scholarly journals A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes

2015 ◽  
Author(s):  
Sergey D Stavisky ◽  
Jonathan C Kao ◽  
Paul Nuyujukian ◽  
Stephen I Ryu ◽  
Krishna V Shenoy
Keyword(s):  
Local Field ◽  
High Performance ◽  
Premotor Cortex ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Control Signal ◽  
Multielectrode Arrays ◽  
Field Potentials ◽  
Reaching Task ◽  
Improved Performance

Objective. Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main Results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

Early Visuomotor Representations Revealed From Evoked Local Field Potentials in Motor and Premotor Cortical Areas

2006 ◽  
Vol 96 (3) ◽  
pp. 1492-1506 ◽  
Author(s):  
John G. O'Leary ◽  
Nicholas G. Hatsopoulos
Keyword(s):  
Local Field ◽  
Primary Motor Cortex ◽  
Premotor Cortex ◽  
Local Field Potentials ◽  
Delay Period ◽  
Field Potentials ◽  
Frequency Bands ◽  
Reaching Task ◽  
Target Direction ◽  
Related Information

Local field potentials (LFPs) recorded from primary motor cortex (MI) have been shown to be tuned to the direction of visually guided reaching movements, but MI LFPs have not been shown to be tuned to the direction of an upcoming movement during the delay period that precedes movement in an instructed-delay reaching task. Also, LFPs in dorsal premotor cortex (PMd) have not been investigated in this context. We therefore recorded LFPs from MI and PMd of monkeys ( Macaca mulatta) and investigated whether these LFPs were tuned to the direction of the upcoming movement during the delay period. In three frequency bands we identified LFP activity that was phase-locked to the onset of the instruction stimulus that specified the direction of the upcoming reach. The amplitude of this activity was often tuned to target direction with tuning widths that varied across different electrodes and frequency bands. Single-trial decoding of LFPs demonstrated that prediction of target direction from this activity was possible well before the actual movement is initiated. Decoding performance was significantly better in the slowest-frequency band compared with that in the other two higher-frequency bands. Although these results demonstrate that task-related information is available in the local field potentials, correlations among these signals recorded from a densely packed array of electrodes suggests that adequate decoding performance for neural prosthesis applications may be limited as the number of simultaneous electrode recordings is increased.

scholarly journals Low-Frequency Local Field Potentials and Spikes in Primary Visual Cortex Convey Independent Visual Information

2008 ◽  
Vol 28 (22) ◽  
pp. 5696-5709 ◽  
Author(s):  
A. Belitski ◽  
A. Gretton ◽  
C. Magri ◽  
Y. Murayama ◽  
M. A. Montemurro ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
Visual Information ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Field Potentials

scholarly journals Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials

2012 ◽  
Vol 107 (5) ◽  
pp. 1337-1355 ◽  
Author(s):  
Arjun K. Bansal ◽  
Wilson Truccolo ◽  
Carlos E. Vargas-Irwin ◽  
John P. Donoghue
Keyword(s):  
Local Field ◽  
Local Field Potentials ◽  
Multielectrode Arrays ◽  
Field Potentials ◽  
Frequency Bands ◽  
Reach And Grasp ◽  
Multiunit Activity ◽  
Relative Value ◽  
Movement Parameters ◽  
First Time

Neural activity in motor cortex during reach and grasp movements shows modulations in a broad range of signals from single-neuron spiking activity (SA) to various frequency bands in broadband local field potentials (LFPs). In particular, spatiotemporal patterns in multiband LFPs are thought to reflect dendritic integration of local and interareal synaptic inputs, attentional and preparatory processes, and multiunit activity (MUA) related to movement representation in the local motor area. Nevertheless, the relationship between multiband LFPs and SA, and their relationship to movement parameters and their relative value as brain-computer interface (BCI) control signals, remain poorly understood. Also, although this broad range of signals may provide complementary information channels in primary (MI) and ventral premotor (PMv) areas, areal differences in information have not been systematically examined. Here, for the first time, the amount of information in SA and multiband LFPs was compared for MI and PMv by recording from dual 96-multielectrode arrays while monkeys made naturalistic reach and grasp actions. Information was assessed as decoding accuracy for 3D arm end point and grip aperture kinematics based on SA or LFPs in MI and PMv, or combinations of signal types across areas. In contrast with previous studies with ≤16 simultaneous electrodes, here ensembles of >16 units (on average) carried more information than multiband, multichannel LFPs. Furthermore, reach and grasp information added by various LFP frequency bands was not independent from that in SA ensembles but rather typically less than and primarily contained within the latter. Notably, MI and PMv did not show a particular bias toward reach or grasp for this task or for a broad range of signal types. For BCIs, our results indicate that neuronal ensemble spiking is the preferred signal for decoding, while LFPs and combined signals from PMv and MI can add robustness to BCI control.

scholarly journals A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

2015 ◽  
Vol 12 (3) ◽  
pp. 036009 ◽  
Author(s):  
Sergey D Stavisky ◽  
Jonathan C Kao ◽  
Paul Nuyujukian ◽  
Stephen I Ryu ◽  
Krishna V Shenoy
Keyword(s):  
Local Field ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Brain Machine Interface ◽  
Field Potentials ◽  
High Performing ◽  
Machine Interface

scholarly journals Inferring Spike Trains From Local Field Potentials

2008 ◽  
Vol 99 (3) ◽  
pp. 1461-1476 ◽  
Author(s):  
Malte J. Rasch ◽  
Arthur Gretton ◽  
Yusuke Murayama ◽  
Wolfgang Maass ◽  
Nikos K. Logothetis
Keyword(s):  
Spontaneous Activity ◽  
Local Field ◽  
Local Field Potentials ◽  
Low Frequency ◽  
Spike Trains ◽  
Dorsal Lateral Geniculate Nucleus ◽  
Support Vector ◽  
Field Potentials ◽  
Data Set ◽  
Spiking Activity

We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100-ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high γ-range (40–90 Hz) and information contained in low-frequency oscillations (<10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during seminatural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of non-anesthetized monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g., LFPs derived from recordings in the dorsal lateral geniculate nucleus) hold no useful information for predicting spiking activity.

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