Patient-specific neural implants engineered via 3D printing technology

Abstract

Embodiments relate to bioelectrodes designed to accommodate patient specific gyral patterns, and to methods of making and using thereof. A bioelectrode may be manufactured by obtaining a three-dimensional scan of at least a portion of a brain; identifying a target region of the brain; designing a bioelectrode model configured to fit the target region; and printing the bioelectrode based on the bioelectrode model. The bioelectrode is printed to include a top layer, a bottom layer, and an electrode layer positioned between the top layer and the bottom layer such that the top layer and bottom layer encapsulate the electrode layer. The bioelectrode may have a Young's modulus between 0.1 and 10 kPa to better mechanically match brain tissue.

Description

Atty. Ref. No. 0073605-001041PATIENT-SPECIFIC NEURAL IMPLANTS ENGINEERED VIA 3D PRINTING TECHNOLOGYCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This patent application is related to and claims the benefit of priority of U.S. Provisional Application 63 / 687,166, filed on August 26, 2024, the entire contents of which are incorporated by reference.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH DEVELOPMENT

[0002] This invention was made with government support under Grant No. HL171633 awarded by the National Institutes of Health. The Government has certain rights in the invention.FIELD

[0003] Embodiments relate to patient specific neural implants, and particularly to three- dimensional (3D) printable bioelectrodes designed to accommodate patient specific gyral patterns.BACKGROUND

[0004] The human brain’s intricate structure, characterized by unique gyral patterns, presents significant challenges for the development of effective neural interfaces. The cerebral cortex consists of complex folds, known as gyri and sulci, which enhance neural connectivity and facilitate efficient information processing. Individual variability in these patterns, influenced by factors such as age, sex, and genetics, creates a distinct “fingerprint” for each brain. This variability highlights the necessity for personalized neural interfaces that can accurately engage with specific cortical topographies for therapeutic applications, including neuromodulation and neuroprosthetics.Atty. Ref. No. 0073605-001041

[0005] Traditional neural interfaces, such as electrocorticography (ECoG) systems, predominantly utilize rigid, lithographically produced electrodes designed for mass production. These one-size-fits-all solutions fail to conform to the diverse anatomical structures of individual patients' brains, leading to suboptimal electrode-tissue contact. Consequently, this mechanical mismatch results in signal degradation and adverse tissue reactions, including inflammation and scarring. While softer materials have been explored, existing solutions still lack the ability to customize electrode designs according to the unique gyral patterns of individual patients, which is crucial for achieving optimal biocompatibility and signal fidelity.

[0006] The increasing prevalence of neurological disorders underscores the urgent need for improved neural recording technologies. According to the World Health Organization, neurological conditions are a leading cause of mortality worldwide, highlighting the critical demand for innovative neural interfaces that can provide effective treatment options. Conventional probes often fall short in terms of softness, conformability, and personalization, leaving a significant gap in the market for advanced solutions that can address these challenges. The limitations of existing technologies necessitate the exploration of different approaches that integrate patient-specific anatomical data with advanced fabrication techniques to enhance the efficacy and safety of neural interfaces.SUMMARY

[0007] The present disclosure introduces a platform for the development of patient-specific neural interfaces, aimed at overcoming the limitations of traditional rigid electrodes. Embodiments integrate scanning techniques, such as magnetic resonance imaging (MRI), for detailed cortical mapping, optimized electrode design based on the cortical mapping, and computer aided manufacturing (CAM) to customize electrode fabrication. This synergisticAtty. Ref. No. 0073605-001041 approach enables the creation of electrodes tailored to the unique gyral patterns of individual patients, thereby enhancing the precision of neuromodulation therapies and neuroprosthetic applications.

[0008] Particularly, we have found that honeycomb-inspired printable gel electrodes may leverage a bioinspired architecture to achieve mechanical properties that closely match those of brain tissue. The use of soft hydrogels within the honeycomb structure not only ensures exceptional conformability to the complex topography of the cortex but also maintains long-term durability and cost-effectiveness. This design addresses the critical need for high-fidelity electrophysiological recordings while minimizing the risk of inflammatory responses and tissue deformation post-implantation.

[0009] Our approach aims to revolutionize the treatment landscape for individuals suffering from neurological disorders, providing them with improved therapeutic options and restoring functional mobility through direct communication between the brain and external devices.

[0010] In an exemplary embodiment, a method of manufacturing a bioelectrode comprises obtaining a three-dimensional scan of at least a portion of a brain; identifying a target region of the brain; designing a bioelectrode model configured to fit the target region; and printing the bioelectrode based on the bioelectrode model.

[0011] In some embodiments, obtaining the three-dimensional scan comprises scanning the brain with a magnetic resonance imaging scanner.

[0012] In some embodiments, the method further comprises generating a three-dimensional model of the brain using scan data of the three-dimensional scan.

[0013] In some embodiments, identifying the target region of the brain comprises analyzing the three-dimensional model of the brain.Atty. Ref. No. 0073605-001041

[0014] In some embodiments, the bioelectrode model is designed to fit the target region of the three-dimensional model of the brain.

[0015] In some embodiments, the bioelectrode model is designed using an iterative process to ensure placement and shape of the bioelectrode model achieve sufficient conformal contact with the target region of the brain surface without gaps or misalignment.

[0016] In some embodiments, the bioelectrode is printed using a direct ink writing printing device.

[0017] In an exemplary embodiment, a bioelectrode is manufactured from the method described above.

[0018] In some embodiments, the bioelectrode comprises a top layer, a bottom layer, and an electrode layer positioned between the top layer and the bottom layer such that the top layer and bottom layer encapsulate the electrode layer.

[0019] In some embodiments, the bottom layer comprises a printed honeycomb pattern.

[0020] In some embodiments, the electrode layer comprises a plurality of electrode probe strands configured to match the honeycomb pattern of the bottom layer.

[0021] In some embodiments, the top layer comprises a plurality of strands configured to match the electrode probe strands of the electrode layer and the honeycomb pattern of the bottom layer.

[0022] In some embodiments, the top layer and bottom layer are printed using a polydimethylsiloxane ink.

[0023] In some embodiments, the electrode layer is printed using a polymer hydrogel ink.

[0024] In some embodiments, the hydrogel ink comprises poly(3,4-ethylenedioxythiophene) polystyrene sulfonate and polyurethane.

[0025] In some embodiments, the bioelectrode has a Young’s modulus between 0.1 and 10 kPa.Atty. Ref. No. 0073605-001041

[0026] In some embodiments, the bioelectrode is configured to be implanted onto a brain.

[0027] In some embodiments, the bioelectrode is operatively connected to an input / output device such that the bioelectrode transmits collected brain activity data to the input / output device.

[0028] In some embodiments, the bioelectrode is operatively connected to an input / output device such that the input / output data transmits signals to the bioelectrode.

[0029] In an exemplary embodiment, a system for manufacturing a bioelectrode comprises a scanning device configured to obtain a three-dimensional scan of at least a portion of a brain; a computer device configured to receive the three-dimensional scan from the scanning device and design a bioelectrode model configured to fit a target region of the brain; and a printing device configured to receive bioelectrode model from the computer device and print the bioelectrode based on the bioelectrode model.

[0030] In some embodiments, the scanning device is a magnetic resonance imaging scanner.

[0031] In some embodiments, the printing device is a direct ink writing printer.

[0032] Other details, objects, and advantages will become apparent as the following description of certain exemplary embodiments thereof proceeds.BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The above and other objects, aspects, features, advantages, and possible applications of embodiments of the present innovation will be more apparent from the following more particular description thereof, presented in conjunction with the following drawings. Like reference numbers used in the drawings may identify like components.

[0034] FIG. 1 is an illustration of an exemplary embodiment of an implanted bioelectrode conformed to a patient’s cortical surface.Atty. Ref. No. 0073605-001041

[0035] FIG. 2 is an illustration of ECoG recording with a personalized bioelectrode from somatosensory and motor cortex as designated target regions.

[0036] FIG. 3 is a flow chart demonstrating an exemplary method of manufacturing a bioelectrode.

[0037] FIG. 4 is an illustration of three anatomical planes and demonstration of MRI structural images of sagittal plane, transverse plane, and frontal plane.

[0038] FIG. 5 shows MRI structural images of the three planes - transverse (top left), sagittal(top right), and frontal (bottom left), and reconstructed 3D model from the MRI structural images (bottom right) in 3D Slicer.

[0039] FIG. 6 is a demonstration of 3D models, side view (left) and top view (right).

[0040] FIG. 7 is an illustration of the cortical surface and its zoom-in cross-sectional view of individuals (right-handed and left-handed).

[0041] FIG. 8 is an illustration showing the differences of individuals’ cortical surface and its zoom-in cross-sectional view of gyral patterns (left-handed and ambidextrous).

[0042] FIG. 9 is a block diagram illustrating an exemplary system for manufacturing a bioelectrode.

[0043] FIG. 10 is an illustration of an exemplary bioelectrode.

[0044] FIG. 11 is an illustration of an exemplary bioelectrode with three layers (bottom, electrode, and top) and three parts (interface, interconnect, and VO part).

[0045] FIG. 12A is a block diagram illustrating an exemplary embodiment of a system implementing the bioelectrode.

[0046] FIG. 12B is a block diagram illustrating an exemplary embodiment of a system implementing a plurality of bioelectrodes.Atty. Ref. No. 0073605-001041

[0047] FIG. 13 is a graph showing a comparison of bending stiffness of the described bioelectrode, brain tissue, and other control devices, quadrilateral control, PDMS control, SBS control, and Metal control.

[0048] FIG. 14 is an illustration showing geometrical of the bioelectrode (top) and control device (bottom) for mechanics evaluation simulations.

[0049] FIG. 15 is a schematic illustration showing a conformability simulation setup. The described bioelectrode suspends on top of a part of the MRI-reconstructed 3D brain model’s tissue and drops down to conform to the brain surface out of gravity.

[0050] FIG. 16 shows the final configurations of devices attached to the brain tissue after conformability simulation. A color map shows the distance from the devices to the brain surface for the described bioelectrode, PDMS control, and SBS control.

[0051] FIG. 17 is a probability histogram showing the distance distribution for the described bioelectrode, PDMS control, and SBS control.

