DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/05/2026 has been entered.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 5, 7-8, 11, 13-14, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Howard (US 20130338526) in view of Flaherty et al., (US 20050273890; hereinafter Flaherty) and Ghaffari et al., (US 20100298895; hereinafter Ghaffari).
Regarding claim 1, Howard (Figures 1-3) discloses a method for neural stimulation comprising: receiving electrical signals from electrophysiological neural signals, via an implantable device (device comprising sensors+effectors in Figure 3), of neural tissue from at least one read modality (sensors), wherein the electrophysiological neural signals are Spike frequency modulated (using frequencies of neuronal activity/action potential spikes); encoding the received electrical signals using a Fundamental Code Unit ([0028]); automatically generating at least one machine learning model using the Fundamental Code Unit encoded electrical signals ([0011]: a Medical Co-Processor MCP device correlates multiple data streams temporally using one or more read modalities); generating at least electrical signal to be transmitted to the brain tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals are Spike frequency modulated ([0028]: using select treatment frequencies); wherein the generated Spike frequency modulated signals are generated using signal transform function that converts an analog stimulus on a sensory neuron into a sequence of spikes, wherein the rate of spikes per second (sps) is proportional to the intensity of the input ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes; the rate of spikes per second would therefore be proportional to the intensity of the input); and transmitting the generated at least electrical signal to the neural tissue to provide electrophysiological stimulation of the neural tissue using at least one write modality (effectors), ([0011], [0013], [0028], [0103]-[0107]).
Howard fails to disclose performing the steps above with optical signals in addition to the electrical signals. However, Flaherty teaches a method using an implant device adapted to be implanted within a body of a person for interacting with brain tissue in which the electrodes are a plurality of optically conductive fibers comprising optical fibers ([0031], [0048], [0092]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the optical fibers taught by Flaherty because Howard discloses that a variety of sensors may be used in the method. Therefore, the optical fibers taught by Flaherty may also be used as sensors in the method. Furthermore, in the modified device, the optical fibers would be adapted to receive optical signals from electrophysiological neural signals of brain tissue and to transmit optical signals to provide electrophysiological stimulation of the brain tissue.
Howard/Flaherty fails to teach the implantable device is an oblate spheroid shaped implantable device. However, Ghaffari teaches an implant device (200), which may be shaped as an oblate spheroid ([0079], [0188]). It would have been an obvious matter of design choice to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty to include the implant device shaped as an oblate spheroid, as taught by Ghaffari, since applicant has not disclosed that having the implant device shaped as an oblate spheroid solves any stated problem or is for any particular purpose and it appears that the device would perform equally well with either design. Furthermore, absent a teaching as to the criticality of the implant device shaped as an oblate spheroid, this particular arrangement is deemed to have been known by those skilled in the art since the instant specification and evidence of record fail to attribute any significance (novel or unexpected results) to a particular arrangement.
Regarding claim 2, Howard (Figures 1-3) further discloses that the received Spike frequency modulated signals (using frequencies of neuronal activity/action potential spikes) are obtained from sensory neurons ([0012], [0031], [0066], [0086]).
Regarding claim 5, Howard (Figures 1-3) further discloses receiving electrical and optical signals from electrophysiological neural signals of neural tissue from at least one read modality (sensors), wherein the electrophysiological neural signals are Spike frequency demodulated ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes), generating at least one optical or electrical signal to be transmitted to the brain tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals are Spike frequency demodulated (using frequencies of neuronal activity/action potential spikes), wherein the received Spike frequency demodulated signals (using frequencies of neuronal activity/action potential spikes) are obtained from motor neurons ([0012], [0031], [0066], [0086]).
Regarding claim 7, Howard (Figures 1-3) discloses a system for neural stimulation comprising: at least one read modality (sensors) adapted to receive electrical signals, via an implantable device (device comprising sensors+effectors in Figure 3), from electrophysiological neural signals of neural tissue, wherein the electrophysiological neural signals are Spike frequency modulated (using frequencies of neuronal activity/action potential spikes); at least one write modality (effectors) adapted to transmit the generated at least electrical signal to the neural tissue to provide electrophysiological stimulation of the brain tissue; and at least one computing device comprising a processor (Interface 1), memory accessible by the processor, and program instructions stored in the memory and executable by the processor to cause the processor to perform: encoding the received electrical signals using a Fundamental Code Unit ([0028]); automatically generating at least one machine learning model using the Fundamental Code Unit encoded electrical signals ([0011]: a Medical Co-Processor MCP device correlates multiple data streams temporally using one or more read modalities); and generating at least one electrical signal to be transmitted to the neural tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals Spike frequency modulated ([0028]: using select treatment frequencies), wherein the generated Spike frequency modulated signals are generated using signal transform function that converts an analog stimulus on a sensory neuron into a sequence of spikes, wherein the rate of spikes per second (sps) is proportional to the intensity of the input ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes; the rate of spikes per second would therefore be proportional to the intensity of the input).
