Changes in responses of the amygdala and hippocampus during fear conditioning are associated with persecutory beliefs.

The persecutory delusion is the most common symptom of psychosis, yet its underlying neurobiological mechanisms are poorly understood. Prior studies have suggested that abnormalities in medial temporal lobe-dependent associative learning may contribute to this symptom. In the current study, this hypothesis was tested in a non-clinical sample of young adults without histories of psychiatric treatment (n = 64), who underwent classical Pavlovian fear conditioning while fMRI data were collected. During the fear conditioning procedure, participants viewed images of faces which were paired (the CS+) or not paired (the CS-) with an aversive stimulus (a mild electrical shock). Fear conditioning-related neural responses were measured in two medial temporal lobe regions, the amygdala and hippocampus, and in other closely connected brain regions of the salience and default networks. The participants without persecutory beliefs (n = 43) showed greater responses to the CS- compared to the CS+ in the right amygdala and hippocampus, while the participants with persecutory beliefs (n = 21) failed to exhibit this response. These between-group differences were not accounted for by symptoms of depression, anxiety or a psychosis risk syndrome. However, the severity of subclinical psychotic symptoms overall was correlated with the level of this aberrant response in the amygdala (p = .013) and hippocampus (p = .033). Thus, these findings provide evidence for a disruption of medial temporal lobe-dependent associative learning in young people with subclinical psychotic symptoms, specifically persecutory thinking.

Saturating Nonlinearities of Contrast Response in Human Visual Cortex.

Response nonlinearities are ubiquitous throughout the brain, especially within sensory cortices where changes in stimulus intensity typically produce compressed responses. Although this relationship is well established in electrophysiological measurements, it remains controversial whether the same nonlinearities hold for population-based measurements obtained with human fMRI. We propose that these purported disparities are not contingent on measurement type and are instead largely dependent on the visual system state at the time of interrogation. We show that deploying a contrast adaptation paradigm permits reliable measurements of saturating sigmoidal contrast response functions (10 participants, 7 female). When not controlling the adaptation state, our results coincide with previous fMRI studies, yielding nonsaturating, largely linear contrast responses. These findings highlight the important role of adaptation in manifesting measurable nonlinear responses within human visual cortex, reconciling discrepancies reported in vision neuroscience, re-establishing the qualitative relationship between stimulus intensity and response across different neural measures and the concerted study of cortical gain control.SIGNIFICANCE STATEMENT Nonlinear stimulus-response relationships govern many essential brain functions, ranging from the sensory to cognitive level. Certain core response properties previously shown to be nonlinear with nonhuman electrophysiology recordings have yet to be reliably measured with human neuroimaging, prompting uncertainty and reconsideration. The results of this study stand to reconcile these incongruencies in the vision neurosciences, demonstrating the profound impact adaptation can have on brain activation throughout the early visual cortex. Moving forward, these findings facilitate the study of modulatory influences on sensory processing (i.e., arousal and attention) and help establish a closer link between neural recordings in animals and hemodynamic measurements from human fMRI, resuming a concerted effort to understand operations in the mammalian cortex.

Population spatial frequency tuning in human early visual cortex.

