Interictal SEEG resting-state connectivity localizes seizure onset zone and predicts seizure outcome

Stereotactic-electroencephalography (SEEG) is a common neurosurgical method to localize epileptogenic zone in drug resistant epilepsy patients and inform treatment recommendations. In the current clinical practice, localization of epileptogenic zone typically requires prolonged recordings to capture seizure, which may take days to weeks. Although epilepsy surgery has been proven to be effective in general, the percentage of unsatisfactory seizure outcomes is still concerning. We developed a method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state SEEG data. In a cohort of 43 drug resistant epilepsy patients, we estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. We hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. We found higher excitability in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions, probably reflecting inhibitory input from non-SOZ to prevent seizure initiation. Greater differences in information flow between SOZ and non-SOZ regions were associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, our method localized the SOZ with an accuracy of 85% and predicted the seizure outcome with an accuracy of 77% using clinically determined SOZ. Overall, our study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.

A personalizable autonomous neural mass model of epileptic seizures

The prospect of personalized computational modeling in neurological disorders, and in particular in epilepsy, is poised to revolutionize the field. Work in the last two decades has demonstrated that neural mass models (NMM) can realistically reproduce and explain epileptic seizure transitions as recorded by electrophysiological methods (EEG, SEEG). In previous work, advances were achieved by i) increasing excitation in NMM and ii) heuristically varying network inhibitory coupling parameters or, equivalently, inhibitory synaptic gains. Based on those studies, we provide here a laminar neural mass model capable of realistically reproducing the electrical activity recorded by SEEG in the epileptogenic zone during interictal to ictal states. With the exception of the external noise input onto the pyramidal cell population, the model dynamics are autonomous --- all model parameters are static. By setting the system at a point close to bifurcation, seizure-like transitions are generated, including pre-ictal spikes, low voltage fast activity, and ictal rhythmic activity. A novel element in the model is a physiologically plausible algorithm for chloride accumulation dynamics: the gain of GABAergic post-synaptic potentials is modulated by the pathological accumulation of Cl$^-$ in pyramidal cells, due to high inhibitory input and/or dysfunctional chloride transport. In addition, in order to simulate SEEG signals to compare with real recordings performed in epileptic patients, the NMM is embedded first in a layered model of the neocortex and then in a realistic physical model. We compare modeling results with data from four epilepsy patient cases. By including key pathophysiological mechanisms, the proposed framework captures succinctly the electrophysiological phenomenology observed in ictal states, paving the way for robust personalization methods using brain network models based on NMMs.

Perisomatic Inhibition and Its Relation to Epilepsy and to Synchrony Generation in the Human Neocortex

Inhibitory neurons innervating the perisomatic region of cortical excitatory principal cells are known to control the emergence of several physiological and pathological synchronous events, including epileptic interictal spikes. In humans, little is known about their role in synchrony generation, although their changes in epilepsy have been thoroughly investigated. This paper demonstraits how parvalbumin (PV)- and type 1 cannabinoid receptor (CB1R)-positive perisomatic interneurons innervate pyramidal cell bodies, and their role in synchronous population events spontaneously emerging in the human epileptic and non-epileptic neocortex, in vitro. Quantitative electron microscopy showed that the overall, PV+ and CB1R+ somatic inhibitory inputs remained unchanged in focal cortical epilepsy. On the contrary, the size of PV-stained synapses increased, and their number decreased in epileptic samples, in synchrony generating regions. Pharmacology demonstrated—in conjunction with the electron microscopy—that although both perisomatic cell types participate, PV+ cells have stronger influence on the generation of population activity in epileptic samples. The somatic inhibitory input of neocortical pyramidal cells remained almost intact in epilepsy, but the larger and consequently more efficient somatic synapses might account for a higher synchrony in this neuron population. This, together with epileptic hyperexcitability, might make a cortical region predisposed to generate or participate in hypersynchronous events.

Control of parallel hippocampal output pathways by amygdalar long-range inhibition

Projections from the basal amygdala (BA) to the ventral hippocampus (vH) are proposed to provide information about the rewarding or threatening nature of learned associations to support appropriate goal-directed and anxiety-like behaviour. Such behaviour occurs via the differential activity of multiple, parallel populations of pyramidal neurons in vH that project to distinct downstream targets, but the nature of BA input and how it connects with these populations is unclear. Using channelrhodopsin-2-assisted circuit mapping in mice, we show that BA input to vH consists of both excitatory and inhibitory projections. Excitatory input specifically targets BA- and nucleus accumbens-projecting vH neurons, and avoids prefrontal cortex-projecting vH neurons; while inhibitory input preferentially targets BA-projecting neurons. Through this specific connectivity, BA inhibitory projections gate place-value associations by controlling the activity of nucleus accumbens-projecting vH neurons. Our results define a parallel excitatory and inhibitory projection from BA to vH that can support goal-directed behaviour.

Circuits for integrating learned and innate valences in the insect brain

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate to modify behavior.

