Bias-free estimation of information content in temporally sparse neuronal activity.

Applying information theoretic measures to neuronal activity data enables the quantification of neuronal encoding quality. However, when the sample size is limited, a naïve estimation of the information content typically contains a systematic overestimation (upward bias), which may lead to misinterpretation of coding characteristics. This bias is exacerbated in Ca2+ imaging because of the temporal sparsity of elevated Ca2+ signals. Here, we introduce methods to correct for the bias in the naïve estimation of information content from limited sample sizes and temporally sparse neuronal activity. We demonstrate the higher accuracy of our methods over previous ones, when applied to Ca2+ imaging data recorded from the mouse hippocampus and primary visual cortex, as well as to simulated data with matching tuning properties and firing statistics. Our bias-correction methods allowed an accurate estimation of the information place cells carry about the animal's position (spatial information) and uncovered the spatial resolution of hippocampal coding. Furthermore, using our methods, we found that cells with higher peak firing rates carry higher spatial information per spike and exposed differences between distinct hippocampal subfields in the long-term evolution of the spatial code. These results could be masked by the bias when applying the commonly used naïve calculation of information content. Thus, a bias-free estimation of information content can uncover otherwise overlooked properties of the neural code.

Dynamic changes in murine forebrain miR-211 expression associate with cholinergic imbalances and epileptiform activity.

Epilepsy is a common neurological disease, manifested in unprovoked recurrent seizures. Epileptogenesis may develop due to genetic or pharmacological origins or following injury, but it remains unclear how the unaffected brain escapes this susceptibility to seizures. Here, we report that dynamic changes in forebrain microRNA (miR)-211 in the mouse brain shift the threshold for spontaneous and pharmacologically induced seizures alongside changes in the cholinergic pathway genes, implicating this miR in the avoidance of seizures. We identified miR-211 as a putative attenuator of cholinergic-mediated seizures by intersecting forebrain miR profiles that were Argonaute precipitated, synaptic vesicle target enriched, or differentially expressed under pilocarpine-induced seizures, and validated TGFBR2 and the nicotinic antiinflammatory acetylcholine receptor nAChRa7 as murine and human miR-211 targets, respectively. To explore the link between miR-211 and epilepsy, we engineered dTg-211 mice with doxycycline-suppressible forebrain overexpression of miR-211. These mice reacted to doxycycline exposure by spontaneous electrocorticography-documented nonconvulsive seizures, accompanied by forebrain accumulation of the convulsive seizures mediating miR-134. RNA sequencing demonstrated in doxycycline-treated dTg-211 cortices overrepresentation of synaptic activity, Ca2+ transmembrane transport, TGFBR2 signaling, and cholinergic synapse pathways. Additionally, a cholinergic dysregulated mouse model overexpressing a miR refractory acetylcholinesterase-R splice variant showed a parallel propensity for convulsions, miR-211 decreases, and miR-134 elevation. Our findings demonstrate that in mice, dynamic miR-211 decreases induce hypersynchronization and nonconvulsive and convulsive seizures, accompanied by expression changes in cholinergic and TGFBR2 pathways as well as in miR-134. Realizing the importance of miR-211 dynamics opens new venues for translational diagnosis of and interference with epilepsy.

Electrocorticographic Dynamics as a Novel Biomarker in Five Models of Epileptogenesis.

Postinjury epilepsy (PIE) is a devastating sequela of various brain insults. While recent studies offer novel insights into the mechanisms underlying epileptogenesis and discover potential preventive treatments, the lack of PIE biomarkers hinders the clinical implementation of such treatments. Here we explored the biomarker potential of different electrographic features in five models of PIE. Electrocorticographic or intrahippocampal recordings of epileptogenesis (from the insult to the first spontaneous seizure) from two laboratories were analyzed in three mouse and two rat PIE models. Time, frequency, and fractal and nonlinear properties of the signals were examined, in addition to the daily rate of epileptiform spikes, the relative power of five frequency bands (theta, alpha, beta, low gamma, and high gamma) and the dynamics of these features over time. During the latent pre-seizure period, epileptiform spikes were more frequent in epileptic compared with nonepileptic rodents; however, this feature showed limited predictive power due to high inter- and intra-animal variability. While nondynamic rhythmic representation failed to predict epilepsy, the dynamics of the theta band were found to predict PIE with a sensitivity and specificity of >90%. Moreover, theta dynamics were found to be inversely correlated with the latency period (and thus predict the onset of seizures) and with the power change of the high-gamma rhythm. In addition, changes in theta band power during epileptogenesis were associated with altered locomotor activity and distorted circadian rhythm. These results suggest that changes in theta band during the epileptogenic period may serve as a diagnostic biomarker for epileptogenesis, able to predict the future onset of spontaneous seizures.SIGNIFICANCE STATEMENT Postinjury epilepsy is an unpreventable and devastating disorder that develops following brain injuries, such as traumatic brain injury and stroke, and is often associated with neuropsychiatric comorbidities. As PIE affects as many as 20% of brain-injured patients, reliable biomarkers are imperative before any preclinical therapeutics can find clinical translation. We demonstrate the capacity to predict the epileptic outcome in five different models of PIE, highlighting theta rhythm dynamics as a promising biomarker for epilepsy. Our findings prompt the exploration of theta dynamics (using repeated electroencephalographic recordings) as an epilepsy biomarker in brain injury patients.

