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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 3/24/2026 has been entered.
Applicant's response, filed 7/2/2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Claim Status
Claims 2, 6-9, 12-14, and 16 are pending.
Claims 3-5, 10-11, and 15 are cancelled.
Claims 2, 6-9, 12-14, and 16 are rejected.
Withdrawn Rejections/Objections
The objection to the specification in the Office Action mailed 4/7/2026 is withdrawn in view of the amendments filed 7/2/2026.
The claim interpretation described in the Office Action mailed 4/7/2026 is withdrawn in view of the amendments filed 7/2/2026.
The rejection of claims 26-30 under 35 U.S.C. §112(a) in the Office action mailed 4/7/2026 is withdrawn in view of the amendments filed 7/2/2026.
Specification
Response to Amendment
In view of applicant’s amendments to the specification, previous objections to the specification over the use of embedded hyperlinks is withdrawn.
Claim Interpretation
In view of applicant’s amendments to the claims, previous claim interpretation of limitations described using “means” or other substitutive verbiage are withdrawn.
Claim Rejections - 35 USC § 112
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections under 35 U.S.C. 112 have been withdrawn.
Claim Rejections - 35 USC § 101
Response to Amendment
In view of applicant’s amendments to the specification the previously withdrawn rejection under 35 U.S.C. 101 is reinstated, specifically in regards to the removal of the active administration of a specific therapy.
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 2, 6-9, 12-14, and 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite a method of diagnosing and predicting sustained pain and determining the effect of relieving the pain via the calculation of a signature response from a specific subset of biomarkers. The judicial exception is not integrated into a practical application because while claims 22, 6-9, 12-14, and 16 attempt to integrate the exception into a practical application, said application is either generically recited computer elements that do not add a meaningful limitation to the abstract idea or it is insignificant extra solution activity and simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer elements only store and retrieve information in memory as well as perform basic calculations that are known to be well-understood, routine and conventional computer functions as recognized by the decisions listed in MPEP § 2105.05(d).
Framework with which to Analyze Subject Matter Eligibility:
Step 1: Are the claims directed to a category of statutory subject matter (a process, machine,
manufacture, or composition of matter)? [see MPEP § 2106.03]
Claims are directed to statutory subject matter, specifically a system (claims 2, 6, 12-13, and 16) and a method (claims 7-9, 14).
Step 2A Prong One: Do the claims recite a judicially recognized exception, i.e., an abstract idea, a law of nature, or a natural phenomenon? [see MPEP § 2106.04(a)]
The claims herein recite abstract ideas, specifically mental processes and mathematical concepts.
With respect to the Step 2A Prong One evaluation, the instant claims are found herein to recite abstract ideas that fall into the grouping of mental processes and mathematical concepts.
Claims 2, 7, and 12: Diagnosing sustained pain in a subject, analyzing the received brain image data, and calculating a signature response are processes of identifying, comparing/contrasting, and computing that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes. Calculating a signature response, and the signature response being calculated by equation 1, with the specified variables and weight values of tables 3 and 4 is a verbal articulation of a mathematical process and is therefore an abstract idea, specifically a mathematical concept. The subject comprising a healthy subject with the specified diseases, the values corresponding to brain connectivity pairs listed in tables 1 and 2, and tables 1 and 2 representing connectivity pairs with the corresponding pain values is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 6: The sustained pain lasting for 10 seconds or more is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 8: Determining that a subject feels increased pain based upon increasing connectivity of brain connectivity pairs in table 1 is a process of comparing/contrasting and computing information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 9: Determining that a subject feels pain based upon decreasing connectivity of brain connectivity pairs in table 2 is a process of comparing/contrasting and computing information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 13: The subject being categorized as belonging to one of the specified criteria is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 14: The subject being categorized as one of the categories provided is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 16: The subject being categorized as belonging to one of the specified criteria is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Step 2A Prong Two: If the claims recite a judicial exception under prong one, then is the judicial exception integrated into a practical application? [see MPEP § 2106.04(d) and MPEP § 2106.05(a)-(c) & (e)-(h)]
Because the claims do recite judicial exceptions, direction under Step 2A Prong Two provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application. However, claims 11 and 15 do not recite any additional elements and therefore cannot integrate the JE into a practical application.
The following claims recite the following additional elements in the form of non-abstract elements:
Claims 2, 7, and 12: A receiver, analyzer, and calculator are generic and nonspecific elements of a computer that do not improve the functioning of any computer or technology described herein [See MPEP § 2106.04(d)(1) and MPEP § 2106.05(d)]. Applying a stimulus and receiving brain image data is an insignificant extra solution activity, specifically mere data gathering (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. V. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. V. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive
concept? [see MPEP § 2106.05]
Because the additional claim elements do not integrate the abstract idea into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept.
The claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that are generic, conventional, nonspecific and insignificant extra solution activity. Additionally, claims 11 and 15 do not recite any additional elements and therefore cannot integrate the JE into a practical application. These additional elements include:
The additional elements of receiver (Conventional: Specification page 26 and 27 paragraphs 5 and 1-2 respectively), analyzer (Conventional: Specification page 24 paragraph 3), and calculator (Conventional: page 24 paragraph 4) are generic and nonspecific elements of a computer that are well-understood, routine and conventional within the art and therefore do not improve the functioning of any computer or technology described therein (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values), and Storing and retrieving information in memory, Versata Dev. Group, Inc. V. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)) [See § MPEP 2106.05(d)(II)]. Therefore, taken both individually and as a whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
The additional elements of applying a stimulus (Conventional: Gore et al. 2003 – Previously Cited), receiving brain image data (Conventional: Specification Page 27, paragraph 1 - if the component that is intended to receive information is well-known within the art so too is what it is used for), brain image data comprising MRI data (Conventional: Gore et al. 2003 – Previously Cited), are insignificant extra solution activities, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. V. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. Therefore, taken both individually and as a whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
Therefore, claims 2, 6-9, 12-14, and 16, when the limitations are considered individually and as a whole, are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
Response to Amendment
In view of applicant’s amendments previous rejections under 35 U.S.C. 103 have been withdrawn and a new examination of the claims under 35 U.S.C. 103 is provided below.
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.
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.
Claims 2, 6-9, 12-14, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (British Journal of Anaesthesia (2013) 64-72; previously cited), Owen et al. (JAMA Neurology (2007) 1-9; previously cited), Kim et al. (Pain (2013) 1343-1351; previously cited), and Bittar et al. (Journal of clinical neuroscience (2005) 515-519; newly cited).
Claim 2 is directed to a system for diagnosing sustained pain using brain image data, an analyzer and calculator along with the biomarker composition from tables 1 and 2.
Claim 7 is directed to a system for diagnosing sustained pain using brain image data collected while applying a stimulus, an analyzer and calculator along with the biomarker composition from tables 1 and 2.
Claim 12 is directed to a system for diagnosing sustained pain and determining the effect of relieving said pain, using brain image data collected while applying a stimulus, an analyzer and calculator along with the biomarker composition from tables 1 and 2.
Lee et al. teaches on page 64, column 2, paragraph 2 “Functional magnetic resonance imaging (fMRI), positron emission tomography (PET), magnetoencephalography (MEG), and scalp electroencephalography (EEG) are commonly used to study the neural bases of pain”, in the abstract “Chronic pain is a state of physical suffering strongly associated with feelings of anxiety, depression and despair. Disease pathophysiology, psychological state, and social milieu can influence chronic pain, but can be difficult to diagnose based solely on clinical presentation. Here, we review brain neuroimaging research that is shaping our understanding of pain mechanisms, and consider how such knowledge might lead to useful diagnostic tools for the management of persistent pain in individual patients”, on page 66, column 1, paragraph 2 “Dynamic causal modelling and structural equation modelling are analytical methods that have the potential to further our understanding of pain. These techniques use data from EEG, MEG, fMRI, or PET studies to investigate brain dynamics and cortical coupling”, on page 64, column 2, paragraph 3 “Neuroimaging studies have now identified several cortical regions in humans that are considered to be important for the perception of pain. The primary and secondary somatosensory cortices (insular and anterior cingulate) and the prefrontal cortices (PFCs) are commonly activated, often bilaterally, and during painful experiences. Furthermore, altered activity in subcortical areas (e.g. brainstem periaqueductal grey (PAG), hypothalamus, amygdala, hippocampus, and cerebellum) is also” with subcortical areas being all those brain regions located below the cerebral cortex (the outside layer or first layer of the brain), reading on wherein the subject comprises one of a healthy subject with sustained pain, a subject with subacute or chronic pain, receiving brain image data of the subject from a scanner, wherein the signature response corresponds to the sustained pain, and the brain connectivity regions of Tables 1 and 2.
Owen et al. teaches in the abstract “Recent advances in functional neuroimaging suggest a novel solution to this problem; in several cases, so-called activation studies have been used to identify residual cognitive function and conscious awareness in patients who are assumed to be in a vegetative state yet retain cognitive abilities that have evaded detection using standard clinical methods…Unlike resting blood flow and glucose metabolism, which provide markers of neural capacity and potential so-called activation methods such as radioactive water positron emission tomography and functional magnetic resonance (fMRI) imaging can be used to link residual neural activity to the presence of covert cognitive function”, reading on a subject having difficulty in reporting pain.
