Spatial sampling in human visual cortex is modulated by both spatial and feature-based attention

Reliability and validity of a novel attention assessment scale (broken ring enVision search test) in the Chinese population

Background

The correct assessment of attentional function is the key to cognitive research. A new attention assessment scale, the Broken Ring enVision Search Test (BReViS), has not been validated in China. The purpose of this study was to assess the reliability and validity of the BReViS in the Chinese population.

Methods

From July to October 2023, 100 healthy residents of Changzhou were selected and subjected to the BReViS, Digital Cancelation Test (D-CAT), Symbol Digit Modalities Test (SDMT), and Digit Span Test (DST). Thirty individuals were randomly chosen to undergo the BReViS twice for test-retest reliability assessment. Correlation analysis was conducted between age, education level, gender, and various BReViS sub-tests including Selective Attention (SA), Orientation of Attention (OA), Focal Attention (FA), and Total Errors (Err). Intergroup comparisons and multiple linear regression analyses were performed. Additionally, correlation analyses between the BReViS sub-tests and with other attention tests were also analyzed.

Results

The correlation coefficients of the BReViS sub-tests (except for FA) between the two tests were greater than 0.600 (p < 0.001), indicating good test-retest reliability. The Cronbach's alpha coefficient was 0.874, suggesting high internal consistency reliability. SA showed a significant negative correlation with the net score of D-CAT (r = -0.405, p < 0.001), and a significant positive correlation with the error rate of D-CAT (r = 0.401, p < 0.001), demonstrating good criterion-related validity. The correlation analysis among the results of each sub-test showed that the correlation coefficient between SA and Err was 0.532 (p < 0.001), and between OA and Err was-0.229 (p < 0.05), whereas there was no significant correlation between SA, OA, and FA, which indicated that the scale had good informational content validity and structural validity. Both SA and Err were significantly correlated with age and years of education, while gender was significantly correlated with OA and Err. Multiple linear regression suggested that Err was mainly affected by age and gender. There were significant differences in the above indexes among different age, education level and gender groups. Correlation analysis with other attention tests revealed that SA negatively correlated with DST forward and backward scores and SDMT scores. Err positively correlated with D-CAT net scores and negatively with D-CAT error rate, DST forward and backward scores, and SDMT scores. OA and FA showed no significant correlation with other attention tests.

Conclusion

The BReViS test, demonstrating good reliability and validity, assessing not only selective attention but also gauging capacities in immediate memory, information processing speed, visual scanning, and hand-eye coordination. The results are susceptible to demographic variables such as age, gender, and education level.

Are neuronal mechanisms of attention universal across human sensory and motor brain maps?

One's experience of shifting attention from the color to the smell to the act of picking a flower seems like a unitary process applied, at will, to one modality after another. Yet, the unique and separable experiences of sight versus smell versus movement might suggest that the neural mechanisms of attention have been separately optimized to employ each modality to its greatest advantage. Moreover, addressing the issue of universality can be particularly difficult due to a paucity of existing cross-modal comparisons and a dearth of neurophysiological methods that can be applied equally well across disparate modalities. Here we outline some of the conceptual and methodological issues related to this problem and present an instructive example of an experimental approach that can be applied widely throughout the human brain to permit detailed, quantitative comparison of attentional mechanisms across modalities. The ultimate goal is to spur efforts across disciplines to provide a large and varied database of empirical observations that will either support the notion of a universal neural substrate for attention or more clearly identify the degree to which attentional mechanisms are specialized for each modality.

Pitfalls in Post Hoc Analyses of Population Receptive Field Data

Data binning involves grouping observations into bins and calculating bin-wise summary statistics. It can cope with overplotting and noise, making it a versatile tool for comparing many observations. However, data binning goes awry if the same observations are used for binning (selection) and contrasting (selective analysis). This creates circularity, biasing noise components and resulting in artifactual changes in the form of regression towards the mean. Importantly, these artifactual changes are a statistical necessity. Here, we use (null) simulations and empirical repeat data to expose this flaw in the scope of post hoc analyses of population receptive field data. In doing so, we reveal that the type of data analysis, data properties, and circular data cleaning are factors shaping the appearance of such artifactual changes. We furthermore highlight that circular data cleaning and circular sorting of change scores are selection practices that result in artifactual changes even without circular data binning. These pitfalls might have led to erroneous claims about changes in population receptive fields in previous work and can be mitigated by using independent data for selection purposes. Our evaluations highlight the urgency for us researchers to make the validation of analysis pipelines standard practice.