[0052] FIG. 18 shows the deformed brain tissue after conformability simulation. A color map shows the logarithm strain distribution on the brain tissue for the described bioelectrode, PDMS control, and SBS control.

[0053] FIG. 19 is a probability histogram showing the logarithm strain distribution for the described bioelectrode, PDMS control, and SBS control.

[0054] FIG. 20 is a schematic illustration is a bioelectrode on the brain surface.

[0055] FIG. 21 shows connectivity simulation results.

[0056] FIG. 22 is a graph showing connectivity rate of different devices, including the described bioelectrode, PDMS control, SBS control, PDMS matrix, and SBS matrix.Atty. Ref. No. 0073605-001041

[0057] FIG. 23 is an illustration showing patient-specific design on the bioelectrode. Four locations were selected for electrodes.

[0058] FIG. 24 is an illustration showing patient-specific design on the bioelectrode. All electrodes are connected to the electrochemical signal on the cortical surface of the brain tissue.

[0059] FIG. 25 shows in silico modeling of connectivity test on PDMS control devices. Four of the same locations were selected for electrodes as the bioelectrode. Only two out of four electrodes successfully connected to the electrical signal.

[0060] FIG. 26 shows in silico modeling of connectivity test on SBS control devices. Four of the same locations were selected for electrodes as the bioelectrode. Only two out of four electrodes successfully connected to the electrical signal.

[0061] FIG. 27 shows in silico modeling of connectivity test on PDMS matrix devices.Conventional matrix-aligned electrodes were used. Only a few electrodes are connected to the electrical signal.

[0062] FIG. 28 shows in silico modeling of connectivity test on SBS matrix devices.Conventional matrix-aligned electrodes were used. Only a few electrodes are connected to the electrical signal.

[0063] FIG. 29 is an illustration of brain segmentation as anatomical reference points for the SM region.

[0064] FIG. 30 shows illustrations of personalized designs of bioelectrodes based on patients’ SM regions. (Handedness; A = ambidextrous, L = left-handed, R = right-handed).

[0065] FIG. 31 shows illustrations of printing pathways of bioelectrodes for interfacing with ECoG recording.Atty. Ref. No. 0073605-001041

[0066] FIG. 32 shows photographs of a printed bottom layer on a glass substrate for an individual, a photograph of printing the top layer of the device, a photograph of a personalized bioelectrode printed on a glass substrate, and five-patient-specific bioelectrodes conformed to their corresponding individual patient’s right hemisphere. Scale bars are 1 cm.

[0067] FIG. 33 shows images of slicing the brain’s model in Creality Slicer, a 3D model of the brain without (left) and with (right) support layer, for 3D printing as a demonstration

[0068] FIG. 34 is an illustration of the 3D printed human brain by FDM 3D printers.

[0069] FIG. 35 is a photograph demonstrating easy handling of a bioelectrode. Scale bar is 1 cm.

[0070] FIG. 36 is a photograph illustrating the designs and the sizes of five bioelectrodes tailored for five different patients. Scale bar is 2 cm.

[0071] FIG. 37 shows photographs of a bioelectrode without (top) and with (bottom) stretching position. Scale bars are 1 cm.

[0072] FIG. 38 demonstrates different sizes of personalized bioelectrodes on their corresponding patients’ 3D-printed brain models. Scale bar is 3 cm.

[0073] FIG. 39 shows graphs demonstrating electrochemical impedance spectroscopy (EIS) of the described bioelectrode, Platinum (Pt) electrode, and Stainless Steel (SS) electrode.

[0074] FIG. 40 shows graphs demonstrating a comparison of impedance among bioelectrode, Pt electrode, and SS electrode.

[0075] FIG. 41 shows graphs demonstrating a comparison of phase among bioelectrode, Pt electrode, and SS electrode.

[0076] FIG. 42 is a graph showing impedance (kQ) at 100 Hz.

[0077] FIG. 43 is a graph showing phase (°) (d) at 100 Hz.

[0078] FIG. 44 is a graph showing impedance (kQ) at 1000 Hz.Atty. Ref. No. 0073605-001041

[0079] FIG. 45 is a graph showing phase (°) (d) at 1000 Hz. For FIGS. 42-45, the 25th and 75th percentiles are displayed by the box limits, center lines indicate the mean, and whiskers exhibit the 5th and 95th percentiles. Data points (mean and standard errors) are shown for n = 4 independent samples.

[0080] FIG. 46 is a graph showing current density (mA / cm2) vs potential (V) plots for the described bioelectrode, Pt, and SS.

[0081] FIG. 47 shows graphs demonstrating a comparison of current density among bioelectrode, Pt electrode, and SS electrode

[0082] FIG. 48 shows graphs demonstrating charge storage capacity (CSC) and charge injection capacity (CIC) for the described bioelectrode, Pt, and SS. In bar plots, values represent the mean and standard errors for n = 4 independent samples.

[0083] FIG. 49 shows graphs demonstrating impedance of a bioelectrode on different days in a PBS bath at 50°C. Measurement of impedance at 100 Hz (left) and at 1 K Hz (right). Values represent the mean and the standard deviation (n=3; independent samples). Statistical significance and P values are determined by a one-way ANOVA test; NS, not significant.

[0084] FIG. 50 is a schematic illustration of a rat and its somatosensory and motor (SM) cortex.

[0085] FIG. 51 is a schematic illustration of the implantation of the bioelectrode on the SM cortex of a rat’s brain.

[0086] FIG. 52 is a schematic illustration of a bioelectrode.

[0087] FIG. 53 is a schematic illustration of three layers of a bioelectrode for both male (top) and female (bottom).

[0088] FIG. 54 is a schematic illustration of 3D printing pathways of three layers of a bioelectrode for both male (top) and female (bottom).Atty. Ref. No. 0073605-001041

[0089] FIG. 55 shows photographs of 3D printed bioelectrodes and a penny. Scale bars are 1 cm.

[0090] FIG. 56 is a plot showing filtered signal (0.1 - 200 Hz) of a male rate.

[0091] FIG. 57 shows graphs demonstrating time-frequency analysis of a male rat.

[0092] FIG. 58 is a plot showing filtered signal (0.1 - 200 Hz) of a female rat.

[0093] FIG. 59 shows graphs demonstrating time-frequency analysis of a female rat.

[0094] FIG. 60 is a schematic illustration of three layers of conventional electrodes (top) and its 3D printing pathways (bottom).

[0095] FIG. 61 shows graphs demonstrating ECoG signals recorded from the bioelectrode and conventional electrode.

[0096] FIG. 62 shows graphs demonstrating whisker-evoked potential from both the bioelectrode and conventional electrodes. Stimulation duration was 1 s, and resting duration was 5 s. SNR for bioelectrodes: Chi : 29.06 dB, Ch2: 28.50 dB, Ch3: 30.07 dB, Ch4: 30.47 dB, Ch5: 30.45 dB, and Ch6: 29.05 dB; SNR for conventional electrodes: Chi : 17.45 dB, Ch2: 17.41 dB, Ch3: 22.30 dB, Ch4: 22.79 dB, Ch5: 17.88 dB, and Ch6:17.44 dB.

[0097] FIG. 63 shows signal to Noise (SNR) Ratio of whisker-evoked potential for the bioelectrode.

[0098] FIG. 64 shows SNR Ratio of whisker-evoked potential for convention electrodes.

[0099] FIG. 65 is a photograph showing a bioelectrode placed on the right hemisphere of a rat brain (left) 2% w / v agarose in a tube and the bioelectrode attached to the brain was immersed in that tube, then the tube was filled with saline (right).

[0100] FIG. 66 shows the results of a phantom test of the bioelectrode. T2-weighted images of the brain with an electrode showing no significant artifact.Atty. Ref. No. 0073605-001041

[0101] FIG. 67 shows structural and functional images of a male rat brain without a bioelectrode (before surgery) (top) and with a bioelectrode (after surgery) (bottom) on the surface of the left SM cortex. The SM cortical regions under the bioelectrode were manually selected in a mirrored configuration relative to the right hemisphere in structural images, which were marked in the second row of panels (top) and (bottom).

[0102] FIG. 68 shows structural and functional images of a female rat brain (top) without the bioelectrode (before surgery) and (bottom) with the bioelectrode (after surgery) on the surface of the left SM cortex. The SM cortical regions under the electrode were manually selected in a mirrored configuration relative to the right hemisphere in structural images, which were marked as in the second row of panels (top) and (bottom).

[0103] FIG. 69 shows graphs demonstrating signal intensity of voxels in left SM cortex and right SM cortex without (top) and with the bioelectrode (bottom).

[0104] FIG. 70 shows graphs demonstrating signal intensity of voxels in left SM cortex and right SM cortex without electrode (left) and with electrode (right).

[0105] FIG. 71 shows representative histological images of a rat’s brain 4 weeks postimplantation. Hematoxylin and Eosin, Masson’s Tri chrome, iba-1, and DAPI staining, and zoom-in view of the implanted and non-implanted regions, The boxes refer to non-implanted and implanted regions.

[0106] FIG. 72 shows illustrations of histological images of rat’s cortical surface for 8 weeks, (top left) Hematoxylin and Eosin, (top right) Masson’s Trichrome, (bottom left) iba-1 and DAPI labeled, (bottom right) Zoom-in view of the implanted and non-implanted regions. Squares refer to non-implant and implant regions.

[0107] FIG. 73 is a table providing details of tested patients.Atty. Ref. No. 0073605-001041

[0108] FIG. 74A-C is a table providing sizes of 3D reconstructed brain models of the test patients.DETAILED DESCRIPTION

[0109] The following description is of exemplary embodiments and methods of use that are presently contemplated for carrying out the present invention. This description is not to be taken in a limiting sense, but is made merely for the purpose of describing the general principles and features of various aspects of the present invention. The scope of the present invention is not limited by this description.

[0110] Embodiments generally relate to a printable, tissue-like bioelectrode for patientspecific neural interface, and to methods of producing and using thereof. FIG. 1 shows an exemplary bioelectrode 100 implanted on a patient’s brain 200.

[0111] The bioelectrode is specifically designed to match the shape and cortical contours of the patient’s brain 200. As seen in FIG. 2, a brain includes ridges (gyri) and grooves (sulci) that together form gyral patterns, which are unique to each individual patient. Individual variability in gyral patterns, possibly shaped by factors such as sex, age, weight, height, and / or handedness of the patient.

