Precise Spatial Tuning of Visually Driven Alpha Oscillations in Human Visual Cortex.

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across occipital cortex, reflecting general cognitive states such as arousal and alertness. However, there is also evidence that modulation of alpha oscillations in visual cortex can be spatially specific. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We separated the alpha oscillatory power from broadband power changes. The variation in alpha oscillatory power with stimulus position was then fit by a population receptive field (pRF) model. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power (70-180 Hz), but are several times larger. The results demonstrate that alpha suppression in human visual cortex can be precisely tuned. Finally, we show how the pattern of alpha responses can explain several features of exogenous visual attention. Significance Statement: The alpha oscillation is the largest electrical signal generated by the human brain. An important question in systems neuroscience is the degree to which this oscillation reflects system-wide states and behaviors such as arousal, alertness, and attention, versus much more specific functions in the routing and processing of information. We examined alpha oscillations at high spatial precision in human patients with intracranial electrodes implanted over visual cortex. We discovered a surprisingly high spatial specificity of visually driven alpha oscillations, which we quantified with receptive field models. We further use our discoveries about properties of the alpha response to show a link between these oscillations and the spread of visual attention.

Temporal Dynamics of Neural Responses in Human Visual Cortex.

Neural responses to visual stimuli exhibit complex temporal dynamics, including subadditive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic recordings from patients presented with stimuli that varied in duration, interstimulus interval (ISI) and contrast. Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several nonlinear features. Peak response amplitude saturates with high contrast and longer stimulus durations, the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs, and response latency decreases with increasing contrast. These features are accurately captured by a computational model composed of a small set of canonical neuronal operations, that is, linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex and demonstrate that a simple model captures these dynamics at millisecond resolution.SIGNIFICANCE STATEMENT Sensory inputs and neural responses change continuously over time. It is especially challenging to understand a system that has both dynamic inputs and outputs. Here, we use a computational modeling approach that specifies computations to convert a time-varying input stimulus to a neural response time course, and we use this to predict neural activity measured in the human visual cortex. We show that this computational model predicts a wide variety of complex neural response shapes, which we induced experimentally by manipulating the duration, repetition, and contrast of visual stimuli. By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the brain processes dynamic sensory information.

Impact of task-specific training on saccadic eye movement performance.

Prosaccades are saccadic eye movements made reflexively in response to the sudden appearance of visual stimuli, whereas antisaccades are saccades that are directed to a location opposite a stimulus. Bibi and Edelman (Bibi R, Edelman JA. J Neurophysiol 102: 3101-3110, 2009) demonstrated that decreases in reaction time resulting from training prosaccades along one spatial axis (horizontal or vertical) could transfer to prosaccades made along the other axis. To help determine whether visual or motor-related processes underlie this facilitation, in the present study we trained participants to make prosaccades and probed their performance (reaction time, error rate) on antisaccade trials and vice versa. Subjects were probed for the effects of training on saccade performance before, during, and after 12 sessions of training. Training on prosaccades improved performance on both pro- and antisaccade tasks. Antisaccade training, with either a classic step task or a gap task, improved performance on gap prosaccades, though by less than it improved antisaccade performance, but had limited effect on an overlap prosaccade task. Across all subjects, training on one task only rarely had an adverse impact on an untrained task. These findings suggest that the predominant effect of saccade training is to facilitate fixation disengagement and motor preparation processes while having little impact on visual input to the saccadic system.NEW & NOTEWORTHY This is the first systematic examination of whether training of prosaccades and antisaccades is task specific or instead transfers to the other saccade type. It finds that training tends to improve performance of all saccade types tested. These behavioral results provide insight into saccade neurophysiology, suggesting that saccade training enhances processes related to motor excitation and inhibition.

Molecular Signature and Mechanisms of Hepatitis D Virus-Associated Hepatocellular Carcinoma.

There is limited data on the molecular mechanisms whereby hepatitis D virus (HDV) promotes liver cancer. Therefore, serum and liver specimens obtained at the time of liver transplantation from well-characterized patients with HDV-HCC (n = 5) and with non-HCC HDV cirrhosis (n = 7) were studied using an integrated genomic approach. Transcriptomic profiling was performed using laser capture-microdissected (LCM) malignant and nonmalignant hepatocytes, tumorous and nontumorous liver tissue from patients with HDV-HCC, and liver tissue from patients with non-HCC HDV cirrhosis. HDV-HCC was also compared with hepatitis B virus (HBV) HBV-HCC alone, and hepatitis C virus (HCV) HCV-HCC. HDV malignant hepatocytes were characterized by an enrichment of upregulated transcripts associated with pathways involved in cell-cycle/DNA replication, damage, and repair (Sonic Hedgehog, GADD45, DNA-damage-induced 14-3-3σ, cyclins and cell-cycle regulation, cell cycle: G2-M DNA-damage checkpoint regulation, and hereditary breast cancer). Moreover, a large network of genes identified functionally relate to DNA repair, cell cycle, mitotic apparatus, and cell division, including 4 cancer testis antigen genes, attesting to the critical role of genetic instability in this tumor. Besides being overexpressed, these genes were also strongly coregulated. Gene coregulation was high not only when compared with nonmalignant hepatocytes, but also to malignant hepatocytes from HBV-HCC alone or HCV-HCC. Activation and coregulation of genes critically associated with DNA replication, damage, and repair point to genetic instability as an important mechanism of HDV hepatocarcinogenesis. This specific HDV-HCC trait emerged also from the comparison of the molecular pathways identified for each hepatitis virus-associated HCC. Despite the dependence of HDV on HBV, these findings suggest that HDV and HBV promote carcinogenesis by distinct molecular mechanisms.Implications: This study identifies a molecular signature of HDV-associated hepatocellular carcinoma and suggests the potential for new biomarkers for early diagnostics. Mol Cancer Res; 16(9); 1406-19. ©2018 AACR.