Cortical Slow Oscillations Research Articles

Dorsal vs. ventral differences in fast Up-state-associated oscillations in the medial prefrontal cortex of the urethane-anesthetized rat.

Cortical slow oscillations (0.1-1 Hz), which may play a role in memory consolidation, are a hallmark of non-rapid eye movement (NREM) sleep and also occur under anesthesia. During slow oscillations the neuronal network generates faster oscillations on the active Up-states and these nested oscillations are particularly prominent in the PFC. In rodents the medial prefrontal cortex (mPFC) consists of several subregions: anterior cingulate cortex (ACC), prelimbic (PrL), infralimbic (IL), and dorsal peduncular cortices (DP). Although each region has a distinct anatomy and function, it is not known whether slow or fast network oscillations differ between subregions in vivo. We have simultaneously recorded slow and fast network oscillations in all four subregions of the rodent mPFC under urethane anesthesia. Slow oscillations were synchronous between the mPFC subregions, and across the hemispheres, with no consistent amplitude difference between subregions. Delta (2-4 Hz) activity showed only small differences between subregions. However, oscillations in the spindle (6-15 Hz)-, beta (20-30 Hz), gamma (30-80 Hz)-, and high-gamma (80-150 Hz)-frequency bands were consistently larger in the dorsal regions (ACC and PrL) compared with ventral regions (IL and DP). In dorsal regions the peak power of spindle, beta, and gamma activity occurred early after onset of the Up-state. In the ventral regions, especially the DP, the oscillatory power in the spindle-, beta-, and gamma-frequency ranges peaked later in the Up-state. These results suggest variations in fast network oscillations within the mPFC that may reflect the different functions and connectivity of these subregions.NEW & NOTEWORTHY We demonstrate, in the urethane-anesthetized rat, that within the medial prefrontal cortex (mPFC) there are clear subregional differences in the fast network oscillations associated with the slow oscillation Up-state. These differences, particularly between the dorsal and ventral subregions of the mPFC, may reflect the different functions and connectivity of these subregions.

FV 6. Striatal Microcircuit alterations in a mouse model of preclinical parkinsonism

Objective During recent years, extensive studies in different genetic model systems have complemented conventional toxin-based dopamine depletion approaches and significantly advanced our pathophysiological understanding of familial Parkinson’s disease (PD) from a molecular level to human clinical practice. One of the particular strengths of genetic models is that they open experimental windows to hitherto inaccessible presymptomatic periods in PD, allowing for an investigation of functional changes and adaptive mechanisms during very early phases of this complex neurodegenerative disorder. Mice with a loss-of-function mutation in the parkin-encoding PARK2 gene (a frequent cause of young-onset, autosomal recessive PD) display no motor symptoms, show no appreciable dopaminergic neurodegeneration but exhibit abnormalities of striatal dopaminergic neurotransmission and impaired signalling at the cortico-striatal synapse. Here, we set out to determine whether and how loss of parkin function affects neuronal activity in cortex-basal ganglia networks in vivo. Methods To dissect the cortico-striato-pallidal circuitry in this premanifest model of PD, we performed simultaneous microelectrode recordings in motor cortex, striatum and globus pallidus of anesthetized parkin-mutant mice and controls. Results Based on electrophysiological criteria of striatal single unit activity, we identified several presumably different striatal cell types: Medium spiny projection neurons (pMSN), tonically active neurons (pTAN – corresponding to cholinergic interneurons) and fast spiking interneurons (pFSI – a subpopulation of GABAergic interneurons). In transgenic mice, pTANs displayed significantly increased activity levels, while pFSIs showed reduced discharge rates compared to controls. Furthermore, we found evidence for a disrupted functional connectivity within the striatal FSI microcircuit. In line with the absence of motor symptoms, we observed no changes in the ongoing discharge characteristics of transgenic pMSNs and pallidal neurons. Phase locking analysis revealed elevated and phase-shifted phase coupling to slow (1–3 Hz) cortical local field potential oscillations. Unexpectedly, local field potentials recorded from striatum and globus pallidus of parkin-mutant mice robustly exhibited amplified beta oscillations. Notably, the subgroup of pFSIs showed a selective enhancement of phase coupling to these beta oscillations. Conclusions Our findings suggest that loss of parkin function leads to amplifications of synchronized cortico-striatal oscillations in multiple frequency ranges and an intrastriatal reconfiguration of interneuronal circuits. This presymptomatic disarrangement of striatal dynamic functional connectivity may precede nigrostriatal neurodegeneration and predispose to imbalance of striatal outflow accompanying symptomatic PD.

