Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex

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However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological interactions remain largely unexplored. Therefore, in this study, we recruited six patients who underwent awake craniotomy with opened lateral ventricles. The electrodes were placed on the thalamic surface over the ventricular wall and brain surface around the central sulcus. Electrical stimulation was applied to each electrode to record the evoked responses. Furthermore, we performed time-frequency and statistical analyses to investigate the cortical responses induced by electrical stimulation. High gamma activity was elicited in the cerebral cortex following thalamic stimulation. However, regarding frequency bands, the cortical spectral response induced by thalamic stimulation (TCSR) showed power increases in more restricted bands at approximately 100 Hz compared with the cortical spectral response induced by cortical stimulation (CCSR). In contrast, more electrodes in CCSRs showed a power decrease after the power increase than those in TCSRs. Finally, compared with the cortex, thalamic projections evoked localized neural activity in the cortex. Adjusting stimulus intensity and comparison with deep thalamic electrode stimulation will further clarify thalamocortical linkages. Biological sciences/Neuroscience Biological sciences/Neuroscience/Neural circuit thalamocortical connectivity neural networks cortico-cortical evoked potential thalamic projections time-frequency analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The thalamus is a hub for neural networks in the human brain 1 . Furthermore, except for olfaction, it relays almost all information input to the cortex, including sensory, motor, auditory, and visual inputs 2 , and is crucial for signal transmission. The connectivity between the thalamus and cortex has been studied for a long time. In 1942, Morison and Dempsey reported the existence of two projection systems between the thalamus and cortex in animal experiments in cats 3 . In addition, many previous studies have assessed thalamocortical connectivity using magnetic resonance imaging (MRI)-based diffusion tensor imaging 4 , 5 or functional MRI 6 . Notably, several studies have evaluated its transformation in patients with psychiatric disorders, including schizophrenia 7 , insomnia 8 , and mood disorders 9 . In addition, optogenetic techniques in rats have confirmed that thalamus stimulation activates a large area of the forebrain, bringing the sleeping rat brain to a waking state 10 . This projection system sends fibers to extensive cerebrum areas and helps regulate consciousness and arousal. Notably, most non-specific nuclei of the non-specific projection system are located in the median thalamus or group of nuclei within the medullary plate. However, specific nuclei have bidirectional fiber connections with particular areas of the cortex. These specific nuclei are mainly located in the lateral part of the thalamus 11 . Thalamocortical and corticocortical fibers reach the cortex entangled, complicating their differentiation macroscopically. The rich connectivity between the cortex and thalamus is also a central component for electroencephalogram (EEG) generation. EEG rhythms < 20 Hz are thought to be generated by the thalamocortical connection, transforming local excitability under the control of subcortical nuclei 12 . The corticothalamic neurons provide feedback to the thalamocortical nuclei and synapse with the thalamic reticular nuclei and thalamocortical neurons to form oscillatory thalamocortical loops. These loop structures reportedly generate delta rhythms and spindle waves 13 . Therefore, visualizing the difference between corticocortical and thalamocortical connectivity aids in revealing the mechanism that generates cortical EEG rhythms. Beyond its role in physiological neural networks, the thalamus is implicated in epileptic abnormal activity. The thalamus contributes to the generation of spindle wave rhythms during sleep 14 , 15 , and may facilitate generalized epileptic discharges in idiopathic generalized epilepsy via a similar thalamo-cortical loop 16 . Evidence from a zero-magnesium in vitro model of epilepsy indicates synchronous firing between thalamic and cortical neurons 17 . Additionally, the thalamus is recruited nonlinearly into synchronous cortical discharges, with coupling reliability increasing over time 17 . Electrical stimulation of the thalamus modulates cortical activity: low-frequency stimulation of the prethalamic nucleus induces rhythmic EEG synchronization 18 , 19 , whereas high-frequency stimulation leads to desynchronization of the EEG 20 . High-frequency stimulation of the prethalamic nucleus thalamic nucleus in experimental animals reduces seizure activity in epileptic seizure models 21 , 22 . Clinical trials have been conducted in humans with drug-resistant epilepsy 23 , 24 , and the use of deep brain stimulation of the anterior thalamic nucleus is gaining traction in clinical practice as a neuromodulation therapy. Corticocortical-evoked potential (CCEP) is a method that allows for investigating electrophysiological connectivity. This technique was established by Matsumoto et al. in 2004 to search for functional connectivity in the brain 25 and is currently in clinical use worldwide 26 , 27 . This method analyzes the corticocortical connectivity by administering electrical stimulation to a specific cortical region and recording subsequent neuronal responses in other regions. Furthermore, electrical stimulation has been demonstrated to elicit a cortico-cortical spectral response (CCSR) 28 . Stimulation initiates action potentials in the cortex, modulating the power in the high-frequency band 29 , 30 . Physiologically, gamma oscillations, particularly those > 60 Hz (60–200 Hz), are closely linked to brain functions, such as motor, language, attention, auditory, and visual functions 31 – 34 . Neuronal activity < 60–80 Hz is derived not only from the synchronization of excitatory neurons, but also from inhibitory interneurons 35 , whereas neuronal activity between 80–200 Hz reflects increased multiunit activity or local potentials 36 . Therefore, we hypothesized that analyzing the causal functional connectivity between the thalamus and cortex could be possible by stimulating the thalamus and recording responses in the cortex using a methodology similar to CCSR. We termed this method the “thalamocortical spectral response (TCSR)”. In practice, opportunities to directly record action potentials in the thalamus and cortex are extremely limited, particularly given the difficulty in simultaneously recording the cortical and subcortical nuclei. Therefore, the physiological mechanisms of cortical-thalamic coupling and its relevance to epileptic activity remain largely unknown. Furthermore, whether stimulating the thalamus could have different or similar effects on other brain parts remains unclear 37 . In this study, we implanted electrodes in patients whose lateral ventricles were opened during neurosurgery for lesion removal. This approach allowed direct recording of responses to bipolar stimulation of the cerebral cortex and thalamus. By analyzing the data, we compared the responses induced by cortical and thalamus stimulation, identifying key differences in their characteristics. Results Fig. 1 shows the recording schema. Electrodes were placed intraoperatively on the surface of the thalamus, via the opened ventricles (1×4 electrode strip), and brain surface (4×4 electrode grid). Bipolar stimulation was performed through each electrode, after which the cortical response was recorded. Time-frequency and rigorous statistical analyses were performed to compare between TCSR and CCSR. The position of electrode placement was confirmed using a navigation system, although there was some variation between patients. Electrodes were placed on the medial surface of the thalamus in all patients; 17 of the 24 electrodes were deployed in the dorsomedial nucleus of the thalamus (Fig. 2). The MNI coordinates (presented in FSL view (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslView)) are listed in Supplementary Table S1A. The average waveform of the thalamic stimulation was not reproducible (Fig. 3b-1), as a CCEP-like waveform was observed in only one electrode in two of the 24 trials. In contrast, the average waveform of the cortical stimulation showed CCEP waveforms at the cortical electrodes surrounding the stimulating electrode. However, no clear CCEP waveforms were observed at the thalamic electrodes (Fig. 3a-1). Significant CCSR and TCSR were observed in all six patients immediately after stimulation (from + 20 ms to + 40 ms), with 11 and 10 trials, respectively (see Supplementary Tables S1B and 1C for the stimulation electrode pairs, S2 and S3 for electrodes showed significant response). TCSR showed increased high gamma activities (HGA, 60–200 Hz) power at approximately the 100 Hz band. However, it seemed that CCSR showed increased power over a wider frequency band (Figs. 3 and 4). The electrode positions at which the HGA power modulation was observed varied greatly from patient to patient. The statistical analysis results for the power modulation observed in the time-frequency analysis showed that the response observed in TCSR had a more limited frequency bandwidth than that of CCSR (z value = 2.0102, ranksum = 150, p = 0.0444). Furthermore, the distribution of electrodes showing power modulation in the TCSR did not differ significantly between the frontal and parietal lobes (df = 1, χ 2 = 1.0418, p = 0.3074). However, when looking at individual patients, significant responses in the parietal lobe were more common in patient 3, whereas most significant responses in the other patients were found in the frontal lobe. It should be noted that the small population size limits the interpretation of the results, and the results of this statistical analysis are heavily influenced by patient 3.The ratio of electrodes in which the HGA power decrease was observed was 