Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined
under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are
moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Regarding the applicant’s request for an interview, the examiner invites the Applicant to schedule an interview after reviewing the present Office Action. The present Office Action sets forth new grounds of rejection and does not rely upon any of the prior art references applied in the previous Office Action. Accordingly, an interview following Applicant’s review of the present Office Action would provide the parties an opportunity to discuss the newly applied prior art and grounds of rejection.
The indicated allowability of claims 9 and 19 is withdrawn in view of the newly
discovered references. Rejections based on the newly cited reference(s) follow.
Under 35 USC § 101
Although claims 1 and 12 include abstract ideas, claims 1 and 12 also recite
additional elements such as “Under 35 USC § 101
Although claims 1 and 12 include abstract ideas, claims 1 and 12 also recite
additional elements such as “grouping, from among a plurality of electrodes, electrodes that detect spike signals generated from a same neuron of among a plurality of neurons into a group, generating, based on respective detected spike signals, weights corresponding to each electrode within the group and generating, based on the weights, enhanced spike signal for the neuron”. Although the limitations directed to grouping electrodes/signals and generating weights based on respective detected spike signals may encompass mathematical concepts, under Step 2A, Prong One, the claims considered as a whole integrate any such abstract idea into practical application under Step 2A, Prong Two. In particular, the claims require grouping, from among a plurality of electrodes, electrodes that detect spike signals generated from the same neuron, generating respective weights corresponding to the grouped electrodes based on the detected spike signals, and using the weights to generate an enhanced spike signal for the neuron. Claim 12 further recites the plurality of electrodes and communication interface configured to receive neurons spike signals detected by the electrodes. Thus, the claimed mathematical processing is applied as part of a particular multi-electrode neuron signal processing technique to produce an enhanced neuron spike signal, rather than merely calculating/generating, organizing, or displaying information. The inclusion of these additional elements integrates the identified judicial exception into a practical application that effects a 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. Therefore, claims 1-20 are considered eligible under 35 USC 101.
Claim Objections
Claims 13-20 are objected to because of the following informalities:
In claims 13-20, change “execution of the instructions further configures the apparatus” to -execution of the instructions further configure the apparatus”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
6. 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 2, 3, 13 and 14 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.
Claims 2 and 13 recite the limitation “the threshold from among the spike signals”, line 3. It is not clear from the claim what threshold the applicant is referring to. Therefore, claims 2, 3, 13 and 14 are considered indefinite.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 5, 7, 8-12, 14, and 17-20 are rejected under 35 U.S.C. 103 as
being unpatentable over Montgomery, JR. et al. (Pub. No. US 2006/0167369) (hereinafter Montgomery) in view of Yeh et al. (Pub. No. 2008/0214218) (hereinafter Yeh).
As per claims 1, 11, and 12, Montgomery teaches processor-implemented processing of neuronal spike signals obtained from microelectrode readings and explains that the spike identification and storing procedures may be automatically implemented by computers and medical instrumentation (see ¶¶ [0012] and [0040]-[0055]). Montgomery further teaches grouping neuronal spike signals to determine whether spikes originated from the same or different neurons, including analysis obtained from microelectrodes, and groups spikes according to timing characteristics and amplitude characteristics so that a resulting group corresponds to a particular neuron (see ¶¶ [0039]- [0040]).
Montgomery therefore teaches identifying and grouping signals associated with common neuronal source.
Montgomery, however, fails to teach generating a respective weight for each electrode within the group and generating an enhanced spike signal based on those weights.
Yeh teaches combining multiple detected versions of a common signal using respective weights. Yeh teaches corresponding weight processor, multiplication of received signals by respective weights, summing the weighted signals, and combining the signals using maximum ratio combining (MRC) (see ¶¶ [0037]-[0040]).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify Montgomery’s processing of neuronal spike signals obtained from multiple microelectrodes by assigning respective weights to the grouped signals and combining the weighted signals as taught by Yeh because Yeh teaches that weighting and combining multiple received versions of a signal using MRC improved signal reception, thereby providing an enhanced representation of the neuronal spike detected by the grouped electrodes. The modification represents the predictable use of known signal-combining technique to multiple measurements associated with a common signal source.
As per claims 4 and 14, the combination of Montgomery and Yeh teaches the system as stated above. Montgomery further teaches selecting neuronal spikes to an amplitude threshold. Montgomery determines a threshold amplitude from the noise distribution and treats candidate signals whose amplitude exceed the threshold as neuronal spikes (see ¶ [0007]). Montgomery also teaches grouping spikes according to temporal characteristics that include the timing of amplitude maxima and minima, and according to amplitude scaling, for identifying spikes originating from the same neuron (see ¶¶ [0039]-[0040]).
As per claim 5, the combination of Montgomery and Yeh teaches the system as stated above.
Montgomery teaches detecting neuronal spike signals and grouping neuronal spikes according to their originating neuron, and using characteristics of the detected neuronal spikes, including their amplitudes, in processing and distinguishing the neuronal spike signals. Thus, Montgomery recognizes amplitude as a signal characteristic associated with the detected neuronal spike signals (see ¶¶ [0007], [0009] and [0019]).
