The information content of physiological and epileptic brain activity

Loss of neuronal heterogeneity in epileptogenic human tissue impairs network resilience to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity, in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure-generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population-activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

Mechanisms for Cognitive Impairment in Epilepsy: Moving Beyond Seizures

There has been a major emphasis on defining the role of seizures in the causation of cognitive impairments like memory deficits in epilepsy. Here we focus on an alternative hypothesis behind these deficits, emphasizing the mechanisms of information processing underlying healthy cognition characterized as rate, temporal and population coding. We discuss the role of the underlying etiology of epilepsy in altering neural networks thereby leading to both the propensity for seizures and the associated cognitive impairments. In addition, we address potential treatments that can recover the network function in the context of a diseased brain, thereby improving both seizure and cognitive outcomes simultaneously. This review shows the importance of moving beyond seizures and approaching the deficits from a system-level perspective with the guidance of network neuroscience.

Decreased Intrinsic Neural Timescales in Mesial Temporal Lobe Epilepsy

It is well established that epilepsy is characterized by the destruction of the information capacity of brain network and the interference with information processing in regions outside the epileptogenic focus. However, the potential mechanism remains poorly understood. In the current study, we applied a recently proposed approach on the basis of resting-state fMRI data to measure altered local neural dynamics in mesial temporal lobe epilepsy (mTLE), which represents how long neural information is stored in a local brain area and reflect an ability of information integration. Using resting-state-fMRI data recorded from 36 subjects with mTLE and 36 healthy controls, we calculated the intrinsic neural timescales (INT) of neural signals by summing the positive magnitude of the autocorrelation of the resting-state brain activity. Compared to healthy controls, the INT values were significantly lower in patients in the right orbitofrontal cortices, right insula, and right posterior lobe of cerebellum. Whereas, we observed no statistically significant changes between patients with long- and short-term epilepsy duration or between left-mTLE and right-mTLE. Our study provides distinct insight into the brain abnormalities of mTLE from the perspective of the dynamics of the brain activity, highlighting the significant role of intrinsic timescale in understanding neurophysiological mechanisms. And we postulate that altered intrinsic timescales of neural signals in specific cortical brain areas may be the neurodynamic basis of cognitive impairment and emotional comorbidities in mTLE patients.

Repeated hippocampal seizures lead to brain-wide reorganization of circuits and seizure propagation pathways

Repeated seizure activity can lead to long-term changes in seizure dynamics and behavior. However, resulting changes in brain-wide dynamics remain poorly understood. This is due partly to technical challenges in precise seizure control and in vivo whole-brain mapping of circuit dynamics. Here, we developed an optogenetic kindling model through repeated stimulation of ventral hippocampal CaMKII neurons in adult rats. We then combined fMRI with electrophysiology to track brain-wide circuit dynamics resulting from non-afterdischarge (AD)-generating stimulations and individual convulsive seizures. Kindling induced widespread increases in non-AD-generating stimulation response and ipsilateral functional connectivity and elevated anxiety. Individual seizures in kindled animals showed more significant increases in brain-wide activity and bilateral functional connectivity. Onset time quantification provided evidence for kindled seizure propagation from the ipsilateral to the contralateral hemisphere. Furthermore, a core of slow-migrating hippocampal activity was identified in both non-kindled and kindled seizures, revealing a novel mechanism of seizure sustainment and propagation.

Impact of GABAA and GABAB Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States

Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABAA receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABAB receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network.SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABAA or GABAA receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest.

Changes of Ictal-Onset Epileptic Network Synchronicity in Childhood Absence Epilepsy: A Magnetoencephalography Study

Objective: To further understand the mechanisms underlying epileptic network and the characteristics of individual specific network, we conducted a study on brain network by magnetoencephalography (MEG) focusing on patients with childhood absence epilepsy (CAE). Methods: The network connectivity of 22 patients was investigated with MEG at the source level. Network connectivity of spikes and slow waves was computed with accumulated source imaging (ASI) and correlation analysis. Time-frequency analysis was used to characterize the network changes during the ictal-onset period of each patient and the potential factors. Results: We found that spectral power increased at around 1 s and distributed at 2-4 Hz in all patients. Ictal spikes simultaneously showed elevation of network connectivity, predominantly excitatory connections, when generalized firing activity spread to the overall brain. High-frequency oscillations (HFOs) were prone to detect overexcited neuronal firing in certain focal areas. Conclusions: Personal network changes during ictal onset had unique features in the time range and parallel seizure rhythm uniformly in every patient. There was an important time point for generalized discharges of the epileptic network. Ictal spiking activity played an important role in the epileptic network synchronicity of childhood absence epilepsy. Frequency oscillations provided references for locating abnormal changes in neuromagnetic signals.

