials, rats can perform above chance without the later/beta-associated period. Longer sampling, which includes beta oscillations, is associated with better performance. Gamma followed by beta oscillations therefore represents a sequence of cognitive and neural states during odor discrimination, which can be separately modified depending on the demands of a task and odor discrimination. Additionally, fast (85 Hz) and slow (70 Hz) olfactory bulb gamma oscillation sub-bands have been hypothesized to represent tufted and mitral cell networks, respectively (Manabe and Mori, 2013). We find that fast gamma favors the early and slow gamma the later (beta-dominated) odor-sampling period and that the relative contributions of these oscillations are consistent across tasks.

SIGNIFICANCE STATEMENT

Olfactory system gamma (40-110 Hz) and beta (15-35 Hz) oscillations of the local field potential indicate different neural firing statistics and functional circuits. We show that gamma and beta oscillations occur in stereotyped sequence during odor sampling in associative tasks, with local gamma dominating the first 250 ms of odor sniffing, followed by systemwide beta as behavioral responses are prepared. Oscillations and coupling strength between brain regions are modulated by task, odor, and learning, showing that task features can dramatically adjust the dynamics of a cortical sensory system, which changes state every ∼250 ms. Understanding cortical circuits, even at the biophysical level, depends on careful use of multiple behavioral contexts and stimuli.

Removal of Perineuronal Nets Unlocks Juvenile Plasticity Through Network Mechanisms of Decreased Inhibition and Increased Gamma Activity

Perineuronal nets (PNNs) are extracellular matrix structures mainly enwrapping parvalbumin-expressing inhibitory neurons. The assembly of PNNs coincides with the end of the period of heightened visual cortex plasticity in juveniles, whereas removal of PNNs in adults reopens for plasticity. The mechanisms underlying this phenomenon remain elusive. We have used chronic electrophysiological recordings to investigate accompanying electrophysiological changes to activity-dependent plasticity and we report on novel mechanisms involved in both induced and critical period plasticity. By inducing activity-dependent plasticity in the visual cortex of adult rats while recording single unit and population activity, we demonstrate that PNN removal alters the balance between inhibitory and excitatory spiking activity directly. Without PNNs, inhibitory activity was reduced, whereas spiking variability was increased as predicted in a simulation with a Brunel neural network. Together with a shift in ocular dominance and large effects on unit activity during the first 48 h of monocular deprivation (MD), we show that PNN removal resets the neural network to an immature, juvenile state. Furthermore, in PNN-depleted adults as well as in juveniles, MD caused an immediate potentiation of gamma activity, suggesting a novel mechanism initiating activity-dependent plasticity and driving the rapid changes in unit activity.

SIGNIFICANCE STATEMENT

Emerging evidence suggests a role for perineuronal nets (PNNs) in learning and regulation of plasticity, but the underlying mechanisms remain unresolved. Here, we used chronic in vivo extracellular recordings to investigate how removal of PNNs opens for plasticity and how activity-dependent plasticity affects neural activity over time. PNN removal caused reduced inhibitory activity and reset the network to a juvenile state. Experimentally induced activity-dependent plasticity by monocular deprivation caused rapid changes in single unit activity and a remarkable potentiation of gamma oscillations. Our results demonstrate how PNNs may be involved directly in stabilizing the neural network. Moreover, the immediate potentiation of gamma activity after plasticity onset points to potential new mechanisms for the initiation of activity-dependent plasticity.

When brain rhythms aren't 'rhythmic': implication for their mechanisms and meaning

Rhythms are a prominent signature of brain activity. Their expression is correlated with numerous examples of healthy information processing and their fluctuations are a marker of disease states. Yet, their causal or epiphenomenal role in brain function is still highly debated. We review recent studies showing brain rhythms are not always 'rhythmic', by which we mean representative of repeated cycles of activity. Rather, high power and continuous rhythms in averaged signals can represent brief transient events on single trials whose density accumulates in the average. We also review evidence showing time-domain signals with vastly different waveforms can exhibit identical spectral-domain frequency and power. Further, non-oscillatory waveform feature can create spurious high spectral power. Knowledge of these possibilities is essential when interpreting rhythms and is easily missed without considering pre-processed data. Lastly, we discuss how these findings suggest new directions to pursue in our quest to discover the mechanism and meaning of brain rhythms.

Prefrontal Parvalbumin Neurons in Control of Attention

While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top-down control of attention are largely unknown. Using chronic recordings in mice, we found that fast-spiking parvalbumin (FS-PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal-driven attentional processing, correlating to the level of attention. Elevated activity of FS-PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS-PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase-locked pyramidal neurons showed gamma-phase-dependent rate modulation during successful attentional processing. Optogenetic silencing of FS-PV neurons deteriorated attentional processing, while optogenetic synchronization of FS-PV neurons at gamma frequencies had pro-cognitive effects and improved goal-directed behavior. FS-PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal-driven attentional processing.

