Overnight EEG to Forecast Epilepsy Development in Children with Autism Spectrum Disorders.

OBJECTIVE: To establish the utility of long-term electroencephalogram (EEG) in forecasting epilepsy onset in children with autism spectrum disorder (ASD). STUDY DESIGN: A single-institution, retrospective analysis of children with ASD, examining long-term overnight EEG recordings collected over a period of 15 years, was conducted. Clinical EEG findings, patient demographics, medical histories, and additional Autism Diagnostic Observation Schedule (ADOS) data were examined. Predictors for the timing of epilepsy onset were evaluated using survival analysis and Cox regression. RESULTS: Among 151 patients, 17.2% (n=26) developed unprovoked seizures (Sz group), while 82.8% (n=125) did not (non-Sz group). The Sz group displayed a higher percentage of interictal epileptiform discharges (IEDs) in their initial EEGs compared with the non-Sz group (46.2% vs. 20.0%, p=0.01). The Sz group also exhibited a greater frequency of slowing (42.3% vs. 13.6%, p < 0.01). The presence of IEDs or slowing predicted an earlier seizure onset, based on survival analysis. Multivariate Cox proportional hazards regression revealed that the presence of any IEDs (HR 3.83, 95% CI 1.38-10.65, p=0.01) or any slowing (HR 2.78, 95% CI 1.02-7.58, p=0.046 significantly increased the risk of developing unprovoked seizures. CONCLUSION: Long-term EEGs are valuable for predicting future epilepsy in children with ASD. These findings can guide clinicians in early education and potential interventions for epilepsy prevention.

Discovering Neurophysiological Characteristics of Pathological High-Frequency Oscillations in Epilepsy with an Explainable Deep Generative Model.

Interictal high-frequency oscillation (HFO) is a promising biomarker of the epileptogenic zone (EZ). However, objective definitions to distinguish between pathological and physiological HFOs have remained elusive, impeding HFOs' clinical applications. We employed self-supervised deep generative variational autoencoders to learn such discriminative HFO features directly from their morphologies in a data-driven manner. We studied a large retrospective cohort of 185 patients who underwent intracranial monitoring and analyzed 686,410 candidate HFO events collected from 18,265 brain contacts across diverse brain regions. The model automatically clustered HFOs into distinct morphological groups in the latent space. One cluster consisted of putative morphologically defined pathological HFOs (mpHFOs): HFOs in that cluster were observed to be associated with spikes and exhibited high signal intensity both in the HFO band (>80 Hz) at detection and in the sub-HFO band (10-80 Hz) surrounding the detection and were primarily localized in the seizure onset zone (SOZ). Moreover, resection of brain regions based on a higher prevalence of interictal mpHFOs better predicted postoperative seizure outcomes than current clinical standards based on SOZ removal. Our self-supervised, explainable, deep generative model distills pathological HFOs and thus potentially helps delineate the EZ purely from interictal intracranial EEG data.

Brain gray matter changes in children at risk for sudden unexpected death in epilepsy.

BACKGROUND: Potential failing adult brain sites, stratified by risk, mediating Sudden Unexpected Death in Epilepsy (SUDEP) have been described, but are unknown in children. METHODS: We examined regional brain volumes using T1-weighted MRI images in 21 children with epilepsy at high SUDEP risk and 62 healthy children, together with SUDEP risk scores, calculated from focal seizure frequency. Gray matter tissue type was partitioned, maps normalized, smoothed, and compared between groups (SPM12; ANCOVA; covariates, age, sex, and BMI). Partial correlations between regional volumes and seizure frequency were examined (SPM12, covariates, age, sex, and BMI); 67% were at high risk for SUDEP. RESULTS: The cerebellar cortex, hippocampus, amygdala, putamen, cingulate, thalamus, and para-hippocampal gyrus showed increased gray matter volumes in epilepsy, and decreased volumes in the posterior thalamus, lingual gyrus, and temporal cortices. The cingulate, insula, and putamen showed significant positive relationships with focal seizure frequency indices using whole-brain voxel-by-voxel partial correlations. Tissue volume changes in selected sites differed in direction from adults; particularly, cerebellar sites, key for hypotensive recovery, increased rather than adult declines. CONCLUSION: The volume increases may represent expansion by inflammatory or other processes that, with sustained repetitive seizure discharge, lead to tissue volume declines described earlier in adults. IMPACT: Children with epilepsy, who are at risk for Sudden Unexplained Death, show changes in brain volume that often differ in direction of change from adults at risk for SUDEP. Sites of volume change play significant roles in mediating breathing and blood pressure, and include areas that serve recovery from prolonged apnea and marked loss of blood pressure. The extent of volume changes correlated with focal seizure frequency. Although the underlying processes contributing to regional volume changes remain speculative, regions of tissue swelling in pediatric brain areas may represent transitory conditions that later lead to tissue loss in the adult condition.

