A New Neuromodulation Tool: TheAcoustic Non-Periodic Stimulation

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Lucena, Igor T.M. Oliveira, José G. V. Miranda, Belmira L.S.A Costa, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7049350/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Epilepsy represents a significant contemporary challenge. Approximately one-third of epileptic patients are considered refractory, meaning they resist conventional pharmacological treatment. In response to the need for alternative methods to control epilepsy, our research group developed Non-Periodic Acoustic Stimulation (ANPS). The present study aimed to assess the electrophysiological characteristics of ANPS in individuals with and without epilepsy, as well as to determine if this stimulus would induce the same effect as a control stimulus of white noise (WN). Evaluations were conducted using EEG before, during, and after applying ANPS and WN in the respective groups. The analysis was based on intracortical electrical density (sLORETA). ANPS, but not WN, showed statistically significant differences in activation within the theta and beta 1 frequency bands in the epilepsy group (EG), but not in the control group (CG). The areas of greater activation were observed in the frontal and parietal regions. These findings suggest that ANPS exhibited distinct electrophysiological characteristics compared to WN and that patients with epilepsy responded differently to ANPS compared to individuals without epilepsy. ANPS in patients with epilepsy promoted increased activity in regions involved in the dorsal pathway, likely interfering with sound source localization function. To our notice, it is the first time that a sound reduced epileptic seizures in refractory patients. ANPS s eems to be a new neuromodulation tool, with brain effects differing from normal acoustic stimulation. Acoustic Stimulation EEG Non-Periodic Stimulation Epilepsy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Epilepsy is a chronic brain disorder with profound effects on life quality. Approximately 50 million people worldwide have epilepsy, making it one of the most common neurological diseases 1 . Epilepsy is characterized by a lasting predisposition to generate spontaneous epileptic seizures and has numerous neurobiological, cognitive, and psychosocial consequences 2 . Seizures occur when there is abnormal synchronous neuronal firing in a brain region or throughout the brain, often due to irregular network formation or disruption caused by structural, infectious, or metabolic disorders 2 . It is believed that the origin of seizures is deeply linked to a hyperexcitability and hypersynchrony characteristic of neural tissue activity 3,4 . Neuronal hypersynchronization occurs when excitatory mechanisms prevail, resulting from increased excitation or decreased inhibition. As abnormal hypersynchronized neuronal activity continues, more and more neurons are activated (high-frequency depolarization/repolarization), leading to an epileptiform crisis 5 . For clarity, synchrony can be defined as the relationship between the dynamics of two coupled oscillatory systems 6 . Thus, if the oscillatory activity of one neural circuit drives the dynamics of another, they are said to be synchronized, and some form of synchronization can be objectively observed in their temporal characteristics 7 . In epilepsy, hypersynchronization contributes to the aberrant coupling of dysfunctional hyperactive microoscillators, giving rise to seizures 8,9 , while desynchronization induces functional isolation that purportedly impairs epileptic phenomena 7,10 . Mounting evidence suggests that hypersynchrony is also a key factor in understanding the disease and enabling robust, safe, and effective treatment 7,9,10 . As many epileptic patients are refractory, that is, experiencing seizures despite taking medications, there is a strong demand for new concepts and methods to block the phenomenon beyond the molecular level with pharmacological agonists or antagonists to specific receptors 11 . One alternative is to intervene at the circuit and network levels 12_14 . These approaches would recruit not only glutamatergic or GABAergic neurons, but also networks involving other neurotransmitters and cell types (e.g., glia) 15 , orchestrating brain connectivity to a different functional state apart from the strong attractors of epilepsy 16 . These concepts are based on the complexity of neural networks, interchangeability between temporally connected hubs, information distribution, and local recruitments 16_18 . The desynchronization of epileptogenic neural networks has been demonstrated in various investigations as a mechanism responsible for the effectiveness of neurostimulation 10 . Studies that employed non-periodic electrical stimulation, i.e., low-frequency stimuli with randomized pulse intervals, have shown anticonvulsant properties in animal models subjected to controlled infusion of the convulsive drug pentetrazol (PTZ) 4,7 . Another independent research group demonstrated that a similar approach also impairs epileptogenesis in a kindling animal model 19 . Based on this premise, the non-periodic acoustic stimulation (ANPS) was developed in our laboratory. This stimulus is based on the principle of NPS but is non-invasive, employing asynchronous low-frequency auditory pulses randomized according to a power law. ANPS is a stereo soundtrack with a baseband of 400 Hz that is interrupted by very short, slightly faster events called "pulses." Recent studies 20 in patients with refractory epilepsy showed a significant effect on reducing overall connectivity in the brain network during the acute phase, i.e., shortly after ANPS usage. Furthermore, it was observed that there was a change in the arrangement of connections, as evidenced by variations in hubs 20 . The logic behind ANPS is to shift brain oscillatory activity from low to high, starting with the brainstem nuclei responsible for auditory processing, which would also modulate the cortex at both molecular and circuital levels. Based on this, the present study aimed to evaluate the electrophysiological effects of ANPS in individuals with and without epilepsy and to investigate whether this stimulus would cause the same effect as a control stimulus (white noise). The main question of the present work is concerned with the genuine effects of ANPS in the brain compared to a normal sound like white noise in adult patients with epilepsy (PWE) and healthy controls (HC). Additionally, as ANPS was developed to control seizures, we also conducted a pilot study to check if it could somehow interfere with seizure frequency in microcephalic children. Methods Acoustic Non-Periodic Stimulation ANPS has been developed (patent pending process BR 10 2019 009701 9). The ANPS was constructed as follows: first, a 60000 points x axis was created in the Octave software. This corresponds to 60 epochs of 1000 points each, that is, 60 s of 1 second epoch (divided in 1000 ms). Based on this x axis, a 400 Hz sinusoid was constructed. Four aleatory points (called “pulse locations”) were chosen every second (that is, every 1000 points of the x axis). This implies that ANPS is a 4Hz stimulation (four pulses every second). In each pulse location, 5 points (corresponding to 5 ms) of the signal were substituted for the same number of points of another sinusoid, a 420 Hz with a 20% increase in amplitude compared to the initial 400 Hz one. The soundtrack was later exported to the Audacity 2.0 software (open source, multiplatform audio editor) and recorded in WAV format to be reproduced on acoustic stimulus reproduction devices (cell phones, computers) without interruption. The acoustic stimulus has the same baseband in both ears, but the pulse locations are different in the acoustic stimulus emitted for the right and left ear. This strategy was also based on the NPS, as it has maximum effectiveness when applied bilaterally and asynchronously 21 . Headphones are needed because it is a stereo sound. Adult Participants The procedures were approved by the Ethics Committee