Brain State-dependency Research Articles

Neuropharmacology and brain-state dependence: a review of the extant literature on these two potent aspects of TMS effects on the brain.

Neuropharmacology and brain-state dependence: a review of the extant literature on these two potent aspects of TMS effects on the brain.

Combined transcranial direct current stimulation and psychological interventions: State of the art and promising perspectives for clinical psychology

Recent literature shows great heterogeneity in the reported efficacy of transcranial direct current stimulation (tDCS) as a stand-alone psychiatric treatment. Aiming to increase its efficacy, tDCS has been combined with psychological interventions. Our state-of-the-art overview of such combined treatment trials indicates, however, that these usually do not elicit synergistic clinical effects. We therefore explored more basic mechanisms related to the brain state-dependency of tDCS. Importantly, based on our overview, the efficacy of combined interventions may depend on whether individual patients present with endophenotypes that are implicated in the development and maintenance of psychopathology, such as prefrontal-mediated cognitive dysfunction. We discuss how future studies may contribute to the development of personally-tailored dual active treatments by adhering to the Research Domain Criteria (RDoC) framework. RDoC-based mechanistic research may reveal alternative neural circuits that should be functionally targeted by both tDCS and psychological interventions, with promising avenues for clinical psychological science and practice.

The impact of pathological high-frequency oscillations on hippocampal network activity in rats with chronic epilepsy.

In epilepsy, brain networks generate pathological high-frequency oscillations (pHFOs) during interictal periods. To understand how pHFOs differ from normal oscillations in overlapping frequency bands and potentially perturb hippocampal processing, we performed high-density single unit and local field potential recordings from hippocampi of behaving rats with and without chronic epilepsy. In epileptic animals, we observed two types of co-occurring fast oscillations, which by comparison to control animals we could classify as 'ripple-like' or 'pHFO'. We compared their spectral characteristics, brain state dependence, and cellular participants. Strikingly, pHFO occurred irrespective of brain state, were associated with interictal spikes, engaged distinct subnetworks of principal neurons compared to ripple-like events, increased the sparsity of network activity, and initiated both general and immediate disruptions in spatial information coding. Taken together, our findings suggest that events that result in pHFOs have an immediate impact on memory processes, corroborating the need for proper classification of pHFOs to facilitate therapeutic interventions that selectively target pathological activity.

Layer-Specific Physiological Features and Interlaminar Interactions in the Primary Visual Cortex of the Mouse

SummaryThe relationship between mesoscopic local field potentials (LFPs) and single-neuron firing in the multi-layered neocortex is poorly understood. Simultaneous recordings from all layers in the primary visual cortex (V1) of the behaving mouse revealed functionally defined layers in V1. The depth of maximum spike power and sink-source distributions of LFPs provided consistent laminar landmarks across animals. Coherence of gamma oscillations (30–100 Hz) and spike-LFP coupling identified six physiological layers and further sublayers. Firing rates, burstiness, and other electrophysiological features of neurons displayed unique layer and brain state dependence. Spike transmission strength from layer 2/3 cells to layer 5 pyramidal cells and interneurons was stronger during waking compared with non-REM sleep but stronger during non-REM sleep among deep-layer excitatory neurons. A subset of deep-layer neurons was active exclusively in the DOWN state of non-REM sleep. These results bridge mesoscopic LFPs and single-neuron interactions with laminar structure in V1.

Brain state dependency of corticospinal excitability

Brain state dependency of corticospinal excitability

Brain State Dependence of Hippocampal Subthreshold Activity in Awake Mice

Monitoring the membrane potential of individual neurons has uncovered how single-cell properties contribute to network processing across different brain states in neocortex. In contrast, the subthreshold modulation of hippocampal neurons by brain state has not been systematically characterized. Toaddress this, we combined whole-cell recordingsfrom dentate granule cells and CA1 pyramidal neurons with multisite extracellular recordings and behavioral measurements in awake mice. We show that the average membrane potential, amplitude of subthreshold fluctuations, and distance to spike threshold are all modulated by brain state. Furthermore, even within individual states, rapid variations in arousal are reflected in membrane potential fluctuations. These factors produce depolarizing ramps in the membrane potential of hippocampal neurons that precede ripples and mirror transitions to a network regime conducive for ripple generation. These results suggest that there are coordinated shifts in the subthreshold dynamics of individual neurons that underlie the transitions between distinct modes of hippocampal processing.

Commentary: On the possible role of stimulation duration for after-effects of transcranial alternating current stimulation.