[0112] Conventional neural interfaces often rely on rigid electrodes adhering to universal designs. However, such designs fail to adapt to individualized brain shapes and gyral patterns, which inevitably leads to poor electrode-tissue contact and signal degradation due to scar formation. Accordingly, providing a bioelectrode designed to match gyral patterns of a specific patient, precise neuromodulation may be achieved, adverse tissue responses may be mitigated, and therapeutic efficacy and safety may be optimized.Atty. Ref. No. 0073605-001041

[0113] As used herein, the term “patient” may refer to any biological system with which a bioelectrode may be used, including without limitation, humans and other animals (e.g., dogs, cats, horses, cows, cattle, etc.).

[0114] FIG. 3 shows an exemplary method 300 for producing a bioelectrode for patientspecific neural interface.

[0115] In step 302, a three-dimensional (3D) scan of at least a portion of a patient’s brain is obtained. The 3D scan includes scan data on at least a portion of the shape and / or topography of the patient’s cerebral cortex, or the outer layer, of the brain. The scan data may therefore enable identification and mapping of the functional areas of the cerebral cortex, such as motor areas (e.g., primary motor cortex, premotor cortex, or other areas that control and execute voluntary movements), sensory areas (e.g., primary somatosensory cortex, primary visual cortex, primary auditory cortex, primary olfactory cortex, primary gustatory cortex, or other areas that process sensory information), or association areas (e.g., parietal association areas, temporal association areas, frontal association areas, occipital association areas, or other areas that integrate sensory information and support higher cognitive function).

[0116] The scan data may be obtained by scanning the brain with a scanning device or technique, such as magnetic resonance imaging (MRI), computed tomography (CT), or other suitable brain scanning device. In one particular embodiment, the scan data may be obtained by scanning the brain with an MRI scanner. In some embodiments, such as in cases that require more precise planning, MRI and CT scans may be combined to obtain more detailed, patientspecific data. Other scanning techniques, such as positron emission tomography (PET), single photon emission computed tomography (SPECT), and / or magnetoencephalography (MEG) mayAtty. Ref. No. 0073605-001041 also be used in combination with MRI to localize functional or metabolic target regions, when necessary.

[0117] In some embodiments, the scan data may be used to generate a 3D model of at least a portion of the patient’s brain. The 3D model may allow a user to visualize the shape and / or topography of the patient’s cerebral cortex. FIGS. 4-8 show exemplary scan data and 3D models generated from scan data obtained via MRI. While 3D models are shown in the figures as 2D drawings, in practice a 3D model will necessarily be three dimensional and can be turned and seen from all sides by a user. Generating a 3D model may include developing a mathematical representation of the three-dimensional surface of the patient’s brain via software. The 3D model represents the brain using a collection of points in 3D space, connected by various geometric objects such as triangles, lines, curved surfaces, etc.

[0118] In step 304, a target region of the patient’s brain is identified. The target region is the portion of the brain on which the bioelectrode may be positioned to study, monitor, and / or treat various neurological or psychological conditions.

[0119] In some embodiments, the target region may be identified by observing symptoms and / or behaviors of the patient and by using known information of particular regions of the brain that may affect or cause such symptom s / behaviors. For example, with regard to a patient experiencing paralysis of one or more limbs, the motor cortex or specific areas of the motor cortex may be identified as a target region. As another example, with regard to a patient experiencing eyesight impairment, the visual cortex or specific areas of the visual cortex may be identified as a target region. Accordingly, in some embodiments, the target region may be identified either before or after a 3D scan of the patient’s brain is obtained. In any case, the 3D scan and the scan data may encompass the identified target region.Atty. Ref. No. 0073605-001041

[0120] In some embodiments, the target region may be identified by analyzing the scan data and / or 3D model obtained via the 3D scan and by determining particular regions of the brain to be studied, monitored, and / or treated. Accordingly, the 3D scan of the patient’s brain may encompass the target region such that it may be identified after the 3D scan is obtained.

[0121] In step 306, a bioelectrode configured to fit the target region is designed.Designing the bioelectrode to fit the target region may include producing a virtual bioelectrode model that may be utilized together with the 3D scan (e.g., the scan data and / or the 3D model) to determine (i) a specific position within the target region at which the bioelectrode should be placed, and (ii) a specific design of the bioelectrode such that the bioelectrode may match the shape, topography, and / or contour of the position within the target region. As the shape and cortical contours of a patient’s brain are unique to each patient, as demonstrated in FIGS. 7 and 8, this step may advantageously enable precise positioning of the bioelectrode at the target region, and may ensure maximum electrode contact with the brain.

[0122] The bioelectrode model may be designed to ensure that its placement and shape result in conformal contact with the cortical surface of the patient’s brain. In some embodiments, the design process includes using patient-specific 3D brain models to identify anatomical landmarks and to iteratively adjust the bioelectrode pathways such that an electrode layer of a bioelectrode fully conforms to the targeted cortical region without gaps. This ensures stable physical contact between the bioelectrode and the brain surface, which may improve recording and stimulation consistency

[0123] An iterative process may be employed to design the bioelectrode model such that a particular placement of the bioelectrode within the target region and a particular shape of the bioelectrode may be determined. The iterative process may begin with an initial attempt to placeAtty. Ref. No. 0073605-001041 and shape the virtual bioelectrode model within the target region of the 3D scan. After positioning, tests may be conducted, such as via Finite Element Analysis (FEA), to collect data and assess the initial attempt to position and shape the virtual bioelectrode. For example, the collected data may be analyzed to determine whether the virtual bioelectrode model achieves sufficient conformal contact with the cortical surface of the target region, ensuring there are no gaps or misalignments. Based on this analysis, the placement and / or shape of the electrode may be adjusted to a new placement and / or shape, and testing may be repeated to determine whether full conformal contact has been achieved. The conformability can be visually assessed within a 3D view of the brain and bioelectrode models, and users can observe that there are no gaps or misalignments between the models. As the brain and bioelectrode models are fully rendered 3D models, the interface fit between the models is clearly visible, helping to confirm structural alignment. This process of testing, analyzing, and adjusting may continue iteratively until the bioelectrode design achieves the desired conformal contact with the cortical surface.

[0124] The bioelectrode model may be designed using digital design software, such as a computer-aided design (CAD design) software. Developing the bioelectrode may therefore include developing a digital file with the designed bioelectrode produced using such software.

[0125] In some embodiments, designing the bioelectrode model may be done manually by a user via digital design software.

[0126] In some embodiments, designing the bioelectrode model may be done automatically, such that a trained neural network, machine learning, deep learning, etc. may utilize the 3D scan to determine a design of the bioelectrode within the target region, such as via an iterative process.Atty. Ref. No. 0073605-001041

[0127] In step 308, the bioelectrode is manufactured. In particular, the designed bioelectrode may be transmitted to a 3D manufacturing device, such as a computer aided manufacturing (CAM) device, so that a physical bioelectrode may be produced in accordance with the designed bioelectrode. In some embodiments, the manufacturing device may be a 3D printing device, such as direct ink writing (DIW) printing device capable of printing polymeric or hydrogel-based ink. Other suitable types of additive manufacturing devices can also be utilized to form the bioelectrode.

[0128] Once the bioelectrode is formed, the manufactured bioelectrode can be implanted onto the patient's brain at the target region of the patient's brain (step 310). The bioelectrode may then be formed to study, monitor, treat, etc. various neurological or psychological conditions.

[0129] For example, in step 312, the bioelectrode may be used to collect brain activity data in the target region of the patient's brain. Such collected data can be sent to a computer device that can be communicatively connectable to the bioelectrode for evaluation of the collected data. This type of data that is sent to a computer device can be sensor data that can be sent from the implanted bioelectrode to the computer device when the data is sensed or in periodic intervals after the data is sensed and recorded. The computer device that receives the sensor data can be any suitable device (e.g. a tablet, a smart phone, a specialized bioelectrode data collection device, a laptop computer, etc.). In some embodiments, the computer device is or is part of a brain-computer interface (BCI) system configured to decode the data for control of external devices.

[0130] As another example, in step 314, the bioelectrode may be used to neuromodulate (e g., stimulate) the target region of the patient's brain. Such neuromodulation can be achieved by delivering electrical signals or other forms of stimulation through the bioelectrode to influenceAtty. Ref. No. 0073605-001041 neuronal activity in the target region. The bioelectrode can be communicatively connected to a computer device that controls the parameters of the neuromodulation, such as the frequency, duration, and intensity of the stimulation. This connection may allow for real-time adjustments based on feedback from the patient's brain activity or other physiological signals. The computer device that manages the neuromodulation can be any suitable device (e.g., a tablet, a smart phone, a specialized neuromodulation control device, a laptop computer, etc.), and may be the same device described above with respect to step 310.

[0131] An implanted bioelectrode may be used in various applications, such as to study, monitor, and / or treat various neurological or psychological conditions.

[0132] In one application, the bioelectrode may be used in a closed-loop system. For example, the bioelectrode can be used in a closed-loop system for real-time recording and responsive stimulation of neural activity. This embodiment allows for continuous monitoring of brain signals, enabling the system to adaptively adjust stimulation parameters based on the detected neural responses. Such dynamic interactions may enhance the precision of treatments, and may lead to improved outcomes in therapeutic contexts.

[0133] In another application, the bioelectrode may be used in BCI applications. For example, the bioelectrode can be used as part of BCI system to decode neural signals for control of external devices. By capturing and processing electrical activity from the brain, the bioelectrode enables the interpretation of user intent, which can then be translated into commands for various external devices. This functionality allows for enhanced interaction with technology, including assistive devices, computer applications, and / or robotic systems.Atty. Ref. No. 0073605-001041

[0134] In another application, the bioelectrode may be used for cognitive behavioral therapy. For example, the bioelectrode can be used to modulate regions of the brain implicated in cognitive, emotional, or behavioral regulation.

[0135] In another application, the bioelectrode may be used for pain management. For example, the bioelectrode can be used to stimulate neural structures involved in pain perception and modulation for therapeutic pain management.