of the Federal University of Pernambuco, Brazil (protocol 4.983.183) and written consent was obtained from all participants. The research included 40 individuals, divided into two groups: patients with epilepsy (Experimental Group, EG, n=20; 14 females, 32.5 ± 14.8 years) and 20 individuals without epilepsy (Control Group, CG, n=20, 12 females, 36.1 ± 15.2 years) recruited through publications on social media and dissemination in epilepsy patient groups. Among the patients with epilepsy, 45% had focal epilepsy and 40% had generalized epilepsy. Additionally, 70% of them were on multiple medications, and 70% reported experiencing up to 1 seizure per year, with 50% of these patients experiencing monthly seizures. EEG data recording and procedures in Adult Participants High-density EEG recording was performed using a 32-channel electrode cap (Nautilus, G.TEC, Austria). The sampling rate was 500 Hz, with a band-pass filter set to 0.5 to 50 Hz, and the reference electrode used was Cz. The impedance between each electrode was kept below 5 kΩ. A baseline EEG was recorded and remained for 2 minutes. Then, the hearing threshold was measured. White noise or ANPS was played by the computer and the volume was initially set to zero, increased afterward in 1% steps until the participant warned that started to hear. All stimulations had an intensity of 30 dB above the hearing threshold. The computer output sound was calibrated. This aims to ensure that the stimulus is audible but comfortable 22 . Subsequently, the volunteer received acoustic stimulation. The duration of each acoustic stimulation was 10 min, with a 2 min interval of silence between them. Half of the subjects received ANPS stimuli and, 2 min later, white noise. The white noise is Gaussian and was created in the free software Audacity. In the others, this was reversed (see Fig 1.), to exclude any synergism effects. The instructions that participants (patients and health volunteers) received was that our laboratory was testing new acoustic stimulation with possible effects on epilepsy, but at that time it was not known if they actually had anticonvulsant effects. It was also said that the main objective of the research was to evaluate two acoustic stimulation effects on the brain. It was not told to participants that one of those acoustic stimulations was the control (white noise) and the other was supposed to be the verum acoustic stimulation (ANPS). This procedure was used to avoid any kind of expectation. Participants were instructed simply to listen to the presented acoustic stimulation. sLORETA Analysis of EEG recordings from adult participants The EEG signals were preprocessed using Matlab® software, version 2018, and EEGLAB. The EEG signals were re-referenced to the average of the electrodes, which approximates the ideal reference at infinity. The data were band-pass filtered between 0.5 and 50 Hz, with an amplitude threshold set between 100 µV and -100 µV during automatic filtering, followed by manual filtering when necessary. After these procedures, the tasks were separated, and for each patient, it was used two epochs containing 60 seconds: Acoustic Non-Periodic Stimulation (NP) and white noise (WN). The preprocessed data were then analyzed using the sLORETA software 23,24 . For each subject in the study, the mean of the cross-spectral matrices was computed for the classical frequency bands (δ delta [1.5...6], θ theta [6.5...8], α alpha [8.5...12], β1 beta 1 [12.5...18], β2 beta 2 [18.5...21], β3 beta 3 [21.5...30]), considering the total number of electrodes = 31, and a sampling rate of 500Hz. Using the statistical package of sLORETA, EEG records were calculated through the log of the ratio of averages, followed by 5000 data randomizations. To correct for multiple comparisons, the non-parametric single-threshold test based on the theory of randomization and permutation tests developed by Nichols and Holmes for functional mapping experiments 25 was used. The procedure for correcting for multiple hypotheses testing is known as the t-max test. The t-max statistic with a logarithmic calculation of the ratio between averages is the non-parametric analysis established in LORETA, which provides, after the randomization procedure, a random distribution of the maximum statistic in each voxel, resulting in a threshold for p-values of 0.01, 0.05, and 0.10. These thresholds for each p-value correspond to the values that fall between 1%, 5%, and 10%, respectively, of the highest values obtained in the randomization. The t-max test has demonstrated excellent control over type I errors. Results are considered significant at an alpha of 0.05. A two-tailed statistical test was considered significant for the voxel that exceeded the t-max significance threshold. For each significantly different voxel between PWE and controls, the corresponding Brodmann area (BA) was identified in the Talairach Brain Atlas 23 . Results Adult participants. Comparison of intracortical current density in patients with epilepsy and epilepsy-free controls during ANPS stimulation In Table 1 and Fig. 2 , the results for the non-parametric variance test employed by sLORETA during the use of ANPS in the experimental group (EG) and the control group (CG) are presented. For the voxel-to-voxel analysis of current source density, a two-tailed threshold of t(max) = 3.776 for p = 0.05 was determined based on the calculated values. Areas showing activation values exceeding the t(max) threshold, i.e., greater than 3.776, exhibit statistically significant differences (p < 0.05). Table 1 Location of cortical areas with statistically significant higher activation during the use of ANPS in subjects with epilepsy compared to controls Brodmann Area Region Frequency Value of max est. Coordinates location (X, Y, Z) 44 Precentral gyrus Theta 4.349 55, 10, 15 44 Inferior frontal gyrus Theta 4.332 60, 15, 15 45 Inferior frontal gyrus Theta 4.249 60, 10, 20 13 Insula (sublobar region) Theta 4.033 40, 10, 10 9 Inferior frontal gyrus Theta 4.016 55, 20, 25 46 Middle frontal gyrus Theta 4.007 55, 25, 25 6 Precentral gyrus Theta 3.972 55, 0, 15 46 Inferior frontal gyrus Theta 3.940 50, 30, 20 43 Postcentral gyrus, parietal lobe Theta 3.783 65, -5, 15 40 Inferior parietal lobe Beta 1 3.926 -55, -35, 45 40 Postcentral gyrus, parietal lobe Beta 1 3.923 -50, -35, 50 2 Postcentral gyrus, parietal lobe Beta 1 3.855 -45, -30, 50 22 Superior temporal gyrus Beta 1 3.782 65, -40, 20 42 Superior temporal gyrus Beta 1 3.778 65, -35, 20 Frequencies related to t(max) = 3.776 for α = 0.05 In the theta frequency band, statistically significant activations (p < 0.05; t(max) test) were observed in the inferior and middle frontal regions, as well as in the parietal region (postcentral gyrus) and insular cortex in the EG (Table 1 ). In the beta 1 frequency band (p < 0.05; t(max) test), greater activation was found in the parietal region (postcentral gyrus) and temporal region (superior temporal gyrus) in the EG (Table 1 ). An analysis of cortical activation caused by WN in the EG compared to the CG was also conducted, but no statistically significant areas or frequency bands were found in this comparison. In Fig. 2 , a three-dimensional representation of the areas that showed differences in cortical intracortical current density in the theta (Fig. 2 A) frequency band, and beta 1 (Fig. 2 B) frequency band during ANPS stimulation, as calculated by sLORETA. Hot pseudocolors (red and yellow) are depicted in those areas with statistically significant results (EG > CG). Cold pseudocolors (black to blue) represent areas where CG supposedly had higher values compared to EG, but none had statistical significance. Positive values indicate areas with greater activation in the EG compared to the CG, represented in warm colors. No areas were more activated by ANPS in the CG compared to the EG (depicted in blue). There were no statistically significant differences in other frequency bands during ANPS use between the groups. During the comparison between the EG and CG during white noise stimulation, no significant differences were observed in any EEG