7. Thalamic mechanisms in the generation and modulation of the cortical slow oscillation in mice

It is well established that thalamus plays a crucial role in the generation of the synchronous slow oscillation in the cortex during non-REM sleep. The slow/delta power (0.2–4 Hz) is the main measured factor of the quality of sleep. However, the contribution of different thalamic nuclei to the inception of the slow wave activities and its synchronization is not known. We hypothesized that the first-order (specific) thalamic nuclei provide a control of slow waves in primary cortical areas, while higher-order (non-specific) thalamic nuclei may synchronize the slow-wave activities across wide cortical regions. We analyzed local field potentials and spiking activities from different cortical and thalamic areas of anesthetized mice while a thalamic nucleus was inactivated by the GABA-agonist muscimol. Extracellular multiunit recordings in first-order (VPM, VL) and higher-order (PO, CL) thalamic nuclei show dramatically decreased spiking activity and strongly reduced burst firing after inactivation. We conclude that the injection of muscimol strongly reduced the spiking activity and does not potentiate the generation of low-threshold spike mediated bursts. Inactivation of specific thalamic nuclei with muscimol decreased the slow/delta power in the corresponding primary cortical area. The inactivation of a non-specific nucleus with muscimol significantly reduced the delta power in all investigated cortical. Our experiments demonstrate that the thalamus is required for the fine tuning of the cortical slow oscillation. Supported by CIHR and NSERC.

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the role of slow oscillations, 0.2-1 Hz rhythmic transitions between Up and Down states during stage 3/4 sleep, on dynamics of synaptic connectivity in the thalamocortical network model implementing spike-timing-dependent synaptic plasticity. We found that the spatiotemporal pattern of Up-state propagation determines the changes of synaptic strengths between neurons. Furthermore, an external input, mimicking hippocampal ripples, delivered to the cortical network results in input-specific changes of synaptic weights, which persisted after stimulation was removed. These synaptic changes promoted replay of specific firing sequences of the cortical neurons. Our study proposes a neuronal mechanism on how an interaction between hippocampal input, such as mediated by sharp wave-ripple events, cortical slow oscillations, and synaptic plasticity, may lead to consolidation of memories through preferential replay of cortical cell spike sequences during slow-wave sleep. Sleep is critical for memory and learning. Replay during sleep of temporally ordered spike sequences related to a recent experience was proposed to be a neuronal substrate of memory consolidation. However, specific mechanisms of replay or how spike sequence replay leads to synaptic changes that underlie memory consolidation are still poorly understood. Here we used a detailed computational model of the thalamocortical system to report that interaction between slow cortical oscillations and synaptic plasticity during deep sleep can underlie mapping hippocampal memory traces to persistent cortical representation. This study provided, for the first time, a mechanistic explanation of how slow-wave sleep may promote consolidation of recent memory events.

Temporal Prediction in lieu of Periodic Stimulation.

Predicting not only what will happen, but also when it will happen is extremely helpful for optimizing perception and action. Temporal predictions driven by periodic stimulation increase perceptual sensitivity and reduce response latencies. At the neurophysiological level, a single mechanism has been proposed to mediate this twofold behavioral improvement: the rhythmic entrainment of slow cortical oscillations to the stimulation rate. However, temporal regularities can occur in aperiodic contexts, suggesting that temporal predictions per se may be dissociable from entrainment to periodic sensory streams. We investigated this possibility in two behavioral experiments, asking human participants to detect near-threshold auditory tones embedded in streams whose temporal and spectral properties were manipulated. While our findings confirm that periodic stimulation reduces response latencies, in agreement with the hypothesis of a stimulus-driven entrainment of neural excitability, they further reveal that this motor facilitation can be dissociated from the enhancement of auditory sensitivity. Perceptual sensitivity improvement is unaffected by the nature of temporal regularities (periodic vs aperiodic), but contingent on the co-occurrence of a fulfilled spectral prediction. Altogether, the dissociation between predictability and periodicity demonstrates that distinct mechanisms flexibly and synergistically operate to facilitate perception and action.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans.

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5–1.0Hz) and thalamic spindles (12–15Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Closed-loop transcranial alternating current stimulation of slow oscillations

Abstract Transcranial alternating current stimulation (tACS) is an emerging non-invasive tool for modulating brain oscillations. There is evidence that weak oscillatory electrical stimulation during sleep can entrain cortical slow oscillations to improve the memory consolidation in rodents and humans. Using a novel method and a custom built stimulation device, automatic stimulation of slow oscillations in-phase with the endogenous activity in a real-time closed-loop setup is possible. Preliminary data from neuroplasticity experiments show a high detection performance of the proposed method, electrical measurements demonstrate the outstanding quality of the presented stimulation device.

