WO2022251542A1

WO2022251542A1 - Device and method that efficiently causes long-lasting neuronal desynchronization

Info

Publication number: WO2022251542A1
Application number: PCT/US2022/031199
Authority: WO
Inventors: Peter A. Tass; Justus A. KROMER
Original assignee: The Board Of Trustees Of The Leland Stanford Junior University
Priority date: 2021-05-27
Filing date: 2022-05-26
Publication date: 2022-12-01

Abstract

A single-site (with possible delivery through multiple sites) stimulation technique allows for parameter adjustment to yield sustained long-lasting therapeutic effects. Prior to stimulation the presence/ strength of symptoms and/or the degree of neuronal synchrony are quantified using the biomarkers YS and YE. Their values are stored as reference values YS_0 and YE O, respectively. To find stimulation parameters that yield long-lasting therapeutic effects, stimulation steps and evaluation steps are performed. During stimulation steps, acute effect of stimulation are evaluated using the biomarkers YS. During evaluation steps, long-lasting effects of stimulation are evaluated using the biomarkers YE. Based on YS and YE, stimulation parameters are adjusted and further stimulation and evaluation steps are performed until a parameter set X has been found for which desired long-lasting therapeutic effects are obtained.

Description

DEVICE AND METHOD THAT EFFICIENTLY CAUSES LONG-LASTING NEURONAL DESYNCHRONIZATION

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] The present application claims priority to United States Provisional Patent

Application No. 63/194,058, filed May 27, 2021, the contents of which are incorporated herein by reference in their entirety.

TECHNICAL FIELD

[0002] The present embodiments relate generally to neurology, and more particularly to a device and method that efficiently causes long-lasting neuronal desynchronization.

BACKGROUND

[0003] Excessive neuronal synchrony is related to several neurological disorders, including epilepsy, essential tremor, and Parkinson’s disease. High-frequency (HF) deep brain stimulation (DBS) is a common technological treatment for medically refractory Parkinson’s disease. However, symptoms typically return shortly after cessation of HF DBS (Temperli et ak, “How do parkinsonian signs return after discontinuation of subthalamic DBS?,” Neurology 60,

78 (2003)). Consequently, sustained symptom relief requires permanent stimulation, which increases the risk for unwanted side effects, e.g., due to current spread to neighboring areas and/or stimulation of fibers passing through the target area.

[0004] It is against this background that a need arose to develop a technological solution to these and other problems rooted in this technology.

SUMMARY

[0005] The present embodiments are generally directed to a single-site (with possible delivery through multiple sites) stimulation technique that allows for parameter adjustment to yield sustained long-lasting therapeutic effects. In some embodiments, prior to stimulation, the presence/strength of symptoms and/or the degree of neuronal synchrony are quantified using biomarkers. Their values are stored as reference values. Subsequently, the method aims at quantifying the acute effect of stimulation (e.g. effects during stimulation) and the long-lasting effect of stimulation (e.g. effects occurring after cessation of stimulation). An example approach according to embodiments consists of two treatment steps (stimulation and evaluation) that are repeated in a closed-loop setup.

BRIEF DESCRIPTION OF THE DRAWINGS [0006] These and other aspects and features of the present embodiments will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments in conjunction with the accompanying figures, wherein:

[0007] FIGs. 1A and IB illustrate example aspects of how long-lasting effects of periodic stimulation may differ from acute effects.

[0008] FIGs. 2A to 2E illustrate aspects of an example theoretical analysis of acute and long-lasting effects of periodic stimulation.

[0009] FIG. 3 illustrates an example algorithm for possible closed-loop operation according to embodiments.

[0010] FIGs. 4A to 4F illustrate example aspects of how long-lasting effects of periodic stimulation depend on pulse shape.

[0011] FIG. 5 is a block diagram illustrating an example system for implementing stimulation and evaluation techniques in accordance with embodiments.

DETAILED DESCRIPTION

[0012] The present embodiments will now be described in detail with reference to the drawings, which are provided as illustrative examples of the embodiments so as to enable those skilled in the art to practice the embodiments and alternatives apparent to those skilled in the art. Notably, the figures and examples below are not meant to limit the scope of the present embodiments to a single embodiment, but other embodiments are possible by way of interchange of some or all of the described or illustrated elements. Moreover, where certain elements of the present embodiments can be partially or fully implemented using known components, only those portions of such known components that are necessary for an understanding of the present embodiments will be described, and detailed descriptions of other portions of such known components will be omitted so as not to obscure the present embodiments. Embodiments described as being implemented in software should not be limited thereto, but can include embodiments implemented in hardware, or combinations of software and hardware, and vice- versa, as will be apparent to those skilled in the art, unless otherwise specified herein. In the present specification, an embodiment showing a singular component should not be considered limiting; rather, the present disclosure is intended to encompass other embodiments including a plurality of the same component, and vice-versa, unless explicitly stated otherwise herein. Moreover, applicants do not intend for any term in the specification or claims to be ascribed an uncommon or special meaning unless explicitly set forth as such. Further, the present embodiments encompass present and future known equivalents to the known components referred to herein by way of illustration.

[0013] As set forth above, the present embodiments are generally directed to a single-site

(with possible delivery through multiple sites) stimulation technique that allows for parameter adjustment to yield sustained long-lasting therapeutic effects.