frequency band between the groups. Comparison of intracortical current density in adult patients with epilepsy during ANPS and white noise stimulation In this analysis, we aimed to identify statistically significant differences in cortical density during ANPS and WN stimulation, calculated for the following condition pairs: EG during ANPS - EG during WN. Table 2 presents the results of the ANPS-WN comparison in the EG. When comparing the voxel-to-voxel analysis of current source density in the EEG recording, a two-tailed threshold of t(max) = 4.038 for p = 0.05 was determined. Statistically significant results were observed in the theta frequency band of the EEG (p < 0.05; t(max) test), with areas of greater activation in the frontal region (inferior frontal gyrus, middle frontal gyrus, and precentral gyrus) during ANPS use in the EG. Additionally, in the beta 1 frequency band (p < 0.05; t-max test), significant activation was observed in the parietal region (postcentral gyrus) and frontal region (precentral gyrus) during ANPS in the EG. Figure 3 shows a three-dimensional representation of the areas that exhibited statistically significant differences in cortical intracortical current density in the theta and beta 1 frequency bands of the EEG during ANPS use, depicted in warm colors. There were no statistically significant differences in other frequency bands in the EG when comparing ANPS to WN. As for the CG listening to ANPS and RB (ANPS - RB for CG): no statistically significant results were found when comparing the voxel-to-voxel analysis of current source density in any EEG frequency band. Children with microcephaly Among the children included in this study, the most frequent type of seizures were spasms (55.5%), followed by generalized seizure type (33.3%) and focal seizure type (22.2%). Most children (66.6%) were using more than one type of antiseizure drug (ASD). A reduction in seizures in 88.8% of the children was observed. Only one child showed no change in seizure frequency during the two months of intervention. As a whole, there was a statistically significant reduction comparing two months before (147.0 +- 59.8 seizures, mean and SEM, n = 9) and two months after ANPS (47.8 +- 28.7) (p = 0.0078, two-tailed, Wilcoxon Signed Rank Test) (Fig. 4). FIGURE 4 AROUND HERE Regarding the adverse effects of ANPS, only two children described drowsiness, followed by nausea and mood change. As for the PGIC, it was observed that most of the parents (7/9) declared a good outcome from the stimulation, but two did not observe changes in the clinical aspect of their children. Discussion Although several cortical areas were activated by both WN and ANPS in both groups, such as the primary auditory area, only those areas that showed statistically significant activation by ANPS in the Experimental Group (EG) compared to the Control Group (EG - CG) were included in the main analysis. Additionally, areas that were differentially activated by ANPS compared to WN only in the EG (ANPS minus WN for EG) were also included. The sLORETA results showed that ANPS induced greater activation in the theta and beta1 frequency bands in patients with epilepsy (EG) but not in individuals without epilepsy (CG). The theta frequency band was predominant in frontal regions (BA 44, 45, 46, 9) extending to the precentral gyrus limit (BA 6). On the other hand, beta1 frequency was observed in more posterior regions, including parietal regions near the postcentral gyrus (BA 40, 43, and 2), and temporal gyrus (BA 22 and 42). In the literature, it has been described that in epilepsy, there may be increased theta and alpha connectivity in posterior regions and decreased connectivity in the beta band in pre and postcentral areas (sensorimotor areas) 26 . However, in the case of ANPS, an acoustic stimulus developed with the purpose of reducing epileptic seizures, the opposite was observed: there was an increase in slow oscillations (theta) in the anterior region and an increase in beta in the posterior sensorimotor regions of the brain. This may suggest a potential antagonism of circuits, where the effects of ANPS appear to be contrary to what is observed in epilepsy. Regarding the evaluation between ANPS and WN in the EG, we observed that ANPS maintained significant activation in the theta and beta1 frequency bands. In the theta frequency band, there was an increase in current density in the regions of the inferior frontal gyrus, middle frontal gyrus, and precentral gyrus (BA 6, 8, 9). In the beta1 frequency band, there was activation in the postcentral gyrus regions (BA 3, 4) during ANPS stimulation but not during WN stimulation. No differences were observed between the stimuli in the control group. Taken together, these data, along with the locations of the Broadmann areas involved in the dorsal and ventral sensory propagation pathways (introduction figure), suggest that ANPS appears to activate the dorsal pathway (BA 42, 40, 2, 3, 4, 6, and 8), terminating in the frontal and prefrontal areas (BA 9, 44, 45, and 46). It is known that this dorsal pathway, also known as the "where" pathway, transports information about the location of visual and auditory stimuli, in contrast to the ventral pathway, the "what" pathway 27 . One possible interpretation is that by providing an acoustic stimulation caused by pulses that never occur simultaneously in both ears (due to their shuffled asynchrony nature), we are deliberately altering the physiological system of spatial sound source localization. As this system is responsible for an essential and highly conserved function in animal phyla, to identify potential prey or predators even in the dark, the processing nuclei in the brainstem involved in the auditory pathway (cochlear nuclei, olivary complex, lateral lemniscus nucleus, inferior colliculus) may try to compare the incomparable. Determining a legitimate sound source, which may be closer to one ear than the other, will always result in the same stimulus being captured by both auditory pathways (ipsi and contralateral) but with a characteristic phase lag. It is precisely this phase lag that provides the clue about which ear received the acoustic stimulus first. This fact probably leads to changes in bottom-up synchronization, that is, from the brainstem to the primary auditory cortex. Upon reaching the cortex, one would expect this change to be more expressive in the dorsal pathway than in the ventral. After all, it is not about the identification of beings (what system) but rather about location (where system). More studies are needed to understand how ANPS acts in the brains of patients with epilepsy. Further investigations may consider separation by etiological groups or seizure types, as well as a larger sample size, to reduce sample variability. The ANPS was created to antagonize epileptic synchronism. The present study had a too small number of participants to confirm such a strong claim. However, the reduction in the number of seizures seen in children with microcephaly suggests this may be the case (Fig. 4). Conclusion Present results demonstrate that: The ANPS, in patients with epilepsy, increases theta and beta1 oscillations, and apparently activates the dorsal pathway ("where system") (BA 42, 40, 2, 3, 4, 6, and 8), terminating in frontal and prefrontal areas (BA 9, 44, 45, and 46) more than the ventral pathway ("what system"). This interference likely affects the functioning of sound source localization from the brainstem to the cortex (bottom-up). Declarations Acknowledgements We would like to express our sincere gratitude to the AMAPE Association (Association and Movement of Support for People with Epilepsy in Pernambuco) for the support provided during the execution of this study. We are especially grateful for their assistance in disseminating the research and for the essential resources and information that enriched our investigation. Author contributions statement M. M. L. drafted the manuscript, collected the clinical data, performed the EEG records and interventions, performed the data analysis and discussions. I. T. M. O contributed to data analysis, J. G. V. M. and B. L. A. S. C. contributed to discussions, Cairrão M created the non-periodic acoustic stimulus, designed the study, oriented, discussed the data and edited the manuscript. All authors reviewed the manuscript. Funding sources Authors had financial support from the brazilian agency Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq (grants 473554/ 2011-9 and 480053/2013-8) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES. Lucena M.M had a PhD scholarship from CAPES from the Neuropsychiatry and Behavioral Science Graduate Program from the Federal University of Pernambuco. NGC holds a CNPq-Brazil Research Fellowship. Publishing policy I have read and understood the publishing policy of the journal, and submit this manuscript in accordance with this policy. Competing interests policy I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper. Dual publication The results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration (from you or one of your Contributing Authors) by another publisher. Data availability No/Not applicable (this manuscript does not report data generation or analysis). References Fiest, KM et al. 