Down regulation of vestibular balance stabilizing mechanisms to enable transition between motor states
The initiation of movement from a stable posture is a central issue in neuroscience because of the need to overcome reflex-stabilizing mechanisms to enable motion ( von Holst and Mittelstaedt , 1950 ) . Navigating our world involves frequent transitions between posture ( e . g . quiet stance ) and movement ( e . g . locomotion ) , representing an ideal model to explore this issue . Indeed , balance correcting responses may hinder locomotor initiation and the transitions that are essential to safely navigate our environment ( Ostry and Feldman , 2003 ) . Optimal feedback control theory ( OFC ) ( Todorov and Jordan , 2002; Scott , 2004 ) , a prominent motor control theory , proposes that the brain implements the optimal means of performing a task by adjusting the appropriate feedback gains to reach the goal . Specific postural configurations and movement patterns are considered separate control policies , one of which must be disengaged ( i . e . by decreasing sensory feedback gains ) prior to the engagement of another ( i . e . by adjusting and increasing sensory feedback gains ) ( Cluff and Scott , 2016 ) . In this respect , OFC seems to diverge from other motor control theories , such as referent ( threshold ) control theory ( Asatryan and Feldman , 1965; Ostry and Feldman , 2003 ) . This latter theory suggests that a transition between postures involves a monotonic shift in the referent body orientation ( Feldman et al . , 2011; Mullick et al . , 2018 ) , transforming posture-stabilizing mechanisms into movement-inducing ones . To determine whether transition between motor states is comprised of discrete events or is a continuous process , we examined the temporal dynamics of sensory feedback gains prior to and during the transition between two motor states . Specifically , we examined the contribution of vestibular sensory signals to the control of balance during transition between quiet standing and locomotion as well as between two standing postures . The vestibular system encodes motion of the head in space , and is vital to our ability to maintain stability during both quiet standing and locomotion ( Angelaki and Cullen , 2008; Goldberg et al . , 2012 ) . Vestibular signals influence the activation of muscles engaged in the control of posture . This influence depends on the muscles’ active engagement in balance control , and the alignment of the muscles’ mechanical action with both the plane of instability and the direction of the vestibular disturbance ( Lund and Broberg , 1983; Britton et al . , 1993; Fitzpatrick et al . , 1994; Luu et al . , 2012; Mian and Day , 2014; Forbes et al . , 2016 ) . Contextually-dependent vestibular responses have been observed during both quiet standing ( Lund and Broberg , 1983; Fitzpatrick et al . , 1994; Marsden et al . , 2002; Son et al . , 2008; Luu et al . , 2012; Mian and Day , 2014; Forbes et al . , 2016 ) and locomotion , where the magnitude of vestibular-evoked muscle responses are modulated further during the phase of the gait cycle ( Orlovsky , 1972; Matsuyama and Drew , 2000; Blouin et al . , 2011; Dakin et al . , 2013; Forbes et al . , 2017 ) . The vestibular control of balance during locomotor or posture-to-posture transitions can be monitored by continuously quantifying the magnitude of vestibular-evoked balance responses over the transition . A similar approach has been used previously to monitor the time course of engagement and disengagement of the vestibular control of balance between self- and externally-driven states of balance control ( Luu et al . , 2012 ) . Here , the continuity of the vestibular influence on postural control during transitions was assessed to determine whether a discrete change in balance correcting mechanisms accompanies transitions between two motor states . We hypothesized that a discrete suspension in the vestibular control of balance would occur prior to the transition , due to the disengagement of the current control policy prior to the implementation of the next control policy , as predicted under OFC theory .
During the quiet standing period preceding the onset of locomotion , subjects swayed , generating low amplitude shear forces at the feet ( root-mean-square of 0 . 39 ± 0 . 3 N ) and relatively small accelerations of the head ( averaged horizontal linear acceleration <0 . 01 ± 0 . 3 m/s2 ) ( Figure 2 ) . All subjects ( n = 10 ) also exhibited significant EVS-GRF coherence across the 0–10 Hz bandwidth in both head orientations ( Figure 2 ) . On average , coherence peaked with a magnitude of 0 . 29 ± 0 . 11 and 0 . 41 ± 0 . 07 at frequencies of 2 . 1 ± 0 . 6 and 2 . 4 ± 0 . 