The influence of spontaneous activity on stimulus processing in primary visual cortex

Spontaneous activity in the resting human brain has been studied extensively; however, how such activity affects the local processing of a sensory stimulus is relatively unknown. Here, we examined the impact of spontaneous activity in primary visual cortex on neuronal and behavioural responses to a simple visual stimulus, using functional MRI. Stimulus-evoked responses remained essentially unchanged by spontaneous fluctuations, combining with them in a largely linear fashion (i.e., with little evidence for an interaction). However, interactions between spontaneous fluctuations and stimulus-evoked responses were evident behaviourally: high levels of spontaneous activity tended to be associated with increased stimulus detection at perceptual threshold. Our results extend those found in studies of spontaneous fluctuations in motor cortex and higher order visual areas, and suggest a fundamental role for spontaneous activity in stimulus processing. (C) 2011 Elsevier Inc. All rights reserved

Supplemental vitamin B-12 enhances the neural response to sensory stimulation in the barrel cortex of healthy rats but does not affect spontaneous neural activity

Background: Although vitamin B-12 (B-12) is known to contribute to the structural and functional development of the brain, it is unclear if B-12 supplementation has any beneficial effect in healthy populations in terms of enhanced neurological status of the brain or improved cognitive function. Objectives: We investigated the effect of dietary supplementation of B-12 on the cortical neural activity of well-nourished young adult rats and tested the hypothesis that B-12 supplementation in healthy rats may reduce sensory evoked neural activity due to enhanced inhibition. Methods: Female Lister Hooded rats weighing between 190g to 265g (2 to 4 months old) were included in the study. The experimental group was fed with B-12 (Cyanocobalamin) enriched water at a concentration of 1mg/L, and the control (CON) group with tap water for 3 weeks. Animals were then anaesthetised and cortical neural responses to whisker stimulation were recorded in vivo using a multi-channel micro-electrode, from which local field potentials (LFPs) were extracted. Results: Somatosensory evoked LFP was enhanced 25% in the B-12 group (4.13±0.24mV) compared with the CON group (3.30±0.21mV) (P=0.02). Spontaneous neural activity did not differ between groups; frequency spectra at each frequency bin of interest did not pass the cluster-forming threshold at the 5% significance level. Conclusions: These findings do not provide evidence supporting the hypothesis of decreased neural activity due to B-12 supplementation. As the spontaneous neural activity was unaffected, the increase in somatosensory evoked LFP may be due to enhanced afferent signal reaching the barrel cortex from the whisker pad, indicating that B-12 supplemented rats may have enhanced sensitivity to sensory stimulation compared to the CON group. We suggest that this enhancement might be the result of lowered sensory threshold, although the underlying mechanism has yet to be elucidated

Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience

Cognitive neuroscience depends on the use of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to probe brain function. Although commonly used as a surrogate measure of neuronal activity, BOLD signals actually reflect changes in brain blood oxygenation. Understanding the mechanisms linking neuronal activity to vascular perfusion is, therefore, critical in interpreting BOLD. Advances in cellular neuroscience demonstrating differences in this neurovascular relationship in different brain regions, conditions or pathologies are often not accounted for when interpreting BOLD. Meanwhile, within cognitive neuroscience, increasing use of high magnetic field strengths and the development of model-based tasks and analyses have broadened the capability of BOLD signals to inform us about the underlying neuronal activity, but these methods are less well understood by cellular neuroscientists. In 2016, a Royal Society Theo Murphy Meeting brought scientists from the two communities together to discuss these issues. Here we consolidate the main conclusions arising from that meeting. We discuss areas of consensus about what BOLD fMRI can tell us about underlying neuronal activity, and how advanced modelling techniques have improved our ability to use and interpret BOLD. We also highlight areas of controversy in understanding BOLD and suggest research directions required to resolve these issues

Predicting perceptual decision biases from early brain activity

Perceptual decision making is believed to be driven by the accumulation of sensory evidence following stimulus encoding. More controversially, some studies report that neural activity preceding the stimulus also affects the decision process. We used a multivariate pattern classification approach for the analysis of the human electroencephalogram (EEG) to decode choice outcomes in a perceptual decision task from spatially and temporally distributed patterns of brain signals. When stimuli provided discriminative information, choice outcomes were predicted by neural activity following stimulus encoding; when stimuli provided no discriminative information, choice outcomes were predicted by neural activity preceding the stimulus. Moreover, in the absence of discriminative information, the recent choice history primed the choices on subsequent trials. A diffusion model fitted to the choice probabilities and response time distributions showed that the starting point of the evidence accumulation process was shifted toward the previous choice, consistent with the hypothesis that choice priming biases the accumulation process toward a decision boundary. This bias is reflected in prestimulus brain activity, which, in turn, becomes predictive of future decisions. Our results provide a model of how non-stimulus-driven decision making in humans could be accomplished on a neural level

A machine learning approach to predict perceptual decisions: an insight into face pareidolia

The perception of an external stimulus not only depends upon the characteristics of the stimulus but is also influenced by the ongoing brain activity prior to its presentation. In this work, we directly tested whether spontaneous electrical brain activities in prestimulus period could predict perceptual outcome in face pareidolia (visualizing face in noise images) on a trial-by-trial basis. Participants were presented with only noise images but with the prior information that some faces would be hidden in these images, while their electrical brain activities were recorded; participants reported their perceptual decision, face or no-face, on each trial. Using differential hemispheric asymmetry features based on large-scale neural oscillations in a machine learning classifier, we demonstrated that prestimulus brain activities could achieve a classification accuracy, discriminating face from no-face perception, of 75% across trials. The time–frequency features representing hemispheric asymmetry yielded the best classification performance, and prestimulus alpha oscillations were found to be mostly involved in predicting perceptual decision. These findings suggest a mechanism of how prior expectations in the prestimulus period may affect post-stimulus decision making

Frequency-band signatures of visual responses to naturalistic input in ferret primary visual cortex during free viewing

Neuronal firing responses reflect the statistics of visual input and emerge from the interaction with endogenous network dynamics. Artificial visual stimuli presented to animals in which the network dynamics were constrained by anesthetic agents or trained behavioral tasks have provided fundamental understanding of how individual neurons in primary visual cortex respond to input. In contrast, very little is known about the mesoscale network dynamics and their relationship to microscopic spiking activity in the awake animal during free viewing of naturalistic visual input. To address this gap in knowledge, we recorded local field potential (LFP) and multiunit activity (MUA) in all layers of primary visual cortex (V1) of awake, freely viewing ferrets presented with naturalistic visual input (nature movie clips). We found that naturalistic visual stimuli modulated the entire oscillation spectrum; low frequency oscillations were mostly suppressed whereas higher frequency oscillations were enhanced. In average across all cortical layers, stimulus-induced change in delta and alpha power negatively correlated with the MUA responses, whereas sensory-evoked increases in gamma power positively correlated with MUA responses. The time-course of the band-limited power in these frequency bands provided evidence for a model in which naturalistic visual input switched V1 between two distinct, endogenously present activity states defined by the power of low (delta, alpha) and high (gamma) frequency oscillatory activity. Therefore, the two mesoscale activity states delineated in this study may define the engagement of the circuit with processing sensory input at the level of spiking activity