4-Hz Transcranial Alternating Current Stimulation Phase Modulates Hearing.

Non-invasive brain stimulation with transcranial alternating currents (tACS) has been shown to entrain slow cortical oscillations and thereby influence various aspects of visual perception. Much less is known about its potential effects on auditory perception. In the present study, we apply a novel variant that enables near-equivalent stimulation of both auditory cortices to investigate the causal role of the phase of 4-Hz cortical oscillations for auditory perception. We measured detection performance for near-threshold auditory stimuli (4-Hz click trains) that were presented at various moments during ongoing tACS (two synchronous 4-Hz alternating currents applied transcranially to the two cerebral hemispheres). We found that changes in the relative timing of acoustic and electric stimulation cause corresponding perceptual changes that oscillate predominantly at the 4-Hz frequency of the electric stimulation, which is consistent with previous results based on 10-Hz tACS. TACS at various frequencies can affect auditory perception. Together with converging previous results based on acoustic stimulation (rather than tACS), this finding implies that fundamental aspects of auditory cognition are mediated by the temporal coherence of sound-induced cortical activity with ongoing cortical oscillations at multiple time scales.

Slow cortical rhythms: from single-neuron electrophysiology to whole-brain imaging in vivo.

The slow cortical oscillation is the major brain rhythm occurring during sleep, and has been the object of thorough investigation for over thirty years. Despite all these efforts, the function and the neuronal mechanisms behind slow cortical rhythms remain only partially understood. In this review we will provide an overview of the techniques available for the in vivo study of slow cortical oscillations in animal models. Our goal is to provide an up to date resource for the selection of the best experimental strategies to study specific aspects of slow oscillations. We will cover both traditional, population-level electrophysiological approaches (electroencephalography - EEG, local field potentials) as well as more recent techniques, such as two photon calcium imaging and optogenetics. Overall, we believe that new breakthroughs in our understanding of slow cortical rhythms will require the integration of different techniques, to bridge the gap between different spatio-temporal scales and go from a correlative to a causal level of analysis.

Characterization of K-complexes and slow wave activity in a neural mass model.

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.

Cortical network switching: possible role of the lateral septum and cholinergic arousal.

Cortical networks undergo large-scale switching between states of increased or decreased activity in normal sleep and cognition as well as in pathological conditions such as epilepsy. We previously found that focal hippocampal seizures in rats induce increased neuronal firing and cerebral blood flow in subcortical structures including the lateral septal area, along with frontal cortical slow oscillations resembling slow wave sleep. In addition, stimulation of the lateral septum in the absence of a seizure resulted in cortical deactivation with slow oscillations. We hypothesized that lateral septal activation might cause neocortical deactivation indirectly, possibly through impaired subcortical arousal. But how does subcortical stimulation cause slow wave activity in frontal cortex? How do arousal neurotransmitter levels (e.g. acetylcholine) change in cortex during the excitation of inhibitory projection nuclei? In the current study, we used simultaneous electrophysiology and enzyme-based amperometry in a rat model, and found a decrease in choline, along with slow wave activity in orbital frontal cortex during lateral septal stimulation in the absence of seizures. In contrast, the choline signal and local field potential in frontal cortex had no significant changes when stimulating the hippocampus, but showed increased choline and decreased slow wave activity with an arousal stimulus produced by toe pinch. These findings indicate that the activation of subcortical inhibitory structures (such as lateral septum) can depress subcortical cholinergic arousal. This mechanism may play an important role in large-scale transitions of cortical activity in focal seizures, as well as in normal cortical function.

Reactivating Memories during Sleep by Odors: Odor Specificity and Associated Changes in Sleep Oscillations

Memories are reactivated during sleep. Re-exposure to olfactory cues during sleep triggers this reactivation and improves later recall performance. Here, we tested if the effects of odor-induced memory reactivations are odor-specific, that is, requiring the same odor during learning and subsequent sleep. We also tested whether odor-induced memory reactivation affects oscillatory EEG activity during sleep, as a putative mechanism underlying memory processing during sleep. Participants learned a visuospatial memory task under the presence of an odor. During subsequent SWS, the same odor, a different odor, or an odorless vehicle was presented. We found that odor re-exposure during sleep significantly improves memory only when the same odor was presented again, whereas exposure to a new odor or the odorless vehicle had no effect. The memory-enhancing effect of the congruent odor was accompanied by significant increases in frontal delta (1.5-4.5 Hz) and parietal fast spindle (13.0-15.0 Hz) power as well as by an increased negative-to-positive slope of the frontal slow oscillation. Our results indicate that odor-induced memory reactivations are odor specific and trigger changes in slow-wave and spindle power possibly reflecting a bottom-up influence of hippocampal memory replay on cortical slow oscillations as well as thalamo-cortical sleep spindles.