9 Hz , for the head forward and the head left conditions respectively ( Figure 3 ) . At the end of the quiet standing period , that is immediately preceding the onset of the transition period , the forces applied to the body , the linear acceleration of the head and the angular velocity of the head all remained in the range observed during the quiet standing period ( Figure 2 ) indicating the initiation of locomotion had yet to begin . However , during this period , the EVS-GRF coherence decreased in all subjects ( n = 10 ) . Coherence fell below the 99% confidence limit for both head orientations: 0 . 435 ± 0 . 191 s prior to the onset of the transition , for a duration of 0 . 860 ± 0 . 260 s with the head facing forward ( Figure 4 ) and 0 . 259 ± 0 . 143 s before the onset of the transition when the head was turned to the left . However , unlike the head forward condition , coherence did not return once subjects began to walk with the head turned to the left ( Figure 2 and 4 ) . During the transition period , EVS-GRF coherence returned in the head forward condition ( Figures 2 and 4 ) . It peaked on average with a magnitude of 0 . 18 ± 0 . 05 at 6 . 6 ± 2 . 0 Hz across subjects ( n = 10 , Figure 3 ) . Periods of significant EVS-GRF coherence continued during locomotion ( i . e . the two first steps ) for the head forward condition , but only during the double-support phases ( shaded grey areas , Figure 2 ) . The maximum coherence measured during the first step of locomotion ( Figure 1 ) in the head forward condition was 0 . 15 ± 0 . 06 at 3 . 9 ± 1 . 9 Hz ( n = 10 , Figure 3 ) . In general , EVS-GRF coherence in the head forward condition was greater during quiet standing than during both the transition and the first step ( Figure 3 ) . Peak coherence during quiet standing was significantly greater than during the transition ( difference of ( Δ ) =0 . 17 ± 0 . 10 , t ( 9 ) = 3 . 32 , p=0 . 009 ) and the first step ( Δ = 0 . 14 ± 0 . 11 , t ( 9 ) = 3 . 12 , p=0 . 012 ) ( Table 1 ) . Peak coherence during quiet standing also occurred at a lower frequency than during the transition ( Δ = −4 . 4 ± 1 . 9 Hz , t ( 9 ) = −7 . 50 , p<0 . 001 ) and the first step ( Δ = −4 . 8 ± 1 . 9 Hz , t ( 9 ) = −2 . 98 , p=0 . 015 ) ( Figure 3 ) . No statistical difference was observed between the transition and the first step ( p=0 . 073 ) . During the locomotion period preceding locomotor termination ( i . e . the last two steps ) , all subjects ( n = 10 ) exhibited significant EVS-GRF coherence when the head was facing forward but not when the head was turned to the left ( Figure 5 ) . EVS-GRF coherence showed a peak magnitude of 0 . 14 ± 0 . 03 at 4 . 6 ± 2 . 7 Hz during locomotion for the head forward condition ( Figure 3 ) . As we observed significant coherence for every double-support phase following the transition at locomotion initiation in the head forward condition ( shaded grey areas , Figure 2 ) , we expected similar significant coherence levels in the double-support phase prior to the transition associated with the termination of locomotion . Coherence , however , was non-significant for the last double support phase prior to the transition in most subjects ( n = 8 ) , even though participants performed a complete final step , which displayed similar kinetics and kinematics to the previous steps ( shaded grey areas , Figure 5 ) . During the transition period from locomotion to quiet standing ( i . e . between the grey and red lines ) , EVS-GRF coherence increased past the 99% confidence limit ( >0 . 045 for individual subjects ) and remained significant into , and for the duration of , quiet standing ( Figure 5 ) . During the transition , on average , coherence peaked at a magnitude of 0 . 41 ± 0 . 08 and 0 . 24 ± 0 . 08 at frequencies of 3 . 3 ± 0 . 8 and 2 . 4 ± 0 . 4 Hz for the head forward and the head left conditions ( Figure 3 ) , respectively . Subjects exhibited larger EVS-GRFs coherence during quiet standing at the end of each trial and during the transition than during the last step ( refer to Figure 1 for the total duration representing the final step ) , regardless of head orientation . On average , with the head facing forward , peak coherence during the last step was significantly smaller than during the transition ( Δ = −0 . 27 ± 0 . 09 , t ( 9 ) = −9 . 22 , p<0 . 001 ) and during quiet standing ( Δ = −0 . 29 ± 0 . 1 , t ( 9 ) = −9 . 02 , p<0 . 001 ) . Similar results were observed when the head was turned to the left ( last step versus transition: Δ = −0 . 15 ± 0 . 09 , t ( 9 ) = −4 . 65 , p=0 . 001; last step versus quiet standing: Δ = −0 . 33 ± 0 . 08 , t ( 9 ) = −12 . 64 , p<0 . 001 ) . Peak coherence was not different between quiet standing and transition periods in the head forward condition ( p=0 . 857 ) , but was significantly higher during quiet standing when compared to the transition period with the head turned to the left ( Δ = 0 . 18 ± 0 . 09 , t ( 9 ) = −6 . 21 , p<0 . 001 ) ( Table 1 and Figure 3 ) . Finally , the kinematics and kinetics of the quiet standing period at the end of each trial were similar to those observed during the quiet standing period at the start of each trial ( i . e . small amplitude oscillations at low frequency ) . Similarly , significant EVS-GRF coherence persisted for the duration of the quiet standing period at the end of trials , with coherence peaking at a magnitude of 0 . 