CTNF 17/649,668 CTNF 98504 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Response to Amendment This Office Action is responsive to the amendment filed on 20 Mar 2026. As directed by the amendment: claims 1, 6-7, 10-11, 17, and 20 have been amended, claims 8-9 and 18-19 have been canceled, and no claims have been added. Thus, claims 1-7, 10-17, and 20 are presently pending in this application. Response to Arguments Applicant’s arguments, see Remarks, filed 20 Mar 2026, with respect to the rejection(s) of claim(s) 1, 5, 11, and 15 under 35 U.S.C. 103 have been fully considered and are persuasive in light of the claim amendments. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Petrucci et al. ("A Closed-loop Deep Brain Stimulation Approach for Mitigating Burst Durations in People with Parkinson’s Disease," 2020, previously cited), hereinafter Petrucci, as explained in further detail below. Examiner agrees with Applicant’s arguments (Remarks, pages 7-8) that the previously cited GIftakis reference does not teach “maintaining stimulation intensity when a previously identified beta burst has terminated but the time since cessation of the previously identified beta burst has not exceeded a termination delay threshold”, as recited in claims 1 and 11. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15 AIA Claim s 1-7, 10-17, and 20 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Petrucci et al. ("A Closed-loop Deep Brain Stimulation Approach for Mitigating Burst Durations in People with Parkinson’s Disease," 2020, previously cited), hereinafter Petrucci . Applicant may rely on the exception under 35 U.S.C. 102(b)(1)(A) to overcome this rejection under 35 U.S.C. 102(a)(1) by a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application, and is therefore not prior art under 35 U.S.C. 102(a)(1). Alternatively, applicant may rely on the exception under 35 U.S.C. 102(b)(1)(B) by providing evidence of a prior public disclosure via an affidavit or declaration under 37 CFR 1.130(b). Regarding claim 1, Petrucci discloses a deep brain stimulation system (Fig. 2, Section II.B), comprising: a neurostimulator (Fig. 2, Section II.B, implanted neurostimulator (INS)); and a controller (Fig. 2, Section II.B, Summit Communicator), where the controller is communicatively coupled to the neurostimulator (Section II.B, "our application makes use of the Summit Communicator to establish a bidirectional communication channel with the INS") and configured to: obtain a plurality of neural activity signals from the neurostimulator (Section II.B, "we begin shifting data from new neural packets into two buffers for digital signal processing"); identify beta bursts within each neural activity signal (Section II.B, "The most recent beta burst is identified by finding periods of time in buffered data where the enveloped data is above the patient identified threshold"); classify identified beta bursts as pathological or normal based on a duration of the identified beta bursts (Section II.B, "The duration of this burst is checked against the burst duration threshold to determine if the burst is 'pathological' or 'normal'"); and modify an amplitude of continuous stimulation provided by the neurostimulator based on the classified beta bursts, wherein the controller is configured to modify the amplitude of continuous stimulation using a stimulation map (Section II.B, "Adjustment of stimulation based on the identified beta burst activity is performed by making use of the Summit INS on-board state table, which can be used to ramp stimulation parameters to desired setpoints based on an embedded stimulation table"), the stimulation map comprising: decrease stimulation intensity when a normal beta burst is identified (Fig. 3, Section II.B, "slowly ramp stimulation down when normal beta burst activity is detected"); maintain stimulation intensity when a previously identified beta burst has terminated but the time since cessation of the previously identified beta burst has not exceeded a termination dela threshold (Fig. 3, Section II.B, "A termination delay, or amount of time after the burst has ended before changing stimulation again, can be set on a participant specific basis based on their neural dynamics. ... hold stimulation constant during the termination delay"); and increase stimulation intensity when a pathological beta burst is identified (Fig. 3, Section II.B, "ramp stimulation up in a specific STN in the case of a pathological burst being detected"). Regarding claim 2, Petrucci discloses the deep brain stimulation system of claim 1, as explained above. Petrucci further discloses that the neural activity signals are local field potential signals (Section II.A, "Beta burst durations were identified from raw local field potentials (LFPs)"). Regarding claim 3, Petrucci discloses the deep brain stimulation system of claim 1, as explained above. Petrucci further discloses that to identify beta bursts in a neural activity signal, the controller is configured to: filter the neural activity signal to remove components outside of the beta band of 13-30 Hz using a filter to create a first filtered signal (Section II.B, "We then apply a 128th-order bandpass FIR filter to the data using patient-specific coefficients to isolate the beta-band of interest"; Section I, "Persistent synchrony of beta band oscillations (13–30 Hz) has emerged as a biomarker of Parkinson’s disease (PD)"); and identify portions of the first filtered signal that exceed a