Temporary Unilateral Hearing Loss Impairs Spatial Auditory Information Processing in Neurons in the Central Auditory System

Temporary conductive hearing loss (CHL) can lead to hearing impairments that persist beyond resolution of the CHL. In particular, unilateral CHL leads to deficits in auditory skills that rely on binaural input (e.g., spatial hearing). Here, we asked whether single neurons in the auditory midbrain, which integrate acoustic inputs from the two ears, are altered by a temporary CHL. We introduced 6 weeks of unilateral CHL to young adult chinchillas via foam earplug. Following CHL removal and restoration of peripheral input, single-unit recordings from inferior colliculus (ICC) neurons revealed the CHL decreased the efficacy of inhibitory input to the ICC contralateral to the earplug and increased inhibitory input ipsilateral to the earplug, effectively creating a higher proportion of monaural responsive neurons than binaural. Moreover, this resulted in a ∼10 dB shift in the coding of a binaural sound location cue (interaural-level difference, ILD) in ICC neurons relative to controls. The direction of the shift was consistent with a compensation of the altered ILDs due to the CHL. ICC neuron responses carried ∼37% less information about ILDs after CHL than control neurons. Cochlear peripheral-evoked responses confirmed that the CHL did not induce damage to the auditory periphery. We find that a temporary CHL altered auditory midbrain neurons by shifting binaural responses to ILD acoustic cues, suggesting a compensatory form of plasticity occurring by at least the level of the auditory midbrain, the ICC.

Persistent synaptic inhibition of the subthalamic nucleus by high frequency stimulation

Background: Deep brain stimulation (DBS) provides symptomatic relief in a growing number of neurological indications, but local synaptic dynamics in response to electrical stimulation that may relate to its mechanism of action have not been fully characterized. Objective: The objectives of this study were to (1) study local synaptic dynamics during high frequency extracellular stimulation of the subthalamic nucleus (STN), and (2) compare STN synaptic dynamics with those of the neighboring substantia nigra pars reticulata (SNr). Methods: Two microelectrodes were advanced into the STN and SNr of patients undergoing DBS surgery for PD. Neuronal firing and evoked field potentials (fEPs) were recorded with one microelectrode during stimulation from an adjacent microelectrode. Results: Excitatory and inhibitory fEPs could be discerned within the STN and their amplitudes predicted bidirectional effects on neuronal firing (p = .007). There were no differences between STN and SNr inhibitory fEP dynamics at low stimulation frequencies (p > .999). However, inhibitory neuronal responses were sustained over time in STN during high frequency stimulation, but not SNr (p < .001) where depression of inhibitory input was coupled with a return of neuronal firing (p = .003). Interpretation: Persistent inhibitory input to the STN suggests a local synaptic mechanism for the suppression of subthalamic firing during high frequency stimulation. Moreover, differences in the resiliency versus vulnerability of inhibitory inputs to the STN and SNr suggest a projection source- and frequency-specificity for this mechanism. The feasibility of targeting electrophysiologically-identified neural structures may provide insight into how DBS achieves frequency-specific modulation of neuronal projections.

Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex

Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. Within L2/3, PyrCs show functional and structural specializations depending on their pial depth, indicating participation in different functional microcircuits. However, it is unknown whether these depth-dependent differences result from separable L2/3 PyrC subtypes or whether functional and structural features represent a continuum while correlating with pial depth. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory synaptic connectivity across the depth of L2/3 in the binocular visual cortex (bV1) of female mice. We find that the structure of the apical but not the basal dendritic tree varies with pial depth, which is accompanied by differences in passive but not active electrophysiological properties. PyrCs in lower L2/3 receive increased excitatory and inhibitory input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. Complementary in vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper L2/3 PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper L2/3 PyrCs are more strongly driven by contralateral than ipsilateral eye stimulation. In contrast, orientation- and direction-selectivity of L2/3 PyrCs are not dependent on pial depth. Importantly, the transitions of the various properties are gradual, and cluster analysis does not support the classification of L2/3 PyrCs into discrete subtypes. These results show that L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth within L2/3, forming a continuum rather than representing discrete subtypes.

How Self-Appraisal Is Mediated by the Brain

Self-appraisal is a process that leads to the formation of self-esteem, which contributes to subjective well-being and mental health. Neuroimaging studies link self-esteem with the activity of the medial prefrontal cortex (MPFC), right temporoparietal junction (rTPJ), posterior cingulate cortex (PCC), anterior insula (AIns), and dorsolateral prefrontal cortex. It is not known, however, how the process of self-appraisal itself is mediated by the brain and how different nodes of the self-appraisal network interact with each other. In this study, we used multilevel mediation analysis of functional MRI data recorded during the trait adjective judgment task, treating the emotional valence of adjectives as the predictor, behavioral response as the dependent variable, and brain activity as the mediator. The mediation effect was revealed in the rTPJ. Dynamic causal modeling showed that positive self-descriptions trigger communication within the network, with the rTPJ exerting the strongest excitatory output and MPFC receiving the strongest excitatory input. rAIns receives the strongest inhibitory input and sends exclusively inhibitory connections to other regions pointing out to its role in the processing of negative self-descriptions. Analysis of individual differences showed that in some individuals, self-appraisal is mostly driven by the endorsement of positive self-descriptions and is accompanied by increased activation and communication between rTPJ, MPFC, and PCC. In others, self-appraisal is driven by the rejection of negative self-descriptions and is accompanied by increased activation of rAIns and inhibition of PCC and MPFC. Membership of these groups was predicted by different personality variables. This evidence uncovers different mechanisms of positive self-bias, which may contribute to different facets of self-esteem and are associated with different personality profiles.