Oversampling method to extract excitatory and inhibitory conductances from single-trial membrane potential recordings

Variations of excitatory and inhibitory conductances determine the membrane potential (V(m)) activity of neurons, as well as their spike responses, and are thus of primary importance. Methods to estimate these conductances require clamping the cell at several different levels of V(m), thus making it impossible to estimate conductances from "single trial" V(m) recordings. We present here a new method that allows extracting estimates of the full time course of excitatory and inhibitory conductances from single-trial V(m) recordings. This method is based on oversampling of the V(m). We test the method numerically using models of increasing complexity. Finally, the method is evaluated using controlled conductance injection in cortical neurons in vitro using the dynamic-clamp technique. This conductance extraction method should be very useful for future in vivo applications.     

Abnormalities in GABAergic synaptic transmission of intralaminar thalamic neurons in a genetic rat model of absence epilepsy

Synaptic activity mediated via GABA receptors in thalamic circuits is critically involved in the generation of hypersynchrony associated with absence epilepsy. Neurons of "unspecific" intralaminar thalamic nuclei display characteristic burst patterns during seizure activity, although their synaptic properties remain largely unknown. Here, we used in vitro patch-clamp techniques in neurons of the paracentral (PC) thalamic nucleus, derived from a genetic model of absence epilepsy (WAG-Rij) and a non-epileptic control strain (ACI) to elucidate intrinsic and synaptic properties. PC neurons displayed voltage-dependent low threshold spike bursts or tonic spike firing, typical of thalamic neurons. These parameters, and electrotonic properties, were similar in PC neurons of the two strains. Analyses of miniature inhibitory post synaptic currents (mIPSCs) mediated via GABA(A) receptors revealed no difference in decay time constant and inter-event interval between strains, but a significantly larger amplitude and higher single channel conductance (as assessed by non-stationary variance analysis) in WAG-Rij compared to ACI. By comparison, thalamocortical neurons from the ventrobasal complex of the thalamus showed no difference in mIPSC kinetics and unitary conductance between the two rat strains. In view of the critical role of GABAergic inhibition for synchronous activity in thalamocortical circuits, it is concluded that the increase in unitary conductance of IPSCs in PC neurons contributes to hypersynchrony characterizing seizure activity.     

Brain-derived neurotrophic factor rapidly increases NMDA receptor channel activity through Fyn-mediated phosphorylation

Brain-derived neurotrophic factor (BDNF) is a potent modulator of hippocampal synaptic plasticity. Previously, we found that one of the targets of BDNF modulation is NR2B-containing NMDA receptors. Furthermore, exposure to the trophin rapidly increases NMDA receptor activity and enhances tyrosine phosphorylation of NR2B in cortical and hippocampal postsynaptic densities (PSDs), potentially linking receptor phosphorylation to synaptic plasticity. To define the specific NR2B residue(s) regulated by BDNF, we focused on tyrosine 1472, phosphorylation of which increases after LTP. BDNF rapidly increased phosphorylation in cortical PSDs. The tyrosine kinase Fyn is critical since BDNF-dependent phosphorylation was abolished in Fyn knockout mice. Single-channel patch clamp recordings showed that Fyn is required for the increase in NMDA receptor activity elicited by BDNF. Collectively, our results suggest that BDNF enhances phosphorylation of NR2B tyrosine 1472 through activation of Fyn, leading to alteration of NMDA receptor activity and increased synaptic transmission.     

Stimulus-selective spiking is driven by the relative timing of synchronous excitation and disinhibition in cat striate neurons in vivo

What patterns of synaptic input cause cortical neurons to fire action potentials? Are they stochastic in nature, or do action potentials arise from the specific timing of synaptic input? We addressed these questions by measuring the membrane potential fluctuations associated with the generation of visually evoked action potentials in cat striate cortical neurons in vivo. In response to visual stimulation, action potentials occurred at the crest of large‐amplitude, transient depolarizations (TDs) riding on sustained depolarization of the membrane potential. The magnitude, duration and rate of depolarization of these transient events were tuned for stimulus orientation. Using numerical simulations, we find that these transient events can arise from the temporal interplay between synchronous excitation and inhibition. To validate these findings, we made conductance measurements, at the preferred stimulus orientation, and showed that the TDs arise either from an increase in excitatory conductance, or from a combination of increased excitatory and decreased inhibitory conductance, both riding on sustained changes in synaptic conductances. The properties of the TDs and their underlying conductance suggest that they arise from a specific temporal interplay between synchronous excitatory and inhibitory synaptic inputs. Our results illustrate a mechanism by which the timing of synaptic inputs determines much of the spiking activity in striate cortical neurons.     

