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 .
Status of claims
The claim set received 25 November 2022 has been entered into the application.
Claim 10 is amended.
Claims 1 and 8-9 are objected to.
Claims 1-10 are pending
Priority
This Application is a 371 of PCT/CN2021095360 which claims benefit to CN 202110559426.0 filed 21 May 2021 and claims benefit to CN 202010447142.8 filed 25 May 2020.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. PCT/CN2021095360 filed 23 May 2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 25 November 2022 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
It is noted the IDS is not being considered because translated copies of the foreign references were not provided.
Drawings
The drawings were received on 25 November 2022. These drawings are accepted.
Specification
The specification received 25 November 2022 has been entered into the application.
The Amendments to the specification received 25 November 2022 has been entered into the application.
Claim Objections
Claim 1 is objected to because of the following informalities: “A modeling method of artificial neural pathway across brain regions”. The claim should be amended to recite “” to address the grammatical correctness (i.e., pluralization) of the claimed preamble.
Claim 8 is objected to because of the following informalities: “the cluster center is determined. The time sequence...”. The claim should be amended to recite “” to address the correctness of the claim.
Claim 9 is objected to because of the following informalities: “…the neural pulse signals of the output neurons are predicted using the artificial neural pathway model, an artificial neural pathway is formed according to input neurons”. The claim should be amended to recite “…the neural pulse signals of the output neurons are predicted using the artificial neural pathway model,, thereby forming an artificial neural pathway according to input neurons. ” to address the grammatical correctness and clarity of the claim.
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 1-10 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 "...to the waveform…" in line 2 of the conducting step. There is insufficient antecedent basis for this limitation in the claim. The claim should be amended to recite “to a waveform…” because the previous claimed steps do not contain earlier recitations or limitations of the waveform, and it would be unclear as to what element the limitation was making reference. See MPEP 2173.05(e). The limitation “…to the waveform characteristics” renders the claim indefinite because it is not clear what waveform characteristic is utilized such that the time of releasing neural pulse signals and the corresponding neurons can be used for calibrating the time of the releasing neural pulse signals and corresponding neurons. For example, it is not clear if the waveform characteristic of the neural pulse signal is referring such as frequency, wavelength, phase, or amplitude, and what about the waveform characteristic(s) is used for calibrations. Here, and to provide clarity, the claim can be amended to encompass limitations describing the waveform characteristic(s) using language consistent with and supported by the specification (i.e., wave peak values, peak valley time interval [page 4 lines 22-27]). It is further not clear how the time of the releasing neural pulse signals and corresponding neurons is calibrated based on or according to the waveform characteristic of the neural pulse signal when the claims do not recite what is being analyzed from the waveform characteristics such pulse signals and neurons can be calibrated.
Claim 1 recites the limitation "... calibrating the time of the releasing neural pulse signals and corresponding neurons" in lines 3-4 of the conducting step. There is insufficient antecedent basis for “the time of the releasing neural pulse signals and corresponding neurons” in the claimed step. The claim should be amended to recite “a time of the releasing neural pulse signals and corresponding neurons” because the previous claimed steps do not contain an earlier recitation or limitation the waveform. . See MPEP 2173.05(e).
Claim 1 recites the limitation "discreting the time slot of all neural pulse signals…" in line 1 discreting step. There is insufficient antecedent basis for “the time slot of all the neural pulse signals …” in the claimed step. The claim should be amended to recite “a time of the releasing neural pulse signals and corresponding neurons” because the previous claimed steps do not contain an earlier recitation or limitation the waveform.. See MPEP 2173.05(e).
Claim 1 for each remaining step recites “for each remaining output neuron screened and filtered in the output brain region, screening multiple input neurons…”. The claimed step is rendered indefinite because it recites “for each remaining output neuron screened and filtered” but the claim and the previous claimed steps do not contain any “screening and filtering” steps for the remaining output neuron(s) in the output brain region.
Claim 1 for each remaining step recites “constructing a time sequence input neural pulse history of the sample neurons according to the time of releasing neural pulse signals.” The claimed step is render indefinite because it is not clear what or which “the time of releasing neural pulse signals” is referring to. It is noted the “the time of releasing neural pulse signals” of the conducting step does not provide antecedent basis such that the two “the time of releasing neural pulse signals” can be distinguished from each other.