33.8% (52 of the 154 electrodes) and 1.3% (2 of the 160 electrodes) for CCSR and TCSR, respectively, showing a higher value in the CCSR than that in the TCSR (df = 1, χ 2 = 58.2645, p = 2.2915×10 − 14 ). After subtracting the average waveform from each trial (see Supplementary Fig. 1), the number of electrodes showing increased power compared with before subtraction decreased, but a significant increase in HGA power was observed in TCSR and CCSR. No significant differences were found for the frequency band distribution (ranksum = 86, p = 0.1067); however, a similar trend to that observed before subtraction was noted. Discussion To our knowledge, this is the first study to focus on patients who underwent neurosurgery, wherein the ventricle was opened for clinical reasons, allowing grid placement on the surface of the thalamus. Previous studies using deep electrodes, such as stereoelectroencephalography 38 , have examined thalamic stimulation and its interaction with sparsely implanted electrodes in other regions 39 . However, no prior research has directly compared between CCSR and TCSR within the same patient. Here, intraoperative recordings were analyzed to test the hypothesis that thalamic and cortical stimulations could affect the cortex differently; the responses produced by CCSR and TCSR differed in time and space. TCSR analysis demonstrated the electrophysiological connectivity between the thalamus and cortex during electrical stimulation of the surface of the thalamus. In our results, CCEP-like waveforms were not identifiable with thalamic stimulation. As TCEP is derived from an additive average, oscillations may have been cancelled out. However, we hypothesized that TCSR could detect even a small number of trials with high sensitivity. Compared with TCSR, CCSR exhibited power modulation over a wide frequency range (0–500 Hz) during latencies corresponding to N1, which exhibited power modulation over a relatively restricted frequency band centered at 100 Hz. After subtracting the average waveform, the distribution of frequency bands no longer showed a significant difference. However, the frequency band of TCSR tends to be more limited. In the spectrum analysis without subtraction, the HG component synchronized with electrical stimulation may have been included. As previously demonstrated 40 , 41 , CCSR exhibited a power increase followed by a power decrease in the HGA, a pattern rarely observed in TCSR. This phenomenon, which states that “a stronger degree of power increase is more likely to induce a power decrease immediately afterward,” was observed in our previous study 42 , 43 . Therefore, it is likely that the smaller degree of power increase in TCSR compared with that in CCSR did not induce a rebound power decrease. Within the first 60 ms after stimulation, TCSR shows a continuous increase up to 60 ms, whereas CCSR exhibit a strong decrease. Although this remains a hypothesis, it is possible that CCSR originally follows a similar increasing trend as TCSR, but this effect is cancelled by the decrease. In contrast, previous reports highlight delayed high-frequency inhibition following single-pulse electrical stimulation 44 . Therefore, HGA power may fluctuate in diverse patterns, reflecting increases and decreases. Each nucleus in the thalamus is thought to play a role in multisensory integration. Furthermore, projection fibers are thought to have selective connections to each cortical area 45 , 46 . For example, the primary motor cortex and supplementary motor area are thought to receive thalamocortical projections from the ventral anterior and ventral lateral nuclei of the motor thalamic nuclei 47 . However, the primary sensory cortex receives thalamocortical projections from the ventral posterolateral, ventral posteromedial, and ventral posteroinferior nuclei of the sensory thalamic nuclei 48 , 49 . In this study, extensive stimulation was applied to the medial surface of the anterior thalamus (dorsomedial nucleus), which is believed to project fibers to the prefrontal cortex and contribute to higher cognitive functions, along with other regions 50 . However, this study was conducted as part of clinical neurophysiological monitoring, with electrodes placed in the central sulcus, the standard site for MEP/SEP recordings. Additionally, in most patients, the prefrontal cortex was resected, resulting in the absence of recordings from this region. If recordings had been possible from the prefrontal cortex, where the dorsomedial nucleus projects, the results may have been more reproducible. Consequently, these findings may not be fully generalizable to thalamo-cortical interactions because the electrodes were implanted in sensorimotor areas that have no structural connection to the dorsomedial nucleus. However, in this study, it was stimulated broadly rather than selectively. This may have resulted in its transmission by non-specific fibers rather than specific fibers bound to specific subnuclei and may have led to variations in the sites of power modulation around the central sulcus. Alternatively, the stimulus to the medial surface of the thalamus may have been attenuated and relayed through surrounding thalamic nuclei, which then transmitted it to the cortex via their projections, resulting in only a small response being picked up. The recordings were conducted with open lateral ventricles filled as much as possible with artificial cerebrospinal fluid. However, artificial cerebrospinal fluid leaked continuously during recording, and the possibility that the conditions differed from those of stimulation under physiological conditions cannot be ruled out. Continuous electrode impedance monitoring was not possible; however, the thalamic electrodes were secured with cotton and positioned against the ventricular wall for recording, and it was confirmed that they successfully captured EEG signals. The data were recorded intraoperatively during surgical procedures and contained environmental noise and artifacts resulting from surgical manipulation. However, the common average reference method and visual artifact elimination were deemed sufficient to permit a successful analysis of the HGA. We hypothesized that HGA most could likely occur in the cortex when stimuli arrive from the thalamus, in contrast to CCSR, which evokes several spectral responses. Physiologically, HGA (60–200 Hz) is suggested to be closely associated with various brain functions, including movement, language, attention, hearing, and vision 31 – 34 . The narrow gamma band of 60–80 Hz is believed to arise not only from the synchronization of excitatory neurons but also from inhibitory interneurons 35 . Broadband power, including the HGA of 80–200Hz, is thought to correlate closely with local potential firing rate 36 , 51 . In contrast, the exact generator of lower-frequency activity (< 50 Hz) is unknown. Our findings suggest that corticocortical connectivity influences multiple generators, contributing to lower-band oscillations. However, thalamic connectivity transmits information more precisely and minimally, spatially and as a cell type. Deep brain stimulation of the anterior thalamic nucleus is currently approved as a neuromodulation treatment of refractory epilepsy and may become more widely available in the future 23 , 24 , 52 . Therefore, further data on the electrical stimulation of the anterior thalamic nucleus and its cortical responses should be obtained to ensure new findings on the thalamocortical network and optimal stimulation methods by comparing them with our data. Methods Patients Between 2021 and 2023, ten consecutive patients were scheduled for surgeries performed at the Department of Neurosurgery, Kyoto University Hospital, which included the following procedures: 1) craniotomy, 2) large opening of the lateral ventricle, 3) intraoperative neuromonitoring such as sensory evoked potentials (SEP) motor-evoked potentials (MEP) and CCEP, and 4) awake surgery. Six of these patients were included in this study, excluding those with inaccurate electrode position information based on the navigation system, those with significant environmental noise contamination, and those under general anesthesia rather than awake at recording time. Table 1 . Patient Profile and analyzed electrodes No. Age, gender Tumor lesion Tumor diagnosis Antiseizure medication Epilepsy # of electrodes placed Frontal Parietal 1 58, M Rt. frontal Gliosarcoma f-PHT － 12 4 2 46, F Lt. frontal Anaplastic oligodendroglioma f-PHT, LEV ＋ 11 5 3 40, M Lt. frontal Glioblastoma f-PHT, LEV － 7 9 4 34, M Lt. frontal Diffuse astrocytoma f-PHT, LEV － 6 10 5 42, M Rt. frontal Anaplastic astrocytoma LEV ＋ 8 8 6 45, M Rt. frontal Glioblastoma fPHT, LEV － 7 9 Abbreviations f-PHT: fos-phenytoin, LEV: levetiracetam The patients (five men and one woman) aged 34–58 years (mean: 44.6 years), and they all had intraparenchymal frontal lobe tumors, three each on the left and right sides. Furthermore, they were treated with anti-seizure medications in the perioperative period, and two patients were diagnosed with brain tumor-related epilepsy (Table 1). This study was approved by the Ethics Committee of the Kyoto University Graduate School of Medicine (C1082) and appropriate informed consent was obtained from all patients preoperatively. In addition, this study was conducted in accordance with the Declaration of Helsinki. Data acquisition After craniotomy, a 4×4 electrode grid (Unique Medical, Tokyo, Japan; recording diameter, 3 mm; inter-electrode spacing, 1 cm; made of platinum) was placed on the brain surface around the central sulcus. Stimulation was delivered through a silver disk electrode (Nihon Kohden, Tokyo, Japan) implanted on the contralateral median nerve preoperatively, and the location of the central sulcus was identified by recording SEPs and confirming phase reversal 53 . Intraoperative photographs and structures of the surrounding veins confirmed that, in all patients, the 4×4 grid spanned the central sulcus and was implanted close to the hand motor cortex (Fig. 5, created using Brainlab Elements software). Table 1 lists the locations of each electrode