Reactivation of emergent task-related ensembles during slow-wave sleep after neuroprosthetic learning

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1 r t i c l e s Rectivtion of emergent tsk-relted ensemles during slow-wve sleep fter neuroprosthetic lerning Tnuj Gulti,2, Dhkshin S Rmnthn,3,4, Chelse C Wong,2 & Krunesh Gnguly,2 npg 24 Nture Americ, Inc. All rights reserved. Brin-mchine interfces cn llow neurl control over ssistive devices. They lso provide n importnt pltform for studying neurl plsticity. Recent studies hve suggested tht optiml enggement of lerning is essentil for roust neuroprosthetic control. However, little is known out the neurl processes tht my consolidte neuroprosthetic skill. On the sis of the growing ody of evidence linking slow-wve ctivity (SWA) during sleep to consolidtion, we exmined whether there is offline processing fter neuroprosthetic lerning. Using rodent model, we found tht, fter successful lerning, tsk-relted units specificlly experienced incresed locking nd coherency to SWA during sleep. Moreover, spike-spike coherence mong these units ws sustntilly enhnced. These chnges were not present with poor skill cquisition or fter control wke periods, demonstrting the specificity of our oservtions to lerning. Notly, the time spent in SWA predicted the performnce gins. Thus, SWA ppers to e involved in offline processing fter neuroprosthetic lerning. Brin-mchine interfces (BMIs) hve the potentil to semlessly merge the computtionl power of the motor system with tht of rtificil electronic systems. Reserch into the development of BMIs hs flourished over the pst decde, leding to impressive demonstrtions of rodents 3, non-humn primtes 4 nd humns controlling prosthetic devices 3 in rel-time through modultion of neurl signls. This ody of work hs lso identified tht dptive processes, oth in the motor system nd in the lgorithms tht trnsform neurl ctivity into prosthetic control signls (tht is, decoders), re essentil for chieving stle neuroprosthetic control 3,6,8,9,4,5. For exmple, prcticing neuroprosthetic control over multiple sessions in the setting of fixed decoder is known to result in persistent improvements in performnce 4. Moreover, long-term dpttion of decoders t rte tht is seemingly concordnt with neurl lerning rtes cn e essentil for long-term stle performnce 5. Together, these studies underscore the importnce of optiml enggement of long-term neurl lerning mechnisms 9,4,5. However, the specific neurl process tht stilizes newly cquired prosthetic skill remins incompletely understood. Given the growing ody of literture indicting tht corticl SWA is ssocited with offline processing 6 9, we hypothesized tht such processing fcilittes direct corticl control of n rtificil ctutor. Studies in humns hve suggested tht offline processing during overnight sleep 2 23, s well s during dytime nps 24, fcilittes memory consolidtion. Motor tsk performnce is lso known to improve fter sleep versus n equivlent mount of wkefulness Although SWA hs een directly implicted in the consolidtion of motor skills 26 3, it remins poorly understood how neurl ensemles in motor cortex re precisely modified during SWA fter skill cquisition. Wheres most theories suggest tht rectivtion of corticl neurons during SWA is importnt for consolidtion 3, there is, to the est of our knowledge, little experimentl support of this for procedurl memory formtion. In this context, BMIs offer powerful tool to directly modulte single units, therey llowing precise chrcteriztion of how oth tskrelted (TR) nd tsk-unrelted () corticl units re differentilly processed in motor cortex during SWA. In these experiments, rts were trined to control the ngulr velocity of feeding tue vi direct modultion of corticl units through opernt conditioning. We hypothesized tht, fter neuroprosthetic skill cquisition, TR units would e differentilly processed from units during SWA. RESULTS After implnttion of microelectrodes in M, we trined six rts to exert direct neurl control of the ngulr velocity of mechnicl ctutor tht could lso deliver wter (Fig. ). A liner decoder with rndomized weights typiclly converted the firing rtes of two rndomly selected units (herefter referred to s direct units) into the ngulr velocity of the ctutor (Supplementry Fig. nd Online Methods). We lso recorded multiple other units tht were not cuslly linked to ctutor movements (herefter referred to s indirect units). The decoder weights were held constnt during the session to exclusively rely on neurl lerning mechnisms. Ech tril strted with the simultneous delivery of n uditory tone nd the opening of door to llow ccess to the tue (Fig.,). At the strt of ech tril, the ngulr position of the tue ws set to (P ). If the ngulr position of the tue ws held for >3 ms t position P 2 (9 ), defined mount of wter ws delivered (tht is, successful tril). A tril ws stopped if this ws not chieved within 5 s (tht is, unsuccessful tril). At the end of tril, the door ws closed nd the ctutor ws returned to position P. Over the course of typicl 2-h prctice session, nimls showed improvements in tsk performnce, with significnt reduction in the time to successful tril completion nd decrese in the numer of unsuccessful trils (Fig. c,e). Specificlly, of 9 such trining Neurology nd Rehilittion Deprtment, Sn Frncisco VA Medicl Center, Sn Frncisco, Cliforni, USA. 2 Deprtment of Neurology, University of Cliforni, Sn Frncisco, Cliforni, USA. 3 Deprtment of Psychitry, Sn Frncisco VA Medicl Center, Sn Frncisco, Cliforni, USA. 4 Deprtment of Psychitry, University of Cliforni, Sn Frncisco, Cliforni, USA. Correspondence should e ddressed to K.G. (krunesh.gnguly@ucsf.edu). Received 8 April; ccepted 2 June; pulished online 6 July 24; doi:.38/nn.3759 nture NEUROSCIENCE VOLUME 7 NUMBER 8 AUGUST 24 7