43 ± 0 . 09 at 3 . 1 ± 0 . 9 Hz with the head forward and 0 . 42 ± 0 . 07 at 2 . 0 ± 0 . 5 Hz with the head left ( Figure 3 ) . During the quiet standing period preceding the shift in postures , subjects swayed with low amplitude horizontal linear acceleration ( <0 . 02 ± 0 . 2 m/s2 ) , generating small GRF ( root-mean-square of 0 . 44 ± 0 . 4 N ) . All subjects ( n = 6 ) exhibited significant EVS-GRF coherence that peaked with a magnitude of 0 . 45 ± 0 . 21 at 3 . 6 ± 1 . 2 Hz ( Figure 6 ) . Before the onset of the posture-to-posture transition ( vertical red line , Figure 6 ) , coherence decreased in all subjects ( n = 6 ) , while the linear acceleration of the head and the angular velocity of the head both remained in the range observed during the quiet standing period . On average , coherence fell below the 99% confidence limit 0 . 336 ± 0 . 230 s before the onset of the transition and remained below significant level for 0 . 810 ± 0 . 351 s . Coherence returned during the transition , and remained significant into , and for the duration of , the new standing posture period . On average , coherence peaked at a magnitude of 0 . 53 ± 0 . 07 at 4 . 7 ± 1 . 9 Hz during the transition period ( i . e . between the red and grey vertical lines , Figure 6 ) , and at a magnitude of 0 . 51 ± 0 . 08 at 4 . 8 ± 2 . 3 Hz in the shifted posture period ( i . e . after the vertical grey line ) . Statistical analysis revealed that peak coherence measured during each of the three movement phases ( quiet standing posture , transition , standing posture with new weight distribution ) were not different from each other ( F ( 2 , 5 ) = 0 . 76 , p=0 . 56 ) .
In order to transition between two motor states , balance correcting responses are disrupted . Indeed , prior to the transitions tested , the vestibular influence on whole-body balance responses is suspended . The suspension of vestibular-evoked responses at movement initiation starts while subjects are still maintaining quiet upright stance , well before the transition onset ( vertical red line , Figures 2 , 4 and 6 ) . At locomotion termination , the suspension begins during the final step and ends after the transition onset ( vertical grey line , Figure 1 and 5 ) . Thus , changes in vestibulo-motor control occur before overt markers of the biomechanical transition . In addition , inhibition of ankle plantar flexor muscular activity during locomotion initiation occurs 150 ms before the first change in vertical GRF ( Herman et al . , 1973 ) , suggesting that balance correcting responses are down regulated 100 to 300 ms before the step-related modulation in muscle activity . These results partly confirm and extend previous work that reported a decrease in vestibular influence at locomotion initiation but increased vestibular influence at locomotor termination ( Bent et al . , 2002 ) . The apparent contradiction between these two studies is likely due to the near continuous approach we used , which improves upon the resolution with which vestibulo-motor responses can be observed compared to the discrete stimuli used by Bent et al . ( 2002 ) . The period of null coherence preceding the transition was robust and observed in all individual subjects ( n = 16 ) , and it provides insight into the neural control of stabilizing mechanisms that enable motion from a stable posture . From an OFC perspective , distinct neural processes govern the control of posture and movement ( Scott , 2004; Kurtzer et al . , 2005; Cluff and Scott , 2016 ) . To transition from quiet standing to movement , or another relatively stable posture , the current motor policy associated with quiet standing must be disengaged to permit the implementation of a new control policy ( Cluff and Scott , 2016 ) . In the locomotor transition task , the control policy regulating standing balance is disengaged to allow implementation of the locomotor control policy , and reversely when terminating locomotion . For the posture-to-posture transition , the motor control policy associated with standing balance is disengaged to permit the shift to a new posture . These periods of null coherence preceding transition thus illustrate when the brain disengages the current control policy . Furthermore , this vestibular disengagement solves the classic problem formulated by von Holst and Mittelstaedt regarding the opposing action from stabilizing reflexes when initiating motion ( von Holst and Mittelstaedt , 1950 ) . From a biomechanical point of view , the disengagement of vestibular influence on the whole-body postural responses may also be necessary for the transition process , and thus incorporated into motor planning . The disruption in vestibular contribution to balance during transitions appears to contradict a key prediction from referent control theory: a monotonic shift in referent body