[0014] In this regard, the present Applicant recognizes that, in general, to avoid side effects, it is crucial to reduce the integral amount of stimulus current administered. Recently, multisite stimulation techniques, such as coordinated reset (CR) stimulation, were developed that counteract abnormal neuronal synchrony (Tass et ah, “A model of desynchronizing deep brain stimulation with a demand-controlled coordinated reset of neural subpopulations,” Biological Cybernetics 81, 88 (2003)). See also WO2019246561, the contents of which are incorporated herein by reference in their entirety. CR stimulation has been shown to cause long-lasting desynchronization and sustained symptom relief, i.e. desynchronization and therapeutic effects outlast stimulation (Tass et ah, “Coordinated reset neuromodulation has sustained after-effects in parkinsonian monkeys,” Annals of Neurology 72, 816 (2012)); Adamchic et ah, “Coordinated Reset Neuromodulation for Parkinson’s Disease: Proof-of-Concept Study,” Movement Disorders 29, 1679 (2014)). This reduces the amount of delivered stimulation current and may reduce unwanted side effects.

[0015] Compared to classical HF DBS, parameter calibration for multisite stimulation aiming for long-lasting therapeutic effects faces additional challenges. First, for successful delivery of multisite stimulation, multiple stimulation contacts have to be placed in the target brain area. One of the main target areas for HF DBS in Parkinson’s patients is the subthalamic nucleus (STN). The STN is part of the basal ganglia and its spatial dimensions are approximately 3.4-9.7 mm (anteroposterior), 2.5-5.3 mm (mediolateral), and 2.9-9.4 mm (dorsoventral) (according to MRI data by Richter et al., “Determining the position and size of the subthalamic nucleus based on magnetic resonance imaging results in patients with advanced Parkinson disease,” Journal of Neurosurgery 100, 541 (2004)). Typically, HF DBS is only delivered to subregions of the STN using DBS electrodes. These electrodes consist of multiple stimulation contacts. Commonly used DBS electrodes possess contacts of 1.5 mm length that are equi distantly arranged along the electrode axes and separated by gaps of either 0.5 or 1.5 mm length (Krauss et al., “Technology of deep brain stimulation: current status and future directions,” Nature Reviews Neurology 17, 75 (2021)). Accurate electrode placement requires high precision during electrode placement surgery. Deviations from the target positions are quantified using the difference between the location of the electrode tip relative to its intended location, or the radial error, which has been defined as the 2D vector difference between the intended and the actual electrode position measured in the axial plane that was used for anatomical targeting (Ostrem et al., “Clinical outcomes using ClearPoint interventional MRI for deep brain stimulation lead placement in Parkinson’s disease,” Journal of Neurosurgery 124, 908 (2016)).

[0016] For electrode placement for HF DBS of the STN, McClelland et al. reported distances between the actual and intended tip locations of 2.9 ± 1.4 mm (mean (M) ± standard deviation (SD)) (McClelland et al., “Subthalamic stimulation for Parkinson disease: determination of electrode location necessary for clinical efficacy,” Neurosurgical Focus 19, E12 (2005)). Reported mean radial errors are of the order of 0.6 ± 0.3 (M ± SD) mm (Ostrem et al., “Clinical outcomes using ClearPoint interventional MRI for deep brain stimulation lead placement in Parkinson’s disease,” Journal of Neurosurgery 124, 908 (2016)). Ostrem et al. used quadripolar lead electrodes even though DBS was delivered through a single active stimulation contact. The availability of multiple stimulation contacts for single site stimulation enabled them to correct for misplacements along the axis of implantation of up to 2 mm by selecting a different contact for DBS delivery. However, this might not be sufficient for the delivery of multisite DBS as several contacts need to be placed in the target area for stimulus delivery. Therefore, the required precision during electrode placement surgery for multisite stimulation may be even higher and may make proper electrode placement hardly feasible. Second, standardized procedures for DBS parameter adjustment are based on acute effects of stimulation (J. Volkmann et ah, “Basic algorithms for the programming of deep brain stimulation in Parkinson's disease,” Movement Disorders 21, S284 (2006)). However, long-lasting after-effects can differ significantly from acute effects. For instance, while classical HF DBS is able to efficiently suppress symptoms during the stimulation, i.e. yields pronounced acute effects, tremor typically returns within seconds to minutes, and all other symptoms within minutes up to half an hour after cessation of stimulation (Temperli et al., “How do parkinsonian signs return after discontinuation of subthalamic DBS?,” Neurology 60, 78 (2003)). Hence, classical HF DBS does not have long- lasting effects (i.e. the therapeutic and side effects of HF DBS are both acute, occurring primarily during stimulation).

[0017] Parameter adjustment is typically restricted by the type of implantable pulse generator. Implantable pulse generators use charge-balanced pulses to avoid tissue damage. Typically, the pulse is kept constant and cannot be modified by either medical personnel or patients. Thus, parameter adjustment is often restricted to variations of the stimulation amplitude (peak voltage or current per pulse) or variations of the stimulation frequency (number of pulses per time). Surprisingly, simulation studies by the present Applicant indicated that the pulse shape, especially the pulse width may have a strong impact on acute and, in particular, long- lasting effects of stimulation. Therefore, some of the present embodiments are directed to enabling it to be varied in order to induce optimal acute and long-lasting effects.