Deviations from Critical Dynamics in Interictal Epileptiform Activity.

The framework of criticality provides a unifying perspective on neuronal dynamics from in vitro cortical cultures to functioning human brains. Recent findings suggest that a healthy cortex displays critical dynamics, giving rise to scale-free spatiotemporal cascades of activity, termed neuronal avalanches. Pharmacological manipulations of the excitation-inhibition balance (EIB) in cortical cultures were previously shown to result in deviations from criticality and from the power law scaling of avalanche size distribution. To examine the sensitivity of neuronal avalanche metrics to altered EIB in humans, we focused on epilepsy, a neurological disorder characterized by hyperexcitable networks. Using magnetoencephalography, we quantitatively assessed deviations from criticality in the brain dynamics of patients with epilepsy during interictal (between-seizures) activity. Compared with healthy control subjects, epilepsy patients tended to exhibit a higher neural gain and larger avalanches, particularly during interictal epileptiform activity. Moreover, deviations from scale-free behavior were exclusively connected to brief intervals at epileptiform discharges, strengthening the association between deviations from criticality and the instantaneous changes in EIB. The avalanches collected during interictal epileptiform activity had not only a stereotypical size range but also involved particular spatial patterns of activations, as expected for periods of epileptic network dominance. Overall, the neuronal avalanche metrics provide a quantitative novel description of interictal brain activity of patients with epilepsy. SIGNIFICANCE STATEMENT: Healthy brain dynamics requires a delicate balance between excitatory and inhibitory processes. Several brain disorders, such as epilepsy, are associated with altered excitation-inhibition balance, but assessing this balance using noninvasive tools is still challenging. In this study, we apply the framework of critical brain dynamics to data from epilepsy patients, which were recorded between seizures. We show that metrics of criticality provide a sensitive tool for noninvasive assessment of changes in the balance. Specifically, brain activity of epilepsy patients deviates from healthy critical brain dynamics, particularly during abnormal epileptiform activity. The study offers a novel quantitative perspective on epilepsy and its relation to healthy brain dynamics.

Blood-brain barrier dysfunction can contribute to pharmacoresistance of seizures.

OBJECTIVE: We tested the hypothesis that interstitial albumin can contribute to pharmacoresistance, which is common among patients with focal epilepsies. These patients often present with an open blood-brain barrier (BBB), resulting in diffusion of drug-binding albumin into the brain interstitial space. METHODS: Seizure-like events (SLEs) induced by 100 µm 4-aminopyridine (4-AP) were monitored using extracellular field potential recordings from acute rat entorhinal cortex-hippocampus slices. Effects of standard antiepileptic drugs (phenytoin, valproic acid, carbamazepine, and phenobarbital) were studied in the presence of albumin applied acutely or by intraventricular injection. Unbound antiepileptic drugs (AEDs) were detected by ultrafiltration and high-performance liquid chromatography (HPLC). RESULTS: Contrary to the absence of albumin, conventional AEDs failed to suppress SLEs in the rat entorhinal cortex in the presence of albumin. This effect was partially caused by buffering of phenytoin and carbamazepine (CBZ) by albumin. Increasing CBZ concentration from 50 µm to 100 µm resulted in block of SLEs. In slices obtained from animals that were pretreated with intraventricular albumin application 24 h prior to experiment, CBZ suppressed SLEs similar to control slices. We also found that application of serum-like electrolytes transformed SLEs into late recurrent discharges (LRDs), which were no longer responding to CBZ. SIGNIFICANCE: A dysfunctional BBB with acute extravasation of serum albumin into the brain's interstitial space could contribute to pharmacoresistance. In such instances, choice of an AED with low albumin binding affinity may help in seizure control.

Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code.

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we performed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

Multiple Maps of the Same Spatial Context Can Stably Coexist in the Mouse Hippocampus.

Hippocampal place cells selectively fire when an animal traverses a particular location and are considered a neural substrate of spatial memory. Place cells were shown to change their activity patterns (remap) across different spatial contexts but to maintain their spatial tuning in a fixed familiar context. Here, we show that mouse hippocampal neurons can globally remap, forming multiple distinct representations (maps) of the same familiar environment, without any apparent changes in sensory input or behavior. Alternations between maps occurred only across separate visits to the environment, implying switching between distinct stable attractors in the hippocampal network. Importantly, the different maps were spatially informative and persistent over weeks, demonstrating that they can be reliably stored and retrieved from long-term memory. Taken together, our results suggest that a memory of a given spatial context could be associated with multiple distinct neuronal representations, rather than just one.