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Juvenile myoclonic epilepsy shows increased posterior theta, and reduced sensorimotor beta resting connectivity. Epilepsy Res. 163 , 106324 (2020). Brancucci, A et al. Involvement of ordinary auditory cortical what and where areas during illusory perception. Brain Struct Funct. 223 , 965–979 (2018). Table Table 2 is not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7049350","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":546378973,"identity":"a6b4e90c-9b68-4137-9a35-9ecd2e196844","order_by":0,"name":"Marília M. 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A.","lastName":"Rodrigues","suffix":""}],"badges":[],"createdAt":"2025-07-04 20:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7049350/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7049350/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96454149,"identity":"44111526-3963-460d-a33e-4961f5d87b68","added_by":"auto","created_at":"2025-11-21 10:02:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1824239,"visible":true,"origin":"","legend":"","description":"","filename":"ARTIGOLORETATERCEIRASUBMISSOv4.docx","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/8cd6eb3a66d5fcb3ad6c23ee.docx"},{"id":96453746,"identity":"e6dd6eac-0e71-42db-bd13-5558070f462e","added_by":"auto","created_at":"2025-11-21 10:01:29","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7053,"visible":true,"origin":"","legend":"","description":"","filename":"fc73d34b4db646259c36b3b26416170a.json","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/8fffcc944765cdd8119a71b7.json"},{"id":96399495,"identity":"1d5048e8-4e6b-4ded-816f-ea33e21ded04","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73826,"visible":true,"origin":"","legend":"","description":"","filename":"fc73d34b4db646259c36b3b26416170a1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/a4bfd388ec44f0c0bff60fa0.xml"},{"id":96399492,"identity":"46000755-b27a-4236-a09f-23c7b821474e","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96175,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/69cb0e9b5b1aa7785ed79e44.jpeg"},{"id":96453695,"identity":"bb4fa4a2-9e25-4936-ac07-6edf87995ff0","added_by":"auto","created_at":"2025-11-21 10:01:20","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":432784,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/c669859f767b2b8fac18b9bb.png"},{"id":96399494,"identity":"97d7c3f1-3b27-4937-a085-539d2f427af4","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89026,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/ba473db04510a86b4aef2ccd.png"},{"id":96399498,"identity":"f53a9097-3628-43fe-9054-27b27fa47914","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71783,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/bc82b6331f10649109cf276c.png"},{"id":96399496,"identity":"8ac6851f-21f2-48af-9212-872677b34d67","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":69814,"visible":true,"origin":"","legend":"","description":"","filename":"fc73d34b4db646259c36b3b26416170a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/936b0bbf6f005755c4bba069.xml"},{"id":96399499,"identity":"feba903d-8772-4ee5-a090-1a4820909ff0","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80174,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/1c331296d13b9e709cd70c62.html"},{"id":96399488,"identity":"8c5f0c0b-4421-4d74-9ec3-d86691125494","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":202697,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental procedure\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/3bb461eadfb05fe6dc460d80.png"},{"id":96399493,"identity":"a07f18c7-a4d0-43ac-ad24-47e5894d590f","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":247940,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional representation of intracortical density in areas exhibiting greater activity in the Experimental Group (EG) during ANPS stimulation. The areas with higher activation surpassed the two-tailed threshold of t(max) = 3.776 (p \u0026lt; 0.05), showing statistically significant differences during ANPS use between EG - CG. Warm colors represent the activated areas in the Experimental Group, while cool colors represent the activated areas in the Control Group. A. Areas showing greater activation in the theta frequency band (θ); B. Areas showing greater activation in the beta 1 frequency band (β1).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/cc6cd744e34672f0797c33af.png"},{"id":96399490,"identity":"d2adb18c-18b0-496a-b64d-402622ceb465","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eA three-dimensional representation of the areas that exhibited statistically significant differences in cortical intracortical current density in the theta and beta 1 frequency bands of the EEG during ANPS use, depicted in warm colors.\u003c/p\u003e","description":"","filename":"placeholderimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/049bf447c6f7bba56c4d7a4a.png"},{"id":96399489,"identity":"09d6aa1f-44fd-49b8-86b3-3efc19cb56bd","added_by":"auto","created_at":"2025-11-20 16:00:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eA reduction in seizures was observed.\u003c/p\u003e","description":"","filename":"placeholderimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/6b49bd821917556dd6821bc1.png"},{"id":96726148,"identity":"1693c71b-d4ef-493f-8f49-020512c53644","added_by":"auto","created_at":"2025-11-25 12:24:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1138160,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7049350/v1/5ea3dfdc-5f6d-4e01-899c-cae592e77907.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA New Neuromodulation Tool: TheAcoustic Non-Periodic Stimulation\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEpilepsy is a chronic brain disorder with profound effects on life quality. Approximately 50 million people worldwide have epilepsy, making it one of the most common neurological diseases \u003csup\u003e1\u003c/sup\u003e. Epilepsy is characterized by a lasting predisposition to generate spontaneous epileptic seizures and has numerous neurobiological, cognitive, and psychosocial consequences \u003csup\u003e2\u003c/sup\u003e. Seizures occur when there is abnormal synchronous neuronal firing in a brain region or throughout the brain, often due to irregular network formation or disruption caused by structural, infectious, or metabolic disorders \u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIt is believed that the origin of seizures is deeply linked to a hyperexcitability and hypersynchrony characteristic of neural tissue activity \u003csup\u003e3,4\u003c/sup\u003e. Neuronal hypersynchronization occurs when excitatory mechanisms prevail, resulting from increased excitation or decreased inhibition. As abnormal hypersynchronized neuronal activity continues, more and more neurons are activated (high-frequency depolarization/repolarization), leading to an epileptiform crisis \u003csup\u003e5\u003c/sup\u003e. For clarity, synchrony can be defined as the relationship between the dynamics of two coupled oscillatory systems \u003csup\u003e6\u003c/sup\u003e. Thus, if the oscillatory activity of one neural circuit drives the dynamics of another, they are said to be synchronized, and some form of synchronization can be objectively observed in their temporal characteristics \u003csup\u003e7\u003c/sup\u003e. In epilepsy, hypersynchronization contributes to the aberrant coupling of dysfunctional hyperactive microoscillators, giving rise to seizures \u003csup\u003e8,9\u003c/sup\u003e, while desynchronization induces functional isolation that purportedly impairs epileptic phenomena \u003csup\u003e7,10\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMounting evidence suggests that hypersynchrony is also a key factor in understanding the disease and enabling robust, safe, and effective treatment \u003csup\u003e7,9,10\u003c/sup\u003e. As many epileptic patients are refractory, that is, experiencing seizures despite taking medications, there is a strong demand for new concepts and methods to block the phenomenon beyond the molecular level with pharmacological agonists or antagonists to specific receptors \u003csup\u003e11\u003c/sup\u003e. One alternative is to intervene at the circuit and network levels \u003csup\u003e12_14\u003c/sup\u003e. These approaches would recruit not only glutamatergic or GABAergic neurons, but also networks involving other neurotransmitters and cell types (e.g., glia) \u003csup\u003e15\u003c/sup\u003e, orchestrating brain connectivity to a different functional state apart from the strong attractors of epilepsy\u003csup\u003e16\u003c/sup\u003e. \u0026nbsp; These concepts are based on the complexity of neural networks, interchangeability between temporally connected hubs, information distribution, and local recruitments \u003csup\u003e16_18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe desynchronization of epileptogenic neural networks has been demonstrated in various investigations as a mechanism responsible for the effectiveness of neurostimulation \u003csup\u003e10\u003c/sup\u003e. Studies that employed non-periodic electrical stimulation, i.e., low-frequency stimuli with randomized pulse intervals, have shown anticonvulsant properties in animal models subjected to controlled infusion of the convulsive drug pentetrazol (PTZ) \u003csup\u003e4,7\u003c/sup\u003e. Another independent research group demonstrated that a similar approach also impairs epileptogenesis in a kindling animal model \u003csup\u003e19\u003c/sup\u003e. Based on this premise, the non-periodic acoustic stimulation (ANPS) was developed in our laboratory. This stimulus is based on the principle of NPS but is non-invasive, employing asynchronous low-frequency auditory pulses randomized according to a power law. ANPS is a stereo soundtrack with a baseband of 400 Hz that is interrupted by very short, slightly faster events called \u0026quot;pulses.\u0026quot; Recent studies \u003csup\u003e20\u003c/sup\u003e in patients with refractory epilepsy showed a significant effect on reducing overall connectivity in the brain network during the acute phase, i.e., shortly after ANPS usage. Furthermore, it was observed that there was a change in the arrangement of connections, as evidenced by variations in hubs \u003csup\u003e20\u003c/sup\u003e. The logic behind ANPS is to shift brain oscillatory activity from low to high, starting with the brainstem nuclei responsible for auditory processing, which would also modulate the cortex at both molecular and circuital levels.\u003c/p\u003e\n\u003cp\u003eBased on this, the present study aimed to evaluate the electrophysiological effects of ANPS in individuals with and without epilepsy and to investigate whether this stimulus would cause the same effect as a control stimulus (white noise).\u003c/p\u003e\n\u003cp\u003eThe main question of the present work is concerned with the genuine effects of ANPS in the brain compared to a normal sound like white noise in adult patients with epilepsy (PWE) and healthy controls (HC). Additionally, as ANPS was developed to control seizures, we also conducted a pilot study to check if it could somehow interfere with seizure frequency in microcephalic children.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eAcoustic Non-Periodic Stimulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eANPS has been developed (patent pending process BR 10 2019 009701 9). The ANPS was constructed as follows: first, a 60000 points x axis was created in the Octave software. This corresponds to 60 epochs of 1000 points each, that is, 60 s of 1 second epoch (divided in 1000 ms). Based on this x axis, a 400 Hz sinusoid was constructed. Four aleatory points (called \u0026ldquo;pulse locations\u0026rdquo;) were chosen every second (that is, every 1000 points of the x axis). This implies that ANPS is a 4Hz stimulation (four pulses every second). In each pulse location, 5 points (corresponding to 5 ms) of the signal were substituted for the same number of points of another sinusoid, a 420 Hz with a 20% increase in amplitude compared to the initial 400 Hz one. The soundtrack was later exported to the Audacity 2.0 software (open source, multiplatform audio editor) and recorded in WAV format to be reproduced on acoustic stimulus reproduction devices (cell phones, computers) without interruption. The acoustic stimulus has the same baseband in both ears, but the pulse locations are different in the acoustic stimulus emitted for the right and left ear. This strategy was also based on the NPS, as it has maximum effectiveness when applied bilaterally and asynchronously \u003csup\u003e21\u003c/sup\u003e. Headphones are needed because it is a stereo sound.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdult Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe procedures were approved by the Ethics Committee of the Federal University of Pernambuco, Brazil (protocol 4.983.183) and written consent was obtained from all participants. The research included 40 individuals, divided into two groups: patients with epilepsy (Experimental Group, EG, n=20; 14 females, 32.5 \u0026plusmn; 14.8 years) and 20 individuals without epilepsy (Control Group, CG, n=20, 12 females, 36.1 \u0026plusmn; 15.2 years) recruited through publications on social media and dissemination in epilepsy patient groups. Among the patients with epilepsy, 45% had focal epilepsy and 40% had generalized epilepsy. Additionally, 70% of them were on multiple medications, and 70% reported experiencing up to 1 seizure per year, with 50% of these patients experiencing monthly seizures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEEG data recording and procedures in Adult Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh-density EEG recording was performed using a 32-channel electrode cap (Nautilus, G.TEC, Austria). The sampling rate was 500 Hz, with a band-pass filter set to 0.5 to 50 Hz, and the reference electrode used was Cz. The impedance between each electrode was kept below 5 k\u0026Omega;.