2 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. Figure Direct control of motor cortex units. () Direct neurl control of feeding tue (θ = ngulr position). Ech tril strted with the tue t P. () Tril strted with n udio tone cue nd opening of the door. A successful tril required movement of the tue to P 2 within 5 s. (c) Chnge in tsk completion time s function of tril numer (line shows moving verge of 2 trils). (d) Angulr position of the tue is shown from single session. Peri-event histogrm from erly nd lte trils from single session re shown in left nd right pnels, respectively. Thick line represents men nd shded re is s.e.m. (e) Comprison of time to tril completion nd chnge in percentge of unsuccessful trils for roust lerning nd poor lerning sessions (men ± s.e.m.). In roust lerning sessions, time to rewrd reduced significntly over trils (t test, t 4 = 7.3, P < 5 ) nd the proportion of unsuccessful trils lso dropped significntly (t test, t 4 = 8.58, P < 6 ). In poor lerning sessions, time to rewrd did not chnge significntly (t test, t 3 =.73, P =.8). Similrly, the proportion of unsuccessful trils did not chnge significntly (t test, t 3 =.52, P =.68). (f) Histogrm of percentge chnge in modultion depth (MD chnge ) for ech of the three ctegories of units. sessions, there were 5 roust lerning sessions with significnt reductions for oth Roust lerning metrics (n = 5 sessions; erly completion time, 2.42 ±.74 s; lte completion time, 5.93 ±.48 (men ± s.e.m.); t test, t 4 = 7.3, P < 5 ; Fig. e). Moreover, the percentge of unsuccessful trils significntly decresed from ± 4.4% to 6. ±.5% (t test, t 4 = 8.5, P < 6 ). For the remining four sessions, these vlues did not improve with trining (tht is, poor lerning). In the roust lerning sessions, we lso found tht the pth of the ctutor tken from position P to P 2 ecme direct (Fig. d). For direct units tht were cuslly linked to ctutor movements vi the decoder (tht is, irect or ), nerly ll experienced significnt chnges in TR modultion t the end of session (96% of 27 units with significnt increse in modultion depth). We ssigned weights in the decoder tht rnged from + to. Although we did not see suppression of ctivity reltive to the seline, there ws significntly greter modultion of the units ssigned positive weights (tht is, TR + d ) thn negtive weights (tht is, TR d ) (t test, t 25 = 5.7, P < 4 ; Supplementry Fig. 2 c). Direct units were lso significntly more likely to experience chnge in modultion thn indirect units (n = 5 sessions; direct, 96.7% ± 3.5%; indirect, 65.7 ± 3.7%; t test, t 28 = 5.84, P < 4 ). However, given the growing notion tht susets of indirect units likely contriute to neuroprosthetic control 32 34, we further suclssified such units s eing either tsk-relted ( ) or sed on chnges in modultion depth with lerning. A unit ws declred if its post-lerning chnge in firing rte ws 2.5 s.d. ove the seline firing rte (Online Methods). Moreover, we did not find prepondernce of prticulr cell types in either ctegory, s determined y the width of the record spike (Supplementry Fig. d). For susequent nlysis, we respectively used 27, 8 nd 39 units in 5 BMI trining sessions (Supplementry Tle ). TR ( nd ) units experienced lrge chnges in modultion depth (Fig. f). Notly, fter lerning, the temporl profiles of ctivtion c e 5 Neurl signls Brin-controlled feeding tue P 2 2 Trils θ P Wter Tril strt Time out (5 s) Audio cue door open 5 Erly Tril time Lte Erly Lte Erly Lte Erly Door close Lte 65 Poor lerning Percentge unsuccessful d Rte (Hz) Rte (Hz) Θ ( ) Rte (Hz) f Count Before lerning P Tril onset After lerning (Fig. d) for nd were not significntly different (time to pek firing: direct, 3. ±.2 s;, 3.3 ±. s; t test, t 33 =.8, P =.24), suggesting tht these two distinct groups of TR units ecme functionlly nd temporlly coupled with lerning nd successful tsk performnce. We lso sw evidence for chnges in the spike-triggered locl field potentil (LFP) for TR units tht ws not present for the units (Supplementry Fig. 2e,f). Incresed locking to SWA fter lerning Given tht previous studies hve suggested link etween slow-wve sleep (SWS) nd motor lerning 6 8, we first exmined whether the spike-field reltionship during SWS is ltered fter roust lerning sessions. To look for signtures of offline processing, we first ssessed whether individul units (, nd ) experienced chnges when compring the pre- nd post-sws round successful trining session (herefter referred to s SWS pre nd SWS post ; Online Methods nd Supplementry Fig. 3). Specificlly, we used spike-triggered verging (STA) to quntify the reltionship etween spiking nd SWA. The STA provides n intuitive estimte of how neurl spiking is modulted y corticl oscilltions. To SWS durtions, we used the first min of SWS pre nd SWS post for this nlysis (Online Methods). Notly, we found tht nd units consistently experienced significnt increse in the pek-to-pek mplitude of the STA in comprison to units even in the sence of ny chnges in the LFP power (Fig. 2). This ppered to e the result of greter likelihood of spikes occurring t specific phse of the SWA (Fig. 2). Although nd units experienced 48.7 ± 5.78% nd ± 3.78% increses in STA mplitude, respectively, units experienced significnt net.44 ± 3.44% reduction (one-wy ANOVA, F 2,7 = 52, P 2 2 s MD chnge (%) Trils Trils Trils 8 VOLUME 7 NUMBER 8 AUGUST 24 nture NEUROSCIENCE

3 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. Figure 2 Chnges in phse-locking nd coherent spiking during SWS fter lerning. () Exmples of 5 rw LFP trces during SWS pre nd SWS post for tsk-relted direct neuron. Superimposed is the men trce from n SWS epoch. Ech trce ws ligned to time of spike (dshed line). () Percent chnge in STA mplitude for ech of the three ctegories of units in 5 sessions (men ± s.e.m., one-wy ANOVA, F 2,7 = 52, P < 7 ; post hoc t test showed significnt difference for the nd, nd nd groups, P <.5). (c) Filtered (.3 3 Hz) nd unfiltered STAs during SWS efore nd fter successful cquisition of neuroprosthetic skill (shded res re s.e.m.). (d) Sctter plot showing reltionship of depth of modultion during tsk performnce to chnge in STA mplitude (R =.85, Spermn correltion, P <.5). Color code represents ech clss of neuron. Dshed lines re the vlues for the x nd y xes. (e) Comprison of the power spectr from min of SWS pre nd SWS post from single experiment (shded re is s.e.m.). Inset compres the power in the.3 3-Hz nd for multiple experiments (n = 5, normlized to SWS pre for ech experiment; verge chnge of 3. ± 6.48% (men ± s.e.m.), t test, t 4 =.83, P =.79). P < 7, post hoc t test showed significnt difference for nd ; nd nd groups, P <.5; Fig. 2). In contrst, we did not find ny