High Frequency Spikes Research Articles

Multistability of bursting rhythms in a half-center oscillator and the protective effects of synaptic inhibition.

For animals to meet environmental challenges, the activity patterns of specialized oscillatory neural circuits, central pattern generators (CPGs), controlling rhythmic movements like breathing and locomotion, are adjusted by neuromodulation. As a representative example, the leech heartbeat is controlled by a CPG driven by two pairs of mutually inhibitory interneurons, heart interneuron (HN) half-center oscillators (HCO). Experiments and modeling indicate that neuromodulation of HCO navigates this CPG between dysfunctional regimes by employing a co-regulating inverted relation; reducing Na+/K+ pump current and increasing hyperpolarization-activated (h-) current. Simply reducing pump activity or increasing h-current leads to either seizure-like bursting or an asymmetric bursting dysfunctional regime, respectively. Here, we demonstrate through modeling that, alongside this coregulation path, a new bursting regime emerges. Both regimes fulfill the criteria for functional bursting activity. Although the cycle periods and burst durations of these patterns are roughly the same, the new one exhibits an intra-burst spike frequency that is twice as high as the other. This finding suggests that neuromodulation could introduce additional functional regimes with higher spike frequency, and thus more effective synaptic transmission to motor neurons. We found that this new regime co-exists with the original bursting. The HCO can be switched between them by a short pulse of excitatory or inhibitory conductance. In this domain of coexisting functional patterns, an isolated cell model exhibits only one regime, a severely dysfunctional plateau-containing, seizure-like activity. This aligns with widely reported notion that deficiency of inhibition can cause seizures and other dysfunctional neural activities. We show that along the coregulation path of neuromodulation, the high excitability of the single HNs induced by myomodulin is harnessed by mutually inhibitory synaptic interactions of the HCO into the functional bursting pattern.

Lesion volume and spike frequency on EEG impact perfusion values in focal cortical dysplasia: a pediatric arterial spin labeling study

Arterial spin labelling (ASL), an MRI sequence non-invasively imaging brain perfusion, has yielded promising results in the presurgical workup of children with focal cortical dysplasia (FCD)-related epilepsy. However, the interpretation of ASL-derived perfusion patterns remains unclear. Hence, we compared ASL qualitative and quantitative findings to their clinical, EEG, and MRI counterparts. We included children with focal structural epilepsy related to an MRI-detectable FCD who underwent single delay pseudo-continuous ASL. ASL perfusion changes were assessed qualitatively by visual inspection and quantitatively by estimating the asymmetry index (AI). We considered 18 scans from 15 children. 16 of 18 (89%) scans showed FCD-related perfusion changes: 10 were hypoperfused, whereas six were hyperperfused. Nine scans had perfusion changes larger than and seven equal to the FCD extent on anatomical images. Hyperperfusion was associated with frequent interictal spikes on EEG (p = 0.047). Perfusion changes in ASL larger than the FCD corresponded to larger lesions (p = 0.017). Higher AI values were determined by frequent interictal spikes on EEG (p = 0.004). ASL showed FCD-related perfusion changes in most cases. Further, higher spike frequency on EEG may increase ASL changes in affected children. These observations may facilitate the interpretation of ASL findings, improving treatment management, counselling, and prognostication in children with FCD-related epilepsy.

Early classification of Alzheimer's disease phenotype based on hippocampal electrophysiology in the TgF344-AD rat model

The hippocampus plays a vital role in navigation, learning, and memory, and is affected in Alzheimer's disease (AD). This study investigated the classification of AD-transgenic rats versus wild-type littermates using electrophysiological activity recorded from the hippocampus at an early, presymptomatic stage of the disease (6months old) in the TgF344-AD rat model. The recorded signals were filtered into low frequency (LFP) and high frequency (spiking activity) signals, and machine learning classifiers were employed to identify the rat genotype (TG vs. WT). By analyzing specific frequency bands in the low frequency signals and calculating distance metrics between spike trains in the high frequency signals, accurate classification was achieved. Gamma band power emerged as a valuable signal for classification, and combining information from both low and high frequency signals improved the accuracy further. These findings provide valuable insights into the early stage effects of AD on different regions of the hippocampus.

