Review of epilepsy care in the Democratic Republic of the Congo.

Epilepsy imposes a substantial burden on the Democratic Republic of Congo (DRC). These challenges encompass the lack of comprehensive disease surveillance, an unresolved understanding of its pathophysiology, economic barriers limiting access to essential care, the absence of epilepsy surgical capabilities, and deeply ingrained societal stigmas. Notably, the national prevalence of epilepsy remains undetermined, with research primarily concentrating on infectious factors like Onchocerca volvulus, leaving other potential causes underexplored. Most patients lack insurance, incurring out-of-pocket expenses that often lead them to opt for traditional medicine rather than clinical care. Social stigma, perpetuated by common misconceptions, intensifies the social isolation experienced by individuals living with epilepsy. Additionally, surgical interventions are unavailable, and the accessibility of anti-seizure medications and healthcare infrastructure remains inadequate. Effectively tackling these interrelated challenges requires a multifaceted approach, including conducting research into region-specific factors contributing to epilepsy, increasing healthcare funding, subsidizing the costs of treatment, deploying mobile tools for extensive screening, launching awareness campaigns to dispel myths and reduce stigma, and promoting collaborations between traditional healers and medical practitioners to enhance local understanding and epilepsy management. Despite the difficulties, significant progress can be achieved through sustained and compassionate efforts to understand and eliminate the barriers faced by epilepsy patients in the region. This review outlines essential steps for alleviating the epilepsy burden in the DRC. PLAIN LANGUAGE SUMMARY: There are not enough resources to treat epilepsy in the DRC. PWEs struggle with stigma and the lack of money. Many of them still use traditional medicine for treatment and hold wrong beliefs about epilepsy. That is why there is a need for more resources to make the lives of PWEs better in the DRC.

Microscale Physiological Events on the Human Cortical Surface.

Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.

Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy.

Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence diagnosis based on MRI is challenging. Anatomical abnormalities underlying brain dysfunctions in IGE are unclear and their relation to the pathomechanisms of epileptogenesis is poorly understood. In this study, we applied connectometry, an advanced quantitative neuroimaging technique for investigating localised changes in white-matter tissues in vivo. Analysing white matter structures of 32 subjects we incorporated our in vivo findings in a computational model of seizure dynamics to suggest a plausible mechanism of epileptogenesis. Patients with IGE have significant bilateral alterations in major white-matter fascicles. In the cingulum, fornix, and superior longitudinal fasciculus, tract integrity is compromised, whereas in specific parts of tracts between thalamus and the precentral gyrus, tract integrity is enhanced in patients. Combining these alterations in a logistic regression model, we computed the decision boundary that discriminated patients and controls. The computational model, informed with the findings on the tract abnormalities, specifically highlighted the importance of enhanced cortico-reticular connections along with impaired cortico-cortical connections in inducing pathological seizure-like dynamics. We emphasise taking directionality of brain connectivity into consideration towards understanding the pathological mechanisms; this is possible by combining neuroimaging and computational modelling. Our imaging evidence of structural alterations suggest the loss of cortico-cortical and enhancement of cortico-thalamic fibre integrity in IGE. We further suggest that impaired connectivity from cortical regions to the thalamic reticular nucleus offers a therapeutic target for selectively modifying the brain circuit for reversing the mechanisms leading to epileptogenesis.

Not All Predictions Are Equal: "What" and "When" Predictions Modulate Activity in Auditory Cortex through Different Mechanisms.

Using predictions based on environmental regularities is fundamental for adaptive behavior. While it is widely accepted that predictions across different stimulus attributes (e.g., time and content) facilitate sensory processing, it is unknown whether predictions across these attributes rely on the same neural mechanism. Here, to elucidate the neural mechanisms of predictions, we combine invasive electrophysiological recordings (human electrocorticography in 4 females and 2 males) with computational modeling while manipulating predictions about content ("what") and time ("when"). We found that "when" predictions increased evoked activity over motor and prefrontal regions both at early (∼180 ms) and late (430-450 ms) latencies. "What" predictability, however, increased evoked activity only over prefrontal areas late in time (420-460 ms). Beyond these dissociable influences, we found that "what" and "when" predictability interactively modulated the amplitude of early (165 ms) evoked responses in the superior temporal gyrus. We modeled the observed neural responses using biophysically realistic neural mass models, to better understand whether "what" and "when" predictions tap into similar or different neurophysiological mechanisms. Our modeling results suggest that "what" and "when" predictability rely on complementary neural processes: "what" predictions increased short-term plasticity in auditory areas, whereas "when" predictability increased synaptic gain in motor areas. Thus, content and temporal predictions engage complementary neural mechanisms in different regions, suggesting domain-specific prediction signaling along the cortical hierarchy. Encoding predictions through different mechanisms may endow the brain with the flexibility to efficiently signal different sources of predictions, weight them by their reliability, and allow for their encoding without mutual interference.SIGNIFICANCE STATEMENT Predictions of different stimulus features facilitate sensory processing. However, it is unclear whether predictions of different attributes rely on similar or different neural mechanisms. By combining invasive electrophysiological recordings of cortical activity with experimental manipulations of participants' predictions about content and time of acoustic events, we found that the two types of predictions had dissociable influences on cortical activity, both in terms of the regions involved and the timing of the observed effects. Further, our biophysical modeling analysis suggests that predictability of content and time rely on complementary neural processes: short-term plasticity in auditory areas and synaptic gain in motor areas, respectively. This suggests that predictions of different features are encoded with complementary neural mechanisms in different brain regions.

