Friday, 16 December 2011
Vagus Nerve Stimulation (VNS) & Transcutaneous Vagus Nerve Stimulation (tVNS)
Sunday, 11 December 2011
Mirror Neurons - Fact or Fable?
Sunday, 27 November 2011
How to set up a target
Saturday, 26 November 2011
Neuro-protection by caffeine in a model of Parkinson's disease.
Thursday, 24 November 2011
Research Project Into the Dynamics of Throwing
After recently finishing a movement analysis essay on biomechanical equipment and the relatively high costs of each piece (some up to £10,000 a camera!) we have started to look at equipment we will ourselves use in our investigation into elite throwing using cricketers from the University of Leeds.
Our task last week was to assemble a target made for the perception and action lab last year and it's fair to say it's not the most expensive piece of equipment and that we were not the best at assembling it! However, the target that was actually made for us by students doing engineering last year and is perfect for the experiment we are going to conduct and I'm sure the practice of putting it together should cut the time down from an hour (1st attempt) to at most; 15minutes during the real experiment.
We are meeting Brendan today to sort out the use of the cameras (a very expensive piece of equipment) and will try to familiarise ourselves as best as possible with the equipment before the day of the data collection.
We will be completing a step by step guide of how to put together the target and use of the camera in an attempt to partly complete and have a framework of the method section of the dissertation write-up.
That's all for this week.
Vince.
Wednesday, 23 November 2011
Bimanual coordinated rhythmic movements
There was no transfer of learning from the trained feedback methods to the untrained method. Initially this was a little disappointing as this was not expected or more correctly not the desired outcome. It was originally hoped that the coordination feedback training group would show transfer to the Lissajous feedback but not vice versa. However on closer inspection the actual results provide strong evidence for perceptual learning and differing task dynamics. This is evident as people learnt to use the trained feedback method correctly. In such that people do not learn the desired movement pattern per se, but learn how to produce the desired feedback display. As a result people learn to perceive their movements in the form of a movement display not as an action. Since this is the case and no transfer occurred it suggests that the two feedback methods are informationally distinct from one another. With the learnt perceptual information encapsulated within the specific feedback displays. Therefore each group learnt fundamentally different task dynamics where subjects learnt to generate 90° mean relative phase using specific visual feedback.
Despite this, questions still arose from other areas of the results. Firstly in our study 0 degrees and 180 degrees are defined in terms of visual feedback not muscle activation. As a consequence 0 degrees produced a non-homologous muscle group activation whilst 180 degrees produced homologous muscle group activation. Which may account for a slightly higher than normal 180 degree performance. Secondly the judgement data did not change with training, but this may have been due to the design of the study. As judgements were performed at 1Hz which may be too fast to allow successful judgements of phase to occur.
In conclusion after dipping my toe into the water for the first time so to say the results were very positive and have produced favourable and exciting data from which my thesis and first paper can be written. So all in all I would say so far so good.
Tuesday, 22 November 2011
The Timed Up & Go Test: Its Reliability and Association With Lower-Limb Impairments and Locomotor Capacities in People With Chronic Stroke
The aim of the study was to examine test-retest reliability of the Timed Up & Go test, its ability to differentiate subjects with chronic stroke from healthy elderly subjects, and its associations with ankle plantarflexor spasticity, ankle muscle strength, gait performance, and distance walked in 6 minutes in subjects with chronic stroke. The individual measures used for the test was the Berg scale and the Barthel index.
For this study twenty one participants were used for the task (ten healthy elderly adults and eleven elderly adults with chronic stroke). The study also conducted four clinical and laboratory measures of the lower limb functions. They are spasticity of the plantarflexors, maximum isometric voluntary contraction of the ankle muscles, gait performance and a six minute walk test.
The timed up and go test required subjects were required to stand up from a chair with armrests, walk 3m, turn around, return to the chair, and sit down. The time taken to complete this task was measured in seconds with a stopwatch.
Results showed the spasticity in the ankle plantarflexors in the affected legs of subjects with stroke was significantly (P_.001) higher compared with their unaffected legs and with the mean scores of both legs in the healthy elderly subjects. For gait parameters, patients with stroke walked significantly (P_.001) slower (mean gait velocity, 48.7_22.1cm/s) than the healthy elderly subjects (mean gait velocity,125.6_23.8cm/s), with significantly (P_.001) reduced cadence (84.3_20.7 steps/min) compared with the healthy elderly subjects.
