A central transformation that occurs within mammalian visual cortex is the change from linear, polarity-sensitive responses to nonlinear, polarity-insensitive responses. These neurons are classically labelled as either simple or complex, respectively, on the basis of their response linearity (Skottun et al., 1991). While the difference between cell classes is clear when the stimulus strength is high, reducing stimulus strength diminishes the differences between the cell types and causes some complex cells to respond as simple cells (Crowder et al., 2007; van Kleef et al., 2010; Hietanen et al., 2013). To understand the synaptic basis for this shift in behavior, we used whole-cell recordings while systematically shifting stimulus contrast. We find systematic shifts in the degree of complex cell responses in mouse primary visual cortex (V1) at the subthreshold level, demonstrating that synaptic inputs change in concert with the shifts in response linearity and that the change in response linearity is not simply due to the threshold nonlinearity. These shifts are consistent with a visual cortex model in which the recurrent amplification acts as a critical component in the generation of complex cell responses (Chance et al., 1999).
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http://dx.doi.org/10.1523/ENEURO.0480-18.2019 | DOI Listing |
Elife
January 2025
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, United States.
High-resolution awake mouse functional magnetic resonance imaging (fMRI) remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radio frequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Furthermore, this study provides a thorough acclimation method used to accustom animals to the MRI environment minimizing motion-induced artifacts.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Background: Many proposed clinical decision support systems (CDSS) require multiple disparate data elements as input, which makes implementation difficult, and furthermore have a black-box nature leading to low interpretability. Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is an established modality for the diagnosis of dementia, and a CDSS that uses only an FDG-PET image to produce a reliable and understandable result would ease both of these challenges to clinical application.
Method: A deep variational autoencoder (VAE) was used to extract a latent representation of each image through prior training from FDG-PET brain images (n=2000).
Background: Alzheimer's disease (AD) is multifactorial, thus multivariate analyses help untangle its effects. We employed multiple contrast MRI to reveal age-related brain changes in populations at risk for AD, due to APOE4 carriage. We assessed volume and microstructure changes using diffusion weighted imaging, and quantitative magnetic susceptibility maps (QSM) reflective primarily of cerebral iron metabolism.
View Article and Find Full Text PDFBackground: Attention deficits are notable in Lewy body dementia (LBD) and in Alzheimer's disease (AD), however, its underlying neurobiology and neuropathology are unclear. Functional magnetic resonance imaging (fMRI) and electroencephalograph (EEG) provides information about attention deployment and regional neural oscillatory deficits in LBD and AD. In this study, we combined fMRI and EEG to detect neural correlates of attention dysfunctions in LBD and AD.
View Article and Find Full Text PDFAccounting for why discrimination between different perceptual contents is not always accompanied conscious detection of that content remains a challenge for predictive processing theories of perception. Here, we test a hypothesis that detection is supported by a distinct inference within generative models of perceptual content. We develop a novel visual perception paradigm that probes such inferences by manipulating both expectations about stimulus content (stimulus identity) and detection of content (stimulus presence).
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