Visual Working Memory Adapts to the Nature of Anticipated Interference

Visual working memory has been proven to be relatively robust against interference. However, little is known on whether such robust coding is obligatory, or can be flexibly recruited depending on its expected usefulness. To address this, participants remembered both the color and orientation of a grating. During the maintenance, we inserted a secondary color/orientation memory task, interfering with the primary task. Crucially, we varied the expectations of the type of interference by varying the probability of the two types of intervening task. Behavioral data indicate that to-be-remembered features for which interference is expected are bolstered, whereas to-be-remembered features for which no interference is expected are left vulnerable. This was further supported by fMRI data obtained from visual cortex. In conclusion, the flexibility of visual working memory allows it to strengthen memories for which it anticipates the highest risk of interference.

A population receptive field model of the magnetoencephalography response

Computational models which predict the neurophysiological response from experimental stimuli have played an important role in human neuroimaging. One type of computational model, the population receptive field (pRF), has been used to describe cortical responses at the millimeter scale using functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG). However, pRF models are not widely used for non-invasive electromagnetic field measurements (EEG/MEG), because individual sensors pool responses originating from several centimeter of cortex, containing neural populations with widely varying spatial tuning. Here, we introduce a forward-modeling approach in which pRFs estimated from fMRI data are used to predict MEG sensor responses. Subjects viewed contrast-reversing bar stimuli sweeping across the visual field in separate fMRI and MEG sessions. Individual subject's pRFs were modeled on the cortical surface at the millimeter scale using the fMRI data. We then predicted cortical time series and projected these predictions to MEG sensors using a biophysical MEG forward model, accounting for the pooling across cortex. We compared the predicted MEG responses to observed visually evoked steady-state responses measured in the MEG session. We found that pRF parameters estimated by fMRI could explain a substantial fraction of the variance in steady-state MEG sensor responses (up to 60% in individual sensors). Control analyses in which we artificially perturbed either pRF size or pRF position reduced MEG prediction accuracy, indicating that MEG data are sensitive to pRF properties derived from fMRI. Our model provides a quantitative approach to link fMRI and MEG measurements, thereby enabling advances in our understanding of spatiotemporal dynamics in human visual field maps.

Visuospatial coding as ubiquitous scaffolding for human cognition

For more than 100 years we have known that the visual field is mapped onto the surface of visual cortex, imposing an inherently spatial reference frame on visual information processing. Recent studies highlight visuospatial coding not only throughout visual cortex, but also brain areas not typically considered visual. Such widespread access to visuospatial coding raises important questions about its role in wider cognitive functioning. Here, we synthesise these recent developments and propose that visuospatial coding scaffolds human cognition by providing a reference frame through which neural computations interface with environmental statistics and task demands via perception-action loops.

Divisive normalization unifies disparate response signatures throughout the human visual hierarchy

A canonical neural computation is a mathematical operation applied by the brain in a wide variety of contexts and capable of explaining and unifying seemingly unrelated neural and perceptual phenomena. Here, we use a combination of state-of-the-art experiments (ultra-high-field functional MRI) and mathematical methods (population receptive field [pRF] modeling) to uniquely demonstrate the role of divisive normalization (DN) as the canonical neural computation underlying visuospatial responses throughout the human visual hierarchy. The DN pRF model provides a tool to investigate and interpret the computational processes underlying neural responses in human and animal recordings, but also in clinical and cognitive dimensions.

Neural processing is hypothesized to apply the same mathematical operations in a variety of contexts, implementing so-called canonical neural computations. Divisive normalization (DN) is considered a prime candidate for a canonical computation. Here, we propose a population receptive field (pRF) model based on DN and evaluate it using ultra-high-field functional MRI (fMRI). The DN model parsimoniously captures seemingly disparate response signatures with a single computation, superseding existing pRF models in both performance and biological plausibility. We observe systematic variations in specific DN model parameters across the visual hierarchy and show how they relate to differences in response modulation and visuospatial information integration. The DN model delivers a unifying framework for visuospatial responses throughout the human visual hierarchy and provides insights into its underlying information-encoding computations. These findings extend the role of DN as a canonical computation to neuronal populations throughout the human visual hierarchy.