Robust bursting dynamics based on the interaction of persistent Na and Na/K pump currents: a dynamic clamp approach.

Life-supporting rhythmic motor functions like heart-beating in invertebrates and breathing in vertebrates require an indefatigable generation of a robust rhythm by specialized oscillatory circuits, Central Pattern Generators (CPGs). These CPGs should be sufficiently flexible to adjust to environmental changes and behavioral goals. Continuous self-sustained operation of bursting neurons requires intracellular Na+ concentration to remain in a functional range and to have checks and balances of the Na+ fluxes met on a cycle-to-cycle basis during bursting. We hypothesize that at a high excitability state, the interaction of the Na+/K+ pump current, Ipump and persistent Na+ current, INaP, produces a mechanism supporting functional bursting. INaP is a low voltage-activated inward current that initiates and supports the bursting phase. This current does not inactivate and is a significant source of Na+ influx. Ipump is an outward current activated by [Na+]i and is the major source of Na+ efflux. Both currents are active and counteract each other between and during bursts. We apply a combination of electrophysiology, computational modeling, and dynamic clamp to investigate the role of Ipump and INaP in the leech heartbeat CPG interneurons (HN neurons). Applying dynamic clamp to introduce additional Ipump and INaP into the dynamics of living synaptically isolated HN neurons in real-time, we show that their joint increase produces transition into a new bursting regime characterized by higher spike frequency and larger amplitude of the membrane potential oscillations. Further increase of Ipump speeds up this rhythm by shortening burst duration and interburst interval.Significance statementCentral Pattern Generators (CPGs) are neuronal networks that control rhythmic motor functions such as breathing and walking. Synaptic and membrane properties enable participating neurons to generate functional bursting patterns; intracellular Na+ concentration reflects the intensity of the spiking activity during bursts and regulates the Na+/K+ pump current playing a critical role in sculpting these patterns by providing negative feedback in response to excitation. Here, we show that the dynamic interaction of Na+/K+ pump current with persistent Na+ current offers a mechanism for the generation of a robust and flexible pattern of bursting activity. We provide physiological data and present a simple model that explains the underlying dynamics of the oscillatory mechanism.

Stochastic Switching in a Magnetic-Tunnel-Junction Neuron and a Bias-Dependent Néel-Arrhenius Model

Back hopping or telegraphic switching describes stochastic bistate oscillation in magnetic tunnel junctions (MTJ) at high bias, which significantly increases the write error rate of memory storage. Nevertheless, this unfavorable stochastic switching could be utilized to construct extremely compact spiking neuron circuits, where both the spike frequency and duty cycle are proportional to the applied bias voltage. This MTJ neuron is the fundamental building block of future all-spin neural networks. This paper analyzes the mechanism of stochastic switching in the MTJ neuron in detail. The self-heating effect at high bias is identified to induce thermal perturbation through a reduced energy barrier of a weakened perpendicular magnetic anisotropy. The high spike frequency is measured up to 10 MHz, which is mainly limited by the transition time between states and the multistate switching when approaching the Curie temperature of the ferromagnetic phase. Finally, to quantitatively describe the stochastic switching phenomenon, we establish a bias-dependent N\'eel-Arrhenius compact model, which calibrates well with experimental data. Based on this model, the potential and design guideline for realizing MTJ neurons with a spike frequency toward the gigahertz range are also discussed.

Spontaneous Activity Predicts Survival of Developing Cortical Neurons.

Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.

Electrophysiological and Morphological Features of Rebound Depolarization Characterized Interneurons in Rat Superficial Spinal Dorsal Horn.

