Low- and high-gamma oscillations deviate in opposite directions from zero-phase synchrony in the limbic corticostriatal loop

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.

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.

Distributed cell assemblies spanning prefrontal cortex and striatum

Highly synchronous neuronal assembly activity is deemed essential for cognitive brain function. In theory, such synchrony could coordinate multiple brain areas performing complementary processes. However, cell assemblies have been observed only in single structures, typically cortical areas, and little is known about their synchrony with downstream subcortical structures, such as the striatum. Here, we demonstrate distributed cell assemblies activated at high synchrony (∼10 ms) spanning prefrontal cortex and striatum. In addition to including neurons at different brain hierarchical levels, surprisingly, they synchronized functionally distinct limbic and associative sub-regions. These assembly activations occurred when members shifted their firing phase relative to ongoing 4 Hz and theta rhythms, in association with high gamma oscillations. This suggests that these rhythms could mediate the emergence of cross-structural assemblies. To test for the role of assemblies in behavior, we trained the rats to perform a task requiring cognitive flexibility, alternating between two different rules in a T-maze. Overall, assembly activations were correlated with task-relevant parameters, including impending choice, reward, rule, or rule order. Moreover, these behavioral correlates were more robustly expressed by assemblies than by their individual member neurons. Finally, to verify whether assemblies can be endogenously generated, we found that they were indeed spontaneously reactivated during sleep and quiet immobility. Thus, cell assemblies are a more general coding mechanism than previously envisioned, linking distributed neocortical and subcortical areas at high synchrony.

Prefrontal Cortical Neurons Are Selective for Non-Local Hippocampal Representations during Replay and Behavior

Diverse functions such as decision-making and memory consolidation may depend on communication between neurons in the hippocampus (HP) and prefrontal cortex (PFC). HP replay is a candidate mechanism to facilitate this communication, however details remain largely unknown because of the technical challenges of recording sufficient numbers of HP neurons for replay while also recording PFC neurons. Here, we implanted male rats with 40-tetrode drives, split between HP and PFC, during learning of a Y-maze spatial memory task. Surprisingly, we found that in contrast to their non-selectivity for maze arm during movement, a portion of PFC neurons were highly selective for HP replay of different arms. Moreover, PFC neurons' selectivity to HP non-local arm representation during running tended to match their replay arm selectivity and was predictive of future choice. Thus, PFC activity that is tuned to HP activity is best explained by non-local HP position representations rather than HP representation of actual position, providing a new potential mechanism of HP-PFC coordination during HP replay.SIGNIFICANCE STATEMENT The hippocampus (HP) is implicated in spatial learning while the prefrontal cortex (PFC) is implicated in decision-making. The question of how the two areas interact has been of great interest. A specific activity type in HP called replay is particularly interesting because it resembles internal exploration of non-local experiences, but is technically challenging to study, requiring recordings from large numbers of HP neurons simultaneously. Here, we combined replay recordings from HP with prefrontal recordings, to reveal a surprising degree of selectivity for replay, and a pattern of coordination that supports some conceptions of hippocampocortical interaction and challenges others.

Adolescent nicotine induces depressive and anxiogenic effects through ERK 1-2 and Akt-GSK-3 pathways and neuronal dysregulation in the nucleus accumbens

Long-term tobacco dependence typically develops during adolescence and neurodevelopmental nicotine exposure is associated with affective disturbances that manifest as a variety of neuropsychiatric comorbidities in clinical and preclinical studies, including mood and anxiety-related disorders. The nucleus accumbens shell (NASh) is critically involved in regulating emotional processing, and both molecular and neuronal disturbances in this structure are associated with mood and anxiety-related pathologies. In the present study, we used a rodent model of adolescent neurodevelopmental nicotine exposure to examine the expression of several molecular biomarkers associated with mood/anxiety-related phenotypes. We report that nicotine exposure during adolescence (but not adulthood) induces profound upregulation of the ERK 1-2 and Akt-GSK-3 signalling pathways directly within the NASh, as well as downregulation of local D1R expression that persists into adulthood. These adaptations were accompanied by decreases in τ, α, β, and γ-band oscillatory states, hyperactive medium spiny neuron activity with depressed bursting rates, and anxiety and depressive-like behavioural abnormalities. Pharmacologically targeting these molecular and neuronal adaptations revealed that selective inhibition of local ERK 1-2 and Akt-GSK-3 signalling cascades rescued nicotine-induced high-γ-band oscillatory signatures and phasic bursting rates in the NASh, suggesting that they are involved in mediating adolescent nicotine-induced depressive and anxiety-like neuropathological trajectories.