[0018] As further set forth above, an approach according to embodiments consists of two steps that are repeated in a closed-loop setup. The two steps as well as an algorithm for possible closed-loop operation are explained in detail below, in which the index n is used to refer to the nth run through the loop, called nth run.

[0019] Stimulation step

[0020] During the nth run, the first step is a stimulation step S_n. During S_n, periodic stimulation with parameter set X_n is delivered for a duration TS_n and one or several biomarkers YS_n are evaluated. The latter is used to quantify acute effects of the stimulation. Potential biomarkers for quantifying the degree of neuronal synchrony include the EEG power or LFP power in symptom related frequency bands, i.e. theta or beta band, or interactions of different rhythms (oscillations), e.g., in terms of their phase amplitude coupling. Stimulation can be delivered through a single or multiple stimulation sites, such as the stimulation technique described in WO2019246561. During the first stimulation step, stimulation parameters and the stimulation site can — but need not - be selected by means of test stimulations with classical DBS aiming at pronounced acute symptom suppression and no or minimal side effects.

[0021] For illustration, presented are results of theoretical and computational studies of periodic single-site stimulation of networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity to estimate the effect of periodic stimulation with different stimulation parameters, such as stimulation amplitudes, frequencies, and pulse shapes, on the degree of neuronal synchrony after cessation of stimulation.

[0022] In particular, FIGs. 1A and IB illustrate example aspects of how long-lasting effects of periodic stimulation may differ from acute effects. Acute and long-lasting effects of periodic stimulation with two different parameter sets delivered to a plastic network of synchronized leaky integrate-and-fire neurons were measured. FIG. 1 A illustrates an effect of periodic stimulation with stimulation amplitude A_stim=0.56 and frequency 30 Hz that was delivered in the interval 102 for 1000 sec (shaded). Shown are the degree of (pathological) synchrony p(t) and the mean synaptic weight (w(t)). Capital letters mark desynchronization (D) and synchronization (S) before, during, and after cessation of stimulation, respectively. FIG. IB is the same as FIG. 1A but for periodic stimulation with amplitude A_stim=0.14 and frequency 50 Hz delivered in the interval 104 for 1000 sec. While both sets of stimulation parameters led to long-lasting desynchronization after cessation of stimulation, the parameter set used in FIG. 1 A did not lead to acute desynchronization.

[0023] In the examples provided in FIGs. 1 A and IB, simulation results were obtained for a network of 1000 model neurons. These results show that periodic stimulation with suitable stimulation parameters reduces the degree of pathological synchrony after cessation of stimulation (marked by low values of the Kuramoto order parameter p(t) quantifying the degree of synchrony in FIGs. 1 A andlB). Counterintuitively, it was in general not possible to predict the long-lasting degree of synchrony based on the degree of synchrony during the stimulation. For instance, in FIG. 1 A, no reduction of p(t) was observed during the stimulation, i.e. periodic stimulation had an insufficient acute effect, while a significant reduction of p(t) was observed after cessation of stimulation, i.e. periodic stimulation had pronounced long-lasting after effects. In contrast, in FIG. IB periodic stimulation causes both a pronounced acute and long-lasting reduction of the degree of pathological synchrony p(t).

[0024] The relation between acute and long-lasting effects is generally complex. In some models, stimulation affected the strength of synapses such that either a weakening or a strengthening of synapses was obtained. Strong synaptic connections stabilized the network in a state of pronounced neuronal synchrony, which may correspond to pathological neuronal activity in Parkinson’s disease. In contrast, weak synaptic connections stabilized the network in a desynchronized state, which may correspond to a healthy state.

[0025] The present Applicant has identified a complex dependence of the rate of synaptic weight change J on stimulation parameters. In particular it was found that the relation between acute synchrony, observed during stimulus delivery, and long-lasting synchrony, observed after cessation of stimulation, showed a complex dependence on stimulation parameters and the type of synaptic plasticity considered, as will now be described in more detail in connection with FIGs. 2A to 2E.

[0026] FIG. 2A illustrates an example of periodic stimulation that induced m: 1 phase locking between spikes of individual neurons and stimuli. The color map shows theoretical predictions for phase locking coefficient m as function of both stimulation frequency f stim (e.g. between about 20Hz and 120Hz) and stimulation amplitude A stim (e.g. between about 0 and 1). As can be seen by FIG. 2A, in region 202, corresponding to high stimulation frequency and low stimulation amplitude, the values of phase locking coefficient m are high, approaching 30. By contrast, as shown by region 204, for high stimulation amplitudes, and particularly with lower simulation frequencies, the values of phase locking coefficient m are low, around 1.

[0027] FIG. 2B corresponds to FIG. 2A and illustrates an example theoretical prediction for time-averaged degree of acute synchronization p_ac. As shown, shaded region 210 of high time-averaged degree of acute synchronization in FIG. 2B corresponds roughly to region 204 of low values of phase locking coefficient m in FIG. 2A, in which stimulation amplitudes are high and particularly where stimulation frequencies are low.

