DETAILED ACTION
The Examiner acknowledges the amendments received 05 June 2026. Claims 2-3 are cancelled; claims 9-12 are withdrawn; claims 1 and 4-8 are pending.
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 .
Response to Arguments
Applicant’s arguments, see “Remarks”, filed 09 June 2026, with respect to the rejection(s) of claim(s) 1 under Howard have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Koller.
Specification
The amendments to the Specification received 05 June 2026 are acknowledged and entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 and 4-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1 and 4-7 are directed to a method (process) of evaluating a living system.
Step 2A, Prong One
Regarding claim 1, the recited steps are directed to a mental process of performing concepts in a human mind or by a human using a pen and paper. See MPEP § 2106.04(a)(2)(Ill). The limitation(s) of “(a) measuring in vivo physiologic, behavioral, or physiologic and behavioral characteristics of a living subject to obtain non-invasive data; (b) establishing an in vitro cell model of a cellular network, exposing the in vitro cell model to a condition(s) to model a cellular environment in the living subject, and measuring cellular changes to obtain in vitro model data; (c) transforming the non-invasive data to functional graphs; (d) transforming the in vitro model data to topological, functional, or topological and functional graphs; integrating the non-invasive graphs and the in vitro model graphs; and using the integrated non-invasive and in vitro model graphs to identify patterns in brain activity of the living subject” is/are a process that, as drafted, covers performance of the limitation by a human mind (including an observation, evaluation, judgment, opinion) under the broadest reasonable standard interpretation. For example, these limitations are nothing more than observing the behavior of a person, drawing a model on a piece of paper of cellular structures, and then creating a graph from these previous steps.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. In particular, claim 1 provides no structure for implementing the method steps. The additional limitations of the “cell-network analysis software” and “CNN-LSTM neural network” generally could be applied to a piece of software rather than a physical structure. “Neural network” here is recited at a high level of generality and is nothing more than a deep learning neural network that is well known as suggested in par. 0076-0078 of the published application.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, there are no structures claimed.
Regarding dependent claims 4-7, the limitations of claim 1 further defines the limitations already indicated as being directed to the abstract idea.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 and 4-8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 1 recites the limitation "the in vitro model graphs" in lines 11-12. There is insufficient antecedent basis for this limitation in the claim.
Claim Objections
Claim 1 is objected to because of the following informalities: the phrases “in vitro” and “in vivo”, throughout claim 1, are italicized in the latest claim set, but were not italicized in the claims as originally filed. Appropriate correction is required.
Claim 8 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 1. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m). Since claim 1 requires “a CNN-LSTM neural network”, in the only mention of “neural network” in the claims as amended, and claim 8 requires “the neural network is long short-term memory network (CNN-LSTM)”, claim 8 is not considered to further limit claim 1.
Claim Rejections - 35 USC § 103
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.
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.
Claims 1, 4-5 and 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Howard (U.S. 2019/0381314) in view of Koller et al (U.S. 2021/0366577). Regarding claims 1 and 8, Howard discloses (par. 0080-0083) (a) measuring in vivo physiologic and behavioral characteristics of a living subject to obtain non-invasive data (“With multimodal, multiscale data and corresponding analysis methods, it is possible to build the structural and functional mapping from peripheral stimulation, to brain activity, and to behavioral output.”); (b) establishing an in vitro cell model of a cellular network, exposing the in vitro cell model to a condition(s) to model a cellular environment in the living subject, and measuring cellular changes to obtain in vitro model data (“data from in vitro and in vivo may be analyzed using intracellular and extracellular recordings to measure plasticity on a cellular/neuronal level and develop anatomical and functional mapping by using cellular imaging data as well as electrode electrophysiological data. Here neural plasticity refers to changes in spiking activity or dendritic spine density.”); (c) transforming the non-invasive data to functional graphs (par. 0204 and 0206, especially “Graph theoretical analysis with peripheral stimulation, brain activity, and behavioral output. Graph theoretical analysis of structural and functional systems: with multimodal brain activity and big behavioral data, we will focus on graph theoretical approaches to the analysis of complex networks that could provide a powerful new way of quantifying the brain's structural and functional systems, thus to enhance cognitive skill learning in healthy adults by using noninvasive peripheral neurostimulation to promote synaptic plasticity in the brain.”); (d) transforming the in vitro model data to functional graphs (see previous citation); and (e) integrating the non-invasive graphs and the in vitro model graphs using a neural network (previous citation and par. 0151) that identifies brain activity patterns predictive of neural plasticity and enables closed-loop neurostimulation adjustment (par. 0092); and (f) using the integrated non-invasive and in vitro model graphs to identify patterns in brain activity of the living subject. (par. 0138).
Howard discloses the claimed invention except for a CNN-LSTM and cell-network analysis software. Koller, however, discloses (par. 0257) generating machine learning models including CNN and LSTM models. Koller and Howard both disclose systems of gathering and analyzing data using neural network models. Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to modify Howard’s topological and/or functional graphs with Koller’s CNN-LSTM models in order to differentiate between artifact differences and intrinsic data for more accurate reporting (par. 0580 of Koller). Koller also discloses use of cell-network analysis software (par. 0415 and 0430) for analyzing image data of the cells. Therefore 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’s close-loop stimulation with Koller’s cell-network analysis software in order to provide another tool for more accurate analysis.
Regarding claim 4, Howard discloses (par. 0204) the non-invasive data comprises at least bio-electrical patterns (“With neural and behavioral data we will analyze the structural and functional systems using graph theory. Closed-loop neurostimulation will be correlated with EEG recording, behavioral measures and cognitive skill training performance to automatically adjust level of peripheral neurostimulation while the training is underway for real time optimization.”).
Regarding claim 5, Howard discloses (par. 0204) bio-electrical patterns comprise electroencephalograms (“With neural and behavioral data we will analyze the structural and functional systems using graph theory. Closed-loop neurostimulation will be correlated with EEG recording, behavioral measures and cognitive skill training performance to automatically adjust level of peripheral neurostimulation while the training is underway for real time optimization.”).
Regarding claim 7, Howard discloses (par. 0074) non-invasive imaging comprises biomarker analysis of a blood sample (“We may use Calcium imaging to measure changes in neural activity and demonstrate that VNS promotes synaptic plasticity.”).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Howard in view of Koller et al (U.S. 2021/0366577) and in further view of (U.S. 2019/0381314) in view of Werblin et al (U.S. 5,717,834). Howard and Koller disclose the claimed invention except for the non-invasive imaging comprises retinal scans. Werblin, however, discloses (col. 2, lines 34-65) a bionic sensor for generating models of a retina using a neural network. Werblin, Koller and Howard both disclose methods of generating models using physiologic and cell changes. Therefore it would have been obvious to one of ordinary skill in the art at the time of the invention to modify Koller and Howard’s brain model with Werblin’s retinal imaging scan in order to provide treatment to visual processing disorders ( “These retinas, and other sensory organs, not only respond in specific ways to the sensory input, but they adjust their responsive properties to match the environment and the objective of the animal. All of these functions and the adjustments in function performed by biological sensors are also implementable in a CNN universal machine through its analogic (analog and logical) programming capability.”).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEBORAH L MALAMUD whose telephone number is (571)272-2106. The examiner can normally be reached Mon - Fri 1:00-9:30 Eastern.
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/DEBORAH L MALAMUD/Primary Examiner, Art Unit 3792
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