Howard fails to disclose performing the steps above with optical signals in addition to the electrical signals. However, Flaherty teaches a system for neural stimulation in which the electrodes are a plurality of optically conductive fibers comprising optical fibers ([0031], [0048], [0092]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the optical fibers taught by Flaherty because Howard discloses that a variety of sensors may be used in the method. Therefore, the optical fibers taught by Flaherty may also be used as sensors in the method. Furthermore, in the modified device, the optical fibers would be adapted to receive optical signals from electrophysiological neural signals of brain tissue and to transmit optical signals to provide electrophysiological stimulation of the brain tissue.
Howard/Flaherty fails to teach the implantable device is an oblate spheroid shaped implantable device. However, Ghaffari teaches an implant device (200), which may be shaped as an oblate spheroid ([0079], [0188]). It would have been an obvious matter of design choice to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty to include the implant device shaped as an oblate spheroid, as taught by Ghaffari, since applicant has not disclosed that having the implant device shaped as an oblate spheroid solves any stated problem or is for any particular purpose and it appears that the device would perform equally well with either design. Furthermore, absent a teaching as to the criticality of the implant device shaped as an oblate spheroid, this particular arrangement is deemed to have been known by those skilled in the art since the instant specification and evidence of record fail to attribute any significance (novel or unexpected results) to a particular arrangement.
Regarding claim 8, Howard (Figures 1-3) further discloses that the received Spike frequency modulated signals (using frequencies of neuronal activity/action potential spikes) are obtained from sensory neurons ([0012], [0031], [0066], [0086]).
Regarding claim 11, Howard (Figures 1-3) further discloses at least one read modality (sensors) adapted to receive electrical and optical signals from electrophysiological neural signals of neural tissue, wherein the electrophysiological neural signals are Spike frequency demodulated ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes), generating at least one optical or electrical signal to be transmitted to the neural tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals are Spike frequency demodulated (using frequencies of neuronal activity/action potential spikes), wherein the received Spike frequency demodulated signals (using frequencies of neuronal activity/action potential spikes) are obtained from motor neurons ([0012], [0031], [0066], [0086]).
Regarding claim 13, Howard (Figures 1-3) discloses a computer program product comprising a non-transitory computer readable storage having program instructions embodied therewith, the program instructions executable by a computer system (Interfaces and analyzer), to cause the computer system to perform a method of neural stimulation comprising: receiving electrical signals from electrophysiological neural signals of neural tissue, via an implantable device (device comprising sensors+effectors in Figure 3), from at least one read modality (sensors), wherein the electrophysiological neural signals are Spike frequency modulated (using frequencies of neuronal activity/action potential spikes); encoding the received electrical signals using a Fundamental Code Unit ([0028]); automatically generating at least one machine learning model using the Fundamental Code Unit encoded electrical signals ([0011]: a Medical Co-Processor MCP device correlates multiple data streams temporally using one or more read modalities); generating at least one electrical signal to be transmitted to the brain tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals are Spike frequency modulated ([0028]: using select treatment frequencies); wherein the generated Spike frequency modulated signals are generated using signal transform function that converts an analog stimulus on a sensory neuron into a sequence of spikes, wherein the rate of spikes per second (sps) is proportional to the intensity of the input ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes; the rate of spikes per second would therefore be proportional to the intensity of the input); and transmitting the generated at least electrical signal to the neural tissue to provide electrophysiological stimulation of the neural tissue using at least one write modality (effectors), ([0011], [0013], [0028], [0103]-[0107]).
Howard fails to disclose performing the steps above with optical signals in addition to the electrical signals. However, Flaherty teaches a system for neural stimulation in which the electrodes are a plurality of optically conductive fibers comprising optical fibers ([0031], [0048], [0092]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the optical fibers taught by Flaherty because Howard discloses that a variety of sensors may be used in the method. Therefore, the optical fibers taught by Flaherty may also be used as sensors in the method. Furthermore, in the modified device, the optical fibers would be adapted to receive optical signals from electrophysiological neural signals of brain tissue and to transmit optical signals to provide electrophysiological stimulation of the brain tissue.
Howard/Flaherty fails to teach the implantable device is an oblate spheroid shaped implantable device. However, Ghaffari teaches an implant device (200), which may be shaped as an oblate spheroid ([0079], [0188]). It would have been an obvious matter of design choice to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty to include the implant device shaped as an oblate spheroid, as taught by Ghaffari, since applicant has not disclosed that having the implant device shaped as an oblate spheroid solves any stated problem or is for any particular purpose and it appears that the device would perform equally well with either design. Furthermore, absent a teaching as to the criticality of the implant device shaped as an oblate spheroid, this particular arrangement is deemed to have been known by those skilled in the art since the instant specification and evidence of record fail to attribute any significance (novel or unexpected results) to a particular arrangement.
Regarding claim 14, Howard (Figures 1-3) further discloses that the received Spike frequency modulated signals (frequencies of neuronal activity/action potential spikes) are obtained from sensory neurons ([0012], [0031], [0066], [0086]).