Kim et al. teaches on page 1345, column 1, paragraph 1 “The electrocardiogram data were collected with an MRI-compatible Patient Monitoring system”, reading on a receiver configured to receive brain image data of a subject from a scanner. Kim et al. teaches on page 1345, paragraph 2 “fMRI data were preprocessed using the validated FSL, AFNI, and FreeSurfer software packages” and in paragraph 4 “Functional connectivity MRI analysis was performed using the validated dual-regression independent component analysis”, reading on analyze the received brain image data obtain a plurality of brain functional connectivity values corresponding to the brain connectivity pairs ranked from 1 to 39 listed in Table 1 and Table 2. Kim et al. teaches on page 1345, column 1, paragraph 5 “This approach consists of 3 stages. First, a probabilistic ICA was applied on concatenated, preprocessed functional data from both REST and PAIN runs from all subjects… In the second stage, these independent spatial maps were used in a general linear model as a spatial regressor for each individual subject… In the third stage of dual regression, this fMRI time series from each subject was variance normalized and used in a subject-level general linear model to reconstruct spatial maps for each subject”, reading on a calculator for calculating a signature response, by applying corresponding predetermined weights listed in Table 3 and Table 4 to the plurality of brain functional connectivity values according to Equation 1, the signature response quantifying the sustained pain experienced by the subject. Kim et al. teaches on page 1344, column 2, paragraph 6 “Functional MRI (fMRI) data were acquired using a 3T Siemens TIM Trio MRI system”, reading on a magnetic resonance imaging (MRI) scanner. Kim et al. teaches on page 1345, column 1, paragraph 4 “Functional connectivity MRI analysis was performed using the validated dual-regression independent component analysis” and on page 1346, column 1, paragraph 2 “…we performed a linear regression…”, which reads on equation 1 as it is merely a sum of weighted regions of the brain, which is essentially the right side of a regression. Furthermore, it would have been obvious to optimize the weights and parameters associated with the model as it is merely a regression framework which inherently fits a best fit line according to the data by modifying the specified weights of each feature (brain connectivity region), thereby reading on wherein n is an integer of 1 to 39, wherein i is an integer of n or less, wherein wi is a weight corresponding to the brain functional connectivity of #i, and xi is test data corresponding to the brain functional connectivity of #i,wherein the wi is a weight corresponding to the brain functional connectivity of #i, listed in Table 3 and Table 4. It should be noted that while Kim et al. does not directly teach the weights given in tables 3 and 4, these are obvious optimizations as a person having ordinary skill in the art at the time of invention would optimize the weights used in the linear model (See Kim et al. page 1345, column 2, paragraph 2 “this fMRI time series from each subject was variance normalized and used in a subject-level general linear model”) to achieve the highest accuracy of the output (“signature response”).
Bittar et al. teaches in the abstract “Deep brain stimulation (DBS) has been used to treat intractable pain for over 50 years…To better understand its efficacy, we performed a meta-analysis of DBS for pain relief…The long-term pain alleviation rate was highest with DBS of the PVG/PAG (79%), or the PVG/PAG plus sensory thalamus/internal capsule (87%). Stimulation of the sensory thalamus alone was less effective (58% long-term success) (p < 0.05). DBS was more effective for nociceptive than deafferentation pain (63% vs 47% long-term success; p < 0.01). Long-term success was attained in over 80% of patients with intractable low back pain (failed back surgery) following successful trial stimulation. Trial stimulation was successful in approximately 50% of those with post-stroke pain, and 58% of patients permanently implanted achieved ongoing pain relief. Higher rates of success were seen with phantom limb pain and neuropathies. We conclude that DBS is frequently effective when used in well-selected patients”, reading on and output information for customizing brain stimulation to reduce the sustained pain of the subject based on the signature response.
