Inter-individual Differences in Occipital Alpha Oscillations Correlate with White Matter Tissue Properties of the Optic Radiation

Abstract

Neural oscillations at ∼10 Hz, called alpha oscillations, are one of the most prominent components of neural oscillations in the human brain. In recent years, characteristics (power/frequency/phase) of occipital alpha oscillations have been correlated with various perceptual phenomena. However, the relationship between inter-individual differences in alpha oscillatory characteristics and the properties of the underlying brain structures, such as white matter pathways, is unclear. A possibility is that intrinsic occipital alpha oscillations are mediated by thalamocortical interaction; we hypothesized that the most promising candidate for characterizing the intrinsic alpha oscillation is optic radiation (OR), which is the geniculo-cortical pathway carrying signals between the lateral geniculate nucleus (LGN) and primary visual cortex (V1). We used resting-state magnetoencephalography (MEG) and diffusion-weighted/quantitative magnetic resonance imaging (MRI) (dMRI/qMRI) to correlate the frequency and power of occipital alpha oscillations with the tissue properties of the OR by focusing on the different characteristics across individuals. We found that the peak alpha frequency (PAF) negatively correlated with intracellular volume fraction (ICVF), reflecting diffusion properties in intracellular (axonal) space, whereas the peak alpha power was not correlated with any tissue properties measurements. No significant correlation was found between OR and beta frequency/amplitude or between other white matter tract connecting parietal and inferotemporal cortex and alpha frequency/amplitude. These results support the hypothesis that an interaction between thalamic nuclei and early visual areas is essential for the occipital alpha oscillatory rhythm.

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

“…We collected T1-weighted MRI, dMRI and qT1 data from all subjects. We note that many parts of MRI acquisition method is common to those used in our previous works (Oishi et al, 2018;Minami et al, 2020).…”

“…We note that many parts of MRI data analysis pipeline are common to those used in our previous works (Oishi et al, 2018;Takemura et al, 2019;Minami et al, 2020).…”

“…We evaluated the tissue properties of white matter tracts (the optic radiation and the corticospinal tract) based on previously reported methods (Levin et al, 2010;Yeatman et al, 2012;Duan et al, 2015;Takemura et al, 2019;Minami et al, 2020). Briefly, we resampled individual streamlines which belong to white matter tracts to 100 equidistant nodes.…”

Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains

“…The MTV data were acquired from all subjects according to a previously described protocol (Mezer et al, 2013;Minami et al, 2020;Oishi et al, 2018;Takemura et al, 2019). Four fast low-angle shot (FLASH) images were measured with flip angles of 4°, 10°, 20°, and 30° (TR, 12 ms; TE, 2.43 ms) with 1 mm isotropic voxels.…”

“…Besides its function as a relay station, a growing body of evidence suggests that the LGN is involved in a wide range of visual functions, including eye-specific dominance and suppression during binocular rivalry (Haynes et al, 2005), visual attention (Ling et al, 2015;O'Connor et al, 2002;Schneider and Kastner, 2009), and visual perceptual learning (Yu et al, 2016). The LGN is also involved in the neuronal synchrony widely observed in the visual cortex (Hughes et al, 2004;Liu et al, 2012;Minami et al, 2020). Human LGN is composed of six layers that are categorized into two major subdivisions, the magnocellular (M) and parvocellular (P) subdivisions.…”