Transient Cognitive Impairment in Epilepsy

Impairments of the dialog between excitation and inhibition (E/I) is commonly associated to neuropsychiatric disorders like autism, bipolar disorders and epilepsy. Moderate levels of hyperexcitability can lead to mild alterations of the EEG and are often associated with cognitive deficits even in the absence of overt seizures. Indeed, various testing paradigms have shown degraded performances in presence of acute or chronic non-ictal epileptiform activity. Evidences from both animal models and the clinics suggest that anomalous activity can cause cognitive deficits by transiently disrupting cortical processing, independently from the underlying etiology of the disease. Here, we will review our understanding of the influence of an abnormal EEG activity on brain computation in the context of the available clinical data and in genetic or pharmacological animal models.

Epileptiform activity in the mouse visual cortex interferes with cortical processing in connected areas

Epileptiform activity is associated with impairment of brain function even in absence of seizures, as demonstrated by failures in various testing paradigm in presence of hypersynchronous interictal spikes (ISs). Clinical evidence suggests that cognitive deficits might be directly caused by the anomalous activity rather than by its underlying etiology. Indeed, we seek to understand whether ISs interfere with neuronal processing in connected areas not directly participating in the hypersynchronous activity in an acute model of epilepsy. Here we cause focal ISs in the visual cortex of anesthetized mice and we determine that, even if ISs do not invade the opposite hemisphere, the local field potential is subtly disrupted with a modulation of firing probability imposed by the contralateral IS activity. Finally, we find that visual processing is altered depending on the temporal relationship between ISs and stimulus presentation. We conclude that focal ISs interact with normal cortical dynamics far from the epileptic focus, disrupting endogenous oscillatory rhythms and affecting information processing.

Integrative properties and transfer function of cortical neurons initiating absence seizures in a rat genetic model

KEY POINTS

Absence seizures are accompanied by spike-and-wave discharges in cortical electroencephalograms. These complex paroxysmal activities, affecting the thalamocortical networks, profoundly alter cognitive performances and preclude conscious perception. Here, using a well-recognized genetic model of absence epilepsy, we investigated in vivo how information processing was impaired in the ictogenic neurons, i.e. the population of cortical neurons responsible for seizure initiation. In between seizures, ictogenic neurons were more prone to generate bursting activity and their firing response to weak depolarizing events was considerably facilitated compared to control neurons. In the course of seizures, information processing became unstable in ictogenic cells, alternating between an increased and a decreased responsiveness to excitatory inputs, depending on the spike and wave patterns. The state-dependent modulation in the excitability of ictogenic neurons affects their inter-seizure transfer function and their time-to-time responsiveness to incoming inputs during absences.

ABSTRACT

Epileptic seizures result from aberrant cellular and/or synaptic properties that can alter the capacity of neurons to integrate and relay information. During absence seizures, spike-and-wave discharges (SWDs) interfere with incoming sensory inputs and preclude conscious experience. The Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established animal model of absence epilepsy, allows exploration of the cellular basis of this impaired information processing. Here, by combining in vivo electrocorticographic and intracellular recordings from GAERS and control animals, we investigated how the pro-ictogenic properties of seizure-initiating cortical neurons modify their integrative properties and input-output operation during inter-ictal periods and during the spike (S-) and wave (W-) cortical patterns alternating during seizures. In addition to a sustained depolarization and an excessive firing rate in between seizures, ictogenic neurons exhibited a pronounced hyperpolarization-activated depolarization compared to homotypic control neurons. Firing frequency versus injected current relations indicated an increased sensitivity of GAERS cells to weak excitatory inputs, without modifications in the trial-to-trial variability of current-induced firing. During SWDs, the W-component resulted in paradoxical effects in ictogenic neurons, associating an increased membrane input resistance with a reduction in the current-evoked firing responses. Conversely, the collapse of cell membrane resistance during the S-component was accompanied by an elevated current-evoked firing relative to W-sequences, which remained, however, lower compared to inter-ictal periods. These findings show a dynamic modulation of ictogenic neurons' intrinsic properties that may alter inter-seizure cortical function and participate in compromising information processing in cortical networks during absences.