significnt differences when we clculted the STA for spindle (8 2 Hz) nd ripple ( 3 Hz) frequency nds (one-wy ANOVA, F 2,7 =.35, P =.69 for spindle-nd comprisons; one wy ANOVA, F 2,7 =.27, P =.75 for ripple nd; Supplementry Fig. 4). We next ssessed whether chnges in the power or frequency of SWS or firing properties of units could ccount for our oservtions. There were no significnt chnges in either the SWA power (verge chnge of 3. ± 6.48%, t test, t 4 =.83, P =.79; Fig. 2e), density of delt wves in SWS (.82 ± 5.67 wves min versus 2.86 ± 6.9 delt wves min, t test, t 4 =.48, P =.6; Supplementry Fig. 5c), firing rte (6.42 ±.43 Hz versus 7. ±.34 Hz, t test, t 73 =., P =.27; Supplementry Fig. e g) or chnges in ursting properties (Kolmogorov-Smirnov test, P >.5 for over 9% units; Supplementry Fig. 5,). We lso did not find ny evidence for significnt reltionship etween the chnges in the firing rtes of individul units nd chnges in STA mplitude (liner regression R 2 =., P =.29; Supplementry Fig. e) or the chnges in the LFP power reltive to chnge in STA mplitude (liner regression R 2 =.33, P =.64). Moreover, we did not find evidence for sptiotemporl chnges in the occurrence nd rte of SWA (Supplementry Fig. 6). To further estlish link etween the tsk-dependent modultion tht emerges fter lerning nd the chnge in phse-locking to SWA, we exmined the reltionship etween the extent of tsk-dependent modultion nd the percent chnges in the STA mplitude. Notly, we found tht the degree of TR firing rte modultion significntly predicted the extent of incresed STA mplitude during the susequent SWS (Spermn correltion, r 72 =.85, P <.5; Fig. 2d). The non-liner nture of the curve is likely the result of the significnt reduction in STA mplitude without mirror symmetric reduction in depth of modultion for units. Consistent with the notion of link.3 SFC.3 3 Hz 2 Frequency (Hz) Hz 2 Frequency (Hz) c SFC mg chnge (%) 7 3 c Filtered STA SWS pre µv 25 ms SWS post Unfiltered STA 5 µv 25 ms µv 2 ms etween the extent of tsk-dependent modultion nd the chnge in STA mplitude, we found tht + units experienced significntly greter chnge in the STA mplitude thn units (t test, t 25 = 3.37, P <.5; Supplementry Fig. 2d). Together, these results suggest tht there is greter locking of the TR corticl spiking to SWA fter successful lerning of direct corticl control. To further confirm tht chnges in STA mplitude reflect greter phse-locking of nd units, we used spike-field coherence (SFC) to mesure coherence in the.3 3-Hz nd etween the spiking ctivity nd the LFP. The SFC mesure complements the STA nlysis in tht it is not sensitive to chnges in power nd cn redily ssess ll frequencies. The mgnitude of SFC, which vries s function of frequency nd yields vlue etween nd, showed similr trend of enhnced SFC for nd units in the SWA frequency rnge (Fig. 3 nd Supplementry Fig. 7). Consistent with the STA results in the spindle/ripple nds, there were no detectle differences for other frequency nds (tht is, multitper method using jckknife-sed confidence intervls). The, nd groups experienced chnge in SFC mgnitude of 53.8 ± 7.49%, 6.29 ± 3.6% nd 2.2 ± 4.4%, respectively. Thus, TR units (oth nd ) showed significnt increse in SFC mgnitude compred with units (one-wy ANOVA, F 2,7 = 77, P < 23, post hoc t test showed significnt difference for nd ; nd groups, P <.5). There were no significnt chnges in SFC phses of the TR units etween SWS pre nd SWS post (.8 ±.4 rdins, men ± s.e.m., net chnge in phse nd P =.44, Wtson-Willims circulr t test d e STA mp chnge (%) STA mp chnge (%) Log power MD chnge (%) Hz Power (norm) SWS pre SWS post Frequency (Hz) 2 Figure 3 Chnges in SFC fter lerning. () Exmple plot of SFC s function of frequency efore (lue) nd fter (red) skill cquisition for direct pir. The lighter nd is the jckknife error. The ox highlights the.3 3-Hz nd. () Tsk-unrelted SFC. (c) Men chnges in SFC for the vrious ctegories of units (men ± s.e.m., one-wy ANOVA, F 2,7 = 77, P < 23, post hoc t test showed significnt difference for nd, nd nd groups, P <.5). nture NEUROSCIENCE VOLUME 7 NUMBER 8 AUGUST 24 9

4 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. SSC Counts Counts Hz 2 Frequency (Hz) Hz 6 SWS 6 pre SWS pre 6 SWS post 6 SWS post 5 2 Frequency (Hz) Time (ms) Time (ms) Figure 4 Chnges in SSC fter lerning. () Exmple plot of SSC s function of frequency efore (lue) nd fter (red) skill cquisition for direct pir. The lighter nd is the jckknife error. The ox highlights the.3 3-Hz nd. Below re the respective cross-correlogrms from SWS pre nd SWS post. () SSC of tsk-unrelted pir. (c) Men chnges in SSC for the vrious ctegories of neuron pirs re shown s men ± s.e.m. (one-wy ANOVA, F 5,27 = 45, P < 29 ; post hoc t test, P <.5). for comprison of phses pre- nd post-lerning; Supplementry Fig. 7). Together with the findings from the STA nlysis, these results confirm tht TR units, in contrst with units, were significntly more phse-locked to SWA fter successful lerning. Incresed spike-spike coherence fter lerning We susequently ssessed whether there re chnges in the functionl connectivity mong the recorded M neurl ensemles during SWS post. We clculted the mgnitude of spike-spike coherence (SSC) for oth SWS post nd SWS pre for direct units ( ) reltive to ll other units (tht is,,, nd neuronl pirs). We used shuffling method to ssess significnt SSC increses in SWS post in comprison to SWS pre. We oserved tht only the SWS post SSC curves of tsk relted unit pirs showed significnt increse in the.3 3-Hz nd (Fig. 4,). We found surprisingly roust increses in SSC (.3 3-Hz rnge) for TR pirs (tht is, nd ) fter successful lerning (93.5 ± 6.5% increse for 2 pirs nd ± 4.98% increse for 8 pirs; Fig. 4c). In comprison, the chnge in SSC for the pirs ws 3.4 ± 5.