[0028] FIG. 2C illustrates four qualitatively different spike-timing-dependent plasticity

(STDP) functions 222, 224, 226 and 228. These functions are denoted as symmetric Hebbian (222), asymmetric Hebbian (224), symmetric anti-Hebbian (226) and asymmetric anti-Hebbian (228), and are characterized by four respective different curves for the synaptic weight change due to STDP Aw as a function of the time lag tpost-tpre between postsynaptic and presynaptic spike times.

[0029] FIG. 2D illustrates an example of how the different STDP functions shown in

FIG. 2C result in different mean rates of synaptic weight change J during stimulation. In particular, example colormaps 232, 234, 236 and 238 in FIG. 2D show theoretical predictions for J as function of stimulation frequency f stim (e.g. between about 5Hz and 130Hz) and A stim (e.g. between 0 and 1) and the STDP functions 222, 224, 226 and 228, respectively. Gray curves 242, 244, 246 and 248 mark predicted boundaries between parameter regions of stimulation- induced strengthening of synapses (J>0) and stimulation-induced weakening of synapses (J<0).

In the latter parameter region, stimulation may induce long-lasting desynchronization (K-D), while other stimulation parameters may lead to long-lasting synchronization (K-S). Here, K stands for either acute desynchronization (K=D) or acute synchronization (K=S).

[0030] Example predicted maps 252, 254, 256 and 258 of acute and long-lasting synchrony for the different STDP functions 222, 224, 226 and 228, respectively, shown in FIG. 2C, are presented in FIG. 2E. Black curves 262, 264, 266 and 268 mark the predicted boundary between acute synchronization p_ac ~1 and desynchronization p_ac ~0 obtained from FIG. 2B. The parameter regions for K-D, K-S, K=D,S as described above in FIG. 2D are also shown in FIG. 2E.

[0031] As set forth above, in an example two-stage method according to embodiments, therefore, during a given stimulation step S_n, the biomarker YS_n is compared to a criterium Cl. The latter determines whether stimulation leads to tolerable acute effects. If Cl is matched, stimulation is assumed to be tolerated. Then stimulation is delivered for the full duration of the stimulation step TS_n. Afterwards stimulation is ceased and an evaluation step E_n is performed. If Cl is violated, stimulation is assumed to cause severe acute and/or side effects and the stimulation step is interrupted. Then, the (n+l)th run is started.

[0032] FIG. 3 illustrates an example algorithm for closed-loop operation according to embodiments. During treatment according to the algorithm in FIG. 3, both stimulation steps and evaluation steps are performed.

[0033] Treatment starts in S302, where biomarkers YS and YE are measured to get reference values YS_0 and YE_0. Then treatment proceeds to a closed loop (i.e. n increases from 1 to a final value) of both stimulation and evaluation.

[0034] During the nth stimulation step (S_n, denoted by S304), one or multiple biomarkers YS_n are evaluated and stimulation with parameters X_n is delivered for a duration TS_n with reference to criterium Cl. Cl aims at quantifying acute effects of stimulation and is violated if stimulation causes severe acute symptoms and/or side effects. As shown by S308, violation of Cl leads to S310 where n is increased to n+1 for performing a new stimulation step S_n+1 in S304 with different stimulation parameters X_n+1 ¹ X_n. X_n includes typical stimulation parameters such as the stimulation frequency, pulse amplitude, it may also include the pulse shape.

[0035] As further shown in FIG. 3, if Cl is matched, treatment proceeds to S306 where stimulation ceases after time TS_n and then to step S312 where an evaluation step (E_n) is performed for a duration TE_n. During E_n one or multiple biomarkers YE_n are evaluated. The outcome of YE_n is compared to criterium C2, which aims at quantifying long-lasting effects of stimulation.

[0036] If C2 is matched as determined in S316, the parameter set X_n is considered suitable for inducing long-lasting effects and treatment proceeds to S318 where the next stimulation step (S_n+1) is performed for the same parameter set X_n+l=X_n in S304. In this case, TS_n+l might different from TS_n. Typically TS_n+l>TS_n which aims at improving the long-lasting outcome by stimulating longer with suitable stimulation parameters. The duration of the next evaluation step may be varied as well, TE_n+l ¹ TE_n.

[0037] If C2 is violated as determined in S314, stimulation parameters are considered not suitable for inducing long -lasting effects and treatment returns to S310 where another stimulation step S_n+1 is performed using a new parameter set X_n+1¹ X_n. The durations TS_n+l and TE_n+l of the next stimulation step S_n+1 and evaluation step E_n+1, respectively, may also differ from those of previous steps.

[0038] Possible formulations of Cl used in the determinations of S306 and S308 include

(but are not restricted to) the following criteria or combinations of the following criteria:

[0039] - Motor symptoms reduce relative to baseline: YS_n at evaluation time (during

S_n), its average over multiple evaluation time steps (during S_n), or its time average over one or multiple evaluation time intervals (during S_n) reduces relative to YS_0 by more than 5%, 10%, or 15%, 20% or 25%, up to 35%.

[0040] - Motor symptoms reduce relative to previous stimulation time steps: YS_n at evaluation time (during S_n), its average over multiple evaluation time steps (during S_n), or its time average over one or multiple evaluation time intervals (during S_n) reduces relative to YS_n-l or a set of YS_m with m<n by more than 5%, 10%, or 15%, 20% or 25%, up to 35%. [0041] - Motor symptoms do not worsen compared to baseline: YS_n at evaluation time

(during S_n), its average over multiple evaluation time steps (during S_n), or its time average over one or multiple evaluation time intervals (during S_n) remains within a range of 5%, 10%, 15% or 20% of YS_0, i.e. (1-D)*YS_0 < YS_n < (1+D)*YS_0 with D=0.05, 0.1, 0.2.