Lack of redundancy between electrophysiological measures of long-range neuronal communication

Background

Communication between brain areas has been implicated in a wide range of cognitive and emotive functions and is impaired in numerous mental disorders. In rodent models, various metrics have been used to quantify inter-regional neuronal communication. However, in individual studies, typically, only very few measures of coupling are reported and, hence, redundancy across such indicators is implicitly assumed.

Results

In order to test this assumption, we here comparatively assessed a broad range of directional and non-directional metrics like coherence, Weighted Phase Lag Index (wPLI), phase-locking value (PLV), pairwise phase consistency (PPC), parametric and non-parametric Granger causality (GC), partial directed coherence (PDC), directed transfer function (DTF), spike-phase coupling (SPC), cross-regional phase-amplitude coupling, amplitude cross-correlations and others. We applied these analyses to simultaneous field recordings from the prefrontal cortex and the ventral and dorsal hippocampus in the schizophrenia-related Gria1-knockout mouse model which displays a robust novelty-induced hyperconnectivity phenotype. Using the detectability of coupling deficits in Gria1^−/− mice and bivariate correlations within animals as criteria, we found that across such measures, there is a considerable lack of functional redundancy. Except for three pairwise correlations—PLV with PPC, PDC with DTF and parametric with non-parametric Granger causality—almost none of the analysed metrics consistently co-varied with any of the other measures across the three connections and two genotypes analysed. Notable exceptions to this were the correlation of coherence with PPC and PLV that was found in most cases, and partial correspondence between these three measures and Granger causality. Perhaps most surprisingly, partial directed coherence and Granger causality—sometimes regarded as equivalent measures of directed influence—diverged profoundly. Also, amplitude cross-correlation, spike-phase coupling and theta-gamma phase-amplitude coupling each yielded distinct results compared to all other metrics.

Conclusions

Our analysis highlights the difficulty of quantifying real correlates of inter-regional information transfer, underscores the need to assess multiple coupling measures and provides some guidelines which metrics to choose for a comprehensive, yet non-redundant characterization of functional connectivity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-00950-4.

A biophysical model of striatal microcircuits suggests gamma and beta oscillations interleaved at delta/theta frequencies mediate periodicity in motor control

Striatal oscillatory activity is associated with movement, reward, and decision-making, and observed in several interacting frequency bands. Local field potential recordings in rodent striatum show dopamine- and reward-dependent transitions between two states: a "spontaneous" state involving β (∼15-30 Hz) and low γ (∼40-60 Hz), and a state involving θ (∼4-8 Hz) and high γ (∼60-100 Hz) in response to dopaminergic agonism and reward. The mechanisms underlying these rhythmic dynamics, their interactions, and their functional consequences are not well understood. In this paper, we propose a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms, as well as their modulation by dopamine. Building on previous modeling and experimental work suggesting that striatal projection neurons (SPNs) are capable of generating β oscillations, we show that networks of striatal fast-spiking interneurons (FSIs) are capable of generating δ/θ (ie, 2 to 6 Hz) and γ rhythms. Under simulated low dopaminergic tone our model FSI network produces low γ band oscillations, while under high dopaminergic tone the FSI network produces high γ band activity nested within a δ/θ oscillation. SPN networks produce β rhythms in both conditions, but under high dopaminergic tone, this β oscillation is interrupted by δ/θ-periodic bursts of γ-frequency FSI inhibition. Thus, in the high dopamine state, packets of FSI γ and SPN β alternate at a δ/θ timescale. In addition to a mechanistic explanation for previously observed rhythmic interactions and transitions, our model suggests a hypothesis as to how the relationship between dopamine and rhythmicity impacts motor function. We hypothesize that high dopamine-induced periodic FSI γ-rhythmic inhibition enables switching between β-rhythmic SPN cell assemblies representing the currently active motor program, and thus that dopamine facilitates movement in part by allowing for rapid, periodic shifts in motor program execution.

Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption

Background

Although male and female rats differ in their patterns of alcohol use, little is known regarding the neural circuit activity that underlies these differences in behavior. The current study used a machine learning approach to characterize sex differences in local field potential (LFP) oscillations that may relate to sex differences in alcohol-drinking behavior.

Methods

LFP oscillations were recorded from the nucleus accumbens shell and the rodent medial prefrontal cortex of adult male and female Sprague-Dawley rats. Recordings occurred before rats were exposed to alcohol (n = 10/sex × 2 recordings/rat) and during sessions of limited access to alcohol (n = 5/sex × 5 recordings/rat). Oscillations were also recorded from each female rat in each phase of estrous prior to alcohol exposure. Using machine learning, we built predictive models with oscillation data to classify rats based on: (1) biological sex, (2) phase of estrous, and (3) alcohol intake levels. We evaluated model performance from real data by comparing it to the performance of models built and tested on permutations of the data.

Results

Our data demonstrate that corticostriatal oscillations were able to predict alcohol intake levels in males (p < 0.01), but not in females (p = 0.45). The accuracies of models predicting biological sex and phase of estrous were related to fluctuations observed in alcohol drinking levels; females in diestrus drank more alcohol than males (p = 0.052), and the male vs. diestrus female model had the highest accuracy (71.01%) compared to chance estimates. Conversely, females in estrus drank very similar amounts of alcohol to males (p = 0.702), and the male vs. estrus female model had the lowest accuracy (56.14%) compared to chance estimates.

Conclusions

The current data demonstrate that oscillations recorded from corticostriatal circuits contain significant information regarding alcohol drinking in males, but not alcohol drinking in females. Future work will focus on identifying where to record LFP oscillations in order to predict alcohol drinking in females, which may help elucidate sex-specific neural targets for future therapeutic development.

Adaptive spike-artifact removal from local field potentials uncovers prominent beta and gamma band neuronal synchronization

BACKGROUND

Many neurons synchronize their action potentials to the phase of local field potential (LFP) fluctuations in one or more frequency bands. Analyzing this spike-to-LFP synchronization is challenging, however, when neural spikes and LFP are generated in the same local circuit, because the spike's action potential waveform leak into the LFP and distort phase synchrony estimates. Existing approaches to address this spike bleed-through artifact relied on removing the average action potential waveforms of neurons, but this leaves artifacts in the LFP and distorts synchrony estimates.

NEW METHOD

We describe a spike-removal method that surpasses these limitations by decomposing individual action potentials into their frequency components before their removal from the LFP. The adaptively estimated frequency components allow for variable spread, strength and temporal variation of the spike artifact.

RESULTS

This adaptive approach effectively removes spike bleed-through artifacts in synthetic data with known ground truth, and in single neuron and LFP recordings in nonhuman primate striatum. For a large population of neurons with both narrow and broad action potential waveforms, the use of adaptive artifact removal uncovered 20-35 Hz beta and 35-45 Hz gamma band spike-LFP synchronization that would have remained contaminated otherwise.

COMPARISON WITH EXISTING METHODS

We demonstrate that adaptive spike-artifact removal cleans LFP data that remained contaminated when applying existing Bayesian and non-Bayesian methods of average spike-artifact removal.