[0136] In another application, the bioelectrode may be used for neurorehabilitation. For example, the bioelectrode can be used to promote functional recovery by stimulating neural plasticity in patients with neurological injuries such as stroke, amyotrophic lateral sclerosis (ALS), spinal cord injury (SCI), or traumatic brain injury. The stimulation can help re-establish neural connections and enhance motor and cognitive functions. Additionally, the bioelectrode's ability to adapt stimulation based on patient progress can optimize rehabilitation protocols.

[0137] In another application, the bioelectrode may be used for sleep modulation. For example, the bioelectrode can be used to monitor and modulate brain activity associated with sleep cycles and sleep disorders, such as insomnia or narcolepsy. The bioelectrode can help regulate sleep architecture and promote restorative sleep phases.

[0138] In another application, the bioelectrode may be used for memory enhancement or modulation. For example, the bioelectrode can be used to record and stimulate brain regions involved in memory formation and retrieval.

[0139] In another application, the bioelectrode may be used in research applications, such as research applications beyond humans. For example, the bioelectrode can be used in preclinical research models to investigate neurological and psychiatric conditions.Atty. Ref. No. 0073605-001041

[0140] FIG. 9 shows a schematic of an exemplary system 400 for producing a bioelectrode for patient-specific neural interface. The system 400 includes a scanning device 402 configured to obtain a 3D scan of at least a portion of the patient’s brain, as described above. A computer device 404 may be operatively connected to the scanning device 402 such that the computer device 404 is capable of receiving the 3D scan (e.g., scan data) from the scanning device 402.

[0141] In some embodiments, the scanning device 402 may be hardwire connected to the computer device 404, or the scanning device 402 may be communicatively connected to the computer device 404 via a network connection or wireless connection (e.g., internet connection, wide area network connection, near field communication connection, Bluetooth connection, etc.).

[0142] The computer device 404 is capable of forming a 3D model based on the scan data received from the scanning device 402. The received scan data and / or the 3D model may then be stored on the computer device 404, such as stored in a non-transitory memory (Mem.) of the computer device 404 and provided to a processor (Proc.) of the computer device 404. The computer device 404 is also capable of designing a bioelectrode and producing a digital file with the designed bioelectrode, as described above.

[0143] A manufacturing device 406, such as a computer aided manufacturing / printing device, may be operatively connected to the computer device 404 such that the manufacturing device 406 is capable of receiving the designed bioelectrode from the computer device 404.

[0144] In some embodiments, the manufacturing device 406 may be hardwire connected to the computer device 404, or the manufacturing device 406 may be communicatively connected to the computer device 404 via a network connection or wireless connection (e g.,Atty. Ref. No. 0073605-001041 internet connection, wide area network connection, near field communication connection, Bluetooth connection, etc ).

[0145] In some implementations, the computer device 404 can be configured as a server or cloud-based service providing device for analysis and storage of the scan data obtained via the scanning device 402. In some embodiments, the computer device 404 may include a display device such that the scan data, 3D model, and / or designed bioelectrode can be communicated to a user via the display device, which can be a tablet, smart phone, laptop computer, personal computer, or other type of terminal device. The display device can be effectuated via an application programming interface and / or use of an application stored on the display device. It is contemplated that the computer device 404 may comprise the display device, or the display device may be a separate device.

[0146] The computer device 404 can include a processor (Proc.) connected to a non- transitory memory (Mem.) and at least one transceiver (Trcvr) for forming communicative connections with one or more other devices. The at least one transceiver (Trcvr) can include a Bluetooth module and / or other type of transceiver unit (Trcvr) such that the scanning device 402 and / or other input devices may transmit data to the computer device 404, and such that the computer device 404 may transmit the designed bioelectrode to the manufacturing device 406.

[0147] The processor (Proc.) can be hardware (e.g., processor, integrated circuit, central processing unit, microprocessor, core processor, computer device, etc.), configured to perform operations by execution of instructions embodied in algorithms, data processing program logic, artificial intelligence programming, automated reasoning programming, etc. that can be defined by code stored in the memory. The processor can facilitate receipt, processing, and / or storage of data from the scanning device 402.Atty. Ref. No. 0073605-001041

[0148] It should be noted that use of processors herein can include hardware, such as for example any one or combination of a Graphics Processing Unit (GPU), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), etc. The processor can include one or more processing or operating modules. A processing or operating module can be a software or firmware operating module configured to implement any of the functions disclosed herein. The processing or operating module can be embodied as software and stored in non-transitory memory; the memory being operatively associated with the processor. A processing module can be embodied as a web application, a desktop application, a console application, etc.

[0149] The memory (Mem.) can be a non-transitory computer readable memory configured to store data. Embodiments of the memory can include a processor module and other circuitry to allow for the transfer of data to and from the memory, which can include to and from other components of a communication system. This transfer can be via hardwired links or wireless transmission communication links. The communication system can include transceivers, which can be used in combination with switches, receivers, transmitters, routers, gateways, waveguides, etc. to facilitate communications between different devices via a communication approach or protocol for controlled and coordinated signal transmission and processing to any other component or combination of components of the communication system. The transmission can be via a communication link, which can be a wireless type of communication connection and / or a wired type of connection.

[0150] The computer or non-transitory machine-readable medium can be configured to store one or more instructions thereon. The instructions can be in the form of algorithms, program logic, etc. that cause the processor to execute any of the functions disclosed herein.Atty. Ref. No. 0073605-001041

[0151] The processor can be in communication with other processors of other devices (e g., a computer system, a laptop computer, a desktop computer, etc.). An exemplary other device can be a Bluetooth enabled device, near field communication device, etc. Any of those other devices can include any of the exemplary processors disclosed herein as well as transceivers or other communication devices / circuitry to facilitate transmission and reception of wireless signals or other type of communicative connections.

[0152] The computer device 404 can also be configured to be connected to other input devices (ID) and output devices (OD). Examples of input devices can include a keyboard, a mouse, or other type of input device. Examples of output devices can include a display, a printer, a speaker, or other type of output device.

[0153] FIG. 10 shows an exemplary bioelectrode 100 for patient-specific neural interface. The bioelectrode 100 may be produced using the method 300 and system 400 described above.

[0154] The bioelectrode 100 has an interface portion 102, an input / output portion 106, and an interconnected portion 104 located between the interface portion 102 and the input / output portion 106. The interface portion 102 is configured to directly interface with the cortical surface of the patient’s brain, such that the interface portion is configured to be in direct contact with the cortical surface of the patient’s brain to receive and / or transmit signals. The input / output portion 106 is configured to connect to an input / output device such that signals received by the bioelectrode 100 may be transmitted to the input / output device and / or signals may be transmitted to the bioelectrode 100 via the input / output device. The interconnected portion 104 is configured to bridge the interface portion 102 and the input / output portion 106.Atty. Ref. No. 0073605-001041

[0155] The bioelectrode 102 includes a top layer 110, a bottom layer 114, and an electrode layer 112 positioned between the top layer 110 and the bottom layer 114.

[0156] The electrode layer 112 is configured to receive signals from a brain and / or transmit signals to the brain. The electrode layer 112 may include a hydrogel-based electrode, and may be formed from a bi-continuous conducting polymer hydrogel. In some embodiments, the hydrogel may include poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) combined with polyurethane (PU) or other suitable polymeric materials. The electrode layer 112 may further comprise one or more conductive materials, such as polypyrrole (PPy), polyaniline (PANI), or derivatives thereof. Conductive nanomaterials including carbon nanotubes, graphene, MXenes, or metallic nanowires may be incorporated to enhance electrical conductivity, mechanical properties, or tissue interfacing. In some embodiments, biocompatible metal nanomesh structures, such as gold or platinum nanogrids, may also be used as a conductive material, optionally embedded within or combined with a hydrogel matrix.

[0157] Additionally, the electrode layer 112 may include conductive polymers or composites embedded within or combined with hydrogel matrices such as gelatin methacrylate (GelMA), polyvinyl alcohol (PVA), or other biocompatible hydrogels to provide mechanical support and tissue-like properties. The hydrogel may be printed via a 3D printing device, such as a direct ink writing (D1W) printer.

[0158] The electrode layer 112 similarly includes interface, interconnected, and input / output portions. In some embodiments, the interface portion of the electrode layer 112 may include a plurality of electrode probe strands, or an array of electrode probe strands. The strands may be configured to spread across and interface with the cortical surface such that cortical surface coverage is increased.Atty. Ref. No. 0073605-001041

[0159] The top layer 110 is configured to fully or partially encapsulate the electrode layer 112. For example, in some embodiments, the top layer 110 may fully encapsulate the electrode layer 112 such that no parts of the electrode layer 112 are exposed. In some embodiments, the top layer 110 may partially encapsulate the electrode layer 112 such that one or more portions of the electrode layer 112 are exposed. In such embodiments, the exposed parts of the electrode layer 112 should remain uncovered by the top layer 1 10 to ensure proper signal acquisition.

[0160] The bottom layer 114 is configured to fully encapsulate the electrode layer 112, such that no parts of the electrode layer 112 are exposed via the bottom layer 114.

[0161] The top layer 110 and bottom layer 114 are configured to encapsulate the electrode layer 112. The top layer 110 and bottom layer 114 may be formed from flexible and / or stretchable polymeric materials. In some embodiments, the substrate may be a hydrophilic polymeric material. Suitable materials for the top and bottom layers may include polymers such as polydimethylsiloxane (PDMS), polyethylene glycol (PEG), PEG-modified PDMS (PEG- PDMS), polyimide, parylene-C, polyurethane (PU), silicone elastomers, fluorinated ethylene propylene (FEP), cyclic olefin copolymer (COC), thermoplastic elastomers such as styrene- ethylene-butylene-styrene (SEBS), hydrogels such as agarose or gelatin methacrylate (GelMA), as well as commercially available medical-grade polymers or elastomers including, but not limited to, C5, C40, D3, D640, and other related materials in the C and D series. These materials provide desirable mechanical flexibility, biocompatibility, and durability suitable for neural implant applications. The polymeric materials may be printed or formed via various manufacturing techniques, including 3D printing devices such as direct ink writing (DIW) printers.Atty. Ref. No. 0073605-001041

[0162] The top layer 110 and bottom layer 114 may similarly include interface, interconnected, and input / output portions. The interconnected and input / output portions of both the top layer 110 and the bottom layer 114 may be continuous, filmdike structures to ensure encapsulation of the electrode layer 112.

