DETAILED ACTION
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
Priority
Applicant's arguments filed 2/19/26 (“Remarks”) have been fully considered but they are not persuasive. Applicant argues that the ‘411 App provides support for the subject matter of claim 25 by citing to alleged support “in the specification at page 22 lines 15-16.” Remarks at 13. Applicant appears to confuse the subject matter disclosed in the specification of the present application (filed 10/10/22) with the specification of the ‘411 App (filed 10/13/21). The specification of the ‘411 App at page 22, lines 15-17 states:
The term "data processing apparatus" refers to data processing hardware and encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers.
The citation from page 22, lines 15-16 of the specification of the ‘411 App does not provide any support for or contain any disclosure of the features recited in claim 25, lines 4-5. Therefore, Applicant’s arguments are not persuasive.
35 U.S.C. 112(a) Rejections
Applicant's arguments filed 2/19/26 have been fully considered but they are not persuasive. Applicant argues that the specification of the present application (filed 10/10/22) at page 22 lines 15-16 “stating: ‘This information can be useful to guide the treatment to be an activation or deactivation stimulation burst’” provides support for the subject matter of claim 25, lines 4-5. Remarks at 13-14. As stated in the Non-Final Rejection mailed 10/28/25 (“NF”) at 3, Applicant
does not address that there is no disclosure of the method or means by which contribution values guide a treatment plan in selecting between an activation or deactivation stimulation burst.
Further, as presented in the NF at 9:
The originally filed disclosure is limited to the ability of clinicians to “design an effective treatment plan” upon viewing the output contribution information (P.2, lines 6-21 and P.22, line 29 – P.23, line 7) and that the contributions “can be useful to guide the treatment to be an activation or deactivation stimulation burst” (P.22, lines 15-16).
Applicant does not provide argument or evidence that the alleged usefulness would demonstrate to a PHOSITA that the Applicant in fact possessed a means or method by which the output information guides the selection of an activation or deactivation stimulation burst. That the output information can be useful, i.e., is capable of use, for selecting between an activation or deactivation stimulation burst, only provides explicit support for the output of the useful information itself. What it does not provide support for, and the claim positively recites, is a method step “to guide the treatment plan to be an activation stimulation burst or a deactivation stimulation burst.” (claim 25, lines 4-5). Such a method step is not disclosed.
In arguendo, even accepting Applicant’s argument, which the Office does not, that “the specification enables outputting information to guide a treatment for the symptom” (Remarks at 13-14), analysis of written description under 35 U.S.C. 112(a) is not akin to analysis of enablement under 35 U.S.C. 112(a). MPEP 2163 I. states:
35 U.S.C. 112(a) and the first paragraph of pre-AIA 35 U.S.C. 112 require that the "specification shall contain a written description of the invention ...." This requirement is separate and distinct from the enablement requirement. Ariad Pharm., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1340, 94 USPQ2d 1161, 1167 (Fed. Cir. 2010) (en banc); Vas-Cath, Inc. v. Mahurkar, 935 F.2d 1555, 1560, 19 USPQ2d 1111, 1114 (Fed. Cir. 1991); see also Univ. of Rochester v. G.D. Searle & Co., 358 F.3d 916, 920-23, 69 USPQ2d 1886, 1890-93 (Fed. Cir. 2004) (discussing the history and purpose of the written description requirement); In re Curtis, 354 F.3d 1347, 1357, 69 USPQ2d 1274, 1282 (Fed. Cir. 2004) ("conclusive evidence of a claim’s enablement is not equally conclusive of that claim’s satisfactory written description"). Emphasis added.
That a PHOSITA allegedly has knowledge that enables the PHOSITA in light of the Applicant’s specification to bridge the gap between the disclosed output information and a method step “to guide the treatment plan to be an activation stimulation burst or a deactivation stimulation burst,” i.e., the PHOSITA is capable of developing a method step that selects between an activation or a deactivation stimulation burst based on the output information (the output information being disclosed by the Applicant), does not answer whether the Applicant possessed such a method as of the filing date of the originally filed specification (10/10/22). See also the discussion of the lack of support in the ‘411 App from which the Applicant claims priority above, infra, and in the NF at 2 and 8. Merely espousing the usefulness of output information is not sufficient to establish possession of the explicit method step.