Do Cortical Circuits Need Protecting from Themselves?

All hippocampal and neocortical networks can be driven to seize quite easily. This can be done using drugs, by altering the ionic constituency of the bathing medium [cerebrospinal fluid (CSF)], or by electrical stimulation (both experimentally and clinically, as in electroconvulsive therapy). It is worth asking why this is so, because this will both tell us more about potentially devastating neurological disorders and extend our understanding of cortical function and architecture. Here I review work examining the features of cortical networks that bias activity towards and away from hyperexcitability. I suggest that several cellular- and circuit-level features of rapidly responsive interneuron networks tip the balance away from seizure in the healthy brain.

The role of inhibition in epileptic networks

Inhibition plays many roles in cortical circuits, including coordination of network activity in different brain rhythms and neuronal clusters, gating of activity, gain control, and dictating the manner in which activity flows through the network. This latter is particularly relevant to epileptic states, when extreme hypersynchronous discharges can spread across cortical territories. We review these different physiological and pathological roles and discuss how inhibition can be compromised and why this predisposes the network to seizures.

Information in pallidal neurons increases with parkinsonian severity

INTRODUCTION

The motor symptoms of Parkinson's disease (PD) present with pathological neuronal activity in the basal ganglia. Although neuronal firing rate changes in the globus pallidus internus (GPi) and externus (GPe) are reported to underlie the development of PD motor signs, firing rates change inconsistently, vary confoundingly with some therapies, and are poor indicators of symptom severity.

METHODS

We explored the relationship between parkinsonian symptom severity and the effectiveness with which pallidal neurons transmit information. We quantify neuronal entropy and information - alternatives to firing rate and correlations respectively - in and between GPe and GPi neurons using a progressive, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, non-human primate model of PD.

RESULTS

Neuronal entropy and symptom severity were not linearly correlated: in both pallidal segments, entropy increased from naive to moderate parkinsonism, but decreased with further progression to the severely parkinsonian condition. In contrast, information transmitted from GPe to GPi increased consistently with symptom severity. Furthermore, antidromic information from GPi to GPe increased substantially with symptom severity. Together, these findings suggest that as parkinsonian severity increases, more and more information enters GPe and GPi from common sources, diminishing the relative importance of the orthodromic GPe to GPi connection.

CONCLUSIONS

With parkinsonian progression, the direct and indirect pathways lose their independence and start to convey redundant information. We hypothesize that a loss of parallel processing impairs the ability of the network to select and implement motor commands, thus promoting the hypokinetic symptoms of PD.

Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model

Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics.

Single unit action potentials in humans and the effect of seizure activity

Spike-sorting algorithms have been used to identify the firing patterns of isolated neurons ('single units') from implanted electrode recordings in patients undergoing assessment for epilepsy surgery, but we do not know their potential for providing helpful clinical information. It is important therefore to characterize both the stability of these recordings and also their context. A critical consideration is where the units are located with respect to the focus of the pathology. Recent analyses of neuronal spiking activity, recorded over extended spatial areas using microelectrode arrays, have demonstrated the importance of considering seizure activity in terms of two distinct spatial territories: the ictal core and penumbral territories. The pathological information in these two areas, however, is likely to be very different. We investigated, therefore, whether units could be followed reliably over prolonged periods of times in these two areas, including during seizure epochs. We isolated unit recordings from several hundred neurons from four patients undergoing video-telemetry monitoring for surgical evaluation of focal neocortical epilepsies. Unit stability could last in excess of 40 h, and across multiple seizures. A key finding was that in the penumbra, spike stereotypy was maintained even during the seizure. There was a net tendency towards increased penumbral firing during the seizure, although only a minority of units (10-20%) showed significant changes over the baseline period, and notably, these also included neurons showing significant reductions in firing. In contrast, within the ictal core territories, regions characterized by intense hypersynchronous multi-unit firing, our spike sorting algorithms failed as the units were incorporated into the seizure activity. No spike sorting was possible from that moment until the end of the seizure, but recovery of the spike shape was rapid following seizure termination: some units reappeared within tens of seconds of the end of the seizure, and over 80% reappeared within 3 min (τrecov = 104 ± 22 s). The recovery of the mean firing rate was close to pre-ictal levels also within this time frame, suggesting that the more protracted post-ictal state cannot be explained by persistent cellular neurophysiological dysfunction in either the penumbral or the core territories. These studies lay the foundation for future investigations of how these recordings may inform clinical practice.See Kimchi and Cash (doi:10.1093/awv264) for a scientific commentary on this article.

