Activity In Human Visual Cortex Research Articles

Local field potentials, spiking activity, and receptive fields in human visual cortex.

The concept of receptive field (RF) is central to sensory neuroscience. Neuronal RF properties have been substantially studied in animals, while those in humans remain nearly unexplored. Here, we measured neuronal RFs with intracranial local field potentials (LFPs) and spiking activity in human visual cortex (V1/V2/V3). We recorded LFPs via macro-contacts and discovered that RF sizes estimated from low-frequency activity (LFA, 0.5-30 Hz) were larger than those estimated from low-gamma activity (LGA, 30-60 Hz) and high-gamma activity (HGA, 60-150 Hz). We then took a rare opportunity to record LFPs and spiking activity via microwires in V1 simultaneously. We found that RF sizes and temporal profiles measured from LGA and HGA closely matched those from spiking activity. In sum, this study reveals that spiking activity of neurons in human visual cortex could be well approximated by LGA and HGA in RF estimation and temporal profile measurement, implying the pivotal functions of LGA and HGA in early visual information processing.

A cortical zoom-in operation underlies covert shifts of visual spatial attention

Shifting the focus of attention without moving the eyes poses challenges for signal coding in visual cortex in terms of spatial resolution, signal routing, and cross-talk. Little is known how these problems are solved during focus shifts. Here, we analyze the spatiotemporal dynamic of neuromagnetic activity in human visual cortex as a function of the size and number of focus shifts in visual search. We find that large shifts elicit activity modulations progressing from highest (IT) through mid-level (V4) to lowest hierarchical levels (V1). Smaller shifts cause those modulations to start at lower levels in the hierarchy. Successive shifts involve repeated backward progressions through the hierarchy. We conclude that covert focus shifts arise from a cortical coarse-to-fine process progressing from retinotopic areas with larger toward areas with smaller receptive fields. This process localizes the target and increases the spatial resolution of selection, which resolves the above issues of cortical coding.

Early High-Gamma Activity in Human Visual Cortex Increases with Visual Awareness

Early High-Gamma Activity in Human Visual Cortex Increases with Visual Awareness

Task-related activity in human visual cortex

Task-related activity in human visual cortex

Perception and memory have distinct spatial tuning properties in human visual cortex

Reactivation of earlier perceptual activity is thought to underlie long-term memory recall. Despite evidence for this view, it is unclear whether mnemonic activity exhibits the same tuning properties as feedforward perceptual activity. Here, we leverage population receptive field models to parameterize fMRI activity in human visual cortex during spatial memory retrieval. Though retinotopic organization is present during both perception and memory, large systematic differences in tuning are also evident. Whereas there is a three-fold decline in spatial precision from early to late visual areas during perception, this pattern is not observed during memory retrieval. This difference cannot be explained by reduced signal-to-noise or poor performance on memory trials. Instead, by simulating top-down activity in a network model of cortex, we demonstrate that this property is well explained by the hierarchical structure of the visual system. Together, modeling and empirical results suggest that computational constraints imposed by visual system architecture limit the fidelity of memory reactivation in sensory cortex.

Subjective confidence reflects representation of Bayesian probability in cortex.

What gives rise to the human sense of confidence? Here, we tested the Bayesian hypothesis that confidence is based on a probability distribution represented in neural population activity. We implemented several computational models of confidence, and tested their predictions using psychophysics and fMRI. Using a generative model-based fMRI decoding approach, we extracted probability distributions from neural population activity in human visual cortex. We found that subjective confidence tracks the shape of the decoded distribution. That is, when sensory evidence was more precise, as indicated by the decoded distribution, observers reported higher levels of confidence. We furthermore found that neural activity in the insula, anterior cingulate, and prefrontal cortex was linked to both the shape of the decoded distribution and reported confidence, in ways consistent with the Bayesian model. Altogether, our findings support recent statistical theories of confidence and suggest that probabilistic information guides the computation of one’s sense of confidence.

Cortical Reorganization: Reallocated Responses without Rewiring

Summary Is the brain able to reorganise following loss of sensory input? New work on individuals with sight loss shows that, while brain areas normally allocated to vision respond to other sensory stimuli, those responses are unlikely to mean the brain has rewired.

Differential impact of endogenous and exogenous attention on activity in human visual cortex

How do endogenous (voluntary) and exogenous (involuntary) attention modulate activity in visual cortex? Using ROI-based fMRI analysis, we measured fMRI activity for valid and invalid trials (target at cued/un-cued location, respectively), pre- or post-cueing endogenous or exogenous attention, while participants performed the same orientation discrimination task. We found stronger modulation in contralateral than ipsilateral visual regions, and higher activity in valid- than invalid-trials. For endogenous attention, modulation of stimulus-evoked activity due to a pre-cue increased along the visual hierarchy, but was constant due to a post-cue. For exogenous attention, modulation of stimulus-evoked activity due to a pre-cue was constant along the visual hierarchy, but was not modulated due to a post-cue. These findings reveal that endogenous and exogenous attention distinctly modulate activity in visuo-occipital areas during orienting and reorienting; endogenous attention facilitates both the encoding and the readout of visual information whereas exogenous attention only facilitates the encoding of information.

