Biomedical subjects

Bijan Pesaran

Publications and source records attributed to Bijan Pesaran.

5 recordsLinked to original sources

PubMed2006

Dorsal premotor neurons encode the relative position of the hand, eye, and goal during reach planning.

When reaching to grasp an object, we often move our arm and orient our gaze together. How are these movements coordinated? To investigate this question, we studied neuronal activity in the dorsal premotor area (PMd) and the medial intraparietal area (area MIP) of two monkeys while systematically varying the starting position of the hand and eye during reaching. PMd neurons encoded the relative position of the target, hand, and eye. MIP neurons encoded target location with respect to the eye only. These results indicate that whereas MIP encodes target locations in an eye-centered reference frame, PMd uses a relative position code that specifies the differences in locations between all three variables. Such a relative position code may play an important role in coordinating hand and eye movements by computing their relative position.

Action Potentials↗

PubMed2006

A method for detection and classification of events in neural activity.

We present a method for the real time prediction of punctuate events in neural activity, based on the time-frequency spectrum of the signal, applicable both to continuous processes like local field potentials (LFPs) as well as to spike trains. We test it on recordings of LFP and spiking activity acquired previously from the lateral intraparietal area (LIP) of macaque monkeys performing a memory-saccade task. In contrast to earlier work, where trials with known start times were classified, our method detects and classifies trials directly from the data. It provides a means to quantitatively compare and contrast the content of LFP signals and spike trains: we find that the detector performance based on the LFP matches the performance based on spike rates. The method should find application in the development of neural prosthetics based on the LFP signal. Our approach uses a new feature vector, which we call the 2d cepstrum.

Algorithms↗

PubMed2004

Selecting the signals for a brain-machine interface.

Brain-machine interfaces are being developed to assist paralyzed patients by enabling them to operate machines with recordings of their own neural activity. Recent studies show that motor parameters, such as hand trajectory, and cognitive parameters, such as the goal and predicted value of an action, can be decoded from the recorded activity to provide control signals. Neural prosthetics that use simultaneously a variety of cognitive and motor signals can maximize the ability of patients to communicate and interact with the outside world. Although most studies have recorded electroencephalograms or spike activity, recent research shows that local field potentials (LFPs) offer a promising additional signal. The decode performances of LFPs and spike signals are comparable and, because LFP recordings are more long lasting, they might help to increase the lifetime of the prosthetics.

Action Potentials↗

PubMed2003

Neural prosthetic control signals from plan activity.

The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals. To demonstrate how control signals can be derived from such plan activity we performed a computational study with neural activity previously recorded from the posterior parietal cortex of rhesus monkeys planning arm movements. We employed maximum likelihood decoders to estimate movement direction and to drive finite state machines governing when to move. Performance exceeded 90% with as few as 40 neurons.

Action Potentials↗

PubMed2002

Temporal structure in neuronal activity during working memory in macaque parietal cortex.

Many cortical structures have elevated firing rates during working memory, but it is not known how the activity is maintained. To investigate whether reverberating activity is important, we studied the temporal structure of local field potential (LFP) activity and spiking from area LIP in two awake macaques during a memory-saccade task. Using spectral analysis, we found spatially tuned elevated power in the gamma band (25-90 Hz) in LFP and spiking activity during the memory period. Spiking and LFP activity were also coherent in the gamma band but not at lower frequencies. Finally, we decoded LFP activity on a single-trial basis and found that LFP activity in parietal cortex discriminated between preferred and anti-preferred direction with approximately the same accuracy as the spike rate and predicted the time of a planned movement with better accuracy than the spike rate. This finding could accelerate the development of a cortical neural prosthesis.

Action Potentials↗