\u003c/p\u003e\n\u003cp\u003eA baseline EEG was recorded and remained for 2 minutes. Then, the hearing threshold was measured. White noise or ANPS was played by the computer and the volume was initially set to zero, increased afterward in 1% steps until the participant warned that started to hear. All stimulations had an intensity of 30 dB above the hearing threshold. The computer output sound was calibrated. This aims to ensure that the stimulus is audible but comfortable \u003csup\u003e22\u003c/sup\u003e. Subsequently, the volunteer received acoustic stimulation. The duration of each acoustic stimulation was 10 min, with a 2 min interval of silence between them. Half of the subjects received ANPS stimuli and, 2 min later, white noise. The white noise is Gaussian and was created in the free software Audacity. In the others, this was reversed (see Fig 1.), to exclude any synergism effects. The instructions that participants (patients and health volunteers) received was that our laboratory was testing new acoustic stimulation with possible effects on epilepsy, but at that time it was not known if they actually had anticonvulsant effects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt was also said that the main objective of the research was to evaluate two acoustic stimulation effects on the brain. It was not told to participants that one of those acoustic stimulations was the control (white noise) and the other was supposed to be the verum acoustic stimulation (ANPS). This procedure was used to avoid any kind of expectation. Participants were instructed simply to listen to the presented acoustic stimulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003esLORETA Analysis of EEG recordings from adult participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe EEG signals were preprocessed using Matlab\u0026reg; software, version 2018, and EEGLAB. The EEG signals were re-referenced to the average of the electrodes, which approximates the ideal reference at infinity. The data were band-pass filtered between 0.5 and 50 Hz, with an amplitude threshold set between 100 \u0026micro;V and -100 \u0026micro;V during automatic filtering, followed by manual filtering when necessary. After these procedures, the tasks were separated, and for each patient, it was used two epochs containing 60 seconds: Acoustic Non-Periodic Stimulation (NP) and white noise (WN).\u003c/p\u003e\n\u003cp\u003eThe preprocessed data were then analyzed using the sLORETA software \u003csup\u003e23,24\u003c/sup\u003e. For each subject in the study, the mean of the cross-spectral matrices was computed for the classical frequency bands (\u0026delta; delta [1.5...6], \u0026theta; theta [6.5...8], \u0026alpha; alpha [8.5...12], \u0026beta;1 beta 1 [12.5...18], \u0026beta;2 beta 2 [18.5...21], \u0026beta;3 beta 3 [21.5...30]), considering the total number of electrodes = 31, and a sampling rate of 500Hz.\u003c/p\u003e\n\u003cp\u003eUsing the statistical package of sLORETA, EEG records were calculated through the log of the ratio of averages, followed by 5000 data randomizations. To correct for multiple comparisons, the non-parametric single-threshold test based on the theory of randomization and permutation tests developed by Nichols and Holmes for functional mapping experiments \u003csup\u003e25\u003c/sup\u003e was used. The procedure for correcting for multiple hypotheses testing is known as the t-max test. The t-max statistic with a logarithmic calculation of the ratio between averages is the non-parametric analysis established in LORETA, which provides, after the randomization procedure, a random distribution of the maximum statistic in each voxel, resulting in a threshold for p-values of 0.01, 0.05, and 0.10. These thresholds for each p-value correspond to the values that fall between 1%, 5%, and 10%, respectively, of the highest values obtained in the randomization. The t-max test has demonstrated excellent control over type I errors. Results are considered significant at an alpha of 0.05. A two-tailed statistical test was considered significant for the voxel that exceeded the t-max significance threshold. For each significantly different voxel between PWE and controls, the corresponding Brodmann area (BA) was identified in the Talairach Brain Atlas \u003csup\u003e23\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eAdult participants. Comparison of intracortical current density in patients with epilepsy and epilepsy-free controls during ANPS stimulation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the results for the non-parametric variance test employed by sLORETA during the use of ANPS in the experimental group (EG) and the control group (CG) are presented. For the voxel-to-voxel analysis of current source density, a two-tailed threshold of t(max)\u0026thinsp;=\u0026thinsp;3.776 for p\u0026thinsp;=\u0026thinsp;0.05 was determined based on the calculated values. Areas showing activation values exceeding the t(max) threshold, i.e., greater than 3.776, exhibit statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLocation of cortical areas with statistically significant higher activation during the use of ANPS in subjects with epilepsy compared to controls\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrodmann Area\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eValue of max est.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCoordinates location (X, Y, Z)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrecentral gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55, 10, 15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInferior frontal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60, 15, 15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInferior frontal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60, 10, 20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInsula (sublobar region)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40, 10, 10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInferior frontal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55, 20, 25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle frontal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55, 25, 25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrecentral gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55, 0, 15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInferior frontal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50, 30, 20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostcentral gyrus, parietal lobe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65, -5, 15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInferior parietal lobe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeta 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-55, -35, 45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostcentral gyrus, parietal lobe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeta 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.923\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-50, -35, 50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostcentral gyrus, parietal lobe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeta 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.855\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-45, -30, 50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuperior temporal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeta 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65, -40, 20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuperior temporal gyrus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeta 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65, -35, 20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eFrequencies related to t(max)\u0026thinsp;=\u0026thinsp;3.776 for α\u0026thinsp;=\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the theta frequency band, statistically significant activations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; t(max) test) were observed in the inferior and middle frontal regions, as well as in the parietal region (postcentral gyrus) and insular cortex in the EG (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the beta 1 frequency band (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; t(max) test), greater activation was found in the parietal region (postcentral gyrus) and temporal region (superior temporal gyrus) in the EG (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). An analysis of cortical activation caused by WN in the EG compared to the CG was also conducted, but no statistically significant areas or frequency bands were found in this comparison.