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Drug resistant epilepsy (DRE) is defined as the persistence of seizures despite at least two syndrome-adapted antiseizure drugs (ASD) used at efficacious daily dose. Despite the increasing number of available ASD, about a third of patients with epilepsy still suffer from drug resistance. Several factors are associated with the risk of evolution to DRE in patients with newly diagnosed epilepsy, including epilepsy onset in the infancy, intellectual disability, symptomatic epilepsy and abnormal neurological exam. Pharmacological management often consists in ASD polytherapy. However, because quality of life is driven by several factors in patients with DRE, including the tolerability of the treatment, ASD management should try to optimize efficacy while anticipating the risks of drug-related adverse events. All patients with DRE should be evaluated at least once in a tertiary epilepsy center, especially to discuss eligibility for non-pharmacological therapies. This is of paramount importance in patients with drug resistant focal epilepsy in whom epilepsy surgery can result in long-term seizure freedom. Vagus nerve stimulation, deep brain stimulation or cortical stimulation can also improve seizure control. Lastly, considering the effect of DRE on psychologic status and social integration, comprehensive care adaptations are always needed in order to improve patients' quality of life. Keywords: drug resistant epilepsy, epilepsy surgery, antiseizure drugs, comprehensive care

Three neuromodulation therapies have been appropriately tested and approved in refractory focal epilepsies: vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS), and closed-loop responsive neurostimulation of the epileptogenic zone or zones. These therapies are primarily palliative. Only a few individuals have achieved complete freedom from seizures for more than 12 months with these therapies, whereas more than half have benefited from long-term reduction in seizure frequency of more than 50%. Implantation-related adverse events primarily include infection and pain at the implant site. Intracranial haemorrhage is a frequent adverse event for ANT-DBS and responsive neurostimulation. Other stimulation-specific side-effects are observed with VNS and ANT-DBS. Biomarkers to predict response to neuromodulation therapies are not available, and high-level evidence to aid decision making about when and for whom these therapies should be preferred over other antiepileptic treatments is scant. Future studies are thus needed to address these shortfalls in knowledge, approve other forms of neuromodulation, and develop personalised closed-loop therapies with embedded machine learning. Until then, neuromodulation could be considered for individuals with intractable seizures, ideally after the possibility of curative surgical treatment has been carefully assessed and ruled out or judged less appropriate.

Epilepsy surgery is the most effective way to control seizures in patients with drug-resistant focal epilepsy, often leading to improvements in cognition, behaviour, and quality of life. Risks of serious adverse events and deterioration of clinical status can be minimised in carefully selected patients. Accordingly, guidelines recommend earlier and more systematic assessment of patients' eligibility for surgery than is seen at present. The effectiveness of surgical treatment depends on epilepsy type, underlying pathology, and accurate localisation of the epileptogenic brain region by various clinical, neuroimaging, and neurophysiological investigations. Substantial progress has been made in the methods of presurgical assessment, particularly in patients with normal features on MRI, but evidence is scarce for the indication and effect of most presurgical investigations, with no biomarker precisely delineating the epileptogenic zone. A priority for the development of epilepsy surgery is the generation of high-level evidence to promote the harmonisation and dissemination of best practices.

Estimating the value of alternative options is a key process in decision-making. Human functional magnetic resonance imaging and monkey electrophysiology studies have identified brain regions, such as the ventromedial prefrontal cortex (vmPFC) and lateral orbitofrontal cortex (lOFC), composing a value system. In the present study, in an effort to bridge across species and techniques, we investigated the neural representation of value ratings in 36 people with epilepsy, using intracranial electroencephalography. We found that subjective value was positively reflected in both vmPFC and lOFC high-frequency activity, plus several other brain regions, including the hippocampus. We then demonstrated that subjective value could be decoded (1) in pre-stimulus activity, (2) for various categories of items, (3) even during a distractive task and (4) as both linear and quadratic signals (encoding both value and confidence). Thus, our findings specify key functional properties of neural value signals (anticipation, generality, automaticity, quadraticity), which might provide insights into human irrational choice behaviors.Lopez-Persem et al. used intracranial recordings in people with epilepsy to uncover key functional properties of neural value signals that might explain irrational choice behavior.