In their recent article, Struber et al. (2015) demonstrate that 1s application of transcranial alternating current stimulation (tACS) do not lead to any significant changes in the phase and amplitude of the electroencephalogram (EEG) signal. Therefore, they concluded that it is too short to induce synaptic plasticity. This is a very important observation that sheds light on possible underlying mechanisms of tACS. Although the results clearly show the absence of certain specific tACS-induced electrophysiological after-effects when applied only for 1s, some additional considerations need to be made in order to fully interpret these null results as well as probe the mechanism of tACS at shorter timescales. An important question is whether at these smaller time scales, the lack of prolonged entrainment during the post stimulation session necessarily reflect a lack of tACS efficacy. Alternatively, these results might also suggest that for 1s stimulation paradigms, we are simply looking at the wrong electrophysiological measure. At these smaller time scales, changes in measures such as spike rate adaptation (Fernandez et al., 2011; Kar and Krekelberg, 2014), spike time precision (Reato et al., 2010), neurovascular coupling (Zheng et al., 2011; Kar and Wright, 2014) are likely to be more relevant for behavioral aftereffects. The EEG signal typically comprises of synchronized oscillations across the superficial cortex (for review, see Buzsaki et al., 2012). Hence it might be more sensitive to changes in entrainment whereas much less sensitive to these subtle effects (which might also still be behaviorally relevant). However, some of these changes might indeed be a result of changes in short-term synaptic plasticity (which is a very broad term). It must however be noted that the aforementioned mechanisms could also be a direct result of network entrainment during tACS but lack entrainment related features in the EEG measured at the scalp in the post tACS session. One way to test this hypothesis further, would be to use the method introduced by Helfrich et al. (2014) to remove the tACS-induced artifacts for the 1s tACS period, and estimate changes in EEG during stimulation. This would be very informative to test whether tACS applied at the individual alpha frequency (IAF) for 1s could entrain the underlying cortex at all. Then we would be able to say whether the lack of effect is despite similar entrainment during tACS. The effects of tACS on the underlying cortex often depends on the presence of an experimental task that actively recruits the underlying brain area or otherwise, produces a specific brain state. For instance, Kar and Krekelberg (2014) demonstrated, that tACS induced changes in human motion discrimination performance is only present when tACS was paired with the visual motion stimulus. Ten Hertz tACS applied for 4s reduced the after-effects of motion adaptation and the effects scaled with how much adaptation there was to begin with. Similarly, Feurra et al. (2013) also demonstrated the state dependent effects of tACS on the motor cortex. Given this brain state dependency of the tACS induced effects, it remains unclear whether the lack of tACS-induced aftereffect reported in the study could be due to an absence of an appropriate brain state in the stimulated area. In this regard, it might be interesting to probe the brain areas while doing a relevant task. Choosing the stimulation intensity is also a key consideration during tACS studies (Groppa et al., 2010). However, it is crucial to consider the confounding aspects of tACS-induced phosphenes (Kar and Krekelberg, 2012) and tactile sensations (Feurra et al., 2011). I argue that lower stimulation amplitudes might not necessarily control for phosphenes and these low amplitudes might fail to induce the desired cortical effects (entrainment). First, the accuracy of the threshold values are highly depended on the sensitivity of the adaptive method used to estimate them. In addition, we can never rule out the effects of subthreshold retinal stimulation during tACS. Hence, it is important to consider other strategies to design control experiments to rule out general effects of tACS (phosphenes, tactile sensations, reduced/increased arousal etc.). Some recent studies have used brain laterization to test their hypotheses (Kar and Krekelberg, 2014). But, given the large current spread during tACS and asymmetries between the two hemispheres of the human brain, this is not always feasible. Therefore, control strategies remain a challenging issue for tACS experiments. The Struber et al. (2015) study provides a lead into the hypothesis that tACS mechanisms vary according to stimulation duration. This can be addressed in future experiments, where the stimulation duration can be varied as an independent variable to systematically map out its relationship with the boost in entrainment, changes in coherence and other short-term plasticity related changes.

State-Dependent Perceptual Learning

Learning constitutes a fundamental property of the human brain-yet an unresolved puzzle is the profound variability of the learning success between individuals. Here we highlight the relevance of individual ongoing brain states as sources of the learning variability in exposure-based somatosensory perceptual learning. Electroencephalogram recordings of ongoing rhythmic brain activity before and during learning revealed that prelearning parietal alpha oscillations as well as during-learning stimulus-induced contralateral central alpha changes are predictive for the learning outcome. These two distinct alpha rhythm sources predicted up to 64% of the observed learning variability, one source representing an idling state with posteroparietal focus and a potential link to the default mode network, the other representing the sensorimotor mu rhythm, whose desynchronization is indicative for the degree of engagement of sensorimotor neuronal populations during application of the learning stimuli. Unspecific effects due to global shifts of attention or vigilance do not explain our observations. Our study thus suggests a brain state-dependency of perceptual learning success in humans opening new avenues for supportive learning tools in the clinical and educational realms.

Relationships between the firing of identified striatal interneurons and spontaneous and driven cortical activities in vivo.