% (Fig. 4c, one wy ANOVA, F 2,56 = 65, P < 2 ; post hoc t test showed significnt differences etween, nd pirs; nd, nd pirs, P <.5). When we used cross correltion nlysis, we lso found similr results (one wy ANOVA, F 2,56 = 27, P < ; Fig. 4, nd Supplementry Fig. 8). This indictes tht TR units re significntly more likely to fire synchronously thn units during SWS post. Lck of chnges fter poor lerning We next determined whether these chnges in STA, SFC nd SSC re specific to successful lerning. We nlyzed four sessions in which nimls performed the BMI tsk, ut did not demonstrte roust lerning (Figs. e nd 5). During these sessions, mny of the trils ended ecuse the 5-s timeout ws reched. The respective times to completion were 2.22 ±.74 s for erly trils versus.2 ±.79 s for lte trils (t test, t 3 =.7, P =.8; Fig. e), nd the percentge of unsuccessful trils remined unchnged (52.5 ± 3.29% erly versus 54.7 ± 6.36%, for lte; t test, t 3 =.52, P =.68). In these sessions, TR units did not experience n increse in STA mplitude (Fig. 5,). The men STA mplitude chnge for units ws 2.3 ± 3.9% (n = 8 units). In ddition, the SSC etween pirs did not c SSC mg chnge (%) 2 4 increse in mnner similr to tht during roust lerning sessions ( 5.5 ±.32%, n = 4 pirs). These were significntly different from the corresponding vlues in roust lerning sessions (t test, t 4 = 3.9, P <.). Moreover, we lso performed control experiments in which rodents were plced in the BMI chmer, ut did not perform ny tsk (control sleep; Fig. 5). Insted, they received n equivlent mount of wter rewrd over time period tht ed typicl prctice session. The STA efore nd fter these control sessions did not show ny increse. The overll chnge ws significntly different from units from roust lerning sessions (n = 3 sessions with 32 units,.49 ± 2.74% STA chnge, one wy ANOVA, F 2,64 = 59, P < 4 with post hoc t test showing significnt difference, P <.5; Fig. 5). This suggests tht fctors such s sustined ttention, rewrd nd ttempts t execution without evidence of lerning re not sufficient to trigger incresed coherent ctivtion during the SWA post. Together, this further supports conclusion tht enhnced locking occurs only for tsk-relted ensemles linked to lerning. Rectivtion of emergent tsk-relted ensemles The nlysis presented ove exmined chnges in spike-field reltionships nd pirwise interctions mong TR units fter roust nd poor lerning. We next used method previously developed to identify tsk-relted neuronl cell ssemlies nd their coordinted rectivtion This method uses principl components nlysis (PCA, Online Methods) to identify significnt signl components, or ensemles of neurons tht ecome temporlly correlted during lerning nd tsk performnce. The output of this nlysis re principle components (PCs), consisting of n rry of weights ssigned to ech unit in the identified ensemle, nd the eigenvlue, numericl vlue tht represents the extent of totl vrince tht is cptured y given PC; PCs with the lrgest eigenvlues cpture the most vrince (Fig. 6,). Whether clculted PC represents significnt temporlly correlted pttern of ctivity is determined y λ mx, tht is, the highest eigenvlue tht rises out of n equivlently sized rndom mtrix sed on the Mrchenko-Pstur lw (Fig. 6). Thus, PCs with eigenvlues greter thn λ mx were considered signl components, wheres those elow λ mx were considered s rising from chnce interctions. We strted y estimting the signl components (tht is, ensemle ptterns of ctivity) linked to successful lerning (Fig. 6,). Notly, we found evidence for significnt signls only for roust lerning sessions (Fig. 6). In contrst, poor-lerning sessions generted PCs tht were never greter thn λ mx. We then exmined whether there ws chnge in the rectivtion strength during SWS post y clculting the instntneous rectivtion 5 Trils 5 µv 25 ms STA mp chnge (%) 6 2 Roust lerning ( neurons) Poor lerning ( neurons) Control sleep (ll neurons) Figure 5 Lck of increse in coherent spiking with poor lerning nd in control sleep. () Plot of tril times versus tril numer. Right, the STA efore nd fter (shded re is s.e.). () Men chnges in direct unit STA for roust lerning (reproduced from Fig. 2) nd poor lerning sessions. Also shown re units from control wke periods (men ± s.e.m., one-wy ANOVA, F 2,64 = 59, P < 4 ; significnt post hoc t tests, P <.5). VOLUME 7 NUMBER 8 AUGUST 24 nture neuroscience

5 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. Figure 6 Chnges in rectivtion strength fter lerning. () Peri-event firing rte modultion of units from single session. Only TR units re shown nd sorted y weights in the first PC. () Correltion mtrix eigenvlues clculted from ctivity during tsk performnce (RL, roust lerning; PL, poor lerning). Dshed line is the signl threshold (λ mx ), defined s the theoreticl upper ound for rndomized spike trin. (c) Rectivtion strength during SWS pre nd SWS post for RL nd PL. (d) Men popultion differences etween SWS pre nd SWS post distriutions of rectivtion strengths for RL (n = 5 sessions) nd PL (n = 4 sessions). P <.5 logrnk test. (e) Event-triggered verge of rectivtion strength centered on mximum delt wve negtivity (time = ) for SWS post (shded re represents s.e.m.). strength of signl components The rectivtion strength is n instntneous mesure of how similr the ensemle ctivity during the SWS epoch is to tht identified during the wke period using the PCA nlysis. Notly, y compring the SWS pre nd the SWS post epochs, we cn identify chnges tht re specificlly linked to lerning control. After roust lerning sessions, the oserved strength of rectivtion of the signl component ws gretly enhnced in comprison to SWS pre (Fig. 6c,d). Moreover, this ws not evident during the wke spontneous periods efore the onset of SWS (n = 5, logrnk test, P <.5; Supplementry Fig. 9). Across multiple sessions, the rectivtion strength of the tsk-relted ensemle during SWS post ws significntly greter fter roust lerning thn fter poor lerning (logrnk test, P <.5; Fig. 6d). We lso exmined the specific reltionship etween instntneous rectivtion nd SWA. We therefore performed delt wve triggered verging of rectivtion strength. We found tht cell ssemly rectivtion events occurred in concert with mximum delt wve negtivity (Fig. 6e). The rtio of pek rectivtion t the time of mximum delt negtivity to the seline rectivtion strength ws significntly greter fter roust lerning thn either fter poor lerning (t test, t 7 = 3.6, P <.5; Fig. 6e) or during spontneous wke periods fter roust lerning (t test, t 4 = 7.37, P < 5 ; Supplementry Fig. 9c,d). Improvements in tsk performnce We lso conducted experiments in which the nimls performed the tsk during two sessions (referred to s Block nd Block 2 ) using the Sleep 5 Block Sleep 2 Block 2 Sleep 3 STA 2 STA 2 3 Trils 8 Trils 35 c d e STA mp chnge (%) Block end Block 2egin Sleep 2 Sleep 2 3 µv 25 ms 5 f SFC mg chnge (%) Block 2egin Block 2end Time improvement (%) 6 R =.85, P =. 