threshold power level (Section II.B, "The most recent beta burst is identified by finding periods of time in buffered data where the enveloped data is above the patient identified threshold"). Regarding claim 4, Petrucci discloses the deep brain stimulation system of claim 3, as explained above. Petrucci further discloses that the filter is a finite response filter (Section II.B, 128th-order bandpass FIR filter). Regarding claim 5, Petrucci discloses the deep brain stimulation system of claim 3, as explained above. Petrucci further discloses that the controller is configured to classify beta bursts exceeding 300 ms (Section II.A, "A pathological burst was defined as being longer than 300 ms"). Regarding claim 6, Petrucci discloses the deep brain stimulation system of claim 3, as explained above. Petrucci further discloses that to identify beta bursts in a neural activity signal, the controller is configured to: filter the first filtered signal using a 6 Hz band centered on peak beta power to create a second filtered signal (Section II.A, "Data was bandpass filtered (specifics of the filters used are in sections B and C) using a 6 Hz band centered on the peak beta power"); square the second filtered signal (Section II.B, "We then square the output"); locate peaks in the squared second filtered signal (Section II.B, "find the peaks"); perform a linear interpolation between the peaks to create a linear envelope (Section II.B, "enveloping the data using linear interpolation between peaks"; Section II.A, "A linear envelope was then calculated by squaring the data, finding the peaks in the data, and linearly interpolating between the peaks"), identify beta bursts based on the average trough power in the linear envelope in a 45-65 Hz band of the neural activity signal (Section II.A, "A burst was defined as the duration of time the linear envelope remained above a participant specific threshold that was determined based on the average trough (minima) power in the linear envelope of the signal in the 45–65 Hz band"). Regarding claim 7, Petrucci discloses the deep brain stimulation system of claim 3, as explained above. Petrucci further discloses that the termination delay threshold is 10 ms (Section II.C, "the termination delay was set to 10 ms"). Regarding claim 10, Petrucci discloses the deep brain stimulation system of claim 1, as explained above. Petrucci further discloses that the stimulation intensity is bounded between 2 mA and 5 mA (Section II.C., "the stimulation intensity was bounded between 2 mA (Imin) and 5 mA (Imax)"). Regarding claim 11, Petrucci discloses a method of deep brain stimulation (Fig. 2, Section II.B), comprising: obtaining a plurality of neural activity signals from the neurostimulator (Section II.B, "we begin shifting data from new neural packets into two buffers for digital signal processing"); identifying beta bursts within each neural activity signal (Section II.B, "The most recent beta burst is identified by finding periods of time in buffered data where the enveloped data is above the patient identified threshold"); classifying identified beta bursts as pathological or normal based on a duration of the identified beta bursts (Section II.B, "The duration of this burst is checked against the burst duration threshold to determine if the burst is 'pathological' or 'normal'"); and modifying an amplitude of continuous stimulation provided by the neurostimulator based on the classified beta bursts, wherein modifying the amplitude of continuous stimulation comprises using a stimulation map (Section II.B, "Adjustment of stimulation based on the identified beta burst activity is performed by making use of the Summit INS on-board state table, which can be used to ramp stimulation parameters to desired setpoints based on an embedded stimulation table"), the stimulation map comprising: decreasing stimulation intensity when a normal beta burst is identified (Fig. 3, Section II.B, "slowly ramp stimulation down when normal beta burst activity is detected"); maintaining stimulation intensity when a previously identified beta burst has terminated but the time since cessation of the previously identified beta burst has not exceeded a termination dela threshold (Fig. 3, Section II.B, "A termination delay, or amount of time after the burst has ended before changing stimulation again, can be set on a participant specific basis based on their neural dynamics. ... hold stimulation constant during the termination delay"); and increasing stimulation intensity when a pathological beta burst is identified (Fig. 3, Section II.B, "ramp stimulation up in a specific STN in the case of a pathological burst being detected"). Regarding claim 12, Petrucci discloses the method of deep brain stimulation of claim 11, as explained above. Petrucci further discloses that the neural activity signals are local field potential signals (Section II.A, "Beta burst durations were identified from raw local field potentials (LFPs)"). Regarding claim 13, Petrucci discloses the method of deep brain stimulation of claim 11, as explained above. Petrucci further discloses that identifying beta bursts in a neural activity signal comprises: filtering the neural activity signal to remove components outside of the beta band of 13-30 Hz using a filter to create a first filtered signal (Section II.B, "We then apply a 128th-order bandpass FIR filter to the data using patient-specific coefficients to isolate the beta-band of interest"; Section I, "Persistent