The folding fingerprint of visual cortex reveals the timing of human V1 and V2

Primate neocortex contains over 30 visual areas. Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics between adjacent visual areas, a critical component of understanding visual cognition. The voltages recorded at the scalp, electroencephalography (EEG), is a direct measure of neural activity that reflects the summed activity across all brain areas. Identifying the cortical sources that contribute to the EEG is a difficult problem. We developed an anatomically constrained dipole search method that solves the traditional problems by combining fMRI, EEG and many stimuli that activate small cortical regions. The method provides a means to validate the extracted waveforms. Both V1 and V2 waveforms have similar onset latencies as well as dynamics that can explain previous controversial findings about the responses of these areas

Top-down effects on early visual processing in humans: a predictive coding framework

An increasing number of human electroencephalography (EEG) studies examining the earliest component of the visual evoked potential, the so-called C1, have cast doubts on the previously prevalent notion that this component is impermeable to top-down effects. This article reviews the original studies that (i) described the C1, (ii) linked it to primary visual cortex (V1) activity, and (iii) suggested that its electrophysiological characteristics are exclusively determined by low-level stimulus attributes, particularly the spatial position of the stimulus within the visual field. We then describe conflicting evidence from animal studies and human neuroimaging experiments and provide an overview of recent EEG and magnetoencephalography (MEG) work showing that initial V1 activity in humans may be strongly modulated by higher-level cognitive factors. Finally, we formulate a theoretical framework for understanding top-down effects on early visual processing in terms of predictive coding

Dynamic Construction of Stimulus Values in the Ventromedial Prefrontal Cortex

Signals representing the value assigned to stimuli at the time of choice have been repeatedly observed in ventromedial prefrontal cortex (vmPFC). Yet it remains unknown how these value representations are computed from sensory and memory representations in more posterior brain regions. We used electroencephalography (EEG) while subjects evaluated appetitive and aversive food items to study how event-related responses modulated by stimulus value evolve over time. We found that value-related activity shifted from posterior to anterior, and from parietal to central to frontal sensors, across three major time windows after stimulus onset: 150–250 ms, 400–550 ms, and 700–800 ms. Exploratory localization of the EEG signal revealed a shifting network of activity moving from sensory and memory structures to areas associated with value coding, with stimulus value activity localized to vmPFC only from 400 ms onwards. Consistent with these results, functional connectivity analyses also showed a causal flow of information from temporal cortex to vmPFC. Thus, although value signals are present as early as 150 ms after stimulus onset, the value signals in vmPFC appear relatively late in the choice process, and seem to reflect the integration of incoming information from sensory and memory related regions

The influence of mood on visual perception of neutral material

In the study we investigated how current mood affects spontaneous perceptual processes of neutral stimuli of low‑arousal, unrelated to any specific task. Two separate but similar procedures were carried out: one using functional magnetic resonance imaging (fMRI), the other using electroencephalography based source localization. In both experiments, sessions of passive viewing of neutral pictures were preceded by either a negative or positive mood induction. In response to neutral stimuli, we observed higher activation of visual areas after positive mood induction and lower activations in medial prefrontal and right frontotemporal regions after negative mood induction. We conclude that in relatively safe laboratory conditions, after being exposed to negative emotional content, automatic processes of affective control are recruited by the prefrontal cortex. This results in attenuation of processing of incoming stimuli, as the stimuli do not carry salient information with respect to bottom‑up or top‑down processes. The observed effects may therefore represent an implicit mechanism of perceptual modulation

Reward feedback stimuli elicit high-beta EEG oscillations in human dorsolateral prefrontal cortex

Reward-related feedback stimuli have been observed to elicit a burst of power in the beta frequency range over frontal areas of the human scalp. Recent discussions have suggested possible neural sources for this activity but there is a paucity of empirical evidence on the question. Here we recorded EEG from participants while they navigated a virtual T-maze to find monetary rewards. Consistent with previous studies, we found that the reward feedback stimuli elicited an increase in beta power (20-30 Hz) over a right-frontal area of the scalp. Source analysis indicated that this signal was produced in the right dorsolateral prefrontal cortex (DLPFC). These findings align with previous observations of reward-related beta oscillations in the DLPFC in non-human primates. We speculate that increased power in the beta frequency range following reward receipt reflects the activation of task-related neural assemblies that encode the stimulus-response mapping in working memory

An introduction to time-resolved decoding analysis for M/EEG

The human brain is constantly processing and integrating information in order to make decisions and interact with the world, for tasks from recognizing a familiar face to playing a game of tennis. These complex cognitive processes require communication between large populations of neurons. The non-invasive neuroimaging methods of electroencephalography (EEG) and magnetoencephalography (MEG) provide population measures of neural activity with millisecond precision that allow us to study the temporal dynamics of cognitive processes. However, multi-sensor M/EEG data is inherently high dimensional, making it difficult to parse important signal from noise. Multivariate pattern analysis (MVPA) or "decoding" methods offer vast potential for understanding high-dimensional M/EEG neural data. MVPA can be used to distinguish between different conditions and map the time courses of various neural processes, from basic sensory processing to high-level cognitive processes. In this chapter, we discuss the practical aspects of performing decoding analyses on M/EEG data as well as the limitations of the method, and then we discuss some applications for understanding representational dynamics in the human brain

Feeling happy enhances early spatial encoding of peripheral information automatically: electrophysiological time-course and neural sources.

Previous research has shown that positive mood may broaden attention, although it remains unclear whether this effect has a perceptual or a postperceptual locus. In this study, we addressed this question using high-density event-related potential methods. We randomly assigned participants to a positive or a neutral mood condition. Then they performed a demanding oddball task at fixation (primary task ensuring fixation) and a localization task of peripheral stimuli shown at three positions in the upper visual field (secondary task) concurrently. While positive mood did not influence behavioral performance for the primary task, it did facilitate stimulus localization on the secondary task. At the electrophysiological level, we found that the amplitude of the C1 component (reflecting an early retinotopic encoding of the stimulus in V1) was enhanced in the positive, as compared with the neutral, mood group. Importantly, this effect appeared to be largely automatic, because it occurred regardless of the task relevance of the peripheral stimulus and prior to top-down gain control effects seen at the level of the subsequent P1 component. This early effect was also observed irrespective of a change of the target-related P300 component (primary task) by positive mood. These results suggest that positive mood can automatically boost the spatial encoding of peripheral stimuli early on following stimulus onset. This effect can eventually underlie the broadening of spatial attention, which has been associated with this specific mood state