3 9 STA mp chnge (%) TR g d SSC mg chnge (%) 4 c Rectivtion strength Rectivtion strength d Counts PC weights..8 Firing rte (norm) 35 Tsk strt SWS pre RL 2,5 SWS pre sme decoder, ut seprted y period of spontneous ctivity nd sleep (Fig. 7). Notly, we found tht tsk performnce consistently improved t the strt of Block 2 (P <.5 for ech of the eight individul comprisons of the lst 3 trils from Block nd the first 3 trils from Block 2, overll t test, t 7 = 4.87, P <.5; Fig. 7). Such improvements were lso evident if we compred the est performnce t the end of Block with tht of erly Block 2 (t test, t 7 = 4.38, P <.5; Supplementry Fig. ). Tht incresed motivtion fter rest does not ccount for this finding is supported y the lck of significnt 2,5 RL PL 2 Rectivtion strength PL e Rectivtion strength Eigenvlue Eigenvlue SWS post 2,5 2, SWS post RL PL PC numer mx mx 24 8 RL PL.5 Figure 7 Continued tsk performnce fter sleep. () Plot of time to tsk completion versus tril numer. Dt re presented s in Figure c. Trce inset shows the STA from the respective sleep for tsk-relted neuron. STA scles re the sme (shded re represents s.e.). () Averge time to rewrd t the end of first trining session (Block end ) compred with the eginning of second session (Block 2egin ). P <.5 for ll eight comprisons (overll t test, t 7 = 4.87, P <.5). (c) Averge tril time t the eginning of second session (Block 2egin ) compred with its end (Block 2end ) (overll t test, t 7 =.87, P =.4). (d) Reltionship etween men chnge in STA mplitude for units nd the improvement in performnce. Also noted re the correltion coefficient nd P vlue for the Spermn test. (e) Reltive chnges in STA mplitude for nd units etween Sleep 2 nd Sleep 2 3. STA chnges reduced to for oth ctegories significntly (men ± s.e.m.;, t test, t 4 = 7.77, P < 8 ;, t test, t 53 =.6, P < 22 ). (f) Reltive chnge in SFC mgnitude (men ± s.e.m.). SFC mgnitudes were lso reduced significntly (, t test, t 4 = 5.84, P < 6 ;, t test, t 53 = 2.2, P < 23 ). (g) Reltive chnge in SSC mgnitude (men ± s.e.m.). SSC mgnitudes were lso reduced for oth pirs nd for pirs etween Sleep 2 nd Sleep 2 3 ( pirs, t test, t 7 = 5.25, P < 4 ; pirs, t test, t 53 =.45, P < 8 ). nture NEUROSCIENCE VOLUME 7 NUMBER 8 AUGUST 24

6 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. performnce chnges during Block 2 itself (P >.5 for ech of the eight comprisons, overll t test, t 7 =.87, P =.4; Fig. 7c). Moreover, lthough the totl period ws the sme etween the two locks, the time spent in SWS fter Block ws positively correlted with the extent of improvement t the eginning of Block 2 (Spermn correltion, r(6) =.67, P <.5). Notly, the extent of improvement ws lso positively correlted with the men chnge in STA mplitude etween Sleep nd Sleep 2 for units (Spermn correltion, r(6) =.85, P <.5; Fig. 7d). Chnges with continued tsk performnce We first compred the STA mplitude nd SFC mgnitude chnges for nd units (n = 8 experiments, 5 nd 47 units for Sleep 2 nd Sleep 2 3 ). With continued execution of the tsk, there ws no further increse in coherent spiking for TR units (Fig. 7,e g). STA mplitude chnges were 9.3 ± 5.94% for units nd 8.63 ± 3.74 for units (Fig. 7e), wheres SFC mgnitude chnges were 2.59 ± 7.7% for units nd 8.7 ± 2.26 for units (Fig. 7f), fter the second trining session (for Sleep 2 3 ). We lso exmined SSC mgnitude chnges for TR pirs ( nd ). The chnges in SSC mgnitude were 2.37 ±.6% for pirs (n = 7) nd 6.5 ± 2.89 for pirs (n = 47 pirs; Fig. 7g). The smll chnges oserved etween Sleep 2 nd Sleep 3 (STA mp nd SSC mg ; Fig. 7e g) were not significntly different from the solute chnges seen during poor lerning sessions (STA mp chnges:, t test, t 2 =.85, P =.4;, t test, t 53 =.7, P =.48; SSC mg chnges: pirs, t test, t 9 =.38, P =.7; pirs, t test, t 49 =.9, P =.92). Together, this indictes tht the continued execution of the tsk in the sence of new lerning is not sufficient to trigger further increses in phse-locking nd coherent spiking. DISCUSSION In summry, we found tht successful lerning of direct neurl control of n ctutor is linked to enhnced phse-locking nd coherent ctivtion of emergent tsk-relted ctivity, oth direct nd indirect, during the post-lerning SWS. During the process of lerning, these two sets of TR units ecme incresingly ctivted with similr temporl profiles. Notly, we found strong evidence for coherent rectivtion of these newly functionlly coupled ensemles during SWA. In contrst, tsk-unrelted ctivity either remined unchnged or experienced reduction in phse-locking nd coherent ctivtion. For control sleep sessions, poor-lerning sessions nd second sessions without evidence of new performnce gins, we did not find evidence of incresed phse-locking to SWA or coherent ctivtion, indicting specificity of our oserved findings to new lerning nd skill cquisition. Notly, we found positive correltion etween oth time spent in SWS nd the extent of STA mplitude chnge nd improvements in tsk performnce following wkening. Processing of n emergent tsk-relted ensemle Lerning ws ssocited with the emergence of novel tsk-relted ensemle of oth direct nd indirect units. In our experiments, rndomly chosen pirs of direct units were conditioned through feedck to e volitionlly modulted to move n ctutor. Consistent with growing ody of literture 3,33,34, modultion of direct units ws ccompnied y similr tsk-relted firing rte chnges in suset of indirect units ( ). Nerly ll direct nd suset of indirect units ecme incresingly modulted in tsk-dependent mnner with prctice (Fig. ). The emergent functionl coupling etween these units ppered to e consequence of lerning nd successful completion of the neuroprosthetic tsk. Becuse direct units re emedded in highly connected M corticl networks, it is possile tht such modultion of djcent indirect ctivity is importnt for precise corticl control. During the post-lerning SWS, there ws significntly higher coincident ctivtion of the emergent tsk-relted ensemle. We lso found tht the extent of firing-rte modultion during tsk performnce predicted the