[0042] - Motor symptoms do not worsen compared to previous stimulation time step:

YS_n at evaluation time (during S_n), its average over multiple evaluation time steps (during S_n), or its time average over one or multiple evaluation time intervals (during S_n) remains within a range of 5%, 10%, 15% or 20% of YS_n-l, i.e. l-D)*YS_n-l < YS_n < (l+D)*YS_n-l with D=0.05, 0.1, 0.2, or a set of YS_m with m<n.

[0043] - Motor symptoms worsen only slightly compared to baseline: the difference between YS_n and YS_0 at evaluation time (during S_n), its average over multiple evaluation time steps (during S_n), or its time average over one or multiple evaluation time intervals (during S_n) remains below YS_0*1.05 or YS_0*1.10.

[0044] Evaluation step

[0045] As shown in the example of FIG. 3, unless Cl is violated as determined in S308, a stimulation step S_n in S304 is followed by an evaluation step E_n in S312. During E_n, stimulation is paused for a duration TE_n (or only very weak stimulation is delivered). [0046] Potential long-lasting effects of stimulation with stimulation parameters X_n (that was delivered during previous stimulation step) are evaluated by measuring the biomarker(s) YE_n and comparing the result to a criterium C2. YE_n aims at quantifying the long-lasting outcome of stimulation by evaluating the degree of pathological synchrony and/or the presence/strength of symptoms in the absence of stimulation. See above for potential biomarkers. [0047] Possible choices for the criterium C2 used in the determinations made in S314 and S316 are:

[0048] - Motor symptoms reduce relative to baseline: YE_n at evaluation time (during

E_n), its average over multiple evaluation time steps (during E_n), or its time average over one or multiple evaluation time intervals (during E_n) reduces relative to YE_0 by more than 5%, 10%, or 15%, 20% or 25%, up to 35%.

[0049] - Motor symptoms reduce relative to previous evaluation steps: YE_n at evaluation time (during E_n), its average over multiple evaluation time steps (during E_n), or its time average over one or multiple evaluation time intervals (during E_n) reduces relative to YE_n-l or a set of YE_m with m<n by more than 5%, 10%, or 15%, 20% or 25%, up to 35%. [0050] - Motor symptoms do not worsen compared to baseline: YE_n at evaluation time

(during E_n), its average over multiple evaluation time steps (during E_n), or its time average over one or multiple evaluation time intervals (during E_n) remains within a range of 5% , 10%, 15% or 20% of YE_0, i.e. (1-D)*YE_0 < YE_n < (1+D)*YE_0 with D=0.05, 0.1, 0.2.

[0051] - Motor symptoms do not worsen compared to previous evaluation time step:

YE_n at evaluation time (during E_n), its average over multiple evaluation time steps (during E_n), or its time average over one or multiple evaluation time intervals (during E_n) remains within a range of 5%, 10%, 15% or 20% of YE_n-l, i.e. (l-D)*YE_n-l < YE_n < (l+D)*YE_n- 1 with D=0.05, 0.1, 0.2, or a set of YE_m with m<n.

[0052] Parameter adjustment algorithm

[0053] One preferred goal of the example method of FIG. 3 is to find a set of stimulation parameters X such that stimulation entails pronounced long-lasting after-effects, i.e. a reduction of symptoms that outlasts stimulation. [0054] In order to find a suitable parameter set X, several runs are performed and the parameter set X_n+1 for the (n+l)th stimulation step is chosen according to the outcome of the nth run. The two criteria Cl and C2 specify how stimulation parameters and durations of stimulation step S_n+1 and evaluation step E_n+1 during the (n+l)th run are chosen given results of biomarker evaluations from the nth run. Criterium Cl characterizes acute effects, measured by the biomarker(s) YS, and criterium C2 characterizes long-lasting effects, measured by the biomarker(s) YE. Potential choices for Cl and C2 were given in the previous sections. [0055] Criterium Cl aims at avoiding stimulation parameters that lead to severe acute and/or side effects. As shown in the example of FIG. 3, if Cl is violated, the stimulation step is interrupted and a new parameter set X_n+1 for the next stimulation step is selected.

[0056] Criterium C2 aims at stimulating with parameters that lead to pronounced long- lasting effects. To this end, long-lasting effects that outlast stimulation are evaluated during evaluation steps using the biomarker(s) YE_n as shown in the example of FIG. 3. If YE_n matches C2 the current stimulation parameters are considered suitable for inducing long-lasting effects. Then, X_n+1 = X_n, i.e. stimulation parameters remain the same during the next stimulation step. However, the duration of the next stimulation step TS_n+l may be increased, aiming for inducing even more pronounced long-lasting effects. If C2 is violated, a new parameter set X_n+1 is selected.

[0057] Possible choices for TS_n are times between 1 min and 2 hours, where shorter times are chosen when new parameter sets X_n are explored, i.e. after violation of Cl or C2, and longer times are chosen if C2 has been matched. Typically, matching of C2 leads to a slight increase of the stimulation time such that TS_n+l = TS_n + TD with possible TD = 1 min, 2 min, 5 min, etc.