WONOEP appraisal: Modeling early onset epilepsies.

Epilepsy has a peak incidence during the neonatal to early childhood period. These early onset epilepsies may be severe conditions frequently associated with comorbidities such as developmental deficits and intellectual disability and, in a significant percentage of patients, may be medication-resistant. The use of adult rodent models in the exploration of mechanisms and treatments for early life epilepsies is challenging, as it ignores significant age-specific developmental differences. More recently, models developed in immature animals, such as rodent pups, or in three-dimensional organoids may more closely model aspects of the immature brain and could result in more translatable findings. Although models are not perfect, they may offer a more controlled screening platform in studies of mechanisms and treatments, which cannot be done in pediatric patient cohorts. On the other hand, more simplified models with higher throughput capacities are required to deal with the large number of epilepsy candidate genes and the need for new treatment options. Therefore, a combination of different modeling approaches will be beneficial in addressing the unmet needs of pediatric epilepsy patients. In this review, we summarize the discussions on this topic that occurred during the XVI Workshop on Neurobiology of Epilepsy, organized in 2022 by the Neurobiology Commission of the International League Against Epilepsy. We provide an overview of selected models of early onset epilepsies, discussing their advantages and disadvantages. Heterologous expression models provide initial functional insights, and zebrafish, rodent models, and brain organoids present increasingly complex platforms for modeling and validating epilepsy-related phenomena. Together, these models offer valuable insights into early onset epilepsies and accelerate hypothesis generation and therapy discovery.

Giant chiral magnetoelectric oscillations in a van der Waals multiferroic.

Helical spin structures are expressions of magnetically induced chirality, entangling the dipolar and magnetic orders in materials1-4. The recent discovery of helical van der Waals multiferroics down to the ultrathin limit raises prospects of large chiral magnetoelectric correlations in two dimensions5,6. However, the exact nature and magnitude of these couplings have remained unknown so far. Here we perform a precision measurement of the dynamical magnetoelectric coupling for an enantiopure domain in an exfoliated van der Waals multiferroic. We evaluate this interaction in resonance with a collective electromagnon mode, capturing the impact of its oscillations on the dipolar and magnetic orders of the material with a suite of ultrafast optical probes. Our data show a giant natural optical activity at terahertz frequencies, characterized by quadrature modulations between the electric polarization and magnetization components. First-principles calculations further show that these chiral couplings originate from the synergy between the non-collinear spin texture and relativistic spin-orbit interactions, resulting in substantial enhancements over lattice-mediated effects. Our findings highlight the potential for intertwined orders to enable unique functionalities in the two-dimensional limit and pave the way for the development of van der Waals magnetoelectric devices operating at terahertz speeds.

WONOEP 2022: Neurotechnology for the diagnosis of epilepsy.

Epilepsy's myriad causes and clinical presentations ensure that accurate diagnoses and targeted treatments remain a challenge. Advanced neurotechnologies are needed to better characterize individual patients across multiple modalities and analytical techniques. At the XVIth Workshop on Neurobiology of Epilepsy: Early Onset Epilepsies: Neurobiology and Novel Therapeutic Strategies (WONOEP 2022), the session on "advanced tools" highlighted a range of approaches, from molecular phenotyping of genetic epilepsy models and resected tissue samples to imaging-guided localization of epileptogenic tissue for surgical resection of focal malformations. These tools integrate cutting edge research, clinical data acquisition, and advanced computational methods to leverage the rich information contained within increasingly large datasets. A number of common challenges and opportunities emerged, including the need for multidisciplinary collaboration, multimodal integration, potential ethical challenges, and the multistage path to clinical translation. Despite these challenges, advanced epilepsy neurotechnologies offer the potential to improve our understanding of the underlying causes of epilepsy and our capacity to provide patient-specific treatment.

