Biomedical subjects

Daniel W Moran

Publications and source records attributed to Daniel W Moran.

5 recordsLinked to original sources

PubMed2006

Computational model of a primate arm: from hand position to joint angles, joint torques and muscle forces.

Three-dimensional reaching by non-human primates is an important behavioral paradigm for investigating representations existing in motor control areas of the brain. Most studies to date have correlated neural activity to a few of the many arm motion parameters including: global hand position or velocity, joint angles, joint angular velocities, joint torques or muscle activations. So far, no single study has been able to incorporate all these parameters in a meaningful way that would allow separation of these often highly correlated variables. This paper introduces a three-dimensional, seven degree-of-freedom computational musculoskeletal model of the macaque arm that translates the coordinates of eight tracking markers placed on the arm into joint angles, joint torques, musculotendon lengths and finally into an optimized prediction of muscle forces. This paper uses this model to illustrate how the classic center-out reaching task used by many researchers over the last 20 years is not optimal in separating out intrinsic, extrinsic, kinematic and kinetic variables. However, by using the musculoskeletal model to design and test novel behavioral movement tasks, a priori, it is possible to disassociate the myriad of movement parameters in motor neurophysiological reaching studies.

Algorithms↗

PubMed2006

Brain-controlled interfaces: movement restoration with neural prosthetics.

Brain-controlled interfaces are devices that capture brain transmissions involved in a subject's intention to act, with the potential to restore communication and movement to those who are immobilized. Current devices record electrical activity from the scalp, on the surface of the brain, and within the cerebral cortex. These signals are being translated to command signals driving prosthetic limbs and computer displays. Somatosensory feedback is being added to this control as generated behaviors become more complex. New technology to engineer the tissue-electrode interface, electrode design, and extraction algorithms to transform the recorded signal to movement will help translate exciting laboratory demonstrations to patient practice in the near future.

Algorithms↗

PubMed2006

Local field potential spectral tuning in motor cortex during reaching.

In this paper, intracortical local field potentials (LFPs) and single units were recorded from the motor cortices of monkeys (Macaca fascicularis) while they preformed a standard three-dimensional (3-D) center-out reaching task. During the center-out task, the subjects held their hands at the location of a central target and then reached to one of eight peripheral targets forming the corners of a virtual cube. The spectral amplitudes of the recorded LFPs were calculated, with the high-frequency LFP (HF-LFP) defined as the average spectral amplitude change from baseline from 60 to 200 Hz. A 3-D linear regression across the eight center-out targets revealed that approximately 6% of the beta LFPs (18-26 Hz) and 18% of the HF-LFPs were tuned for velocity (p-value < 0.05), while 10% of the beta LFPs and 15% of the HF-LFPs were tuned for position. These results suggest that a multidegree-of-freedom brain-machine interface is possible using high-frequency LFP recordings in motor cortex.

Animals↗

PubMed2004

A brain-computer interface using electrocorticographic signals in humans.

Brain-computer interfaces (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the brain can enable users to control a one-dimensional computer cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3-24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74-100% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the brain.

Adult↗

PubMed2004

Differential representation of perception and action in the frontal cortex.

A motor illusion was created to separate human subjects' perception of arm movement from their actual movement during figure drawing. Trajectories constructed from cortical activity recorded in monkeys performing the same task showed that the actual movement was represented in the primary motor cortex, whereas the visualized, presumably perceived, trajectories were found in the ventral premotor cortex. Perception and action representations can be differentially recognized in the brain and may be contained in separate structures.

Animals↗