\u003c/p\u003e\u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, a three-dimensional representation of the areas that showed differences in cortical intracortical current density in the theta (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) frequency band, and beta 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) frequency band during ANPS stimulation, as calculated by sLORETA. Hot pseudocolors (red and yellow) are depicted in those areas with statistically significant results (EG\u0026thinsp;\u0026gt;\u0026thinsp;CG). Cold pseudocolors (black to blue) represent areas where CG supposedly had higher values compared to EG, but none had statistical significance. Positive values indicate areas with greater activation in the EG compared to the CG, represented in warm colors. No areas were more activated by ANPS in the CG compared to the EG (depicted in blue). There were no statistically significant differences in other frequency bands during ANPS use between the groups.\u003c/p\u003e\u003cp\u003eDuring the comparison between the EG and CG during white noise stimulation, no significant differences were observed in any EEG frequency band between the groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparison of intracortical current density in adult patients with epilepsy during ANPS and white noise stimulation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this analysis, we aimed to identify statistically significant differences in cortical density during ANPS and WN stimulation, calculated for the following condition pairs: EG during ANPS - EG during WN.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;2 presents the results of the ANPS-WN comparison in the EG. When comparing the voxel-to-voxel analysis of current source density in the EEG recording, a two-tailed threshold of t(max)\u0026thinsp;=\u0026thinsp;4.038 for p\u0026thinsp;=\u0026thinsp;0.05 was determined. Statistically significant results were observed in the theta frequency band of the EEG (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; t(max) test), with areas of greater activation in the frontal region (inferior frontal gyrus, middle frontal gyrus, and precentral gyrus) during ANPS use in the EG. Additionally, in the beta 1 frequency band (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; t-max test), significant activation was observed in the parietal region (postcentral gyrus) and frontal region (precentral gyrus) during ANPS in the EG.\u003c/p\u003e\u003cp\u003eFigure 3 shows a three-dimensional representation of the areas that exhibited statistically significant differences in cortical intracortical current density in the theta and beta 1 frequency bands of the EEG during ANPS use, depicted in warm colors. There were no statistically significant differences in other frequency bands in the EG when comparing ANPS to WN.\u003c/p\u003e\u003cp\u003eAs for the CG listening to ANPS and RB (ANPS - RB for CG): no statistically significant results were found when comparing the voxel-to-voxel analysis of current source density in any EEG frequency band.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChildren with microcephaly\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong the children included in this study, the most frequent type of seizures were spasms (55.5%), followed by generalized seizure type (33.3%) and focal seizure type (22.2%). Most children (66.6%) were using more than one type of antiseizure drug (ASD).\u003c/p\u003e\u003cp\u003eA reduction in seizures in 88.8% of the children was observed. Only one child showed no change in seizure frequency during the two months of intervention. As a whole, there was a statistically significant reduction comparing two months before (147.0 +- 59.8 seizures, mean and SEM, n\u0026thinsp;=\u0026thinsp;9) and two months after ANPS (47.8 +- 28.7) (p\u0026thinsp;=\u0026thinsp;0.0078, two-tailed, Wilcoxon Signed Rank Test) (Fig.\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eFIGURE 4 AROUND HERE\u003c/p\u003e\u003cp\u003eRegarding the adverse effects of ANPS, only two children described drowsiness, followed by nausea and mood change.\u003c/p\u003e\u003cp\u003e As for the PGIC, it was observed that most of the parents (7/9) declared a good outcome from the stimulation, but two did not observe changes in the clinical aspect of their children.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough several cortical areas were activated by both WN and ANPS in both groups, such as the primary auditory area, only those areas that showed statistically significant activation by ANPS in the Experimental Group (EG) compared to the Control Group (EG - CG) were included in the main analysis. Additionally, areas that were differentially activated by ANPS compared to WN only in the EG (ANPS minus WN for EG) were also included.\u003c/p\u003e\u003cp\u003eThe sLORETA results showed that ANPS induced greater activation in the theta and beta1 frequency bands in patients with epilepsy (EG) but not in individuals without epilepsy (CG). The theta frequency band was predominant in frontal regions (BA 44, 45, 46, 9) extending to the precentral gyrus limit (BA 6). On the other hand, beta1 frequency was observed in more posterior regions, including parietal regions near the postcentral gyrus (BA 40, 43, and 2), and temporal gyrus (BA 22 and 42). In the literature, it has been described that in epilepsy, there may be increased theta and alpha connectivity in posterior regions and decreased connectivity in the beta band in pre and postcentral areas (sensorimotor areas) \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, in the case of ANPS, an acoustic stimulus developed with the purpose of reducing epileptic seizures, the opposite was observed: there was an increase in slow oscillations (theta) in the anterior region and an increase in beta in the posterior sensorimotor regions of the brain. This may suggest a potential antagonism of circuits, where the effects of ANPS appear to be contrary to what is observed in epilepsy.\u003c/p\u003e\u003cp\u003eRegarding the evaluation between ANPS and WN in the EG, we observed that ANPS maintained significant activation in the theta and beta1 frequency bands. In the theta frequency band, there was an increase in current density in the regions of the inferior frontal gyrus, middle frontal gyrus, and precentral gyrus (BA 6, 8, 9). In the beta1 frequency band, there was activation in the postcentral gyrus regions (BA 3, 4) during ANPS stimulation but not during WN stimulation. No differences were observed between the stimuli in the control group.\u003c/p\u003e\u003cp\u003eTaken together, these data, along with the locations of the Broadmann areas involved in the dorsal and ventral sensory propagation pathways (introduction figure), suggest that ANPS appears to activate the dorsal pathway (BA 42, 40, 2, 3, 4, 6, and 8), terminating in the frontal and prefrontal areas (BA 9, 44, 45, and 46). It is known that this dorsal pathway, also known as the \"where\" pathway, transports information about the location of visual and auditory stimuli, in contrast to the ventral pathway, the \"what\" pathway \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. One possible interpretation is that by providing an acoustic stimulation caused by pulses that never occur simultaneously in both ears (due to their shuffled asynchrony nature), we are deliberately altering the physiological system of spatial sound source localization. As this system is responsible for an essential and highly conserved function in animal phyla, to identify potential prey or predators even in the dark, the processing nuclei in the brainstem involved in the auditory pathway (cochlear nuclei, olivary complex, lateral lemniscus nucleus, inferior colliculus) may try to compare the incomparable. Determining a legitimate sound source, which may be closer to one ear than the other, will always result in the same stimulus being captured by both auditory pathways (ipsi and contralateral) but with a characteristic phase lag. It is precisely this phase lag that provides the clue about which ear received the acoustic stimulus first. This fact probably leads to changes in bottom-up synchronization, that is, from the brainstem to the primary auditory cortex. Upon reaching the cortex, one would expect this change to be more expressive in the dorsal pathway than in the ventral. After all, it is not about the identification of beings (what system) but rather about location (where system).