CONCLUSIONS

Applying adaptive spike-removal from field potentials allows to estimate the phase at which neurons synchronize and the consistency of their phase-locked firing for both beta and low gamma frequencies. These metrics may prove essential to understand cell-to-circuit neuronal interactions in multiple brain systems.

Corticostriatal Oscillations Predict High vs. Low Drinkers in a Rat Model of Limited Access Alcohol Consumption

Individuals differ in their vulnerability to develop alcohol dependence, which is determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations and that these subgroups would differentially respond to corticostriatal brain stimulation. Male Sprague–Dawley rats (n = 13) were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able to predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Moreover, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p < 0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p > 0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.

Phase shifts in high-beta- and low-gamma-band local field potentials predict the focus of visual spatial attention

The local field potential (LFP) contains rich information about activity in local neuronal populations. However, it has been challenging to establish direct links between LFP modulations and task-relevant behavior or cognitive processes, such as attention. We sought to determine whether LFP amplitude or phase modulations are predictive of the allocation of visual spatial attention. LFPs were recorded simultaneously in multiple early visual brain structures of alert macaque monkeys performing attention-demanding detection and discrimination tasks. Attention directed toward the receptive field of recorded neurons generated systematically larger phase shifts in high-beta- and low-gamma-frequency LFPs compared with LFP phase shifts on trials in which attention was directed away from the receptive field. This attention-mediated temporal advance corresponded to ~10 ms. LFP phase shifts also correlated with reaction times when monkeys were engaged in the tasks. Importantly, attentional modulation of LFP phase was consistent across monkeys, tasks, visual brain structures, and cortical layers. In contrast, attentional modulation of LFP amplitude varied across frequency bands, visual structures/layers, and tasks. Because LFP phase shifts were robust, consistent, and predictive of spatial attention, they could serve as a reliable marker for attention signals in the brain. NEW & NOTEWORTHY Local field potentials (LFPs) reflect the activity of spatially localized populations of neurons. Whether alterations in LFP activity are indicative of cognitive processes, such as attention, is unclear. We found that shifts in the phase of LFPs measured in multiple visual brain areas reliably predicted the focus of spatial attention. LFP phase shifts could therefore serve as a marker for behaviorally relevant attention signals in the brain.

Top-Down Control of Alpha Phase Adjustment in Anticipation of Temporally Predictable Visual Stimuli

Alpha oscillations (8-14 Hz) are proposed to represent an active mechanism of functional inhibition of neuronal processing. Specifically, alpha oscillations are associated with pulses of inhibition repeating every ∼100 msec. Whether alpha phase, similar to alpha power, is under top-down control remains unclear. Moreover, the sources of such putative top-down phase control are unknown. We designed a cross-modal (visual/auditory) attention study in which we used magnetoencephalography to record the brain activity from 34 healthy participants. In each trial, a somatosensory cue indicated whether to attend to either the visual or auditory domain. The timing of the stimulus onset was predictable across trials. We found that, when visual information was attended, anticipatory alpha power was reduced in visual areas, whereas the phase adjusted just before the stimulus onset. Performance in each modality was predicted by the phase of the alpha oscillations previous to stimulus onset. Alpha oscillations in the left pFC appeared to lead the adjustment of alpha phase in visual areas. Finally, alpha phase modulated stimulus-induced gamma activity. Our results confirm that alpha phase can be top-down adjusted in anticipation of predictable stimuli and improve performance. Phase adjustment of the alpha rhythm might serve as a neurophysiological resource for optimizing visual processing when temporal predictions are possible and there is considerable competition between target and distracting stimuli.