in the frontal and parietal lobes. After opening the lateral ventricles by removing the lesion, a 1 × 4 electrode strip (Unique Medical, Tokyo, Japan; recording diameter, 3 mm; inter-electrode spacing, 1 cm; platinum) was inserted into the lateral ventricles. The electrodes were placed on the surface of the thalamus over the ventricular wall, facing the foramen of Monro, anterior septal vein, choroid plexus, and thalamostriate vein as landmarks (Fig. 4). The position of the electrodes was confirmed by recording the coordinates using the Brainlab navigation system and three-dimensional image composition, in addition to the position of the vein on the brain surface. The electrodes were located at 1 cm intervals from the pointed coordinate on the anterior-posterior axis on the preoperative MRI while reviewing the video taken intraoperatively. Co-registration was made to the MNI coordinate (Fig. 1). The co-registration procedure has been previously described 25,43,54 . After placement, the electrodes were covered with gauze or threaded cotton to prevent them from floating off the brain surface and thalamus. The ventricles were filled with artificial cerebrospinal fluid as much as possible. The reference electrode was a disk electrode (Nihon Kohden) implanted in the contralateral mastoid process, and a skin pretreatment agent and electrode paste (Nihon Kohden) were used to reduce electrical resistance. The resting state, SEP, TCSR, and CCSR were recorded. TCSR and CCSR were assessed in this study. The detailed methodology of CCEP has been previously described 25 ; thalamic stimulation was performed accordingly. Single-pulse electrical stimulation of alternating polarity was applied using two adjacent subdural electrodes, and the evoked responses were recorded from other electrodes using a constant-current stimulator (MEE-1232; Nihon Kohden). Regarding the stimulating electrodes, we selected electrodes positioned to straddle the central sulcus, as is usually performed for MEPs during cortical stimulation. However, considering the thalamic electrodes, we selected electrodes that we assumed to be in contact with the thalamic surface. Consequently, when neither of the stimulated electrodes was located on the surface of the thalamus in the MNI space, the data were excluded from further analysis. In previous studies, CCEPs consisted of early (N1) and late (N2) negative potentials with latencies of 10–50 ms and 100–200 ms, respectively 25,26 . In the present study, thalamo-cortical evoked potentials were defined as evoked potentials recorded using short-pulse electrical stimulations from electrodes implanted in the thalamus and recorded by electrodes on the cortex. However, TCSR was the main target for analysis. The sampling rates were 5000 Hz or 1000 Hz; the same constant-current stimulator (MEE-1232, Nihon Kohden, Tokyo, Japan) recorded SEP with a stimulation and intensity frequency of 0.3 Hz and10 mA, respectively. Furthermore, the set of 100 trials was repeated twice; Thalamo-cortical evoked potential and CCEP were performed with a stimulation frequency of 0.4 Hz, intensity of 10 mA with alternating polarity, and duration of 0.3 ms. Each set of 30 trials was repeated twice, so the total duration of the stimulation was 18 ms. Notably, all patients underwent neurological function monitoring; all recordings were made while the patients were awake following propofol withdrawal. The absence of after-discharge due to electrical stimulation was constantly monitored. In addition, we confirmed that thalamic and cortical stimulation in the awake state did not induce any clinical symptoms. Time-frequency analysis The analysis was performed using in-house scripts in Matlab software (Matlab version 9.14.0; MathWorks Inc., MA, USA). Data recorded at a sampling rate of 5000 Hz were analyzed by downsampling to 1000 Hz, with the low-frequency filter set at 0.08–1 Hz 55 . Furthermore, to reduce noise due to intraoperative manipulation and environmental noise, data were derived using a common average reference (four electrodes on the thalamus and 16 electrodes on the cerebral cortex separately), and each stimulus timing was marked. The analysis window was set from 500 ms before the stimulus onset to 1000 ms after this onset; a short-time Fourier transform was performed to extract stimulus-induced spectral responses, including high-gamma activities (HGAs: 60–200 Hz). The Fourier transform window was set to 20 ms, and the window center position was shifted by 10 ms. Based on previous studies, stimulus-induced artifacts could persist for 3–4 ms after the stimulus onset 42 . Therefore, this setting allowed the frequency resolution to reach 50 Hz (0, 50, 100, and 150 Hz). However, the time bin after 20 ms could be considered, excluding the influence of stimulus artifacts. The baseline was set at 500 ms and 490 ms before stimulus onset. Raw electrocorticography data were carefully analyzed; the corresponding trial was excluded from the analysis if any obvious noise or artifacts associated with surgical manipulation were found in the analysis window. The polarity of the stimuli varied between odd and even trials; therefore, they were excluded as pairs so that their numbers were equal. Furthermore, to focus on the modulation of HGA corresponding to the N1, electrodes with a statistically significant increase in HGA power of 20–40 ms after stimulation were defined as those with a significant increase in power in the present analysis. Similarly, electrodes with a statistically significant decrease in HGA power up to 200 ms, corresponding to the latency of N2, were defined as electrodes with a significant decrease in power. Spectral analysis may be influenced by time-synchronized evoked potential, as impulse-like activity can cause broadband changes 56 . To address this, we conducted a supplementary analysis after subtracting the average waveform from each trial and compared the results before and after subtraction. Statistical analysis Stimulation-induced significant changes in the time-frequency domain were searched using a cluster-level nonparametric permutation test 57,58 . The F -value in the analysis window was calculated and compared with the baseline; the corresponding P -value threshold was set at 0.05. In the time-frequency domain, the sum of consecutive F -values that satisfied p < 0.025 at the upper side (significant increase) or the inverse sum of consecutive F -values satisfying p < 0.025 at the lower side (significant decrease) was calculated for the cluster-level statistics. In contrast, surrogate trials were prepared by taking the same number of real trials randomly from the same EEG file, with each analysis window (-500 – +1000 ms at sham stimulus) that did not involve stimulus artifacts. Notably, similar to the original trials, the maximum or minimum cluster-level statistics were calculated based on F-values. This procedure was repeated 10,000 times, and the null distribution of the maximum/minimum cluster-level statistics was compared with that of the original cluster-level statistics at each electrode level. A P -value threshold was defined at < 0.05. After collecting the electrodes that showed significant CCSR or TCSR, the null hypothesis that “there was no difference in the width of the frequency bands in which power modulation occurred in TCSR and CCSR” was tested as a group analysis, not considering the subject of origin, focusing on the number of significant clusters in each analysis in the time bin in which the HGA corresponding to N1 was found to increase, namely, the +20 ms – +40 ms bin. A higher number of clusters indicates a wider distribution of the frequency bands in which power modulation occurs. The Wilcoxon rank-sum test was used to calculate the mean number of clusters at electrodes with significant responses in each TCSR and CCSR trial. Additionally, the number of electrodes with significant HGA elevation in the TCSR located in the frontal and parietal lobes was counted. Then, a χ-squared test was applied under the null hypothesis that “the number of electrodes with significant HGA elevations does not differ between the frontal and parietal lobes.” Similarly, the number of electrodes with significant decrease in power in each trial was counted, and a χ-squared test was applied under the null hypothesis that “the number of electrodes with significant decrease in power does not differ between TCSR and CCSR”. Declarations Data availability statement The data will be available upon a reasonable request; contact Usami K [email protected] . Acknowledgments This study was supported by the Japanese Society for the Promotion of Science, KAKENHI (20K16492 and 23K14775 to K. U.). We would like to thank Editage (www.editage.jp). Author contributions Y.N. and K.U. contributed to the conception and design of the study, acquisition and analysis of data, drafting a significant portion of the manuscript or figures. 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Deep brain stimulation of the anterior nucleus of the thalamus for drug-resistant epilepsy. Neurosurg. Rev. 42 , 287-296 (2019). https://doi.org:10.1007/s10143-017-0941-x Miron, G., Strauss, I., Fried, I. & Fahoum, F. Anterior thalamic deep brain stimulation in epilepsy patients refractory to vagus nerve stimulation: A single center observational study. Epilepsy. Behav. Rep 20 , 100563 (2022). https://doi.org:10.1016/j.ebr.2022.100563 Matsumoto, R. et al. Functional connectivity in the human language system: a cortico-cortical evoked potential study. Brain 127 , 2316-2330 (2004). https://doi.org:10.1093/brain/awh246 Yamao, Y. et al. Clinical impact of intraoperative CCEP monitoring in evaluating the dorsal language white matter pathway. Hum. Brain. Mapp. 38 , 1977-1991 (2017). https://doi.org:10.1002/hbm.23498 de Zwart, B. & Ruis, C. An update on tests used for intraoperative monitoring of cognition during awake craniotomy. 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A., Malekmohammadi, M., Woo Choi, J. & Pouratian, N. Movement-related changes in pallidocortical synchrony differentiate action execution and observation in humans. Clin. Neurophysiol. 