Extremely fast pRF mapping for real-time applications

Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity. A major stumbling block for such an application is, however, that the pRF mapping procedure is computationally heavy and time consuming. To address this, we propose a novel and fast pRF mapping procedure that is suitable for real-time applications. The method is built upon hashed-Gaussian encoding of the stimulus, which tremendously reduces computational resources. After the stimulus is encoded, mapping can be performed using either ridge regression for fast offline analyses or gradient descent for real-time applications. We validate our model-agnostic approach in silico, as well as on empirical fMRI data obtained from 3T and 7T MRI scanners. Our approach is capable of estimating receptive fields and their parameters for millions of voxels in mere seconds. This method thus facilitates real-time applications of population receptive field mapping.

Attention selectively enhances stimulus information for surround over foveal stimulus representations in occipital cortex

By attending to part of a visual scene, we can prioritize processing of the most relevant visual information and so use our limited resources effectively. Previous functional magnetic resonance imaging (fMRI) work has shown that attention can increase overall blood-oxygen-level-dependent (BOLD) signal responsiveness but also enhances the stimulus information in terms of classifier performance. Here, we investigate how these effects vary across the visual field. We compare attention-enhanced fMRI-BOLD amplitude responses and classifier accuracy in fovea and surrounding stimulus regions using a set of four simple stimuli subdivided into a foveal region (1.4° diameter) and a surround region (15° diameter). We found dissociations between the effects of attention on average response and in enhancing stimulus information. In early visual cortex, we found that attention increased the amplitude of responses to both foveal and surround parts of the stimuli and increased classifier performance only for the surround stimulus. Conversely, ventral visual areas showed less change in average response but greater changes in decoding. Unlike for early visual cortex, in the ventral visual cortex attention produced similar changes in decoding for center and surround stimuli.

Altered cortical functional network in drug-naive adult male patients with attention-deficit hyperactivity disorder: A resting-state electroencephalographic study

Relatively little is known about the neurophysiology of adult Attention-deficit/hyperactivity disorder (ADHD). Brain network analysis can yield important insights into the neuropathology in adult ADHD. The objective of this study was to investigate source-level cortical functional network using resting-state electroencephalography (EEG) in drug-naive adult patients with ADHD. Resting-state EEG was performed for 30 adult male patients with ADHD and 27 male healthy controls. Source-level weighted functional networks based on graph theory were evaluated, including strength, clustering coefficient (CC) and path length (PL) in six frequency bands. At the global level, strength (η² = 0.167) and CC (η² = 0.156) were lower while PL (η² = 0.159) was higher for the high beta band in the ADHD patient group compared to healthy controls. At the nodal level, CCs of the high beta band were lower in the left middle temporal gyrus (η² = 0.244), right inferior occipital cortex (η² = 0.214), right posterior transverse collateral sulcus (η² = 0.237), and right anterior occipital sulcus (η² = 0.251) for the adult ADHD group. Furthermore, the nodal-level high beta band CCs of the left middle temporal gyrus and right anterior occipital sulcus were significantly negatively correlated with ADHD symptoms. The altered cortical functional network showed inefficient connectivity in the left middle temporal gyrus, belonging to the default mode network, the right inferior occipital cortex, belonging to the extrastriate visual resting state network, the right posterior transverse collateral sulcus, belonging to the visual network, and the anterior occipital sulcus, reflecting visual attention, which might affect the pathophysiology of ADHD. Taken together, these attenuated network inefficiencies in adult patients with ADHD may lead to suboptimal information processing and affect symptoms of ADHD, such as inattention and hyperactivity. Our findings should be further replicated using longitudinal study designs.

Topographic connectivity reveals task-dependent retinotopic processing throughout the human brain

The human visual system is organized as a hierarchy of maps that share the topography of the retina. Known retinotopic maps have been identified using simple visual stimuli under strict fixation, conditions different from everyday vision which is active, dynamic, and complex. This means that it remains unknown how much of the brain is truly visually organized. Here I demonstrate widespread stable visual organization beyond the traditional visual system, in default-mode network and hippocampus. Detailed topographic connectivity with primary visual cortex during movie-watching, resting-state, and retinotopic-mapping experiments revealed that visual-spatial representations throughout the brain are warped by cognitive state. Specifically, traditionally visual regions alternate with default-mode network and hippocampus in preferentially representing the center of the visual field. This visual role of default-mode network and hippocampus would allow these regions to interface between abstract memories and concrete sensory impressions. Together, these results indicate that visual-spatial organization is a fundamental coding principle that structures the communication between distant brain regions.