Substantia gelatinosa (SG) neurons, which are located in the spinal dorsal horn (lamina II), have been identified as the “central gate” for the transmission and modulation of nociceptive information. Rebound depolarization (RD), a biophysical property mediated by membrane hyperpolarization that is frequently recorded in the central nervous system, contributes to shaping neuronal intrinsic excitability and, in turn, contributes to neuronal output and network function. However, the electrophysiological and morphological properties of SG neurons exhibiting RD remain unclarified. In this study, whole-cell patch-clamp recordings were performed on SG neurons from parasagittal spinal cord slices. RD was detected in 44.44% (84 out of 189) of the SG neurons recorded. We found that RD-expressing neurons had more depolarized resting membrane potentials, more hyperpolarized action potential (AP) thresholds, higher AP amplitudes, shorter AP durations, and higher spike frequencies in response to depolarizing current injection than neurons without RD. Based on their firing patterns and morphological characteristics, we propose that most of the SG neurons with RD mainly displayed tonic firing (69.05%) and corresponded to islet cell morphology (58.82%). Meanwhile, subthreshold currents, including the hyperpolarization-activated cation current (Ih) and T-type calcium current (IT), were identified in SG neurons with RD. Blockage of Ih delayed the onset of the first spike in RD, while abolishment of IT significantly blunted the amplitude of RD. Regarding synaptic inputs, SG neurons with RD showed lower frequencies in both spontaneous and miniature excitatory synaptic currents. Furthermore, RD-expressing neurons received either Aδ- or C-afferent-mediated monosynaptic and polysynaptic inputs. However, RD-lacking neurons received afferents from monosynaptic and polysynaptic Aδ fibers and predominantly polysynaptic C-fibers. These findings demonstrate that SG neurons with RD have a specific cell-type distribution, and may differentially process somatosensory information compared to those without RD.

The Effect of Sodium Accumulation and Removal on Axonal Resilience to High Frequency Spiking

The Effect of Sodium Accumulation and Removal on Axonal Resilience to High Frequency Spiking

Lag times and invasion dynamics of established and emerging weeds: insights from herbarium records of Queensland, Australia

Herbarium records provide comprehensive information on plant distribution, offering opportunities to construct invasion curves of introduced species, estimate their rates and patterns of expansions in novel ranges, as well as identifying lag times and hence “sleeper weeds”, if any. Lag times especially have rarely been determined for many introduced species, including weeds in the State of Queensland, Australia as the trait is thought to be unpredictable and cannot be screened for. Using herbarium records (1850–2010), we generated various invasiveness indices, and developed simple invasion and standardised proportion curves of changes in distribution with time for ~ 100 established and emerging weed species of Queensland. Four major periods (decades) of increased weed spread (spikes) were identified: 1850s, 1900–1920, 1950–1960 and 2000–2010, especially for grasses and trees/shrubs. Many weeds with spikes in spread periods did so only 1–2 decadal times, except for a few species with higher spike frequencies > 6; the majority of these spikes occurred recently (1950–1990). A significant proportion (~ 60%) of Queensland’s weeds exhibit non-linear increase in spread with time, and hence have lag phases (mean: 45.9 years; range: 12–126 years); of these lag-phase species, 39% are “sleeper” weeds with > 50 years of lag time (mainly trees/shrubs and grasses). Twelve traits of invasiveness, including lag time and species-specific/historical factors were screened, of which frequency of invasion waves, spread rates and residence time were the main drivers of weeds’ distribution. The low predictive power of lag time on weed distribution suggests that retrospective analyses offer little hope for a robust generalisation to identify weeds of tomorrow.

Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones

ObjectiveOne barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both pathological and physiological HFBS. This study was to find specific biomarkers for localizing epileptogenic zones (EZs). MethodsTwenty three children with drug-resistant epilepsy and age/sex matched healthy controls were studied with magnetoencephalography (MEG). High frequency oscillations (HFOs, > 4 oscillatory waveforms) and high frequency spikes (HFSs, > 1 spiky or sharp waveforms) in 80–250 Hz and 250–600 Hz bands were blindly detected with an artificial intelligence method and validated with visual inspection. The magnitude of HFOs and HFSs were quantified with spectral analyses. Sources of HFSs and HFOs were localized and compared with clinical EZs determined by invasive recordings and surgical outcomes. ResultsHFOs in 80–250 Hz and 250–600 Hz were identified in both epilepsy patients (18/23, 12/23, respectively) and healthy controls (6/23, 4/23, respectively). HFSs in 80–250 Hz and 250–600 Hz were detected in patients (16/23, 11/23, respectively) but not in healthy controls. A combination of HFOs and HFSs localized EZs for 22 (22/23, 96%) patients. ConclusionsThe results indicate, for the first time, that HFSs are a newer and more specific biomarker than HFOs for localizing EZs because HFOs appeared in both epilepsy patients and healthy controls while HFSs appeared only in epilepsy patients.