orientation during shifts in postures while standing upright ( Mullick et al . , 2018 ) . Our data show the intermittent use of vestibular feedback during transition between standing postures but it is unclear if a shift in referent body configuration is associated with such a transition . The period of suspension of vestibular-evoked responses appears related to the different relative sensory feedback gains needed to control whole-body movements by the quiet standing and locomotor control policies . During quiet standing , whole-body accelerations ( and related GRF ) and oscillations within the limits of the base of support are small . An adaptive feedback controller ( Fitzpatrick et al . , 1996; van der Kooij and de Vlugt , 2007 ) to which vestibular feedback contributes , can generate the appropriate muscular torques required to maintain upright stance . When initiating movement , whole-body accelerations larger than those observed during quiet stance are needed to move the whole-body center of mass towards the base of support limits or outside the base of support . If the gain of the vestibular channel in the adaptive controller remained unchanged during the transition , the vestibular-evoked whole-body responses would increase due simply to the larger whole-body accelerations , potentially challenging the limits of postural stability or countering the intended motion of the body . Consequently , an adaptive controller would need to adjust the gain of the vestibular channel to maintain upright stability during this transition period . Based on our results , it appears that the transition in gains between the initial and the final policies is preceded by a suppression of vestibular gain . Vestibular gain is increased once again following the transition , but in a context-dependent manner . For example , in the event of a transition from quiet standing to locomotion , vestibular gain is increased during locomotion to control lateral stability , primarily ( Figure 2 ) . Similarly , it appears that the locomotor control policy is interrupted preceding locomotion termination ( i . e . during the last step ) to allow the implementation of the quiet standing control policy . Lastly , an alternative interpretation is that the brain abruptly switches policies and starts predicting the whole-body’s future state whilst the body briefly remains in the previous state . Thus , for a short period of time , there is a discrepancy between the predicted and the actual sensory feedback that might result in a reduction in the size of the vestibular-evoked responses ( Luu et al . , 2012 ) . Significant coherence between EVS and the GRF were limited primarily to the 0–10 Hz bandwidth despite using EVS up to 20 Hz . These observations are in line with previous studies that characterized vestibular-evoked responses when humans are standing and walking ( Dakin et al . , 2007 , 2010 ) . As vestibular signals cascade from the nervous system to muscle activation and from muscle activation to whole-body accelerations , the vestibular signals are low-pass filtered ( Dakin et al . , 2010 ) . Presumably , the inertia of the limb segments and whole-body impose mechanical constraints that limit the frequencies at which their motion can remain in phase with , and thus correlate with , the EVS . These low frequency responses observed in the GRF to the vestibular stimuli are thought to reflect neural processing underlying an organised balance correcting response to a craniocentric vestibular error signal ( Reynolds , 2010; Mian and Day , 2014 ) . Although the exact anatomical regions associated with the suppression of vestibular-evoked responses are unclear , putative regions that may contribute to control policy changes have been proposed . Primary motor cortex neurons responding to externally applied mechanical loads were found active only during the maintenance of postural orientation while others only during movement ( Kurtzer et al . , 2005; Herter et al . , 2009 ) . For certain cortical neurons , Kurtzer et al . ( 2005 ) observed an abrupt switch in the pattern of neural processing ~0 . 3 s before the transition from a stationary posture to a reaching movement . Our results appear to mirror this behavior and extend the framework to a balance-locomotor context . In the brainstem , selective attenuation of ‘vestibular only’ neurons might change the response of vestibular nuclei neurons during self-generated locomotor movement ( Roy and Cullen , 2001 ) . However , these neuronal responses are largely related to the predictable nature of the feedback and would therefore be ineffective at selectively suppressing an unpredictable EVS-induced perturbation signal . Although this mechanism may contribute to the attenuation of EVS-GRF responses , recent findings ( Brooks and Cullen , 2014 ) indicate that it is likely insufficient to suppress the vestibular-evoked responses observed in this study . Whole-body balance responses evoked by EVS are craniocentric