132 , 1990-2001 (2021). https://doi.org:10.1016/j.clinph.2021.03.037 Tanji, K., Suzuki, K., Delorme, A., Shamoto, H. & Nakasato, N. High-frequency gamma-band activity in the basal temporal cortex during picture-naming and lexical-decision tasks. J. Neurosci. 25 , 3287-3293 (2005). https://doi.org:10.1523/JNEUROSCI.4948-04.2005 Edwards, E., Soltani, M., Deouell, L. Y., Berger, M. S. & Knight, R. T. High gamma activity in response to deviant auditory stimuli recorded directly from human cortex. J. Neurophysiol. 94 , 4269-4280 (2005). https://doi.org:10.1152/jn.00324.2005 Bartos, M., Vida, I. & Jonas, P. Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat. Rev. Neurosci. 8 , 45-56 (2007). https://doi.org:10.1038/nrn2044 Miller, K. J. Broadband spectral change: evidence for a macroscale correlate of population firing rate? J. Neurosci. 30 , 6477-6479 (2010). https://doi.org:10.1523/JNEUROSCI.6401-09.2010 Parvizi, J., Lyu, D., Stieger, J., Lusk, Z. & Buch, V. Causal Cortical and Thalamic Connections in the Human Brain. Res. Sq. (2024). https://doi.org:10.21203/rs.3.rs-4366486/v1 Malekmohammadi, M., Price, C. M., Hudson, A. E., DiCesare, J. A. T. & Pouratian, N. Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans. Brain 142 , 2288-2302 (2019). https://doi.org:10.1093/brain/awz169 Jacobs, F. et al. Thalamocortical coherence and causality in different sleep stages using deep brain stimulation recordings. Sleep Med. 100 , 573-576 (2022). https://doi.org:10.1016/j.sleep.2022.10.010 Claar, L. D. et al. Cortico-thalamo-cortical interactions modulate electrically evoked EEG responses in mice. Elife 12 , RP84630 (2023). https://doi.org:10.7554/eLife.84630 Grenier, F., Timofeev, I. & Steriade, M. Leading role of thalamic over cortical neurons during postinhibitory rebound excitation. Proc. Natl. Acad. Sci. U S A. 95 , 13929-13934 (1998). https://doi.org:10.1073/pnas.95.23.13929 Kobayashi, K. et al. Different Mode of Afferents Determines the Frequency Range of High Frequency Activities in the Human Brain: Direct Electrocorticographic Comparison between Peripheral Nerve and Direct Cortical Stimulation. PLoS One 10 , e0130461 (2015). https://doi.org:10.1371/journal.pone.0130461 Usami, K. et al. Sleep modulates cortical connectivity and excitability in humans: Direct evidence from neural activity induced by single-pulse electrical stimulation. Hum. Brain. Mapp. 36 , 4714-4729 (2015). https://doi.org:10.1002/hbm.22948 Davis, T. S., Rolston, J. D., Bollo, R. J. & House, P. A. Delayed high-frequency suppression after automated single-pulse electrical stimulation identifies the seizure onset zone in patients with refractory epilepsy. Clin. Neurophysiol. 129 , 2466-2474 (2018). https://doi.org:10.1016/j.clinph.2018.06.021 Tyll, S., Budinger, E. & Noesselt, T. Thalamic influences on multisensory integration. Commun. Integr. Biol. 4 , 378-381 (2011). https://doi.org:10.4161/cib.4.4.15222 Macchi, G. & Bentivoglio, M. Is the "nonspecific" thalamus still "nonspecific"? Arch. Ital. Biol. 137 , 201-226 (1999). Villalba, R. M., Behnke, J. A., Pare, J. F. & Smith, Y. Comparative Ultrastructural Analysis of Thalamocortical Innervation of the Primary Motor Cortex and Supplementary Motor Area in Control and MPTP-Treated Parkinsonian Monkeys. Cereb. Cortex. 31 , 3408-3425 (2021). https://doi.org:10.1093/cercor/bhab020 Sankarasubramanian, V. et al. Transcranial Direct Current Stimulation Targeting Primary Motor Versus Dorsolateral Prefrontal Cortices: Proof-of-Concept Study Investigating Functional Connectivity of Thalamocortical Networks Specific to Sensory-Affective Information Processing. Brain Connect. 7 , 182-196 (2017). https://doi.org:10.1089/brain.2016.0440 Jones, E. G. The Thalamus . (Cambridge University Press, 2007). Pergola, G. et al. The Regulatory Role of the Human Mediodorsal Thalamus. Trends Cogn. Sci. 22 , 1011-1025 (2018). https://doi.org:10.1016/j.tics.2018.08.006 Manning, J. R., Jacobs, J., Fried, I. & Kahana, M. J. Broadband shifts in local field potential power spectra are correlated with single-neuron spiking in humans. J. Neurosci. 29 , 13613-13620 (2009). https://doi.org:10.1523/JNEUROSCI.2041-09.2009 Fisher, R. et al. Electrical stimulation of the anterior nucleus of thalamus for treatment of refractory epilepsy. Epilepsia 51 , 899-908 (2010). https://doi.org:10.1111/j.1528-1167.2010.02536.x Allison, T., McCarthy, G., Wood, C. C. & Jones, S. J. Potentials evoked in human and monkey cerebral cortex by stimulation of the median nerve. A review of scalp and intracranial recordings. Brain 114 ( Pt 6) , 2465-2503 (1991). https://doi.org:10.1093/brain/114.6.2465 Matsumoto, R. et al. Left anterior temporal cortex actively engages in speech perception: A direct cortical stimulation study. Neuropsychologia 49 , 1350-1354 (2011). https://doi.org:10.1016/j.neuropsychologia.2011.01.023 Yamao, Y. et al. Intraoperative Brain Mapping by Cortico-Cortical Evoked Potential. Front Hum. Neurosci. 15 , 635453 (2021). https://doi.org:10.3389/fnhum.2021.635453 Crone, N. E., Sinai, A. & Korzeniewska, A. High-frequency gamma oscillations and human brain mapping with electrocorticography. Prog. Brain. Res. 159 , 275-295 (2006). https://doi.org:10.1016/S0079-6123(06)59019-3 Usami, K. et al. The dynamics of cortical interactions in visual recognition of object category: living versus nonliving. Cereb. Cortex 33 , 5740-5750 (2023). https://doi.org:10.1093/cercor/bhac456 Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164 , 177-190 (2007). https://doi.org:10.1016/j.jneumeth.2007.03.024 Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformation20250403.docx Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 02 May, 2025 Reviews received at journal 30 Apr, 2025 Reviews received at journal 28 Apr, 2025 Reviewers agreed at journal 18 Apr, 2025 Reviewers agreed at journal 14 Apr, 2025 Reviewers agreed at journal 14 Apr, 2025 Reviewers invited by journal 11 Apr, 2025 Editor assigned by journal 11 Apr, 2025 Editor invited by journal 11 Apr, 2025 Submission checks completed at journal 04 Apr, 2025 First submitted to journal 27 Mar, 2025 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. 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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-5257628","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442841130,"identity":"e5da5a6e-d327-4030-a9dc-1031e2f429c4","order_by":0,"name":"Yawara Nakamura","email":"","orcid":"","institution":"Ehime University","correspondingAuthor":false,"prefix":"","firstName":"Yawara","middleName":"","lastName":"Nakamura","suffix":""},{"id":442841131,"identity":"ed7be9ed-afe2-42a1-8c2b-fe75cf349db2","order_by":1,"name":"Kiyohide Usami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYDACHsYGBoaKBAYDBgZmZHE2AlrOwLUYEKMFiBnbMLXgBgZnDrdJfJyXlrhduoHZmKfijxyDRALjhx8MfHk4tZxtbJOcuS0nceecA8zJPGcMjIFamCV7GNiKcWo5z9gmzbutInHDjQTmw7xtBon7byQwSAP9ktiAV8scJC0NQFt+49UCdJg0b0MOWEsyVAsbXlskzxxstpxxLM14w52DzYZzzhgbM/A8bLPsMcDtF74z6Q9vfKhJlt1wu/mwxJsKOTkG9uTDN35UHMMZYkDAIgGmJBgbmHjALFDkGhxLwKOF+QNEC1DtD4RoDT4to2AUjIJRMLIAADAlVbXam/cVAAAAAElFTkSuQmCC","orcid":"","institution":"Kyoto University","correspondingAuthor":true,"prefix":"","firstName":"Kiyohide","middleName":"","lastName":"Usami","suffix":""},{"id":442841132,"identity":"f12a60cf-8b0f-4f39-b5dc-b046ec201943","order_by":2,"name":"Haruo Yamanaka","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Haruo","middleName":"","lastName":"Yamanaka","suffix":""},{"id":442841133,"identity":"6072e9ed-5820-43d2-afe3-0821685bd437","order_by":3,"name":"Daisuke Yamada","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Daisuke","middleName":"","lastName":"Yamada","suffix":""},{"id":442841136,"identity":"31d62149-19d2-4d7b-9e55-26a6b63f8ab3","order_by":4,"name":"Yohei Mineharu","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Yohei","middleName":"","lastName":"Mineharu","suffix":""},{"id":442841138,"identity":"b466f2ff-2f7f-4e65-a087-4d05d95ac8af","order_by":5,"name":"Takayuki Kikuchi","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Takayuki","middleName":"","lastName":"Kikuchi","suffix":""},{"id":442841140,"identity":"112d077e-3c25-4b6b-96db-2643a6ea7b10","order_by":6,"name":"Yoshiki Arakawa","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Yoshiki","middleName":"","lastName":"Arakawa","suffix":""},{"id":442841142,"identity":"d45b0339-f72f-455e-8b35-587a744733b6","order_by":7,"name":"Takeharu Kunieda","email":"","orcid":"","institution":"Ehime University","correspondingAuthor":false,"prefix":"","firstName":"Takeharu","middleName":"","lastName":"Kunieda","suffix":""}],"badges":[],"createdAt":"2024-10-14 03:08:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5257628/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5257628/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-09456-3","type":"published","date":"2025-07-01T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80730770,"identity":"dd4901f9-3270-4070-a29d-6aefaed24f4a","added_by":"auto","created_at":"2025-04-16 12:32:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1334831,"visible":true,"origin":"","legend":"\u003cp\u003eSchema of the present study. (a) Intra-operative recording flowchart. The stimulus conditions are thalamo-cortical evoked potential (TCEP): alternate stimulation, frequency 0.4 Hz, Intensity 10 mA, 30 times×2, SEP: Frequency 0.3 Hz, Intensity 10 mA, 100 times. (b) Waveforms obtained by recording. A in the electrode name indicates electrodes implanted in the cortex and B in the thalamus. (c) Intraoperative recording schemas. Electrodes implanted on the brain surface and thalamic surface through the lateral ventricles are shown in d and e, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/ed59b6c1d3cc519c0a9b4dfd.png"},{"id":80728906,"identity":"596745de-7ced-4ef1-b43f-49e087b29d98","added_by":"auto","created_at":"2025-04-16 12:16:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93466,"visible":true,"origin":"","legend":"\u003cp\u003eThe position of the implantedelectrodeson the surface of the thalamus is shown in the MNI standard space (FSLeyes version 0.31.2). The beige structures represent the thalamus. Each is indicated by the following colors: Patient 1: red, Patient 2: blue, Patient 3: green, Patient 4: yellow, Patient 5: white, and Patient 6: light blue.