Deterministic neural dynamics transmitted through neural networks

Precise spatiotemporal sequences of neuronal discharges (i.e., intervals between epochs repeating more often than expected by chance), have been observed in a large set of experimental electrophysiological recordings. Sensitivity to temporal information, by itself, does not demonstrate that dynamics embedded in spike trains can be transmitted through a neural network. This study analyzes how synaptic transmission through three archetypical types of neurons (regular-spiking, thalamo-cortical and resonator), simulated by a simple spiking model, can affect the transmission of precise timings generated by a nonlinear deterministic system (i.e., the Zaslavskii mapping in the present study). The results show that cells with subthreshold oscillations (resonators) are very sensitive to stochastic inputs, and are not a good candidate for transmitting temporally coded information. Thalamo-cortical neurons may transmit very well temporal patterns in the absence of background activity, but jitter accumulates along the synaptic chain. Conversely, we observed that cortical regular-spiking neurons can propagate filtered temporal information in a reliable way through the network, and with high temporal accuracy. We discuss the results in the general framework of neural dynamics and brain theories.     

Neuronal sensitivity to GABA and glutamate in generalized epilepsy with spike and wave discharges

In awake but painlessly immobilized cats the extracellular activity of the same cortical neurons was recorded before and for 2 to 5 h after the injection of penicillin G (350,000 IU/kg, i.m.) during the development of generalized epilepsy with bilaterally synchronous spike and wave discharges. Possible changes in their sensitivity to microiontophoretically applied glutamate and GABA during this period were searched for using computer-generated periejection histograms at intervals of about 30 min. In contrast to reported studies in other models of epilepsy, glutamate excited and GABA depressed virtually all neurons tested during fully developed spike and wave epilepsy. Spike height was not apparently affected either by the amino acids or by the development of epilepsy. Comparison of relative thresholds for the above effects on rhythmical neuronal activity associated with spike and wave discharge versus effects on random neuronal activity during the interburst periods, supported the idea that spikes and waves result from strong excitatory and inhibitory synaptic drives of the neurons. In all neurons until the appearance of spike and wave discharges, changes in the effect of amino acids, if observed, were small and statistically nonsignificant. This suggests that the hyperexcitability of cortical neurons which reportedly leads to the appearance of spike and wave discharges depends on mechanisms other than an increase in sensitivity to glutamate or a desensitization to GABA. Sometimes the sensitivity to GABA decreased later in this experimental model when the very frequent appearance of spike and wave discharges eventually led to EEG tonic-clonic seizures.     

Mechanism of aminopyridine-induced ictal seizure activity in the cat neocortex

Intracellular recordings were obtained from neurons in the motor cortex of anesthetized cats in order to examine membrane and synaptic processes involved in aminopyridine (AP)-induced ictal seizure activity. Depolarizing and hyperpolarizing membrane potential sequences which behaved as large, synchronized excitatory and inhibitory postsynaptic potentials, were found to accompany the ictal seizure potentials. After several repetitions of the seizure attack, partial responses, bursts and depolarizing plateaus with spike inactivation occurred. In layers IV and V we found non-pyramidal tract neurons showing endogenous bursting ability activated by AP. These neurons seemed to be the initiators of the rhythmic synchronous activity of the epileptic neuron population. Our results suggest that AP-induced epileptogenesis represents an adequate model of ictal events in the neocortex.     

