Single-Trial Decoding of Visual Attention from Local Field Potentials in the Primate Lateral Prefrontal Cortex Is Frequency-Dependent

Abstract

Local field potentials (LFPs) are fluctuations of extracellular voltage that may reflect the physiological phenomena occurring within a volume of neural tissue. It is known that the allocation of spatial attention modulates the amplitude of LFPs in visual areas of primates. An issue that remains poorly investigated is whether and how attention modulates LFPs in executive brain areas, such as the lateral prefrontal cortex (LPFC), thought to be involved in the origins of attention. We addressed this issue by recording LFPs from multielectrode arrays implanted in the LPFC of two macaques. We found that the allocation of attention can be reliably decoded on a single-trial basis from ensembles of LFPs with frequencies Ͼ60 Hz. Using LFP frequencies Ͻ60 Hz, we could not decode the allocation of attention, but we could decode the location of a visual stimulus as well as the endpoint of saccades toward that stimulus. The information contained in the high-frequency LFPs was fully redundant with the information contained in the spiking activity of single neurons recorded from the same electrodes. Moreover, the decoding of attention using ␥ frequency LFPs was less accurate than using spikes, but it was twice more stable across time. Finally, decorrelating the LFP signals from the different electrodes increased decoding performance in the high frequencies by up to ϳ14%. Our findings suggest that LFPs recorded from chronically implanted multielectrode arrays in the LPFC contain information about sensory, cognitive, and motor components of a task in a frequency-dependent manner.

Decoding of top-down cognitive processing for SSVEP-controlled BMI

“…As compared with our findings of decoding covert attentional shift to subsets of external stimuli, there are other recent studies decoding visuospatial attention directly from the intrinsically driven brain activity patterns evoked by attention6970717273. As our study demonstrates the possibility of seamlessly decoding human top-down processes, if a further refined grid-shaped line array is developed and combined with a more elaborated classification method, a recent study74 provides advances in extending previous studies of decoding visuospatial attention6970717273, which were limited to decoding up to four discrete locations/classes.…”

“…As our study demonstrates the possibility of seamlessly decoding human top-down processes, if a further refined grid-shaped line array is developed and combined with a more elaborated classification method, a recent study74 provides advances in extending previous studies of decoding visuospatial attention6970717273, which were limited to decoding up to four discrete locations/classes. The authors found a neuronal signature of direct two-dimensional access to the spatial location of covert attention in macaque prefrontal cortex74.…”

Modulation of local field potentials and neuronal activity in primate hippocampus during saccades

“…To obtain the analytical signal from the preprocessed LFP data, we convolved it with 34 logarithmically spaced complex Morlet wavelets, with seven oscillations (Tallon‐Baudry, Bertrand, Delpuech, & Permier, ) and center frequencies ranging from 2.63 to 256 Hz (Hughes, Whitten, Caplan, & Dickson, ; Liebe, Hoerzer, Logothetis, & Rainer, ; Tremblay, Doucet, Pieper, Sachs, & Martinez‐Trujillo, ). Power was obtained from the squared magnitude of the analytical signal, while phase was derived from the angle between the real and complex parts.…”

“…Saccades have been shown to modulate LFPs in multiple brain areas, such as PFC (Tremblay et al, 2015) and visual cortex (Ito et al, 2011(Ito et al, , 2013Staudigl et al, 2017) cortices. In V1, both saccades and fixations have been found to elicit PC in the delta/theta and alpha/beta bands (Ito et al, 2011(Ito et al, , 2013.…”

Reorganization between preparatory and movement population responses in motor cortex

“…Different circuit-level mechanisms will produce different population structures and it can be critical to know which structure is present when analysing data. For example, a common analysis approach is to train a decoder to predict key experimental variables during one epoch or context and use that decoder to interpret data from another epoch or context14454647. This approach is appropriate in the case of overlapping structure, but not for independent or orthogonal-but-linked structures.…”