and thus the direction of the error can be manipulated by actively maintaining the head in different orientations ( Materials and methods , Lund and Broberg , 1983; Dalton et al . , 2014 ) . In the frontal plane , our upright posture is normally unstable during locomotion because the whole-body centre of mass is always medial to the propulsive foot ( Winter , 1995 ) . Stability in the sagittal plane , on the other hand , is enhanced by the forward momentum of the body ( Sparrow and Tirosh , 2005 ) and the long base of support during double-support phases . This difference in stability between the frontal and the sagittal planes may explain the small ( or absent ) vestibular-evoked responses observed during locomotion when the head is turned to the left ( i . e . vestibular error directed in the anteroposterior direction ) . The reduced coherence between EVS and anteroposterior GRF further support the hypothesis that the anteroposterior control of whole-body balance during locomotion requires less feedback-driven control than in the frontal plane , and may instead be largely passively controlled . Thus , our results agree with the assumption that sagittal plane stability is passively controlled ( Bauby and Kuo , 2000 ) . We further showed that vestibular-evoked whole-body responses in the frontal plane are phasically modulated during locomotion , exhibiting larger coherence during the double-support phase ( excluding the last step at termination , Figures 2 and 5 ) . Vestibulo-muscular coherence also exhibits phasic behavior for single muscles during locomotion with the head facing forward ( Blouin et al . , 2011; Dakin et al . , 2013; Forbes et al . , 2017 ) , however it was not clear from summing coherence over several muscles whether the whole-body response is also phasically modulated ( Dakin et al . , 2013 ) . From a biomechanical point of view , the double-support phase is important for stability: the base of support is larger in the mediolateral direction compared to single-support phase , the swing foot lands and body weight is transferred from one foot to another ( Winter , 1995 ) . Not surprisingly , EVS applied during either locomotor transition or walking leads to increased upper body roll and modified lateral foot placement ( Bent et al . , 2002 ) . This could result in an inefficient mediolateral transfer of body weight and to steps placed more laterally than usual , raising energy consumption ( Kuo , 2002 ) . The disruption in the vestibular control of balance observed prior to biomechanical transition indicates that the brain first down regulates balance-correcting mechanisms to enable the transition . This disruption in the vestibular control of balance reduces counteracting effects of vestibular balance correcting responses that could prohibit movement initiation , thus supporting a prediction from current OFC models . Importantly , the suppression of vestibular balance stabilizing mechanisms is not specific to one type of transition , suggesting it represents a general control process that occurs during transitions between standing balance and other motor states . Thus , our results demonstrate that humans ‘stop balancing’ before they start moving and ‘stop moving’ before they start balancing again .
Sixteen healthy young subjects without any history of neurological nor muscular disorders participated in our experimental protocol approved by the University of British Columbia Clinical Research Ethics Committee and conforms to the Declaration of Helsinki . The experimental protocols were explained to each subject and written consent was obtained . Among our participants , ten males [age 27 . 6 ± 4 . 6 years old , height 1 . 81 ± 0 . 04 m , weight 80 . 5 ± 9 . 6 kg ( mean ± SD ) ] performed the experiment involving locomotion initiation and termination ( locomotor transition ) and three males and three females [age 27 . 5 ± 2 . 1 years old , height 1 . 74 ± 0 . 07 m , weight 69 . 9 ± 6 . 3 kg] performed the experiment involving a change in body-weight distribution ( posture-to-posture transition ) . During trials , subjects were exposed to electrical vestibular stimulation ( EVS ) ( Dakin et al . , 2007 , 2013; Blouin et al . , 2011 ) applied to the mastoid processes behind each ear . EVS non-specifically modulates the firing rate of the nearby vestibular nerves ( Goldberg et al . , 1984; Kim and Curthoys , 2004 ) and , when delivered in a binaural bipolar electrode configuration , evokes a perception of rotation ( Fitzpatrick et al . , 2002; Peters et al . , 2015 ) about an axis directed posteriorly and superiorly 18° relative to the Reid’s plane ( Fitzpatrick and Day , 2004 ) . When the head is facing forward , the binaural bipolar electrical stimulus induces a postural response to compensate for the vestibular-induced roll error signal of the body in the frontal plane ( Lund and Broberg , 1983; Britton et al . , 1993; Day et al . , 1997; Mian and Day , 2014; Forbes et al . , 2016 , 2017 ) . Subjects were