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Increased firing of mPFC PV interneurons is a signature of top-down attention

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Attention is characterized by synchronization of mPFC PV neurons and elevated gamma

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Local pyramidal neurons show gamma-phase-dependent rate modulation during attention

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Synchronization of mPFC PV neurons at gamma frequencies has pro-cognitive effects

Disruption of corticocortical information transfer during ketamine anesthesia in the primate brain

The neural mechanisms of anesthetic-induced unconsciousness have yet to be fully elucidated, in part because of the diverse molecular targets of anesthetic agents. We demonstrate, using intracortical recordings in macaque monkeys, that information transfer between structurally connected cortical regions is disrupted during ketamine anesthesia, despite preserved primary sensory representation. Furthermore, transfer entropy, an information-theoretic measure of directed connectivity, decreases significantly between neuronal units in the anesthetized state. This is the first direct demonstration of a general anesthetic disrupting corticocortical information transfer in the primate brain. Given past studies showing that more commonly used GABAergic drugs inhibit surrogate measures of cortical communication, this finding suggests the potential for a common network-level mechanism of anesthetic-induced unconsciousness.

Membrane Potential Dynamics of Spontaneous and Visually Evoked Gamma Activity in V1 of Awake Mice

Cortical gamma activity (30–80 Hz) is believed to play important functions in neural computation and arises from the interplay of parvalbumin-expressing interneurons (PV) and pyramidal cells (PYRs). However, the subthreshold dynamics underlying its emergence in the cortex of awake animals remain unclear. Here, we characterized the intracellular dynamics of PVs and PYRs during spontaneous and visually evoked gamma activity in layers 2/3 of V1 of awake mice using targeted patch-clamp recordings and synchronous local field potentials (LFPs). Strong gamma activity patterned in short bouts (one to three cycles), occurred when PVs and PYRs were depolarizing and entrained their membrane potential dynamics regardless of the presence of visual stimulation. PV firing phase locked unconditionally to gamma activity. However, PYRs only phase locked to visually evoked gamma bouts. Taken together, our results indicate that gamma activity corresponds to short pulses of correlated background synaptic activity synchronizing the output of cortical neurons depending on external sensory drive.

Gamma activity, an important component of brain dynamics, is driven by synaptic background activity and synchronizes distinct cortical cell types differently depending on visual input.

The neocortex is the main substrate of cognitive activity of the mammalian brain. During active wakefulness, it exhibits an oscillatory activity in the gamma range (30–80Hz), which is believed to play an important functional role and is altered in schizophrenic patients. Experimental studies have shown that gamma activity arises from the interaction of excitatory pyramidal neurons, the main neuronal type of the cortex, and local inhibitory neurons expressing the protein parvalbumin (PV). However, how these neuronal types behave during gamma activity remains largely unknown. Here, we recorded the intracellular activity of pyramidal and PV-expressing neurons in the visual cortex of awake mice while acquiring Local Field Potentials (LFPs)—extracellular voltage fluctuations within a small volume of the cortex—to monitor gamma activity. We found that gamma activity arises when PV-expressing neurons synchronize their output in response to a correlated input, reflecting the general activation of the local cortical network. This happens even in the absence of visual input. On the other hand, the output of pyramidal neurons only becomes entrained to gamma activity when the mice are exposed to visual stimulation. Thus, our results suggest that gamma activity synchronizes pyramidal neurons specifically when the cortex is engaged in processing external inputs.

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Reduction of Trial-to-Trial Perceptual Variability by Intracortical Tonic Inhibition

Variability is a prominent characteristic of cognitive brain function. For instance, different trials of presentation of the same stimulus yield higher variability in its perception: subjects sometimes fail in perceiving the same stimulus. Perceptual variability could be attributable to ongoing-spontaneous fluctuation in neuronal activity prior to sensory stimulation. Simulating a cortical neural network model, we investigated the underlying neuronal mechanism of perceptual variability in relation to variability in ongoing-spontaneous neuronal activity. In the network model, populations of principal cells (cell assemblies) encode information about sensory features. Each cell assembly is sensitive to one particular feature stimulus. Transporters on GABAergic interneurons regulate ambient GABA concentration in a neuronal activity-dependent manner. Ambient GABA molecules activate extrasynaptic GABAa receptors on principal cells and interneurons, and provide them with tonic inhibitory currents. We controlled the variability of ongoing-spontaneous neuronal activity by manipulating the basal level of ambient GABA and assessed the perceptual performance of the network: detection of a feature stimulus. In an erroneous response, stimulus-irrelevant but not stimulus-relevant principal cells were activated, generating trains of action potentials. Perceptual variability, reflected in error rate in detecting the same stimulus that was presented repeatedly to the network, was increased as the variability in ongoing-spontaneous membrane potential among cell assemblies increased. Frequent, transient membrane depolarization below firing threshold was the major cause of the increased neuronal variability, for which a decrease in basal ambient GABA concentration was responsible. We suggest that ambient GABA in the brain may have a role in reducing the variability in ongoing-spontaneous neuronal activity, leading to a decrease in perceptual variability and therefore to reliable sensory perception.