[0163] The interface portion of the bottom layer 114 may include a honeycomb architecture, or multiple hexagonal lattice units. It has been found that the honeycomb architecture may advantageously allow for maximized cortical surface coverage while maintaining isotropic elasticity through the six-fold rotational symmetry of the lattice units.

[0164] The interface portion of the top layer 110 may include a plurality of strands, or an array of strands, to match and fully or partially encapsulate the electrode probe strands of the electrode layer 112. The configurations of the strands of the top layer 110 and the electrode probe strands of the electrode layer 112 advantageously overlay the honeycomb structure of the bottom layer 116.

[0165] The bioelectrode 100 may therefore result in a porous architecture that may enhance mechanical strength, flexibility, and conformability to uneven surfaces of the brain. Importantly, it has been found that fluids in the cranial space are essential for brain function, so the porous design of the bioelectrode 100 may advantageously minimize disruptions in native brain tissue and allow for unrestricted fluid exchange post-implantation.

[0166] The bioelectrode 100 has a bending stiffness that matches the bending stiffness of brain tissue, which has a Young’s modulus between 0.1 and 10 kPa. The bioelectrode 100 may therefore eliminate mechanical mismatch with the brain tissue, thus mitigating adverse tissue response once implanted.Atty. Ref. No. 0073605-001041

[0167] The bioelectrode 100 is flexible, such that the bioelectrode 100 may be configured accommodate any contour and properly function while undergoing stresses and / or deformations.

[0168] In some embodiments, a plurality of bioelectrodes 100 and / or an array of bioelectrodes 100 may be implanted on the brain. In embodiments including a plurality of bioelectrodes 100, each bioelectrode 100 may operate and collect data independently with no interference between their input signals. Similarly, in embodiments including a plurality of bioelectrodes 100, each bioelectrode 100 may operate and transmit signals to the brain independently with no interference between their output signals

[0169] As described above, the bioelectrode 100 may be configured to receive signals and / or stimulate the brain. Referring to FIGS. 12A and 12B, the bioelectrode 100 may be hardwire connected to an input / output device 500. The input / output device 500 may be configured to receive signals from the bioelectrode 100 for storage and analysis of data. The input / output device 500 may further be configured to transmit signals to the bioelectrode 100, such as for neuromodulation.

[0170] In some implementations, the input / output device 500 can be configured as a server or cloud-based service providing device for analysis and storage of the signals / data obtained via the bioelectrode 100, which can be communicated to a user via display device such as a tablet, smart phone, laptop computer, personal computer, or other type of terminal device. The display device can be effectuated via an application programming interface (API) and / or use of an application stored on the display device. It is contemplated that the input / output device 500 may comprise the display device, or the display device may be a separate device.

[0171] Signals / data obtained via the bioelectrode 100 may alternatively or subsequently be sent to a central computer device 600 (e.g. server, an operator workstation, etc.) that can beAtty. Ref. No. 0073605-001041 connected to the input / output device 500 (e.g. via a network connection and application programming interface (API) the central computer device may have with the input / output device 500 running the application, etc.). The forwarding of such data can be provided via a communication connection the bioelectrode 100 directly has with an input / output device 500 such that data is sent to the central computer device 600 via the input / output device 500.

[0172] The input / output device 500 and / or the central computer device 600 can be a computer device that can include a processor (Proc.) connected to a non-transitory memory (Mem.) and at least one transceiver (Trcvr) for forming communicative connections with one or more other devices. The at least one transceiver (Trcvr) can include a Bluetooth module and / or other type of transceiver unit (Trcvr) such as the bioelectrode 100 and / or other input devices ID that may be configured for use with the input / output device 500. For instance, the bioelectrode 100 can be communicatively connected to input / output device 500 and / or the central computer device 600 so that information collected by the bioelectrode 100 may be transmitted to the input / output device 500 and / or the central computer device 600 so that data can be stored and analyzed, or displayed using the display device or other type of output device OD.

[0173] The processor can be hardware (e.g., processor, integrated circuit, central processing unit, microprocessor, core processor, computer device, etc.), configured to perform operations by execution of instructions embodied in algorithms, data processing program logic, artificial intelligence programming, automated reasoning programming, etc. that can be defined by code stored in the memory. The processor can facilitate receipt, processing, and / or storage of readings from bioelectrode 100 and / or control transmission of the collected data to the input / output device 500 and / or the central computer device 600.Atty. Ref. No. 0073605-001041

[0174] It should be noted that use of processors herein can include hardware, such as for example any one or combination of a Graphics Processing Unit (GPU), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), etc. The processor can include one or more processing or operating modules. A processing or operating module can be a software or firmware operating module configured to implement any of the functions disclosed herein. The processing or operating module can be embodied as software and stored in non-transitory memory; the memory being operatively associated with the processor. A processing module can be embodied as a web application, a desktop application, a console application, etc.

[0175] The memory (Mem.) can be a non-transitory computer readable memory configured to store data. Embodiments of the memory can include a processor module and other circuitry to allow for the transfer of data to and from the memory, which can include to and from other components of a communication system. This transfer can be via hardwired links or wireless transmission communication links. The communication system can include transceivers, which can be used in combination with switches, receivers, transmitters, routers, gateways, waveguides, etc. to facilitate communications between different devices via a communication approach or protocol for controlled and coordinated signal transmission and processing to any other component or combination of components of the communication system. The transmission can be via a communication link, which can be a wireless type of communication connection and / or a wired type of connection.

[0176] The computer or non-transitory machine-readable medium can be configured to store one or more instructions thereon. The instructions can be in the form of algorithms, program logic, etc. that cause the processor to execute any of the functions disclosed herein.Atty. Ref. No. 0073605-001041

[0177] The processor can be in communication with other processors of other devices (e g., a second external device, a computer system, a BCI system, a laptop computer, a desktop computer, etc.). An exemplary other device can be a Bluetooth enabled device, near field communication device, etc. Any of those other devices can include any of the exemplary processors disclosed herein as well as transceivers or other communication devices / circuitry to facilitate transmission and reception of wireless signals or other types of communication connections.EXAMPLES

[0178] In neuroscience research and clinical applications, ECoG offers a significant advantage by enabling high temporal resolution recording of cortical electrophysiological signals (FIG. 2), providing invaluable insights into cortical dynamics. To design patient-specific neural electrodes for ECoG recordings and ensure maximum electrode contact with the brain based on individual brain size, structure, and gyri patterns, MRI imaging was utilized. By providing a clear delineation of gyri variations from structural images (FIG. 4), MRI imaging enables guided design of personalized neural electrodes.

[0179] To account for cross-individual variability in cortical folding, we reconstructed 3D brain models from MRI data of 21 patients from the Open Access Series of Imaging Studies (OASIS) database using 3D Slicer (FIGS. 5-7) to analyze individual gyral patterns of the brains. These models revealed significant inter-subject differences in brain sizes and gyral complexity (FIGS. 8, 73, 74A-C), highlighting the inadequacy of conventional one-size-fits-all neural implants. By integrating MRI-based surface curvature analysis and region-of-interest (ROI) mapping, we generated patient-specific neural electrode designs tailored to individual cortical geometries.Atty. Ref. No. 0073605-001041

[0180] Inspired by natural honeycomb structures, our bioelectrode (FIG. 10) employs hexagonal lattice units to maximize cortical surface coverage while maintaining isotropic elasticity through its six-fold rotational symmetry. Building on this principle, the bioelectrode incorporates multiple hexagonal lattices to form a porous architecture that enhances mechanical strength, flexibility, and conformability to uneven surfaces (FIG. 1). Recent studies have demonstrated that fluids in the cranial space are essential for brain functions and neurological disorders. Our design minimizes disruption to native brain tissue and allows unrestricted fluid exchange post-implantation, a critical advantage over conventional ECoG electrodes, which often obstruct fluid dynamics. The honeycomb design also enables cost-effective, massive fabrication of personalized electrodes, reducing healthcare costs and broadening accessibility.

[0181] FEA-guided design and mechanics evaluation: The human cerebral cortex exhibits a soft, convoluted structure with a low Young’s modulus of 0.1-10 kPa. To minimize mechanical mismatch and tissue damage, the bioelectrode employs low-stiffness materials such as polydimethylsiloxane (PDMS) and poly (3,4-ethylene di oxy thiophene): polystyrene sulfonate (PEDOTPSS)-based hydrogels. However, experimental quantification of critical metrics, including bending stiffness, cortical contact area, and implantation-induced strain, remains labor- intensive and prone to experimental error. We thus integrated finite element analysis (FEA) to optimize device geometry, enhancing device design efficiency and precision. FEA revealed the bending stiffness of the bioelectrode closely matched brain tissue (FIGS. 13 and 14), outperforming non-porous controls, including PDMS, polystyrene-block-polybutadiene-block- polystyrene(SBS), and metal. The honeycomb architecture reduced the bending stiffness threefold compared to quadrilateral porous designs, given the same material. These results areAtty. Ref. No. 0073605-001041 consistent with previous studies on honeycomb structures, further validating the advantages of this design.

[0182] Simulated gravitational settling of a device-brain assembly, consisting of the device suspended above bottom-fixed brain tissue (FIG. 15), demonstrated the bioelectrode’s superior adaptation to cortical topography. Distance contour maps (FIGS. 16 and 17) showed that the bioelectrode maintained closer contact (average distance: 2.66 mm) compared to PDMS (4.16 mm) and SBS (5.22mm). Strain distribution analysis further confirmed that the bioelectrode induced minimal tissue deformation, contrasting sharply with the rigid control devices (FIGS. 18 and 19). The bioelectrode’s patient-specific electrode placement, guided by gyral patterns, was validated by in silico modeling (FIGS. 20 and 21). Simulating constant electrical potential (brain set to constant potential), only exposed electrodes (not passivated by the encapsulation layers) recorded signals, with the signal connectivity dependent on physical proximity to the cortical surface. The connectivity rate (connected electrodes / total electrodes) quantifies signal recording efficacy. As shown in FIG. 22, the bioelectrode achieved a nearperfect connectivity rate (FIGS. 23 and 24), surpassing the PDMS and SBS controls (FIGS. 25 and 26), and non-personalized probes with matrix-aligned electrodes (FIGS. 27 and 28). The modeling-guided electrode placement of the bioelectrode, combined with the soft mechanics, eliminated signal gaps caused by poor contact in rigid controls.

