Cortical gamma band synchronization through somatostatin interneurons

Computational modeling of ketamine-induced changes in gamma-band oscillations: The contribution of parvalbumin and somatostatin interneurons

Ketamine, an NMDA receptor (NMDA-R) antagonist, produces psychotomimetic effects when administered in sub-anesthetic dosages. While previous research suggests that Ketamine alters the excitation/inhibition (E/I)-balance in cortical microcircuits, the precise neural mechanisms by which Ketamine produces these effects are not well understood. We analyzed resting-state MEG data from n = 12 participants who were administered Ketamine to assess changes in gamma-band (30-90 Hz) power and the slope of the aperiodic power spectrum compared to placebo. In addition, correlations of these effects with gene-expression of GABAergic interneurons and NMDA-Rs subunits were analyzed. Finally, we compared Ketamine-induced spectral changes to the effects of systematically changing NMDA-R levels on pyramidal cells, and parvalbumin-, somatostatin- and vasoactive intestinal peptide-expressing interneurons in a computational model of cortical layer-2/3 to identify crucial sites of Ketamine action. Ketamine resulted in a flatter aperiodic slope and increased gamma-band power across brain regions, with pronounced effects in prefrontal and central areas. These effects were correlated with the spatial distribution of parvalbumin and GluN2D gene expression. Computational modeling revealed that reduced NMDA-R activity in parvalbumin or somatostatin interneurons could reproduce increased gamma-band power by increasing pyramidal neuron firing rate, but did not account for changes in the aperiodic slope. The results suggest that parvalbumin and somatostatin interneurons may underlie increased gamma-band power following Ketamine administration in healthy volunteers, while changes in the aperiodic component could not be recreated. These findings have implications for current models of E/I-balance, as well as for understanding the mechanisms underlying the circuit effects of Ketamine.

Orbitofrontal High-Gamma Reflects Spike-Dissociable Value and Decision Mechanisms

The orbitofrontal cortex (OFC) plays a crucial role in value-based decisions. While much is known about how OFC neurons represent values, far less is known about information encoded in OFC local field potentials (LFPs). LFPs are important because they can reflect subthreshold activity not directly coupled to spiking and because they are potential targets for less invasive forms of brain-machine interface (BMI). We recorded neural activity in the OFC of male macaques performing a two-option value-based decision task. We compared the value- and decision-coding properties of high-gamma LFPs (HG, 50-150 Hz) to the coding properties of spiking multiunit activity (MUA) recorded concurrently on the same electrodes. HG and MUA both represented the values of decision targets, but HG signals had value-coding features that were distinct from concurrently measured MUA. On average HG amplitude increased monotonically with value, whereas in MUA the value encoding was net neutral on average. HG encoded a signal consistent with a comparison between target values, a signal which was negligible in MUA. In individual channels, HG could predict choice outcomes more accurately than MUA; however, when channels were combined in a population-based decoder, MUA was more accurate than HG. In summary, HG signals reveal value-coding features in OFC that could not be observed from spiking activity, including representation of value comparisons and more accurate behavioral predictions. These results have implications for the role of OFC in value-based decisions and suggest that high-frequency LFPs may be a viable-or even preferable-target for BMIs to assist cognitive function.

Untangling stability and gain modulation in cortical circuits with multiple interneuron classes

Synaptic inhibition is the mechanistic backbone of a suite of cortical functions, not the least of which are maintaining network stability and modulating neuronal gain. In cortical models with a single inhibitory neuron class, network stabilization and gain control work in opposition to one another - meaning high gain coincides with low stability and vice versa. It is now clear that cortical inhibition is diverse, with molecularly distinguished cell classes having distinct positions within the cortical circuit. We analyze circuit models with pyramidal neurons (E) as well as parvalbumin (PV) and somatostatin (SOM) expressing interneurons. We show how, in E - PV - SOM recurrently connected networks, SOM-mediated modulation can lead to simultaneous increases in neuronal gain and network stability. Our work exposes how the impact of a modulation mediated by SOM neurons depends critically on circuit connectivity and the network state.

Synaptic plasticity facilitates oscillations in a V1 cortical column model with multiple interneuron types

Neural rhythms are ubiquitous in cortical recordings, but it is unclear whether they emerge due to the basic structure of cortical microcircuits or depend on function. Using detailed electrophysiological and anatomical data of mouse V1, we explored this question by building a spiking network model of a cortical column incorporating pyramidal cells, PV, SST, and VIP inhibitory interneurons, and dynamics for AMPA, GABA, and NMDA receptors. The resulting model matched in vivo cell-type-specific firing rates for spontaneous and stimulus-evoked conditions in mice, although rhythmic activity was absent. Upon introduction of long-term synaptic plasticity in the form of an STDP rule, broad-band (15-60 Hz) oscillations emerged, with feedforward/feedback input streams enhancing/suppressing the oscillatory drive, respectively. These plasticity-triggered rhythms relied on all cell types, and specific experience-dependent connectivity patterns were required to generate oscillations. Our results suggest that neural rhythms are not necessarily intrinsic properties of cortical circuits, but rather they may arise from structural changes elicited by learning-related mechanisms.

Anatomically resolved oscillatory bursts reveal dynamic motifs of thalamocortical activity during naturalistic stimulus viewing

Natural vision requires circuit mechanisms which process complex spatiotemporal stimulus features in parallel. In the mammalian forebrain, one signature of circuit activation is fast oscillatory dynamics, reflected in the local field potential (LFP). Using data from the Allen Neuropixels Visual Coding project, we show that local visual features in naturalistic stimuli induce in mouse primary visual cortex (V1) retinotopically specific oscillations in various frequency bands and V1 layers. Specifically, layer 4 (L4) narrowband gamma was linked to luminance, low-gamma to optic flow, and L4/L5 epsilon oscillations to contrast. These feature-specific oscillations were associated with distinct translaminar spike-phase coupling patterns, which were conserved across a range of stimuli containing the relevant visual features, suggesting that they might constitute feature-specific circuit motifs. Our findings highlight visually induced fast oscillations as markers of dynamic circuit motifs, which may support differential and multiplexed coding of complex visual input and thalamocortical information propagation.