A neurodynamic model of the interaction between color perception and color memory

The memory color effect and Spanish castle illusion have been taken as evidence of the cognitive penetrability of vision. In the same manner, the successful decoding of color-related brain signals in functional neuroimaging studies suggests the retrieval of memory colors associated with a perceived gray object. Here, we offer an alternative account of these findings based on the design principles of adaptive resonance theory (ART). In ART, conscious perception is a consequence of a resonant state. Resonance emerges in a recurrent cortical circuit when a bottom-up spatial pattern agrees with the top-down expectation. When they do not agree, a special control mechanism is activated that resets the network and clears off erroneous expectation, thus allowing the bottom-up activity to always dominate in perception. We developed a color ART circuit and evaluated its behavior in computer simulations. The model helps to explain how traces of erroneous expectations about incoming color are eventually removed from the color perception, although their transient effect may be visible in behavioral responses or in brain imaging. Our results suggest that the color ART circuit, as a predictive computational system, is almost never penetrable, because it is equipped with computational mechanisms designed to constrain the impact of the top-down predictions on ongoing perceptual processing.

In search of exogenous feature-based attention

Visual attention prioritizes the processing of sensory information at specific spatial locations (spatial attention; SA) or with specific feature values (feature-based attention; FBA). SA is well characterized in terms of behavior, brain activity, and temporal dynamics-for both top-down (endogenous) and bottom-up (exogenous) spatial orienting. FBA has been thoroughly studied in terms of top-down endogenous orienting, but much less is known about the potential of bottom-up exogenous influences of FBA. Here, in four experiments, we adapted a procedure used in two previous studies that reported exogenous FBA effects, with the goal of replicating and expanding on these findings, especially regarding its temporal dynamics. Unlike the two previous studies, we did not find significant effects of exogenous FBA. This was true (1) whether accuracy or RT was prioritized as the main measure, (2) with precues presented peripherally or centrally, (3) with cue-to-stimulus ISIs of varying durations, (4) with four or eight possible target locations, (5) at different meridians, (6) with either brief or long stimulus presentations, (7) and with either fixation contingent or noncontingent stimulus displays. In the last experiment, a postexperiment participant questionnaire indicated that only a small subset of participants, who mistakenly believed the irrelevant color of the precue indicated which stimulus was the target, exhibited benefits for valid exogenous FBA precues. Overall, we conclude that with the protocol used in the studies reporting exogenous FBA, the exogenous stimulus-driven influence of FBA is elusive at best, and that FBA is primarily a top-down, goal-driven process.

Modulating the global orientation bias of the visual system changes population receptive field elongations

The topographical structure of the visual system in individual subjects can be visualized using fMRI. Recently, a radial bias for the long axis of population receptive fields (pRF) has been shown using fMRI. It has been theorized that the elongation of receptive fields pointing toward the fovea results from horizontal local connections bundling orientation selective units mostly parallel to their polar position within the visual field. In order to investigate whether there is a causal relationship between orientation selectivity and pRF elongation the current study employed a global orientation adapter to modulate the orientation bias for the visual system while measuring spatial pRF characteristics. The hypothesis was that the orientation tuning change of neural populations would alter pRF elongations toward the fovea particularly at axial positions parallel and orthogonal to the affected orientation. The results indeed show a different amount of elongation of pRF units and their orientation at parallel and orthogonal axial positions relative to the adapter orientation. Within the lower left hemifield, pRF radial bias and elongation showed an increase during adaptation to a 135° grating while both parameters decreased during the presentation of a 45° adapter stimulus. The lower right visual field showed the reverse pattern. No modulation of the pRF topographies were observed in the upper visual field probably due to a vertical visual field asymmetry of sensitivity toward the low contrast spatial frequency pattern of the adapter stimulus. These data suggest a direct relationship between orientation selectivity and elongation of population units within the visual cortex.

The Importance of Considering Model Choices When Interpreting Results in Computational Neuroimaging

Model-based analyses open exciting opportunities for understanding neural information processing. In a commentary published in eNeuro, Gardner and Liu (2019) discuss the role of model specification in interpreting results derived from complex models of neural data. As a case study, they suggest that one such analysis, the inverted encoding model (IEM), should not be used to assay properties of "stimulus representations" because the ability to apply linear transformations at various stages of the analysis procedure renders results "arbitrary." Here, we argue that the specification of all models is arbitrary to the extent that an experimenter makes choices based on current knowledge of the model system. However, the results derived from any given model, such as the reconstructed channel response profiles obtained from an IEM analysis, are uniquely defined and are arbitrary only in the sense that changes in the model can predictably change results. IEM-based channel response profiles should therefore not be considered arbitrary when the model is clearly specified and guided by our best understanding of neural population representations in the brain regions being analyzed. Intuitions derived from this case study are important to consider when interpreting results from all model-based analyses, which are similarly contingent upon the specification of the models used.

Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches

Unsolved questions in computational visual neuroscience research are whether and how neurons and their connecting cortical networks can adapt when normal vision is compromised by a neurodevelopmental disorder or damage to the visual system. This question on neuroplasticity is particularly relevant in the context of rehabilitation therapies that attempt to overcome limitations or damage, through either perceptual training or retinal and cortical implants. Studies on cortical neuroplasticity have generally made the assumption that neuronal population properties and the resulting visual field maps are stable in healthy observers. Consequently, differences in the estimates of these properties between patients and healthy observers have been taken as a straightforward indication for neuroplasticity. However, recent studies imply that the modeled neuronal properties and the cortical visual maps vary substantially within healthy participants, e.g., in response to specific stimuli or under the influence of cognitive factors such as attention. Although notable advances have been made to improve the reliability of stimulus-driven approaches, the reliance on the visual input remains a challenge for the interpretability of the obtained results. Therefore, we argue that there is an important role in the study of cortical neuroplasticity for approaches that assess intracortical signal processing and circuitry models that can link visual cortex anatomy, function, and dynamics.

Functional MRI and EEG Index Complementary Attentional Modulations

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two noninvasive methods commonly used to study neural mechanisms supporting visual attention in humans. Studies using these tools, which have complementary spatial and temporal resolutions, implicitly assume they index similar underlying neural modulations related to external stimulus and internal attentional manipulations. Accordingly, they are often used interchangeably for constraining understanding about the impact of bottom-up and top-down factors on neural modulations. To test this core assumption, we simultaneously manipulated bottom-up sensory inputs by varying stimulus contrast and top-down cognitive modulations by changing the focus of spatial attention. Each of the male and female subjects participated in both fMRI and EEG sessions performing the same experimental paradigm. We found categorically different patterns of attentional modulation on fMRI activity in early visual cortex and early stimulus-evoked potentials measured via EEG (e.g., the P1 component and steady-state visually-evoked potentials): fMRI activation scaled additively with attention, whereas evoked EEG components scaled multiplicatively with attention. However, across longer time scales, a contralateral negative-going potential and oscillatory EEG signals in the alpha band revealed additive attentional modulation patterns like those observed with fMRI. These results challenge prior assumptions that fMRI and early stimulus-evoked potentials measured with EEG can be interchangeably used to index the same neural mechanisms of attentional modulations at different spatiotemporal scales. Instead, fMRI measures of attentional modulations are more closely linked with later EEG components and alpha-band oscillations. Considered together, hemodynamic and electrophysiological signals can jointly constrain understanding of the neural mechanisms supporting cognition.SIGNIFICANCE STATEMENT fMRI and EEG have been used as tools to measure the location and timing of attentional modulations in visual cortex and are often used interchangeably for constraining computational models under the assumption that they index similar underlying neural processes. However, by varying attentional and stimulus parameters, we found differential patterns of attentional modulations of fMRI activity in early visual cortex and commonly used stimulus-evoked potentials measured via EEG. Instead, across longer time scales, a contralateral negative-going potential and EEG oscillations in the alpha band exhibited attentional modulations similar to those observed with fMRI. Together, these results suggest that different physiological processes assayed by these complementary techniques must be jointly considered when making inferences about the neural underpinnings of cognitive operations.