[0183] Fabrication: After successfully verifying the mechanics superiority of the bioelectrode, five patients were randomly selected from 21 reconstructed 3D brain models to design personalized the bioelectrodes tailored to their individual brain architecture. The pathways and positions of electrodes were first guided by prominent anatomical landmarks, including the longitudinal fissure, central sulcus, and lateral sulcus (FIG. 28), with theAtty. Ref. No. 0073605-001041 sensorimotor (SM) regions designated as ROIs. Based on these anatomical references, five designs were developed for the right hemispheres of the brains (FIGS. 30 and 21), with electrode configurations tailored to the gyri contours obtained from anatomical measurements in 3D Slicer-based brain models. Following the design process, PDMS was used for encapsulation layers (bottom and top), and a soft and stretchable bi-continuous conducting polymer hydrogel consisting of PEDOT:PSS and polyurethane was used for the electrode layer (FIG. 11). The bioelectrode consists of three main parts: the interface (the part that directly interfaces with the cortical surface), the interconnect (the part that bridges interface and VO part), and the VO (input / output for the connection to the recording system). These sandwich-structured devices were fabricated on glass substrates (FIG. 32) using DIW 3D printing technology.

[0184] Upon fabricating the bioelectrodes, we demonstrated the practical application of our approach by processing five reconstructed 3D brain models using Creality Slicer (FIG. 33), followed by importing them into FDM (Fused Deposition Method) 3D printing technology (FIG. 34) for fabrication. The resulting printed brain models were used to showcase how personalized neural implants conform to distinctive brain anatomies, highlighting the devices' conformability to the cortical surface and the precise alignment of electrode positions with individual gyri structures. The personalized bioelectrodes demonstrated precise conformity to the unique shapes and spatial arrangements of the gyri in each individual, as depicted in FIG. 32. In addition, the devices exhibit robustness and ease of handling, as shown in FIG. 35. The variations in device dimensions, reflecting the anatomical differences among patients, are clearly demonstrated in FIG. 36. Furthermore, the bioelectrode shows excellent stretchability (FIG. 37), demonstrating its robustness in dynamic cortical environments. All five different patients' brain models withAtty. Ref. No. 0073605-001041 their personalized devices are exquisitely displayed in FIG. 38, highlighting the precision and adaptability of the bioelectrode designs according to individual brain structures and gyri patterns.

[0185] Electrical characterization: The electrical impedance of biological tissues plays a crucial role in providing information on cellular response, emphasizing the significance of assessing the impedance of neural devices. Electrochemical impedance spectroscopy (EIS) was applied to study the interfacial impedances of the bioelectrode in PBS, mimicking physiologically relevant environments. The impedance characterization of the bioelectrode was compared to control electrodes - platinum (Pt) electrode and stainless steel (SS) electrode. The results demonstrated that the impedance of the bioelectrode was below 10 k'Q for all the tested frequencies from 1 to 100,000 Hz, where the impedance for Pt and SS was up to three or four magnitudes higher than the bioelectrode, illustrated in FIGS. 39 and 40. It also clearly showed that the phase angles for the bioelectrode were close to zero, while phase angles for Pt and SS were much higher than the bioelectrode (FIGS. 39 and 41). The impedance and phase angles of each electrode were also evaluated at frequencies of 100 Hz and 1000 Hz, respectively. The results illustrated that the impedance values of the bioelectrodes were below 10 k'Q, and phase angles were close to zero. In contrast, the impedance and phase angles for the control electrodes were much higher than the bioelectrodes, as depicted in FIGS. 42-45. For further investigation of the electrochemical properties of the bioelectrodes, cyclic voltammetry (CV) was conducted and compared to the control electrodes, as shown in FIGS. 46-48. The charge storage capacity (CSC) and the charge injection capacity (CIC) for the bioelectrode are both superior to the control electrodes (FIG. 48). Moreover, the electrodes were immersed in PBS for 28 days at 50°C to evaluate their stability under accelerated aging conditions. While 37°C typically mimics physiological in vivo temperatures, the elevated temperature of 50°C was used to simulateAtty. Ref. No. 0073605-001041 accelerated aging and degradation characteristics. The results showed that the bioelectrodes demonstrated stable properties for 28 days of incubation at 50°C in PBS (equivalent to 69 days at physiological temperature, FIG. 49).

[0186] In vivo functionality assessment: To validate the functional capacity of the interface of the bioelectrode, the device was implanted in the rat models to demonstrate that the fabricated bioelectrode can conform to the cortical surface of the brain as well as effectively record the ECoG signal from the SM region, which is designated as ROI, of the cortex (FIGS. 50-52). Two rats, one male and one female, were selected for recording purposes, followed by making personalized designs and fabricating the devices based on the brain size and shape of each rat (FIGS. 53-54). With the advancement of 3D printing technology, it is feasible to fabricate the devices at the micro-scale in a programmable manner, illustrated in FIG. 55. To evaluate the functional performance of personalized the bioelectrodes for both male and female rats, electrophysiological signals were recorded from the ROI of both rats. The raw electrophysiology signal underwent notch filtering to remove power supply noise (60 Hz and its harmonics) and band-pass filtering (0.1 - 200 Hz) to extract the local field potential (LFP). The LFP data of the bioelectrode were then assessed in a frequency-time domain for further analysis, which demonstrated high-quality ECoG signals being recorded from both rats, owing to the conformal contact between the tailored devices and individual brains (FIGS. 56-59).

[0187] In addition, to compare ECoG recordings obtained using the bioelectrode and replicative conventional electrode (FIG. 60), both devices were implanted in the ROI of the brain to record electrophysiological signals at the same anesthetic level. It has been reported that variations in anesthetic levels can alter neural activity, potentially confounding electrophysiological recordings. To address this, the anesthetic level was carefully maintainedAtty. Ref. No. 0073605-001041 constant across recordings, ensuring that differences in signal quality were attributable to the devices rather than anesthetic conditions. The results in FIG. 61 demonstrate that the bioelectrode exhibited a higher amplitude compared to the conventional electrode, with its superior performance attributed to its enhanced contact with the cortical surface, facilitating improved signal recording capability. These findings also confirm the greater conformability of the bioelectrode to the cortical surface compared to the conventional electrode. Additionally, whisker stimulation-evoked potential was measured using both the bioelectrode and conventional electrode when air puffs were applied to the contralateral side in rats at the same anesthetized condition for 25-second intervals consecutively (FIG. 62). The six channels of the bioelectrode exhibited a higher signal-to-noise ratio (SNR) than the six channels of the conventional electrode, demonstrating a superior performance in recording evoked potential as well (FIGS. 62-64).

[0188] Multimodal evaluation of morphological integrity and tissue response: To comprehensively evaluate the effects of the bioelectrode on the cortical surface before and after implantation, its MRI compatibility was initially assessed using a phantom test (FIGS. 65-66). Following the confirmation of MRI compatibility, structural and functional MRI (fMRI) scans were collected from rats pre- and post-implantation of the bioelectrode utilizing a 7T scanner, as illustrated in FIGS. 67 and 68. No significant distortion or signal loss was observed surrounding the electrode in either structural or functional MRI images. Furthermore, to validate that the signal intensity was not impacted by the electrode, SM cortical regions under the electrode were manually selected in a mirrored configuration relative to the right hemisphere for all structural images. The signal intensity of voxels within these two regions was plotted for both male and female rats before and after electrode implantation, as shown in FIGS. 69 and 70. The resultsAtty. Ref. No. 0073605-001041 demonstrated that the difference in signal intensity between the left and right hemispheres was comparable across genders and remained consistent before and after the bioelectrode implantation.

[0189] To assess the long-term effects of the bioelectrode implantation on cortical morphology and tissue responses, rat brain tissue from implanted and non-implanted rat brain regions was harvested and evaluated at 4 (FIG. 71) and 8 weeks (FIG. 73) post-surgery. Hematoxylin and Eosin (H&E) staining of sectioned brain slices revealed no significant morphological differences between the implanted and non-implanted regions (FIG. 71). Masson’s tri chrome staining was employed for precise evaluation of fibrotic scar tissue formation and no collagen fiber deposition was observed in the implanted regions, resembling the non-implanted control (FIG. 71). Additionally, brain slices were labeled with iba-1, a microglial marker, to further investigate neuroinflammation and glial scar formation. The fluorescent images (FIG. 71) demonstrated comparable microglial signals for both the bioelectrode-implanted brain and the control brain, where nothing was implanted, indicating no obvious immune response to the implanted bioelectrode. Collectively, these findings demonstrate that the bioelectrode achieves seamless integration with minimal tissue response, preserves cortical structures, and avoids adverse effects, even at 8 weeks post-implantation.[00190J Methods - Materials: For the preparation of the bi-continuous conducting polymer hydrogel material for electrodes, poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) (Agfa Corporation), ethanol (Sigma- Aldrich), dimethyl sulfoxide (DMSO; Sigma-Aldrich), and hydrophilic polyurethane (AdvanSource Biomaterials) were used. For the preparation of the encapsulation layers of the designed devices, PDMS (SYLGARD™ 186, Dow Coming) was used. For device fabrication, 5-mL syringe barrels and 200 pm and 100Atty. Ref. No. 0073605-001041 pm nozzles were used (Nordson EFD). For demonstration purposes, a 3D printer (FDM technology, Creality CR Series) and CR-PLA as a filament (Shenzhen Creality 3D Technology Co., LTAD.) were used for manufacturing human brain models.

[0191] Methods - 3D brain model reconstruction: For patient-specific brain models, all MRI data were downloaded from the Open Access Series of Imaging Studies (OASIS, www.oasis-brains.org) Website. A total of 21 patient data were selected (Detailed Information is given in FIGS. 73 and 74A-C), and 3D brain models were reconstructed using the free and open source software 3D Slicer (Version 5.6.2, www.slicer.org). In 3D Slicer, after brain construction, the ROI SM cortex areas were selected to determine the dimensions for the personalized bioelectrode devices for specific individual patients.

