Prosecution Insights
Last updated: September 19, 2026
Application No. 18/027,902

SYSTEMS AND METHODS OF USING SPIKE TRAINS

Non-Final OA §101
Filed
Mar 22, 2023
Priority
Sep 25, 2020 — provisional 63/083,482 +2 more
Examiner
GO, RICKY
Art Unit
Tech Center
Assignee
University of Pittsburgh
OA Round
1 (Non-Final)
80%
Grant Probability
Favorable
1-2
OA Rounds
0m
Est. Remaining
89%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allowance Rate
837 granted / 1045 resolved
+20.1% vs TC avg
Moderate +9% lift
Without
With
+8.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
22 currently pending
Career history
1064
Total Applications
across all art units

Statute-Specific Performance

§101
33.8%
-6.2% vs TC avg
§103
21.8%
-18.2% vs TC avg
§102
29.2%
-10.8% vs TC avg
§112
11.5%
-28.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1045 resolved cases

Office Action

§101
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 . Information Disclosure Statement The references listed in the Information Disclosure Statements filed on 03/22/2023 and 04/03/2024 have been considered by the examiner (see attached PTO-1449 forms). 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to an abstract idea without significantly more. Claim 1 recites a method comprising: determining, by at least one processor, a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject; determining, by the at least one processor, a plurality of first layer feature vectors, the plurality of first layer feature vectors including a first feature vector that comprises temporal- relation values of a subset of the plurality of spike trains with respect to a time instance of a reference spike train of the subset, corresponding to a time constant τ having a first value; establishing, by the at least one processor, a first layer comprising a first plurality of clusters of the first layer feature vectors; identifying, by the at least one processor, a set of one or more clusters from the first plurality of clusters most similar to a cluster formed according to an incoming feature vector; determining, by the at least one processor, a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster- subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establishing, by the at least one processor, a second layer comprising a first plurality of clusters of the second layer feature vectors; establishing, by the at least one processor, at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value; and determining, by the at least one processor, that a type of motion performed by the subject corresponds to one or more clusters of layer feature vectors of one of the at least one successive layer or the second layer… Claim 24 recites a system comprising: at least one processor configured to: determine a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject; determine a plurality of first layer feature vectors, the plurality of first layer feature vectors including a first feature vector that comprises temporal-relation values of a subset of the plurality of spike trains with respect to a time instance of a reference spike train of the subset, corresponding to a time constant τ having a first value; establish a first layer comprising a first plurality of clusters of the first layer feature vectors; identify a set of one or more clusters from the first plurality of clusters most similar to a cluster formed according to an incoming feature vector; determine a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster-subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establish a second layer comprising a first plurality of clusters of the second layer feature vectors; establish at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value; and determine that a type of motion performed by the subject corresponds to one or more clusters of layer feature vectors of one of the at least one successive layer or the second layer… Claim 43 recites a non-transitory computer-readable medium storing a program including instructions that, when executed by a processor, determines a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject; determines a plurality of first layer feature vectors, the plurality of first layer feature vectors including a first feature vector that comprises temporal-relation values of a subset of the plurality of spike trains with respect to a time instance of a reference spike train of the subset, corresponding to a time constant τ having a first value; establishes a first layer comprising a first plurality of clusters of the first layer feature vectors; identifies a set of one or more clusters from the first plurality of clusters most similar to a cluster formed according to an incoming feature vector; determines a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster-subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establishes a second layer comprising a first plurality of clusters of the second layer feature vectors; establishes at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value; and determines that a type of motion performed by the subject corresponds to one or more clusters of layer feature vectors of one of the at least one successive layer or the second layer… and thus grouped as Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations. These judicial exceptions are not integrated into a practical application because the additional elements, the data gathering step, (claim 1) “determining, by at least one processor, a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject” (claim 24) “determine a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject” (claim 43) “determines a plurality of spike trains from a plurality of neurons of a cerebral cortex of a subject” are mere data gathering that do not add a meaningful limitation to the method as they are insignificant extra-solution activity. Furthermore, the additional elements (claims 1, 24 and 43) the “at least one processor, a processor” are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions amount to no more than using a computer as a tool to perform an abstract idea. All of which are considered not indicative of integration into a practical application (see MPEP 2106.04(d)). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because are mere data gathering that do not add a meaningful limitation to the method as they are insignificant extra-solution activity - see MPEP 2106.05(g). The additional elements of the processors are mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and deemed insufficient to qualify as “significantly more” see MPEP 2106.05(f). Dependent claims 2, 4-6, 9, 10, 13-15, 17, 18, 21, 22, 25, 38, 41 and 44 when analyzed as a whole are patent ineligible under 35 U.S.C. §101 because the dependent claims fail to establish that the claims are not directed to an abstract idea as they are directed mathematical concepts and/or mental processes and do not add significantly more to the abstract idea. Allowable Subject Matter Claims 1, 2, 4-6, 9, 10, 13-15, 17, 18, 21, 22, 24, 25, 38, 41, 43 and 44 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action. The following is an examiner’s statement of reasons for allowance: Claim 1 is considered to be allowable over the cited prior art because none of the cited prior art teaches or suggests, in combination with the other claimed limitations, determining, by the at least one processor, a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster- subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establishing, by the at least one processor, a second layer comprising a first plurality of clusters of the second layer feature vectors; establishing, by the at least one processor, at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value… Claim 24 is considered to be allowable over the cited prior art because none of the cited prior art teaches or suggests, in combination with the other claimed limitations, determine a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster-subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establish a second layer comprising a first plurality of clusters of the second layer feature vectors; establish at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value… Claim 43 is considered to be allowable over the cited prior art because none of the cited prior art teaches or suggests, in combination with the other claimed limitations, determines a plurality of second layer feature vectors comprising a second plurality of clusters that includes the set of one or more clusters, the second plurality of clusters including a first cluster that comprises temporal-relation values of a cluster-subset of the second plurality of clusters with respect to a time instance of a reference cluster of the cluster-subset, corresponding to τ having a second value; establishes a second layer comprising a first plurality of clusters of the second layer feature vectors; establishes at least one successive layer after the second layer, each of the at least one successive layer corresponding to τ having a respective value… Relevant Prior Art / Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Hunt et al. (US Patent Number 9,195,934 B1) discloses a spiking neuron classifier apparatus with one or more subset neuron layers configured to determine presence of one or more features in the subset of plurality of conditionally independent features; Natroshvili (US Patent Application Publication 2019/0042942 A1) discloses a hybrid spiking neural network with a support vector machine classifier; BANERJEE et al. (US Patent Application Publication 2023/0334300 A1) discloses methods and systems for time-series classification using a reservoir-based spiking neural network. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICKY GO whose telephone number is (571)270-3340. The examiner can normally be reached on Monday through Friday from 9:00 a.m. to 5:30 p.m. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen M. Vazquez can be reached on (571) 272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RICKY GO/Primary Examiner, Art Unit 2857
Read full office action

Prosecution Timeline

Mar 22, 2023
Application Filed
Aug 26, 2026
Non-Final Rejection mailed — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
80%
Grant Probability
89%
With Interview (+8.8%)
3y 0m (~0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1045 resolved cases by this examiner. Grant probability derived from career allowance rate.

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