Claim 1 recites the limitation "... to the time of releasing neural pulse signals." in line 4 for each remaining step. There is insufficient antecedent basis for “the time of the releasing neural pulse signal” in the claim. The claim should be amended to recite “... to a time of releasing neural pulse signals."” because the previous claimed steps do not contain an earlier recitation or limitation the waveform. See MPEP 2173.05(e). Amending the antecedent basis issue in the previous conducting step could also would provide clarity for this step as well.
Claim 1 recites the limitation “a non-discrete neural pulse sequence kernel function based on the time sequence input neural pulse history of the input neuron" in line 1-2 constructing step. There is insufficient antecedent basis for “the time sequence input neural pulse history of the input neuron” in the claim. The claim should be amended to recite “…a time sequence input neural pulse history of the input neuron” because the previous claimed steps do not contain an earlier recitation or limitation ”the time sequence input neural pulse history of the input neuron” but recites “time sequence input neural pulse history of the sample neurons according to the time of releasing neural pulse signals” which is a time sequence input neural pulse history for sample neurons, not for the time sequence input neural pulse history of the input neuron of the previous step. See MPEP 2173.05(e).
Claim 1 in reproducing step recites the limitation "using the non-discrete neural pulse sequence kernel function”, “optimizing the weight parameters of linear weighting”,” with the objective to maximize”, “the linear mapping relationship”, and “relationship consisting of the weight parameters of the artificial neural pathway model”. There is insufficient antecedent basis for "the non-discrete neural pulse sequence kernel function”, “the weight parameters of linear weighting”, “the objective to maximize”, “the linear mapping relationship”, and “the weight parameters of the artificial pathway model” in the claim. The claim should be amended to recite "a non-discrete neural pulse sequence kernel function”, “optimizing weight parameters of linear weighting”, “an objective to maximize the likelihood”, “a linear mapping relationship”, and “ consisting of weight parameters of the artificial pathway model” because the previous claimed steps do not contain an earlier recitation or limitations for "the non-discrete neural pulse sequence kernel function”, “the parameters of linear weighting”, “the objective to maximize”, “the linear mapping relationship”, and “the weight parameters of the artificial neural pathway model. See MPEP 2173.05(e).
Claim 1 reproducing step recites “after linear weighting”. The limitation renders the claim indefinite because the previous claimed steps do not recite any steps of linear weighting. Thus, it is not clear how the claimed step can result in a predictive value using a linear weighted non-discrete neural pulse sequence kernel when the claimed step is missing steps linear weighting for linearly weighting a non-discrete neural pulse sequence kernel function. Moreover, claim 1 reproducing step recites “…of the predicted value of the neural pulse signal of the output neuron”. The claimed limitation renders the claim indefinite because previous steps do not recite a step of predicting. Here, the claim requires a predicted value, but the previous claimed steps do not contain any predicting value analysis such that to yield predicted values of the neural pulse signal of the output neuron, for example. It is recommended to amend the claim to recite a linear weighting and predicting step. It is noted that any amendments should be consistent with and supported by the specification.
Claims 2-10 are rejected because they fail to provide limitations to overcome the deficiencies of the base claim(s).
Claim 5 recites “for each remaining output neuron screened and filtered in the output brain region, multiple input neurons are selected”. The claimed step renders the claim indefinite because the claims recite “for each remaining output neuron screened and filtered” but the claim and the previous claimed steps do not recite any screening and filtering remaining output neuron steps. It is recommended to amend the claim to provide a screening and filtering step. It is noted that any amendments should be consistent with and supported by the specification.
Claim 6 recites the formula
X
k
=
τ
k
m
,
n
m
x
n
,
w
h
e
r
e
τ
k
m
,
n
,
t
k
. The formula renders the claim indefinite because the claim does not provide as to what k is equal. Thus, it is not clear the relationship k with respect to
X
k
and/or
τ
k
m
,
n
m
x
n
,
w
h
e
r
e
τ
k
m
,
n
,
t
k
, as the claim does not define what the variable is or provide a legend illustrating the what data of the variable of the claimed formula encompasses. Therefore, the undefined variable of the formula renders the formula indefinite. It is recommended to amend the claim to provide as to what k represents.
Claim 7 recites a formula. The formula uses the variable(s)
κ
c
.
However, the claim does not provide as to what quantitative data
κ
c
is to represent and to encompass. Therefore, the undefined variable data of the formula renders the claim indefinite. Moreover, the formula further renders the claim indefinite because it is not clear what the variable(s)
σ
S
2
and
σ
R
2
are, and what the S and R variables are and what data they encompass. Here, the claim does not define what the variables are or provide a legend illustrating what data the variables of the claimed formula are to encompass.