synchrony of beta band oscillations (13–30 Hz) has emerged as a biomarker of Parkinson’s disease (PD)"); and identifying portions of the first filtered signal that exceed a threshold power level (Section II.B, "The most recent beta burst is identified by finding periods of time in buffered data where the enveloped data is above the patient identified threshold"). Regarding claim 14, Petrucci discloses the method of deep brain stimulation of claim 13, as explained above. Petrucci further discloses that the filter is a finite response filter (Section II.B, 128th-order bandpass FIR filter). Regarding claim 15, Petrucci discloses the method of deep brain stimulation of claim 13, as explained above. Petrucci further discloses that beta bursts exceeding 300 ms are classified by the controller as pathological beta bursts (Section II.A, "A pathological burst was defined as being longer than 300 ms"). Regarding claim 16, Petrucci discloses the method of deep brain stimulation of claim 13, as explained above. Petrucci further discloses that identifying beta bursts in a neural activity signal further comprises: filtering the first filtered signal using a 6 Hz band centered on peak beta power to create a second filtered signal (Section II.A, "Data was bandpass filtered (specifics of the filters used are in sections B and C) using a 6 Hz band centered on the peak beta power"); squaring the second filtered signal (Section II.B, "We then square the output"); locating peaks in the squared second filtered signal (Section II.B, "find the peaks"); performing a linear interpolation between the peaks to create a linear envelope (Section II.B, "enveloping the data using linear interpolation between peaks"; Section II.A, "A linear envelope was then calculated by squaring the data, finding the peaks in the data, and linearly interpolating between the peaks"), identifying beta bursts based on the average trough power in the linear envelope in a 45-65 Hz band of the neural activity signal (Section II.A, "A burst was defined as the duration of time the linear envelope remained above a participant specific threshold that was determined based on the average trough (minima) power in the linear envelope of the signal in the 45–65 Hz band"). Regarding claim 17, Petrucci discloses the method of deep brain stimulation of claim 13, as explained above. Petrucci further discloses that the termination delay threshold is 10 ms (Section II.C, "the termination delay was set to 10 ms"). Regarding claim 20, Petrucci discloses the method of deep brain stimulation of claim 11, as explained above. Petrucci further discloses that the stimulation intensity is bounded between 2 mA and 5 mA (Section II.C., "the stimulation intensity was bounded between 2 mA (Imin) and 5 mA (Imax)") . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure : Stanslaski et al. (US Publication No. 20180085586 A1, previously cited) discloses a deep brain stimulation system that alters stimulation intensity in response to detected changes in neurological signals within the beta frequency (paragraphs [0053], [0081]) Tinkhauser et al. (The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease. 2017 Apr 1, cited in IDS filed 22 Mar 2023, previously cited) discloses a deep brain stimulation system that switches stimulation on or off in response to detected beta bursts that exceed a threshold (page 1056) Giftakis et al. (U.S. Patent Application No. 20130218232 A1, previously cited) discloses a method of delivering electrical stimulation to the brain based on detected bioelectrical responses (paragraph [0042]) Kehnemouyi et al. (Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia, Brain, 10 December 2020, https://doi.org/10.1093/brain/awaa394) discloses “To calculate beta power for each STN, the peak frequency in the beta band (13–30 Hz), which was also the frequency at which the PSD power differential between 0% and 100% stimulation was largest, was identified. A 6 Hz band, defined as the movement band, was then created and centred on this peak frequency. Relative beta power in the movement band was normalized by dividing these values by the mean power across the 45–65 Hz band during the movement state, enabling comparison among STNs” (page 476, first paragraph) Wu et al. (US 20170259064 A1) discloses changing stimulation intensity based on sensed beta band signals (paragraphs [0105], [0110]) Swann et al. (Adaptive deep brain stimulation for Parkinson’s disease using motor cortex sensing, 2018) discloses adaptive brain stimulation that changes stimulation intensity based on sensed gamma signals (pages 2-4, Control algorithms for adaptive DBS) Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTINE SISON whose telephone number is (703)756-4661. The examiner can normally be reached 8 am - 5 pm PT, Mon - Fri. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHRISTINE SISON/Examiner, Art Unit 3796 /Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792 Application/Control Number: 17/649,668 Page 2 Art Unit: 3796 Application/Control Number: 17/649,668 Page 3 Art Unit: 3796 Application/Control Number: 17/649,668 Page 5 Art Unit: 3796 Application/Control Number: 17/649,668 Page 6 Art Unit: 3796 Application/Control Number: 17/649,668 Page 7 Art Unit: 3796 Application/Control Number: 17/649,668 Page 8 Art Unit: 3796 Application/Control Number: 17/649,668 Page 9 Art Unit: 3796 Application/Control Number: 17/649,668 Page 10 Art Unit: 3796
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