strength of the modifictions evident during SWS (Fig. 2d). In the sence of lerning or new performnce gins, this ws not present. This strongly suggests tht the functionl coctivtion of units during successful lerning is directly linked to the modified functionl connectivity nd coherent rectivtion detected during SWS. We lso noted positive correltion etween time spent in SWS nd susequent improvements in tsk performnce. This oserved performnce gin is consistent with pst studies, suggesting tht even rief periods of sleep cn improve motor performnce It remins uncler whether our oserved offline processing during SWA is sufficient nd necessry to trigger performnce gins following wkening; there my e other processes recruited during SWS tht could lso contriute to tsk improvements 7,38. Broder link to sleep nd memory A growing ody of literture hs linked offline processing during sleep to memory consolidtion 7,8. Memory formtion in the hippocmpl system is the most widely studied 9, In generl, fter n initil encoding phse, hippocmpus-sed memories pper to undergo process of consolidtion in which its representtion is stilized to neocorticl systems. Although the precise mechnisms underlying such consolidtion re incompletely understood, sleep-dependent interctions etween hippocmpl nd corticl circuits hve een linked to this process of consolidtion. Spontneous rectivtion of neurons reflecting previous experiences hve een found during oth non-rem (tht is, including SWA) nd REM sleep in oth the hippocmpus nd cortex 9. Recent studies hve lso suggested tht oth disruption of hippocmpl circuits with electricl stimultion nd sensory cue dependent fcilittion of memory formtions cn impede nd fcilitte memory formtion, respectively, suggesting direct link etween the offline processing nd the consolidtion of episodic memories 43,44. Sleep, in generl, nd SWS, in prticulr, lso pper to e importnt for the consolidtion of procedurl memories For exmple, fter lerning new motor skill, offline processing during overnight sleep 2 23 or rief dytime nps 24 cn fcilitte consolidtion. Locl chnges in SWA re lso ssocited with motor lerning nd performnce After new motor lerning or sensory stimultion there pper to e locl increses of SWA in specific corticl res or hemispheres 26,45. In contrst, disuse nd inctivity cn loclly decrese SWA nd deteriorte tsk performnce 28. It remins incompletely understood, however, how neurl ensemles in motor cortex re precisely modified during SWA fter skill cquisition. In this context, BMIs offer powerful tool to directly modulte neurons in motor cortex, therey llowing precise chrcteriztion of how oth tskrelted nd tsk-unrelted ensemles re differentilly processed in motor cortex during SWA. Although the exct link etween neuroprosthetic lerning nd generl procedurl lerning remins uncler, our results suggest tht the emergent tsk-relted ensemles could e lso processed in similr mnner fter nturl motor lerning. Implictions for neuroprosthetic control An importnt gol of the field of BMIs is to llow stle control of complex devices over long periods of time. Although decoder dpttion cn speed the overll rte of skill cquisition, dpttion of neurl circuits nd neurl plsticity over longer periods of time 2 VOLUME 7 NUMBER 8 AUGUST 24 nture neuroscience

7 r t i c l e s npg 24 Nture Americ, Inc. All rights reserved. my e essentil for stle skill cquisition. This my e especilly importnt for skilled control over complex devices tht resemle our nturl control of lims. For exmple, recent study highlighted tht optiml recruitment of long-term neurl plsticity is essentil for chieving flexile control tht resemles our nturl ilities 4. The study illustrted tht long-term neurl plsticity (tht is, cross multiple sessions) is essentil for chieving BMI control tht cn redily switch etween two control schemes without interference. Specificlly, only fter long-term stiliztion of single control scheme ws simultneous cquisition of second control scheme possile. Bsed on the prllels etween motor nd neuroprosthetic control, resonle hypothesis is tht consolidtion of prosthetic memory is essentil for such pprent resistnce to interference. Our oserved phenomenon of offline processing during SWS my consolidte such prosthetic memory. Conclusion Our results provide direct evidence tht n emergent group of TR units, which were incresingly functionlly coupled with lerning nd tsk performnce, experienced coherent rectivtion during SWS post. Knowledge out this phenomenon should help to etter ccount for mechnisms of neurl plsticity nd further the gol of chieving stle long-lsting neuroprosthetic control tht resemles nturl motor control. Methods Methods nd ny ssocited references re ville in the online version of the pper. Note: Any Supplementry Informtion nd Source Dt files re ville in the online version of the pper. Acknowledgments This work ws supported y the Deprtment of Veterns Affirs (B6674 to K.G.), the Burroughs Wellcome Fund (9855 to K.G.), the Americn Hert/Stroke Assocition (8756N to K.G.) nd VA Psychitric Reserch Advnced Fellowship (to D.S.R.). AUTHOR CONTRIBUTIONS C.C.W., T.G. nd K.G. conducted the experiments. T.G. nd D.S.R. nlyzed the dt. K.G. supervised the study. All of the uthors contriuted to the writing nd editing of the mnuscript. COMPETING FINANCIAL INTERESTS The uthors declre no competing finncil interests. Reprints nd permissions informtion is ville online t reprints/index.html.. Chpin, J.K., Moxon, K.A., Mrkowitz, R.S. & Nicolelis, M.A. Rel-time control of root rm using simultneously recorded neurons in the motor cortex. Nt. Neurosci. 2, (999). 2. Korlek, A.C., Jin, X., Long, J.D. II, Cost, R.M. & Crmen, J.M. Corticostritl plsticity is necessry for lerning intentionl neuroprosthetic skills. Nture 483, (22). 3. Arduin, P.J., Fregnc, Y., Shulz, D.E. & Ego Stengel, V. Mster neurons induced y opernt conditioning in rt motor cortex during rin-mchine interfce tsk. J. Neurosci. 33, (23). 4. Crmen, J.M. et l. Lerning to control rin-mchine interfce for reching nd grsping y primtes. PLoS Biol., E42 (23). 5. Serruy, M.D., Htsopoulos, N.G., Pninski, L., Fellows, M.R. & Donoghue, J.P. Instnt neurl control of movement signl. Nture 46, 4 42 (22). 