\u003c/p\u003e\u003cp\u003eMore studies are needed to understand how ANPS acts in the brains of patients with epilepsy. Further investigations may consider separation by etiological groups or seizure types, as well as a larger sample size, to reduce sample variability.\u003c/p\u003e\u003cp\u003eThe ANPS was created to antagonize epileptic synchronism. The present study had a too small number of participants to confirm such a strong claim. However, the reduction in the number of seizures seen in children with microcephaly suggests this may be the case (Fig.\u0026nbsp;4).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePresent results demonstrate that: The ANPS, in patients with epilepsy, increases theta and beta1 oscillations, and apparently activates the dorsal pathway (\"where system\") (BA 42, 40, 2, 3, 4, 6, and 8), terminating in frontal and prefrontal areas (BA 9, 44, 45, and 46) more than the ventral pathway (\"what system\"). This interference likely affects the functioning of sound source localization from the brainstem to the cortex (bottom-up).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to the AMAPE Association (Association and Movement of Support for People with Epilepsy in Pernambuco) for the support provided during the execution of this study. We are especially grateful for their assistance in disseminating the research and for the essential resources and information that enriched our investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM. M. L. drafted the manuscript, collected the clinical data, performed the EEG records and interventions, performed the data analysis and discussions. I. T. M. O contributed to data analysis, J. G. V. M. and B. L. A. S. C. contributed to discussions, Cairr\u0026atilde;o M created the non-periodic acoustic stimulus, designed the study, oriented, discussed the data and edited the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors had financial support from the brazilian agency Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico - CNPq (grants 473554/ 2011-9 and 480053/2013-8) and Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - CAPES. Lucena M.M had a PhD scholarship from CAPES from the Neuropsychiatry and Behavioral Science Graduate Program from the Federal University of Pernambuco. NGC holds a CNPq-Brazil Research Fellowship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublishing policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI have read and understood the publishing policy of the journal, and submit this manuscript in accordance with this policy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration (from you or one of your Contributing Authors) by another publisher.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eNo/Not applicable (this manuscript does not report data generation or analysis).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFiest, KM et al. Prevalence and incidence of epilepsy: a systematic review and meta-analysis of international studies, \u003cem\u003eNeurol.\u003c/em\u003e \u003cstrong\u003e88\u003c/strong\u003e, 296-303 (2017). \u003c/li\u003e\n\u003cli\u003eFisher, RS et al. Official ILAE report: a practical clinical definition of epilepsy. Epilepsia \u003cstrong\u003e55\u003c/strong\u003e, 475-482 (2014).\u003c/li\u003e\n\u003cli\u003ePenfield, W \u0026amp; Jasper, H. Epilepsy and the functional anatomy of the human brain, Southern Med, J. \u003cstrong\u003e47\u003c/strong\u003e, 704 (1954).\u003c/li\u003e\n\u003cli\u003eCota, VR et al. Distinct patterns of electrical stimulation of the basolateral amygdala influence pentylenetetrazole seizure outcome. Epilepsy Behav. \u003cstrong\u003e14\u003c/strong\u003e, 26\u0026ndash;31 (2009).\u003c/li\u003e\n\u003cli\u003eBerendt, M et al. Prevalence and characteristics of epilepsy in the Belgian shepherd variants Groenendael and Tervueren born in Denmark 1995-2004. 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Brain Connectivity. \u003cstrong\u003e11\u003c/strong\u003e, 457-470 (2021).\u003c/li\u003e\n\u003cli\u003ePegg, EJ et al. Interictal electroencephalographic functional network topology in drug‐resistant and well‐controlled idiopathic generalized epilepsy. Epilepsia \u003cstrong\u003e62\u003c/strong\u003e, 492-503 (2021).\u003c/li\u003e\n\u003cli\u003eMartorell, AJ et al. Multi-sensory gamma stimulation ameliorates alzheimer\u0026rsquo;s-Associated pathology and improves cognition. Cell. \u003cstrong\u003e177\u003c/strong\u003e, 256\u0026ndash;271 (2019).\u003c/li\u003e\n\u003cli\u003eTejada, J et al. The epilepsies: complex challenges needing complex solutions. Epilepsy \u0026amp; Beh. \u003cstrong\u003e26\u003c/strong\u003e, 212-228 (2013).\u003c/li\u003e\n\u003cli\u003eGarcia-cairasco, N. Learning about brain physiology and complexity from the study of the epilepsies. 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Brain Mapp. \u003cstrong\u003e15\u003c/strong\u003e, 1-25 (2002).\u003c/li\u003e\n\u003cli\u003eRoutley, B et al. Juvenile myoclonic epilepsy shows increased posterior theta, and reduced sensorimotor beta resting connectivity. Epilepsy Res. \u003cstrong\u003e163\u003c/strong\u003e, 106324 (2020).\u003c/li\u003e\n\u003cli\u003eBrancucci, A et al. Involvement of ordinary auditory cortical what and where areas during illusory perception. Brain Struct Funct. \u003cstrong\u003e223\u003c/strong\u003e, 965\u0026ndash;979 (2018). \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 2 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acoustic Stimulation, EEG, Non-Periodic Stimulation, Epilepsy","lastPublishedDoi":"10.21203/rs.3.rs-7049350/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7049350/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eEpilepsy represents a significant contemporary challenge. Approximately one-third of epileptic patients are considered refractory, meaning they resist conventional pharmacological treatment. In response to the need for alternative methods to control epilepsy, our research group developed Non-Periodic Acoustic Stimulation (ANPS).\u003c/span\u003e The present \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003estudy aimed to assess the electrophysiological characteristics of ANPS in individuals with and without epilepsy, as well as to determine if this stimulus would induce the same effect as a control stimulus of white noise (WN). Evaluations were conducted using EEG before, during, and after\u003c/span\u003e applying \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eANPS and WN in the respective groups. The analysis was based on intracortical electrical density (sLORETA). ANPS, but not WN, showed statistically significant differences in activation within the theta and beta 1 frequency bands in the epilepsy group (EG), but not in the control group (CG). The areas of greater activation were observed in the frontal and parietal regions. These findings suggest that ANPS exhibited distinct electrophysiological characteristics compared to WN and that patients with epilepsy responded differently to ANPS compared to individuals without epilepsy. ANPS in patients with epilepsy promoted increased activity in regions involved in the dorsal pathway, likely interfering with sound source localization function.\u003c/span\u003e To our notice, it is the first time that a sound reduced epileptic seizures in refractory patients. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eANPS s\u003c/span\u003eeems to be a new neuromodulation tool, with brain effects differing from normal acoustic stimulation.\u003c/p\u003e","manuscriptTitle":"A New Neuromodulation Tool: TheAcoustic Non-Periodic Stimulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 16:00:12","doi":"10.21203/rs.3.rs-7049350/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a63c41c-c316-4085-b363-37e556f35a87","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-25T12:23:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 16:00:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7049350","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7049350","identity":"rs-7049350","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}