As discussed with respect to claim 1, Yeh teaches maximum ratio combining in which multiple received signals are assigned respective weights and the weighted signals are combined. Yeh therefore teaches determining and applying respective signal combining weights to multiple received versions of a signal.
Although Montgomery fails to explicitly teach calculating a respective combining weight for each grouped electrode based on the amplitude of the spike signal detected by that electrode, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to determine the respective weights of Yeh for the grouped neuronal signals of Montgomery based on the amplitudes of the spike signals corresponding to the respective electrodes because Montgomery teaches that amplitude is a characteristic of the detected neuronal spike signal and Yeh teaches weighting respective received signals when combining multiple received versions of a signal, thereby allowing the contribution of each grouped electrode signal to the combined neuronal signal to be adjusted according to the magnitude of the spike signal received by that electrode.
As per claims 7 and 17, the combination of Montgomery and Yeh teaches the system as stated above. Montgomery further teaches determining whether newly detected neuronal signals correspond to an existing neuronal group/template. Montgomery stores identified spike templates and compares subsequent identified spikes with previously stored templates; a spike satisfying the comparison criteria is assigned to the neuron associated with the existing template (see ¶¶ [0010] and [0040]-[0043]).
In applying Yeh’s weighting technique to Montgomery’s neuronal groups, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to generate and use weights according to the group to which the corresponding signals have been assigned because Montgomery identifies and maintains groups associated with respective neuronal sources thereby permitting signal-combining parameters to be associated with the identified neuronal group rather than unrelated signals.
As per claims 8 and 18, the combination of Montgomery and Yeh teaches the system as stated above.
Montgomery further teaches that when newly detected neuronal spike does not satisfy the criteria of a previously stored template, the spike may be determined to correspond to a new neuron, designated as new template, and added to the stored template library/database (see ¶ [0041]).
Yeh supplies the generation and application of respective signal weights. It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to generate corresponding weights for signals belonging to Montgomery’s newly established group because the new group represents another identified signal source to which the same weight combination processing would predictably be applied, thereby permitting signals associated with the newly identified neuron to receive enhanced signal processing.
As per claims 9 and 19, the combination of Montgomery and Yeh teaches the system as stated above.
Montgomery further teaches maintaining information representative of an existing neuronal group. Montgomery teaches storing a first-encountered neuronal spike having unique characteristics as a template for matching/grouping subsequently detected neuronal spikes and creating “a separate running average neuronal spike for each group” (see ¶ [0043]). Montgomery explains that the averaged neuronal spike provides “a more representative depiction of the group than the template” (see ¶ [0043]). Thus, after detected neuronal spikes have been determined to correspond to an existing neuronal group, Montgomery maintains an average value representative of the spike signals associated with that existing group.
Montgomery fails to explicitly teach generating signal combining weights based on the average spike signal associated with the existing group.
Yeh, however, teaches a signal combining system in which respective received signals are multiplied by corresponding weights and the resulting weighted signals are summed and combined using maximum ratio combining (see ¶¶ [0036]-[0039]). Yeh further teaches determining weights from signals information associated with the received and combined signals (see ¶ [0057]).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to use Montgomery’s running average neuronal spike for existing group in determining the weights used to combine the corresponding detected spike signals according to the weighted combining technique of Yeh because Montgomery explicitly teaches that the running average provides a more representative depiction of the neuronal group than an individual stored spikes, and Yeh teaches determining and applying signal dependent weights when combining multiple received signals, thereby permitting the weights applied to the signals of an existing neuronal group to be based on a representative signal value for that group and improving the resulting combined signal. Accordingly, the combination of Montgomery and Yeh renders obvious generating the weights based on an average value of spike signals associated with an existing group as recited in claims 9 and 19.
As per claims 10 and 20, the combination of Montgomery and Yeh teaches the system as stated above.
Yeh further teaches multiplying respective received signals by corresponding weights and providing the multiplication results to summing circuitry that sums the weighted signals for combination using MRC (see ¶¶ [0011]-[0012]).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to apply Yeh’s weighted summation to Montgomery’s grouped neuronal spike signals because weighted summation combines multiple measurements associated with the common neuronal source, thereby producing an enhanced representation of the neuronal signal.
Claims 2 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over
Montgomery in view of Yeh and further in view of Kaneko et al. (Patent No. US 5,692,516) (hereinafter Kaneko).
As per claims 2, 3, 13 and 14, Montgomery teaches detecting neuronal spikes based on an amplitude threshold and grouping detected neuronal spikes according to the neuron from which the spikes originated (see ¶¶ [0007], [0009] and [0019]).
Montgomery fails to teach determining target electrodes corresponding to spike signals generated from the same neuron using covariance among the detected spike signals.
