Awake State Research Articles

Pontine parabrachial nucleus-basal forebrain circuitry regulating cortical and hippocampal arousal

IntroductionThe basal forebrain (BF) and the medial septum (MS) respectively drive neuronal activity of cerebral cortex and hippocampus (HPC) in sleep-wake cycle. Our previous studies of lesions and neuronal circuit tracing have shown that the pontine parabrachial nucleus (PB) projections to the BF and MS may be a key circuit for cortical and HPC arousal. AimsThis study aims to demonstrate that PB projections to the BF and MS activate the cerebral cortex and HPC. ResultsBy using chemogenetic stimulation of the BF, the PB-BF and the PB-MS pathway combined with electroencephalogram (EEG) Fast Fourier Transformation (FFT) analysis in rats, we demonstrated that chemogenetic stimulation of the BF or PB neurons projecting to the BF activated the cerebral cortex while chemogenetic stimulation of the MS or PB neurons projecting to the MS activated HPC activity, in sleep and wake state. These stimulations did not significantly alter sleep-wake amounts. ConclusionsOur results support that PB projections to the BF and MS specifically regulating cortical and HPC activity.

EEG-based spatiotemporal dynamics of fast ripple networks and hubs in infantile epileptic spasms.

Infantile epileptic spasms (IS) are epileptic seizures that are associated with increased risk for developmental impairments, adult epilepsies, and mortality. Here, we investigated coherence-based network dynamics in scalp EEG of infants with IS to identify frequency-dependent networks associated with spasms. We hypothesized that there is a network of increased fast ripple connectivity during the electrographic onset of clinical spasms, which is distinct from controls. We retrospectively analyzed peri-ictal and interictal EEG recordings of 14 IS patients. The data was compared with 9 age-matched controls. Wavelet phase coherence (WPC) was computed between 0.2 and 400 Hz. Frequency- and time-dependent brain networks were constructed using this coherence as the strength of connection between two EEG channels, based on graph theory principles. Connectivity was evaluated through global efficiency (GE) and channel-based closeness centrality (CC), over frequency and time. GE in the fast ripple band (251-400 Hz) was significantly greater following the onset of spasms in all patients (P < 0.05). Fast ripple networks during the first 10s from spasm onset show enhanced anteroposterior gradient in connectivity (posterior > central > anterior, Kruskal-Wallis P < 0.001), with maximum CC over the centroparietal channels in 10/14 patients. Additionally, this anteroposterior gradient in CC connectivity is observed during spasms but not during the interictal awake or asleep states of infants with IS. In controls, anteroposterior gradient in fast ripple CC was noted during arousals and wakefulness but not during sleep. There was also a simultaneous decrease in GE in the 5-8 Hz range after the onset of spasms (P < 0.05), of unclear biological significance. We identified an anteroposterior gradient in the CC connectivity of fast ripple hubs during spasms. This anteroposterior gradient observed during spasms is similar to the anteroposterior gradient in the CC connectivity observed in wakefulness or arousals in controls, suggesting that this state change is related to arousal networks.

Interictal invasive very high-frequency oscillations in resting awake state and sleep

Interictal very high-frequency oscillations (VHFOs, 500–2000 Hz) in a resting awake state seem to be, according to a precedent study of our team, a more specific predictor of a good outcome of the epilepsy surgery compared to traditional interictal high-frequency oscillations (HFOs, 80–500 Hz). In this study, we retested this hypothesis on a larger cohort of patients. In addition, we also collected patients' sleep data and hypothesized that the occurrence of VHFOs in sleep will be greater than in resting state. We recorded interictal invasive electroencephalographic (iEEG) oscillations in 104 patients with drug-resistant epilepsy in a resting state and in 35 patients during sleep. 21 patients in the rest study and 11 patients in the sleep study met the inclusion criteria (interictal HFOs and VHFOs present in iEEG recordings, a surgical intervention and a postoperative follow-up of at least 1 year) for further evaluation of iEEG data. In the rest study, patients with good postoperative outcomes had significantly higher ratio of resected contacts with VHFOs compared to HFOs. In sleep, VHFOs were more abundant than in rest and the percentage of resected contacts in patients with good and poor outcomes did not considerably differ in any type of oscillations. In conclusion, (1) our results confirm, in a larger patient cohort, our previous work about VHFOs being a specific predictor of the area which needs to be resected; and (2) that more frequent sleep VHFOs do not further improve the results.

Awake responses suggest inefficient dense coding in the mouse retina.