Hippocampal replay and cortical slow oscillations: a computational study

Sleep is known to be important for memory consolidation [1], and memories are thought to be stored in the hippocampus during the wakefulness and “transferred” to cortex during sleep [2]. Recently, memory replay – repeatable sequences of pyramidal cell firing – has been demonstrated during sleep, and associated with characteristic brain oscillations, giving rise to the hypothesis that these may form the critical neural substrate of memory consolidation. Tampering with replay can disrupt memory formation and consolidation [3], and the mechanisms underlying sequence replay are still unknown. During sleep, replay events are associated with specific patterns of neuronal activity. Replay is seen in cortex during sleep oscillation – a rhythmic ( 150 Hz) firing [4]. It is believed that hippocampal ripples may contribute to the cortical active state generation, however specific interactions between ripples and slow oscillation remain unknown. In the present study, build on our previous research [5], we develop a model of ripple generation to explore interaction between cortical slow oscillation and hippocampal ripples during sleep. Data suggest that during ripple events only a few pyramidal (excitatory) cells are recruited in CA1, and they spike at the peak of the event, while perisomatic interneurons (a kind of inhibitory cells) spike across the duration of the event [6]. The distribution of spike timing with respect to ripple peak is different for different types of interneurons. In hippocampal area CA1, axo-axonic cells tend to spike at ripple initiation and be suppressed in the later part of a ripple [7]. Since axo-axonic cells are in a crucial position to suppress the spikes of the pyramidal cell they impinge upon, we hypothesize that they can regulate the initiation of specific cell activity replay. In this study we designed a computational model of ripple generation that emphasizes the role of axo-axonic cells in selecting which pyramidal cells are participating in ripple activity, hence what sequence is replayed during a given ripple. In our model, high-frequency firing of the perisomatic interneurons mediate high-frequency LFP oscillations in pyramidal neurons while axo-axonic interneurons define specific sequence of pyramidal cell firing. Using such model, we investigate the timing relationship between cortical slow-wave oscillations and hippocampal ripples. Our study proposes a novel mechanism of hippocampal ripple generation and predicts how interactions between different electrographic events during sleep may contribute to coordinated replay in cortical and hippocampal networks.

The dynamic separation of pallidal neurons into anti-phase oscillatory groups under Parkinsonian conditions in a computational model

Neurons in the globus pallidus (GP) of urethane anesthetized rats typically display one of four spiking patterns: tonic, non-modulated, firing (the NM group); firing that occurs preferentially during either the active or inactive phases of slow cortical oscillations (TA or TI group, respectively); or silence/quiescence (QU group). In healthy animals the vast majority of neurons are in the non-modulated group. However, under conditions of experimentally-induced Parkinsonism there is a dramatic increase in the number of neurons whose firing patterns show modulation by the slow cortical rhythm, either in-phase or anti-phase [1]. The mechanism that underlies the increased tendency for GP neurons to become entrained by cortical rhythms is unclear, but it may contribute to some of the motor symptoms of Parkinson’s disease. There are two main pathways from the cortex to the GP: via the inhibitory striatum and via the excitatory subthalamic nucleus (STN), but it is not known how these inputs sculpt the pathological pallidal firing patterns. To study this we developed a neural network model of single compartment conductance-based (Hodgkin-Huxley) pallidal neurons, based on a previous multi-compartment model [2]. The GP neurons received rhythmic input from STN neurons and reciprocal inhibition from each other. Under “healthy” conditions, almost all model GP neurons showed tonic firing that was not significantly modulated by the rhythmic STN input (Figure 1A,B). We attempted to model “Parkinsonian” conditions by increasing the intensity of STN neuron firing and the strength of STN-GP and GP-GP synapses. Under these conditions, two groups of anti-phase oscillatory GP neurons emerged (Figure 1C,D). Our model also includes downregulation of Hyperpolarization activated Cyclic Nucleotide-gated (HCN) channels in response to bursting, since this may contribute to emergence of Parkinsonian activity [3]. We found that this provides better agreement with experimental data but that it is not essential in order for the two groups to appear. Figure 1 Proportions of neurons in each category (A,C) and spiking activity sorted by classification confidence (B,D) for healthy (left) and Parkinsonian (right) parameters. Our results [4] support the hypothesis that oscillatory entrainment occurs primarily via the subthalamic pathway. We find that as a result of the interplay between excitatory input from the STN and mutual inhibition between GP neurons, the network shows a self-organizing dynamical behavior where two groups of neurons (TI and TA) emerge out of a homogeneous population.