Bilateral centromedian nucleus of thalamus responsive neurostimulation for pediatric-onset drug-resistant epilepsy.

Neuromodulation therapies offer an efficacious treatment alternative for patients with drug-resistant epilepsy (DRE), particularly those unlikely to benefit from surgical resection. Here we present our retrospective single-center case series of patients with pediatric-onset DRE who underwent responsive neurostimulation (RNS) depth electrode implantation targeting the bilateral centromedian nucleus (CM) of the thalamus between October 2020 and October 2022. Sixteen patients were identified; seizure outcomes, programming parameters, and complications at follow-up were reviewed. The median age at implantation was 13 years (range 3.6-22). Six patients (38%) were younger than 12 years of age at the time of implantation. Ictal electroencephalography (EEG) patterns during patients' most disabling seizures were reliably detected. Ten patients (62%) achieved 50% or greater reduction in seizure frequency at a median 1.3 years (range 0.6-2.6) of follow-up. Eight patients (50%) experienced sensorimotor side effects, and three patients (19%) had superficial pocket infection, prompting the removal of the RNS device. Side effects of stimulation were experienced mostly in monopolar-cathodal configuration and alleviated with programming change to bipolar configuration or low-frequency stimulation. Closed-loop neurostimulation using RNS targeting bilateral CM is a feasible and useful therapy for patients with pediatric-onset DRE.

Outpatient management of prolonged seizures and seizure clusters to prevent progression to a higher-level emergency: Consensus recommendations of an expert working group.

OBJECTIVE: The management of prolonged seizures (PS) and seizure clusters (SC) is impeded by the lack of international, evidence-based guidance. We aimed to develop expert recommendations regarding consensus definitions of PS, SC, and treatment goals to prevent progression to higher-level emergencies such as status epilepticus (SE). METHODS: An expert working group, comprising 12 epileptologists, neurologists, and pharmacologists from Europe and North America, used a modified Delphi consensus methodology to develop and anonymously vote on statements. Consensus was defined as ≥75% voting "Agree"/"Strongly agree." RESULTS: All group members strongly agreed that termination of an ongoing seizure in as short a time as possible is the primary goal of rapid and early seizure termination (REST) and that an ideal medication for REST would start to act within 2 min of administration to terminate ongoing seizure activity. Consensus was reached on the terminology defining PS (with proposed thresholds of 5 min for prolonged focal seizures and 2 min for prolonged absence seizures and the convulsive phase of bilateral tonic-clonic seizures) and SC (an abnormal increase in seizure frequency compared with the individual patient's usual seizure pattern). All group members strongly agreed or agreed that patients who have experienced a PS should be offered a REST medication, and all patients who have experienced a SC should be offered an acute cluster treatment (ACT). Further, when prescribing a REST medication or ACT, a seizure action plan should be agreed upon in consultation with the patient and caregiver. SIGNIFICANCE: The expert working group had a high level of agreement on the recommendations for defining and managing PS and SC. These recommendations will complement the existing guidance for the management of acute seizures, with the possibility of treating them earlier to potentially avoid progression to more severe seizures, including SE.

PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.

Objective. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.Approach. We introduced PyHFO, which enables time-efficient high-frequency oscillation (HFO) detection algorithms like short-term energy and Montreal Neurological Institute and Hospital detectors. It incorporates DL models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware.Main results. The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained DL model or use their EEG data for custom model training.Significance. PyHFO successfully bridges the computational challenge faced in applying DL techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset.

OBJECTIVE: Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. METHODS: We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset. RESULTS: In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. SIGNIFICANCE: It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Determining the Electron Scattering from Interfacial Coulomb Scatterers in Two-Dimensional Transistors.

Two-dimensional (2D) transistors are promising for potential applications in next-generation semiconductor chips. Owing to the atomically thin thickness of 2D materials, the carrier scattering from interfacial Coulomb scatterers greatly suppresses the carrier mobility and hampers transistor performance. However, a feasible method to quantitatively determine relevant Coulomb scattering parameters from interfacial long-range scatterers is largely lacking. Here, we demonstrate a method to determine the Coulomb scattering strength and the density of Coulomb scattering centers in InSe transistors by comprehensively analyzing the low-frequency noise and transport characteristics. Moreover, the relative contributions from long-range and short-range scattering in the InSe transistors can be distinguished. This method is employed to make InSe transistors consisting of various interfaces a model system, revealing the profound effects of different scattering sources on transport characteristics and low-frequency noise. Quantitatively accessing the scattering parameters of 2D transistors provides valuable insight into engineering the interfaces of a wide spectrum of ultrathin-body transistors for high-performance electronics.