exposed to a bandwidth-limited noisy EVS ( 0–20 Hz , zero-mean low-pass filtered white noise , 20 Hz cut-off frequency , zero lag , 4-order Butterworth , peak amplitude of 4 mA , root mean square ~2 mA ) lasting 30 s ( locomotor transition ) or 15 s ( posture-to-posture transition ) , and created using LabVIEW software ( 2011 version; National Instruments , Austin , TX , USA ) ( Dakin et al . , 2007 , 2013 ) . EVS was delivered to subjects using an isolated constant current stimulation unit ( STMISOLA , Biopac Systems , Goleta , CA , USA ) connected to carbon rubber electrodes ( ~9 cm2 ) coated with conductive gel ( Spectra 360 , Parker Laboratories , Fairfield , NJ , USA ) and secured over their mastoid processes with adhesive tape and an elastic headband . During the experiment , the stimulation unit remained in a torso-pack worn by the subject . The stimulus bandwidth ( 0–20 Hz ) was chosen to characterize the entire frequency response of vestibular-induced modulation in lower limb muscle and whole-body force production ( Dakin et al . , 2007 , 2010 , 2011; Mian et al . , 2010; Reynolds , 2010 ) . The stimulus amplitude varied between ±4 mA , and was chosen to evoke measurable force responses during both standing and walking and ensure subject comfort , based on previous experience ( Dakin et al . , 2007 , 2013; Blouin et al . , 2011; Forbes et al . , 2017 ) . Across all subjects ( n = 16 ) , six were new to EVS . First , subjects stood with each foot over distinct forceplates ( FP1 and FP5 , Figure 1 ) , their arms at their side and eyes open . Subjects self-selected both the position and orientation of their feet , to ensure their comfort , but were encouraged to choose a foot width close to their pelvis width , because support width influences the magnitude of EVS-evoked responses ( Day et al . , 1997 ) . Once chosen , the position and orientation of the feet were marked on the ground , to ensure a reproducible starting position across trials . Subjects wore a head-mounted laser pointer and were instructed to maintain the projected position of this laser at a specific point on the wall , which was 4 m in front of them at the start of the trial . We determined the target for the laser by positioning participant’s head nose up from the floor , with their Frankfurt plane ( the auriculo-orbital plane ) approximately 18° up from horizontal , to maximize the EVS-evoked balance responses ( see Fitzpatrick and Day , 2004 , for a review ) . Participants were required to maintain this head orientation for the duration of the trial . The experimenter visually monitored the inclination angle of the head during the trial . To control the modulating effect of head orientation on the vestibular-induced instability during locomotor transition , participants completed trials in one of two head orientations . During this experiment , subjects repeated blocks of 105 trials with the head facing forward or turned 90° over the left shoulder ( Figure 1 ) . During the posture-to-posture experiment , subjects performed only one block of 105 trials with the head facing forward . When the head is facing forward , EVS induces a postural response along the mediolateral whole-body axis . When the head is turned 90° to the left , postural responses are directed along the anteroposterior whole-body axis ( Lund and Broberg , 1983; Fitzpatrick et al . , 1994; Forbes et al . , 2016 ) . Subjects participating in the locomotor transition experiment performed blocks of trials on separate days and we randomly assigned the order of the two blocks for each subject . During each block , the first five trials were used to collect the subject's kinetic and kinematic data in absence of EVS . These trials served as a control to determine if EVS modified the movement pattern . We provided EVS for the remaining 100 trials . Statistical analysis of the movement patterns between trials with and without EVS were performed using two-sided t-tests for each head position condition . In the locomotor transition experiment , the analysis did not reveal any major behavioral difference between these two conditions , except at locomotion termination , for a significantly decreased transition period ( Δ = −0 . 094 ± 0 . 070 s , t ( 54 ) = −4 . 93 , p<0 . 001 and Δ = −0 . 330 ± 0 . 123 s , t ( 51 ) = −7 . 49 , p<0 . 001 ) and an increased walking velocity ( Δ = 0 . 044 ± 0 . 013 m/s , t ( 50 ) = −15 . 79 , p<0 . 001 and Δ = 0 . 113 ± 0 . 070 m/s , t ( 51 ) = 73 . 82 , p<0 . 001 ) , respectively in the head forward and head left conditions . In the posture-to-posture experiment , we did not find any significant behavioral differences between the trials with and without EVS . To quantify the effect of the vestibular stimulus on subjects' behaviour , we recorded the ground reaction forces ( GRF ) applied to their body as well as linear acceleration and angular velocity of their head over the duration of each trial . The GRF were collected from eight forceplates ( squares of 60 × 60 cm , AMTI , Watertown , MA , USA ) recessed into the ground of the experimental room , covering an area of 2 . 