[0058] Possible choices for TE_n are times between 1 min and 24 hours, where shorter times are chosen when new parameter sets X_n are explored, i.e. after violation of Cl or C2, and longer times are chosen if C2 has been matched.

[0059] Stimulation parameters X

[0060] Violation of either Cl or C2 leads to a change of the stimulation parameter set

X_n+1 ¹ X_n. The following discusses potential stimulation parameters. [0061] Periodic stimulation can be characterized by stimulation parameters such as the stimulation frequency f stim and the stimulation amplitude A stim together they quantify the amount of stimulation voltage or current delivered per time. A theoretical analysis for plastic networks of leaky integrate-and-fire neurons such as that described above in FIGs. 1 and 2 illustrates that both have a strong impact on the long-lasting outcome of periodic stimulation. [0062] Additionally, the present Applicant has discovered that the shape of individual stimulation pulses can have a strong impact on long-lasting effects. Varying the shape of exemplary DBS pulses in simulations on the same network of leaky integrate-and-fire neurons showed that, depending on the pulse width, periodic stimulation either caused long-lasting desynchronization or long-lasting synchronization after cessation of stimulation. Furthermore, the selected stimulation site in a multisite stimulation setup may be considered as a parameter and varied accordingly.

[0063] FIGs. 4A to 4F illustrate example aspects of how long-lasting effects of periodic stimulation depend on pulse shape. Acute and long-lasting synchronization effects of periodic stimulation with different pulse widths d_e delivered to plastic networks of synchronized leaky integrate-and-fire neurons. In FIG. 4A, stimulation pulses were characterized by the stimulation amplitude A stim and the pulse width d_e as shown by 402. FIG. 4B shows simulated distributions 404 of spiking responses k(t-s) for different pulse widths. It was found that longer pulses lead to a broader distributions of spiking response times.

[0064] FIG. 4C illustrates that acute synchronization (p_ac )~1 is observed for various combinations of A stim and d_e across various pulse widths from about 0.5 ms to about 128 ms. Meanwhile, FIG. 4D illustrates that strong stimulation with short pulses (light gray region in FIG. 4D, e.g. less than about 5 ms) entailed long-lasting desynchronization (p_ll )~0 (FIG. 4D). This is caused by a weakening of synapses during stimulation quantified by a reduced acute mean synaptic weight (w_ac) at the end of the stimulation period as shown in FIG. 4E. For low (w_ac), the network approached a desynchronized state with weak synaptic connections after cessation of stimulation. In contrast, for high (w_ac), the network approached a stable (pathological) state with synchronized neuronal activity and strong synaptic connections (see FIGs. 4D and 4F). [0065] A safe choice for initial stimulation parameters X_1 are parameter sets that yield pronounced acute effects, i.e. are used during chronic HF DBS. After evaluation of biomarkers YS_1 and YE_1 parameter changes X_n X_n+1, including changes of the stimulation frequency, amplitude, and/or the shape of individual pulses, can be performed by means of systematic variation, random variation, deterministic (e.g. chaotic) or combined random-chaotic variation or specific algorithms, e.g. gradient descent algorithms on the space of biomarkers, evolutionary algorithms.

[0066] Example system

[0067] FIG. 5 schematically illustrates an example of a system 500 for invasive treatment of a patient using multichannel desynchronizing stimulation. The apparatus 500 can be used for the treatment of disorders characterized by abnormal neuronal synchrony. The apparatus 500 includes a pulse generator 510, at least one electrode 516, which is connected to the pulse generator 510 via a wired or wireless connection, and a collection unit 526, which is similarly connected to pulse generator 510 via a wired or wireless connection. Although shown separately for ease of illustration, it should be apparent that electrode 516 and collection unit 526 can be implemented partially or fully using some or all of the same components.

[0068] The pulse generator 510 can be an implantable or semi-implantable component, and includes a signal generator 512 and a controller 514. The signal generator 512 is configured to generate electrical stimuli, such as in the form of successive bursts of electrical current or voltage, which are applied to the patient via the electrode 516. The signal generator 512 can be implemented using signal processing circuits, or using an application-specific integrated circuit. The controller 514 is connected to the signal generator 512 to direct operation of the signal generator 512 and controls the generation of stimuli. The controller 514 also can be integrated in the signal generator 512. The controller 514 can be implemented using a processor and an associated memory storing instructions executable by the processor, or using an application- specific integrated circuit.

[0069] The electrode 516 is an implantable component that is configured for placement within a tissue volume of the patient. Depending on the disorder to be treated, the electrode 516 can be implemented as a depth electrode, an epicortical electrode, or a spinal cord electrode. As shown in the example of FIG. 5, the electrode 516 is a single contact or typically multi-contact electrode, and includes a single or typically multiple stimulation contacts 518.

[0070] Depending on the neurological condition to be treated, as will be appreciated by those skilled in the art, the stimulation contact(s) 518 is/are configured for placement in a target area to be stimulated next to different areas of the tissue volume to allow the different areas to be stimulated in a temporally and/or spatially controlled pattern. The apparatus 500 shown in FIG. 5 is to be understood as an example implementation, and, more generally, the apparatus 500 can include N electrodes 516, where N is 1 or greater than 1, and can include n stimulation contacts 518 distributed over the N electrodes 516 to deliver n-channel stimulation, where n is 1 or greater than 1, such as 2, 3, 4, 5, 6, 7, 8, 9, 10, and so forth.