Electrical and optoelectronic anisotropy and surface electron accumulation in ReS2 nanostructures.

Two interesting electronic transport properties including in-plane anisotropy and nonhomogeneous carrier distribution were observed in ReS2 nanoflakes. The electrical conductivity defined by the current parallel to the b-axis (‖b) is 32 times higher than that perpendicular to the b-axis (⊥b). Similar anisotropy was also observed in optoelectronic properties in which the ratio of responsivity ‖b to ⊥b reaches 20. In addition, conductivity and thermal activation energy with substantial thickness dependence were observed, which indicates a surface-dominant 2D transport in ReS2 nanoflakes. The presence of surface electron accumulation (SEA) in ReS2 has been confirmed by angle-resolved photoemission spectroscopy and scanning tunneling spectroscopy. The electron concentration (∼1019 cm-3) at the surface is over three orders of magnitude higher than that of the bulks. Sulfur vacancies which are sensitive to air molecules are suggested to be the major factor resulting in SEA and high conductivity in ReS2 nanostructures.

Ruthenium-Catalyzed Self-Coupling of Secondary Alcohols.

A simple catalytic method for self-coupling of secondary alcohols leading to the synthesis of ß-branched ketones under mild conditions is reported. Well-defined ruthenium pincer complex catalyzed the reactions. Optimization studies revealed that sodium tert-butoxide is an appropriate base for this transformation. Functionalized aryl methanols, heteroaryl methanols, and linear and branched aliphatic secondary alcohols underwent facile catalytic self-coupling reactions. Mechanistic studies revealed that both catalyst and base are crucial to achieve dehydrogenation of secondary alcohols to ketones, their subsequent controlled aldol condensation, and further hydrogenation of α,ß-unsaturated intermediates, leading to the selective formation of ß-branched ketone products. Notably, the noninnocent PNP ligand which displays amine-amide metal-ligand cooperation operative in a catalyst played a key role in facilitating this catalytic self-coupling of secondary alcohols. Liberated molecular hydrogen and water are the only byproducts.

Direct Synthesis of Aldoximes: Ruthenium-Catalyzed Coupling of Alcohols and Hydroxylamine Hydrochloride.

A catalytic method for the direct synthesis of oximes from alcohols and hydroxyl amine hydrochloride salt is reported. The reaction is catalyzed by a ruthenium pincer catalyst, which oxidizes alcohols involving amine-amide metal-ligand cooperation, and the in situ formed aldehydes condense with hydroxyl amine to deliver the oximes. Notably, the reaction requires only a catalyst and base; water and liberated hydrogen are the only byproducts, making this protocol attractive and environmentally benign.

Uncovering Spatiotemporal Dynamics of the Corticothalamic Network during Seizures.

Objective: Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human EEG recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. Methods: We analyzed ten patients (aged 2.7-28.1) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic coverage. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM). Results: In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. Interpretation: It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network during seizures, and this knowledge could guide personalized neuromodulation treatment strategies.

Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy.

OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery. METHODS: We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method. RESULTS: The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification. CONCLUSIONS: HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs. SIGNIFICANCE: Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Characteristics of ictal thalamic EEG in pediatric-onset neocortical focal epilepsy.