Extending Mathematical Frameworks to Investigate Neuronal Dynamics in the Presence of Microglial Ensheathment

Recent experimental evidence has shown that glial cells, including microglia and astrocytes, can ensheathe specific synapses, positioning them to disrupt neurotransmitter flow between pre- and post-synaptic terminals. This study, as part of the special issue "Problems, Progress and Perspectives in Mathematical and Computational Biology," expands micro- and network-scale theoretical frameworks to incorporate these new experimental observations that introduce substantial heterogeneities into the system. Specifically, we aim to explore how varying degrees of synaptic ensheathment affect synaptic communication and network dynamics. Consistent with previous studies, our microscale model shows that ensheathment accelerates synaptic transmission while reducing its strength and reliability, with the potential to effectively switch off synaptic connections. Building on these findings, we integrate an "effective" glial cell model into a large-scale neuronal network. Specifically, we analyze a network with highly heterogeneous synaptic strengths and time constants, where glial proximity parametrizes synaptic properties. This parametrization results in a multimodal distribution of synaptic parameters across the network, introducing significantly greater variability compared to previous modeling efforts that assumed a normal distribution. This framework is applied to large networks of exponential integrate-and-fire neurons, extending linear response theory to analyze not only firing rate distributions but also noise correlations across the network. Despite the significant heterogeneity in the system, a mean-field approximation accurately captures network statistics. We demonstrate the utility of our model by reproducing experimental findings, showing that microglial ensheathment leads to post-anesthesia hyperactivity in excitatory neurons of mice. Furthermore, we explore how glial ensheathment may be used in the visual cortex to target specific neuronal subclasses, tuning higher-order network statistics.

Infralimbic parvalbumin neural activity facilitates cued threat avoidance

The infralimbic cortex (IL) is essential for flexible behavioral responses to threatening environmental events. Reactive behaviors such as freezing or flight are adaptive in some contexts, but in others a strategic avoidance behavior may be more advantageous. IL has been implicated in avoidance, but the contribution of distinct IL neural subtypes with differing molecular identities and wiring patterns is poorly understood. Here, we study IL parvalbumin (PV) interneurons in mice as they engage in active avoidance behavior, a behavior in which mice must suppress freezing in order to move to safety. We find that activity in inhibitory PV neurons increases during movement to avoid the shock in this behavioral paradigm, and that PV activity during movement emerges after mice have experienced a single shock, prior to learning avoidance. PV neural activity does not change during movement toward cued rewards or during general locomotion in the open field, behavioral paradigms where freezing does not need to be suppressed to enable movement. Optogenetic suppression of PV neurons increases the duration of freezing and delays the onset of avoidance behavior, but does not affect movement toward rewards or general locomotion. These data provide evidence that IL PV neurons support strategic avoidance behavior by suppressing freezing.

Integrating multimodal data to understand cortical circuit architecture and function

In recent years there has been a tremendous growth in new technologies that allow large-scale investigation of different characteristics of the nervous system at an unprecedented level of detail. There is a growing trend to use combinations of these new techniques to determine direct links between different modalities. In this Perspective, we focus on the mouse visual cortex, as this is one of the model systems in which much progress has been made in the integration of multimodal data to advance understanding. We review several approaches that allow integration of data regarding various properties of cortical cell types, connectivity at the level of brain areas, cell types and individual cells, and functional neural activity in vivo. The increasingly crucial contributions of computation and theory in analyzing and systematically modeling data are also highlighted. Together with open sharing of data, tools and models, integrative approaches are essential tools in modern neuroscience for improving our understanding of the brain architecture, mechanisms and function.

Lateral inhibition in V1 controls neural and perceptual contrast sensitivity

Lateral inhibition is a central principle in sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. However, the neurons, computations and mechanisms underlying cortical lateral inhibition remain debated, and its importance for perception remains unknown. Here we show that lateral inhibition from parvalbumin neurons in mouse primary visual cortex reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from somatostatin neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model, anatomical tracing and direct subthreshold measurements indicated that the larger spatial footprint for somatostatin versus parvalbumin synaptic inhibition explains this difference. Together, these results define cell-type-specific computational roles for lateral inhibition in primary visual cortex, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

Distinct roles of PV and Sst interneurons in visually induced gamma oscillations

Gamma-frequency oscillations are a hallmark of active information processing and are generated by interactions between excitatory and inhibitory neurons. To examine the contribution of distinct inhibitory interneurons to visually induced gamma oscillations, we recorded from optogenetically identified PV+ (parvalbumin) and Sst+ (somatostatin) interneurons in mouse primary visual cortex (V1). PV and Sst inhibitory interneurons exhibited distinct correlations to gamma oscillations. PV cells were strongly phase locked, while Sst cells were weakly phase locked, except for narrow-waveform Sst cells. PV cells fired at a substantially earlier phase in the gamma cycle (≈6 ms) than Sst cells. PV cells fired shortly after the onset of tightly synchronized burst events in excitatory cells, while Sst interneurons fired after subsequent burst spikes or single spikes. These findings indicate a main role of PV interneurons in synchronizing network activity and suggest that PV and Sst interneurons control the excitability of somatic and dendritic neural compartments with precise time delays coordinated by gamma oscillations.

Environmental context influences visual processing in thalamus

Behavioral state modulates neural activity throughout the visual system.1,2,3 This is largely due to changes in arousal that alter internal brain states.4,5,6,7,8,9,10 Much is known about how these internal factors influence visual processing,7,8,9,10,11 but comparatively less is known about the role of external environmental contexts.12 Environmental contexts can promote or prevent certain actions,13 and it remains unclear if and how this affects visual processing. Here, we addressed this question in the thalamus of awake, head-fixed mice while they viewed stimuli but remained stationary in two different environmental contexts: either a cylindrical tube or a circular running wheel that enabled locomotion. We made silicon probe recordings in the dorsal lateral geniculate nucleus (dLGN) while simultaneously measuring multiple metrics of arousal changes so that we could control for these across contexts. We found surprising differences in spatial and temporal processing in dLGN across contexts. The wheel context (versus tube) showed elevated baseline activity and faster but less spatially selective visual responses; however, these visual processing differences disappeared if the wheel no longer enabled locomotion. Our results reveal an unexpected influence of the physical environmental context on fundamental aspects of early visual processing, even in otherwise identical states of alertness and stillness.