Cognitive Processing Impacts High Frequency Intracranial EEG Activity of Human Hippocampus in Patients With Pharmacoresistant Focal Epilepsy.

The electrophysiological EEG features such as high frequency oscillations, spikes and functional connectivity are often used for delineation of epileptogenic tissue and study of the normal function of the brain. The epileptogenic activity is also known to be suppressed by cognitive processing. However, differences between epileptic and healthy brain behavior during rest and task were not studied in detail. In this study we investigate the impact of cognitive processing on epileptogenic and non-epileptogenic hippocampus and the intracranial EEG features representing the underlying electrophysiological processes. We investigated intracranial EEG in 24 epileptic and 24 non-epileptic hippocampi in patients with intractable focal epilepsy during a resting state period and during performance of various cognitive tasks. We evaluated the behavior of features derived from high frequency oscillations, interictal epileptiform discharges and functional connectivity and their changes in relation to cognitive processing. Subsequently, we performed an analysis whether cognitive processing can contribute to classification of epileptic and non-epileptic hippocampus using a machine learning approach. The results show that cognitive processing suppresses epileptogenic activity in epileptic hippocampus while it causes a shift toward higher frequencies in non-epileptic hippocampus. Statistical analysis reveals significantly different electrophysiological reactions of epileptic and non-epileptic hippocampus during cognitive processing, which can be measured by high frequency oscillations, interictal epileptiform discharges and functional connectivity. The calculated features showed high classification potential for epileptic hippocampus (AUC = 0.93). In conclusion, the differences between epileptic and non-epileptic hippocampus during cognitive processing bring new insight in delineation between pathological and physiological processes. Analysis of computed iEEG features in rest and task condition can improve the functional mapping during pre-surgical evaluation and provide additional guidance for distinguishing between epileptic and non-epileptic structure which is absolutely crucial for achieving the best possible outcome with as little side effects as possible.

Infant and adult SCA13 mutations differentially affect Purkinje cell excitability, maturation, and viability in vivo.

Mutations in KCNC3, which encodes the Kv3.3 K+ channel, cause spinocerebellar ataxia 13 (SCA13). SCA13 exists in distinct forms with onset in infancy or adulthood. Using zebrafish, we tested the hypothesis that infant- and adult-onset mutations differentially affect the excitability and viability of Purkinje cells in vivo during cerebellar development. An infant-onset mutation dramatically and transiently increased Purkinje cell excitability, stunted process extension, impaired dendritic branching and synaptogenesis, and caused rapid cell death during cerebellar development. Reducing excitability increased early Purkinje cell survival. In contrast, an adult-onset mutation did not significantly alter basal tonic firing in Purkinje cells, but reduced excitability during evoked high frequency spiking. Purkinje cells expressing the adult-onset mutation matured normally and did not degenerate during cerebellar development. Our results suggest that differential changes in the excitability of cerebellar neurons contribute to the distinct ages of onset and timing of cerebellar degeneration in infant- and adult-onset SCA13.

Epileptic seizures in a heterogeneous excitatory network with short-term plasticity.

Epilepsy involves a diverse group of abnormalities, including molecular and cellular disorders. These abnormalities prove to be associated with the changes in local excitability and synaptic dynamics. Correspondingly, the epileptic processes including onset, propagation and generalized seizure may be related with the alterations of excitability and synapse. In this paper, three regions, epileptogenic zone (EZ), propagation area and normal region, were defined and represented by neuronal population model with heterogeneous excitability, respectively. In order to describe the synaptic behavior that the strength was enhanced and maintained at a high level for a short term under a high frequency spike train, a novel activity-dependent short-term plasticity model was proposed. Bifurcation analysis showed that the presence of hyperexcitability could increase the seizure susceptibility of local area, leading to epileptic discharges first seen in the EZ. Meanwhile, recurrent epileptic activities might result in the transition of synaptic strength from weak state to high level, augmenting synaptic depolarizations in non-epileptic neurons as the experimental findings. Numerical simulation based on a full-connected weighted network could qualitatively demonstrate the epileptic process that the propagation area and normal region were successively recruited by the EZ. Furthermore, cross recurrence plot was used to explore the synchronization between neuronal populations, and the global synchronization index was introduced to measure the global synchronization. Results suggested that the synchronization between the EZ and other region was significantly enhanced with the occurrence of seizure. Interestingly, the desynchronization phenomenon was also observed during seizure initiation and propagation as reported before. Therefore, heterogeneous excitability and short-term plasticity are believed to play an important role in the epileptic process. This study may provide novel insights into the mechanism of epileptogenesis.