The structure and function of the vertebrate retina have been extensively studied across species with an isolated, ex vivo preparation. Retinal function in vivo, however, remains elusive, especially in awake animals. Here, we performed single-unit extracellular recordings in the optic tract of head-fixed mice to compare the output of awake, anesthetized, and ex vivo retinas. While the visual response properties were overall similar across conditions, we found that awake retinal output had in general (1) faster kinetics with less variability in the response latencies; (2) a larger dynamic range; and (3) higher firing activity, by ~20 Hz on average, for both baseline and visually evoked responses. Our modeling analyses further showed that such awake response patterns convey comparable total information but less efficiently, and allow for a linear population decoder to perform significantly better than the anesthetized or ex vivo responses. These results highlight distinct retinal behavior in awake states, in particular suggesting that the retina employs dense coding in vivo, rather than sparse efficient coding as has been often assumed from ex vivo studies.

Neuronal plasticity features are independent of neuronal holding membrane potential

Dynamical reversible neuronal features in vitro are typically examined using a fixed holding membrane potential, imitating the physiological conditions of intact brains in an awake state. Here, a set of neuronal plasticity features in synaptic blocked cultures are found to be independent of the holding membrane potential in the range [−95, −50] mV. Specifically, dendritic maximal firing frequency and its absolute refractory period are independent of the holding membrane potential. In addition, the stimulation threshold is also independent of the holding membrane potential in neurons that do not show membrane depolarization in response to sub-threshold stimulations. These robust dendritic plasticity features are a prerequisite for neuronal modeling and for their utilization in interconnected neural networks to realize higher-order functionalities.

Capturing the bi-stable asymmetry exchanges in the turbulent air wake of a simplified frigate using Large Eddy Simulation

Turbulent air wake of a Simplified Frigate Ship (SFS2) model is simulated using wall-resolved Large Eddy Simulation. The wake behind the superstructure presents an asymmetric configuration for an otherwise symmetric free stream condition. Bi-stable characteristics of the wake have also been simulated as evidenced by asymmetric state switching events. The wake behind the stern also exhibits bi-stable switching and adapts an opposite asymmetric orientation to the wake behind the superstructure, as also observed experimentally. The resulting time-averaged flow fields for each bi-stable state reveal a differential flux formation around the upstream sides of the superstructure. The instantaneous wake fields also suggest a possible influence of flow structures developed around the upstream end of the superstructure to generate a particular asymmetric wake state downstream.

Dopamine D4 Receptor Agonist Drastically Increases Delta Activity in the Thalamic Nucleus Reuniens: Potential Role in Communication between Prefrontal Cortex and Hippocampus.

Network oscillations are essential for all cognitive functions. Oscillatory deficits are well established in psychiatric diseases and are recapitulated in animal models. They are significantly and specifically affected by pharmacological interventions using psychoactive compounds. Dopamine D4 receptor (D4R) activation was shown to enhance gamma rhythm in freely moving rats and to specifically affect slow delta and theta oscillations in the urethane-anesthetized rat model. The goal of this study was to test the effect of D4R activation on slow network oscillations at delta and theta frequencies during wake states, potentially supporting enhanced functional connectivity during dopamine-induced attention and cognitive processing. Network activity was recorded in the prefrontal cortex (PFC), hippocampus (HC) and nucleus reuniens (RE) in control conditions and after injecting the D4R agonist A-412997 (3 and 5 mg/kg; systemic administration). We found that A-412997 elicited a lasting (~40 min) wake state and drastically enhanced narrow-band delta oscillations in the PFC and RE in a dose-dependent manner. It also preferentially enhanced delta synchrony over theta coupling within the PFC-RE-HC circuit, strongly strengthening PFC-RE coupling. Thus, our findings indicate that the D4R may contribute to cognitive processes, at least in part, through acting on wake delta oscillations and that the RE, providing an essential link between the PFC and HC, plays a prominent role in this mechanism.

Quantitative electroencephalogram in term neonates under different sleep states.

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake vs asleep states, but similar between active vs quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake vs active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake vs quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep vs quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.

Rapid compensatory plasticity revealed by dynamic correlated activity in monkeys in vivo.

To produce adaptive behavior, neural networks must balance between plasticity and stability. Computational work has demonstrated that network stability requires plasticity mechanisms to be counterbalanced by rapid compensatory processes. However, such processes have yet to be experimentally observed. Here we demonstrate that repeated optogenetic activation of excitatory neurons in monkey visual cortex (area V1) induces a population-wide dynamic reduction in the strength of neuronal interactions over the timescale of minutes during the awake state, but not during rest. This new form of rapid plasticity was observed only in the correlation structure, with firing rates remaining stable across trials. A computational network model operating in the balanced regime confirmed experimental findings and revealed that inhibitory plasticity is responsible for the decrease in correlated activity in response to repeated light stimulation. These results provide the first experimental evidence for rapid homeostatic plasticity that primarily operates during wakefulness, which stabilizes neuronal interactions during strong network co-activation.