A human electrophysiological biomarker of Fragile X Syndrome is shared in V1 of Fmr1 KO mice and caused by loss of FMRP in cortical excitatory neurons

Predicting clinical therapeutic outcomes from preclinical animal studies remains an obstacle to developing treatments for neuropsychiatric disorders. Electrophysiological biomarkers analyzed consistently across species could bridge this divide. In humans, alpha oscillations in the resting state electroencephalogram (rsEEG) are altered in many disorders, but these disruptions have not yet been characterized in animal models. Here, we employ a uniform analytical method to show in males with fragile X syndrome (FXS) that the slowed alpha oscillations observed in adults are also present in children and in visual cortex of adult and juvenile Fmr1 -/y mice. We find that alpha-like oscillations in mice reflect the differential activity of two classes of inhibitory interneurons, but the phenotype is caused by deletion of Fmr1 specifically in cortical excitatory neurons. These results provide a framework for studying alpha oscillation disruptions across species, advance understanding of a critical rsEEG signature in the human brain and inform the cellular basis for a putative biomarker of FXS.

Local Differences in Network Organization in the Auditory and Parietal Cortex, Revealed with Single Neuron Activation

The structure of local circuits is highly conserved across the cortex, yet the spatial and temporal properties of population activity differ fundamentally in sensory-level and association-level areas. In the sensory cortex, population activity has a shorter timescale and decays sharply over distance, supporting a population code for the fine-scale features of sensory stimuli. In the association cortex, population activity has a longer timescale and spreads over wider distances, a code that is suited to holding information in memory and driving behavior. We tested whether these differences in activity dynamics could be explained by differences in network structure. We targeted photostimulations to single excitatory neurons of layer 2/3, while monitoring surrounding population activity using two-photon calcium imaging. Experiments were performed in the auditory (AC) and posterior parietal cortex (PPC) within the same mice of both sexes, which also expressed a red fluorophore in somatostatin-expressing interneurons (SOM). In both cortical regions, photostimulations resulted in a spatially restricted zone of positive influence on neurons closely neighboring the targeted neuron and a more spatially diffuse zone of negative influence affecting more distant neurons (akin to a network-level "suppressive surround"). However, the relative spatial extents of positive and negative influence were different in AC and PPC. In PPC, the central zone of positive influence was wider, but the negative suppressive surround was more narrow than in AC, which could account for the larger-scale network dynamics in PPC. The more narrow central positive influence zone and wider suppressive surround in AC could serve to sharpen sensory representations.

Delayed Accumulation of Inhibitory Input Explains Gamma Frequency Variation with Changing Contrast in an Inhibition Stabilized Network

Gamma rhythm (30-70 Hz), thought to represent the interactions between excitatory and inhibitory populations, can be induced by presenting achromatic gratings in the primary visual cortex (V1) and is sensitive to stimulus properties such as size and contrast. In addition, gamma occurs in short bursts and shows a "frequency falloff" effect where its peak frequency is high after stimulus onset and slowly decreases to a steady state. Recently, these size-contrast properties and temporal characteristics were replicated in a self-oscillating Wilson-Cowan (WC) model operating as an inhibition stabilized network (ISN), stimulated by Ornstein-Uhlenbeck (OU) type inputs. In particular, frequency falloff was explained by delayed and slowly accumulated inputs arriving at local inhibitory populations. We hypothesized that if the stimulus is preceded by another higher contrast stimulus, frequency falloff could be abolished or reversed, since the excessive inhibition will now take more time to dissipate. We presented gratings at different contrasts consecutively to two female monkeys while recording gamma using microelectrode arrays in V1 and confirmed this prediction. Further, this model also replicated a characteristic pattern of gamma frequency modulation to counter-phasing stimuli as reported previously. These phenomena were also replicated by an ISN model subject to slow adaptation in feedforward excitatory input. Thus, ISN model with delayed surround input or adapted feedforward input replicates gamma frequency responses to time-varying contrasts.

Interneuronal modulations as a functional switch for cortical computations: mechanisms and implication for disease

Understanding cortical inhibition and its diverse roles remains a key challenge in neurophysiological research. Traditionally, inhibition has been recognized for controlling the stability and rhythmicity of network dynamics, or refining the spatiotemporal properties of cortical representations. In this perspective, we propose that specific types of interneurons may play a complementary role, by modulating the computational properties of neural networks. We review experimental and theoretical evidence, mainly from rodent sensory cortices, that supports this view. Additionally, we explore how dysfunctions in these interneurons may disrupt the network's ability to switch between computational modes, impacting the flexibility of cortical processing and potentially contributing to various neurodevelopmental and psychiatric disorders.

Environmental context sculpts spatial and temporal visual processing in thalamus

Behavioral state modulates neural activity throughout the visual system1-3. This is largely due to changes in arousal that alter internal brain state4-10. Much is known about how these internal factors influence visual processing7-11, but comparatively less is known about the role of external environmental contexts12. Environmental contexts can promote or prevent certain actions13, and it remains unclear if and how this affects visual processing. Here, we addressed this question in the thalamus of awake head-fixed mice while they viewed stimuli but remained stationary in two different environmental contexts: either a cylindrical tube, or a circular running wheel that enabled locomotion. We made silicon probe recordings in the dorsal lateral geniculate nucleus (dLGN) while simultaneously measuring multiple metrics of arousal changes, so that we could control for them across contexts. We found surprising differences in spatial and temporal processing in dLGN across contexts. The wheel context (versus tube) showed elevated baseline activity, and faster but less spatially selective visual responses; however, these visual processing differences disappeared if the wheel no longer enabled locomotion. Our results reveal an unexpected influence of the physical environmental context on fundamental aspects of early visual processing, even in otherwise identical states of alertness and stillness.

Site-specific seeding of Lewy pathology induces distinct pre-motor cellular and dendritic vulnerabilities in the cortex

Circuit-based biomarkers distinguishing the gradual progression of Lewy pathology across synucleinopathies remain unknown. Here, we show that seeding of α-synuclein preformed fibrils in mouse dorsal striatum and motor cortex leads to distinct prodromal-phase cortical dysfunction across months. Our findings reveal that while both seeding sites had increased cortical pathology and hyperexcitability, distinct differences in electrophysiological and cellular ensemble patterns were crucial in distinguishing pathology spread between the two seeding sites. Notably, while beta-band spike-field-coherence reflected a significant increase beginning in Layer-5 and then spreading to Layer-2/3, the rate of entrainment and the propensity of stochastic beta-burst dynamics was markedly seeding location-specific. This beta dysfunction was accompanied by gradual superficial excitatory ensemble instability following cortical, but not striatal, preformed fibrils injection. We reveal a link between Layer-5 dendritic vulnerabilities and translaminar beta event dysfunction, which could be used to differentiate symptomatically similar synucleinopathies.