Sudden unexpected death in epilepsy (SUDEP) represents the main cause of death in patients with refractory epilepsy. No evidence-based intervention to prevent SUDEP exists. We postulated that pooling data from randomised placebo-controlled trials in patients with refractory epilepsy might show a lower incidence of SUDEP in patients receiving antiepileptic drugs (AEDs) at efficacious doses than in those receiving placebo. We searched Medline and the Cochrane Library for randomised trials investigating any AED in the add-on treatment of drug-resistant epilepsy in adults. We extracted the number and causes of death in patients allocated to AEDs at doses that were more efficacious than placebo against seizures, AEDs at non-efficacious doses, and placebo. In our primary analysis, we compared the occurrence of definite or probable SUDEP between patients given efficacious AED doses and those given placebo using the Mantel-Haenszel method, with exclusion of trials with no event. Data of 33 deaths, including 20 deemed as SUDEP, were extracted from 112 eligible randomised trials. 18 deaths were classified as definite or probable SUDEP and two as possible SUDEP. Definite or probable SUDEP, all SUDEP, and all causes of death were significantly less frequent in the efficacious AED group than in the placebo group, with odds ratios of 0·17 (95% CI 0·05–0·57, p=0·0046), 0·17 (0·05–0·57, p=0·0046), and 0·37 (0·17–0·81, p=0·0131), respectively. Rates of definite or probable SUDEP per 1000 person-years were 0·9 (95% CI 0·2–2·7) in patients who received efficacious AED doses and 6·9 (3·8–11·6) in those allocated to placebo. Treatment with adjunctive AEDs at efficacious doses may have reduced the incidence of definite or probable SUDEP by more than seven times compared with placebo in patients with previously uncontrolled seizures. This result provides evidence in favour of active treatment revision for patients with refractory epilepsy. None.

Seizures are common after intracerebral hemorrhage, occurring in 6–15% of the patients, mostly in the first 72 h. Their incidence reaches 30% when subclinical or non-convulsive seizures are diagnosed by continuous electroencephalogram. Several risk factors for seizures have been described including cortical location of intracerebral hemorrhage, presence of intraventricular hemorrhage, total hemorrhage volume, and history of alcohol abuse. Seizures after intracerebral hemorrhage may theoretically be harmful as they can lead to sudden blood pressure fluctuations, increased intracranial pressure, and neuronal injury due to increased metabolic demand. Some recent studies suggest that acute symptomatic seizures (occurring within 7 days of stroke) are associated with worse functional outcome and increased risk of death despite accounting for other known prognostic factors such as age and baseline hemorrhage volume. However, the impact of seizures on prognosis is still debated and it remains unclear if treating or preventing seizures might lead to improved clinical outcome. Thus, the currently available scientific evidence does not support the routine use of antiseizure medication as primary prevention among patients with intracerebral hemorrhage. Only prospective adequately powered randomized-controlled trials will be able to answer whether seizure prophylaxis in the acute or longer term settings is beneficial or not in patients with intracerebral hemorrhage.

Whether maximizing rewards and minimizing punishments rely on distinct brain systems remains debated, given inconsistent results coming from human neuroimaging and animal electrophysiology studies. Bridging the gap across techniques, we recorded intracerebral activity from twenty participants while they performed an instrumental learning task. We found that both reward and punishment prediction errors (PE), estimated from computational modeling of choice behavior, correlate positively with broadband gamma activity (BGA) in several brain regions. In all cases, BGA scaled positively with the outcome (reward or punishment versus nothing) and negatively with the expectation (predictability of reward or punishment). However, reward PE were better signaled in some regions (such as the ventromedial prefrontal and lateral orbitofrontal cortex), and punishment PE in other regions (such as the anterior insula and dorsolateral prefrontal cortex). These regions might therefore belong to brain systems that differentially contribute to the repetition of rewarded choices and the avoidance of punished choices. Whether maximizing rewards and minimizing punishments rely on distinct brain learning systems remains debated. Here, using intracerebral recordings in humans, the authors provide evidence for brain regions differentially engaged in signaling reward and punishment prediction errors that prescribe repetition versus avoidance of past choices.