6. Tylor, D.M., Tillery, S.I. & Schwrtz, A.B. Direct corticl control of 3D neuroprosthetic devices. Science 296, (22). 7. Snthnm, G., Ryu, S.I., Yu, B.M., Afshr, A. & Shenoy, K.V. A high-performnce rin-computer interfce. Nture 442, (26). 8. Moritz, C.T., Perlmutter, S.I. & Fetz, E.E. Direct control of prlyzed muscles y corticl neurons. Nture 456, (28). 9. Jrosiewicz, B. et l. Functionl network reorgniztion during lerning in rincomputer interfce prdigm. Proc. Ntl. Acd. Sci. USA 5, (28).. Musllm, S., Corneil, B.D., Greger, B., Schererger, H. & Andersen, R.A. Cognitive control signls for neurl prosthetics. Science 35, (24).. Hocherg, L.R. et l. Neuronl ensemle control of prosthetic devices y humn with tetrplegi. Nture 442, 64 7 (26). 2. Hocherg, L.R. et l. Rech nd grsp y people with tetrplegi using neurlly controlled rootic rm. Nture 485, (22). 3. Collinger, J.L. et l. High-performnce neuroprosthetic control y n individul with tetrplegi. Lncet 38, (23). 4. Gnguly, K. & Crmen, J.M. 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Hnlon, E.C., Frgun, U., Vyzovskiy, V.V., Tononi, G. & Cirelli, C. Effects of skilled trining on sleep slow wve ctivity nd corticl gene expression in the rt. Sleep 32, (29). 3. Moroni, F. et l. Procedurl lerning nd sleep hippocmpl low frequencies in humns. Neuroimge 42, 9 98 (28). 3. Inostroz, M. & Born, J. Sleep for preserving nd trnsforming episodic memory. Annu. Rev. Neurosci. 36, 79 2 (23). 32. Gnguly, K., Dimitrov, D.F., Wllis, J.D. & Crmen, J.M. Reversile lrge-scle modifiction of corticl networks during neuroprosthetic control. Nt. Neurosci. 4, (2). 33. Fetz, E.E. Volitionl control of neurl ctivity: implictions for rin-computer interfces. J. Physiol. (Lond.) 579, (27). 34. Korlek, A.C., Cost, R.M. & Crmen, J.M. Temporlly precise cell-specific coherence develops in corticostritl networks during lerning. Neuron 79, (23). 35. Peyrche, A., Khmssi, M., Benchenne, K., Wiener, S.I. & Bttgli, F.P. Reply of rule-lerning relted neurl ptterns in the prefrontl cortex during sleep. Nt. Neurosci. 2, (29). 36. Peyrche, A., Benchenne, K., Khmssi, M., Wiener, S.I. & Bttgli, F.P. Principl component nlysis of ensemle recordings revels cell ssemlies t high temporl resolution. J. Comput. Neurosci. 29, (2). 37. Lopes-dos-Sntos, V., Rieiro, S. & Tort, A.B. Detecting cell ssemlies in lrge neuronl popultions. J. Neurosci. Methods 22, (23). 38. Tononi, G. & Cirelli, C. Sleep nd the price of plsticity: from synptic nd cellulr homeostsis to memory consolidtion nd integrtion. Neuron 8, 2 34 (24). 39. Mrshll, L. & Born, J. The contriution of sleep to hippocmpus-dependent memory consolidtion. Trends Cogn. Sci., (27). 4. Pvlides, C. & Winson, J. Influences of hippocmpl plce cell firing in the wke stte on the ctivity of these cells during susequent sleep episodes. J. Neurosci. 9, (989). 4. Wilson, M.A. & McNughton, B.L. Rectivtion of hippocmpl ensemle memories during sleep. Science 265, (994). 42. Buzski, G. Two-stge model of memory trce formtion: role for noisy rin sttes. Neuroscience 3, (989). 43. Rsch, B., Buchel, C., Gis, S. & Born, J. Odor cues during slow-wve sleep prompt declrtive memory consolidtion. Science 35, (27). 44. Jdhv, S.P., Kemere, C., Germn, P.W. & Frnk, L.M. Awke hippocmpl shrpwve ripples support sptil memory. Science 336, (22). 45. Vyzovskiy, V., Borely, A.A. & Toler, I. Unilterl virisse stimultion during wking induces interhemispheric EEG symmetry during susequent sleep in the rt. J. Sleep Res. 9, (2). nture NEUROSCIENCE VOLUME 7 NUMBER 8 AUGUST 24 3

8 npg 24 Nture Americ, Inc. All rights reserved. ONLINE METHODS Animls nd surgery. Experiments were pproved y the Institutionl Animl Cre nd Use Committee t the Sn Frncisco VA Medicl Center. We used six dult Long-Evns mle rts tht were pproximtely 3 months old. No sttisticl test ws run to determine smple size priori. The smple sizes chosen re similr to those used in previous pulictions. Animls were kept under controlled temperture nd 2-h light:2-h drk cycle with lights on t 6:.m. Proes were implnted during recovery surgery performed under isofluorne ( 3%) nesthesi following induction with ketmine (2 mg per kg of ody weight) nd xylzine ( mg per kg). Atropine sulfte ws lso dministered efore nesthesi (.2 mg per kg). The post-opertive recovery regimen included dministrtion of uprenorphine t.2 mg per kg nd meloxicm t.2 mg per kg. Dexmethsone t.5 mg per kg nd trimethoprim sulfdizine t 5 mg per kg were lso dministered post-opertively for 5 d. We used 32-chnnel microwire rrys (33-µm polyimide-coted tungsten microwire rrys) in four rts. We lso used 32-chnnel silicon proe rrys in tetrode configurtion in two rts. Arrys were lowered down to,4,8 µm in the primry motor cortex (M) in the upper lim re ( 3 mm nterior to regm nd 2 4 mm lterl from midline). The reference wire ws wrpped round screw inserted in the midline over the cereellum. Finl locliztion of depth ws sed on qulity of recordings cross the rry t the time of implnttion. In one rt, we implnted electromyogrm (EMG) wires into neck muscles. Specificlly, pirs of Teflon-coted stinless steel wires (AM Systems) were inserted in neck muscles nd tunneled sucutneously to connector on the cp. All nimls were llowed to recover for week efore strt of experiments. Electrophysiology. We recorded extrcellulr neurl ctivity using tungsten microwire electrode rrys (MEAs, n = 4 rts, Tucker-Dvis Technologies) or silicon proes in tetrode configurtion (n = 2 rts, Neuronexus Technologies). We recorded spike nd LFP ctivity using 28-chnnel TDT-RZ2 system (Tucker-Dvies Technologies). Spike dt ws smpled t 24,44 Hz nd LFP dt t,8 Hz. ZIF-clip sed nlog hedstges with unity gin nd high impednce (~ GΩ) were used. Differentil EMG ws lso recorded t,8 Hz nd high-pss filtered with low-frequency cut off t Hz. Only clerly identifile units with good wveforms nd high signl to noise were used. The remining neurl dt ws recorded for offline nlysis. Behvior relted timestmps (tril onset, tril completion) were sent to the RZ2 nlog input chnnel using n Arduino digitl ord nd synchronized to neurl dt. We used the term unit to refer to the sorted spike recordings from oth the MEA nd tetrode recordings. For oth, we initilly used n online sorting progrm (SpikePc, Tucker-Dvies Technologies) for neuroprosthetic