Three distinct gamma oscillatory networks within cortical columns in macaque monkeys' area V1

Introduction

A fundamental property of the neocortex is its columnar organization in many species. Generally, neurons of the same column share stimulus preferences and have strong anatomical connections across layers. These features suggest that neurons within a column operate as one unified network. Other features, like the different patterns of input and output connections of neurons located in separate layers and systematic differences in feature tuning, hint at a more segregated and possibly flexible functional organization of neurons within a column.

Methods

To distinguish between these views of columnar processing, we conducted laminar recordings in macaques' area V1 while they performed a demanding attention task. We identified three separate regions with strong gamma oscillatory activity, located in the supragranular, granular, and infragranular laminar domains, based on the current source density (CSD).

Results and Discussion

Their characteristics differed significantly in their dominant gamma frequency and attention-dependent modulation of their gramma power and gamma frequency. In line, spiking activity in the supragranular, infragranular, and upper part of the granular domain exhibited strong phase coherence with the CSD signals of their domain but showed much weaker coherence with the CSD signals of other domains.

Conclusion

These results indicate that columnar processing involves a certain degree of independence between neurons in the three laminar domains, consistent with the assumption of multiple, separate intracolumnar ensembles. Such a functional organization offers various possibilities for dynamic network configuration, indicating that neurons in a column are not restricted to operate as one unified network. Thus, the findings open interesting new possibilities for future concepts and investigations on flexible, dynamic cortical ensemble formation and selective information processing.

The claustrum and synchronized brain states

Cortical activity is constantly fluctuating between distinct spatiotemporal activity patterns denoted by changes in brain state. States of cortical desynchronization arise during motor generation, increased attention, and high cognitive load. Synchronized brain states comprise spatially widespread, coordinated low-frequency neural activity during rest and sleep when disengaged from the external environment or 'offline'. The claustrum is a small subcortical structure with dense reciprocal connections with the cortex suggesting modulation by, or participation in, brain state regulation. Here, we highlight recent work suggesting that neural activity in the claustrum supports cognitive processes associated with synchronized brain states characterized by increased low-frequency network activity. As an example, we outline how claustrum activity could support episodic memory consolidation during sleep.

Context-dependent orientation discontinuity encoding by gamma rhythms in mouse primary visual cortex

Through the modulation of its surround, an identical visual stimulus can be perceived as more or less salient, allowing it to either stand out or seamlessly integrate with the rest of the visual scene. Gamma rhythms are associated with processing stimulus features across extensive areas of the visual field. Consistent with this concept, the magnitude of visually induced gamma rhythm depends on how well stimulus features aligned both within and outside the classical receptive field (CRF) at the recording site. However, there still exists some uncertainty regarding the encoding of context-modulated orientation discontinuity by gamma rhythms. To address this concern, we conducted extracellular recordings in layers II/III and IV of area V1 using lightly anaesthetized mice to investigate the gamma tuning for stimuli with orientation discontinuity. Our study revealed that gamma rhythms exhibit a preference for stimuli with orientation discontinuity similar to the spiking responses observed in V1, which contradicts the findings of previous studies. Furthermore, the gamma tuning of discontinuous orientations exhibits a moderate correlation with spike tuning and a positive correlation with the strength of surround suppression. Therefore, our study suggests a close association between gamma tuning and nearby spiking tuning; additionally, it highlights the connection between the encoding of visual features by gamma rhythms and functional architecture, as well as neural signal integration. KEY POINTS: Visual context modulates the gamma rhythms in the primary visual cortex. Discontinuous orientation elicits significantly enhanced gamma rhythms compared to the iso-orientation stimulus. The gamma tuning of discontinuous orientations exhibits a moderate correlation with spike tuning. Gamma tuning of orientation discontinuity exhibits a positive correlation with the strength of surround suppression.

Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model

Despite music's omnipresence, the specific neural mechanisms responsible for perceiving and anticipating temporal patterns in music are unknown. To study potential mechanisms for keeping time in rhythmic contexts, we train a biologically constrained RNN, with excitatory (E) and inhibitory (I) units, on seven different stimulus tempos (2-8 Hz) on a synchronization and continuation task, a standard experimental paradigm. Our trained RNN generates a network oscillator that uses an input current (context parameter) to control oscillation frequency and replicates key features of neural dynamics observed in neural recordings of monkeys performing the same task. We develop a reduced three-variable rate model of the RNN and analyze its dynamic properties. By treating our understanding of the mathematical structure for oscillations in the reduced model as predictive, we confirm that the dynamical mechanisms are found also in the RNN. Our neurally plausible reduced model reveals an E-I circuit with two distinct inhibitory sub-populations, of which one is tightly synchronized with the excitatory units.

Firing rate models for gamma oscillations in I-I and E-I networks

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space

Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The interpretation of the recorded data calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Multi-layer spiking neuron network models of local cortical circuits covering about $1\,{\text{mm}^{2}}$ have been developed, integrating experimentally obtained neuron-type-specific connectivity data and reproducing features of observed in-vivo spiking statistics. Local field potentials can be computed from the simulated spiking activity. We here extend a local network and local field potential model to an area of $4\times 4\,{\text{mm}^{2}}$, preserving the neuron density and introducing distance-dependent connection probabilities and conduction delays. We find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations in agreement with experimental recordings from sensory cortex. Also compatible with experimental observations, the correlation of local field potential signals is strong and decays over a distance of several hundred micrometers. Enhanced spatial coherence in the low-gamma band around $50\,\text{Hz}$ may explain the recent report of an apparent band-pass filter effect in the spatial reach of the local field potential.