[0071] The apparatus 500 can be operated to apply a desynchronizing stimulation pattern to the patient. In particular, the controller 514 can direct the signal generator 512 to apply a stimulation pattern that is characterized by a set of stimulation parameters X_n as described above (e.g. stimulation amplitudes, frequencies, and pulse shapes) using electrode(s) 516 and contact(s) 518. Likewise, controller 514 can receive information on biomarkers from collection unit 526 having one or more biomarker sensors 528 (e.g. sensors for obtaining electromyography (EMG) recordings of muscular activity or accelerometer signals, or other activity related to motor symptoms, such as, abnormal oscillatory brain activity recorded as local field potentials (LFP) through depth electrodes or cortical oscillations assessed with epidural and/or epicortical electrodes), each of which can be implemented depending on the type of biomarker to be measured (e.g. EEG power or LFP power in symptom related frequency bands, i.e. theta or beta band, or interactions of different rhythms (oscillations), e.g., in terms of their phase amplitude coupling). Collection unit 526 can similarly be implemented in many various ways depending on the type of biomarker to be measured and can communicate with controller 514 using any variety of wired or wireless means. Controller 514 as shown in the example apparatus 500 of FIG. 5 can also implement a method such as that shown in FIG. 3 using software or firmware as understood by those skilled in the art.

[0072] The herein described subject matter sometimes illustrates different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are illustrative, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as "associated with" each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being "operably connected," or "operably coupled," to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being "operably coupleable," to each other to achieve the desired functionality. Specific examples of operably coupleable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components.

[0073] With respect to the use of plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

[0074] It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as "open" terms (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "includes" should be interpreted as "includes but is not limited to," etc.).

[0075] Although the figures and description may illustrate a specific order of method steps, the order of such steps may differ from what is depicted and described, unless specified differently above. Also, two or more steps may be performed concurrently or with partial concurrence, unless specified differently above. Such variation may depend, for example, on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations of the described methods could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps, and decision steps. [0076] It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation, no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim recitation to inventions containing only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an" (e.g., "a" and/or "an" should typically be interpreted to mean "at least one" or "one or more"); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations," without other modifiers, typically means at least two recitations, or two or more recitations).

[0077] Furthermore, in those instances where a convention analogous to "at least one of

A, B, and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, and C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to "at least one of A, B, or C, etc." is used, in general, such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, or C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "A or B" will be understood to include the possibilities of "A" or "B" or "A and B." [0078] Further, unless otherwise noted, the use of the words “approximate,” “about,”

“around,” “substantially,” etc., mean plus or minus ten percent.

[0079] Although the present embodiments have been particularly described with reference to preferred examples thereof, it should be readily apparent to those of ordinary skill in the art that changes and modifications in the form and details may be made without departing from the spirit and scope of the present disclosure. It is intended that the appended claims encompass such changes and modifications.

Claims

WHAT IS CLAIMED IS:

1. A method for neuronal desynchronization comprising: repeating iterations of a treatment of one or both of: delivering stimulation to a target brain region; and evaluating neuronal synchrony during the delivery of the stimulation and after cessation of the delivering stimulation to the target brain region.

2. The method of claim 1, wherein stimulation parameters of delivering stimulation during a next iteration of treatment are adjusted based on the evaluating performed during a current iteration of treatment.

3. The method of claim 1, wherein before treatment, one or both of biomarkers YS and YE are measured to get reference or baseline values YS_0 and YE_0.

4. The method of claim 3, wherein YS measures acute effects of stimulation.

5. The method of claim 3, wherein YE measures long-lasting effects of stimulation.

6. The method of claim 2, wherein the simulation parameters are evaluated with respect to a criterium Cl which aims at quantifying acute effects of stimulation and which is violated if stimulation causes severe acute symptoms and/or side effects.

7. The method of claim 6, wherein violation of Cl in treatment step n leads to performing a new treatment step n+1 with different stimulation parameters X_n+1 ¹ X_n.

8. The method of claim 7, wherein X_n includes one or more of stimulation frequency, pulse amplitude, and pulse shape.

9. The method of claim 6, wherein if Cl is matched at time TS_n in treatment iteration n, stimulation ceases after time TS_n and then evaluation is performed for a duration TE_n.

10. The method of claim 9, wherein during evaluation one or multiple biomarkers YE_n are evaluated and compared to criterium C2, which aims at quantifying long-lasting effects of stimulation.

11. The method of claim 10, wherein if C2 is matched in treatment iteration n, the parameter set X_n is considered suitable for inducing long-lasting effects and a next treatment iteration n+1 is performed.

12. The method of claim 11, wherein the next treatment iteration includes performing the stimulating using the same parameter set X_n+l=X_n.

13. The method of claim 12, wherein TS_n+l is greater than TS_n which aims at improving the long-lasting outcome by stimulating longer with suitable stimulation parameters.