control (either in single chnnel or tetrode mode). We then conducted offline sorting. We sorted the MEA recordings using stndrd offline cluster cutting methods in Tucker- Dvies Technologies OpenSorter softwre. We susequently used wveform shpe nd the presence of n solute/reltive refrctory period in the interspike intervl to judge qulity of isoltion (Supplementry Fig. ) 4. Offline tetrode sorting ws performed using previously descried method (Supplementry Fig. ) 46,47. Specificlly, voltge-sed threshold ws set sed on visul inspection for ech chnnel tht llowed for est seprtion etween puttive spikes nd noise; typiclly this threshold ws t lest 4 s.d. wy from the men. Events were time-stmped nd wveforms for ech event were pek ligned. K-mens clustering ws then performed cross the entire dt mtrix of wveforms (3 smples per chnnel 4 chnnels numer of wveforms). Automted sorting ws performed y: () first over-clustering wveforms using K-mens lgorithm (split into mny mini clusters), (2) clcultion of interfce energy ( nonliner similrity metric tht llows for n utomted decision of whether mini-clusters re ctully prt of the sme cluster), nd (3) followed y ggregtion of similr clusters. Such ggregtion llows for reduction in the totl numers of clusters tht need to e mnully inspected. Automted sorting ws followed y mnul inspection nd sorting of spikes (including oth merging nd splitting clusters further, nd removing significnt outliers sed on Gussin distriution), using feture spce, uto-correltions, cross-correltions nd liner discriminnt nlysis to determine which clusters represent single units nd to prevent over-sorting. Supplementry Figure illustrtes exmples of sorting chieved with the MEA nd silicon proe tetrode recordings. Behvior. After recovery, nimls were typiclly gentled for severl dys efore the strt of experimentl sessions. Animls cclimted to custom plexiglss ehviorl ox (Fig. ) during this period. The ox ws equipped with slit (covered with door t one end) tht served s drinking zone. Initilly, wter delivery from the ctutor ws not introduced to the rts nd they were just cclimtized to the ox. Towrd the end of the cclimtion period, the rts typiclly fell sleep while in the ox. Animls were then wter scheduled such tht wter (from the feeding tue illustrted in Fig. ) ws ville in rndomized fshion while in the ehviorl ox. We monitored ody weights on dily sis to ensure tht the weight did not drop elow 95% of the initil weight. Behviorl sessions were typiclly conducted in the morning, with second sessions conducted in the fternoon. Two single lerning sessions were conducted in the fternoon. We found the sme results for these experiments. We recorded neurl dt from the rts for 2 h efore strt of BMI trining. The rts were then llowed to perform the tsk over 2-h session. Recorded neurl dt ws entered in rel-time to custom routines in Mtl. These then served s control signls for the ngulr velocity of the feeding tue. The rts typiclly performed ~8 2 trils for roust lerning sessions (for exmple, Figs. c nd 7). Following this, we recorded neurl dt from nimls for 2-h period. For the two session experiments, the nimls then continued with nother 2-h trining session followed y nother spontneous ctivity recording. Sorted units t the eginning of the recording were checked for mintennce throughout the second trining session. We lso collected control sleep dt in suset of nimls. After n initil spontneous ctivity period with sleep, we delivered rndom utomtic wter rewrds over period to typicl time period for tsk performnce. We then recorded spontneous ctivity nd sleep. Neurl control of the feeding tue. During the BMI trining sessions, we typiclly selected two well-isolted units s direct nd llowed their neurl ctivity to control the ngulr velocity of the feeding tue (Fig. d). In 3 of the 5 sessions, there ws only one neuron selected s the direct unit. These units mintined their stility throughout the recording s evidenced y stility of wveform shpe nd interspike-intervl histogrms 4. We inned the spiking ctivity into -ms ins. We then estlished men firing rte for ech neuron over 3 5-min seline period. The men firing rte ws then sutrcted from its current firing rte t ll times. The specific trnsform tht we used ws Θ v = C [ G r ( i) + G2 r2 ( i)] where Θ v is the ngulr velocity of the feeding tue, r (i) nd r 2 (i) re firing rtes of the direct units. G nd G 2 re rndomized coefficients tht rnged from + to nd were held constnt fter initiliztion. C is fixed constnt tht scles the firing rtes to ngulr velocity. The nimls were then llowed to control the feeding tue vi modultion of neurl ctivity. The tue strted t the sme position t the strt of ech tril (P in Fig. ). The clculted ngulr velocity ws dded to the previous ngulr position t ech time step ( ms). During ech tril, the ngulr position could rnge from 45 to +8 degrees. If the tue styed in the trget zone (P 2 in Fig. ; spnned re) for period of 3 ms wter rewrd ws delivered. In the eginning of session, most rts were unsuccessful t ringing the feeding tue to position P 2. Most rts stedily improved control nd reduced the time to completion of the tsk during the first session. In some cses, nimls did not improve control (tht is, poor lerning shown in Fig. 5). In susequent sessions, these nimls did demonstrte tht they could lern the tsk. As shown in Supplementry Tle, multiple lerning sessions were otined from ech niml. These sessions were typiclly week prt to ensure tht new units were recorded. Consistent with pst studies, we lso found tht incorportion of new units into the control scheme required new lerning 8,4,5. In mny sessions we videotped the rt during the BMI trining locks. Consistent with multiple reports, we did not oserve movements tht systemticlly predicted feeding tue movements 2,5,32. Specificlly, we nlyzed whether lim movements mesured using the video recording (tht is, mrkers mnully ssigned to the hed, torso nd ech lim using imge processing softwre) covried with movements of the feeding tue. Across multiple sessions, we did not find evidence for significnt covrition (dt not shown). This is likely result of the fct tht nonmovement relted rndom weights were ssigned to the direct units. nture NEUROSCIENCE doi:.38/nn.3759