Modification of pre-ictal cortico-hippocampal oscillations by medial ganglionic eminence precursor cells grafting in the pilocarpine model of epilepsy

Cell replacement therapies using medial ganglionic eminence (MGE)-derived GABAergic precursors reduce seizures by restoring inhibition in animal models of epilepsy. However, how MGE-derived cells affect abnormal neuronal networks and consequently brain oscillations to reduce ictogenesis is still under investigation. We performed quantitative analysis of pre-ictal local field potentials (LFP) of cortical and hippocampal CA1 areas recorded in vivo in the pilocarpine rat model of epilepsy, with or without intrahippocampal MGE-precursor grafts (PILO and PILO+MGE groups, respectively). The PILO+MGE animals had a significant reduction in the number of seizures. The quantitative analysis of pre-ictal LFP showed decreased power of cortical and hippocampal delta, theta and beta oscillations from the 5 min. interictal baseline to the 20 s. pre-ictal period in both groups. However, PILO+MGE animals had higher power of slow and fast oscillations in the cortex and lower power of slow and fast oscillations in the hippocampus compared to the PILO group. Additionally, PILO+MGE animals exhibited decreased cortico-hippocampal synchrony for theta and gamma oscillations at seizure onset and lower hippocampal CA1 synchrony between delta and theta with slow gamma oscillations compared to PILO animals. These findings suggest that MGE-derived cell integration into the abnormally rewired network may help control ictogenesis.

Spatiotemporal resonance in mouse primary visual cortex

Human primary visual cortex (V1) responds more strongly, or resonates, when exposed to ∼10, ∼15-20, and ∼40-50 Hz rhythmic flickering light. Full-field flicker also evokes the perception of hallucinatory geometric patterns, which mathematical models explain as standing-wave formations emerging from periodic forcing at resonant frequencies of the simulated neural network. However, empirical evidence for such flicker-induced standing waves in the visual cortex was missing. We recorded cortical responses to flicker in awake mice using high-spatial-resolution widefield imaging in combination with high-temporal-resolution glutamate-sensing fluorescent reporter (iGluSnFR). The temporal frequency tuning curves in the mouse V1 were similar to those observed in humans, showing a banded structure with multiple resonance peaks (8, 15, and 33 Hz). Spatially, all flicker frequencies evoked responses in V1 corresponding to retinotopic stimulus location, but some evoked additional peaks. These flicker-induced cortical patterns displayed standing-wave characteristics and matched linear wave equation solutions in an area restricted to the visual cortex. Taken together, the interaction of periodic traveling waves with cortical area boundaries leads to spatiotemporal activity patterns that may affect perception.

Experience Dependence of Alpha Rhythms and Neural Dynamics in the Mouse Visual Cortex

The role of experience in the development and maintenance of emergent network properties such as cortical oscillations and states is poorly understood. To define how early-life experience affects cortical dynamics in the visual cortex of adult, head-fixed mice, we examined the effects of two forms of blindness initiated before eye opening and continuing through recording: (1) bilateral loss of retinal input (enucleation) and (2) degradation of visual input (eyelid suture). Neither form of deprivation fundamentally altered the state-dependent regulation of firing rates or local field potentials. However, each deprivation caused unique changes in network behavior. Laminar analysis revealed two different generative mechanisms for low-frequency synchronization: one prevalent during movement and the other during quiet wakefulness. The former was absent in enucleated mice, suggesting a mouse homolog of human alpha oscillations. In addition, neurons in enucleated animals were less correlated and fired more regularly, but no change in mean firing rate. Eyelid suture decreased firing rates during quiet wakefulness, but not during movement, with no effect on neural correlations or regularity. Sutured animals showed a broadband increase in depth EEG power and an increased occurrence, but reduced central frequency, of narrowband gamma oscillations. The complementary-rather than additive-effects of lid suture and enucleation suggest that the development of emergent network properties does not require vision but is plastic to modified input. Our results suggest a complex interaction of internal set points and experience determines mature cortical activity, with low-frequency synchronization being particularly susceptible to early deprivation.

Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity

Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We developed a cortical circuit model predicting that SST cells become increasingly important for stabilization as sensory input strengthens. We tested this prediction in mouse primary visual cortex by manipulating excitatory input to SST cells, a key parameter for inhibition stabilization, with a novel cell-type specific pharmacological method to selectively block glutamatergic receptors on SST cells. Consistent with our model predictions, we find antagonizing glutamatergic receptors drives a paradoxical facilitation of SST cells with increasing stimulus contrast. In addition, we find even stronger engagement of SST-dependent stabilization when the mice are aroused. Thus, we reveal that the role of SST cells in cortical processing gradually switches as a function of both input strength and behavioral state.

A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity

Three major types of GABAergic interneurons, parvalbumin-, somatostatin-, and vasoactive intestinal peptide-expressing (PV, SOM, VIP) cells, play critical but distinct roles in the cortical microcircuitry. Their specific electrophysiology and connectivity shape their inhibitory functions. To study the network dynamics and signal processing specific to these cell types in the cerebral cortex, we developed a multi-layer model incorporating biologically realistic interneuron parameters from rodent somatosensory cortex. The model is fitted to in vivo data on cell-type-specific population firing rates. With a protocol of cell-type-specific stimulation, network responses when activating different neuron types are examined. The model reproduces the experimentally observed inhibitory effects of PV and SOM cells and disinhibitory effect of VIP cells on excitatory cells. We further create a version of the model incorporating cell-type-specific short-term synaptic plasticity (STP). While the ongoing activity with and without STP is similar, STP modulates the responses of Exc, SOM, and VIP cells to cell-type-specific stimulation, presumably by changing the dominant inhibitory pathways. With slight adjustments, the model also reproduces sensory responses of specific interneuron types recorded in vivo. Our model provides predictions on network dynamics involving cell-type-specific short-term plasticity and can serve to explore the computational roles of inhibitory interneurons in sensory functions.

State modulation in spatial networks with three interneuron subtypes

Several inhibitory interneuron subtypes have been identified as critical in regulating sensory responses. However, the specific contribution of each interneuron subtype remains uncertain. In this work, we explore the contributions of cell-type specific activity and synaptic connections to dynamics of a spatially organized spiking neuron network. We find that the firing rates of the somatostatin (SOM) interneurons align closely with the level of network synchrony irrespective of the target of modulatory input. Further analysis reveals that inhibition from SOM to parvalbumin (PV) interneurons must be limited to allow gradual transitions from asynchrony to synchrony and that the strength of recurrent excitation onto SOM neurons determines the level of synchrony achievable in the network. Our results are consistent with recent experimental findings on cell-type specific manipulations. Overall, our results highlight common dynamic regimes achieved across modulations of different cell populations and identify SOM cells as the main driver of network synchrony.