Balanced Enhancements of Synaptic Excitation and Inhibition Underlie Developmental Maturation of Receptive Fields in the Mouse Visual Cortex

Neurons in the developing visual cortex undergo progressive functional maturation as indicated by the refinement of their visual feature selectivity. However, changes of the synaptic architecture underlying the maturation of spatial visual receptive fields (RFs) per se remain largely unclear. Here, loose-patch as well as single-unit recordings in layer 4 of mouse primary visual cortex (V1) of both sexes revealed that RF development following an eye-opening period is marked by an increased proportion of cortical neurons with spatially defined RFs, together with the increased signal-to-noise ratio of spiking responses. By exploring excitatory and inhibitory synaptic RFs with whole-cell voltage-clamp recordings, we observed a balanced enhancement of both synaptic excitation and inhibition, and while the excitatory subfield size remains relatively constant during development, the inhibitory subfield is broadened. This balanced developmental strengthening of excitatory and inhibitory synaptic inputs results in enhanced visual responses, and with a reduction of spontaneous firing rate, contributes to the maturation of visual cortical RFs. Visual deprivation by dark rearing impedes the normal strengthening of excitatory inputs but leaves the apparently normal enhancement of inhibition while preventing the broadening of the inhibitory subfield, leading to weakened RF responses and a reduced fraction of neurons exhibiting a clear RF, compared with normally reared animals. Our data demonstrate that an experience-dependent and coordinated maturation of excitatory and inhibitory circuits underlie the functional development of visual cortical RFs.SIGNIFICANCE STATEMENT The organization of synaptic RFs is a fundamental determinant of feature selectivity functions in the cortex. However, how changes of excitatory and inhibitory synaptic inputs lead to the functional maturation of visual RFs during cortical development remains not well understood. In layer 4 of mouse V1, we show that a coordinated, balanced enhancement of synaptic excitation and inhibition contributes to the developmental maturation of spatially defined visual RFs. Visual deprivation by dark rearing partially interferes with this process, resulting in a relatively more dominant inhibitory tone and a reduced fraction of neurons exhibiting clear RFs at the spike level. These data provide an unprecedented understanding of the functional development of visual cortical RFs at the synaptic level.     

Role of GABAergic inhibition in hippocampal network oscillations

Physiological rhythmic activity in cortical circuits relies on GABAergic inhibition to balance excitation and control spike timing. With a focus on recent experimental progress in the hippocampus, here we review the mechanisms by which synaptic inhibition can control the precise timing of spike generation, by way of effects of GABAergic events on membrane conductance ('shunting' inhibition) and membrane potential ('hyperpolarizing' inhibition). Synaptic inhibition itself can be synchronized by way of interactions within networks of GABAergic neurons, and by excitatory neurons. The importance of GABAergic mechanisms for generation of cortical rhythms is now well established. What remains to be resolved is how such inhibitory control of spike timing can be harnessed for long-range fast synchronization, and the relevance of these mechanisms to network function. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).     

In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices

In order to better understand the synaptic nature of the integration process operated by cortical neurons during sensory processing, it is necessary to devise quantitative methods which allow one to infer the level of conductance change evoked by the sensory stimulation and, consequently, the dynamics of the balance between excitation and inhibition. Such detailed measurements are required to characterize the static versus dynamic nature of the non-linear interactions triggered at the single cell level by sensory stimulus. This paper primarily reviews experimental data from our laboratory based on direct conductance measurements during whole-cell patch clamp recordings in two experimental preparations: (1) in vitro, during electrical stimulation in the visual cortex of the rat and (2) in vivo, during visual stimulation, in the primary visual cortex of the anaesthetized cat. Both studies demonstrate that shunting inhibition is expressed as well in vivo as in vitro. Our in vivo data reveals that a high level of diversity is observed in the degree of interaction (from linear to non-linear) and in the temporal interplay (from push-pull to synchronous) between stimulus-driven excitation (E) and inhibition (I). A detailed analysis of the E/I balance during evoked spike activity further shows that the firing strength results from a simultaneous decrease of evoked inhibition and increase of excitation. Secondary, the paper overviews the various computational methods used in the literature to assess conductance dynamics, measured in current clamp as well as in voltage clamp in different neocortical areas and species, and discuss the consistency of their estimations.     