Sleep disorders contribute to the development of dementia and Alzheimer’s disease

Life is the highest form of adaptation to the environment which is based on energy metabolism. To maintain life, the neuromuscular system must constantly interact with the environment. The striatal muscles are the main energy consumer and their access to energy fuel is mainly limited by the brain’s needs. In the state of wakefulness, the brain must continuously process streams of sensory signals and respond to them with motor actions. At the same time, the brain to be efficient must memorize the sensory-movement relationships. Brain memory networking requires additional energy allocation, and due to limited systemic energy resources, the processes of memorization are completed during the sleep phase when the inactive muscular system allows allocating the energy fuel to the brain functions such as memory trace formation and the removal of the activity-dependent waste products. Both physiological processes can be completed during sleep only, and consequently, chronic sleep disorder leads to pathological changes in brain functioning and escalation of neurodegenerative processes. Consequently, sleep disorders become the main cause of dementia which is the prodrome of Alzheimer’s disease.

Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness

SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While invitro studies showed PTV reduce action potential firing, consequences at invivo network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+ transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.

Signal processing and machine learning algorithm to classify anaesthesia depth

BackgroundPoor assessment of anaesthetic depth (AD) has led to overdosing or underdosing of the anaesthetic agent, which requires continuous monitoring to avoid complications. The evaluation of the central nervous system...

A role for cortical interneurons as adversarial discriminators.

The brain learns representations of sensory information from experience, but the algorithms by which it does so remain unknown. One popular theory formalizes representations as inferred factors in a generative model of sensory stimuli, meaning that learning must improve this generative model and inference procedure. This framework underlies many classic computational theories of sensory learning, such as Boltzmann machines, the Wake/Sleep algorithm, and a more recent proposal that the brain learns with an adversarial algorithm that compares waking and dreaming activity. However, in order for such theories to provide insights into the cellular mechanisms of sensory learning, they must be first linked to the cell types in the brain that mediate them. In this study, we examine whether a subtype of cortical interneurons might mediate sensory learning by serving as discriminators, a crucial component in an adversarial algorithm for representation learning. We describe how such interneurons would be characterized by a plasticity rule that switches from Hebbian plasticity during waking states to anti-Hebbian plasticity in dreaming states. Evaluating the computational advantages and disadvantages of this algorithm, we find that it excels at learning representations in networks with recurrent connections but scales poorly with network size. This limitation can be partially addressed if the network also oscillates between evoked activity and generative samples on faster timescales. Consequently, we propose that an adversarial algorithm with interneurons as discriminators is a plausible and testable strategy for sensory learning in biological systems.

Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In this study, we employed an attention-based bidirectional long short-term memory (Attention Bi-LSTM) model to accurately predict sleep stages using 60 GHz frequency-modulated continuous-wave (FMCW) radar. Our dataset comprised 78 participants from an ongoing obstructive sleep apnea (OSA) cohort, recruited between July 2021 and November 2022, who underwent overnight polysomnography alongside radar sensor monitoring. The dataset encompasses comprehensive polysomnography recordings, spanning both sleep and wakefulness states. The predictions achieved a Cohen's kappa coefficient of 0.746 and an overall accuracy of 85.2% in classifying wakefulness, rapid-eye-movement (REM) sleep, and non-REM (NREM) sleep (N1 + N2 + N3). The results demonstrated that the models incorporating both Radar 1 and Radar 2 data consistently outperformed those using only Radar 1 data, indicating the potential benefits of utilising multiple radars for sleep stage classification. Although the performance of the models tended to decline with increasing OSA severity, the addition of Radar 2 data notably improved the classification accuracy. These findings demonstrate the potential of radar technology as a valuable screening tool for sleep stage classification.