[0192] Methods - Fabrication of 3D printed brain models: For printing the human brain models, high-print quality, non-toxic, and reliable PLA (polylactic acid) filament was used in the FDM 3D printer. After the reconstruction of the 3D model in STL format, the 3D model was imported into the Creality Slicer software (Version 4.8) to slice the model. During the slicing of the model, the layer height was selected to be 0.16 mm, and the infill density was chosen to be 20% with a gyroid pattern. The build plate adhesion type was brim. To give the support structure of the models, a tree structure was selected with 60° support overhang angle everywhere. After that, the model was exported into geode format to load the file in the FDM printer (Creality). The temperature of the printer’s build plate is 60 ° C, and the 0.4 mm diameter nozzle’s temperature is 200° C.

[0193] Methods - Ink preparation: To prepare the encapsulation ink, part A and part B (10: 1 ratio) of PDMS were mixed by a centrifugal mixer (AR-100, Thinky). The mixed solution was then transferred into a 5-mL syringe, followed by a thorough mixer. For conductive ink, 6Atty. Ref. No. 0073605-001041 w / v% PEDOT :PSS was dissolved in a mixture of deionized water and DMSO (DI water: DMSO 85: 15 v / v) and filtered with a syringe filter. To prepare 10 w / v% polyurethane (PU), 20 w / v% polyurethane in ethanol solution (ethanol :DI water = 95:5 v / v) was used. 10 w / v% PU and 6 w / v% PEDOT :PSS were then thoroughly mixed so that the PEDOT :PSS to PU ratio is 1 :3, followed by filtering. The ink was ready to print after the final stage of transferring the combined solution into a barrel for 3D printing and thoroughly mixing it in the mixer.

[0194] Methods - Device fabrication with 3D printing technology: The designs of the three layers of the bioelectrode were generated by computer-aided design (CAD), followed by exporting them in DXF format. Next, the DXF format was converted into the codes to control the ink printing in the x-y-z direction by the built-in DXF conversion package. As a substrate of the fabrication process, glass plates were used and treated with Rain-X water repellent, followed by printing of the PDMS ink. A 5-mL syringe barrel containing ink was connected to the UlitmusPlus dispenser for applying pressure during printing to control the on and off of the dispenser, which allows the ink to print the designed paths accordingly. The encapsulation layers were printed with PDMS ink in a 5-mL syringe barrel, followed by curing at 125° C for 15 min.

[0195] Methods - Finite element modeling: To evaluate the mechanical properties of the bioelectrode, finite element simulations were carried out by the software ABAQUS. The bioelectrode was reconstructed in modeling, based on the experimental fabrication of patient 39 device (FIG. 30). Since the electrode layer contributes little to the mechanical response of the device, only the encapsulation layer was modeled in FEM. The PDMS, SBS, and metal control devices share the same trapezoidal geometrical setting but feature a space-filled plate rather than a hexagonally porous structure. The PDMS layer was modeled as a Neo-Hookean hyperelastic material with Young’s modulus and Poisson’s ratio as 1.8 MPa and 0.48. For SBS and metal, theAtty. Ref. No. 0073605-001041Young's modulus was set to be 45 MPa and 60 GPa, and Poisson’s ratio to be 0.48 and 0.42. To calculate bending stiffness, a fixed boundary condition was applied at one end of the device, and a small vertical displacement d was given on the other. The external work (1 / 7) required to bend the device was then calculated. The effective bending stiffness per width of the device can then be estimated as D = 2W13 / 3d2b, where I, b are the length and width of the device, respectively. As for the conformability test, the brain tissue was cut from SM cortical regions of an MRI- reconstructed 3D brain model, with a Young's modulus of 6 kPa and a Poisson’s ratio of 0.48. Initially, the device was set to suspend 5 mm above the brain surface and gradually descend because of gravity. The bottom of the brain tissue is fixed, and the surface interaction between the device and the brain tissue was set to be adhesive and inseparable.

[0196] The in silico modeling was carried out by COMSOL Multiphysics to measure the connectivity rate. The geometry setting of the device-brain assembly was inherited from the results of the conformality test. Four locations of electrodes on the bioelectrode were manually picked from the proximal region of the brain surface (distance within 0.5 mm, FIGS. 23 and 24). In PMDS and SBS control devices’ assembly, the same four locations of electrodes were selected as the bioelectrode-brain assembly (FIGS. 25 and 26). In PDMS and SBS matrix devices, the electrodes were set to be matrix-aligned as conventional devices designed, with 12 electrodes in total (FIGS. 27 and 28). Constant unit electrical potential was applied to the surface of brain tissue, and all the domains except electrodes on the devices were set to be insulators. The electrodes were set to be conductors with high conductivity. The number of connected electrodes was counted to calculate the connectivity rate percentage.

[0197] Methods - Electrical characterization: For the electrical characterization, the device interface part, the Platinum counter electrode, and the Ag / AgCl reference electrode wereAtty. Ref. No. 0073605-001041 immersed in phosphate-buffered saline (PBS, as an electrolyte). Electrochemical impedance spectroscopy (EIS) was performed using a potentiostat with a frequency analyzer (Autolab PGSTAT204, Metrohm). The frequency range of 1-100 kHz was scanned with an amplitude of 0.01 V.

[0198] Cyclic voltammetry (CV) measurements were conducted using potentiostat (Autolab PGSTAT204, Metrohm) with the potential of ± 0.6 V (scan rate 0.1 V / s). After that, charge storage capacity (CSC) was calculated from the data of CV measurements using customized MATLAB code from the formula, f i(E) / 2vA), where El and E2 were the range of potential window, i, the current is a function of potential and was taken for each potential value, and v and A were considered as scan rate and area of the device, respectively. To measure the charge injection capacity (CIC) of the device, Chronopotentiometry fast was performed using galvanostat mode (Autolab PGSTAT204, Metrohm). The current pulses were progressively amplified until the electrode under examination polarized to an extent marginally higher than the water electrolysis’s voltage range of -0.6 to 0.8 V. Ohmic resistance in the circuit generated instantaneous polarization of the electrodes, which was subtracted to adjust the voltage traces. The measured output voltage and current were used to calculate the CIC of the device as Q(c)+Q(a) / A (where Q(c) and Q(a) are the total injected current in the cathodal and anodal phase, respectively, and A is the area of the device).

[0199] Methods - Convention electrode fabrication: For comparing the functional performance of the personalized bioelectrode with a conventional electrode, the electrode designs were tailored to match the size of a rat’s brain. To replicate the structure of conventional electrodes (FIGS. 56 and 57), the fabrication included a bottom layer produced with a 500 pmAtty. Ref. No. 0073605-001041 nozzle, a middle layer with a 100 pm nozzle, and a top layer with a 200 pm nozzle. While the same materials were used for printing both designs, the overall stiffness of the replicative electrodes was significantly higher than the bioelectrode due to the thickness of the layers.

[0200] Methods - Animals: To test the functional performance of the bioelectrode, one adult male Long-Evans rat (400 - 650 g) and one adult female Long-Evans rat (260 g) were used in this study. Animals were housed in Plexiglas cages with ad libitum access to water and food. The animal room was under a 12-hour light: 12-hour dark cycle, and the temperature was maintained at 22-24°C. All experiments were approved by the Pennsylvania State University Institutional Animal Care and Use Committee (IACUC).

[0201] Methods - Phantom test: The animal was anesthetized with a cocktail of ketamine (33 mg / kg) and xylazine (13 mg / kg) and perfused first with saline, then with 4% PFA (Thermo Scientific, Catalog No. J61899.AP). The brain was then taken out carefully and fixed in 4% PFA with 30% sucrose for one day. After fixation, the electrode was placed on the surface of the left SM cortex and fixed with a tissue adhesive (Vetabond, 3M, St. Paul, MN). Then, the brain was placed in a plastic tube with 2% w / v agarose. For the preparation of 2% w / v agarose, 2g agarose (Invitrogen, Catalog No. 16500-500) was mixed with 100 mL of water, and then the solution was heated to a boil in a microwave oven. After that, it was kept in a plastic tube and cooled down at room temperature. Then, the brain with the bioelectrode was placed on the surface of agarose, and then the tube was filled with saline. A structural MRI of the phantom was performed on a 7T Broker 70 / 30 BioSpec scanner through ParaVision 6.0.1 software (Bruker, Billerica, MA) at the high-field MRI facility at the Pennsylvania State University. Structural data were collected using a rapid imaging with refocused echoes (RARE) sequence with the following parameters: echoAtty. Ref. No. 0073605-001041 time (TE) = 40 ms; repetition time (TR) = 3000 ms; in-plane resolution = 0.125 x 0.125 mm2; slice thickness = 1 mm; number of slices = 20; FOV = 32 * 32 mm2; image matrix = 256 * 256.

[0202] Methods - MRI scanning: Before and after surgery, anatomical images were recorded using a rapid imaging with refocused echoes (RARE) sequence with the following parameters: echo time (TE) = 40 ms; repetition time (TR) = 3000 ms; in-plane resolution = 0. 125 * 0.125 mm2; slice thickness = 1 mm; number of slices = 20; FOV = 32 * 32 mm2; image matrix = 256 * 256. Moreover, fMRI data were also collected after surgery using a T2-weighted gradient-echo echo-planar-imaging (EPI) sequence with the following parameters: echo time (TE) = 15 ms; repetition time (TR) = 1000 ms; in-plane resolution = 0.5 * 0.5 mm2; slice thickness = 1 mm; number of slices = 20; FOV = 32 * 32 mm2; image matrix = 64 * 64. All MRI scans were aligned to a rat brain template for consistent visualization. For structural scans, the sensorimotor (SM) cortical regions under the electrode in the left hemisphere were manually selected in a mirrored configuration relative to the corresponding regions in the right hemisphere. The BOLD intensity of voxels in the regions under the electrode was then compared to the BOLD intensity of the mirrored brain regions in the right hemisphere. This comparison was conducted before and after surgery across both male and female rats.