It is further not clear what data is to represent c of
κ
c
(
⋅
)
. It is further not clear because
κ
(
⋅
)
is to represent non-discrete neural pulse sequence kernel function. Here, it is not clear how the variable c is to differentiate
κ
c
(
⋅
)
from
κ
(
⋅
)
. It is also not clear if
κ
c
(
⋅
)
represent another non-discrete neural pulse sequence kernel function or if the variable c is to represent a single value.
It is recommended to amend the claim to provide as to what
σ
S
2
and
σ
R
2
and the S and the R of the variable/formula,
κ
c
⋅
, and c represent and/or amend the claims to provide a legend of what all variables are and encompass (i.e.,
κ
⋅
=
non-discrete neural pulse sequence kernel function).
Claim 8 recites the limitation “the time sequence input neural pulse history is clustered and the cluster center is determined." in line 5 constructing step. There is insufficient antecedent basis for “the cluster center” in the claim. The claim should be amended to recite “…a cluster center” because the previous claimed steps do not contain an earlier recitation or limitation such that only one cluster center is determined or if there are multiple cluster centers. Here, it is recommended to amend the claim to clarify whether the claim requires multiple cluster centers or an individual cluster center such that antecedent basis can be established for the claimed limitation.
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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step I - Process, Machine, Manufacture or Composition
Claims 1-10 are drawn to a method for modeling artificial neural pathway, so a process.
Step 2A Prong I - Identification of an Abstract Idea
Claim 1 recites:
according to the waveform characteristics of the neural pulse signals, calibrating the time of releasing neural pulse signals and the corresponding neurons
This step can be performed in the human mind by observing and evaluating waveform characteristics of neural pulse signals to calibrate the time of releasing neural pulse signals and the corresponding neurons and is therefore an abstract idea. Here, the step of calibrating is broadly and generically recited and reads on mathematical concepts. This step encompasses calibrating data (i.e., times of pulse signals and corresponding neurons) which encompasses performing mathematical operations for mathematically adjusting or refining quantitative data which reads on abstract ideas.
discreting the time slot of all neural pulse signals
This step can be performed in the human mind by organizing information/data (i.e., dividing pulse signal data) for discreting (i.e., dividing time collected neural pulse signals to into fixed time slots [Spec page 4 lines 25-30 and page 5 line 1-7]) time data and is therefore an abstract idea. This step encompasses mathematically categorizing data into time slots widths (i.e.., 0 or 1) which encompasses using equalities and inequalities which reads on abstract ideas.
screening and filtering all the neurons in the input brain region and the output brain region based on the neural pulse release rate.
This step can be performed in the human mind by observing, comparing, and evaluating neural pulse release rates for screening and filtering the neurons of the input and output brain regions and is therefore an abstract idea. This step encompasses screening and filtering information based on quantitative/numerical data (i.e., neural pulse release rates) which uses the mathematical concepts (i.e., equalities and inequalities) for filtering data which reads on abstract ideas.
for each remaining output neuron screened and filtered in the output brain region, screening multiple input neurons from the input brain region as sample neurons according to the correlation between the neural pulse signals
This step can be performed in the human mind by observing and evaluating information/quantitative data (i.e., the correlation between neural pulse signal rates) for screening the multiple input neuron as a sample neuron and is therefore an abstract idea.
constructing a time sequence input neural pulse history of the sample neurons according to the time of releasing neural pulse signals
This step can be performed in the human mind by organizing data (i.e., time of releasing neural pulse signals) for constructing time sequence input neural pulse history and is therefore an abstract idea. Here, under broadest reasonable interpretation (BRI), the term “constructing” is interpreted as organizing information (i.e., data input)”, not constructing a physical substance. This step encompasses mathematically organizing data (i.e., time of releasing neural pulse signals) into a different form (i.e., time sequence input) which reads on abstract ideas. See MPEP 2106.04(a)(2)(I)(A)(iv).
constructing a non-discrete neural pulse sequence kernel function based on the time sequence input neural pulse history of the input neuron
This step can be performed in the human mind by organizing information (i.e., time sequence input neural pulse history) to construct a non-discrete neural pulse sequence kernel function sequence input neural pulse history of the input neuron and is therefore an abstract idea. Here, under broadest reasonable interpretation (BRI), the term “constructing” is interpreted as organizing information (i.e., data input), not constructing a physical substance. This step encompasses using quantitative data for constructing a discrete neural pulse sequence kernel function (i.e., mathematical formula [Spec, page 7 lines 10-19]) which reads on abstract ideas. This step also encompasses mathematically organizing data (i.e., time of releasing neural pulse signals) into a different form (i.e., time sequence input) which reads on abstract ideas. See MPEP 2106.04(a)(2)(I)(A)(iv).
