Ongoing Alpha Activity in V1 Regulates Visually Driven Spiking Responses

Abstract

The interlaminar connections in the primate primary visual cortex (V1) are well described, as is the presence of ongoing alpha-range (7-14 Hz) fluctuations in this area. Less well understood is how these interlaminar connections and ongoing fluctuations contribute to the regulation of visual spiking responses. Here, we investigate the relationship between alpha fluctuations and spiking responses to visual stimuli across cortical layers. Using laminar probes in macaque V1, we show that neural firing couples with the phase of alpha fluctuations, and that magnitude of this coupling is particularly pronounced during visual stimulation. The strongest modulation of spiking activity was observed in layers 2/3. Alpha-spike coupling and current source density analysis pointed to an infragranular origin of the alpha fluctuations. Taken together, these results indicate that ongoing infragranular alpha-range fluctuations in V1 play a role in regulating columnar visual activity.

Binocular Modulation of Monocular V1 Neurons

“…In each session, we penetrated the dura mater over V1 with a linear multielectrode array and positioned the array so that its contacts spanned the depth of cortex ( Figure S1A) [14][15][16]. Although we recorded extracellular voltages, we displayed visual stimuli through a mirror stereoscope to stimulate the eyes independently ( Figure 1A, upper panel).…”

“…We excluded contacts on the extreme ends of the array that did not exhibit a visual response. After removing these contacts, the location of the initial current sink was used to align and average data across electrode penetrations, resulting in 0.1 mm ± 0.05 mm resolution across the depth of V1 [14][15][16][65][66][67][68][69][70].…”

The role of alpha oscillations in distractor inhibition during memory retention

“…Alpha oscillations reflect reduced neuronal excitability in sensory brain areas, as indexed by the spike‐firing rate (Haegens et al ., ; Dougherty et al ., ), the hemodynamic fMRI signal (Goldman et al ., ; Becker et al ., ) or behavioral detection performance (van Dijk et al ., ; Chaumon & Busch, ; Myers et al ., ; Iemi et al ., ). According to Jensen & Mazaheri (), alpha oscillations serve as a mechanism for top‐down controlled gating of task‐relevant information by selectively inhibiting task‐irrelevant neural populations, thereby increasing the signal‐to‐noise ratio (see also Klimesch et al ., ; Foxe & Snyder, ).…”

Adaptation of Intracortical Signaling Concurs with Enhanced Encoding Efficiency

“…Neural synchrony can affect sensory processing independently of spike rates, and coherence has been shown to change with stimulation history (Gutnisky and Dragoi 2008; Hansen and Dragoi 2011). The spectral relationship between the local field potential (LFP) and the timing of spikes (spike-field coherence, or SFC) has been tied to neuronal synchronization within and between brain areas (Engel et al 2001; Zeitler et al 2006; Womelsdorf et al 2007; Gilbert et al 2010; Bosman et al 2012; Spaak et al 2012; Brunet et al 2014; Schmiedt et al 2014; Bastos et al 2015; Dougherty et al 2015; Haegens et al 2015; Ninomiya et al 2015). We thus sought to investigate whether SFC is enhanced in V1 when stimuli are presented repeatedly (see also Hansen and Dragoi 2011).…”

“…For display purposes, two-dimensional representations of CSD as a function of time and space were created by interpolating CSD between adjacent electrode contacts, followed by smoothing with a two-dimensional Gaussian filter ( s = 0.1mm and 15ms) (Pettersen et al 2006). Microelectrode contacts were determined to be located in the granular layer based on the initial sink of a flash-evoked CSD (see Maier et al 2010; Maier 2013; Dougherty et al 2015; Ninomiya et al 2015; Cox et al 2017 for details). Infragranular laminar compartment locations were determined by the position of the initial sink in response to a flashed stimulus and corroborated by additional neurophysiological criteria (Maier et al 2010), such as characteristic patterns of LFP power spectral density (van Kerkoerle et al 2014; Bastos et al 2018), signal correlations of the LFP between all channel combinations, and the latency (Self et al 2013) of stimulus-evoked MUA responses (Supplementary Fig.…”