Low frequency transcranial electrical stimulation does not entrain sleep rhythms measured by human intracranial recordings.

Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.

Functional neuroimaging abnormalities in idiopathic generalized epilepsy.

Magnetic resonance imaging (MRI) techniques have been used to quantitatively assess focal and network abnormalities. Idiopathic generalized epilepsy (IGE) is characterized by bilateral synchronous spike-wave discharges on electroencephalography (EEG) but normal clinical MRI. Dysfunctions involving the neocortex, particularly the prefrontal cortex, and thalamus likely contribute to seizure activity. To identify possible morphometric and functional differences in the brains of IGE patients and normal controls, we employed measures of thalamic volumes, cortical thickness, gray-white blurring, fractional anisotropy (FA) measures from diffusion tensor imaging (DTI) and fractional amplitude of low frequency fluctuations (fALFF) in thalamic subregions from resting state functional MRI. Data from 27 patients with IGE and 27 age- and sex-matched controls showed similar thalamic volumes, cortical thickness and gray-white contrast. There were no differences in FA values on DTI in tracts connecting the thalamus and prefrontal cortex. Functional analysis revealed decreased fALFF in the prefrontal cortex (PFC) subregion of the thalamus in patients with IGE. We provide minimum detectable effect sizes for each measure used in the study. Our analysis indicates that fMRI-based methods are more sensitive than quantitative structural techniques for characterizing brain abnormalities in IGE.

Slow cortical dynamics and the accumulation of information over long timescales.

Making sense of the world requires us to process information over multiple timescales. We sought to identify brain regions that accumulate information over short and long timescales and to characterize the distinguishing features of their dynamics. We recorded electrocorticographic (ECoG) signals from individuals watching intact and scrambled movies. Within sensory regions, fluctuations of high-frequency (64-200 Hz) power reliably tracked instantaneous low-level properties of the intact and scrambled movies. Within higher order regions, the power fluctuations were more reliable for the intact movie than the scrambled movie, indicating that these regions accumulate information over relatively long time periods (several seconds or longer). Slow (<0.1 Hz) fluctuations of high-frequency power with time courses locked to the movies were observed throughout the cortex. Slow fluctuations were relatively larger in regions that accumulated information over longer time periods, suggesting a connection between slow neuronal population dynamics and temporally extended information processing.

Perceiving identical sounds as speech or non-speech modulates activity in the left posterior superior temporal sulcus.

The left superior temporal cortex shows greater responsiveness to speech than to non-speech sounds according to previous neuroimaging studies, suggesting that this brain region has a special role in speech processing. However, since speech sounds differ acoustically from the non-speech sounds, it is possible that this region is not involved in speech perception per se, but rather in processing of some complex acoustic features. "Sine wave speech" (SWS) provides a tool to study neural speech specificity using identical acoustic stimuli, which can be perceived either as speech or non-speech, depending on previous experience of the stimuli. We scanned 21 subjects using 3T functional MRI in two sessions, both including SWS and control stimuli. In the pre-training session, all subjects perceived the SWS stimuli as non-speech. In the post-training session, the identical stimuli were perceived as speech by 16 subjects. In these subjects, SWS stimuli elicited significantly stronger activity within the left posterior superior temporal sulcus (STSp) in the post- vs. pre-training session. In contrast, activity in this region was not enhanced after training in 5 subjects who did not perceive SWS stimuli as speech. Moreover, the control stimuli, which were always perceived as non-speech, elicited similar activity in this region in both sessions. Altogether, the present findings suggest that activation of the neural speech representations in the left STSp might be a pre-requisite for hearing sounds as speech.