Therefore, Applicant’s argument is not persuasive.
35 U.S.C. 112(b) Rejections
Applicant’s arguments, see Remarks and Amended Claim Set, filed 2/19/26, with respect to the rejection of claims 15-18 have been fully considered and are persuasive. The rejection of claims 15-18 have been withdrawn.
35 U.S.C. 103 Rejections
Applicant’s arguments, see Remarks and Amended Claim Set, filed 2/19/26, with respect to the rejection of claims 1-20 and 24-25 have been fully considered and are persuasive. The rejection of claims 1-20 and 24-25 have been withdrawn and claims 4-6 and 13 are cancelled.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 63/255,411 (the “‘411 app”), fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application
Claim 1, lines 32-33 recites “indicate the position of the connectivity value of the at least one brain parcellation pair of the patient within a distribution.” Emphasis added. There does not appear to be disclosure in the ‘411 app for a distribution additional to the first and second distributions, i.e., a third distribution. Page 21, lines 11-22 of the specification of the ‘411 App only contains support for “a first distribution of connectivity values across a population that does not have the symptom” and “a second distribution of connectivity values across a population that does have the symptom.”
Independent claim 10, lines 36-37, independent claim 14, lines 34-35, independent claim 15, lines 31-32, independent claim 19, lines 35-36, and independent claim 20, lines 33-34 recite similar subject matter and the ‘411 App similarly fails to provide adequate support upon substantially the same grounds as set forth above for independent claim 1, lines 32-33.
The ‘411 App fails to provide adequate support for the subject matter of claims 1-3, 7-9, 11-12, 16-18, and 24-31 as depending from the corresponding independent claims.
Furthermore, claim 25, lines 4-5 recites “outputting information to a clinician to guide the treatment plan to be an activation stimulation burst or a deactivation stimulation burst.” The disclosure of the ‘411 app is limited to the ability of clinicians to “design an effective treatment plan” upon viewing the output contribution information (P.2, lines 1-7 and P.21, lines 23-31). There is no support for “guid[ing] the treatment plan to be an activation stimulation burst or a deactivation stimulation burst” in the ‘411 app.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-3, 7-12, 14-20, and 24-31 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claim 1, lines 32-33 recites “indicate the position of the connectivity value of the at least one brain parcellation pair of the patient within a distribution.” Emphasis added. Claim 1, lines 20-25 recites:
determining, for at least one brain parcellation pair of the patient, a position of the connectivity value of the brain parcellation pair of the patient within either a first distribution of connectivity values or a second distribution of connectivity values, wherein the first distribution of connectivity values is specified for the brain parcellation pair across a population having the particular condition, and the second distribution of connectivity values is specified for the brain parcellation pair across a population not having the particular condition. Emphasis added.
Lines 32-33 appears to recite “a distribution” distinct from the “first distribution” and “second distribution” recited in lines 20-25. There does not appear to be support in the Applicant’s originally filed specification (filed 10/10/22) for a distribution additional to the first and second distributions, i.e., a third distribution. Page 22, lines 3-14 of the originally filed specification only contains support for “a first distribution of connectivity values across a population that does not have the symptom” and “a second distribution of connectivity values across a population that does have the symptom”
It appears that Applicant may have intended the recited “a distribution” to refer back to one of the “first distribution” or the “second distribution” as recited in claim 1, lines 20-25 given that, for example, the specification at page 22, lines 10-12 states “the connectivity value of 0.14 is positioned in the distribution of the population that does not have the symptom.” This further appears to be the intent given the recitation of similar subject matter in claim 6 in the previous claim set filed 9/23/25 that is cancelled in the present claim set filed 2/19/26 reciting “within the first distribution or the second distribution.”