Subthalamic deep brain stimulation reduces pathological information transmission to the thalamus in a rat model of parkinsonism

The degeneration of dopaminergic neurons in the substantia nigra pars compacta leads to parkinsonian motor symptoms via changes in electrophysiological activity throughout the basal ganglia. High-frequency deep brain stimulation (DBS) partially treats these symptoms, but the mechanisms are unclear. We hypothesize that motor symptoms of Parkinson’s disease (PD) are associated with increased information transmission from basal ganglia output neurons to motor thalamus input neurons and that therapeutic DBS of the subthalamic nucleus (STN) treats these symptoms by reducing this extraneous information transmission. We tested these hypotheses in a unilateral, 6-hydroxydopamine-lesioned rodent model of hemiparkinsonism. Information transfer between basal ganglia output neurons and motor thalamus input neurons increased in both the orthodromic and antidromic directions with hemiparkinsonian (hPD) onset, and these changes were reversed by behaviorally therapeutic STN-DBS. Omnidirectional information increases in the parkinsonian state underscore the detrimental nature of that pathological information and suggest a loss of information channel independence. Therapeutic STN-DBS reduced that pathological information, suggesting an effective increase in the number of independent information channels. We interpret these data with a model in which pathological information and fewer information channels diminishes the scope of possible motor activities, driving parkinsonian symptoms. In this model, STN-DBS restores information-channel independence by eliminating or masking the parkinsonism-associated information, and thus enlarges the scope of possible motor activities, alleviating parkinsonian symptoms.

Deep brain stimulation of the subthalamic nucleus reestablishes neuronal information transmission in the 6-OHDA rat model of parkinsonism

Pathophysiological activity of basal ganglia neurons accompanies the motor symptoms of Parkinson's disease. High-frequency (>90 Hz) deep brain stimulation (DBS) reduces parkinsonian symptoms, but the mechanisms remain unclear. We hypothesize that parkinsonism-associated electrophysiological changes constitute an increase in neuronal firing pattern disorder and a concomitant decrease in information transmission through the ventral basal ganglia, and that effective DBS alleviates symptoms by decreasing neuronal disorder while simultaneously increasing information transfer through the same regions. We tested these hypotheses in the freely behaving, 6-hydroxydopamine-lesioned rat model of hemiparkinsonism. Following the onset of parkinsonism, mean neuronal firing rates were unchanged, despite a significant increase in firing pattern disorder (i.e., neuronal entropy), in both the globus pallidus and substantia nigra pars reticulata. This increase in neuronal entropy was reversed by symptom-alleviating DBS. Whereas increases in signal entropy are most commonly indicative of similar increases in information transmission, directed information through both regions was substantially reduced (>70%) following the onset of parkinsonism. Again, this decrease in information transmission was partially reversed by DBS. Together, these results suggest that the parkinsonian basal ganglia are rife with entropic activity and incapable of functional information transmission. Furthermore, they indicate that symptom-alleviating DBS works by lowering the entropic noise floor, enabling more information-rich signal propagation. In this view, the symptoms of parkinsonism may be more a default mode, normally overridden by healthy basal ganglia information. When that information is abolished by parkinsonian pathophysiology, hypokinetic symptoms emerge.