Algorithm for the classification of phases and stages of sleep in patients with chronic disorders of consciousness based on logical artificial intelligence

BACKGROUND: The analysis of sleep patterns in patients with chronic disorders of consciousness is attracting increasing attention in terms of diagnosis, prognosis, and treatment of severe brain damage. The study describes a software package based on an artificial intelligence (AI) expert system designed to classify the phases and stages of sleep, taking into account the characteristics of impaired cortical rhythm in such patients.&#x0D; AIM: To develop a specialized AI-based software package focused on patients with chronic impairment of consciousness for automatic classification of sleep phases and stages, with an emphasis on identifying sleep spindles and non-rapid eye movement (REM) and REM sleep phases.&#x0D; MATERIALS AND METHODS: To ensure the correct operation of the software package, receiver operating characteristic (ROC) curves were analyzed considering the binary classification of slow sleep, REM sleep, and wakefulness.&#x0D; RESULTS: The average sensitivity and specificity of the algorithm were 87.9 and 70.1, respectively. The average area under the ROC curve was 0.790. The algorithm for determining the REM phase demonstrates low specificity with high sensitivity, and its graph was similar to that of wakefulness, as well as the irregularity of the presence of REMs in the REM sleep phase in patients with CNS and the frequent presence of nystagmus in the waking state. Information about the presence of nystagmus, entered at the start of the program, allowed us to slightly increase the efficiency of the algorithm; however, this aspect probably needs further improvement.&#x0D; CONCLUSION: A software package that takes into account the features of electroencephalography of patients with chronic disorders of consciousness and analyzes sleep and wakefulness automatically is not only useful as a diagnostic tool for neurologists and somnologists but also contributes to a wider dissemination of this technique in clinical practice.

Stimulation of vagus nerve for patients with disorders of consciousness: a systematic review.

The purpose of this study is to evaluate the efficacy and safety of stimulating the vagus nerve in patients with disorders of consciousness (DOCs). A comprehensive systematic review was conducted, encompassing the search of databases such as PubMed, CENTRAL, EMBASE and PEDro from their inception until July 2023. Additionally, manual searches and exploration of grey literature were performed. The literature review was conducted independently by two reviewers for search strategy, selection of studies, data extraction, and judgment of evidence quality according to the American Academy of Cerebral Palsy and Developmental Medicine (AACPDM) Study Quality Scale. A total of 1,269 articles were retrieved, and 10 studies met the inclusion criteria. Among these, there were three case reports, five case series, and only two randomized controlled trials (RCTs). Preliminary studies have suggested that stimulation of vagus nerve can enhance the levels of DOCs in both vegetative state/unresponsive wakefulness state (VS/UWS) and minimally conscious state (MCS). However, due to a lack of high-quality RCTs research and evidence-based medical evidence, no definitive conclusion can be drawn regarding the intervention's effectiveness on consciousness level. Additionally, there were no significant adverse effects observed following stimulation of vagus nerve. A definitive conclusion cannot be drawn from this systematic review as there was a limited number of eligible studies and low-quality evidence. The findings of this systematic review can serve as a roadmap for future research on the use of stimulation of vagus nerve to facilitate recovery from DOCs.

Anesthesia-related brain microstructure modulations detected by diffusion magnetic resonance imaging.

Recent studies have shown significant changes to brain microstructure during sleep and anesthesia. In vivo optical microscopy and magnetic resonance imaging (MRI) studies have attributed these changes to anesthesia and sleep-related modulation of the brain's extracellular space (ECS). Isoflurane anesthesia is widely used in preclinical diffusion MRI (dMRI) and it is therefore important to investigate if the brain's microstructure is affected by anesthesia to an extent detectable with dMRI. Here, we employ diffusion kurtosis imaging (DKI) to assess brain microstructure in the awake and anesthetized mouse brain (n = 22). We find both mean diffusivity (MD) and mean kurtosis (MK) to be significantly decreased in the anesthetized mouse brain compared with the awake state (p < 0.001 for both). This effect is observed in both gray matter and white matter. To further investigate the time course of these changes we introduce a method for time-resolved fast DKI. With this, we show the time course of the microstructural alterations in mice (n = 5) as they transition between states in an awake-anesthesia-awake paradigm. We find that the decrease in MD and MK occurs rapidly after delivery of gas isoflurane anesthesia and that values normalize only slowly when the animals return to the awake state. Finally, time-resolved fast DKI is employed in an experimental mouse model of brain edema (n = 4), where cell swelling causes the ECS volume to decrease. Our results show that isoflurane affects DKI parameters and metrics of brain microstructure and point to isoflurane causing a reduction in the ECS volume. The demonstrated DKI methods are suitable for in-bore perturbation studies, for example, for investigating microstructural modulations related to sleep/wake-dependent functions of the glymphatic system. Importantly, our study shows an effect of isoflurane anesthesia on rodent brain microstructure that has broad relevance to preclinical dMRI.