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/7bce3f7b6719730cfe855bc1.png"},{"id":80728909,"identity":"58a628e6-c5bd-40ba-a5f4-9e656d263d53","added_by":"auto","created_at":"2025-04-16 12:16:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1533918,"visible":true,"origin":"","legend":"\u003cp\u003ePatient 3 is presented as a representative. Schematic of electrodes implanted in the cortex and thalamus (4×4, blue frameand 1×4, yellow frame respectively) and (a-1) CCEP, (a-2) CCSRwithout statistical analysis,(a-3) CCSR with statistical analysis, (b-1) TCEP, (b-2) TCSR without statistical analysis, (b-3) TCSR with statistical analysisresults. In the analysis results, red represent an increase in power in the frequency band, while blue indicates a decrease. Arrowheads indicate stimulating electrodes. (c) A11 in the CCSR and (d) A13 in the TCSR, showing an enlarged view of the analysis results. CCSR shows the power increase in the broadband, ranging between 0 and 500 Hz. In contrast, TCSR increase is confined to the 0–200 Hz band, centered at 100 Hz.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/56d0aed247b2066ab1fc00b7.png"},{"id":80730111,"identity":"e7218dbf-37de-47b9-893a-f13a13abf2c4","added_by":"auto","created_at":"2025-04-16 12:24:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1535187,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of the number of clusters that showed a significant increase in HGA power in (a) TCSR and (b) CCSR in the 20–40 ms, (c) TCSR and (d) CCSR in the 20-60 ms after stimulation is shown by a simple sum of significant bins across all patients. The red bars indicate an increase in power, while the blue bars indicate a decrease. Note that the range of the y-axis differs in each graph.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/fae3d56045775e138fa92c91.png"},{"id":80728913,"identity":"bea97ceb-26f9-4b81-87d0-8eb637273b6d","added_by":"auto","created_at":"2025-04-16 12:16:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2134051,"visible":true,"origin":"","legend":"\u003cp\u003eThe position of the implanted cortical electrodes (red dots) and central sulcus (yellow line) in each patient. The position of the central sulcus is determined by verifying the phase inversion of the SEP. The frontal lobes are deformed due to the presence of intraparenchymal tumors in the ipsilateral frontal lobes.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/d21bdf4f828e20f0f622af9c.png"},{"id":86178933,"identity":"befc69b1-7316-4984-98c5-ee2c1a7fdf90","added_by":"auto","created_at":"2025-07-07 16:11:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9140872,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/fe24fcb0-57d8-4e81-b144-612c3830f7f8.pdf"},{"id":80730769,"identity":"db12016b-d2c9-44f2-909c-abd7beec65c5","added_by":"auto","created_at":"2025-04-16 12:32:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":541202,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation20250403.docx","url":"https://assets-eu.researchsquare.com/files/rs-5257628/v1/09453f8ee2008eba4efed0c5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe thalamus is a hub for neural networks in the human brain\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Furthermore, except for olfaction, it relays almost all information input to the cortex, including sensory, motor, auditory, and visual inputs\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and is crucial for signal transmission. The connectivity between the thalamus and cortex has been studied for a long time. In 1942, Morison and Dempsey reported the existence of two projection systems between the thalamus and cortex in animal experiments in cats\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In addition, many previous studies have assessed thalamocortical connectivity using magnetic resonance imaging (MRI)-based diffusion tensor imaging \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e or functional MRI\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Notably, several studies have evaluated its transformation in patients with psychiatric disorders, including schizophrenia\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, insomnia\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and mood disorders\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, optogenetic techniques in rats have confirmed that thalamus stimulation activates a large area of the forebrain, bringing the sleeping rat brain to a waking state\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This projection system sends fibers to extensive cerebrum areas and helps regulate consciousness and arousal. Notably, most non-specific nuclei of the non-specific projection system are located in the median thalamus or group of nuclei within the medullary plate. However, specific nuclei have bidirectional fiber connections with particular areas of the cortex. These specific nuclei are mainly located in the lateral part of the thalamus\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Thalamocortical and corticocortical fibers reach the cortex entangled, complicating their differentiation macroscopically. The rich connectivity between the cortex and thalamus is also a central component for electroencephalogram (EEG) generation. EEG rhythms\u0026thinsp;\u0026lt;\u0026thinsp;20 Hz are thought to be generated by the thalamocortical connection, transforming local excitability under the control of subcortical nuclei\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The corticothalamic neurons provide feedback to the thalamocortical nuclei and synapse with the thalamic reticular nuclei and thalamocortical neurons to form oscillatory thalamocortical loops. These loop structures reportedly generate delta rhythms and spindle waves\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Therefore, visualizing the difference between corticocortical and thalamocortical connectivity aids in revealing the mechanism that generates cortical EEG rhythms. Beyond its role in physiological neural networks, the thalamus is implicated in epileptic abnormal activity. The thalamus contributes to the generation of spindle wave rhythms during sleep\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, and may facilitate generalized epileptic discharges in idiopathic generalized epilepsy via a similar thalamo-cortical loop\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Evidence from a zero-magnesium \u003cem\u003ein vitro\u003c/em\u003e model of epilepsy indicates synchronous firing between thalamic and cortical neurons\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Additionally, the thalamus is recruited nonlinearly into synchronous cortical discharges, with coupling reliability increasing over time\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Electrical stimulation of the thalamus modulates cortical activity: low-frequency stimulation of the prethalamic nucleus induces rhythmic EEG synchronization\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, whereas high-frequency stimulation leads to desynchronization of the EEG\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. High-frequency stimulation of the prethalamic nucleus thalamic nucleus in experimental animals reduces seizure activity in epileptic seizure models\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Clinical trials have been conducted in humans with drug-resistant epilepsy\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and the use of deep brain stimulation of the anterior thalamic nucleus is gaining traction in clinical practice as a neuromodulation therapy.\u003c/p\u003e \u003cp\u003eCorticocortical-evoked potential (CCEP) is a method that allows for investigating electrophysiological connectivity. This technique was established by Matsumoto et al. in 2004 to search for functional connectivity in the brain\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and is currently in clinical use worldwide \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This method analyzes the corticocortical connectivity by administering electrical stimulation to a specific cortical region and recording subsequent neuronal responses in other regions. Furthermore, electrical stimulation has been demonstrated to elicit a cortico-cortical spectral response (CCSR)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Stimulation initiates action potentials in the cortex, modulating the power in the high-frequency band\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Physiologically, gamma oscillations, particularly those\u0026thinsp;\u0026gt;\u0026thinsp;60 Hz (60\u0026ndash;200 Hz), are closely linked to brain functions, such as motor, language, attention, auditory, and visual functions\u003csup\u003e\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Neuronal activity\u0026thinsp;\u0026lt;\u0026thinsp;60\u0026ndash;80 Hz is derived not only from the synchronization of excitatory neurons, but also from inhibitory interneurons\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, whereas neuronal activity between 80\u0026ndash;200 Hz reflects increased multiunit activity or local potentials\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, we hypothesized that analyzing the causal functional connectivity between the thalamus and cortex could be possible by stimulating the thalamus and recording responses in the cortex using a methodology similar to CCSR. We termed this method the \u0026ldquo;thalamocortical spectral response (TCSR)\u0026rdquo;. In practice, opportunities to directly record action potentials in the thalamus and cortex are extremely limited, particularly given the difficulty in simultaneously recording the cortical and subcortical nuclei. Therefore, the physiological mechanisms of cortical-thalamic coupling and its relevance to epileptic activity remain largely unknown. Furthermore, whether stimulating the thalamus could have different or similar effects on other brain parts remains unclear\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we implanted electrodes in patients whose lateral ventricles were opened during neurosurgery for lesion removal. This approach allowed direct recording of responses to bipolar stimulation of the cerebral cortex and thalamus. By analyzing the data, we compared the responses induced by cortical and thalamus stimulation, identifying key differences in their characteristics.