14. The method of claim 10, wherein if C2 is violated in treatment iteration n, stimulation parameters are considered not suitable for inducing long-lasting effects and a next treatment iteration n+1 is performed with a new parameter set X_n+1¹ X_n.

15. The method of claim 14, wherein stimulating and evaluating durations TS_n+l and TE_n+l of the next treatment iteration differ from TS_n and TE_n.

16. The method of any of claims 6-15, wherein Cl includes one or more of: motor symptoms reduce relative to baseline; motor symptoms reduce relative to previous stimulation time steps; motor symptoms do not worsen compared to baseline; motor symptoms do not worsen compared to previous stimulation time step; and motor symptoms worsen only slightly compared to baseline.

17. The method of any of claims 6-16, wherein C2 includes one or more of: motor symptoms reduce relative to baseline; motor symptoms reduce relative to previous evaluation time steps; motor symptoms do not worsen compared to baseline; motor symptoms do not worsen compared to previous evaluation time steps; and motor symptoms worsen only slightly compared to baseline.

18. The method of any of claims 1-17, wherein evaluating neuronal synchrony is performed by evaluating one or more biomarkers.

19. The method of claim 18, further comprising obtaining information corresponding to the one or more biomarkers using sensors for obtaining electromyography (EMG) recordings of muscular activity or accelerometer signals.

20. The method of claim 18, further comprising obtaining information corresponding to the one or more biomarkers using sensors for obtaining electromyography (EMG) recordings of other activity related to motor symptoms, including one or more of abnormal oscillatory brain activity recorded as local field potentials (LFP) through depth electrodes or cortical oscillations assessed with epidural and/or epicortical electrodes.

21. The method of claim 18, further comprising obtaining information corresponding to the one or more biomarkers using sensors for obtaining EEG power or LFP power in symptom related frequency bands, i.e. theta or beta band, or interactions of different rhythms (oscillations).

22. A method for neuronal desynchronization comprising: repeating iterations of a treatment of one or both of: delivering stimulation to a target brain region; and evaluating neuronal synchrony during the delivery of the stimulation and after cessation of the delivering stimulation to the target brain region; and finding a set of stimulation parameters X such that stimulation entails pronounced long- lasting after-effects.

23. The method of claim 22, wherein several treatment iterations are performed and the parameter set X_n+1 for the (n+l)th treatment iteration is chosen according to the outcome of the nth iteration.

24. The method of claim 23, wherein two criteria Cl and C2 specify how stimulation parameters and durations of stimulation S_n+1 during iteration n+1 and evaluation E_n+1 during iteration n+1 are chosen based on results of biomarker evaluations from the nth iteration.

25. The method of claim 24, wherein criterium Cl characterizes acute effects, measured by the biomarker(s) YS and criterium C2 characterizes long-lasting effects, measured by the biomarker(s) YE.

26. The method of claim 22, wherein duration of stimulating during treatment iteration n (TS_n) is between 1 min and 2 hours.

27. The method of claim 22, wherein duration of evaluating during treatment iteration n (TE_n) is between 1 min and 24 hours.

28. The method of claim 23, wherein parameter set Xn includes stimulation frequency f stim and the stimulation amplitude A stim, which together quantify the amount of stimulation voltage or current delivered per time.

29. The method of claim 23, wherein parameter set Xn includes the shape of individual stimulation pulses.

30. The method of claim 29, wherein the shape includes pulse width.

31. The method of claim 23, wherein the parameter set Xn includes a selected stimulation site.

32. The method of claim 30, wherein pulse width is allowed to vary from about 0.5 ms to about 128 ms during treatment.

33. A system for neuronal desynchronization comprising: a pulse generator including a signal generator and a controller; at least one electrode connected to the pulse generator via a wired or wireless connection; and a collection unit connected to the pulse generator via a wired or wireless connection, wherein the controller is configured to implement a treatment including: causing pulse generator and the at least one electrode to deliver stimulation to a target brain region; and evaluate neuronal synchrony during the delivery of the stimulation and after cessation of the delivering stimulation to the target brain region using information received from the collection unit.

34. The system of claim 33, wherein the pulse generator is an implantable or semi-implantable component.

35. The system of claim 33, wherein the signal generator is configured to generate electrical stimuli, such as in the form of successive bursts of electrical current or voltage, which are applied to patient via the at least one electrode.

36. The system of any of claims 33-35, wherein the at least one electrode is an implantable component that is configured for placement within a tissue volume of a patient.

37. The system of claim 36, wherein the at least one electrode comprises a depth electrode, an epicortical electrode, or a spinal cord electrode.

38. The system of any of claims 33-37, wherein the at least one electrode is a single contact or multi-contact electrode, and includes a single or multiple stimulation contacts.

39. The system of any of claims 33-38, wherein the collection unit comprises one or more biomarker sensors.

40. The system of claim 39, wherein the biomarker sensors are configured for obtaining electromyography (EMG) recordings of muscular activity or accelerometer signals, or other activity related to motor symptoms, such as, abnormal oscillatory brain activity recorded as local field potentials (LFP) through depth electrodes or cortical oscillations assessed with epidural and/or epicortical electrodes), each of which can be implemented depending on the type of biomarker to be measured (e.g. EEG power or LFP power in symptom related frequency bands, i.e. theta or beta band, or interactions of different rhythms (oscillations), e.g., in terms of their phase amplitude coupling).