Attentional selection and communication through coherence: Scope and limitations

Synchronous neural oscillations are strongly associated with a variety of perceptual, cognitive, and behavioural processes. It has been proposed that the role of the synchronous oscillations in these processes is to facilitate information transmission between brain areas, the 'communication through coherence,' or CTC hypothesis. The details of how this mechanism would work, however, and its causal status, are still unclear. Here we investigate computationally a proposed mechanism for selective attention that directly implicates the CTC as causal. The mechanism involves alpha band (about 10 Hz) oscillations, originating in the pulvinar nucleus of the thalamus, being sent to communicating cortical areas, organizing gamma (about 40 Hz) oscillations there, and thus facilitating phase coherence and communication between them. This is proposed to happen contingent on control signals sent from higher-level cortical areas to the thalamic reticular nucleus, which controls the alpha oscillations sent to cortex by the pulvinar. We studied the scope of this mechanism in parameter space, and limitations implied by this scope, using a computational implementation of our conceptual model. Our results indicate that, although the CTC-based mechanism can account for some effects of top-down and bottom-up attentional selection, its limitations indicate that an alternative mechanism, in which oscillatory coherence is caused by communication between brain areas rather than being a causal factor for it, might operate in addition to, or even instead of, the CTC mechanism.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with anatomy and direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

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.

Distinct feedforward and feedback pathways for cell-type specific attention effects

Selective attention is thought to depend on enhanced firing activity in extrastriate areas. Theories suggest that this enhancement depends on selective inter-areal communication via gamma (30-80 Hz) phase-locking. To test this, we simultaneously recorded from different cell types and cortical layers of macaque V1 and V4. We find that while V1-V4 gamma phase-locking between local field potentials increases with attention, the V1 gamma rhythm does not engage V4 excitatory-neurons, but only fast-spiking interneurons in L4 of V4. By contrast, attention enhances V4 spike-rates in both excitatory and inhibitory cells, most strongly in L2/3. The rate increase in L2/3 of V4 precedes V1 in time. These findings suggest enhanced signal transmission with attention does not depend on inter-areal gamma phase-locking and show that the endogenous gamma rhythm has cell-type- and layer-specific effects on downstream target areas. Similar findings were made in the mouse visual system, based on opto-tagging of identified interneurons.

Neocortical long-range inhibition promotes cortical synchrony and sleep

Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.

40 Hz Steady-State Response in Human Auditory Cortex Is Shaped by Gabaergic Neuronal Inhibition

The 40 Hz auditory steady-state response (ASSR), an oscillatory brain response to periodically modulated auditory stimuli, is a promising, noninvasive physiological biomarker for schizophrenia and related neuropsychiatric disorders. The 40 Hz ASSR might be amplified by synaptic interactions in cortical circuits, which are, in turn, disturbed in neuropsychiatric disorders. Here, we tested whether the 40 Hz ASSR in the human auditory cortex depends on two key synaptic components of neuronal interactions within cortical circuits: excitation via N-methyl-aspartate glutamate (NMDA) receptors and inhibition via gamma-amino-butyric acid (GABA) receptors. We combined magnetoencephalography (MEG) recordings with placebo-controlled, low-dose pharmacological interventions in the same healthy human participants (13 males, 7 females). All participants exhibited a robust 40 Hz ASSR in auditory cortices, especially in the right hemisphere, under a placebo. The GABAA receptor-agonist lorazepam increased the amplitude of the 40 Hz ASSR, while no effect was detectable under the NMDA blocker memantine. Our findings indicate that the 40 Hz ASSR in the auditory cortex involves synaptic (and likely intracortical) inhibition via the GABAA receptor, thus highlighting its utility as a mechanistic signature of cortical circuit dysfunctions involving GABAergic inhibition.

Different Trajectories of Functional Connectivity Captured with Gamma-Event Coupling and Broadband Measures of EEG in the Rat Fluid Percussion Injury Model

Functional connectivity (FC) after TBI is affected by an altered excitatory-inhibitory balance due to neuronal dysfunction, and the mechanistic changes observed could be reflected differently by contrasting methods. Local gamma event coupling FC (GEC-FC) is believed to represent multiunit fluctuations due to inhibitory dysfunction, and we hypothesized that FC derived from widespread, broadband amplitude signal (BBA-FC) would be different, reflecting broader mechanisms of functional disconnection. We tested this during sleep and active periods defined by high delta and theta EEG activity, respectively, at 1,7 and 28d after rat fluid-percussion-injury (FPI) or sham injury (n=6/group) using 10 indwelling, bilateral cortical and hippocampal electrodes. We also measured seizure and high-frequency oscillatory activity (HFOs) as markers of electrophysiological burden. BBA-FC analysis showed early hyperconnectivity constrained to ipsilateral sensory-cortex-to-CA1-hippocampus that transformed to mainly ipsilateral FC deficits by 28d compared to shams. These changes were conserved over active epochs, except at 28d when there were no differences to shams. In comparison, GEC-FC analysis showed large regions of hyperconnectivity early after injury within similar ipsilateral and intrahemispheric networks. GEC-FC weakened with time, but hyperconnectivity persisted at 28d compared to sham. Edge- and global connectivity measures revealed injury-related differences across time in GEC-FC as compared to BBA-FC, demonstrating greater sensitivity to FC changes post-injury. There was no significant association between sleep fragmentation, HFOs, or seizures with FC changes. The within-animal, spatial-temporal differences in BBA-FC and GEC-FC after injury may represent different mechanisms driving FC changes as a result of primary disconnection and interneuron loss.

Significance statement

The present study adds to the understanding of functional connectivity changes in preclinical models of traumatic brain injury. In previously reported literature, there is heterogeneity in the directionality of connectivity changes after injury, resulting from factors such as severity of injury, frequency band studied, and methodology used to calculate FC. This study aims to further clarify differential mechanisms that result in altered network topography after injury, by using Broadband Amplitude-Derived FC and Gamma Event Coupling-Derived FC in EEG. We found post-injury changes that differ in complexity and directionality between measures at and across timepoints. In conjunction with known results and future studies identifying different neural drivers underlying these changes, measures derived from this study could provide useful means from which to minimally-invasively study temporally-evolving pathology after TBI.