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFig. 1 shows the recording schema. Electrodes were placed intraoperatively on the surface of the thalamus, via the opened ventricles (1\u0026times;4 electrode strip), and brain surface (4\u0026times;4 electrode grid). Bipolar stimulation was performed through each electrode, after which the cortical response was recorded. Time-frequency and rigorous statistical analyses were performed to compare between TCSR and CCSR.\u003c/p\u003e\n\u003cp\u003eThe position of electrode placement was confirmed using a navigation system, although there was some variation between patients. Electrodes were placed on the medial surface of the thalamus in all patients; 17 of the 24 electrodes were deployed in the dorsomedial nucleus of the thalamus (Fig. 2). The MNI coordinates (presented in FSL view (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslView)) are listed in Supplementary Table S1A. The average waveform of the thalamic stimulation was not reproducible (Fig. 3b-1), as a CCEP-like waveform was observed in only one electrode in two of the 24 trials. In contrast, the average waveform of the cortical stimulation showed CCEP waveforms at the cortical electrodes surrounding the stimulating electrode. However, no clear CCEP waveforms were observed at the thalamic electrodes (Fig. 3a-1).\u003c/p\u003e\n\u003cdiv\u003e\u003c/div\u003e\n\u003cp\u003eSignificant CCSR and TCSR were observed in all six patients immediately after stimulation (from +\u0026thinsp;20 ms to +\u0026thinsp;40 ms), with 11 and 10 trials, respectively (see Supplementary Tables S1B and 1C for the stimulation electrode pairs, S2 and S3 for electrodes showed significant response). TCSR showed increased high gamma activities (HGA, 60\u0026ndash;200 Hz) power at approximately the 100 Hz band. However, it seemed that CCSR showed increased power over a wider frequency band (Figs. 3 and 4). The electrode positions at which the HGA power modulation was observed varied greatly from patient to patient. The statistical analysis results for the power modulation observed in the time-frequency analysis showed that the response observed in TCSR had a more limited frequency bandwidth than that of CCSR (z value\u0026thinsp;=\u0026thinsp;2.0102, ranksum\u0026thinsp;=\u0026thinsp;150, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0444). Furthermore, the distribution of electrodes showing power modulation in the TCSR did not differ significantly between the frontal and parietal lobes (df\u0026thinsp;=\u0026thinsp;1, \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.0418, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3074). However, when looking at individual patients, significant responses in the parietal lobe were more common in patient 3, whereas most significant responses in the other patients were found in the frontal lobe. It should be noted that the small population size limits the interpretation of the results, and the results of this statistical analysis are heavily influenced by patient 3.The ratio of electrodes in which the HGA power decrease was observed was 33.8% (52 of the 154 electrodes) and 1.3% (2 of the 160 electrodes) for CCSR and TCSR, respectively, showing a higher value in the CCSR than that in the TCSR (df\u0026thinsp;=\u0026thinsp;1, \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;58.2645, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.2915\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;14\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eAfter subtracting the average waveform from each trial (see Supplementary Fig. 1), the number of electrodes showing increased power compared with before subtraction decreased, but a significant increase in HGA power was observed in TCSR and CCSR. No significant differences were found for the frequency band distribution (ranksum\u0026thinsp;=\u0026thinsp;86, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1067); however, a similar trend to that observed before subtraction was noted.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study to focus on patients who underwent neurosurgery, wherein the ventricle was opened for clinical reasons, allowing grid placement on the surface of the thalamus. Previous studies using deep electrodes, such as stereoelectroencephalography\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, have examined thalamic stimulation and its interaction with sparsely implanted electrodes in other regions\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. However, no prior research has directly compared between CCSR and TCSR within the same patient. Here, intraoperative recordings were analyzed to test the hypothesis that thalamic and cortical stimulations could affect the cortex differently; the responses produced by CCSR and TCSR differed in time and space.\u003c/p\u003e \u003cp\u003eTCSR analysis demonstrated the electrophysiological connectivity between the thalamus and cortex during electrical stimulation of the surface of the thalamus. In our results, CCEP-like waveforms were not identifiable with thalamic stimulation. As TCEP is derived from an additive average, oscillations may have been cancelled out. However, we hypothesized that TCSR could detect even a small number of trials with high sensitivity. Compared with TCSR, CCSR exhibited power modulation over a wide frequency range (0\u0026ndash;500 Hz) during latencies corresponding to N1, which exhibited power modulation over a relatively restricted frequency band centered at 100 Hz. After subtracting the average waveform, the distribution of frequency bands no longer showed a significant difference. However, the frequency band of TCSR tends to be more limited. In the spectrum analysis without subtraction, the HG component synchronized with electrical stimulation may have been included.\u003c/p\u003e \u003cp\u003eAs previously demonstrated\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, CCSR exhibited a power increase followed by a power decrease in the HGA, a pattern rarely observed in TCSR. This phenomenon, which states that \u0026ldquo;a stronger degree of power increase is more likely to induce a power decrease immediately afterward,\u0026rdquo; was observed in our previous study\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Therefore, it is likely that the smaller degree of power increase in TCSR compared with that in CCSR did not induce a rebound power decrease. Within the first 60 ms after stimulation, TCSR shows a continuous increase up to 60 ms, whereas CCSR exhibit a strong decrease. Although this remains a hypothesis, it is possible that CCSR originally follows a similar increasing trend as TCSR, but this effect is cancelled by the decrease. In contrast, previous reports highlight delayed high-frequency inhibition following single-pulse electrical stimulation\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Therefore, HGA power may fluctuate in diverse patterns, reflecting increases and decreases. Each nucleus in the thalamus is thought to play a role in multisensory integration. Furthermore, projection fibers are thought to have selective connections to each cortical area\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. For example, the primary motor cortex and supplementary motor area are thought to receive thalamocortical projections from the ventral anterior and ventral lateral nuclei of the motor thalamic nuclei\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. However, the primary sensory cortex receives thalamocortical projections from the ventral posterolateral, ventral posteromedial, and ventral posteroinferior nuclei of the sensory thalamic nuclei\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. In this study, extensive stimulation was applied to the medial surface of the anterior thalamus (dorsomedial nucleus), which is believed to project fibers to the prefrontal cortex and contribute to higher cognitive functions, along with other regions\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. However, this study was conducted as part of clinical neurophysiological monitoring, with electrodes placed in the central sulcus, the standard site for MEP/SEP recordings. Additionally, in most patients, the prefrontal cortex was resected, resulting in the absence of recordings from this region. If recordings had been possible from the prefrontal cortex, where the dorsomedial nucleus projects, the results may have been more reproducible. Consequently, these findings may not be fully generalizable to thalamo-cortical interactions because the electrodes were implanted in sensorimotor areas that have no structural connection to the dorsomedial nucleus. However, in this study, it was stimulated broadly rather than selectively. This may have resulted in its transmission by non-specific fibers rather than specific fibers bound to specific subnuclei and may have led to variations in the sites of power modulation around the central sulcus. Alternatively, the stimulus to the medial surface of the thalamus may have been attenuated and relayed through surrounding thalamic nuclei, which then transmitted it to the cortex via their projections, resulting in only a small response being picked up.