Regarding claim 17, Howard (Figures 1-3) further discloses receiving electrical and optical signals from electrophysiological neural signals of neural tissue from at least one read modality (sensors), wherein the electrophysiological neural signals are Spike frequency demodulated ([0011], [0013], [0028], [0103]-[0107]: baseband oscillation frequencies specific to the area of activity are generated using an analog stimulus on a sensory neuron which is converted into a sequence of spikes), generating at least one optical or electrical signal to be transmitted to the brain tissue using the generated at least one machine learning model ([0011]: the MCP device determines the patterns which are deleterious or sub-optimal, and uses a set of write modalities, or means to modify cognitive activity, to neutralize the negative effects of these patterns and stimulate patterns of activity which will have positive short- and long-term effects), wherein the generated signals are Spike frequency demodulated (using frequencies of neuronal activity/action potential spikes), wherein the received Spike frequency demodulated signals (using frequencies of neuronal activity/action potential spikes) are obtained from motor neurons ([0012], [0031], [0066], [0086]).
Claim(s) 4, 10, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Howard/Flaherty/Ghaffari, as applied to claims 2, 8, and 14 above.
Regarding claim 4, Howard/Flaherty/Ghaffari teaches the method of claim 2, but fails to teach that the generated Spike frequency modulated signals have a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to include the generated Spike frequency modulated signals having a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. MPEP 2144.05(I).
Regarding claim 10, Howard/Flaherty/Ghaffari teaches the system of claim 8, but fails to teach that the generated Spike frequency modulated signals have a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to include the generated Spike frequency modulated signals having a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. MPEP 2144.05(I).
Regarding claim 16, Howard/Flaherty/Ghaffari teaches the computer program product of claim 14, but fails to teach that the generated Spike frequency modulated signals have a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to include the generated Spike frequency modulated signals having a rate of 0 to 100 spikes per second and an amplitude of 0 to 100 mV since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. MPEP 2144.05(I).
Claim(s) 6, 12, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Howard/Flaherty/Ghaffari, as applied to claims 5, 11, and 17 above, and further in view of Fan et al., (US 20160232420; hereinafter Fan).
Regarding claim 6, Howard/Flaherty/Ghaffari teaches the method of claim 5, but fails to teach that the generated Spike frequency demodulated signals are generated using a left rectangular numerical integration of the SFM signals for each sampling period determined by a given threshold of conversion. However, Fan teaches a method for processing signal data in which desired signals are generated using a left rectangular numerical integration of input signals for each sampling period, which would be determined by a given threshold of conversion ([0121]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to use a left rectangular numerical integration of the input (SFM) signals for each sampling period determined by a given threshold of conversion to generate the desired (Spike frequency demodulated) signals, as taught by Fan, since it has been held that where the general conditions of a claim are disclosed in the prior art, one of ordinary skill in the art would have been capable of applying a known method of enhancement to a "base" device (method, or product) in the prior art to yield predictable results. MPEP 2143.I(C).
Regarding claim 12, Howard/Flaherty/Ghaffari teaches the system of claim 11, but fails to teach that the generated Spike frequency demodulated signals are generated using a left rectangular numerical integration of the SFM signals for each sampling period determined by a given threshold of conversion. However, Fan teaches a system for processing signal data in which desired signals are generated using a left rectangular numerical integration of input signals for each sampling period, which would be determined by a given threshold of conversion ([0121]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to use a left rectangular numerical integration of the input (SFM) signals for each sampling period determined by a given threshold of conversion to generate the desired (Spike frequency demodulated) signals, as taught by Fan, since it has been held that where the general conditions of a claim are disclosed in the prior art, one of ordinary skill in the art would have been capable of applying a known method of enhancement to a "base" device (method, or product) in the prior art to yield predictable results. MPEP 2143.I(C).
Regarding claim 18, Howard/Flaherty/Ghaffari teaches the computer program product of claim 17, but fails to teach that the generated Spike frequency demodulated signals are generated using a left rectangular numerical integration of the SFM signals for each sampling period determined by a given threshold of conversion. However, Fan teaches a system for processing signal data in which desired signals are generated using a left rectangular numerical integration of input signals for each sampling period, which would be determined by a given threshold of conversion ([0121]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Howard/Flaherty/Ghaffari to use a left rectangular numerical integration of the input (SFM) signals for each sampling period determined by a given threshold of conversion to generate the desired (Spike frequency demodulated) signals, as taught by Fan, since it has been held that where the general conditions of a claim are disclosed in the prior art, one of ordinary skill in the art would have been capable of applying a known method of enhancement to a "base" device (method, or product) in the prior art to yield predictable results. MPEP 2143.I(C).
Response to Arguments
Applicant’s arguments filed 06/05/2026, regarding the newly amended limitations of claims 1, 7, and 13, have been fully considered and are persuasive. Therefore, the rejection(s) has/have been withdrawn. However, upon further consideration, a new ground(s) of rejection is/are made in view of newly found prior art reference Ghaffari, which teaches an implantable device which may be shaped as an oblate spheroid. In combination with Howard/Flaherty, the modified device/method teaches the invention as recited at least in amended independent claims 1, 7, and 13.
Conclusion
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/C.C.P./Examiner, Art Unit 3794
/EUN HWA KIM/Primary Examiner, Art Unit 3794
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