Electroencephalographic abnormalities are correlated with cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes: A clinical study of 61 cases

ObjectiveThe objective of this study was to explore the effect of spikes on cognition in patients with benign childhood epilepsy with centrotemporal spikes (BECTS) and to identify electroencephalography (EEG) markers enabling early detection of cognitive impairment. MethodsSixty-one children with BECTS diagnoses and 60 age- and education-matched healthy controls were enrolled. Four-hour EEG recordings were analyzed for each patient to check for interictal spikes, high-frequency oscillations (HFOs), nondipole spikes, and other atypical EEG features and to examine the spike–wave index of nonrapid eye movement (NREM) sleep. All 121 children underwent a series of neuropsychological tests to assess cognitive function. ResultsPatients with a high NREM sleep discharge index (≥55%) in the first sleep cycle exhibited significantly lower scores for arithmetic calculation, executive function, and attention and memory tests than patients with a low discharge index (<55%). Eight patients with HFOs exhibited even poorer performance than HFO-negative patients for arithmetic calculation, executive function, vocabulary comprehension, visual perception, vocal perception, spatial memory ability, and response ability. Children with bilateral discharge exhibited poorer ability in three-dimensional spatial imaging test, poorer memory, and slower response than did those with unilateral discharge (P < .05). Nondipole spikes, multiple asynchronous discharges, and generalized spike–wave discharges respectively had an impact on calculation ability, memory, and reaction ability respectively (P < .05). ConclusionsSpike frequencies in stage 3 and 4 sleep varied from those observed in stage 1 and 2 sleep; the highest spike frequency was in stage 2 sleep. High NREM sleep discharge index (i.e., ≥55%) and HFOs were linked to the highest risk for cognitive deficit, while bilateral discharges, nondipole spikes, multiple asynchronous discharges, and generalized spike–wave discharges were less indicative of cognitive impairment.

Design of Artificial Neuron Network with Synapse Utilizing Hybrid CMOS Transistors with Memristor for Low Power Applications

Neural networks are mimetic with biological neuron which are employed on digital computers. These networks are designed with CMOS technology using 0.45[Formula: see text][Formula: see text]m in cadence virtuoso. The scaling of CMOS limits parameters like power consumption, area and parallelism. To overcome the limitations, a nanoscale, nonvolatile Memristor device is used to design the synapses. The proposed network is designed for neuron synapse networks implemented with a memristor device. This network is compared with neuron linked with CMOS synapse. The proposed network has low power consumption, high spike frequency, and low delay value. The spike frequency of Memristor synapse increases by 65.51% when compared with the existing CMOS synapse and power consumption is reduced to 52.79%. The delay is reduced to 0.294[Formula: see text][Formula: see text]s. The simulation results are carried using Specter.

Микроэлектрофизиологическое изучение соотношения возбудительных и тормозных синаптических процессов в кортико-нигральной проекции на модели болезни Паркинсона

The impulse activity of single neurons in substantia nigra pars compacta - SNc (242 neurons, n=11) and substantia nigra pars reticulate - SNr (289 neurons, n=12) under high frequency stimulation of primary motor cortex (M1) was analyzed on 23 white male rats in control and rotenone model of Parkinson’s disease (PD). In SNc neurons in PD model there was no stimulation-induced depression, however, the posttetatic potentiation and depression following the tetanic potentiation, were 1.65 and 2.02 times higher than in control. In control SNr neurons the tetanic potentiation followed by the posttetanic potentiation and depression was 2.37 times higher than the tetanic depression, whereas in the PD model both depression and potentiation levels were subnormal. In PD model, both SNc and SNr neurons exhibited significantly higher spike frequency before and during the stimulation in comparison with control. This indicates the presence of the excitotoxicity accompanied by the neurodegenerative damage followed by the apoptosis and the neuronal death. In SNr neurons both depression and potentiation after the stimulation were much more prominent than in SNc neurons, which indicates that the cortical projections on the SNr are more pronounced. Moreover, the SNc neurons demonstrated higher succeptibility to the pathological changes in the poststimulus depression, leading to the more pronounced potentiation in those neurons in comparison with the SNr neurons, which indicates the more prominent involvement of the former in the PD pathogenesis. In the PD model, with no stimulation-induced depression and more prominent potentiation in the SNc neurons, the SNr neurons maintain the depression and show relatively lowered potentiation, which indicates their lower succeptibility to the excitotoxicity, and the excessive excitability of the remaining neurons as a compensation for the dead ones.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset.