\u003c/p\u003e \u003cp\u003eThe recordings were conducted with open lateral ventricles filled as much as possible with artificial cerebrospinal fluid. However, artificial cerebrospinal fluid leaked continuously during recording, and the possibility that the conditions differed from those of stimulation under physiological conditions cannot be ruled out. Continuous electrode impedance monitoring was not possible; however, the thalamic electrodes were secured with cotton and positioned against the ventricular wall for recording, and it was confirmed that they successfully captured EEG signals. The data were recorded intraoperatively during surgical procedures and contained environmental noise and artifacts resulting from surgical manipulation. However, the common average reference method and visual artifact elimination were deemed sufficient to permit a successful analysis of the HGA. We hypothesized that HGA most could likely occur in the cortex when stimuli arrive from the thalamus, in contrast to CCSR, which evokes several spectral responses. Physiologically, HGA (60\u0026ndash;200 Hz) is suggested to be closely associated with various brain functions, including movement, language, attention, hearing, and vision\u003csup\u003e\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The narrow gamma band of 60\u0026ndash;80 Hz is believed to arise not only from the synchronization of excitatory neurons but also from inhibitory interneurons\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Broadband power, including the HGA of 80\u0026ndash;200Hz, is thought to correlate closely with local potential firing rate\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, the exact generator of lower-frequency activity (\u0026lt;\u0026thinsp;50 Hz) is unknown. Our findings suggest that corticocortical connectivity influences multiple generators, contributing to lower-band oscillations. However, thalamic connectivity transmits information more precisely and minimally, spatially and as a cell type.\u003c/p\u003e \u003cp\u003eDeep brain stimulation of the anterior thalamic nucleus is currently approved as a neuromodulation treatment of refractory epilepsy and may become more widely available in the future\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Therefore, further data on the electrical stimulation of the anterior thalamic nucleus and its cortical responses should be obtained to ensure new findings on the thalamocortical network and optimal stimulation methods by comparing them with our data.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eBetween 2021 and 2023, ten consecutive patients were scheduled for surgeries performed at the Department of Neurosurgery, Kyoto University Hospital, which included the following procedures: 1) craniotomy, 2) large opening of the lateral ventricle, 3) intraoperative neuromonitoring such as sensory evoked potentials (SEP) motor-evoked potentials (MEP) and CCEP, and 4) awake surgery. Six of these patients were included in this study, excluding those with inaccurate electrode position information based on the navigation system, those with significant environmental noise contamination, and those under general anesthesia rather than awake at recording time.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003ePatient Profile and analyzed electrodes\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003eAge, gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eTumor lesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eTumor diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eAntiseizure medication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eEpilepsy\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e# of electrodes placed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eFrontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eParietal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e58, M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eGliosarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ef-PHT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e46, F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eAnaplastic oligodendroglioma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ef-PHT, LEV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e40, M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eGlioblastoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ef-PHT, LEV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e34, M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eDiffuse astrocytoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ef-PHT, LEV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e42, M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eAnaplastic astrocytoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLEV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e45, M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRt. frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eGlioblastoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003efPHT, LEV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e f-PHT: fos-phenytoin, LEV: levetiracetam\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The patients (five men and one woman) aged 34\u0026ndash;58 years (mean: 44.6 years), and they all had intraparenchymal frontal lobe tumors, three each on the left and right sides. Furthermore, they were treated with anti-seizure medications in the perioperative period, and two patients were diagnosed with brain tumor-related epilepsy (Table 1). This study was approved by the Ethics Committee of the Kyoto University Graduate School of Medicine (C1082) and appropriate informed consent was obtained from all patients preoperatively. In addition, this study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter craniotomy, a 4\u0026times;4 electrode grid (Unique Medical, Tokyo, Japan; recording diameter, 3 mm; inter-electrode spacing, 1 cm; made of platinum) was placed on the brain surface around the central sulcus. Stimulation was delivered through a silver disk electrode (Nihon Kohden, Tokyo, Japan) implanted on the contralateral median nerve preoperatively, and the location of the central sulcus was identified by recording SEPs and confirming phase reversal\u003csup\u003e53\u003c/sup\u003e. Intraoperative photographs and structures of the surrounding veins confirmed that, in all patients, the 4\u0026times;4 grid spanned the central sulcus and was implanted close to the hand motor cortex (Fig. 5, created using Brainlab Elements software). Table 1 lists the locations of each electrode in the frontal and parietal lobes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter opening the lateral ventricles by removing the lesion, a 1 \u0026times; 4 electrode strip (Unique Medical, Tokyo, Japan; recording diameter, 3 mm; inter-electrode spacing, 1 cm; platinum) was inserted into the lateral ventricles. The electrodes were placed on the surface of the thalamus over the ventricular wall, facing the foramen of Monro, anterior septal vein, choroid plexus, and thalamostriate vein as landmarks (Fig. 4). The position of the electrodes was confirmed by recording the coordinates using the Brainlab navigation system and three-dimensional image composition, in addition to the position of the vein on the brain surface. The electrodes were located at 1 cm intervals from the pointed coordinate on the anterior-posterior axis on the preoperative MRI while reviewing the video taken intraoperatively. Co-registration was made to the MNI coordinate (Fig. 1). The co-registration procedure has been previously described \u003csup\u003e25,43,54\u003c/sup\u003e. After placement, the electrodes were covered with gauze or threaded cotton to prevent them from floating off the brain surface and thalamus. The ventricles were filled with artificial cerebrospinal fluid as much as possible. The reference electrode was a disk electrode (Nihon Kohden) implanted in the contralateral mastoid process, and a skin pretreatment agent and electrode paste (Nihon Kohden) were used to reduce electrical resistance.\u003c/p\u003e\n\u003cp\u003eThe resting state, SEP, TCSR, and CCSR were recorded. TCSR and CCSR were assessed in this study. The detailed methodology of CCEP has been previously described\u003csup\u003e25\u003c/sup\u003e; thalamic stimulation was performed accordingly. Single-pulse electrical stimulation of alternating polarity was applied using two adjacent subdural electrodes, and the evoked responses were recorded from other electrodes using a constant-current stimulator (MEE-1232; Nihon Kohden). Regarding the stimulating electrodes, we selected electrodes positioned to straddle the central sulcus, as is usually performed for MEPs during cortical stimulation. However, considering the thalamic electrodes, we selected electrodes that we assumed to be in contact with the thalamic surface.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsequently, when neither of the stimulated electrodes was located on the surface of the thalamus in the MNI space, the data were excluded from further analysis. In previous studies, CCEPs consisted of early (N1) and late (N2) negative potentials with latencies of 10\u0026ndash;50 ms and 100\u0026ndash;200 ms, respectively\u003csup\u003e25,26\u003c/sup\u003e. In the present study, thalamo-cortical evoked potentials were defined as evoked potentials recorded using short-pulse electrical stimulations from electrodes implanted in the thalamus and recorded by electrodes on the cortex. However, TCSR was the main target for analysis.