Theodore Edgar Milner

Computer-generated models have revolutionized how reconstructions of violent events, such as police use of force, are both performed and visualized. Yet, many experts in the legal and forensic disciplines do not understand them at a level required to use them effectively or create credible arguments supporting their findings. Simply put, models are a simplification of reality. Hence, models permit human programmers to specify the simplified behavior of a system. Since model parameters dictate the system's behavior, the programmer must document and provide justification for the selection of model parameters. The model structure, together with the selected parameters, form the backbone supporting the forensic investigator’s conclusions. This paper will begin with an overview of the usefulness of models in forensic investigations and follow with an example of how a model is constructed and applied in use of force cases. The selected cases are particularly relevant to incidents commonly encountered in law enforcement, frequently leading to litigation.

As we learn to perform a motor task with novel dynamics, the central nervous system must adapt motor commands and modify sensorimotor transformations. The objective of the current research is to identify the neural mechanisms underlying the adaptive process. It has been shown previously that an increase in muscle co-contraction is frequently associated with the initial phase of adaptation and that co-contraction is gradually reduced as performance improves. Our investigation focused on the neural substrates of muscle co-contraction during the course of motor adaptation using a resting-state fMRI approach in healthy human subjects of both genders. We analyzed the functional connectivity in resting-state networks during three phases of adaptation, corresponding to different muscle co-contraction levels and found that change in the strength of functional connectivity in one brain network was correlated with a metric of co-contraction, and in another with a metric of motor learning. We identified the cerebellum as the key component for regulating muscle co-contraction, especially its connection to the inferior parietal lobule, which was particularly prominent in early stage adaptation. A neural link between cerebellum, superior frontal gyrus and motor cortical regions was associated with reduction of co-contraction during later stages of adaptation. We also found reliable changes in the functional connectivity of a network involving primary motor cortex, superior parietal lobule and cerebellum that were specifically related to the motor learning. SIGNIFICANCE STATEMENT It is well known that co-contracting muscles is an effective strategy for providing postural stability by modulating mechanical impedance and thereby allowing the central nervous system to compensate for unfamiliar or unexpected physical conditions until motor commands can be appropriately adapted. The present study elucidates the neural substrates underlying the ability to modulate the mechanical impedance of a limb as we learn during motor adaptation. Using resting-state fMRI analysis we demonstrate that a distributed cerebellar-parietal-frontal network functions to regulate muscle co-contraction with the cerebellum as its key component.

Adaptation to an abrupt change in the dynamics of the interaction between the arm and the physical environment has been reported as occurring more rapidly but with less retention than adaptation to a gradual change in interaction dynamics. Faster adaptation to an abrupt change in interaction dynamics appears inconsistent with kinematic error sensitivity which has been shown to be greater for small errors than large errors. However, the comparison of adaptation rates was based on incomplete adaptation. Furthermore, the metric which was used as a proxy of the changing internal state, namely the linear regression between the force disturbance and the compensatory force (the adaptation index), does not distinguish between internal state inaccuracy resulting from amplitude or temporal errors. To resolve the apparent inconsistency, we compared the evolution of the internal state during complete adaptation to an abrupt and gradual change in interaction dynamics. We found no difference in the rate at which the adaptation index increased during adaptation to a gradual compared to an abrupt change in interaction dynamics. In addition, we separately examined amplitude and temporal errors using different metrics, and found that amplitude error was reduced more rapidly under the gradual than the abrupt condition, whereas temporal error (quantified by smoothness) was reduced more rapidly under the abrupt condition. We did not find any significant change in phase lag during adaptation under either condition. Our results also demonstrate that even after adaptation is complete, online feedback correction still plays a significant role in the control of reaching.

Unpredictable forces which perturb balance are frequently applied to the body through interaction between the upper limb and the environment. Lower limb muscles respond rapidly to these postural disturbances in a highly specific manner. We have shown that the muscle activation patterns of lower limb muscles are organized in a direction specific manner which changes with lower limb stability. Ankle muscles change their activity within 80 ms of the onset of a force perturbation applied to the hand which is earlier than the onset of changes in ground reaction force, ankle angle or head motion. The latency of the response is sensitive to the perturbation direction. However, neither the latency nor the magnitude of the response is affected by stiffening the arm even though this alters the magnitude and timing of motion of the body segments. Based on the short latency, insensitivity of the change in ankle muscle activation to motion of the body segments but sensitivity to perturbation direction we reason that changes in ankle muscle activation are most likely triggered by sensory signals originating from cutaneous receptors in the hand. Furthermore, evidence that the latency of changes in ankle muscle activation depends on the number of perturbation directions suggests that the neural pathway is not confined to the spinal cord.

Belly dance was used to investigate control of rhythmic undulating trunk movements in humans. Activation patterns in lumbar erector spinae muscles were recorded using surface electromyography at four segmental levels spanning T10 to L4. Muscle activation patterns for movement tempos of 2 Hz, 3 Hz, and as fast as possible (up to 6 Hz) were compared to test the hypothesis that frequency modulates muscle timing, causing pattern changes analogous to gait transitions. Groups of trained and untrained female subjects were compared to test the hypothesis that experience modifies muscle coordination patterns and the capacity for selective motion of spinal segments. Three distinct coordination patterns were observed. An ipsilateral simultaneous pattern (S) and a diagonal synergy (D) dominated at lower frequencies. The S pattern was selected most often by novices and resembled the standing wave of activation underlying the alternating lateral trunk bending in salamander trotting. At 2 Hz, most trained subjects selected the D pattern, suggesting a greater capacity for segmental specificity compared with untrained subjects. At 3–4 Hz, there emerged an asynchronous pattern (A) analogous to the rostral-caudal traveling wave in salamander and lamprey swimming. The neural networks and mechanisms identified in primitive vertebrates, such as chains of coupled oscillators and segmental crossed inhibitory connections, could explain the patterns observed in this study in humans. Training allows modification of these patterns, possibly through improved capacity for selectively exciting or inhibiting segmental pattern generators. NEW & NOTEWORTHY Belly dance provides a novel approach for studying spinal cord neural circuits. New evidence suggests that primitive locomotor circuits may be conserved in humans. Erector spinae activation patterns during the hip shimmy at different tempos are similar to those observed in salamander walking and swimming. As movement frequency increases, a sequential pattern similar to lamprey swimming emerges, suggesting that primal involuntary control mechanisms dominate in fast lateral rhythmic spine undulations even in humans.

The objective of this study was to determine how humans use tactile information to guide exploratory movement of the hand. A virtual environment made it possible to adjust the tactile input parameters online, based on subject behavior, something which is impossible with conventional techniques. We employed a haptic interface which applied distributed differential traction to the skin of the fingertip and investigated the effect of reducing tactile contrast on the ability to locate a virtually rendered ridge on a textured background. The difficulty of the task increased as the stimulus amplitude used to render the ridge decreased and the stimulus amplitude used to render the textured background increased. Difficulty depended more strongly on the amplitude of the textured background than on the amplitude of the ridge. The time taken to locate the ridge increased with difficulty. Most frequently, subjects crossed the ridge either once or twice before definitively establishing its location. The ability to locate the ridge did not appear to be sensitive to the velocity at which the ridge was crossed unless the difficulty was high. Our results suggest that haptic interfaces based on tactile stimulation to guide exploration could be used for both diagnostics and rehabilitation of sensorimotor hand function.