It would have been obvious at the time of invention to a person skilled within the art to modify the teachings of Lee et al. for using brain image data on specific regions of the brain to examine chronic pain with the teachings of Owen et al. for identifying residual cognitive function and conscious awareness in coma patients using brain image data, and the methods of Kim et al., specifically the correlated regions of the brain MRI data, and build a simple predictive or diagnostic model using the same regression framework outlined in Kim et al. using brain image data for examining pain in coma patients. This is because all three use the same or similar forms of data (brain image data: MRI, fMRI, etc.) and brain connectivity to examine the effects or presence of pain, and Owen et al. merely shows the ability to examine the presence of such while a patient is in a vegetive state. Furthermore, it would have been obvious to combine the teachings of Owen et al., Kim et al., and Lee et al., with the teachings of Bittar et al. for the application of brain stimulation for pain relief as the latter teaches in the abstract “We conclude that DBS is frequently effective when used in well-selected patients” as well as on page 519, column 1, paragraph 3 “DBS is an effective technique when used in well-selected patients with refractory chronic neuropathic or nociceptive pain. Although the treatment effect is more marked in patients with nociceptive pain, it is nonetheless substantial in patients with deafferentation pain”. One would have had a reasonable expectation of success given that each of the studies are within the same field and examining the same topic of associating brain regions with pain, except for Owen et al. which is merely showing that such studies can be done while a patient is in a coma. Additionally in regards Kim et al. the correlated regions were already identified, as were their effect sizes, and the same general method of regression could be used for prediction. Finally, there would have been a reasonable expectation of success for integrating the teachings of Bittar et al. as they describe within the abstract the treatment being used for over 50 years for the specified criteria. Therefore, it would be obvious to one with ordinary skill in the art to incorporate the teachings of each and to be successful.
Claim 6 is directed to the method of claim 2, but further specifies that the sustained pain lasts for 10 seconds or more.
Kim et al. teaches on page 1344, column 2, paragraph 4 “Subjects provided ratings for each of the 2-minute blocks at the beginning, middle, and end of the 6-minute procedure”, reading on the system of claim 2, wherein the sustained pain lasts for 10 seconds or more.
Claim 8 is directed to the method of claim 7 but further specifies determining that the subject feels more pain with increased connectivity in the regions listed in Table 1.
Lee et al. teaches on page 66, column 1, paragraphs 3-4 “Numerous imaging studies demonstrate that the PFC can regulate the perception and behavioral expression of pain in humans. The PFC is reciprocally connected to limbic regions and these connections form the neural substrates through which the motivational-emotional aspects of pain can be regulated…Frontal-limbic regions are reciprocally connected to the brainstem. This neuroanatomical connection presents another route through which pain can be controlled—via inhibition of neurones within the spinal cord that transmit nociceptive information to the brain. Distraction from pain has been shown to involve activity within the cingulo-frontal cortex, thalamus, and PAG and, more recently, suppression of spinal cord activity”, reading on determining that the subject feels increased pain in response to an increase in connectivity in the brain functional connectivity regions listed in Table 1.
Claim 9 is directed to the method of claim 7 but further specifies determining that the subject feels less pain with less connectivity in the regions listed in Table 2.
Lee et al. teaches on page 66, column 1, paragraphs 3-4 “Numerous imaging studies demonstrate that the PFC can regulate the perception and behavioral expression of pain in humans. The PFC is reciprocally connected to limbic regions and these connections form the neural substrates through which the motivational-emotional aspects of pain can be regulated…Frontal-limbic regions are reciprocally connected to the brainstem. This neuroanatomical connection presents another route through which pain can be controlled—via inhibition of neurones within the spinal cord that transmit nociceptive information to the brain. Distraction from pain has been shown to involve activity within the cingulo-frontal cortex, thalamus, and PAG and, more recently, suppression of spinal cord activity”, reading on determining that a subject feels pain the less the connectivity in Table 2 is present.
Claim 13 is directed to the system of claim 2 but further specifies that the subject be one of those listed in the provided grouping.
Claim 14 is directed to the method of claim 7 but further specifies that the subject be one of those listed in the provided grouping.
Claim 16 is directed to the system of claim 12 but further specifies that the subject be one of those listed in the provided grouping.
Owen et al. teaches in the abstract “Recent advances in functional neuroimaging suggest a novel solution to this problem; in several cases, so-called activation studies have been used to identify residual cognitive function and conscious awareness in patients who are assumed to be in a vegetative state yet retain cognitive abilities that have evaded detection using standard clinical methods…Unlike resting blood flow and glucose metabolism, which provide markers of neural capacity and potential so-called activation methods such as radioactive water positron emission tomography and functional magnetic resonance (fMRI) imaging can be used to link residual neural activity to the presence of covert cognitive function”, reading on wherein the subject is categorized as being one of a patient in a vegetative state, an aphasia patient, an elderly patient, and an infant.
Response to Arguments
Applicant's arguments filed 7/2/2026 have been fully considered but they are not persuasive.