Task-related activity in human visual cortex.

The brain exhibits widespread endogenous responses in the absence of visual stimuli, even at the earliest stages of visual cortical processing. Such responses have been studied in monkeys using optical imaging with a limited field of view over visual cortex. Here, we used functional MRI (fMRI) in human participants to study the link between arousal and endogenous responses in visual cortex. The response that we observed was tightly entrained to task timing, was spatially extensive, and was independent of visual stimulation. We found that this response follows dynamics similar to that of pupil size and heart rate, suggesting that task-related activity is related to arousal. Finally, we found that higher reward increased response amplitude while decreasing its trial-to-trial variability (i.e., the noise). Computational simulations suggest that increased temporal precision underlies both of these observations. Our findings are consistent with optical imaging studies in monkeys and support the notion that arousal increases precision of neural activity.

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.

Activity in human visual areas reflects the precision of motion perception

Any neural representation of a visual stimulus is necessarily uncertain, due to sensory noise and ambiguity in the inputs. Recent advances in fMRI decoding provide a principled approach for estimating the amount of uncertainty in cortical stimulus representations (van Bergen, Ma, Pratte & Jehee, 2015, Nature Neuroscience). However, these previous findings were limited to orientation perception. We here demonstrate that a similar decoding approach can be used to characterize the degree of uncertainty in cortical representations of motion. Participants viewed stimuli consisting of dots that moved coherently into a random direction, while their brain activity was measured with fMRI. Shortly after the dots disappeared from the screen, observers reported the direction of motion. Using a probabilistic analysis approach, we decoded the posterior probability distribution of motion direction from activity in visual areas V1–V4, and hMT+. We found that the decoded posterior distributions were generally bimodal, with two distinct peaks separated by roughly 180 degrees. One peak was reliably larger than the other, and centered on the true direction of stimulus motion. This bimodality suggests that the decoded distributions reflected not only motion, but also orientation information in the patterns of cortical activity. To assess the degree to which the decoded distributions reflected perceptual uncertainty, we computed the entropy of the decoded distributions. We compared this measure of uncertainty with behavioral variability, reasoning that a more precise representation in cortex should result in less variable (more precise) behavior. We found that uncertainty decoded from visual cortex was linked to participant behavior. Specifically, the entropy of the decoded distributions reliably predicted the variability in the observers’ estimates of motion direction. This suggests that the precision of motion perception can be reliably extracted from activity in human visual cortex.

Effects of transcranial direct current stimulation polarity on cortical activity in human visual cortex

Effects of transcranial direct current stimulation polarity on cortical activity in human visual cortex

Dynamics of the cerebral blood flow response to brief neural activity in human visual cortex

The blood oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal depends on an interplay of cerebral blood flow (CBF), oxygen metabolism, and cerebral blood volume. Despite wide usage of BOLD fMRI, it is not clear how these physiological components create the BOLD signal. Here, baseline CBF and its dynamics evoked by a brief stimulus (2 s) in human visual cortex were measured at 3T. We found a stereotypical CBF response: immediate increase, rising to a peak a few second after the stimulus, followed by a significant undershoot. The BOLD hemodynamic response function (HRF) was also measured in the same session. Strong correlations between HRF and CBF peak responses indicate that the flow responses evoked by neural activation in nearby gray matter drive the early HRF. Remarkably, peak CBF and HRF were also strongly modulated by baseline perfusion. The CBF undershoot was reliable and significantly correlated with the HRF undershoot. However, late-time dynamics of the HRF and CBF suggest that oxygen metabolism can also contribute to the HRF undershoot. Combined measurement of the CBF and HRF for brief neural activation is a useful tool to understand the temporal dynamics of neurovascular and neurometabolic coupling.