[0203] Methods - in vivo surgery and recording: For implantation of the bioelectrode, anesthesia was initiated with isoflurane, followed by the intramuscular administration of a ketamine-xylazine cocktail (40 mg / kg and 12 mg / kg, respectively) and a subcutaneous injection of Buprenorphine (1.0 mg / kg). Throughout the surgery, a gas mixture of oxygen and isoflurane (0-2%) was provided constantly through a nose cone to maintain the anesthetic state and blood oxygenation level, and the body temperature was maintained at 37 °C via a warming pad (PhysioSuite, Kent Scientific Corporation). Oxygen saturation (SpO?) and heart rate wereAtty. Ref. No. 0073605-001041 continuously monitored and recorded every 20 minutes via a pulse oximetry (MouseSTAT Jr, Kent Scientific Corporation). During the surgery, the animals were immobilized on a stereotaxic platform (David Kopf Instruments, Tujunga, CA). A craniotomy was made over the left somatosensory and motor cortex area (SM, male rat coordinates: anterior: +1.8, posterior -3.5; medial: -0.5, lateral: -3.5; female rat coordinates: anterior: +1.2, posterior -3.5; medial: -0.5, lateral: -3.2) and dura mater was carefully removed after once exposed. Personalized bioelectrodes were gently placed on the surface of the motor and somatosensory cortices through the window. The grounding and reference wires of the electrode were twisted with a silver wire fixed on the surface of the right cerebellum. The I / O part of the bioelectrode was connected to the recording system (Intan RHS and RHD) to facilitate signal acquisition from the SM cortex. In a similar way, the conventional electrodes were implanted in the same region, and signals were recorded to allow direct comparison. A 60 Hz notch filter was applied to remove the noise interference. For a whisker-evoked potential experiment, both the bioelectrode and conventional electrode were placed on the ROI, and potential was recorded for 25-second intervals. The airpuff stimulator was positioned contralaterally to the implanted devices, with a stimulation duration of 1 second followed by a 5-second resting period. The air-puff stimulator was controlled via a customized system to ensure precise mechanical stimulation of the whiskers. Moreover, isoflurane anesthesia was carefully regulated via a nose cone throughout the whisker stimulation experiment to maintain a consistent level of unconsciousness, ensuring the stability of neural responses and the reliability of the recorded data. After recording the electrophysiology signals, the surface of the SM cortex was fixed using a tissue adhesive (Vetabond, 3M, St. Paul, MN) and dental cement (ParaBond, COLTENE, Cuyahoga Falls, OH). The rats were then euthanized using CO2.Atty. Ref. No. 0073605-001041

[0204] Methods - Data analysis: The recorded data were analyzed using custom MATLAB codes (MATLAB 2021b). During the processing, the data was filtered from 0.1 to 200 Hz. Additionally, the time-frequency analysis spectrogram was performed for all channels (0.1-200 Hz), and the time resolution and overlapping were set to 200 ms and 50%, respectively, at 1 Hz intervals. The signal-to-noise ratio (SNR) was calculated using the formula, SNR= 20 log (S / N), where ‘S’ represents the peak-to-peak signal amplitude of evoked potential during the stimulation period and ‘N’ is the standard deviation of the signal during the resting period.

[0205] Methods - Histology: After 4 weeks and 8 weeks of implantation, the rat was anesthetized with a cocktail of ketamine and xylazine (33mg / kg and 13 mg / kg) and perfused transcardially with saline, followed by a mixed solution containing 4% paraformaldehyde (PF A) and 10% sucrose to ensure thorough fixation. To preserve the brain tissue and minimize structural damage, the brain was taken out carefully and immersed in 4% PFA for 48 hours. Subsequently, the fixed brain was processed using the Tissue-Tek VIP 6 Al Vacuum Infiltration Processor for automated tissue preparation. The processing cycle lasted 16 hours, after which the brain tissue was embedded with evenly distributed paraffin wax using the Tissue-Tek TEC embedding system. The paraffin block was then cooled on a cold plate to solidify. Then, the brain was sectioned into 5 pm-thick slices using the Tissue-Tek Automated Microtome. The sections underwent deparaffinization, followed by hematoxylin and eosin (H&E) staining using the Leica Autostainer. For additional Immunohistochemistry staining, including Masson’s Tri chrome and ionized calcium-binding adapter molecule (iba-1), the deparaffmized sections were collected from the autostainer for subsequent processing.

[0206] For Masson’s Trichrome staining, the deparaffmized brain sections were mordanted in Bouin’s solution for 1 hour at 56°C, followed by washing under running waterAtty. Ref. No. 0073605-001041 until the yellow coloration was completely removed and rinsing with deionized water. Subsequently, the sections were immersed in Weigert’s iron hematoxylin solution for 10 minutes, rinsed in deionized water, and stained with Biebrich scarlet-acid fuchsin solution for 2 minutes. The slices were then rinsed again with deionized water. Next, the sections were treated with a phosphomolybdic-phosphotungstic acid solution for 10 minutes, followed by staining in an aniline blue solution for 5 minutes. After another rinse with deionized water, the sections were treated with glacial acetic acid for 5 minutes. The samples were subsequently dehydrated through graded ethanol solutions (95% ethanol followed by absolute ethanol) and cleared in xylene with two changes for each step. Finally, the sections were mounted onto glass slides using Permount as the mounting medium. For iba-1 staining, brain tissue sections were blocked using a blocking solution consisting of 0.3% Triton X-100 and 5% goat serum (Abeam) in l x PBS for 1 h at room temperature. Slices were then incubated with the primary antibodies, rabbit anti-ibal (1 :400 dilution; FujiFilm Irvine Scientific) containing 0.3% Triton X-100 and 3% goat serum overnight at 4 °C. After the incubation, slices were rinsed nine times over 30 min with 1 * PBS. Slides were then incubated with the secondary antibodies, Alexa Fluor 488 goat anti-rabbit (1:200 dilution; Abeam) for 1 h at room temperature. Slices were then rinsed nine times over 30 min. They were then mounted on glass slides with coverslips using ProLong Gold Antifade Mountant with DAP1 (Thermo Fisher Scientific). The slides were kept in the dark at room temperature for at least 24 h before imaging. Thereafter, the slices were imaged with a Leica SP8 Dive multiphoton microscope.

[0207] Methods - Statistical analysis: OriginPro 2023 software was used to assess the statistical significance of all comparison studies in this work. In the statistical analysis forAtty. Ref. No. 0073605-001041 comparison between multiple samples, one-way ANOVA was conducted with the threshold of *P < 0.05.

[0208] It should be understood that modifications to the embodiments disclosed herein can be made to meet a particular set of design criteria. For instance, the number of or configuration of components or parameters may be used to meet a particular objective.

[0209] It will be apparent to those skilled in the art that numerous modifications and variations of the described examples and embodiments are possible in light of the above teachings of the disclosure. The disclosed examples and embodiments are presented for purposes of illustration only. Other alternative embodiments may include some or all of the features of the various embodiments disclosed herein. For instance, it is contemplated that a particular feature described, either individually or as part of an embodiment, can be combined with other individually described features, or parts of other embodiments. The elements and acts of the various embodiments described herein can therefore be combined to provide further embodiments.

[0210] It is the intent to cover all such modifications and alternative embodiments as may come within the true scope of this invention, which is to be given the full breadth thereof. Additionally, the disclosure of a range of values is a disclosure of every numerical value within that range, including the end points. Thus, while certain exemplary embodiments of the apparatus and process and / or utilization and methods of making and using the same have been discussed and illustrated herein, it is to be distinctly understood that the invention is not limited thereto but may be otherwise variously embodied and practiced within the scope of the following claims.

Claims

Atty. Ref. No. 0073605-001041What is claimed is:

1. A method of manufacturing a bioelectrode, the method comprising: obtaining a three-dimensional scan of at least a portion of a brain; identifying a target region of the brain; designing a bioelectrode model configured to fit the target region; and printing the bioelectrode based on the bioelectrode model.

2. The method of claim 1, wherein obtaining the three-dimensional scan comprises scanning the brain with a magnetic resonance imaging scanner.

3. The method of claim 1, the method further comprising: generating a three-dimensional model of the brain using scan data of the three- dimensional scan.

4. The method of claim 3, wherein identifying the target region of the brain comprises analyzing the three-dimensional model of the brain.

5. The method of claim 3, wherein the bioelectrode model is designed to fit the target region of the three-dimensional model of the brain.Atty. Ref. No. 0073605-0010416. The method of claim 5, wherein the bioelectrode model is designed using an iterative process to ensure placement and shape of the bioelectrode model achieve sufficient conformal contact with the target region of the brain surface without gaps or misalignment.

7. The method of claim 1, wherein the bioelectrode is printed using a direct ink writing printing device.

8. A bioelectrode manufactured from the method of claim 1.

9. The bioelectrode of claim 8, wherein the bioelectrode comprises a top layer, a bottom layer, and an electrode layer positioned between the top layer and the bottom layer such that the top layer and bottom layer encapsulate the electrode layer.

10. The bioelectrode of claim 9, wherein the bottom layer comprises a printed honeycomb pattern.

11. The bioelectrode of claim 10, wherein the electrode layer comprises a plurality of electrode probe strands configured to match the honeycomb pattern of the bottom layer.

12. The bioelectrode of claim 11, wherein the top layer comprises a plurality of strands configured to match the electrode probe strands of the electrode layer and the honeycomb pattern of the bottom layer.Atty. Ref. No. 0073605-00104113. The bioelectrode of claim 9, wherein the top layer and bottom layer are printed using a polydimethylsiloxane ink.

14. The bioelectrode of claim 9, wherein the electrode layer is printed using a polymer hydrogel ink.

15. The bioelectrode of claim 14, wherein the hydrogel ink comprises poly(3,4- ethylenedioxythiophene) polystyrene sulfonate and polyurethane.

16. The bioelectrode of claim 8, wherein the bioelectrode has a Young’s modulus between 0.1 and 10 kPa.

17. The bioelectrode of claim 8, wherein the bioelectrode is configured to be implanted onto a brain.

18. The bioelectrode of claim 17, wherein the bioelectrode is operatively connected to an input / output device such that the bioelectrode transmits collected brain activity data to the input / output device.

19. The bioelectrode of claim 17, wherein the bioelectrode is operatively connected to an input / output device such that the input / output data transmits signals to the bioelectrode.

20. A system for manufacturing a bioelectrode, the system comprising:Atty. Ref. No. 0073605-001041 a scanning device configured to obtain a three-dimensional scan of at least a portion of a brain; a computer device configured to receive the three-dimensional scan from the scanning device and design a bioelectrode model configured to fit a target region of the brain; and a printing device configured to receive bioelectrode model from the computer device and print the bioelectrode based on the bioelectrode model.

21. The system of claim 20, wherein the scanning device is a magnetic resonance imaging scanner.

22. The system of claim 20, wherein the printing device is a direct ink writing printer.

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