Synaptic dynamics: Linear model and adaptation algorithm

In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed.The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation–depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm’s accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and decides with a shorter observation of data. DSNN performance in the benchmark pattern recognition problem shows 96.7% accuracy in classifying three classes of spiking activity.     

Dynamics of information and emergent computation in generic neural microcircuit models

Numerous methods have already been developed to estimate the information contained in single spike trains. In this article we explore efficient methods for estimating the information contained in the simultaneous firing activity of hundreds of neurons. Obviously such methods are needed to analyze data from multi-unit recordings. We test these methods on generic neural microcircuit models consisting of 800 neurons, and analyze the temporal dynamics of information about preceding spike inputs in such circuits. It turns out that information spreads with high speed in such generic neural microcircuit models, thereby supporting—without the postulation of any additional neural or synaptic mechanisms—the possibility of ultra-rapid computations on the first input spikes.     

A study of the transition from spindles to spike and wave discharge in feline generalized penicillin epilepsy: Microphysiological features

The microphysiological features underlying the evolution of spike and wave discharge from spindles in feline generalized penicillin epilepsy were investigated using extracellular microelectrode recordings. Action potentials generated by single cortical neurons were related to the EEG features of the transition from spindles to spike and waves using statistical methods of analysis on a computer. The probability of an action potential being discharged by a spindle wave was weak. It progressively increased after penicillin during the transformation of the spindle wave into the spike of the spike and wave complex. As this occurred, periods of decreased firing probability coinciding with the slow wave of the spike and wave complex developed immediately after each period of enhanced firing probability. The spike and wave pattern was thus characterized by a remarkable oscillation between periods of increased excitation of cortical neurons corresponding to the spike, and periods of markedly decreased firing probability corresponding to the wave of the spike and wave complex. This was associated with increased synchronization of discharge of neighboring cortical neurons. We propose that the transformation of spindles to spike and waves is the consequence of a single feature: increased excitability of cortical neurons to spindle-inducing thalamocortical volleys. Under those conditions cortical cells discharge action potentials more consistently with each thalamocortical volley. Because of this the high threshold intracortical recurrent inhibitory pathway is recruited into the discharging process and induces recurrent periods of powerful inhibition of cortical neurons.     

Accurate spike sorting for multi‐unit recordings

Simultaneous recordings with multi‐channel electrodes are widely used for studying how multiple neurons are recruited for information processing. The recorded signals contain the spike events of a number of adjacent or distant neurons and must be sorted correctly into spike trains of individual neurons. Several mathematical methods have been proposed for spike sorting but the process is difficult in practice, as extracellularly recorded signals are corrupted by biological noise. Moreover, spike sorting is often time‐consuming, as it usually requires corrections by human operators. Methods are needed to obtain reliable spike clusters without heavy manual operation. Here, we introduce several methods of spike sorting and compare the accuracy and robustness of their performance by using publicized data of simultaneous extracellular and intracellular recordings of neuronal activity. The best and excellent performance was obtained when a newly proposed filter for spike detection was combined with the wavelet transform and variational Bayes for a finite mixture of Student’s t‐distributions, namely, robust variational Bayes. Wavelet transform extracts features that are characteristic of the detected spike waveforms and the robust variational Bayes categorizes the extracted features into clusters corresponding to spikes of the individual neurons. The use of Student’s t‐distributions makes this categorization robust against noisy data points. Some other new methods also exhibited reasonably good performance. We implemented all of the proposed methods in a C++ code named ‘EToS’ (Efficient Technology of Spike sorting), which is freely available on the Internet.     