Pattern matters: Snakes exhibiting triangular and diamond-shaped skin patterns modulate electrophysiological activity in human visual cortex

The neural and perceptual mechanisms that support the efficient visual detection of snakes in humans are still not fully understood. According to the Snake Detection Theory, selection pressures posed by snakes on early primates have shaped the development of the visual system. Previous studies in humans have investigated early visual electrophysiological activity in response to snake images vs. various alternative dangerous or non-dangerous stimuli. These studies have shown that the Early Posterior Negativity (EPN) component is selectively elicited by snake or snake-like images. Recent findings yielded the complementary/alternative hypothesis that early humans (and possibly other primates) evolved an aversion especially for potentially harmful triangular shapes, such as teeth, claws or spikes. In the present study we investigated the effect of triangular and diamond-shaped patterns in snake skins on the ERP correlates of visual processing in humans. In the first experiment, we employed pictures of snakes displaying either triangular/diamond-shaped patterns or no particular pattern on their skins, and pictures of frogs as control. Participants observed a random visual presentation of these pictures. Consistent with previous studies, snakes elicited an enhanced negativity between 225 and 300 ms (EPN) compared to frogs. However, snakes featuring triangular/diamond-shaped patterns on their skin produced an enhanced EPN compared to the snakes that did not display such patterns. In a second experiment we used pictures displaying only skin patterns of snakes and frogs. Results from the second experiment confirmed the results of the first experiment, suggesting that triangular snake-skin patterns modulate the activity in human visual cortex. Taken together, our results constitute an important contribution to the snake detection theory.

Neural activity in human visual cortex is transformed by learning real world size

The way that our brain processes visual information is directly affected by our experience. Repeated exposure to a visual stimulus triggers experience-dependent plasticity in the visual cortex of many species. Humans also have the unique ability to acquire visual knowledge through instruction. We introduced human participants to the real-world size of previously unfamiliar species, and to the functional motion of novel tools, during a functional magnetic resonance imaging scan. Using machine learning, we compared activity patterns evoked by images of the new items, before and after participants learned the animals' real-world size or tools' motion. We found that, after acquiring size information, participants' visual activity patterns for the new animals became more confusable with activity patterns evoked by similar-sized known animals in early visual cortex, but not in ventral temporal cortex, reflecting an influence of new size knowledge on posterior, but not anterior, components of the ventral stream. In contrast, learning the functional motion of new tools did not lead to an equivalent change in recorded activity. Finally, the time-points marked by evidence of new size information in early visual cortex were more likely to show size information and greater activation in the right angular gyrus, a key hub of semantic knowledge and spatial cognition. Overall, these findings suggest that learning an item's real-world size by instruction influences subsequent activity in visual cortex and in a region that is central to semantic and spatial brain systems.

Ultrafast Cortical Gain Adaptation in the Human Brain by Trial-To-Trial Changes of Associative Strength in Fear Learning.

In fear conditioning, more efficient sensory processing of a stimulus (the conditioned stimulus, CS) that has acquired motivational relevance by being paired with an aversive event (the unconditioned stimulus, US) has been associated with increased cortical gain in early sensory brain areas (Miskovic and Keil, 2012). Further, this sensory gain modulation related to short-term plasticity changes occurs independently of aware cognitive anticipation of the aversive US, pointing toward implicit learning mechanisms (Moratti and Keil, 2009). However, it is unknown how quickly the implicit learning of CS-US associations results in the adaptation of cortical gain. Here, using steady-state visually evoked fields derived from human Magnetoencephalography (MEG) recordings in two experiments (N = 33, 17 females and 16 males), we show that stimulus-driven neuromagnetic oscillatory activity increases and decreases quickly as a function of associative strength within three or four trials, as predicted by a computationally implemented Rescorla-Wagner model with the highest learning rate. These ultrafast cortical gain adaptations are restricted to early visual cortex using a delay fear conditioning procedure. Short interval (500 ms) trace conditioning resulted in the same ultrafast activity modulations by associative strength, but in a complex occipito-parieto-temporo-frontal network. Granger causal analysis revealed that reverberating top-down and bottom-up influences between anterior and posterior brain regions during trace conditioning characterized this network. Critically, in both delay and trace conditioning, ultrafast cortical gain modulations as a function of associative strength occurred independently of conscious US anticipation.SIGNIFICANCE STATEMENT In ever-changing environments, learned associations between a cue and an aversive consequence must change under new stimulus-consequence contingencies to be adaptive. What predicts potential dangers now might be meaningless in the next situation. Predictive cues are prioritized, as reflected by increased sensory cortex activity for these cues. However, this modulation also must adapt to altered stimulus-consequence contingencies. Here, we show that human visual cortex activity can be modulated quickly according to ultrafast contingency changes within a few learning trials. This finding extends to frontal brain regions when the cue and the aversive event are separated in time. Critically, this ultrafast updating process occurs orthogonally to aware aversive outcome anticipation and therefore relies on unconscious implicit learning mechanisms.

Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex

Recent advances in the field of artificial intelligence have revealed principles about neural processing, in particular about vision. Previous work demonstrated a direct correspondence between the hierarchy of the human visual areas and layers of deep convolutional neural networks (DCNN) trained on visual object recognition. We use DCNN to investigate which frequency bands correlate with feature transformations of increasing complexity along the ventral visual pathway. By capitalizing on intracranial depth recordings from 100 patients we assess the alignment between the DCNN and signals at different frequency bands. We find that gamma activity (30–70 Hz) matches the increasing complexity of visual feature representations in DCNN. These findings show that the activity of the DCNN captures the essential characteristics of biological object recognition not only in space and time, but also in the frequency domain. These results demonstrate the potential that artificial intelligence algorithms have in advancing our understanding of the brain.

Endogenous modulation of human visual cortex activity improves perception at twilight

Perception, particularly in the visual domain, is drastically influenced by rhythmic changes in ambient lighting conditions. Anticipation of daylight changes by the circadian system is critical for survival. However, the neural bases of time-of-day-dependent modulation in human perception are not yet understood. We used fMRI to study brain dynamics during resting-state and close-to-threshold visual perception repeatedly at six times of the day. Here we report that resting-state signal variance drops endogenously at times coinciding with dawn and dusk, notably in sensory cortices only. In parallel, perception-related signal variance in visual cortices decreases and correlates negatively with detection performance, identifying an anticipatory mechanism that compensates for the deteriorated visual signal quality at dawn and dusk. Generally, our findings imply that decreases in spontaneous neural activity improve close-to-threshold perception.

Decoupling of BOLD amplitude and pattern classification of orientation-selective activity in human visual cortex

Multivariate pattern analysis (MVPA) of fMRI data has allowed the investigation of neural representations of stimuli on the basis of distributed patterns of activity within a brain region, independently from overall brain activity. For instance, several studies on early visual cortex have reported reliable MVPA decoding of the identity of a stimulus representation that was kept in working memory or internally generated, despite the fact that the overall BOLD response was low or even at baseline levels. Here we ask how it is possible that reliable stimulus information can be decoded from early visual cortex even when the overall BOLD signal remains low. We reanalyzed a data set in which human participants (N = 24) imagined or kept in working memory an oriented visual grating. We divided voxels from V1, V2, and V3 into groups based on orientation preference, and compared the time course of mean BOLD responses to preferred and non-preferred orientations with the time course of the multivariate decoding performance.Decoding accuracy related to a numerically small, but reliable univariate difference in the mean BOLD response to preferred and non-preferred stimuli. The time course of the difference in BOLD responses to preferred and non-preferred orientations was highly similar to the time course of the multivariate pattern classification accuracy. The reliability of the classification strongly correlated with the magnitude of differences in BOLD signal between preferred and non-preferred stimuli. These activity differences were small compared to the large overall BOLD modulations. This suggests that a substantial part of the task-related BOLD response to visual stimulation might not be stimulus-specific. Rather, stimulus-evoked BOLD signals in early visual cortex during a task context may be an amalgam of small stimulus-specific responses and large task-related but non-stimulus-specific responses. The latter are not evident during the maintenance or internal generation of stimulus representations, but provide an explanation of how reliable stimulus information can be decoded from early visual cortex even though its overall BOLD signal remains low.

Decorrelated Input Dissociates Narrow Band γ Power and BOLD in Human Visual Cortex.

Although fMRI using the BOLD contrast is widely used for noninvasively mapping hemodynamic brain activity in humans, its exact link to underlying neural processing is poorly understood. Whereas some studies have reported that BOLD signals measured in visual cortex are tightly linked to neural activity in the narrow band γ (NBG) range, others have found a weak correlation between the two. To elucidate the mechanisms behind these conflicting findings, we hypothesized that BOLD reflects the strength of synaptic inputs to cortex, whereas NBG is more dependent on how well these inputs are correlated. To test this, we measured NBG, BOLD, and cerebral blood flow responses to stimuli that either correlate or decorrelate neural activity in human visual cortex. Next, we simulated a recurrent network model of excitatory and inhibitory neurons that reproduced in detail the experimental NBG and BOLD data. Results show that the visually evoked BOLD response was solely predicted by the sum of local inputs, whereas NBG was critically dependent on how well these inputs were correlated. In summary, the NBG-BOLD relationship strongly depends on the nature of sensory input to cortex: stimuli that increase the number of correlated inputs to visual cortex will increase NBG and BOLD in a similar manner, whereas stimuli that increase the number of decorrelated inputs will dissociate the two. The NBG-BOLD relationship is therefore not fixed but is rather highly dependent on input correlations that are both stimulus- and state-dependent.SIGNIFICANCE STATEMENT It is widely believed that γ oscillations in cortex are tightly linked to local hemodynamic activity. Here, we present experimental evidence showing how a stimulus can increase local blood flow to the brain despite suppressing γ power. Moreover, using a sophisticated model of cortical neurons, it is proposed that this occurs when synaptic input to cortex is strong yet decorrelated. Because input correlations are largely determined by the state of the brain, our results demonstrate that the relationship between γ and local hemodynamics is not fixed, but rather context dependent. This likely explains why certain neurodevelopmental disorders are characterized by weak γ activity despite showing normal blood flow.