Independent claim 10, lines 36-37, independent claim 14, lines 34-35, independent claim 15, lines 31-32, independent claim 19, lines 35-36, and independent claim 20, lines 33-34 recite similar subject matter and are rejected upon substantially the same grounds as set forth above for independent claim 1, lines 32-33.
Claims 1-3, 7-9, 11-12, 16-18, and 24-31 are rejected as depending from the corresponding independent claims.
Further, claim 25 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
There is no disclosure of “guid[ing] the treatment plan to be an activation stimulation burst or a deactivation stimulation burst” in the originally filed specification, claims, and drawings. The originally filed disclosure is limited to the ability of clinicians to “design an effective treatment plan” upon viewing the output contribution information (P.2, lines 6-21 and P.22, line 29 – P.23, line 7) and that the contributions “can be useful to guide the treatment to be an activation or deactivation stimulation burst” (P.22, lines 15-16). For example, there is no disclosure of the method or means by which contribution values guide a treatment plan in selecting between an activation or deactivation stimulation burst.
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 1-3, 7-12, 14-20, and 24-31 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.
Independent claim 1, lines 32-33 recites “indicate the position of the connectivity value of the at least one brain parcellation pair of the patient within a distribution.” Emphasis added. Claim 1, lines 20-25 recites:
determining, for at least one brain parcellation pair of the patient, a position of the connectivity value of the brain parcellation pair of the patient within either a first distribution of connectivity values or a second distribution of connectivity values, wherein the first distribution of connectivity values is specified for the brain parcellation pair across a population having the particular condition, and the second distribution of connectivity values is specified for the brain parcellation pair across a population not having the particular condition. Emphasis added.
It is unclear if the recited “a distribution” recited in lines 32-33 is distinct from the “first distribution” and “second distribution” recited in lines 20-25, i.e., a third distribution. As discussed above regarding the rejection under 35 U.S.C. 112(a), Applicant appears to have intended “a distribution” to refer back to the “first distribution” and the “second distribution.” For purposes of examination, the recitation of “a distribution” is treated as encompassing the “first distribution” and the “second distribution” as alternatives to one another depending on whether the connectivity is within one of the first distribution or the second distribution.
Independent claim 10, lines 36-37, independent claim 14, lines 34-35, independent claim 15, lines 31-32, independent claim 19, lines 35-36, and independent claim 20, lines 33-34 recite similar subject matter and are rejected upon substantially the same grounds as set forth above for independent claim 1, lines 32-33.
Claims 1-3, 7-9, 11-12, 16-18, and 24-31 are rejected as depending from the corresponding independent claims.
Allowable Subject Matter
Claims 1-3, 7-12, 14-20, and 24-31 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, and 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chun et al. (“Visualizing functional network connectivity difference between healthy control and major depressive disorder using an explainable machine-learning method” 2020), discloses a method (methods, P.1424) comprising:
receiving brain data for a brain of a patient (brain fMRI dataset, P.1424-1425, Fig. 1);
processing the brain data to determine a partition of the data into a plurality of brain parcellation pairs (brain fMRI dataset is partitioned into a plurality of independent components and domains wherein the functional network connectivity between each pair of independent components and domains are calculated as a correlation matrix, P.1425, Figs. 1, 4), wherein the volume of each parcellation of each brain parcellation pair is smaller than 50 cubic millimeters (brain is divided into 3x3x3 mm, i.e., 9 cubic millimeter, voxel volumes, P.1425), and wherein the size of each brain parcellation of each brain parcellation pair is no larger than 1/12 of a brain hemisphere of the brain of the patient (the brain is divided into 53 independent components, i.e., each component is at most 1/53 of the brain or 2/53 of a brain hemisphere, P.1425);
receiving, from the user, an indication of a particular condition for the patient (the authors select major depressive disorder for study, P.1424-1425, Fig. 1);