Dynamical response properties of neocortical neurons to conductance‐driven time‐varying inputs

Ensembles of cortical neurons can track fast‐varying inputs and relay them in their spike trains, far beyond the cut‐off imposed by membrane passive electrical properties and mean firing rates. Initially explored in silico and later demonstrated experimentally, investigating how neurons respond to sinusoidally modulated stimuli provides a deeper insight into spike initiation mechanisms and information processing than conventional F–I curve methodologies. Besides net membrane currents, physiological synaptic inputs can also induce a stimulus‐dependent modulation of the total membrane conductance, which is not reproduced by standard current‐clamp protocols. Here, we investigated whether rat cortical neurons can track fast temporal modulations over a noisy conductance background. We also determined input–output transfer properties over a range of conditions, including: distinct presynaptic activation rates, postsynaptic firing rates and variability and type of temporal modulations. We found a very broad signal transfer bandwidth across all conditions, similar large cut‐off frequencies and power‐law attenuations of fast‐varying inputs. At slow and intermediate input modulations, the response gain decreased for increasing output mean firing rates. The gain also decreased significantly for increasing intensities of background synaptic activity, thus generalising earlier studies on F‐I curves. We also found a direct correlation between the action potentials' onset rapidness and the neuronal bandwidth. Our novel results extend previous investigations of dynamical response properties to non‐stationary and conductance‐driven conditions, and provide computational neuroscientists with a novel set of observations that models must capture when aiming to replicate cortical cellular excitability.     

Interactions between behaviorally relevant rhythms and synaptic plasticity alter coding in the piriform cortex

Understanding how neural and behavioral timescales interact to influence cortical activity and stimulus coding is an important issue in sensory neuroscience. In air-breathing animals, voluntary changes in respiratory frequency alter the temporal patterning olfactory input. In the olfactory bulb, these behavioral timescales are reflected in the temporal properties of mitral/tufted (M/T) cell spike trains. As the odor information contained in these spike trains is relayed from the bulb to the cortex, interactions between presynaptic spike timing and short-term synaptic plasticity dictate how stimulus features are represented in cortical spike trains. Here, we demonstrate how the timescales associated with respiratory frequency, spike timing, and short-term synaptic plasticity interact to shape cortical responses. Specifically, we quantified the timescales of short-term synaptic facilitation and depression at excitatory synapses between bulbar M/T cells and cortical neurons in slices of mouse olfactory cortex. We then used these results to generate simulated M/T population synaptic currents that were injected into real cortical neurons. M/T population inputs were modulated at frequencies consistent with passive respiration or active sniffing. We show how the differential recruitment of short-term plasticity at breathing versus sniffing frequencies alters cortical spike responses. For inputs at sniffing frequencies, cortical neurons linearly encoded increases in presynaptic firing rates with increased phase-locked, firing rates. In contrast, at passive breathing frequencies, cortical responses saturated with changes in presynaptic rate. Our results suggest that changes in respiratory behavior can gate the transfer of stimulus information between the olfactory bulb and cortex.     

Functional synaptic circuits in the subplate during fetal and early postnatal development of cat visual cortex

Among the first postmitotic cells of the cerebral cortex is a special population located below the cortical plate: the subplate neurons. These neurons reach a high degree of morphological maturity during fetal life, well before the neurons of the cortical layers have matured, yet nearly all of these cells die after birth in the cat. Subplate neurons are also known to receive synaptic contacts. Here we have investigated whether these contacts are functional by making intracellular recordings from subplate neurons in cortical slices maintained in vitro. Subplate neurons were identified based on their location and morphology by injecting them with biocytin following the intracellular recordings. At all ages studied between embryonic day 50 and postnatal day 9, electrical stimulation of the optic radiations elicited EPSPs and synaptic and antidromic spikes in subplate neurons, indicating that some of the synapses seen at the ultrastructural level are indeed capable of synaptic transmission. The spiking patterns of 39 morphologically identified subplate neurons were examined by injecting depolarizing current, which revealed that a large majority gave only a single spike or a brief train of spikes in response to maintained depolarization, in contrast to the regular spiking pattern found in many neurons of adult cortex. Biocytin injections into subplate neurons revealed that they are a morphologically heterogeneous population with respect to their dendritic branching patterns; roughly half were inverted pyramids, the classic subplate neuron morphology. The axonal processes of subplate neurons were remarkable in that many not only arborized within the subplate, but also entered the cortical plate and terminated in the marginal zone. At early postnatal ages, these axons also gave off collaterals within cortical layer 4. The results of this study indicate that subplate neurons participate in synaptic microcircuits during development. While the presynaptic identity of the input to subplate neurons is not known conclusively, it is likely that geniculocortical axons, which wait in close proximity to subplate neurons, contribute significantly. The pattern of axonal branching of subplate neurons also implies that information conferred to subplate neurons may be relayed, in turn, to the neurons of cortical layer 4. Finally with the death of subplate neurons, the geniculocortical axons leave the subplate and invade the cortical plate to innervate directly the neurons of layer 4. Thus, subplate neurons may function as a crucial, but transient synaptic link between waiting geniculocortical axons and their ultimate target cells in the cortex.     