88 m2 . GRF were digitized using a sampling rate of 1000 Hz ( PXI-8108 , National Instruments , Austin , TX , USA ) and saved offline , with the vestibular stimulus and the vibration pulse signals . We measured the linear acceleration and angular velocity of the head and waist using two inertial measurement units ( Shimmer2R w450/mAH Battery , 5 . 1 × 3 . 4 × 1 . 4 cm , Shimmer Sensing , Dublin , Ireland ) positioned on the forehead and the sacrum . The inertial measurement units were secured to the head and waist using Velcro belts . During trials , data from the inertial measurement units were sampled at 256 Hz and streamed to a personal computer for storage and future analysis . Because we used two separate computers to save the forceplate and inertial measurement units’ data , the two were synchronized in post-processing using the onset of the first vibration pulse . After identifying the biomechanical markers of the transitions phases , we analyzed the vestibular responses during the transition between standing balance and locomotion and between the two standing postures to determine if vestibular feedback is disrupted as predicted by the OFC theory . All non-statistical analyses were performed using custom-designed routines on Matlab software ( 2015a version , Mathworks , Natick , MA , USA ) . The relationship between EVS and the GRF for each experiment was estimated using time-frequency coherence based on continuous Morlet wavelet decomposition ( Zhan et al . , 2006; Blouin et al . , 2011 ) . This method has been previously used to estimate the changes in vestibular-evoked responses measured by EMG ( Blouin et al . , 2011; Luu et al . , 2012; Dakin et al . , 2013; Forbes et al . , 2014 , 2017 ) and was chosen here to avoid potential issues associated with gain estimates due to the larger GRF during locomotion ( and transitions ) than during quiet standing . We evaluated the coherence between the vestibular stimulus and the horizontal GRF because they reflect the net muscle activity of the body and are related to the horizontal accelerations of the whole-body centre of mass . Coherence [C ( τ , f ) ] used to estimate vestibulo-GRF coupling was computed using the following equation: ( 1 ) C ( τ , f ) = |Pxy ( τ , f ) |2Pxx ( τ , f ) Pyy ( τ , f ) In Equation ( 1 ) : τ is the movement time; f denotes the frequency; Pxy ( τ , f ) is the time-dependent cross-spectrum between the EVS and the shear force of interest; and Pxxτ , f and Pyy ( τ , f ) are the time-dependent auto-spectra of the EVS and the shear force of interest , which depends on head orientation . When the head faces forward , the perturbation resulting from the vestibular stimulus is directed mediolaterally , therefore the mediolateral shear forces ( FY ) were used for the analysis of the head forward condition . When the head is turned to the side , the perturbation resulting from the vestibular stimulus is in the anteroposterior direction , therefore the anteroposterior shear forces ( FX ) were used for the head left condition . Significant whole-body responses to the EVS were identified on a subject-by-subject basis when coherence exceeded a 99% confidence limit determined by the number of trials completed ( n = 100 ) . This confidence limit corresponds to a coherence magnitude threshold of 0 . 045 , and better represents an α-level of 0 . 05 because of the two-dimensional ( time and frequency ) nature of the measures ( Blouin et al . , 2011 ) . For illustrative purposes , we also computed the coherence for all subjects using the same procedure ( n = 1000 for the locomotor transition or n = 600 for the posture-to-posture transition ) . Coherence crossed the 99% confidence limit in these pooled data at a magnitude of 0 . 005 ( locomotor transition ) or 0 . 008 ( posture-to-posture transition ) . Under OFC theory , we expected a discontinuity in time-frequency coherence prior to the different transitions which should be reflective of the disengagement of either the balance , or ( loco ) motor control policies . To test this hypothesis , using the non-normalized time-scale format , we determined whether the magnitude of time-frequency coherence was significant or not ( i . e . above or below the 99% confidence interval , respectively ) over the transition period . To identify state-dependent changes in vestibular control of balance over the locomotor transition period , the magnitude of the peak time-dependent coherence and its corresponding frequency were extracted from the movement-time normalized data in each subject and for the three phases of the balance-locomotor transitions: quiet standing ( from first vibration pulse to transition onset for initiation and from end of transition to last vibration pulse for termination ) , transition ( from transition onset to first foot-off for initiation and from last foot-strike to transition end for termination ) and the first/last step ( from first foot-off to second foot-off for initiation and from second last foot-strike to last foot-strike for termination ) ( Figure 1 ) . The same procedure was repeated for the posture-to-posture transition ( but for the non-normalized time format ) for the three following steps: quiet standing ( from first vibration pulse to transition onset , i . e . vertical red line ) , transition ( from transition onset to transition end , i . e . between the two vertical lines ) and the new posture ( from transition end , i . e . the vertical grey line , to the end of the trial ) ( Figure 6 ) . Peak magnitude and/or frequency were used to determine whether coherence changed between the three phases , relative to the direction of vestibular-evoked responses . To test for significant differences across the three phases of each transition tested , we used repeated-measures multivariate analysis of variance ( MANOVA ) . To decompose the main effect , we used a multivariate post hoc analysis consisting of paired Hotelling’s t-square tests ( Bonferroni corrected ) . For each multivariate post hoc test providing a significant result , we tested whether the significant result was caused by differences in magnitude peak coherence , peak coherence frequency , or both by performing a Bonferroni corrected paired t-test . In the locomotor transition , this whole procedure was repeated independently for each head orientation within each transition ( initiation and termination ) . Coherence confidence limits were computed using Matlab software ( 2015a version , Mathworks , Natick , MA , USA ) . All other statistical tests were performed using R Studio software ( version 3 . 3 . 1 ) with an α level of p<0 . 05 serving as the threshold for significance .
The neural control of transition between posture and movement encompasses the regulation of reflex-stabilizing mechanisms to enable motion . Optimal feedback theory suggests that such transitions require the disengagement of one motor control policy before the implementation of another . To test this possibility , we investigated the continuity of the vestibular control of balance during transitions between quiet standing and locomotion and between two standing postures . Healthy subjects initiated and terminated locomotion or shifted the distribution of their weight between their feet , while exposed to electrical vestibular stimuli ( EVS ) . The relationship between EVS and ground reaction forces was quantified using time-frequency analyses . Discontinuities corresponding to null coherence periods were observed preceding the onset of movement initiation and during the step preceding locomotion termination . These results show humans interrupt the vestibular balance stabilizing mechanisms to transition between motor states , suggesting a discrete change between motor control policies , as predicted by optimal feedback theory .
Crossing Abbey Road is something of a paradox in neuroscientific terms . As you stand waiting to cross , tiny movements of your body – such as those due to breathing – cause you to sway by small amounts . To prevent you from falling over , your brain makes active corrections to your posture . These posture-correcting mechanisms oppose movements such as sway and keep you standing upright . But what happens when you want to cross the road ? To get you moving , your brain has two options . It could temporarily suppress the posture-correcting mechanisms . Or it could reconfigure them so that they work in a different way . The posture-correcting mechanisms rely upon sensory input from various sources . These include the vestibular system of the inner ear . The vestibular system tells the brain about the position and movement of the head in space and relative to gravity . Monitoring vestibular system activity as a person starts to move should thus reveal what is happening to the posture-correcting mechanisms . Tisserand et al . asked healthy volunteers to transition between standing still and walking , or to shift their weight from one foot to the other . At the same time , small non-painful electric currents were applied to the bones behind the volunteers' ears . These currents induced small changes in vestibular system activity . Sensors in the floor measured the forces the volunteers generated while standing or walking , thereby revealing how they adjusted their balance . The results showed that the brain suppresses its posture-correcting mechanisms before people start or stop moving . These findings have implications for robotics . They could make it easier to program robots to show smooth transitions into and out of movement . The findings are also relevant to movement disorders such as Parkinson's disease . One common symptom of this disorder is freezing of gait , in which patients suddenly feel as though their feet are glued to the ground . Understanding how the brain controls movement transitions may reveal how such symptoms arise .