determining a plurality of contribution values for the plurality of brain parcellation pairs (determine Shapley values for the pairs of independent components and domains, P.1425-1426, Figs. 1, 3, 4), wherein each of the plurality of contribution values characterizes a contribution of the brain parcellation pairs to the particular condition (each Shapley value characterizes the contribution of each of the pairs of independent components and domains to major depressive disorder, P.1424-1426, Figs. 1, 3, 4);
processing the brain data of the brain of the patient to determine a connectivity value for each of the brain parcellation pairs of the patient (brain fMRI dataset is partitioned into a plurality of independent components and domains wherein the functional network connectivity between each pair of independent components and domains are calculated as a correlation matrix, P.1425, Figs. 1, 4), wherein the connectivity value for the brain parcellation pair characterizes blood flow or blood oxygen level over time in regions of the brain represented by the brain parcellation pair (brain resting state functional MRI (fMRI) functional connectivity represents brain blood flow and oxygenation level, i.e., functional activation of regions of the brain due to changes in blood flow and blood oxygenation level in response to neural activity, P.1424-1425; see also Elster “fMRI Overview” evidencing that resting state fMRI captures functional activation of regions of the brain due to changes in blood flow and blood oxygenation level in response to neural activity);
determining, for each brain parcellation pair of the patient, a position of the connectivity value of the brain parcellation pair of the patient within either a first distribution of connectivity values or a second distribution of connectivity values (brain fMRI dataset is partitioned into a plurality of independent components and domains wherein the functional network connectivity between each pair of independent components and domains are calculated as a correlation matrix, and wherein the functional network connectivity is placed within either the major depressive disorder population or the healthy control population, P.1424-1426, Figs. 1, 3, 4), wherein the first distribution of connectivity values is specified for the brain parcellation pair across a population having the condition, and the second distribution of connectivity values is specified for the brain parcellation pair across a population not having the condition (brain fMRI dataset is partitioned into a plurality of independent components and domains wherein the functional network connectivity between each pair of independent components and domains are calculated as a correlation matrix, and wherein the functional network connectivity is placed within either the major depressive disorder population or the healthy control population, P.1424-1426, Figs. 1, 3, 4);
providing contribution value data for visualization (Shapley values for the pairs of independent components and domains is displayed as a feature importance list and visualization, Figs. 1, 3, 4) on a user computing device (MATLAB2019 or Python environment, i.e., a software environment on a computer, P.1425), wherein the visualization is configured to:
display the contributions of the one or more corresponding brain parcellation pairs of the plurality of brain parcellation pairs to the particular condition based on (i) the contribution values corresponding to the plurality of brain parcellation pairs and (ii) the indication of the particular condition (Shapley values for the pairs of independent components and domains is displayed as a feature importance list and visualization, wherein each Shapley value characterizes and corresponds to the contribution of each of the pairs of independent components and domains to the indicated condition by the authors of major depressive disorder, P.1424-1426, Figs. 1, 3, 4), and
indicate the position of the at least one parcellation pair of the patient within a distribution (brain fMRI dataset is partitioned into a plurality of independent components and domains wherein the functional network connectivity between each pair of independent components and domains are calculated as a correlation matrix, and wherein the functional network connectivity is placed within either the major depressive disorder population or the healthy control population and is visualized as a list or map, P.1424-1426, Figs. 1, 3, 4); and
outputting information to a clinician to guide a treatment plan for the indicated condition based on the contribution value data (understanding the underlying mechanisms of major depressive disorder by using a SHAP approach to find a subset of the most important features that contribute to the classification of major depressive disorder improves/informs treatment, P.1424, ¶3-4; Shapley values for the pairs of independent components and domains is displayed as a feature importance list and visualization, Figs. 1, 3, 4).