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

Propofol decreases spike firing frequency with an increase in spike synchronization in the cerebral cortex

Little is known about how propofol modulates the spike firing correlation between excitatory and inhibitory cortical neurons in vivo. We performed extracellular unit recordings from rat insular cortical neurons, and classified neurons with high spontaneous firing frequency, bursting, and short spike width as high frequency with bursting neurons (HFB; pseudo fast-spiking GABAergic neurons) and other neurons with low spontaneous firing frequency and no bursting were classified as non-HFB. Intravenous administration of propofol (12 mg/kg) from the caudal vein reduced the firing frequency of HFB, whereas propofol initially increased (within 30 s) and then decreased the firing frequency of non-HFB. Both HFB and non-HFB spontaneous action potential discharge was depressed by propofol with a greater depression seen for HFB. Cross-correlograms and auto-correlograms demonstrated propofol-induced increases in the ratio of the peak, which were mostly observed around 0–10 ms divided to baseline amplitude. The analysis of interspike intervals showed a decrease in spike firing at 20–100 Hz and a relative increase at 8–15 Hz. These results suggest that propofol induces a larger suppression of firing frequency in HFB and an enhancement of synchronized neural activities in the α frequency band in the cerebral cortex (192 words).

Cellular and Network Mechanisms May Generate Sparse Coding of Sequential Object Encounters in Hippocampal-Like Circuits.

The localization of distinct landmarks plays a crucial role in encoding new spatial memories. In mammals, this function is performed by hippocampal neurons that sparsely encode an animal’s location relative to surrounding objects. Similarly, the dorsolateral pallium (DL) is essential for spatial learning in teleost fish. The DL of weakly electric gymnotiform fish receives both electrosensory and visual input from the preglomerular nucleus (PG), which has been hypothesized to encode the temporal sequence of electrosensory or visual landmark/food encounters. Here, we show that DL neurons in the Apteronotid fish and in the Carassius auratus (goldfish) have a hyperpolarized resting membrane potential (RMP) combined with a high and dynamic spike threshold that increases following each spike. Current-evoked spikes in DL cells are followed by a strong small-conductance calcium-activated potassium channel (SK)-mediated after-hyperpolarizing potential (AHP). Together, these properties prevent high frequency and continuous spiking. The resulting sparseness of discharge and dynamic threshold suggest that DL neurons meet theoretical requirements for generating spatial memory engrams by decoding the landmark/food encounter sequences encoded by PG neurons. Thus, DL neurons in teleost fish may provide a promising, simple system to study the core cell and network mechanisms underlying spatial memory.

Observations of Zooplankton Diel Vertical Migration From High‐Resolution Surface Ocean Optical Measurements

AbstractWe demonstrate that signal spikes in optical backscatter measurements provide information on the diel vertical migration patterns of oceanic zooplankton. During nighttime, we observed high frequency spikes in particulate optical backscatter coincident with increased acoustic backscatter from vertically migrating zooplankton. We used our measurements to examine the spatial patterns and daily timing of zooplankton migrations across the eastern Subarctic Pacific Ocean, demonstrating coherence of diel vertical migrations with regional hydrographic features. Vertical zooplankton migration was consistently observed in oligotrophic offshore waters but less apparent in higher productivity waters over the continental shelf, where bottom depth, hydrographic fronts, and plankton abundance influenced apparent zooplankton distributions. Our results suggest that spikes in optical backscatter data, which are normally removed during data processing, can be more fully exploited to examine marine zooplankton dynamics from autonomous measurement systems.