OBJECTIVE: To characterize ictal EEG change in the centromedian (CM) and anterior nucleus (AN) of the thalamus, using stereoelectroencephalography (SEEG) recordings. METHODS: Forty habitual seizures were analyzed in nine patients with pediatric-onset neocortical drug-resistant epilepsy who underwent SEEG (age 2-25 y) with thalamic coverage. Both visual and quantitative analysis was used to evaluate ictal EEG signal in the cortex and thalamus. The amplitude and cortico-thalamic latencies of broadband frequencies at ictal onset were measured. RESULTS: Visual analysis demonstrated consistent detection of ictal EEG changes in both the CM nucleus and AN nucleus with latency to thalamic ictal EEG changes of less than 400 ms in 95% of seizures, with low-voltage fast activity being the most common ictal pattern. Quantitative broadband amplitude analysis showed consistent power changes across the frequency bands, corresponding to ictal EEG onset, while while ictal EEG latency was variable from -18.0 seconds to 13.2 seconds. There was no significant difference between detection of CM and AN ictal activity on visual or amplitude analysis. Four patients with subsequent thalamic responsive neurostimulation (RNS) demonstrated ictal EEG changes consistent with SEEG findings. CONCLUSIONS: Ictal EEG changes were consistently seen at the CM and AN of the thalamus during neocortical seizures. SIGNIFICANCE: It may be feasible to use a closed-loop system in the thalamus to detect and modulate seizure activity for neocortical epilepsy.

Photoconduction Properties in Tungsten Disulfide Nanostructures.

We reported the photoconduction properties of tungsten disulfide (WS2) nanoflakes obtained by the mechanical exfoliation method. The photocurrent measurements were carried out using a 532 nm laser source with different illumination powers. The results reveal a linear dependence of photocurrent on the excitation power, and the photoresponsivity shows an independent behavior at higher light intensities (400-4000 Wm-2). The WS2 photodetector exhibits superior performance with responsivity in the range of 36-73 AW-1 and a normalized gain in the range of 3.5-7.3 10-6 cm2V-1 at a lower bias voltage of 1 V. The admirable photoresponse at different light intensities suggests that WS2 nanostructures are of potential as a building block for novel optoelectronic device applications.

Characteristics of ictal thalamic EEG in pediatric-onset neocortical focal epilepsy.

Objective: To characterize ictal EEG change in the centromedian (CM) and anterior nucleus (AN) of the thalamus, using stereoelectroencephalography (SEEG) recordings. Methods: Forty habitual seizures were analyzed in nine patients with pediatric-onset neocortical drug-resistant epilepsy who underwent SEEG (age 2-25 y) with thalamic coverage. Both visual and quantitative analysis was used to evaluate ictal EEG signal in the cortex and thalamus. The amplitude and cortico-thalamic latencies of broadband frequencies at ictal onset were measured. Results: Visual analysis demonstrated consistent detection of ictal EEG changes in both the CM nucleus and AN nucleus with latency to thalamic ictal EEG changes of less than 400ms in 95% of seizures, with low-voltage fast activity being the most common ictal pattern. Quantitative broadband amplitude analysis showed consistent power changes across the frequency bands, corresponding to ictal EEG onset, while while ictal EEG latency was variable from -18.0 seconds to 13.2 seconds. There was no significant difference between detection of CM and AN ictal activity on visual or amplitude analysis. Four patients with subsequent thalamic responsive neurostimulation (RNS) demonstrated ictal EEG changes consistent with SEEG findings. Conclusions: Ictal EEG changes were consistently seen at the CM and AN of the thalamus during neocortical seizures. Significance: It may be feasible to use a closed-loop system in the thalamus to detect and modulate seizure activity for neocortical epilepsy.

Ruthenium-Catalyzed Selective α-Alkylation of ß-Naphthols using Primary Alcohols: Elucidating the Influence of Base and Water.

Functionalized arenes and arenols have diverse applications in chemical synthesis and material chemistry. Selective functionalization of arenols is a topic of prime interest. In particular, direct alkylation of arenols using alcohols is a challenging task. In this report, a ruthenium pincer catalyzed direct α-alkylation of ß-naphthol using primary alcohols as alkylating reagents is reported. Notably, aryl and heteroaryl methanols and linear and branched aliphatic alcohols underwent selective alkylation reactions, in which water is the only byproduct. Notably, catalytically derived α-alkyl-ß-naphthol products displayed high absorbance, emissive properties, and quantum yields (up to 93.2 %). Dearomative bromination on α-alkyl-ß-naphthol is demonstrated as a synthetic application. Mechanistic studies indicate that the reaction involves an aldehyde intermediate. DFT studies support this finding and further reveal that a stoichiometric amount of base is required to make the aldol condensation as well as elementary steps required for regeneration of catalytically active species. In situ-generated water molecule from the aldol condensation reaction plays an important role in the regeneration of an active catalyst.