The study concluded that results show that there was a high degree of test-retest
reliability in the Timed Up & Go test scores in elderly subjects with chronic stroke. These scores were capable of detecting differences in functional mobility between healthy elderly subjects and subjects with stroke.
Friday, 18 November 2011
60-90 Minute Naps VS 200mg Caffeine - Motor Learning & Perceptual Learning
Thursday, 17 November 2011
A COMPARISON BETWEEN NOVICES AND EXPERTS OF THE VELOCITY-ACCURACY TRADE-OFF IN OVERARM THROWING
A study was conducted to investigate the speed-accuracy trade off in expert and novice throwers, and the movement strategies used to execute the task of throwing. It was hypothesised that the experts would maintain high accuracy throughout the range of velocities, and that the novices would show a trade in accuracy and velocity. It was also hypothesised that a change in co-ordination strategy would be expected in the form of movement patterns leading to a throw between the different groups.
The experts, in this case were male team handball players from a Norwegian second division team, and the novices had never been involved in any organised sport that required any form of throwing activity.
The data was gathered using 3D cameras, with markers placed on the body at the shoulder, hip, elbow, wrist and the ball was also tracked. Linear velocities of these points were calculated, along with time of release and total movement time. Throwing accuracy was measured by a video camera, and a ‘hit’ was recorded when the centre of the ball hit the centre of the target, otherwise, a ‘miss’ was noted.
There were several conditions, the first was where the participants were asked to throw the ball as fast as they could, in order to record maximum velocities. The second condition was also a throw at maximum velocity, but with accuracy as an afterthought. The third condition was where velocity and accuracy were equally important. In the forth condition, accuracy was the main priority with velocity as a secondary priority, and in the final condiditon the only priority was to hit the target with velocity made irrelevant.
In summary, the throwing performance of the experts was better than that of the novices in every condition, as expected, both in terms of speed and accuracy. Also, in the experts, the velocities of most of the body segments were higher than that of the novices. However, no significant differences in absolute and intersegmental timing of the movements of the body segments was found between the two groups. Also, in terms of speed-accuracy trade off both groups performed similarly. This means that when accuracy was required, acceleration and velocities were decreased, although accuracy was not actually improved.
It was thought that the novices would show more of a speed-accuracy trade off as they were thought not to have the ability to throw the ball accurately at high speeds. Therefore, it is suggested that it is the features of the required task rather than the skill level of the subject that explains the lack of a speed-accuracy trade off in handball overarm throwing.
There were no differences in timing of body segment movements between the groups. This suggests that novices and experts may use the same general coordination pattern. The analysis suggests that in a ballistic, whole body movement the accuracy was not affected by a faster execution that was likely to have been induced by more muscle activity.
Overall, it was found that the only essential difference between novice and expert throwers was the use of a wind up or counter movement, which lead on to a stronger and shorter acceleration period. By accelerating and moving faster an expert will reach the end of motion earlier. It is not proved however, that experts use the same movement range as novices. Recent data on throwing with dominant and non-dominant arms suggest that athletes use a longer movement range with the dominant arm.
Wednesday, 16 November 2011
Throwing velocity and accuracy in elite and sub-elite cricket players: A descriptive study
110 Cricket players from 6 different populations were selected as participants for this study.
(1) Elite Senior Males
(2) Elite U19 Junior Males
(3) Elite U17 Junior Males
(4) Elite Senior Females
(5) Elite U19 Junior Females
(6) Sub-Elite Senior Males
Participants (Ps) were assessed on maximum throwing velocity, and throwing accuracy at maximum velocity and 3 sub-max velocities.
The tests were conducted in an indoor sports hall with a synthetic surface and max velocity throws were undertaken from a distance of 20.14m from the target. Regulation 4-piece leather cricket balls weighing 156g were thrown into a net. For the max velocity throw test; a net with no specific target was set up. A cordless speed radar gun was positioned behind the net whilst Ps were instructed to throw as hard as possible. All the throws were overarm and Ps were allowed one stride before throwing to minimise extraneous variables such as approach speed and angle.
For the throwing accuracy test, a specially designed cricket target was assembled and throws were made from behind a line at a distance of 20.14m. The target consisted of one cricket stump in the ground surrounded by five markers in order to attribute scores to how close to the stump, the throw hit.
Elite senior males had highest peak and mean throwing velocities whilst groups of males had significantly higher velocity throws than females. A speed-accuracy trade-off existed as all groups had improved accuracy scores at velocities between 75% and 85% of max throwing velocity.
To conclude, sex, playing experience, and training volume may all contribute to throwing performance in cricket players. Further research should be aimed at the mechanisms behind the differences seen in throwing profiles whilst also looking at the training techniques and differences between the genders.
Perceptual Learning Immediately Yields New Stable Motor Coordination
A review of Individual Difference Measures
When deciding upon a measure to use there are things that should be considered, particularly reliability and validity. The test might be easy to complete, however if it lacks reliability then it wouldn’t be worth doing because of the pitfalls that could result in the data obtained. Also validity is important to ensure that the measure isn’t a waste of experiment time.
In recent years frailty has been considered in research with the elderly as opposed to just age or disability being a risk factor in decreasing functional mobility. The Edmonton Frail Scale allows the assessment of many different domains such as cognition, social support and functional independence. This measure excludes only few participants (communication barriers and manual dexterity). The test is to be completed by the participant and has been described as brief, valid and reliable. Although it is easy to administer we must be aware of the possibility for incorrect answers given. Some participants may feel embarrasses when answering questions about continence for example. Nevertheless this method is a very popular one, and requires little or no specialist training to administer.
The Barthel Index is a simple index of independence and has been used in hospitals since 1955. The index includes everyday activities (feeding, bathing, and dressing) and these are scored on whether they require help or are independent. One advantage of this measure is its simplicity. It’s very easy to understand as there are strict instructions for each of the categories. It is also a useful test for assessing the progression of independence as it is carried out before and during treatment. However if we were to use this then we would need the carer or a nurse that works with the patients to give us all the necessary information on each patient.
A test that would be very easy to administer and would only need the participants to fill in a short answer sheet would be the Test Your Memory measurement. Having reviewed this method it seems a little bit patronising in places. It would be unethical to have any of the participants feel uncomfortable answering any questions. However this would be a good test for assessing cognitive function because there probably would be a difference in the results obtained from the participants.
Other measures would not be suited to our study. For example, the measurement of grip strength or the Geriatric Depression Scale. Although those suffering depression may not be suitable for the test, it is likely that they won’t need to be tested as it will already be knowledge whether they suffer depression or not.
Perception & Action Lab: Learning a coordinated rhythmic movement with task appropriate coordination feedback
The role of the Cerebellum in Learning Movement Coordination
The role of the Cerebellum in Learning
Movement Coordination
W. T. Thach
The aim of this study was to review previous research to see what roles the cerebellum has in learning a coordinated movement.
The cerebellum is said to learn new movements by different pathways going into the cerebellum e.g. purkinje cells. These cells were also said to be the ones producing action potentials when movement occurs.
These different pathways carry information about different situations i.e. learning a new movement. These pathways also contain a great amount of memory cells that contain the information about the new movement that has been learnt. There is also a second pathway that helps these purkinje cells learn and recognize new patterns in the information from the first pathways. In response to the new information that is inputted, new patterns of movements are then created.
Gilbert and Thach (1977) wanted to test to see if the cerebellum actually is involved when trying to learn a new co-ordination movement. To do this they tried to teach monkeys to perform different tasks using a manipulandum against constant torque loads. The main thing they were looking at were the wrist movements of the monkeys.
Within the first 12 to 100 trials the monkeys were able to adapt to the task and this was explained by Evarts (1973) as being because of the long loop functional stretch. This is when the muscle has to activated in order for movement to occur. In order for the muscle to be activated the cerebellum has to be stimulated.
One of the conclusions of the study was that once a skilled movement has been learned, it remains coded in cerebellar memory cells for a really long time.]
Coordination of the many body parts in order to attain smooth movements is usually agreed to be one of the particular roles of cerebellar control. This is often thought of as being due to a “fine-tuning” of the many movement pattern generators downstream from the cerebellum in the spinal cord, brainstem, and motor cortex (Holmes, 1939).
Tuesday, 15 November 2011
Individual difference measures.
Firstly, a reliable measure for individual differences needs to be established. There are hundreds of apporaches in research, and using previous studies I have selected a few that I think would be appropriate for the up and go task.
The mini mental state exam (MMSE) is a 30-point questionnaire that looks at arithmatic, memory and orientation all in the space of around 10 minutes. It is currently used as a screen for dementia or as an indicator of cognitive function, and was developed by Folstein (1975). Scores of above 25 indicate the particiapnt is of sound mind, whereas scors below 9 indicate severe cognitive impairment. This would help research as it would be made clear how cognitive functionality affects how a task is carried out.
Furthermore, Rolfson et al. (2006) developed a valid and reliable version of the Edmonson Frail scale, where frailty as a seperate varible from disability and ageing. A number of tests were carried out on each patient, all aged over 65. The 'up and go' task was included, to test function and mobility, and a clock task to test for cognitive impairment. The results from both of the tasks helped give an indication of both cognitive and physical function, and the results show that despite people being on a similar level of cognitive function, that didn't neccessarily mean they were similar in physical function. this highlights that every individuals needs and personal details differ, and that it is of utmost importance to take these differences into account when trying to correlate data.
Predicting the Probability for Falls in Community-Dwelling Older Adults
This study examined the sensitivity and specificity of the timed up and go test under single task versus dual task conditions for identifying elderly individuals who we prone to falling
Thirty community-dwelling older adults living in the greater Seattle area were enrolled in the study after giving informed consent. The participants were 15 older adults with no history of falls (mean age=78 years, SD = 6 range =65-85) and 15 older adults with a history of 2 or more falls in the previous six months (mean age=86.2 years, SD= 6, range 76-95)
The test was performed under 4 conditions (Timed Up and go, timed up and go with a subtraction task, timed up and go cognitive and timed up and go while carrying a full cup of water). Subjects were given verbal instructions to stand up from a chair walk 3m as quickly and as safely as possible cross a line marked on the floor, turn around, walk back and sit down.
Results showed the older adults with a history of falls were slower than the adults without a history of falling in all 4 conditions. Analysis showed that the difference in time is due to their balance status.
Results suggested that adults who take longer than 14 seconds have a higher risk of falling. The cut off value of 14 seconds is different from that of Podsiadlo and Richardson, who found that a cut off value of greater than 30 seconds was best for predicting functional dependence among older adults
Monday, 14 November 2011
How to Digitise a throwing video
Friday, 28 October 2011
Children throwing bean bags at targets
The reason I was in the lab was to try out a bright idea I've had with a colleague from Leeds Metropolitan for a study. One of the tasks I use to study perception and action is throwing over long distances to hit a target. I ask people to throw overarm to hit a 4ft x 4ft Perspex target from up to 15m away, and we record their throw with high speed cameras to measure the release angle and velocity of the ball. I'm also interested in the development of throwing; this is a very human skill, with all kinds of interesting psychological properties. It's considered a key motor skill for young children to acquire, so much so that it is one of the tasks measured in the Movement Assessment Battery for Children (Movement-ABC). This battery is commonly used to identify children with motor difficulties such as developmental coordination disorder, and throwing is one of the assessment tasks.
Perceptual Learning Immediately Yields New Stable Motor Coordination
Monday, 24 October 2011
The learning of 90° continuous relative phase with and without Lissajous feedback: External and internally generated bimanual coordination
Thursday, 20 October 2011
The aim of the study was to compare the different results between the ‘Timed Get-Up-And-Go’ (TGUG) test and the ‘Expanded Timed Get-Up-And-Go’ (ETGUG) test on 3 groups. The TGUG only measures the time of the movement as a whole whereas the ETGUG could measure the component tasks of the test.
3 groups of 10 subjects participated on the study. Group 1 classified as the young control group aged between 19 and 29 years with a mean age of 25.5. Group 2 were classified as the elderly control group who were aged 65 and over with a mean age score of 72.7 years. Group 3 were classified as the at risk elderly group who were aged over 65 and had a mean age of 75.8 years. All of these subjects were receiving physical therapy, had a history of falls in the past two years or had been treated for gait pathologies or balance disorders.
The subjects all had to complete the ‘Timed Get-Up-And-Go’ test first. This involved standing up from a chair (seat height 46cm) and walking 3 meters at a normal pace, turning around walking back and returning to the seated position. The second test they all completed was the ‘Expanded Timed Get-Up-And-Go’ test. This involved them walking 10 meters so that component tasks could be timed using a multimemory stopwatch. The stopwatch was pressed at the following events: a) standing upright b) as the subject passed the 2m mark c) as the subject passed the 8m mark d) as the subject passes the 8m mark returning and e) as the subject passed the 2m mark returning.
The results displayed no significant differences in the times from the TGUG between the young control group and elderly control group. The young control group’s mean time was 7.36s. The mean time for the elderly control group was 8.74s and the at risk elderly group had a mean time of 18.14s to complete the task. Similar results were found for the ETGUG test. The mean time for the young control group was 15.36s, the elderly control group was 19.095s and the at risk elderly group was 34.52s. A significant difference was found between the young and at risk group and the elderly and the at risk group for every component task of the test. Both control groups were found to be significantly faster at each stage than the at risk group.
All the young and elderly control participants completed the TGUG test in less than 10 seconds which is consistent with previous findings therefore showing they are freely independent in physical mobility. In both of the tests it was found the elderly group and the at risk elderly group had difficulty standing up from the chair. Therefore it has been suggested that only this measure could be used in future research to predict a patient’s risk of falling. Additional research is needed to determine correlations between the increased time for specific component tasks and a decreased functional mobility.
Learning to throw to max distances: Do changes in release angle and speed reflect affordances for throwing?
Adults skilled at long distance throwing, able to pick optimum weight for max. distance (Bingham et al, 1989), but replicated and results from a larger range of object sizes and weights recorded (Zhu et al, 2008). A very functional relation between size and weight was established.
Zhu et al. investigated whether people without good throwing skills could perceive the affordance for throwing and if they would learn to. They were unable to select optimal objects for throwing with any accuracy, but once learned to throw for distance; could then see the affordance.
Affordance property - optimal distance of throws determined by initial angle and speed.
Hypothesis - object size and weight might affect dynamics of hefting in similar ways and that this similarity would allow hefting to provide information about affordance.
Study was performed for perceptual learning of the affordance while learning to throw and to study concurrent changes in the kinematics of throwing.
Method:
48 objects varying in size (marble to waterpolo ball)
18 Indiana Uni students that could throw but not at a competitive sporting level.
Ps were scheduled for 3mnths throwing practice randomly divided into 3 groups using ANOVA on throwing data gathered from pre-test.
Results: Mean distances of throws each of 6 objects for each group, during each week of practice and after practice, plotted against objects.
(1) Distance of throws - Distance increased after practice for all groups.
(2) Release angle - Throwing practice didn't yield significant changes in release angle, however consistency of release angle did increase amongst participants.
(3) Release speed - Mean release speed increased by as much as 50%, however each group exhibited different patterns.
(4) Distance vs Release Angle/Release Speed - Release angle not significant for systematic changes in distance. Release speed was significantly correlated with distance of throws.
(5) Effect of object size and weight on throwing - Object size does affect reliability with which near optimum release angles were produced. Size had no effect on mean angles of release or significant effect on distance of throw.
Wednesday, 19 October 2011
Perception & Action Lab: Perceptual Learning Immediately Yields New Stable Motor Coordination
The timed “Up & Go”: A test of basic functional mobility for frail elderly persons
Learning a co-ordinated Rhythmic movement with task- appropriate co-ordination feedback
Tuesday, 18 October 2011
Learning a coordinated rhythmic movement with task appropriate coordination feedback
10 participants were split into two groups of five individuals. Both groups had the same amount of time to complete the training under two conditions: group 1 (“Feedback”), received feedback during training, whereas group 2 (“Control”) received no feedback during their training. Both groups initially received a baseline assessment session where they viewed a demonstration of the relative movement of 90˚ on a computer screen which they then had 20 seconds to repeat the viewed movement, five times. A computer controlled dot and a metronome was used as a reference point for the individual to produce their movement.
Five later sessions involved the participants receiving training either using feedback for the “Feedback” group or no feedback for the “Control” group. Feedback included the same procedure as the bassline session but participants now had a green coloured dot which indicated that the individual was creating a coordinated movement of 90˚± mean relative phase. As training sessions progressed the error bandwidth decreased from 40˚ then 30˚, 20˚, 15˚ and finally 10˚±, therefore whilst the first training session triggered a green dot while the individual was moving between 50˚ and 130˚ the fifth training session triggered a green dot when the individual was moving between 80˚ and 100˚. The decrease in bandwidth would aim to promote an improvement in coordinated movement at 90˚ after each session. The “Control” group did the same amount of trials but received no such feedback.
The results found that participants who received feedback were significantly better at maintaining a 90˚ movement for longer periods of time than the control group, whereas the control group did not show any improvement whilst doing the same post-training session.
The results therefore show that feedback is vital to learning a new task as the control group were unable to complete the movement task at the same level as the feedback group even though they received the same amount of time to practice the movement as the feedback group.