Applicant asserts on page 24 of the Remarks filed 7/2/2026 that the cited references do not disclose constructing a connectivity-pair-specific weighted predictive model. However, examiner reminds applicant Lee et al. teaches page 64, column 2, paragraph 3 “Neuroimaging studies have now identified several cortical regions in humans that are considered to be important for the perception of pain. The primary and secondary somatosensory cortices (insular and anterior cingulate) and the prefrontal cortices (PFCs) are commonly activated, often bilaterally, and during painful experiences. Furthermore, altered activity in subcortical areas (e.g. brainstem periaqueductal grey (PAG), hypothalamus, amygdala, hippocampus, and cerebellum) is also” with Kim et al. teaching on page 1345, column 1, paragraph 4 “Functional connectivity MRI analysis was performed using the validated dual-regression independent component analysis”. While the specific invention is not taught by any one reference the use of multiple regression along with previous research isolating specific regions of the brain for determining pain, prediction of brain regions using regressions for diagnosing sustained pain would be obvious as these models are used primarily to model correlated and causal features with a specified outcome. Moreover, the models are machine learning models, capable of increased predictive power through optimization of input, features, and weights, meaning it would be obvious to a person skilled in the art to refine their model using the highest predictive features to obtain the most accurate weights for the prediction. Additionally, it should be noted that Kim et al. explicityly examines the role of brain connectivity in pain response “Connectivity in specific networks known to be modulated by evoked pain (sensorimotor, salience, dorsal attention, frontoparietal control, and default mode networks: SMN, SLN, DAN, FCN, and DMN) was evaluated with functional-connectivity magnetic resonance imaging, both at rest and during a sustained (6-minute) pain state in healthy adults”, and Owen et al. is specifically looking at “patients with disorders of consciousness, including the vegetative state” and “A question that is often asked of such studies is whether the presence of normal brain activation in patients who are diagnosed as being in a vegetative state indicates a level of conscious awareness, perhaps even similar to that which exists in healthy volunteers when performing the same tasks. Many types of stimuli, including faces, speech, and pain, will elicit automatic responses from the brain; that is to say, they will occur without the need for willful intervention on the part of the participant (eg, you cannot choose to not recognize a face or to not understand speech that is presented clearly in your native language). By the same argument, normal neural responses in patients who are diagnosed as being in a vegetative state do not necessarily indicate that these patients have any conscious experience associated with processing those same types of stimuli. Therefore, such patients may retain discreet islands of subconscious cognitive function that exist in the absence of awareness”. These references in context suggest that 1. Pain can be modeled from fMRI data via a linear model, 2. Pain alters and is altered by connectivity regions within the brain, and 3. fMRI can be used to examine responses of patients who are incapable of responding themselves.
Applicant further asserts that the connectivity pairs are not arbitrary. However, examiner reminds applicant this was never asserted by the examiner, rather Lee et al. teaching on page 64, column 2, paragraph 3 “Neuroimaging studies have now identified several cortical regions in humans that are considered to be important for the perception of pain. The primary and secondary somatosensory cortices (insular and anterior cingulate) and the prefrontal cortices (PFCs) are commonly activated, often bilaterally, and during painful experiences. Furthermore, altered activity in subcortical areas (e.g. brainstem periaqueductal grey (PAG), hypothalamus, amygdala, hippocampus, and cerebellum) is also” was asserted as motivation for the selection of various brain regions as potentially linked to sustained pain phenotypes.
Applicant asserts that there is a lack of reasonable expectation of success. However, examiner reminds applicant that the methods being used are all similar, routine and conventional methods that are well known for describing relationships and building precise models to accurately predict outcomes across the spectrum of scientific inquiry (basic regressions). Furthermore, these methods refine themselves, calculating weights based upon selected features that most accurately predict the outcomes in question.
Applicant asserts that Bittar et al. does not cure the deficiencies of Lee et al, Owen et al., and Kim et al., and that specifically Bittar et al. does not support the relationship between connectivity-pair model and customized stimulation information. However, examiner reminds applicant that Bittar et al. was never used to disclose the relationship between the connectivity-pair model and a customized stimulation information. Rather Bitter et al. functions as support for the use of brain stimulation as a therapy for pain, and being a meta-analysis shows its effectiveness over a range of settings. Furthermore, the examination of 1. Pain being modeled from fMRI data via a linear model (Lee et al.), 2. Pain altering and being altered by connectivity regions within the brain (Kim et al.), 3. fMRI being used to examine responses (including pain) of patients who are incapable of responding themselves (Owen et al.), and 4. Stimulation being an effective treatment for sustained pain (Bittar et al.), render obvious the instant application claims.
Conclusion
No Claims are allowed.
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 KEENAN NEIL ANDERSON-FEARS whose telephone number is (571)272-0108. The examiner can normally be reached M-Th, alternate F, 8-5.
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/K.N.A./ Examiner, Art Unit 1687
/LARRY D RIGGS II/ Supervisory Patent Examiner, Art Unit 1686