The striatum is comprised of medium-sized spiny projection neurons (MSNs) and several types of interneuron, and receives massive glutamatergic input from the cerebral cortex. Understanding of striatal function requires definition of the electrophysiological properties of neurochemically identified interneurons sampled in the same context of ongoing cortical activity in vivo. To address this, we recorded the firing of cholinergic interneurons (expressing choline acetyltransferase; ChAT) and GABAergic interneurons expressing parvalbumin (PV) or nitric oxide synthase (NOS), as well as MSNs, in anesthetized rats during cortically defined brain states. Depending on the cortical state, these interneurons were partly distinguished from each other, and MSNs, on the basis of firing rate and/or pattern. During slow-wave activity (SWA), ChAT+ interneurons, and some PV+ and NOS+ interneurons, were tonically active; NOS+ interneurons fired prominent bursts but, contrary to investigations in vitro, these were not typical low-threshold spike bursts. Identified MSNs, and other PV+ and NOS+ interneurons, were phasically active. Contrasting with ChAT+ interneurons, whose firing showed poor brain state dependency, PV+ and NOS+ interneurons displayed robust firing increases and decreases, respectively, upon spontaneous or driven transitions from SWA to cortical activation. The firing of most neurons was phase locked to cortical slow oscillations, but only PV+ and ChAT+ interneurons also fired in time with cortical spindle and gamma oscillations. Complementing this diverse temporal coupling, each interneuron type exhibited distinct responses to cortical stimulation. Thus, these striatal interneuron types have distinct temporal signatures in vivo, including relationships to spontaneous and driven cortical activities, which likely underpin their specialized contributions to striatal microcircuit function.

Brain State-Dependence of Electrically Evoked Potentials Monitored With Head-Mounted Electronics

Inferring changes in brain connectivity is critical to studies of learning-related plasticity and stimulus-induced conditioning of neural circuits. In addition, monitoring spontaneous fluctuations in connectivity can provide insight into information processing during different brain states. Here, we quantified state-dependent connectivity changes throughout the 24-h sleep-wake cycle in freely behaving monkeys. A novel, head-mounted electronic device was used to electrically stimulate at one site and record evoked potentials at other sites. Electrically evoked potentials (EEPs) revealed the connectivity pattern between several cortical sites and the basal forebrain. We quantified state-dependent changes in the EEPs. Cortico-cortical EEP amplitude increased during slow-wave sleep, compared to wakefulness, while basal-cortical EEP amplitude decreased. The results demonstrate the utility of using portable electronics to document state-dependent connectivity changes in freely behaving primates.

Brain State Dependent Postinhibitory Rebound in Entorhinal Cortex Interneurons

Postinhibitory rebound (PIR) is believed to play an important role in the genesis and maintenance of biological rhythms. While it has been demonstrated during several in vitro studies, in vivo evidence for PIR remains scarce. Here, we report that PIR can be observed in the dorsomedial entorhinal cortex of anesthetized rats, mostly between putatively connected GABAergic interneurons, and that it is more prevalent during the theta (4-6 Hz) oscillation state than the slow (0.5-2 Hz) oscillation state. Functional inhibition was also found to be brain state and postsynaptic cell type dependent but that alone could not explain this brain state dependence of PIR. A theoretical analysis, using two Fitzhugh-Nagumo neurons coupled to an external periodic drive, predicted that the modulation of a faster spiking rate by the slower periodic drive could account for the brain state dependence of PIR. Model predictions were verified experimentally. We conclude that PIR is cell type and brain state dependent and propose that this could impact network synchrony and rhythmogenesis.

Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans.

Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (∼0.75 Hz) during non-rapid eye movement sleep (NonREM) sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS) oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS) is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8–12 Hz) and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25–45 Hz) activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies.

Brain State-Dependence of Coherent Oscillatory Activity along the Cortico-Striatal Axis of the Rat

Brain State-Dependence of Coherent Oscillatory Activity along the Cortico-Striatal Axis of the Rat

Brain state-dependency of coherent oscillatory activity in the cerebral cortex and basal ganglia of the rat.

The nature of the coupling between neuronal assemblies in the cerebral cortex and basal ganglia (BG) is poorly understood. We tested the hypothesis that coherent population activity is dependent on brain state, frequency range, and/or BG nucleus using data from simultaneous recordings of electrocorticogram (ECoG) and BG local field potentials (LFPs) in anesthetized rats. The coherence between ECoG and LFPs simultaneously recorded from subthalamic nucleus (STN), globus pallidus (GP), and substantia nigra pars reticulata (SNr) was largely confined to slow- ( approximately 1 Hz) and spindle- (7-12 Hz) frequency oscillations during slow-wave activity (SWA). In contrast, during cortical activation, coherence was mostly restricted to high-frequency oscillations (15-60 Hz). The coherence between ECoG and LFPs also depended on BG recording site. Partial coherence analyses showed that, during SWA, STN and SNr shared the same temporal coupling with cortex, thereby forming a single functional axis. Cortex was also tightly, but independently, correlated with GP in a separate functional axis. During activation, STN, GP, and, to a lesser extent, SNr shared the same coherence with cortex as part of one functional axis. In addition, GP formed a second, independently coherent loop with cortex. These data suggest that coherent oscillatory activity is present at the level of LFPs recorded in cortico-basal ganglia circuits, and that synchronized population activity is dynamically organized according to brain state, frequency, and nucleus. These attributes further suggest that synchronized activity should be considered as one of a number of candidate mechanisms underlying the functional organization of these brain circuits.