•The central autonomic network plays a major role in autonomic cardiac adjustments.•We studied cardiac autonomic reactivity to intracortical stimulations.•A core network within the brain is deeply involved in cardiac regulation.•A broader autonomic network also contributes to cardiac regulation.•This organization illustrates the close connection between heart and cerebral cortex. Recent growing neuroimaging evidence support that a set of cortical regions - the central autonomic network - is involved in autonomic control, but its functional organization remains unclear. We studied the direct autonomic cardiac effects produced by 1500 direct cortical electrical stimulations in 43 patients with epilepsy (32.8 ± 8.6 years old, 19 females) undergoing intracerebral recordings during presurgical evaluation. The time course of RR interval (RRI) reactivity and its variability were studied. Nearly half (48.6 %, n = 729) of the cortical stimulations resulted in a cardiac response, divided almost equally between bradycardia (24.47 %) and tachycardia (24.13 %), with no difference between right and left stimulations. Bradycardia was marked by an increase in parasympathetic heart control (increase in HF power and decrease in LF/HF ratio), while tachycardia was marked by a predominance in sympathetic heart control (decrease in HF power and increase in LF/HF ratio). We individualized a main network, where evoked bradycardia and tachycardia were strong, consisting of amygdala, posterior insula, frontal mesial premotor/prefrontal cortex, and anterior cingulate. Other brain regions were also involved, but to a lesser degree, with regions mostly in the limbic system and neocortex (sensory-motor/premotor and lateral temporal regions). These results highlight a close relationship between cerebral cortex and heart. Two hierarchically ordered networks were identified. A ‘core’ autonomic network strongly involved in cardiovascular regulation, consistent with the classical definition of CAN in functional imaging. But also a more ‘widespread’ autonomic network, both consistent with a major role of the cortex in continuous autonomic cardiac adjustments to high level emotional, cognitive or sensorimotor cortical activities. This study establishes for the first time a functional mapping of cardiac responses evoked by cortical electrical stimulations, and evidenced hierarchically ordered networks that extends the classical model of CAN. [Display omitted]

A plethora of neural centers in the central nervous system control the fundamental respiratory pattern. This control is ensured by neurons that act as pacemakers and which activity is modulated through chemical control that reacts to any changes in the O2/CO2 balance. Most of the respiratory neural centers are located in the brainstem, but are difficult to localize on magnetic resonance imaging (MRI) due to their small size, lack of visually-detectable borders with neighboured areas, and significant physiological noise hampering detection of its activity with functional MRI (fMRI). Yet, several approaches make it possible to study the normal response to different abnormal stimuli or conditions such as CO2 inhalation, induced hypercapnia, volitional apnea, induced hypoxia etc. This review provides a comprehensive overview of the majority of available studies on central respiratory control in humans.

How human prefrontal and insular regions interact while maximizing rewards and minimizing punishments is unknown. Capitalizing on human intracranial recordings, we demonstrate that the functional specificity toward reward or punishment learning is better disentangled by interactions compared to local representations. Prefrontal and insular cortices display non-selective neural populations to rewards and punishments. Non-selective responses, however, give rise to context-specific interareal interactions. We identify a reward subsystem with redundant interactions between the orbitofrontal and ventromedial prefrontal cortices, with a driving role of the latter. In addition, we find a punishment subsystem with redundant interactions between the insular and dorsolateral cortices, with a driving role of the insula. Finally, switching between reward and punishment learning is mediated by synergistic interactions between the two subsystems. These results provide a unifying explanation of distributed cortical representations and interactions supporting reward and punishment learning.