Kim et al. (U.S. Pub. No. 2023/0334657) discloses providing user interface data for presentation to a user, wherein the user interface data is configured to allow a user to indicate a particular condition from the plurality of conditions for evaluation for the patient (user input selects the brain disease to be diagnosed from a plurality of brain diseases that may be diagnosed, [0059], [0069], see also [0056]-[0058], [0070]-[0071]; a user input interface including a touch screen receives input and commands from the user, [0074]); and
receiving, from the user, an indication of the particular condition for the patient from the plurality of conditions (user input selects the brain disease to be diagnosed from a plurality of brain diseases that may be diagnosed, [0059], [0069], see also [0056]-[0058], [0070]-[0071]; a user input interface including a touch screen receives input and commands from the user, [0074]).
Li et al. (“Efficient Shapley explanation for features importance estimation under uncertainty” 2020) discloses determining SHAP contribution values for a machine learning classifier of Autism Spectrum Disorder using a connectivity matrix of resting state fMRI data of the brain that comprises 110 parcellation pairs wherein the functional network connectivity between each pair of ROIs are calculated as a connectivity matrix of 5995 features.
Li et al. (“Efficient interpretation of deep learning models using graph structure and cooperative game theory: application to ASD biomarker discovery” 2019) discloses determining SHAP contribution values for a machine learning classifier of Autism Spectrum Disorder using a connectivity matrix of task based fMRI data of the brain that comprises 116 parcellation pairs of 47.33 cubic millimeters.
Pang et al. (“Use of machine learning method on automatic classification of motor subtype of Parkinson’s disease based on multilevel indices of rs-fMRI” 2021) discloses determining SHAP contribution values for a machine learning classifier of Parkinson’s disease using a connectivity matrix of resting state fMRI data of the brain this information being used to define an individualized targeted treatment plan.
El-Sappagh et al. (“A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease” 2021) discloses determining SHAP contribution values for a machine learning classifier of Alzheimer’s disease using a connectivity matrix of resting state fMRI data of the brain.
Sendi et al. (“Visualizing functional network connectivity difference between middle adult and older subjects using an explainable machine-learning method” 2020) discloses determining SHAP contribution values for a machine learning classifier of aging using a connectivity matrix of resting state fMRI data of the brain.
Shen et al. (“Use of machine learning to identify functional connectivity changes in a clinical cohort of patients at risk for dementia” 2022) discloses determining SHAP contribution values for a machine learning classifier of dementia and Alzheimer’s disease using a connectivity matrix of resting state fMRI data of the brain this information being used to define an individualized targeted treatment plan.
Hope et al. (“Phybrata sensors and machine learning for enhanced neurophysiological diagnosis and treatment” 2021) discloses determining SHAP contribution values for a machine learning classifier of concussion and cognitive impairment this information being used to define an individualized targeted treatment plan.
Siddiqi et al. (U.S. Pub. No. 2023/0414959) discloses determining connectivity values from a machine learning classifier of brain conditions, symptoms, behaviors, or combinations thereof this information being used to define an individualized targeted treatment plan using activation or deactivation stimulation bursts.
Williams et al. (U.S. Pub. No. 2022/0110694) discloses determining connectivity values of brain conditions this information being used to define an individualized targeted treatment plan using transcranial magnetic stimulation bursts.
Elster (“fMRI Overview 2020) discloses that resting state fMRI captures functional activation of regions of the brain due to changes in blood flow and blood oxygenation level in response to neural activity.
Rodriguez-Perez et al. (“Interpretation of compound activity predictions from complex machine learning models using local approximations and Shapley values” 2019) discloses the most important SHAP value features can be defined using an absolute SHAP value threshold or the number of top-ranked features.
Williams et al. (U.S. Pub. No. 2019/0217116) discloses personalized accelerated theta burst stimulation (aTBS) treatment targeting based on functional connectivity value information, Abstract, [0052], [0074], [0076]-[0077]; aTBS applied to produce excitation, i.e., activation, or inhibition, i.e., deactivation, [0053]; aTBS provided to deactivate neurological activity, [0086]-[0087]; see also display and user interface, [0057]-[0063].
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.
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/J.M./Examiner, Art Unit 3798
/KEITH M RAYMOND/Supervisory Patent Examiner, Art Unit 3798
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