Rapid developmental emergence of stable depolarization during wakefulness by inhibitory balancing of cortical network excitability.

The ability to generate behaviorally appropriate cortical network states is central to sensory perception and plasticity, but little is known about the timing and mechanisms of their development. I paired intracellular and extracellular recordings in the visual cortex of awake infant rats to determine the synaptic and circuit mechanisms regulating the development of a key network state, the persistent and stable subthreshold membrane potential (Vm) depolarization associated with wakefulness/alertness in cortical networks, called the "desynchronized" or "activated" state. Current-clamp recordings reveal that the desynchronized state is absent during the first 2 postnatal weeks, despite behavioral wakefulness. During this period, Vm remains at the resting membrane potential >80% of the time, regardless of behavioral state. Vm dynamics during spontaneous or light-evoked activity were highly variable, contained long-duration supratheshold plateau potentials, and high spike probability, suggesting an unstable and hyperexcitable early cortical network. Voltage-clamp recordings reveal that effective feedforward inhibition is absent at these early ages despite the presence of feedback inhibition. Stable membrane depolarization during wakefulness finally emerges 1-2 d before eye opening and is statistically indistinguishable from that in adults within days. Reduced cortical excitability, fast feedforward inhibition, and the slow cortical oscillation appear simultaneously with stable depolarization, suggesting that an absence of inhibitory balance during early development prevents the expression of the active state and hence a normal wakeful state in early cortex. These observations identify feedforward inhibition as a potential key regulator of cortical network activity development.

Distinct slow and fast cortical theta dynamics in episodic memory retrieval

Brain oscillations in the theta frequency band (3–8Hz) have been shown to be critically involved in human episodic memory retrieval. In prior work, both positive and negative relationships between cortical theta power and retrieval success have been reported. This study examined the hypothesis that slow and fast cortical theta oscillations at the edges of the traditional theta frequency band are differentially related to retrieval success. Scalp EEG was recorded in healthy human participants as they performed a cued-recall episodic memory task. Slow (~3Hz) and fast (~7Hz) theta oscillations at retrieval were examined as a function of whether an item was recalled or not and as a function of the items' output position at test. Recall success typically declines with output position, due to increases in interference level. The results showed that slow theta power was positively related but fast theta power was negatively related to retrieval success. Concurrent positive and negative episodic memory effects for slow and fast theta oscillations were dissociable in time and space, showing different time courses and different spatial locations on the scalp. Moreover, fast theta power increased from early to late output positions, whereas slow theta power was unaffected by items' output position. Together with prior work, the results suggest that slow and fast theta oscillations have distinct functional roles in episodic memory retrieval, with slow theta oscillations being related to processes of recollection and conscious awareness, and fast theta oscillations being linked to processes of interference and interference resolution.

NREM and REM Sleep

The overall function of sleep is hypothesized to provide “recovery” after preceding waking activities, thereby ensuring optimal functioning during subsequent wakefulness. However, the functional significance of the temporal dynamics of sleep, manifested in the slow homeostatic process and the alternation between non–rapid eye movement (NREM) and REM sleep remains unclear. We propose that NREM and REM sleep have distinct and complementary contributions to the overall function of sleep. Specifically, we suggest that cortical slow oscillations, occurring within specific functionally interconnected neuronal networks during NREM sleep, enable information processing, synaptic plasticity, and prophylactic cellular maintenance (“recovery process”). In turn, periodic excursions into an activated brain state—REM sleep—appear to be ideally placed to perform “selection” of brain networks, which have benefited from the process of “recovery,” based on their offline performance. Such two-stage modus operandi of the sleep process would ensure that its functions are fulfilled according to the current need and in the shortest time possible. Our hypothesis accounts for the overall architecture of normal sleep and opens up new perspectives for understanding pathological conditions associated with abnormal sleep patterns.