Kaneko, however, teaches a multi-channel microelectrode having a plurality of electrode wires (ch1, ch2, and ch3) positioned relative to a plurality of nerve cells and simultaneously measuring neuronal action-potential waveforms through the respective electrode channels. Kaneko teaches calculating, for each channel, a covariance between the action-potential waveform observed through that channel and a template waveform (see col. 2, line 57 through col. 3, line 40). Kaneko explains that the covariance value indicates the amount of the template waveform component contained in the action-potential waveform observed in the respective channel and that, dependent upon the position of the nerve cell relative the electrode wires, a relatively large covariance value may be obtained for one channel and a relatively small covariance value for another channel. Kaneko further teaches using the covariance values of the individual channels as elements of a space-damping vector, e.g., [cov(1), cov(2), cov(3)] ,and teaches that different nerve cells produce different vector values. The covariance-derived vectors are thereafter used for clustering such that nerve-action spikes are classified individually according to the respective nerve cells from which they originate.
Thus, Kaneko teaches using covariance information derived from neuronal spike signals simultaneously detected by respective electrodes/channels to determine the relationship of the detected spike signals to a particular originating neuron. Although Kaneko calculates the respective covariance values relative to a neuronal template waveform rather than explicitly calculating covariance directly between the detected spike signals themselves, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to apply the covariance based multi-channel neuronal source determination taught by Kaneko to the spike signals detected by the electrodes of Montgomery because Kaneko teaches that covariance information obtained from simultaneously detected multi-electrode neuronal signals provides a signal-to-noise resistant measure for distinguishing neuronal signals according to their originating nerve cells, thereby enabling identification and grouping of the electrodes detecting spike signals attributable to the same neuron.
As per claims 3 and 14, the combination of Montgomery, Yeh and Kaneko teaches the system as stated above. Kaneko further teaches calculating, for each channel, a covariance between an action-potential waveform observed through the electrode channel and a neuronal template waveform (see col. 2, lines 30-45). Kaneko explains that the covariance value indicates the amount of the template waveform component contained in the action-potential waveform observed through the respective channel (see col. 3, lines 11-16). Kaneko further teaches that, depending upon the relationship between the nerve cell and the electrode channel, the covariance may have a relatively large value for one channel and relatively small value for another channel, and uses the covariance values of the respective channels as elements of a space-damping vector for classifying nerve-action spikes according to the respective nerve cells from which the spikes originate (see col. 2, line 56 through col. 3, line 40).
Kaneko fails to explicitly teach determining a target electrode by comparing the covariance value with a predetermined threshold. However, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to determine as target electrodes those electrode channels having covariance values greater than a predetermined threshold because Kaneko explicitly teaches that the magnitude of the covariance value represents the amount of the neuronal template waveform component present in the action-potential waveform detected by a respective electrode channel and uses such covariance information to distinguish neuronal signals according to their originating nerve cells, thereby providing an objective criterion for selecting electrode channels having sufficient correspondence to the neuronal spike of interest while excluding channels having insufficient correspondence or predominantly noise. Selection of an appropriate covariance threshold would have amounted to optimization of the degree of correspondence required for an electrode channel to be associated with the neuronal spike being classified. Accordingly, the combination renders obvious determining the target electrodes corresponding to spike signals having covariance greater than a threshold, as recited in claims 3 and 14.
Allowable Subject Matter
Claim 6 and 16 are objected to as being dependent upon a rejected base claim,
but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Regarding claims 6 and 16, none of the prior art of record teaches or fairly suggest a method or apparatus for processing a signal comprising: generating of the weights comprises: generating a sum of the amplitudes of the spike signals corresponding to the grouped electrodes; and generating a weight corresponding to an electrode from among the grouped electrodes, based on a ratio between an amplitude of a spike signal corresponding to the electrode and the sum of the amplitudes, in combination with the rest of the claim limitations as claimed and defined by the applicant.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented
in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Prior art
The prior art made record and not relied upon is considered pertinent to
applicant’s disclosure:
Mason [‘972] discloses a multi-electrode array comprising a plurality of electrodes, the electrodes being spaced apart from each other by spacer means, the electrodes being secured to the spacer means, the spacer means being encapsulated within a housing. The invention also relates to an implantable device comprising a multi-electrode array of the invention, a method of manufacturing electrodes for use in an array of the invention and a method for manufacturing a multi-electrode array of the invention. The invention also relates to a method for monitoring the effect of a test substance on a biological tissue using a multi-electrode array of the invention.
Principe et al. [‘690] discloses multiple electrodes and high-sampling rates to accurately record neural signals as they vary across time and space. The neural responses may be recorded either invasively or non-invasively. Surgically implanted micro-electrode arrays allow invasive recordings to capture both the timing of action potentials (spike trains) across many neurons, and local field potentials (LFPs) across many electrodes. Only the action potential waveforms of neurons in the close vicinity of the electrode are captured, providing a minute fraction of the neurons contributing in the implanted region.
Contact information
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to MOHAMED CHARIOUI whose telephone number is (571)272-2213. The examiner can normally be reached Monday through Friday, from 9 am to 6 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached on (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Mohamed Charioui
/MOHAMED CHARIOUI/Primary Examiner, Art Unit 2857
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