Visibility of synaptically induced conductance changes: theory and simulations of anatomically characterized cortical pyramidal cells

A recent report has provided evidence that there are no significant increases in the neuronal input conductance during the response of cortical cells in cat visual cortex to non-preferred visual stimuli (Douglas et al., 1988). A criticism of experiments of this kind is that changes in the membrane conductance occurring in the dendritic tree may not be visible from electrodes that impale the soma. Our paper describes theoretical and numerical results concerning the visibility of synaptically induced conductance changes from intracellular electrodes, in both ideal and anatomically well-characterized cortical neurons. Based on earlier work by Rall (1967), we here derive theoretical expressions for the change in input conductance at any location in a passive dendritic tree resulting from activation of a single synapse and obtain bounds for the effects of multiple synapses. We find that the conductance change measured at the cell body is always less than the sum of the synaptic conductance changes and that this observed conductance change does not depend on the synaptic reversal potential. For the case of an infinite dendritic cylinder, the change in input resistance due to a single synaptic input decays exponentially with distance of the synapse from the recording site. Numerical simulations of synaptic inputs that change approximately as fast as the membrane time-constant produce an increase in input conductance that is only slightly less visible than that of a constant input. We also compute the changes in somatic input conductance of 2 morphologically identified pyramidal cells from cat visual cortex during activity of a single inhibitory basket cell with known synaptic input locations. We find that the increase in conductance due to the activity of the inhibitory basket cells is clearly visible from the cell body of the pyramidal cells and that a 70% reduction in the amplitude of excitation is associated with at least a 30% increase in somatic input conductance, which would be visible in intracellular recordings. Taken together with the negative experimental evidence of Douglas et al. (1988), our results cast doubt on a large class of models of direction selectivity that rely on synaptically mediated inhibitory conductance increases to veto or block excitatory conductances increases.     

Rhythmic neuronal activity in S2 somatosensory and insular cortices contribute to the initiation of absence‐related spike‐and‐wave discharges

Purpose: The origin of bilateral synchronous spike‐and‐wave discharges (SWDs) that underlie absence seizures has been widely debated. Studies in genetic rodent models suggest that SWDs originate from a restricted region in the somatosensory cortex. The properties of this initiation site remain unknown. Our goal was to characterize the interictal, preictal and ictal neuronal activity in the primary and secondary cortical regions (S1, S2) and in the adjacent insular cortex (IC) in Genetic Absence Epilepsy Rats from Strasbourg (GAERS). Methods: We performed electroencephalography (EEG) recordings in combination with multisite local field potential (LFP) and single cell juxtacellular recordings, and cortical electrical stimulations, in freely moving rats and those under neurolept‐anesthesia. Key Findings: The onset of the SWDs was preceded by 5–9 Hz field potential oscillations, which were detected earlier in S2 and IC than in S1. Sustained SWDs could be triggered by a 2‐s train of 7‐Hz electrical stimuli at a lower current intensity in S2 than in S1. In S2 and IC, subsets of neurons displayed rhythmic firing (5–9 Hz) in between seizures. S2 and IC layers V and VI neurons fired during the same time window, whereas in S1 layer VI, neurons fired before layer V neurons. Just before the spike component of each SW complex, short‐lasting high‐frequency oscillations consistently occurred in IC ～20 msec before S1. Significance: Our findings demonstrate that the S2/IC cortical areas are a critical component of the macro‐network that is responsible for the generation of absence‐related SWDs.