projecting the time sequence input neural pulse history into a Reproducing Kernel Hilbert Space
This step can be performed in the human mind by organizing data (i.e., history) for projection into a space (i.e., data dimensionality reduction [Spec page 7 lines 20-25, page 8 lines 1-19]) and is therefore an abstract idea. This step encompasses projecting data (i.e., neural pulse history) into Reproducing Kernel Hilbert Space which encompasses performing mathematical computations (i.e., linear weighting, clustering, distances [Spec page 8 lines 5-20]) which reads on abstract ideas. This step encompasses taking data (i.e., time sequence input neural pulse history), mathematically manipulating the data (i.e., Reproducing Kernel Hilbert Space), and organizing the data into a form (i.e., projected neural pulse history data). See MPEP 2106.04(a)(2)(I)(A)(iv).
reducing the dimension of the Reproducing Kernel Hilbert Space by clustering the time sequence input neural pulse history
This step can be performed in the human mind by organizing data (i.e., clustering time sequence input neural pulse history) to reduce the dimensions of the data and is therefore an abstract idea. This step encompasses taking data (i.e., time sequence input neural pulse history), mathematically manipulating the data (i.e., clustering), and organizing the data into a different form (i.e., reduced dimensions) which reads on abstract ideas. See MPEP 2106.04(a)(2)(I)(A)(iv).
in the Reproducing Kernel Hilbert Space of reduced dimension, using the non-discrete neural pulse sequence kernel function after linear weighting as the predictive value of the neural pulse signal of the output neuron
This step can be performed in the human mind by following instructions to use the non-discrete neural pulse sequence kernel function as the predictive value of the output neuron and is therefore an abstract idea. This step encompasses the mathematical computations (i.e., linear weighting, data dimension reduction) and variables/formulas (i.e., non-discrete neural pulse sequence kernel function) for reducing data which reads on abstracts idea.
optimizing the weight parameters of linear weighting with the objective of maximizing the likelihood function of the predicted value of the neural pulse signal of the output neuron
This step can be performed in the human mind by organizing data (i.e., weight parameters) to maximize the output neuron s (i.e., optimizing data) and is therefore an abstract. This step encompasses the mathematical concepts of taking information (i.e., weight parameters), mathematically manipulating the data (i.e., optimization), and organizing the data into a different form (i.e., maximized output neuron) which reads on abstract ideas. MPEP 2106.04(a)(2)(I)(A)(iv).
constituting the linear mapping relationship consisting of the weight parameters of the artificial neural pathway model.
This step can be performed in the human mind by organizing data (i.e., weight parameters) to constitute a linear mapping relationship and is therefore an abstract idea. Here, the term “constituting” is interpreted as an alternative term for “generating/calcualting” the linear mapping relationship. See MPEP 2106.04(a)(2)(A)(I). This step encompasses performing mathematical/statistical computations (i.e., constituting) a linear relationship which reads on abstract ideas.
Claims 2-10 are further drawn to limitations that describe the abstract ideas of claim 1 and are therefore also abstract ideas.
Claim 6 recites “…wherein, constructing a time sequence input neural pulse history of the sample neuron…”. Here, under broadest reasonable interpretation (BRI), the term “constructing” is interpreted as organizing information (i.e., data input)”, not constructing a physical substance. This step can be performed in the human mind by organizing data (i.e., time sequence data formed by the time sequence neuron) and is therefore an abstract idea. This step encompasses using the mathematical formula of claim 6 to construct time sequence of the input neural pulse history which reads on performing mathematical operations which reads on abstract ideas. This step encompasses taking data (i.e., time of releasing neural pulse signals), mathematically manipulating the data (i.e., mathematical expression of claim 6), and organizing the data into a different form (i.e., time sequence) which reads on abstract ideas. See MPEP 2106.04(a)(2)(I)(A)(iv).
Claim 7 recites “…wherein, the non-discrete neural pulse pathway sequence kerel function is constructed…”. It is noted under broadest reasonable interpretation (BRI), the term “constructing” is interpreted as organizing information, not constructing a physical substance. Here, claim 7 merely recites that the non-discrete neural pulse pathway sequence kerel function is constructed from the formula of claim 7. As such, this claimed step can be performed in the human mind by organizing information/data (i.e., distances, input and output neural pulse history) to construct a mathematical kernel function and is therefore an abstract idea. This also encompasses mathematical formula and variables for said formula which reads on abstract ideas.