A model for low-frequency bursts in subthalamic nucleus neurons

Burst firing in subthalamic nucleus (STN) has been suggested to be highly associated with the motor symptoms in Parkinson’s disease, which result from a loss of dopamine. Although it is clinically very important to clarify the mechanism underlying the bursting dynamics, complex interactions between STN and other brain areas make it difficult to understand. In anesthetized rats, STN neurons exhibit low-frequency ( 1 Hz) bursts, which are synchronous with cortical slow oscillations and are significantly strengthened by dopamine depletion. To reproduce these low-frequency bursts, we examine a conductance-based model of an STN neuron that includes NMDA-type glutamatergic inputs reflecting cortical oscillations. In addition, the neuron model contains GABAergic inhibitory inputs, which are assumed to result from the activities of globus pallidus (GP). We show that the STN neuron model can reproduce low-frequency bursts synchronized with cortical activity, in the presence of GABAergic inhibition. In addition, we demonstrate that increased GABA activity leads to enhanced burstiness whereas increased NMDA conductances mainly augment STN firing rate. The induction of burst firing additionally decreases the coherence between STN and cortical activities. These results may give insights into how the complicated interactions between the STN, cortex, and GP can modulate the dynamics of bursting oscillations in the basal ganglia.

OP 9. Tailoring transcranial current stimulation to modulate cortical oscillations in computer simulations, ferrets, and humans

Non-invasive transcranial current stimulation (TCS) has emerged as a highly promising therapeutic neuromodulation approach for a broad range of neurological and psychiatric illnesses. The majority of TCS studies are performed with direct current (tDCs). TCS with sine-wave stimulation waveforms (tACs) represents an attractive alternative to enhance cortical oscillations ( Marshall et al., 2006 ). Yet, little is known about how weak sine-wave electric fields interact with endogenous network dynamics ( Frohlich and McCormick, 2010 ). We hypothesize that more closely matching stimulation waveforms to ongoing cortical activity may increase and focus the effect of electrical stimulation. We utilized a multi-technique approach to determine the interaction dynamics between endogenous cortical activity and applied sine-wave stimulation (large-scale computer simulations, in vivo ferret animal model, awake healthy human subjects). Large-scale computer simulations of cortical networks (Izhikevich neuron models, pyramidal cells and fast-spiking inhibitory interneurons) were performed with CUDA-enhanced, custom-written C. TCS was modeled by injection of electric current equal to that caused by application of the electric field. tACs of varying frequencies and tDCs were used to elucidate the underlying mechanisms of how global weak pertubations of the membrane voltage interact with macroscopic network dynamics. An animal model with a gyrencephalic cortex was used to test tACs in vivo. Isoflurane/xylazine anesthesia induced slow endogenous cortical oscillations. tACs matching intrinsic activity from 0.5 to 2 Hz (in steps of 0.5 Hz) was applied transcranially. Extracellular electrophysiology was conducted to measure modulation of oscillation structure. A pre-clinical study in awake, healthy human subjects assessed differential effects of 0.75 and 40 Hz tACs stimulation. Subjects ( N = 16) were fitted with EEG electrodes and two 5 × 7 cm TCS electrodes. Each subject underwent three sessions of tACs (active sham, 0.75 Hz: frequency did not match intrinsic activity of awake subjects, 40 Hz: frequency matched ongoing activity). Five blocks of stimulation (five minutes each) were interleaved with 1-min blocks of EEG recordings. The computational simulations revealed tACs frequencies matched to intrinsic oscillations require the lowest amplitude to achieve entrainment. tACs was more effective than tDCs at entrainment. Entrainment of endogenous oscillations by weak global perturbations is mediated by a non-linear threshold effect where stimulation increases the number of “hotspots” that give rise to network-wide activation patterns. tACs in ferrets increased oscillation power at the frequency matched to stimulation. In our human study, we found that 40 Hz tACs targets ongoing oscillations in the awake cortex more specifically than 0.75 Hz tACs. 40 Hz tACs amplifies the balance between resting and activated states mediated by alpha and gamma oscillations (ratio of normalized stimulation effect to sham: alpha = .944, p = .027; gamma = 1.08, p = .022). Our computer simulations, in vivo animal experiments, and pre-clinical human trial demonstrate that tACs has the potential to become an effective modulator of cortical oscillations, particularly when stimulation frequency is matched to ongoing endogenous cortical oscillations.

Dynamic Interaction of Spindles and Gamma Activity during Cortical Slow Oscillations and Its Modulation by Subcortical Afferents

Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations.