A METHOD TO QUANITIFY MOVEMENT VARIABILITY OF HIGHLY SKILLED GOLFERS PERFORMING DRIVER SWINGS

Variability has been described as inherent in the golf swing (Bradshaw et al., 2009), yet its impact on outcome is not understood. It is necessary to quantify the levels of movement variability before this relationship can be examined effectively. Thus, the aim of this study was to develop a method to quantify movement variability of golfers performing driver swings. 16 highly skilled golfers each performed 10 swings wearing retro reflective markers which were tracked by a 3D motion analysis system operating at 400Hz. Movement variability was calculated for each marker using scalene ellipsoid volume methods; a score representative of the 3D variability over 10 trials was then calculated. The variability levels calculated using this method showed increasing variability from the closed end of the chain (malleoli) to the open end of the chain (wrists)

THE CREATION AND VALIDATION OF A LARGE-SCALE COMPUTER MODEL OF THE GOLF SWING

The aim of this study was to create and validate a full-body musculoskeletal model of a golfer performing a swing with their driver club. An elite female participant performed ten shots with her driver while wearing retro-reflective markers. An optical 3-D 6-camera system captured the kinematics of the markers at 400 Hz on the participant for each trial. A launch monitor device recorded the ball and club head conditions at impact. The kinematic data from one representative trial was selected to drive inverse and forward dynamics simulations of the created model. The validation results showed a very high level of agreement between experimental and simulated trajectories for selected markers (mean r = 0.966

THE EFFECT OF THE APPLICATION OF DIFFERENT LEVELS OF MOVEMENT VARIABILITY ON MOVEMENT OUTCOME

The aim of this study was to assess the effect of the application of a previously validated golfer computer model on different levels of movement variability relative to a shot outcome measure: club head velocity. Movement variability was applied to the computer model on six measures sequentially throughout the body of the computer model. Four different levels of variability, 25%, 50%, 75% and 100% variability, were applied to x, y and z positional data of the aforementioned measures. Simulations were then performed with ADAMS/LifeMOD software for each level of movement variability applied to the measures in question. Club head velocity was measured during the simulation. The results suggest that movement variability application at these landmarks does not have an effect on outcome. These results potentially have implications for the coaching of the participant

Human memory strength is predicted by theta-frequency phase-locking of single neurons

Learning from novel experiences is a major task of the central nervous system. In mammals, the medial temporal lobe is crucial for this rapid form of learning. The modification of synapses and neuronal circuits through plasticity is thought to underlie memory formation. The induction of synaptic plasticity is favoured by coordinated action-potential timing across populations of neurons. Such coordinated activity of neural populations can give rise to oscillations of different frequencies, recorded in local field potentials. Brain oscillations in the theta frequency range (3–8 Hz) are often associated with the favourable induction of synaptic plasticity as well as behavioural memory. Here we report the activity of single neurons recorded together with the local field potential in humans engaged in a learning task. We show that successful memory formation in humans is predicted by a tight coordination of spike timing with the local theta oscillation. More stereotyped spiking predicts better memory, as indicated by higher retrieval confidence reported by subjects. These findings provide a link between the known modulation of theta oscillations by many memory-modulating behaviours and circuit mechanisms of plasticity

Predicting Action Content On-Line and in Real Time before Action Onset - an Intracranial Human Study

The ability to predict action content from neural signals in real time before the action occurs has been long sought in the neuroscientific study of decision-making, agency and volition. On-line real-time (ORT) prediction is important for understanding the relation between neural correlates of decision-making and conscious, voluntary action as well as for brain-machine interfaces. Here, epilepsy patients, implantded with intracranial depth microelectodes or subdural grid electrodes for clinical purposes, participated in a "matching-pennies" game against an opponent. In each trial, subjects were given a 5 s countdown, after which they had to raise their left or right hand immediately as the "go" signal appeared on a computer screen. They won a fixed amount of money if they raised a different hand than their opponent and lost that amount otherwise. The question we here studied was the extent to which neural precursors of the subjects' decisions can be detected in intracranial local field potentials (LFP) prior to the onset of the action. We found that combinded low-frequency (0.1-5 Hz) LFP signals from 10 electrodes were predictive of the intended left-/right-hand movements before the onset of the go signal. Our ORT system predicted which hand the patient would raise 0.5 s before the go signal with 68% accuracy in two patients. Based on these results, we constructed an ORT system that tracked up to 30 electrodes simultaneously, and tested it on retrospective data from 7 patients. On average, we could predict the correct hand choice in 83% of the trials, which rose to 92% if we let the system drop 3/10 of the trials on which it was less confident. Out system demonstrates-for the first time-the feasibility of accurately predicting a binary action on single trials in real time for patients with intracranial recordings, well before the action occurs

Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

Peer reviewedPublisher PD

Neurons in the human amygdala selective for perceived emotion

The human amygdala plays a key role in recognizing facial emotions and neurons in the monkey and human amygdala respond to the emotional expression of faces. However, it remains unknown whether these responses are driven primarily by properties of the stimulus or by the perceptual judgments of the perceiver. We investigated these questions by recording from over 200 single neurons in the amygdalae of 7 neurosurgical patients with implanted depth electrodes. We presented degraded fear and happy faces and asked subjects to discriminate their emotion by button press. During trials where subjects responded correctly, we found neurons that distinguished fear vs. happy emotions as expressed by the displayed faces. During incorrect trials, these neurons indicated the patients’ subjective judgment. Additional analysis revealed that, on average, all neuronal responses were modulated most by increases or decreases in response to happy faces, and driven predominantly by judgments about the eye region of the face stimuli. Following the same analyses, we showed that hippocampal neurons, unlike amygdala neurons, only encoded emotions but not subjective judgment. Our results suggest that the amygdala specifically encodes the subjective judgment of emotional faces, but that it plays less of a role in simply encoding aspects of the image array. The conscious percept of the emotion shown in a face may thus arise from interactions between the amygdala and its connections within a distributed cortical network, a scheme also consistent with the long response latencies observed in human amygdala recordings

Book reviews

Teaching/Communication/Extension/Profession,

Value-related neuronal responses in the human amygdala during observational learning

The amygdala plays an important role in many aspects of social cognition and reward learning. Here, we aimed to determine whether human amygdala neurons are involved in the computations necessary to implement learning through observation. We performed single-neuron recordings from the amygdalae of human neurosurgical patients (male and female) while they learned about the value of stimuli through observing the outcomes experienced by another agent interacting with those stimuli. We used a detailed computational modeling approach to describe patients' behavior in the task. We found a significant proportion of amygdala neurons whose activity correlated with both expected rewards for oneself and others, and in tracking outcome values received by oneself or other agents. Additionally, a population decoding analysis suggests the presence of information for both observed and experiential outcomes in the amygdala. Encoding and decoding analyses suggested observational value coding in amygdala neurons occurred in a different subset of neurons than experiential value coding. Collectively, these findings support a key role for the human amygdala in the computations underlying the capacity for learning through observation

The Effect of Statin Therapy on Heart Failure Events: A Collaborative Meta-Analysis of Unpublished Data from Major Randomized Trials

Aims: The effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events. Methods and results: We searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with \u3e1000 participants followed for \u3e1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring(MI) were excluded. We calculated risk ratios (RR) with fixed-effects meta-analyses. In up to 17 trials with 132 538 participants conducted over 4.3 [weighted standard deviation (SD) 1.4] years, statin therapy reduced LDL-cholesterol by 0.97 mmol/L (weighted SD 0.38 mmol/L). Statins reduced the numbers of patients experiencing non-fatal HF hospitalization (1344/66 238 vs. 1498/66 330; RR 0.90, 95% confidence interval, CI 0.84–0.97) and the composite HF outcome (1234/57 734 vs. 1344/57 836; RR 0.92, 95% CI 0.85–0.99) but not HF death (213/57 734 vs. 220/57 836; RR 0.97, 95% CI 0.80–1.17). The effect of statins on first non-fatal HF hospitalization was similar whether this was preceded by MI (RR 0.87, 95% CI 0.68–1.11) or not (RR 0.91, 95% CI 0.84–0.98). Conclusion: In primary- and secondary-prevention trials, statins modestly reduced the risks of non-fatal HF hospitalization and a composite of non-fatal HF hospitalization and HF death with no demonstrable difference in risk reduction between those who suffered an MI or not