Neurons within early visual cortex are selective for basic image statistics, including spatial frequency. However, these neurons are thought to act as band-pass filters, with the window of spatial frequency sensitivity varying across the visual field and across visual areas. Although a handful of previous functional (f)MRI studies have examined human spatial frequency sensitivity using conventional designs and analysis methods, these measurements are time consuming and fail to capture the precision of spatial frequency tuning (bandwidth). In this study, we introduce a model-driven approach to fMRI analyses that allows for fast and efficient estimation of population spatial frequency tuning (pSFT) for individual voxels. Blood oxygen level-dependent (BOLD) responses within early visual cortex were acquired while subjects viewed a series of full-field stimuli that swept through a large range of spatial frequency content. Each stimulus was generated by band-pass filtering white noise with a central frequency that changed periodically between a minimum of 0.5 cycles/degree (cpd) and a maximum of 12 cpd. To estimate the underlying frequency tuning of each voxel, we assumed a log-Gaussian pSFT and optimized the parameters of this function by comparing our model output against the measured BOLD time series. Consistent with previous studies, our results show that an increase in eccentricity within each visual area is accompanied by a drop in the peak spatial frequency of the pSFT. Moreover, we found that pSFT bandwidth depends on eccentricity and is correlated with the pSFT peak; populations with lower peaks possess broader bandwidths in logarithmic scale, whereas in linear scale this relationship is reversed.NEW & NOTEWORTHY Spatial frequency selectivity is a hallmark property of early visuocortical neurons, and mapping these sensitivities gives us crucial insight into the hierarchical organization of information within visual areas. Due to technical obstacles, we lack a comprehensive picture of the properties of this sensitivity in humans. Here, we introduce a new method, coined population spatial frequency tuning mapping, which circumvents the limitations of the conventional neuroimaging methods, yielding a fuller visuocortical map of spatial frequency sensitivity.

Luminance potentiates human visuocortical responses.

Our visual system is tasked with transforming variations in light within our environment into a coherent percept, typically described using properties such as luminance and contrast. Models of vision often downplay the importance of luminance in shaping cortical responses, instead prioritizing representations that do not covary with overall luminance (i.e., contrast), and yet visuocortical response properties that may reflect luminance encoding remain poorly understood. In this study, we examined whether well-established visuocortical response properties may also reflect luminance encoding, challenging the idea that luminance information itself plays no significant role in supporting visual perception. To do so, we measured functional activity in human visual cortex when presenting stimuli varying in contrast and mean luminance, and found that luminance response functions are strongly contrast dependent between 50 and 250 cd/m2, confirmed with a subsequent experiment. High-contrast stimuli produced linearly increasing responses as luminance increased logarithmically for all early visual areas, whereas low-contrast stimuli produced either flat (V1) or assorted positive linear (V2 and V3) response profiles. These results reveal that the mean luminance information of a visual signal persists within visuocortical representations, potentially reflecting an inherent imbalance of excitatory and inhibitory components that can be either contrast dependent (V1 and V2) or contrast invariant (V3). The role of luminance should be considered when the aim is to drive potent visually evoked responses and when activity is compared across studies. More broadly, overall luminance should be weighed heavily as a core feature of the visual system and should play a significant role in cortical models of vision.NEW & NOTEWORTHY This neuroimaging study investigates the influence of overall luminance on population activity in human visual cortex. We discovered that the response to a particular stimulus contrast level is reliant, in part, on the mean luminance of a signal, revealing that the mean luminance information of our environment is represented within the visual cortex. The results challenge a long-standing misconception about the role of luminance information in the processing of visual information at the cortical level.

Cross-validation of serial optical coherence scanning and diffusion tensor imaging: a study on neural fiber maps in human medulla oblongata.

We established a strategy to perform cross-validation of serial optical coherence scanner imaging (SOCS) and diffusion tensor imaging (DTI) on a postmortem human medulla. Following DTI, the sample was serially scanned by SOCS, which integrates a vibratome slicer and a multi-contrast optical coherence tomography rig for large-scale three-dimensional imaging at microscopic resolution. The DTI dataset was registered to the SOCS space. An average correlation coefficient of 0.9 was found between the co-registered fiber maps constructed by fractional anisotropy and retardance contrasts. Pixelwise comparison of fiber orientations demonstrated good agreement between the DTI and SOCS measures. Details of the comparison were studied in regions exhibiting a variety of fiber organizations. DTI estimated the preferential orientation of small fiber tracts; however, it didn't capture their complex patterns as SOCS did. In terms of resolution and imaging depth, SOCS and DTI complement each other, and open new avenues for cross-modality investigations of the brain.