Sex-dependent neuronal effects of α-synuclein reveal that GABAergic transmission is neuroprotective of sleep-controlling neurons

BackgroundSleep disorders (SDs) are a symptom of the prodromal phase of neurodegenerative disorders that are mechanistically linked to the protein α-synuclein (α-syn) including Parkinson’s disease (PD). SDs during the prodromal phase could result from neurodegeneration induced in state-controlling neurons by accumulation of α-syn predominant early in the disease, and consistent with this, we reported the monomeric form of α-syn (monomeric α-syn; α-synM) caused cell death in the laterodorsal tegmental nucleus (LDT), which controls arousal as well as the sleep and wakefulness state. However, we only examined the male LDT, and since sex is considered a risk factor for the development of α-syn-related diseases including prodromal SDs, the possibility exists of sex-based differences in α-synM effects. Accordingly, we examined the hypothesis that α-synM exerts differential effects on membrane excitability, intracellular calcium, and cell viability in the LDT of females compared to males.MethodsPatch clamp electrophysiology, bulk load calcium imaging, and cell death histochemistry were used in LDT brain slices to monitor responses to α-synM and effects of GABA receptor acting agents.ResultsConsistent with our hypothesis, we found differing effects of α-synM on female LDT neurons when compared to male. In females, α-synM induced a decrease in membrane excitability and heightened reductions in intracellular calcium, which were reliant on functional inhibitory acid transmission, as well as decreased the amplitude and frequency of spontaneous excitatory postsynaptic currents (sEPSCs) with a concurrent reduction in action potential firing rate. Cell viability studies showed higher α-synM-mediated neurodegeneration in males compared to females that depended on inhibitory amino acid transmission. Further, presence of GABA receptor agonists was associated with reduced cell death in males.ConclusionsWhen taken together, we conclude that α-synM induces a sex-dependent effect on LDT neurons involving a GABA receptor-mediated mechanism that is neuroprotective. Understanding the potential sex differences in neurodegenerative processes, especially those occurring early in the disease, could enable implementation of sex-based strategies to identify prodromal PD cases, and promote efforts to illuminate new directions for tailored treatment and management of PD.

An Analytic Method to Determine the Optimal Time for the Induction Phase of Anesthesia

We obtain an analytical solution for the time-optimal control problem in the induction phase of anesthesia. Our solution is shown to align numerically with the results obtained from the conventional shooting method. The induction phase of anesthesia relies on a pharmacokinetic/pharmacodynamic (PK/PD) model proposed by Bailey and Haddad in 2005 to regulate the infusion of propofol. In order to evaluate our approach and compare it with existing results in the literature, we examine a minimum-time problem for anesthetizing a patient. By applying the Pontryagin minimum principle, we introduce the shooting method as a means to solve the problem at hand. Additionally, we conducted numerical simulations using the MATLAB computing environment. We solve the time-optimal control problem using our newly proposed analytical method and discover that the optimal continuous infusion rate of the anesthetic and the minimum required time for transition from the awake state to an anesthetized state exhibit similarity between the two methods. However, the advantage of our new analytic method lies in its independence from unknown initial conditions for the adjoint variables.

Flow Topology of a Slanted Cylinder with Rounded-Edges Under Compressible Conditions

In this study, the slanted afterbody was modified to more closely represent cargo aircraft afterbodies through the addition of a basal edge fillet. Two slant angles ( and ) were explored over two Mach numbers ( and ) and two Reynolds numbers ( and ) using oil flow visualization and pressure-sensitive paint to identify surface flow phenomena, while the spanwise shadowgraph enabled the observation of mean wake phenomena. The rounded-edge afterbody surface measurements displayed a centerline-separated vortex state with flow features and regions of suction qualitatively similar to those of the baseline sharp-edge case, with some notable differences. For example, a separation bubble at the slant leading edge is nearly twice the size of the baseline sharp-edge model. This is accompanied by the presence of a “source point,” indicated by a region of high pressure where the flow reattaches, and a tighter counter-rotating vortex pair in comparison to the baseline. The rounded-edge prevented the previously seen compressible transition to a fully separated wake state within the Mach number range studied while showing an increase in separation bubble size with increasing Mach number. Also noteworthy was the existence of a new vortex state for the model, where the flow remains attached at the model centerline. This is in contrast to the previously observed flow topology of the centerline-separated vortex state in the sharp-edge model, which formed a separation bubble at the model centerline. The transition between the new centerline-attached vortex state and the traditional centerline-separated vortex state was shown to be dependent on both Mach number and Reynolds number, revealing the importance of boundary-layer development on the rounded afterbody flowfield. Overall, these observations indicate that the rounded afterbody produces flowfields with distinct features that vary from the previously described sharp-edge afterbody wake field under certain conditions.