Balanced bidirectional optogenetics reveals the causal impact of cortical temporal dynamics in sensory perception

Whether the fast temporal dynamics of neural activity in brain circuits causally drive perception and cognition remains one of most longstanding unresolved questions in neuroscience 1-6 . While some theories posit a 'timing code' in which dynamics on the millisecond timescale is central to brain function, others instead argue that mean firing rates over more extended periods (a 'rate code') carry most of the relevant information. Existing tools, such as optogenetics, can be used to alter temporal structure of neural dynamics 7 , but they invariably change mean firing rates, leaving the interpretation of such experiments ambiguous. Here we developed and validated a new approach based on balanced, bidirectional optogenetics that can alter temporal structure of neural dynamics while mitigating effects on mean activity. Using this new approach, we found that selectively altering cortical temporal dynamics substantially reduced performance in a sensory perceptual task. These results demonstrate that endogenous temporal dynamics in the cortex are causally required for perception and behavior. More generally, this new bidirectional optogenetic approach should be broadly useful for disentangling the causal impact of different timescales of neural dynamics on behavior.

The influence of electrode types to the visually induced gamma oscillations in mouse primary visual cortex

The local field potential (LFP) is an extracellular electrical signal associated with neural ensemble input and dendritic signaling. Previous studies have linked gamma band oscillations of the LFP in cortical circuits to sensory stimuli encoding, attention, memory, and perception. Inconsistent results regarding gamma tuning for visual features were reported, but it remains unclear whether these discrepancies are due to variations in electrode properties. Specifically, the surface area and impedance of the electrode are important characteristics in LFP recording. To comprehensively address these issues, we conducted an electrophysiological study in the V1 region of lightly anesthetized mice using two types of electrodes: one with higher impedance (1 MΩ) and a sharp tip (10 μm), while the other had lower impedance (100 KΩ) but a thicker tip (200 μm). Our findings demonstrate that gamma oscillations acquired by sharp-tip electrodes were significantly stronger than those obtained from thick-tip electrodes. Regarding size tuning, most gamma power exhibited surround suppression at larger gratings when recorded from sharp-tip electrodes. However, the majority showed enhanced gamma power at larger gratings when recorded from thick-tip electrodes. Therefore, our study suggests that microelectrode parameters play a significant role in accurately recording gamma oscillations and responsive tuning to sensory stimuli.

Top-down modulation in canonical cortical circuits with short-term plasticity

Cortical dynamics and computations are strongly influenced by diverse GABAergic interneurons, including those expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP). Together with excitatory (E) neurons, they form a canonical microcircuit and exhibit counterintuitive nonlinear phenomena. One instance of such phenomena is response reversal, whereby SST neurons show opposite responses to top-down modulation via VIP depending on the presence of bottom-up sensory input, indicating that the network may function in different regimes under different stimulation conditions. Combining analytical and computational approaches, we demonstrate that model networks with multiple interneuron subtypes and experimentally identified short-term plasticity mechanisms can implement response reversal. Surprisingly, despite not directly affecting SST and VIP activity, PV-to-E short-term depression has a decisive impact on SST response reversal. We show how response reversal relates to inhibition stabilization and the paradoxical effect in the presence of several short-term plasticity mechanisms demonstrating that response reversal coincides with a change in the indispensability of SST for network stabilization. In summary, our work suggests a role of short-term plasticity mechanisms in generating nonlinear phenomena in networks with multiple interneuron subtypes and makes several experimentally testable predictions.

Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates

Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.

The laminar organization of cell types in macaque cortex and its relationship to neuronal oscillations

The canonical microcircuit (CMC) has been hypothesized to be the fundamental unit of information processing in cortex. Each CMC unit is thought to be an interconnected column of neurons with specific connections between excitatory and inhibitory neurons across layers. Recently, we identified a conserved spectrolaminar motif of oscillatory activity across the primate cortex that may be the physiological consequence of the CMC. The spectrolaminar motif consists of local field potential (LFP) gamma-band power (40-150 Hz) peaking in superficial layers 2 and 3 and alpha/beta-band power (8-30 Hz) peaking in deep layers 5 and 6. Here, we investigate whether specific conserved cell types may produce the spectrolaminar motif. We collected laminar histological and electrophysiological data in 11 distinct cortical areas spanning the visual hierarchy: V1, V2, V3, V4, TEO, MT, MST, LIP, 8A/FEF, PMD, and LPFC (area 46), and anatomical data in DP and 7A. We stained representative slices for the three main inhibitory subtypes, Parvalbumin (PV), Calbindin (CB), and Calretinin (CR) positive neurons, as well as pyramidal cells marked with Neurogranin (NRGN). We found a conserved laminar structure of PV, CB, CR, and pyramidal cells. We also found a consistent relationship between the laminar distribution of inhibitory subtypes with power in the local field potential. PV interneuron density positively correlated with gamma (40-150 Hz) power. CR and CB density negatively correlated with alpha (8-12 Hz) and beta (13-30 Hz) oscillations. The conserved, layer-specific pattern of inhibition and excitation across layers is therefore likely the anatomical substrate of the spectrolaminar motif.

Significance Statement

Neuronal oscillations emerge as an interplay between excitatory and inhibitory neurons and underlie cognitive functions and conscious states. These oscillations have distinct expression patterns across cortical layers. Does cellular anatomy enable these oscillations to emerge in specific cortical layers? We present a comprehensive analysis of the laminar distribution of the three main inhibitory cell types in primate cortex (Parvalbumin, Calbindin, and Calretinin positive) and excitatory pyramidal cells. We found a canonical relationship between the laminar anatomy and electrophysiology in 11 distinct primate areas spanning from primary visual to prefrontal cortex. The laminar anatomy explained the expression patterns of neuronal oscillations in different frequencies. Our work provides insight into the cortex-wide cellular mechanisms that generate neuronal oscillations in primates.

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Nerve injury disrupts temporal processing in the spinal cord dorsal horn through alterations in PV+ interneurons

How mechanical allodynia following nerve injury is encoded in patterns of neural activity in the spinal cord dorsal horn (DH) remains incompletely understood. We address this in mice using the spared nerve injury model of neuropathic pain and in vivo electrophysiological recordings. Surprisingly, despite dramatic behavioral over-reactivity to mechanical stimuli following nerve injury, an overall increase in sensitivity or reactivity of DH neurons is not observed. We do, however, observe a marked decrease in correlated neural firing patterns, including the synchrony of mechanical stimulus-evoked firing, across the DH. Alterations in DH temporal firing patterns are recapitulated by silencing DH parvalbumin+ (PV+) interneurons, previously implicated in mechanical allodynia, as are allodynic pain-like behaviors. These findings reveal decorrelated DH network activity, driven by alterations in PV+ interneurons, as a prominent feature of neuropathic pain and suggest restoration of proper temporal activity as a potential therapeutic strategy to treat chronic neuropathic pain.