\u003c/p\u003e\n\u003cp\u003eThe sampling rates were 5000 Hz or 1000 Hz; the same constant-current stimulator (MEE-1232, Nihon Kohden, Tokyo, Japan) recorded SEP with a stimulation and intensity frequency of 0.3 Hz and10 mA, respectively. Furthermore, the set of 100 trials was repeated twice; Thalamo-cortical evoked potential and CCEP were performed with a stimulation frequency of 0.4 Hz, intensity of 10 mA with alternating polarity, and duration of 0.3 ms. Each set of 30 trials was repeated twice, so the total duration of the stimulation was 18 ms. Notably, all patients underwent neurological function monitoring; all recordings were made while the patients were awake following propofol withdrawal. The absence of after-discharge due to electrical stimulation was constantly monitored. In addition, we confirmed that thalamic and cortical stimulation in the awake state did not induce any clinical symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime-frequency analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis was performed using in-house scripts in Matlab software (Matlab version 9.14.0; MathWorks Inc., MA, USA). Data recorded at a sampling rate of 5000 Hz were analyzed by downsampling to 1000 Hz, with the low-frequency filter set at 0.08\u0026ndash;1 Hz\u003csup\u003e55\u003c/sup\u003e. Furthermore, to reduce noise due to intraoperative manipulation and environmental noise, data were derived using a common average reference (four electrodes on the thalamus and 16 electrodes on the cerebral cortex separately), and each stimulus timing was marked. The analysis window was set from 500 ms before the stimulus onset to 1000 ms after this onset; a short-time Fourier transform was performed to extract stimulus-induced spectral responses, including high-gamma activities (HGAs: 60\u0026ndash;200 Hz). The Fourier transform window was set to 20 ms, and the window center position was shifted by 10 ms. Based on previous studies, stimulus-induced artifacts could persist for 3\u0026ndash;4 ms after the stimulus onset\u003csup\u003e42\u003c/sup\u003e. Therefore, this setting allowed the frequency resolution to reach 50 Hz (0, 50, 100, and 150 Hz). However, the time bin after 20 ms could be considered, excluding the influence of stimulus artifacts. The baseline was set at 500 ms and 490 ms before stimulus onset. Raw electrocorticography data were carefully analyzed; the corresponding trial was excluded from the analysis if any obvious noise or artifacts associated with surgical manipulation were found in the analysis window. The polarity of the stimuli varied between odd and even trials; therefore, they were excluded as pairs so that their numbers were equal.\u003c/p\u003e\n\u003cp\u003eFurthermore, to focus on the modulation of HGA corresponding to the N1, electrodes with a statistically significant increase in HGA power of 20\u0026ndash;40 ms after stimulation were defined as those with a significant increase in power in the present analysis. Similarly, electrodes with a statistically significant decrease in HGA power up to 200 ms, corresponding to the latency of N2, were defined as electrodes with a significant decrease in power.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpectral analysis may be influenced by time-synchronized evoked potential, as impulse-like activity can cause broadband changes\u003csup\u003e56\u003c/sup\u003e. To address this, we conducted a supplementary analysis after subtracting the average waveform from each trial and compared the results before and after subtraction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStimulation-induced significant changes in the time-frequency domain were searched using a cluster-level nonparametric permutation test\u003csup\u003e57,58\u003c/sup\u003e. The \u003cem\u003eF\u003c/em\u003e-value in the analysis window was calculated and compared with the baseline; the corresponding \u003cem\u003eP\u003c/em\u003e-value threshold was set at 0.05. In the time-frequency domain, the sum of consecutive \u003cem\u003eF\u003c/em\u003e-values that satisfied \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.025 at the upper side (significant increase) or the inverse sum of consecutive \u003cem\u003eF\u003c/em\u003e-values satisfying \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.025 at the lower side (significant decrease) was calculated for the cluster-level statistics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn contrast, surrogate trials were prepared by taking the same number of real trials randomly from the same EEG file, with each analysis window (-500 \u0026ndash; +1000 ms at sham stimulus) that did not involve stimulus artifacts. Notably, similar to the original trials, the maximum or minimum cluster-level statistics were calculated based on F-values. This procedure was repeated 10,000 times, and the null distribution of the maximum/minimum cluster-level statistics was compared with that of the original cluster-level statistics at each electrode level. A \u003cem\u003eP\u003c/em\u003e-value threshold was defined at \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eAfter collecting the electrodes that showed significant CCSR or TCSR, the null hypothesis that \u0026ldquo;there was no difference in the width of the frequency bands in which power modulation occurred in TCSR and CCSR\u0026rdquo; was tested as a group analysis, not considering the subject of origin, focusing on the number of significant clusters in each analysis in the time bin in which the HGA corresponding to N1 was found to increase, namely, the +20 ms \u0026ndash; +40 ms bin. A higher number of clusters indicates a wider distribution of the frequency bands in which power modulation occurs. The Wilcoxon rank-sum test was used to calculate the mean number of clusters at electrodes with significant responses in each TCSR and CCSR trial.\u003c/p\u003e\n\u003cp\u003eAdditionally, the number of electrodes with significant HGA elevation in the TCSR located in the frontal and parietal lobes was counted. Then, a \u0026chi;-squared test was applied under the null hypothesis that \u0026ldquo;the number of electrodes with significant HGA elevations does not differ between the frontal and parietal lobes.\u0026rdquo; Similarly, the number of electrodes with significant decrease in power in each trial was counted, and a \u0026chi;-squared test was applied under the null hypothesis that \u0026ldquo;the number of electrodes with significant decrease in power does not differ between TCSR and CCSR\u0026rdquo;.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be available upon a reasonable request; contact Usami K [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Japanese Society for the Promotion of Science, KAKENHI (20K16492 and 23K14775 to K. U.). We would like to thank Editage (www.editage.jp).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.N. and K.U. contributed to the conception and design of the study, acquisition and analysis of data, drafting a significant portion of the manuscript or figures. H.Y. and D.Y. contributed to the acquisition of data, improvements in recording methods. Y.M. and Y.A. contributed to the acquisition of data as operating surgeon, T.K. and T.K. contributed to the conception and design of the study, interpretation of data.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests regarding this study.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHwang, K., Bertolero, M. A., Liu, W. B. \u0026amp; D\u0026apos;Esposito, M. 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Methods\u003c/em\u003e \u003cstrong\u003e164\u003c/strong\u003e, 177-190 (2007). https://doi.org:10.1016/j.jneumeth.2007.03.024\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"thalamocortical connectivity, neural networks, cortico-cortical evoked potential, thalamic projections, time-frequency analysis","lastPublishedDoi":"10.21203/rs.3.rs-5257628/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5257628/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological interactions remain largely unexplored. Therefore, in this study, we recruited six patients who underwent awake craniotomy with opened lateral ventricles. The electrodes were placed on the thalamic surface over the ventricular wall and brain surface around the central sulcus. Electrical stimulation was applied to each electrode to record the evoked responses. Furthermore, we performed time-frequency and statistical analyses to investigate the cortical responses induced by electrical stimulation. High gamma activity was elicited in the cerebral cortex following thalamic stimulation. However, regarding frequency bands, the cortical spectral response induced by thalamic stimulation (TCSR) showed power increases in more restricted bands at approximately 100 Hz compared with the cortical spectral response induced by cortical stimulation (CCSR). In contrast, more electrodes in CCSRs showed a power decrease after the power increase than those in TCSRs. Finally, compared with the cortex, thalamic projections evoked localized neural activity in the cortex. Adjusting stimulus intensity and comparison with deep thalamic electrode stimulation will further clarify thalamocortical linkages.\u003c/p\u003e","manuscriptTitle":"Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-16 12:16:31","doi":"10.21203/rs.3.rs-5257628/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-02T07:57:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-30T22:32:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-28T20:50:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9199138771879855478459021543031607209","date":"2025-04-18T13:37:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212711110757225564406478756374488105244","date":"2025-04-14T16:39:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304658454640101315560861920071244489240","date":"2025-04-14T15:57:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-12T02:11:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-12T02:05:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-11T07:57:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-04T12:43:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-27T15:42:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bfb778af-ad2a-4e21-a21f-5292ba3bdfc4","owner":[],"postedDate":"April 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47146250,"name":"Biological sciences/Neuroscience"},{"id":47146251,"name":"Biological sciences/Neuroscience/Neural circuit"}],"tags":[],"updatedAt":"2025-07-07T16:00:39+00:00","versionOfRecord":{"articleIdentity":"rs-5257628","link":"https://doi.org/10.1038/s41598-025-09456-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-01 15:57:11","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2025-04-16 12:16:31","video":"","vorDoi":"10.1038/s41598-025-09456-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-09456-3","workflowStages":[]},"version":"v1","identity":"rs-5257628","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5257628","identity":"rs-5257628","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}