Claim 9 recites “...time sequence input neural pulse history is constructed…an artificial neural pathway is formed”. It is noted under broadest reasonable interpretation (BRI), the term “constructing” is interpreted as organizing information (i.e., time sequence input neural pulse history, predicted neural pulse history)”, not constructing a physical substance. Additionally, it is noted that under further BRI the limitation “…an artificial neural pathway is formed…” is interpreted as organizing information (i.e., time sequence input neural pulse history, function of claim 7), not forming a physical substance. Here, the artificial neural pathway is broad and generically recited and reads on mere mathematical formulas and variables for predicting neural pulse signals of output neurons which reads on abstract ideas.
Claim 10 recites “…constructed artificial neural pathway model is also visualized…”. This step can be performed in the human mind by organizing information/data (i.e., neural pulse history, smoothed neural pulse history, combining weight parameters and neural pulse signal output neurons, smooth two signals) to show an interaction of determined pulse neural signals of output neuron and is therefore an abstract idea. It is noted that under BRI the limitation “…visualized…” is interpreted as organized information (i.e., time sequence input neural pulse history, function of claim 7), not outputting information such that the artificial neural pathway is presented on a device to physically visualize data. Here, under further BRI, “visualizing” can also be interpreted as “calculating” because claim 10 describes a process for “visualizing” the constructed artificial neural pathway model using data smoothing methods for processing data to show interactions (i.e., produced quantitative data providing relationships) which illustrate mathematical processes for showing interactions. See MPEP 2106.04(a)(2)(I)(A-B). This step encompasses taking information (i.e., time sequence neural pulse history (i.e., collection of neural pulse signals), weighted parameters, smoothed neural pulse signals), mathematically manipulating information (i.e., artificial neural pathway model, smoothing methods), and organizing/combining to show pulse neural signal interactions which reads on abstract ideas. See MPEP 2106.04(a)(2)(I)(A)(iv).
Step 2A Prong Two: Consideration of Practical Application
Claim 1 does not recite any additional element which integrates the recited judicial exception into a practical application.
Here, in the instant case, the claims merely set forth a method of data analysis for constituting a linear relationship consisting of the weight parameters of the artificial neural pathway model. As such, practicing the claims merely result in constituting/calculating/generating a linear mapping relationship of weight parameters. Such a result only produces information and does not provide for a practical application in the physical-realm of physical things and acts, i.e., the claims do not utilize the data generated by the judicial exception to affect any type of change. See MPEP 2106.04(a)(2)(A)(iv).
Claims 6-7 and 9-10 recites the limitation “constructing/constructed”. As noted in Step II Prong I of this 101 analyses, “constructing” is interpreted as organizing information, not physical constructing a substance. Furthermore, claim 9 also recites “…an artificial neural pathway is formed…”. Also, as noted in Step 2A Prong I of this 101 analyses, the limitation “formed” is interpreted as organizing/combining information/data, not combining a physical substance(s). Additionally, claim 10 recites “visualized”. As noted in Step II Prong I of this 101 analyses, “visualized” is interpreted as organizing information and/or performing calculations, not using a device such that to display the artificial neural pathway model.
Thus, the “constructing/constructed”, “forming”, “combining”, and “visualized” limitations of claims 1, 6-7 and 9-10 are considered abstract ideas and are not considered to be additional elements such as constructing/forming and/or combining physical/tangible objects or substances or using additional elements for visualizing or presenting data. Therefore, the claims do not contain any additional that integrate the recited judicial exception into a practical application.
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Step 2B - Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea.
The recited additional elements of data gathering by conducting synchronous collection of neural pulse signal of claim 1 and collected neural pulse signal input of claim 9 does not add significantly more than the recited judicial exception because collecting data (i.e., neural pulse signals) that is subsequently evaluated and analyzed by the abstract ideas is deemed a routine and conventional extra-solution activity. See MPEP 2106.05(g).
In conclusion, and when viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Conclusion
Claims 1-10 are rejected.
No claims are allowed.
Finality
This Office action is a Non-Final action. A shortened statutory period for reply to this action is set to expire THREE MONTHS from the mailing date of this action.
Inquiries
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/J.C.P./Examiner, Art Unit 1687
/Anna Skibinsky/
Primary Examiner, AU 1635
Prosecution Insights