Simultaneous interneuron labeling reveals population-level interactions among parvalbumin, somatostatin, and pyramidal neurons in cortex

Cortical interneurons shape network activity in cell type-specific ways, and are also influenced by interactions with other cell types. These specific cell-type interactions are understudied, as transgenic labeling methods typically restrict labeling to one neuron type at a time. Although recent methods have enabled post-hoc identification of cell types, these are not available to many labs. Here, we present a method to distinguish between two red fluorophores in vivo, which allowed imaging of activity in somatostatin (SOM), parvalbumin (PV), and putative pyramidal neurons (PYR) in mouse association cortex. We compared population events of elevated activity and observed that the PYR network state corresponded to the ratio between mean SOM and PV neuron activity, demonstrating the importance of simultaneous labeling to explain dynamics. These results extend previous findings in sensory cortex, as activity became sparser and less correlated when the ratio between SOM and PV activity was high.

Gamma oscillation plasticity is mediated via parvalbumin interneurons

Understanding the plasticity of neuronal networks is an emerging field of (patho-) physiological research, yet the underlying cellular mechanisms remain poorly understood. Gamma oscillations (30 to 80 hertz), a biomarker of cognitive performance, require and potentiate glutamatergic transmission onto parvalbumin-positive interneurons (PVIs), suggesting an interface for cell-to-network plasticity. In ex vivo local field potential recordings, we demonstrate long-term potentiation of hippocampal gamma power. Gamma potentiation obeys established rules of PVI plasticity, requiring calcium-permeable AMPA receptors (CP-AMPARs) and metabotropic glutamate receptors (mGluRs). A microcircuit computational model of CA3 gamma oscillations predicts CP-AMPAR plasticity onto PVIs critically outperforms pyramidal cell plasticity in increasing gamma power and completely accounts for gamma potentiation. We reaffirm this ex vivo in three PVI-targeting animal models, demonstrating that gamma potentiation requires PVI-specific signaling via a Gq/PKC pathway comprising mGluR5 and a Gi-sensitive, PKA-dependent pathway. Gamma activity-dependent, metabotropically mediated CP-AMPAR plasticity on PVIs may serve as a guiding principle in understanding network plasticity in health and disease.

Gamma-band-based dynamic functional connectivity in pigeon entopallium during sample presentation in a delayed color matching task

Birds have developed visual cognitions, especially in discriminating colors due to their four types of cones in the retina. The entopallium of birds is thought to be involved in the processing of color information during visual cognition. However, there is a lack of understanding about how functional connectivity in the entopallium region of birds changes during color cognition, which is related to various input colors. We therefore trained pigeons to perform a delayed color matching task, in which two colors were randomly presented in sample stimuli phrases, and the neural activity at individual recording site and the gamma band functional connectivity among local population in entopallium during sample presentation were analyzed. Both gamma band energy and gamma band functional connectivity presented dynamics as the stimulus was presented and persisted. The response features in the early-stimulus phase were significantly different from those of baseline and the late-stimulus phase. Furthermore, gamma band energy showed significant differences between different colors during the early-stimulus phase, but the global feature of the gamma band functional network did not. Further decoding results showed that decoding accuracy was significantly enhanced by adding functional connectivity features, suggesting the global feature of the gamma band functional network did not directly contain color information, but was related to it. These results provided insight into information processing rules among local neuronal populations in the entopallium of birds during color cognition, which is important for their daily life.

Enhancement of low gamma oscillations by volitional conditioning of local field potential in the primary motor and visual cortex of mice

Volitional control of local field potential oscillations in low gamma band via brain machine interface can not only uncover the relationship between low gamma oscillation and neural synchrony but also suggest a therapeutic potential to reverse abnormal local field potential oscillation in neurocognitive disorders. In nonhuman primates, the volitional control of low gamma oscillations has been demonstrated by brain machine interface techniques in the primary motor and visual cortex. However, it is not clear whether this holds in other brain regions and other species, for which gamma rhythms might involve in highly different neural processes. Here, we established a closed-loop brain-machine interface and succeeded in training mice to volitionally elevate low gamma power of local field potential in the primary motor and visual cortex. We found that the mice accomplished the task in a goal-directed manner and spiking activity exhibited phase-locking to the oscillation in local field potential in both areas. Moreover, long-term training made the power enhancement specific to direct and adjacent channel, and increased the transcriptional levels of NMDA receptors as well as that of hypoxia-inducible factor relevant to metabolism. Our results suggest that volitionally generated low gamma rhythms in different brain regions share similar mechanisms and pave the way for employing brain machine interface in therapy of neurocognitive disorders.

Measuring excitation-inhibition balance through spectral components of local field potentials

The balance between excitation and inhibition is critical to brain functioning, and dysregulation of this balance is a hallmark of numerous psychiatric conditions. Measuring this excitation-inhibition (E:I) balance in vivo has remained difficult, but theoretical models have proposed that characteristics of local field potentials (LFP) may provide an accurate proxy. To establish a conclusive link between LFP and E:I balance, we recorded single units and LFP from the prefrontal cortex (mPFC) of rats during decision making. Dynamic measures of synaptic coupling strength facilitated direct quantification of E:I balance and revealed a strong inverse relationship to broadband spectral power of LFP. These results provide a critical link between LFP and underlying network properties, opening the door for non-invasive recordings to measure E:I balance in clinical settings.

Magnetoencephalography in Psychiatry: A Perspective on Translational Research and Applications

Magnetoencephalography (MEG) is a neuroimaging technique that has excellent temporal as well as good spatial resolution for measuring neural activity and has been extensively employed in cognitive neuroscience. However, MEG has only been more recently applied to investigations of brain networks and biomarkers in psychiatry. Besides providing new insights into the pathophysiology of major psychiatry syndromes, especially in schizophrenia, a major objective of current research is the identification of biomarkers that could inform early intervention and novel treatments. This chapter will provide a state-of-the-art overview of MEG as applied to schizophrenia, autism spectrum disorders, and Alzheimer's disease, summarizing methodological approaches and studies investigating alterations during resting-state and task-related paradigms. In addition, we will highlight future methodological developments and their potential for applications of MEG in psychiatry.