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations

Neuromodulation-based interventions continue to be evaluated across an array of appetitive disorders but broader implementation of these approaches remains limited due to variable treatment outcomes. We hypothesize that individual variation in treatment outcomes may be linked to differences in the networks underlying these disorders. Here, Sprague-Dawley rats received deep brain stimulation separately within each nucleus accumbens (NAc) sub-region (core and shell) using a within-animal crossover design in a rat model of binge eating. Significant reductions in binge size were observed with stimulation of either target but with significant variation in effectiveness across individuals. When features of local field potentials (LFPs) recorded from the NAc were used to classify the pre-defined stimulation outcomes (response or non-response) from each rat using a machine-learning approach (lasso), stimulation outcomes could be classified with greater accuracy than expected by chance (effect sizes: core = 1.13, shell = 1.05). Further, these LFP features could be used to identify the best stimulation target for each animal (core vs. shell) with an effect size = 0.96. These data suggest that individual differences in underlying network activity may relate to the variable outcomes of circuit based interventions, and measures of network activity could have the potential to individually guide the selection of an optimal stimulation target to improve overall treatment response rates.

Gamma Oscillations in the Rat Ventral Striatum Originate in the Piriform Cortex

Local field potentials (LFPs) recorded from the human and rodent ventral striatum (vStr) exhibit prominent, behaviorally relevant gamma-band oscillations. These oscillations are related to local spiking activity and transiently synchronize with anatomically related areas, suggesting a possible role in organizing vStr activity. However, the origin of vStr gamma is unknown. We recorded vStr gamma oscillations across a 1.4 mm² grid spanned by 64 recording electrodes as male rats rested and foraged for rewards, revealing a highly consistent power gradient originating in the adjacent piriform cortex. Phase differences across the vStr were consistently small (<15°) and current source density analysis further confirmed the absence of local sink-source pairs in the vStr. Reversible occlusions of the ipsilateral (but not contralateral) nostril, known to abolish gamma oscillations in the piriform cortex, strongly reduced vStr gamma power and the occurrence of transient gamma-band events. These results imply that local circuitry is not a major contributor to gamma oscillations in the vStr LFP and that piriform cortex is an important driver of gamma-band oscillations in the vStr and associated limbic areas.SIGNIFICANCE STATEMENT The ventral striatum (vStr) is an area of anatomical convergence in circuits underlying motivated behavior, but it remains unclear how its inputs from different sources interact. A major proposal about how neural circuits may switch dynamically between convergent inputs is through temporal organization reflected in local field potential (LFP) oscillations. Our results show that, in the rat, the mechanisms controlling gamma-band oscillations in the vStr LFP are primarily located in the in the adjacent piriform cortex rather than in the vStr itself, providing a novel interpretation of previous rodent work on gamma oscillations in the vStr and related circuits and an important consideration for future work seeking to use oscillations in these areas as biomarkers for behavioral and neurological disorders.

Repeated Nicotine Strengthens Gamma Oscillations in the Prefrontal Cortex and Improves Visual Attention

Nicotine has strong addictive as well as procognitive properties. While a large body of research on nicotine continues to inform us about mechanisms related to its reinforcing effects, less is known about clinically relevant mechanisms that subserve its cognitive-enhancing properties. Understanding the latter is critical for developing optimal strategies for treating cognitive deficits. The primary brain region implicated in cognitive functions improved by nicotine is the prefrontal cortex (PFC). Here we assessed the impact of nicotine on unit activity and local field potential oscillations in the PFC of behaving rats. An acute dose of nicotine produced a predominantly inhibitory influence on population activity, a small increase in gamma oscillations, and a decrease in theta and beta oscillations. After a daily dosing regimen, a shift to excitatory-inhibitory balance in single-unit activity and stronger gamma oscillations began to emerge. This pattern of plasticity was specific to the gamma band as lower frequency oscillations were suppressed consistently across daily nicotine treatments. Gamma oscillations are associated with enhanced attentional capacity. Consistent with this mechanism, the repeat dosing regimen in a separate cohort of subjects led to improved performance in an attention task. These data suggest that procognitive effects of nicotine may involve development of enhanced gamma oscillatory activity and a shift to excitatory-inhibitory balance in PFC neural activity. In the context of the clinical use of nicotine and related agonists for treating cognitive deficits, these data suggest that daily dosing may be critical to allow for development of robust gamma oscillations.