Revealing neural correlates of behavior without behavioral measurements.

Measuring neuronal tuning curves has been instrumental for many discoveries in neuroscience but requires a priori assumptions regarding the identity of the encoded variables. We applied unsupervised learning to large-scale neuronal recordings in behaving mice from circuits involved in spatial cognition and uncovered a highly-organized internal structure of ensemble activity patterns. This emergent structure allowed defining for each neuron an 'internal tuning-curve' that characterizes its activity relative to the network activity, rather than relative to any predefined external variable, revealing place-tuning and head-direction tuning without relying on measurements of place or head-direction. Similar investigation in prefrontal cortex revealed schematic representations of distances and actions, and exposed a previously unknown variable, the 'trajectory-phase'. The internal structure was conserved across mice, allowing using one animal's data to decode another animal's behavior. Thus, the internal structure of neuronal activity itself enables reconstructing internal representations and discovering new behavioral variables hidden within a neural code.

Paroxysmal slow cortical activity in Alzheimer's disease and epilepsy is associated with blood-brain barrier dysfunction.

A growing body of evidence shows that epileptic activity is frequent but often undiagnosed in patients with Alzheimer's disease (AD) and has major therapeutic implications. Here, we analyzed electroencephalogram (EEG) data from patients with AD and found an EEG signature of transient slowing of the cortical network that we termed paroxysmal slow wave events (PSWEs). The occurrence per minute of the PSWEs was correlated with level of cognitive impairment. Interictal (between seizures) PSWEs were also found in patients with epilepsy, localized to cortical regions displaying blood-brain barrier (BBB) dysfunction, and in three rodent models with BBB pathology: aged mice, young 5x familial AD model, and status epilepticus-induced epilepsy in young rats. To investigate the potential causative role of BBB dysfunction in network modifications underlying PSWEs, we infused the serum protein albumin directly into the cerebral ventricles of naïve young rats. Infusion of albumin, but not artificial cerebrospinal fluid control, resulted in high incidence of PSWEs. Our results identify PSWEs as an EEG manifestation of nonconvulsive seizures in patients with AD and suggest BBB pathology as an underlying mechanism and as a promising therapeutic target.

Tracking the Same Neurons across Multiple Days in Ca2+ Imaging Data.

Ca2+ imaging techniques permit time-lapse recordings of neuronal activity from large populations over weeks. However, without identifying the same neurons across imaging sessions (cell registration), longitudinal analysis of the neural code is restricted to population-level statistics. Accurate cell registration becomes challenging with increased numbers of cells, sessions, and inter-session intervals. Current cell registration practices, whether manual or automatic, do not quantitatively evaluate registration accuracy, possibly leading to data misinterpretation. We developed a probabilistic method that automatically registers cells across multiple sessions and estimates the registration confidence for each registered cell. Using large-scale Ca2+ imaging data recorded over weeks from the hippocampus and cortex of freely behaving mice, we show that our method performs more accurate registration than previously used routines, yielding estimated error rates <5%, and that the registration is scalable for many sessions. Thus, our method allows reliable longitudinal analysis of the same neurons over long time periods.

Autosomal dominant epilepsy with auditory features: a new LGI1 family including a phenocopy with cortical dysplasia.

We report a new family with autosomal dominant epilepsy with auditory features (ADEAF) including focal cortical dysplasia (FCD) in the proband. We aim to identify the molecular cause in this family and clarify the relationship between FCD and ADEAF. A large Iranian Jewish family including 14 individuals with epileptic seizures was phenotyped including high-resolution 3-T MRI. We performed linkage analysis and exome sequencing. LGI1, KANK1 and RELN were Sanger sequenced. Seizure semiology of 11 individuals was consistent with ADEAF. The proband underwent surgery for right mesiotemporal FCD. 3-T MRIs in four individuals were unremarkable. Linkage analysis revealed peaks on chromosome 9p24 (LOD 2.43) and 10q22-25 (LOD 2.04). A novel heterozygous LGI1 mutation was identified in all affected individuals except for the proband indicating a phenocopy. Exome sequencing did not reveal variants within the chromosome 9p24 region. Closely located variants in KANK1 and a RELN variant did not segregate with the phenotype. We provide detailed description of the phenotypic spectrum within a large ADEAF family with a novel LGI1 mutation that was conspicuously absent in the proband with FCD, demonstrating that despite identical clinical symptoms, phenocopies in ADEAF families may exist. This family illustrates that rare epilepsy syndromes within a single family can have both genetic and structural etiologies.

Hippocampal ensemble dynamics timestamp events in long-term memory.

The capacity to remember temporal relationships between different events is essential to episodic memory, but little is currently known about its underlying mechanisms. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of episodic representations, despite stable place field locations and constant remapping between the two environments. These dynamics time-stamped experienced events via neuronal ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred. Temporally remote episodes had distinct timestamps, even if they occurred within the same spatial context. Our results suggest that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance.