Selective attention gates visual processing in the extrastriate cortex

Background white noise increases neuronal activity by reducing membrane fluctuations and slow-wave oscillations in auditory cortex

The brain faces the challenging task of preserving a consistent portrayal of the external world in the face of disruptive sensory inputs. What alterations occur in sensory representation amidst noise, and how does brain activity adapt to it? Although it has previously been shown that background white noise (WN) decreases responses to salient sounds, a mechanistic understanding of the brain processes responsible for such changes is lacking. We investigated the effect of background WN on neuronal spiking activity, membrane potential, and network oscillations in the mouse central auditory system. We found that, in addition to increasing background spiking activity in the auditory cortex and thalamus, background WN decreases neural activity fluctuations, as reflected in the membrane potential of single neurons and the local field potential. Blocking acetylcholine signaling in the auditory cortex eliminated the WN-dependent increase in background activity as well as the shift in slow-wave oscillations. Together, our observations show that background WN is not filtered away along the auditory pathway, but rather drives sustained changes in cortical activity that can be reverted by blocking cholinergic inputs.

Prefrontal working memory signal controls phase-coded information within extrastriate cortex

In order to understand how prefrontal cortex provides the benefits of working memory (WM) for visual processing we examined the influence of WM on the representation of visual signals in V4 neurons in two macaque monkeys. We found that WM induces strong β oscillations in V4 and that the timing of action potentials relative to this oscillation reflects sensory information- i.e., a phase coding of visual information. Pharmacologically inactivating the Frontal Eye Field part of prefrontal cortex, we confirmed the necessity of prefrontal signals for the WM-driven boost in phase coding of visual information. Indeed, changes in the average firing rate of V4 neurons were correlated with WM-induced oscillatory changes. We present a network model to describe how WM signals can recruit sensory areas by inducing oscillations within these areas and discuss the implications of these findings for a sensory recruitment theory of WM through coherence.

Using N2pc variability to probe functionality: Linear mixed modelling of trial EEG and behaviour

This paper has two concurrent goals. On one hand, we hope it will serve as a simple primer in the use of linear mixed modelling (LMM) for inferential statistical analysis of multimodal data. We describe how LMM can be easily adopted for the identification of trial-wise relationships between disparate measures and provide a brief cookbook for assessing the suitability of LMM in your analyses. On the other hand, this paper is an empirical report, probing how trial-wise variance in the N2pc, and specifically its sub-component the NT, can be predicted by manual reaction time (RT) and stimuli parameters. Extant work has identified a link between N2pc and RT that has been interpreted as evidence of a direct and causative relationship. However, results have left open the less-interesting possibility that the measures covary as a function of motivation or arousal. Using LMM, we demonstrate that the relationship only emerges when the NT is elicited by targets, not distractors, suggesting a discrete and functional relationship. In other analyses, we find that the target-elicited NT is sensitive to variance in distractor identity even when the distractor cannot itself elicit consistently lateralized brain activity. The NT thus appears closely linked to attentional target processing, supporting the propagation of target-related information to response preparation and execution. At the same time, we find that this component is sensitive to distractor interference, which leaves open the possibility that NT reflects brain activity responsible for the suppression of irrelevant distractor information.

Construction and use of mental models: Organizing principles for the science of brain and mind

As an organizing framework for questions of mind and brain, I discuss how the brain builds and uses mental models. Mental models provide a complex, structured description of some situation in the world. The role of perception is to build such a model for the current environment; knowledge provides many of the building blocks; in episodic memory, a previous model is reinstated; in cognitive control, the model dictates a choice of action. A model, I suggest, is a compositional, whole brain state, combining information from multiple specialised brain systems into a structured description of entities in the model and their roles and relationships. The default mode network may play an organizational role as parts of a model are combined into a broader whole. The model combines an active attentional foreground with a more extensive, latent background. Foreground is based on active neural firing, orchestrated by the brain's multiple demand network. Background may also include low-intensity neural activity, but with a substantial contribution from both faster and slower aspects of synaptic change. Interplay between foreground and background underlies core aspects of cognition, including cognitive control, problem solving, abstraction, and learning. Together, these proposals suggest how integrated, whole-brain functions build mental models, providing a unifying framework for the diverse concerns of cognitive neuroscience.

Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications

The concept of modularity in neuropsychology remains a topic of significant debate, especially when considering complex, non-innate, hyper-learned, and adaptable modular systems. This paper critically examines the evolution of cognitive modularity, addressing the challenges of integrating foundational theories with recent empirical and theoretical developments. We begin by analyzing the contributions of Sternberg and Fodor, whose foundational work established the concept of specialized, encapsulated modules within cognitive processes, particularly in the domains of perception and language. Building on this, we explore Carruthers' theory of massive modularity, which extends the modular framework to broader cognitive functions, though we reject its application to central amodal systems, which are overarching and resistant to modularization. We also evaluate recent discoveries, such as mirror neurons and the neural reuse hypothesis, and their implications for traditional modularity models. Furthermore, we investigate the dynamic interactions between the Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN), highlighting their roles in shifting between automatic and controlled states. This exploration refines existing theoretical models, distinguishing innate systems, genetically predisposed ones, and those hyper-learned through working memory, as exemplified by the three-level model of Moscovitch and Umiltà. We address the blurred boundary between domain-specific and domain-general systems, proposing modular versus non-modular states-indexed by automaticity and mandatoriness-as key discriminators. This systematization, supported by empirical literature and our own research, provides a more stable framework for understanding modular systems, avoiding interpretive confusion across varying levels of complexity. These insights advance both theoretical understanding and practical applications in cognitive science.

Modulating synaptic plasticity with metal-organic framework for information-filterable artificial retina

Neuroprosthetics equipped with artificial synapses hold promise to address some most intricate medical problems, such as human sensory disorders. Yet, it is necessitated and of paramount importance for neuroprosthetics to be able to differentiate significant and insignificant signals. Here, we present an information-filterable artificial retina system that integrates artificial synapses with a signal-integration device for signal perception and processing with attention. The synaptic weight modulation is rendered through metal-organic framework (MOF) layers, where distinct short-term and long-term properties are predominantly determined by MOF's pore diameter and functionality. Specifically, four types of isoreticular Zr-based MOFs that share Zr6O4(OH)4 secondary building units have been systematically examined. It is demonstrated that small pore diameters enhance short-term properties, while large pores, which are characterized by increased ion affinity, sustain long-term properties. Moreover, we demonstrated a 6 × 6 pixel artificial retina by incorporating both short-term and long-term artificial synapses with a signal-integration device. Signal summation by the signal-integration device enables attention-based information processing. The information-filterable artificial retina system developed here emulates human perception processes and holds promise in the fields of neuroprosthetics and advanced artificial intelligence.

Attention modulates human visual responses to objects by tuning sharpening

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars, and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias toward the target is not fixed but decreases with increasing target-distractor similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for the behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

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.

Attentional modulation of secondary somatosensory and visual thalamus of mice

Each sensory modality has its own primary and secondary thalamic nuclei. While the primary thalamic nuclei are well understood to relay sensory information from the periphery to the cortex, the role of secondary sensory nuclei is elusive. We trained head-fixed mice to attend to one sensory modality while ignoring a second modality, namely to attend to touch and ignore vision, or vice versa. Arrays were used to record simultaneously from the secondary somatosensory thalamus (POm) and secondary visual thalamus (LP). In mice trained to respond to tactile stimuli and ignore visual stimuli, POm was robustly activated by touch and largely unresponsive to visual stimuli. A different pattern was observed when mice were trained to respond to visual stimuli and ignore touch, with POm now more robustly activated during visual trials. This POm activity was not explained by differences in movements (i.e. whisking, licking, pupil dilation) resulting from the two tasks. Post hoc histological reconstruction of array tracks through POm revealed that subregions varied in their degree of plasticity. LP exhibited similar phenomena. We conclude that behavioral training reshapes activity in secondary thalamic nuclei. Secondary nuclei respond to the same behaviorally relevant, reward-predicting stimuli regardless of stimulus modality.

Brain state and cortical layer-specific mechanisms underlying perception at threshold

Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell class-specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger on hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.

Attentional modulation of secondary somatosensory and visual thalamus of mice

Each sensory modality has its own primary and secondary thalamic nuclei. While the primary thalamic nuclei are well understood to relay sensory information from the periphery to the cortex, the role of secondary sensory nuclei is elusive. We trained head-fixed mice to ateend to one sensory modality while ignoring a second modality, namely to ateend to touch and ignore vision, or vice versa. Arrays were used to record simultaneously from secondary somatosensory thalamus (POm) and secondary visual thalamus (LP). In mice trained to respond to tactile stimuli and ignore visual stimuli, POm was robustly activated by touch and largely unresponsive to visual stimuli. A different pateern was observed when mice were trained to respond to visual stimuli and ignore touch, with POm now more robustly activated during visual trials. This POm activity was not explained by differences in movements (i.e., whisking, licking, pupil dilation) resulting from the two tasks. Post hoc histological reconstruction of array tracks through POm revealed that subregions varied in their degree of plasticity. LP exhibited similar phenomena. We conclude that behavioral training reshapes activity in secondary thalamic nuclei. Secondary nuclei respond to the same behaviorally relevant, reward-predicting stimuli regardless of stimulus modality.

Directing Attention Shapes Learning in Adults but Not Children

Children sometimes learn distracting information better than adults do, perhaps because of the development of selective attention. To understand this potential link, we ask how the learning of children (aged 7-9 years) and the learning of adults differ when information is the directed focus of attention versus when it is not. Participants viewed drawings of common objects and were told to attend to the drawings (Experiment 1: 42 children, 35 adults) or indicate when shapes (overlaid on the drawings) repeated (Experiment 2: 53 children, 60 adults). Afterward, participants identified fragments of these drawings as quickly as possible. Adults learned better than children when directed to attend to the drawings; however, when drawings were task irrelevant, children showed better learning than adults in the first half of the test. And although directing attention to the drawings improved learning in adults, children learned the drawings similarly across experiments regardless of whether the drawings were the focus of the task or entirely irrelevant.

Attention Modulates Human Visual Responses to Objects by Tuning Sharpening

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias towards the target is not fixed but decreases with increasing target-distractor similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

Oscillations in an artificial neural network convert competing inputs into a temporal code

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems.

Correlated variability and its attentional modulation depend on anatomical connectivity

Visual cortical neurons show variability in their responses to repeated presentations of a stimulus and a portion of this variability is shared across neurons. Attention may enhance visual perception by reducing shared spiking variability. However, shared variability and its attentional modulation are not consistent within or across cortical areas, and depend on additional factors such as neuronal type. A critical factor that has not been tested is actual anatomical connectivity. We measured spike count correlations among pairs of simultaneously recorded neurons in the primary visual cortex (V1) for which anatomical connectivity was inferred from spiking cross-correlations. Neurons were recorded in monkeys performing a contrast-change discrimination task requiring covert shifts in visual spatial attention. Accordingly, spike count correlations were compared across trials in which attention was directed toward or away from the visual stimulus overlapping recorded neuronal receptive fields. Consistent with prior findings, attention did not significantly alter spike count correlations among random pairings of unconnected V1 neurons. However, V1 neurons connected via excitatory synapses showed a significant reduction in spike count correlations with attention. Interestingly, V1 neurons connected via inhibitory synapses demonstrated high spike count correlations overall that were not modulated by attention. Correlated variability in excitatory circuits also depended upon neuronal tuning for contrast, the task-relevant stimulus feature. These results indicate that shared variability depends on the type of connectivity in neuronal circuits. Also, attention significantly reduces shared variability in excitatory circuits, even when attention effects on randomly sampled neurons within the same area are weak.

Adaptation of the inferior temporal neurons and efficient visual processing

Numerous studies examining the responses of individual neurons in the inferior temporal (IT) cortex have revealed their characteristics such as two-dimensional or three-dimensional shape tuning, objects, or category selectivity. While these basic selectivities have been studied assuming that their response to stimuli is relatively stable, physiological experiments have revealed that the responsiveness of IT neurons also depends on visual experience. The activity changes of IT neurons occur over various time ranges; among these, repetition suppression (RS), in particular, is robustly observed in IT neurons without any behavioral or task constraints. I observed a similar phenomenon in the ventral visual neurons in macaque monkeys while they engaged in free viewing and actively fixated on one consistent object multiple times. This observation indicates that the phenomenon also occurs in natural situations during which the subject actively views stimuli without forced fixation, suggesting that this phenomenon is an everyday occurrence and widespread across regions of the visual system, making it a default process for visual neurons. Such short-term activity modulation may be a key to understanding the visual system; however, the circuit mechanism and the biological significance of RS remain unclear. Thus, in this review, I summarize the observed modulation types in IT neurons and the known properties of RS. Subsequently, I discuss adaptation in vision, including concepts such as efficient and predictive coding, as well as the relationship between adaptation and psychophysical aftereffects. Finally, I discuss some conceptual implications of this phenomenon as well as the circuit mechanisms and the models that may explain adaptation as a fundamental aspect of visual processing.

Modulation of alpha oscillations by attention is predicted by hemispheric asymmetry of subcortical regions

Evidence suggests that subcortical structures play a role in high-level cognitive functions such as the allocation of spatial attention. While there is abundant evidence in humans for posterior alpha band oscillations being modulated by spatial attention, little is known about how subcortical regions contribute to these oscillatory modulations, particularly under varying conditions of cognitive challenge. In this study, we combined MEG and structural MRI data to investigate the role of subcortical structures in controlling the allocation of attentional resources by employing a cued spatial attention paradigm with varying levels of perceptual load. We asked whether hemispheric lateralization of volumetric measures of the thalamus and basal ganglia predicted the hemispheric modulation of alpha-band power. Lateral asymmetry of the globus pallidus, caudate nucleus, and thalamus predicted attention-related modulations of posterior alpha oscillations. When the perceptual load was applied to the target and the distractor was salient caudate nucleus asymmetry predicted alpha-band modulations. Globus pallidus was predictive of alpha-band modulations when either the target had a high load, or the distractor was salient, but not both. Finally, the asymmetry of the thalamus predicted alpha band modulation when neither component of the task was perceptually demanding. In addition to delivering new insight into the subcortical circuity controlling alpha oscillations with spatial attention, our finding might also have clinical applications. We provide a framework that could be followed for detecting how structural changes in subcortical regions that are associated with neurological disorders can be reflected in the modulation of oscillatory brain activity.

Locus coeruleus norepinephrine contributes to visual-spatial attention by selectively enhancing perceptual sensitivity

Selectively focusing on a behaviorally relevant stimulus while ignoring irrelevant stimuli improves perception. Enhanced neuronal response gain is thought to support attention-related improvements in detection and discrimination. However, understanding of the neuronal pathways regulating perceptual sensitivity remains limited. Here, we report that responses of norepinephrine (NE) neurons in the locus coeruleus (LC) of non-human primates to behaviorally relevant sensory stimuli promote visual discrimination in a spatially selective way. LC-NE neurons spike in response to a visual stimulus appearing in the contralateral hemifield only when that stimulus is attended. This spiking is associated with enhanced behavioral sensitivity, is independent of motor control, and is absent on error trials. Furthermore, optogenetically activating LC-NE neurons selectively improves monkeys' contralateral stimulus detection without affecting motor criteria, supporting NE's causal role in granular cognitive control of selective attention at a cellular level, beyond its known diffuse and non-selective functions.

Differential cortical and subcortical visual processing with eyes shut

Closing our eyes largely shuts down our ability to see. That said, our eyelids still pass some light, allowing our visual system to coarsely process information about visual scenes, such as changes in luminance. However, the specific impact of eye closure on processing within the early visual system remains largely unknown. To understand how visual processing is modulated when eyes are shut, we used functional magnetic resonance imaging (fMRI) to measure responses to a flickering visual stimulus at high (100%) and low (10%) temporal contrasts, while participants viewed the stimuli with their eyes open or closed. Interestingly, we discovered that eye closure produced a qualitatively distinct pattern of effects across the visual thalamus and visual cortex. We found that with eyes open, low temporal contrast stimuli produced smaller responses across the lateral geniculate nucleus (LGN), primary (V1) and extrastriate visual cortex (V2). However, with eyes closed, we discovered that the LGN and V1 maintained similar blood oxygenation level-dependent (BOLD) responses as the eyes open condition, despite the suppressed visual input through the eyelid. In contrast, V2 and V3 had strongly attenuated BOLD response when eyes were closed, regardless of temporal contrast. Our findings reveal a qualitatively distinct pattern of visual processing when the eyes are closed-one that is not simply an overall attenuation but rather reflects distinct responses across visual thalamocortical networks, wherein the earliest stages of processing preserve information about stimuli but are then gated off downstream in visual cortex.NEW & NOTEWORTHY When we close our eyes coarse luminance information is still accessible by the visual system. Using functional magnetic resonance imaging, we examined whether eyelid closure plays a unique role in visual processing. We discovered that while the LGN and V1 show equivalent responses when the eyes are open or closed, extrastriate cortex exhibited attenuated responses with eye closure. This suggests that when the eyes are closed, downstream visual processing is blind to this information.

Proactive selective attention across competition contexts

Selective attention is a cognitive function that helps filter out unwanted information. Theories such as the biased competition model (Desimone & Duncan, 1995) explain how attentional templates bias processing towards targets in contexts where multiple stimuli compete for resources. However, it is unclear how the anticipation of different levels of competition influences the nature of attentional templates, in a proactive fashion. In this study, we used electroencephalography (EEG) to investigate how the anticipated demands of attentional selection (either high or low stimuli competition contexts) modulate target-specific preparatory brain activity and its relationship with task performance. To do so, participants performed a sex/gender judgment task in a cue-target paradigm where, depending on the block, target and distractor stimuli appeared simultaneously (high competition) or sequentially (low competition). Multivariate Pattern Analysis (MVPA) showed that, in both competition contexts, there was a preactivation of the target category to select, with a ramping-up profile at the end of the preparatory interval. However, cross-classification showed no generalization across competition conditions, suggesting different preparatory formats. Notably, time-frequency analyses showed differences between anticipated competition demands, with higher theta band power for high than low competition, which mediated the impact of subsequent stimuli competition on behavioral performance. Overall, our results show that, whereas preactivation of the internal templates associated with the category to select are engaged in advance in high and low competition contexts, their underlying neural patterns differ. In addition, these codes could not be associated with theta power, suggesting that they reflect different preparatory processes. The implications of these findings are crucial to increase our understanding of the nature of top-down processes across different contexts.

Brain-state mediated modulation of inter-laminar dependencies in visual cortex

Spatial attention is critical for recognizing behaviorally relevant objects in a cluttered environment. How the deployment of spatial attention aids the hierarchical computations of object recognition remains unclear. We investigated this in the laminar cortical network of visual area V4, an area strongly modulated by attention. We found that deployment of attention strengthened unique dependencies in neural activity across cortical layers. On the other hand, shared dependencies were reduced within the excitatory population of a layer. Surprisingly, attention strengthened unique dependencies within a laminar population. Crucially, these modulation patterns were also observed during successful behavioral outcomes that are thought to be mediated by internal brain state fluctuations. Successful behavioral outcomes were also associated with phases of reduced neural excitability, suggesting a mechanism for enhanced information transfer during optimal states. Our results suggest common computation goals of optimal sensory states that are attained by either task demands or internal fluctuations.

Attention spotlight in V1-based cortico-cortical interactions in human visual hierarchy

Attention is often viewed as a mental spotlight, which can be scaled like a zoom lens at specific spatial locations and features a center-surround gradient. Here, we demonstrate a neural signature of attention spotlight in signal transmission along the visual hierarchy. fMRI background connectivity analysis was performed between retinotopic V1 and downstream areas to characterize the spatial distribution of inter-areal interaction under two attentional states. We found that, compared to diffused attention, focal attention sharpened the spatial gradient in the strength of the background connectivity. Dynamic causal modeling analysis further revealed the effect of attention in both the feedback and feedforward connectivity between V1 and extrastriate cortex. In a context which induced a strong effect of crowding, the effect of attention in the background connectivity profile diminished. Our findings reveal a context-dependent attention prioritization in information transmission via modulating the recurrent processing across the early stages in human visual cortex.

Early Electrophysiological Correlates of Perceptual Consciousness Are Affected by Both Exogenous and Endogenous Attention

It has been proposed that visual awareness negativity (VAN), which is an early ERP component, constitutes a neural correlate of visual consciousness that is independent of perceptual and cognitive mechanisms. In the present study, we investigated whether VAN is indeed a specific marker of phenomenal awareness or rather reflects the involvement of attention. To this end, we reanalyzed data collected in a previously published EEG experiment in which awareness of visual stimuli and two aspects that define attentional involvement, namely, the inherent saliency and task relevance of a stimulus, were manipulated orthogonally. During the experimental procedure, participants (n = 41) were presented with images of faces that were backward-masked or unmasked, fearful or neutral, and defined as task-relevant targets or task-irrelevant distractors. Single-trial ERP analysis revealed that VAN was highly dependent on attentional manipulations in the early time window (140-200 msec), up to the point that the effect of awareness was not observed for attentionally irrelevant stimuli (i.e., neutral faces presented as distractors). In the late time window (200-350 msec), VAN was present in all attentional conditions, but its amplitude was significantly higher in response to fearful faces and task-relevant face images than in response to neutral ones and task-irrelevant ones, respectively. In conclusion, we demonstrate that the amplitude of VAN is highly dependent on both exogenous (stimulus saliency) and endogenous attention (task requirements). Our results challenge the view that VAN constitutes an attention-independent correlate of phenomenal awareness.

Orienting role of the putative human posterior infero-temporal area in visual attention

The dorsal attention network (DAN) is a network of brain regions essential for attentional orienting, which includes the lateral intraparietal area (LIP) and frontal eye field (FEF). Recently, the putative human dorsal posterior infero-temporal area (phPITd) has been identified as a new node of the DAN. However, its functional relationship with other areas of the DAN and its specific role in visual attention remained unclear. In this study, we analyzed a large publicly available neuroimaging dataset to investigate the intrinsic functional connectivities (FCs) of the phPITd with other brain areas. The results showed that the intrinsic FCs of the phPITd with the areas of the visual network and the DAN were significantly stronger than those with the ventral attention network (VAN) areas and areas of other networks. We further conducted individual difference analyses with a sample size of 295 participants and a series of attentional tasks to investigate which attentional components each phPITd-based DAN edge predicts. Our findings revealed that the intrinsic FC of the left phPITd with the LIPv could predict individual ability in attentional orienting, but not in alerting, executive control, and distractor suppression. Our results not only provide direct evidence of the phPITd's functional relationship with the LIPv, but also offer a comprehensive understanding of its specific role in visual attention.

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip

By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms to help neuromorphic computing achieve energy advantages is a fundamental issue. This work presents an application-oriented algorithm-software-hardware co-designed neuromorphic system for this issue. First, we design and fabricate an asynchronous chip called "Speck", a sensing-computing neuromorphic system on chip. With the low processor resting power of 0.42mW, Speck can satisfy the hardware requirements of dynamic computing: no-input consumes no energy. Second, we uncover the "dynamic imbalance" in spiking neural networks and develop an attention-based framework for achieving the algorithmic requirements of dynamic computing: varied inputs consume energy with large variance. Together, we demonstrate a neuromorphic system with real-time power as low as 0.70mW. This work exhibits the promising potentials of neuromorphic computing with its asynchronous event-driven, sparse, and dynamic nature.

Neural evidence for attentional capture by salient distractors

Salient objects often capture our attention, serving as distractors and hindering our current goals. It remains unclear when and how salient distractors interact with our goals, and our knowledge on the neural mechanisms responsible for attentional capture is limited to a few brain regions recorded from non-human primates. Here we conducted a multivariate analysis on human intracranial signals covering most brain regions and successfully dissociated distractor-specific representations from target-arousal signals in the high-frequency (60-100 Hz) activity. We found that salient distractors were processed rapidly around 220 ms, while target-tuning attention was attenuated simultaneously, supporting initial capture by distractors. Notably, neuronal activity specific to the distractor representation was strongest in the superior and middle temporal gyrus, amygdala and anterior cingulate cortex, while there were smaller contributions from the parietal and frontal cortices. These results provide neural evidence for attentional capture by salient distractors engaging a much larger network than previously appreciated.

Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates

Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.

The influence of cortical activity on perception depends on behavioral state and sensory context

The mechanistic link between neural circuit activity and behavior remains unclear. While manipulating cortical activity can bias certain behaviors and elicit artificial percepts, some tasks can still be solved when cortex is silenced or removed. Here, mice were trained to perform a visual detection task during which we selectively targeted groups of visually responsive and co-tuned neurons in L2/3 of primary visual cortex (V1) for two-photon photostimulation. The influence of photostimulation was conditional on two key factors: the behavioral state of the animal and the contrast of the visual stimulus. The detection of low-contrast stimuli was enhanced by photostimulation, while the detection of high-contrast stimuli was suppressed, but crucially, only when mice were highly engaged in the task. When mice were less engaged, our manipulations of cortical activity had no effect on behavior. The behavioral changes were linked to specific changes in neuronal activity. The responses of non-photostimulated neurons in the local network were also conditional on two factors: their functional similarity to the photostimulated neurons and the contrast of the visual stimulus. Functionally similar neurons were increasingly suppressed by photostimulation with increasing visual stimulus contrast, correlating with the change in behavior. Our results show that the influence of cortical activity on perception is not fixed, but dynamically and contextually modulated by behavioral state, ongoing activity and the routing of information through specific circuits.

Disinhibition by VIP interneurons is orthogonal to cross-modal attentional modulation in primary visual cortex

Attentional modulation of sensory processing is a key feature of cognition; however, its neural circuit basis is poorly understood. A candidate mechanism is the disinhibition of pyramidal cells through vasoactive intestinal peptide (VIP) and somatostatin (SOM)-positive interneurons. However, the interaction of attentional modulation and VIP-SOM disinhibition has never been directly tested. We used all-optical methods to bi-directionally manipulate VIP interneuron activity as mice performed a cross-modal attention-switching task. We measured the activities of VIP, SOM, and parvalbumin (PV)-positive interneurons and pyramidal neurons identified in the same tissue and found that although activity in all cell classes was modulated by both attention and VIP manipulation, their effects were orthogonal. Attention and VIP-SOM disinhibition relied on distinct patterns of changes in activity and reorganization of interactions between inhibitory and excitatory cells. Circuit modeling revealed a precise network architecture consistent with multiplexing strong yet non-interacting modulations in the same neural population.

Paying attention to natural scenes in area V1

Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesized that attentional and contextual signals interact in V1 in a manner that primarily benefits the representation of natural stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes, but not by synthetic stimuli lacking higher-order statistical regularities. Population analysis revealed that neuronal responses converged to a low-dimensional subspace only for natural stimuli. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the natural-scene subspace, indicating an alignment between the attentional and natural stimulus variance. These results suggest that attentional and contextual signals interact in V1 in a manner optimized for natural vision.

Spatial Decoding for Gaze Independent Brain-Computer Interface Based on Covert Visual Attention Shift Using Electroencephalography

The gaze-independent brain-computer interface (BCI) device is used to re-establish interaction for individuals who have abnormal eye movement. It may be possible to control the BCI by shifting your attention spatially. However, spatial attention is rarely employed to increase the effectiveness of target detection and is typically used to provide a simple "yes" or "no" response to the target recognition inquiry. To improve the effectiveness of detecting target, it is crucial to take advantage of the possible advantages of spatial attention. N2-posterior-contralateral (N2pc) component reflects correlates of visual spatial attention and is used to determine target position. In this study, a long-short-term memory (LSTM) network is used to answer "yes/no" questions by decoding covert spatial attention based on N2pc characteristics using EEG signals. The proposed LSTM-based model's average decoding accuracy is 92.79%. The target detection efficiency was successfully increased by about 4% when compared to conventional machine learning algorithms. The proposed model is tested on the independent dataset to validate its performance. The results of this work show that N2pc characteristics can be employed in gaze-independent BCIs for tracking covert attention shifts, which may help persons with poor eye mobility to connect with their environment.

Pre-saccadic Neural Enhancements in Marmoset Area MT

Each time we make an eye movement, attention moves before the eyes, resulting in a perceptual enhancement at the target. Recent psychophysical studies suggest that this pre-saccadic attention enhances the visual features at the saccade target, whereas covert attention causes only spatially selective enhancements. While previous nonhuman primate studies have found that pre-saccadic attention does enhance neural responses spatially, no studies have tested whether changes in neural tuning reflect an automatic feature enhancement. Here we examined pre-saccadic attention using a saccade foraging task developed for marmoset monkeys (one male and one female). We recorded from neurons in the middle temporal area with peripheral receptive fields that contained a motion stimulus, which would either be the target of a saccade or a distracter as a saccade was made to another location. We established that marmosets, like macaques, show enhanced pre-saccadic neural responses for saccades toward the receptive field, including increases in firing rate and motion information. We then examined if the specific changes in neural tuning might support feature enhancements for the target. Neurons exhibited diverse changes in tuning but predominantly showed additive and multiplicative increases that were uniformly applied across motion directions. These findings confirm that marmoset monkeys, like macaques, exhibit pre-saccadic neural enhancements during saccade foraging tasks with minimal training requirements. However, at the level of individual neurons, the lack of feature-tuned enhancements is similar to neural effects reported during covert spatial attention.

Pathway-selective optogenetics reveals the functional anatomy of top-down attentional modulation in the macaque visual cortex

Spatial attention represents a powerful top-down influence on sensory responses in primate visual cortical areas. The frontal eye field (FEF) has emerged as a key candidate area for the source of this modulation. However, it is unclear whether the FEF exerts its effects via its direct axonal projections to visual areas or indirectly through other brain areas and whether the FEF affects both the enhancement of attended and the suppression of unattended sensory responses. We used pathway-selective optogenetics in rhesus macaques performing a spatial attention task to inhibit the direct input from the FEF to area MT, an area along the dorsal visual pathway specialized for the processing of visual motion information. Our results show that the optogenetic inhibition of the FEF input specifically reduces attentional modulation in MT by about a third without affecting the neurons' sensory response component. We find that the direct FEF-to-MT pathway contributes to both the enhanced processing of target stimuli and the suppression of distractors. The FEF, thus, selectively modulates firing rates in visual area MT, and it does so via its direct axonal projections.

Computational components of visual predictive coding circuitry

If a full visual percept can be said to be a 'hypothesis', so too can a neural 'prediction' - although the latter addresses one particular component of image content (such as 3-dimensional organisation, the interplay between lighting and surface colour, the future trajectory of moving objects, and so on). And, because processing is hierarchical, predictions generated at one level are conveyed in a backward direction to a lower level, seeking to predict, in fact, the neural activity at that prior stage of processing, and learning from errors signalled in the opposite direction. This is the essence of 'predictive coding', at once an algorithm for information processing and a theoretical basis for the nature of operations performed by the cerebral cortex. Neural models for the implementation of predictive coding invoke specific functional classes of neuron for generating, transmitting and receiving predictions, and for producing reciprocal error signals. Also a third general class, 'precision' neurons, tasked with regulating the magnitude of error signals contingent upon the confidence placed upon the prediction, i.e., the reliability and behavioural utility of the sensory data that it predicts. So, what is the ultimate source of a 'prediction'? The answer is multifactorial: knowledge of the current environmental context and the immediate past, allied to memory and lifetime experience of the way of the world, doubtless fine-tuned by evolutionary history too. There are, in consequence, numerous potential avenues for experimenters seeking to manipulate subjects' expectation, and examine the neural signals elicited by surprising, and less surprising visual stimuli. This review focuses upon the predictive physiology of mouse and monkey visual cortex, summarising and commenting on evidence to date, and placing it in the context of the broader field. It is concluded that predictive coding has a firm grounding in basic neuroscience and that, unsurprisingly, there remains much to learn.

Attentional Modulation in Early Visual Cortex: A Focused Reanalysis of Steady-state Visual Evoked Potential Studies

Steady-state visual evoked potentials (SSVEPs) are a powerful tool for investigating selective attention. Here, we conducted a combined reanalysis of multiple studies employing this technique in a variety of attentional experiments to, first, establish benchmark effect sizes of attention on amplitude and phase of SSVEPs and, second, harness the power of a large data set to test more specific hypotheses. Data of eight published SSVEP studies were combined, in which human participants (n = 135 in total) attended to flickering random dot stimuli based on their defining features (e.g., location, color, luminance, or orientation) or feature conjunctions. The reanalysis established that, in all the studies, attention reliably enhanced amplitudes, with color-based attention providing the strongest effect. In addition, the latency of SSVEPs elicited by attended stimuli was reduced by ∼4 msec. Next, we investigated the modulation of SSVEP amplitudes in a subset of studies where two different features were attended concurrently. Although most models assume that attentional effects of multiple features are combined additively, our results suggest that neuronal enhancement provided by concurrent attention is better described by multiplicative integration. Finally, we used the combined data set to demonstrate that the increase in trial-averaged SSVEP amplitudes with attention cannot be explained by increased synchronization of single-trial phases. Contrary to the prediction of the phase-locking account, the variance across trials of complex Fourier coefficients increases with attention, which is more consistent with boosting of a largely phase-locked signal embedded in non-phase-locked noise.

Neural Oscillations and Multisensory Processing

Neural oscillations play a role in sensory processing by coordinating synchronized neuronal activity. Synchronization of gamma oscillations is engaged in local computation of feedforward signals and synchronization of alpha-beta oscillations is engaged in feedback processing over long-range areas. These spatially and spectrally segregated bi-directional signals may be integrated by a mechanism of cross-frequency coupling. Synchronization of neural oscillations has also been proposed as a mechanism for information integration across multiple sensory modalities. A transient stimulus or rhythmic stimulus from one modality may lead to phase alignment of ongoing neural oscillations in multiple sensory cortices, through a mechanism of cross-modal phase reset or cross-modal neural entrainment. Synchronized activities in multiple sensory cortices are more likely to boost stronger activities in downstream areas. Compared to synchronized oscillations, asynchronized oscillations may impede signal processing, and may contribute to sensory selection by setting the oscillations in the target-related cortex and the oscillations in the distractor-related cortex to opposite phases.

Feature-Specific Salience Maps in Human Cortex

Priority map theory is a leading framework for understanding how various aspects of stimulus displays and task demands guide visual attention. Per this theory, the visual system computes a priority map, which is a representation of visual space indexing the relative importance, or priority, of locations in the environment. Priority is computed based on both salience, defined based on image-computable properties; and relevance, defined by an individual's current goals, and is used to direct attention to the highest-priority locations for further processing. Computational theories suggest that priority maps identify salient locations based on individual feature dimensions (e.g., color, motion), which are integrated into an aggregate priority map. While widely accepted, a core assumption of this framework, the existence of independent feature dimension maps in visual cortex, remains untested. Here, we tested the hypothesis that retinotopic regions selective for specific feature dimensions (color or motion) in human cortex act as neural feature dimension maps, indexing salient locations based on their preferred feature. We used fMRI activation patterns to reconstruct spatial maps while male and female human participants viewed stimuli with salient regions defined by relative color or motion direction. Activation in reconstructed spatial maps was localized to the salient stimulus position in the display. Moreover, the strength of the stimulus representation was strongest in the ROI selective for the salience-defining feature. Together, these results suggest that feature-selective extrastriate visual regions highlight salient locations based on local feature contrast within their preferred feature dimensions, supporting their role as neural feature dimension maps.SIGNIFICANCE STATEMENT Identifying salient information is important for navigating the world. For example, it is critical to detect a quickly approaching car when crossing the street. Leading models of computer vision and visual search rely on compartmentalized salience computations based on individual features; however, there has been no direct empirical demonstration identifying neural regions as responsible for performing these dissociable operations. Here, we provide evidence of a critical double dissociation that neural activation patterns from color-selective regions prioritize the location of color-defined salience while minimally representing motion-defined salience, whereas motion-selective regions show the complementary result. These findings reveal that specialized cortical regions act as neural "feature dimension maps" that are used to index salient locations based on specific features to guide attention.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Targeted V1 comodulation supports task-adaptive sensory decisions

Sensory-guided behavior requires reliable encoding of stimulus information in neural populations, and flexible, task-specific readout. The former has been studied extensively, but the latter remains poorly understood. We introduce a theory for adaptive sensory processing based on functionally-targeted stochastic modulation. We show that responses of neurons in area V1 of monkeys performing a visual discrimination task exhibit low-dimensional, rapidly fluctuating gain modulation, which is stronger in task-informative neurons and can be used to decode from neural activity after few training trials, consistent with observed behavior. In a simulated hierarchical neural network model, such labels are learned quickly and can be used to adapt downstream readout, even after several intervening processing stages. Consistently, we find the modulatory signal estimated in V1 is also present in the activity of simultaneously recorded MT units, and is again strongest in task-informative neurons. These results support the idea that co-modulation facilitates task-adaptive hierarchical information routing.

A Review on Motor Imagery with Transcranial Alternating Current Stimulation: Bridging Motor and Cognitive Welfare for Patient Rehabilitation

Research has shown the effectiveness of motor imagery in patient motor rehabilitation. Transcranial electrical stimulation has also demonstrated to improve patient motor and non-motor performance. However, mixed findings from motor imagery studies that involved transcranial electrical stimulation suggest that current experimental protocols can be further improved towards a unified design for consistent and effective results. This paper aims to review, with some clinical and neuroscientific findings from literature as support, studies of motor imagery coupled with different types of transcranial electrical stimulation and their experiments onhealthy and patient subjects. This review also includes the cognitive domains of working memory, attention, and fatigue, which are important for designing consistent and effective therapy protocols. Finally, we propose a theoretical all-inclusive framework that synergizes the three cognitive domains with motor imagery and transcranial electrical stimulation for patient rehabilitation, which holds promise of benefiting patients suffering from neuromuscular and cognitive disorders.

Laminar compartmentalization of attention modulation in area V4 aligns with the demands of visual processing hierarchy in the cortex

Attention selectively enhances neural responses to low contrast stimuli in visual area V4, a critical hub that sends projections both up and down the visual hierarchy. Veridical encoding of contrast information is a key computation in early visual areas, while later stages encoding higher level features benefit from improved sensitivity to low contrast. How area V4 meets these distinct information processing demands in the attentive state is unknown. We found that attentional modulation in V4 is cortical layer and cell-class specific. Putative excitatory neurons in the superficial layers show enhanced boosting of low contrast information, while those of deep layers exhibit contrast-independent scaling. Computational modeling suggested the extent of spatial integration of inhibitory neurons as the mechanism behind such laminar differences. Considering that superficial neurons are known to project to higher areas and deep layers to early visual areas, our findings suggest that the interactions between attention and contrast in V4 are compartmentalized, in alignment with the demands of the visual processing hierarchy.

The effects of pre-cue alpha and cueing strategy on age-related deficits in post-cue alpha activity and target processing during visual spatial attention

Electroencephalography alpha-band (8-13 Hz) activity during visual spatial attention declines in normal aging. We recently reported the impacts of pre-cue baseline alpha and cueing strategy on post-cue anticipatory alpha activity and target processing in visual spatial attention (Wang et al., Cerebral Cortex, 2023). However, whether these factors affected aging effects remains unaddressed. We investigated this issue in two independent experiments (n = 114) with different cueing strategies (instructional vs. probabilistic). When median-splitting young adults (YA) by their pre-cue alpha power, we found that older adults exhibited similar pre-cue and post-cue alpha activity as YA with lower pre-cue alpha, and only YA with higher pre-cue alpha showed significant post-cue alpha activity, suggesting that diminished anticipatory alpha activity was not specific to aging but likely due to a general decrease with baseline alpha. Moreover, we found that the aging effects on cue-related event-related potentials were dependent on cueing strategy but were relatively independent of pre-cue alpha. However, age-related deficits in target-related N1 attentional modulation might depend on both pre-cue alpha and cueing strategy. By considering the impacts of pre-cue alpha and cueing strategy, our findings offer new insights into age-related deficits in anticipatory alpha activity and target processing during visual spatial attention.

Staying and Returning dynamics of young children's attention

In this paper, we decompose selective sustained attending behavior into components of continuous attention maintenance and attentional transitions and study how each of these components develops in young children. Our results in two experiments suggest that changes in children's ability to return attention to a target locus after distraction ("Returning") play a crucial role in the development of selective sustained attention between the ages of 3.5-6 years, perhaps to a greater extent than changes in the ability to continuously maintain attention on the target ("Staying"). We further distinguish Returning from the behavior of transitioning attention away from task (i.e., becoming distracted) and investigate the relative contributions of bottom-up and top-down factors on these different types of attentional transitions. Overall, these results (a) suggest the importance of understanding the cognitive process of transitioning attention for understanding selective sustained attention and its development, (b) provide an empirical paradigm within which to study this process, and (c) begin to characterize basic features of this process, namely its development and its relative dependence on top-down and bottom-up influences on attention. RESEARCH HIGHLIGHTS: Young children exhibited an endogenously ability, Returning, to preferentially transition attention to task-relevant information over task-irrelevant information. Selective sustained attention and its development were decomposed into Returning and Staying, or task-selective attention maintenance, using novel eye-tracking-based measures. Returning improved between the ages of 3.5-6 years, to a greater extent than Staying. Improvements in Returning supported improvements in selective sustained attention between these ages.

Attentional effects on local V1 microcircuits explain selective V1-V4 communication

Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.

Prefrontal activity sharpens spatial sensitivity of extrastriate neurons

Prefrontal cortex is known to exert its control over representation of visual signals in extrastriate areas such as V4. Frontal Eye Field (FEF) is suggested to be the proxy for the prefrontal control of visual signals. However, it is not known which aspects of sensory representation within extrastriate areas are under the influence of FEF activity. We employed a causal manipulation to examine how FEF activity contributes to spatial sensitivity of extrastriate neurons. Finding FEF and V4 areas with overlapping response field (RF) in two macaque monkeys, we recorded V4 responses before and after inactivation of the overlapping FEF. We assessed spatial sensitivity of V4 neurons in terms of their response gain, RF spread, coding capacity, and spatial discriminability. Unexpectedly, we found that in the absence of FEF activity, spontaneous and visually-evoked activity of V4 neurons both increase and their RFs enlarge. However, assessing the spatial sensitivity within V4, we found that these changes were associated with a reduction in the ability of V4 neurons to represent spatial information: After FEF inactivation, V4 neurons showed a reduced response gain and a decrease in their spatial discriminability and coding capacity. These results show the necessity of FEF activity for shaping spatial responses of extrastriate neurons and indicates the importance of FEF inputs in sharpening the sensitivity of V4 responses.

The Architecture of Object-Based Attention

The allocation of attention to objects raises several intriguing questions: What are objects, how does attention access them, what anatomical regions are involved? Here, we review recent progress in the field to determine the mechanisms underlying object-based attention. First, findings from unconscious priming and cueing suggest that the preattentive targets of object-based attention can be fully developed object representations that have reached the level of identity. Next, the control of object-based attention appears to come from ventral visual areas specialized in object analysis that project downward to early visual areas. How feedback from object areas can accurately target the object's specific locations and features is unknown but recent work in autoencoding has made this plausible. Finally, we suggest that the three classic modes of attention may not be as independent as is commonly considered, and instead could all rely on object-based attention. Specifically, studies show that attention can be allocated to the separated members of a group-without affecting the space between them-matching the defining property of feature-based attention. At the same time, object-based attention directed to a single small item has the properties of space-based attention. We outline the architecture of object-based attention, the novel predictions it brings, and discuss how it works in parallel with other attention pathways.

Early sensory gain control is dominated by obligatory and global feature-based attention in top-down shifts of combined spatial and feature-based attention

What are the dynamics of global feature-based and spatial attention, when deployed together? In an attentional shifting experiment, flanked by three control experiments, we investigated neural temporal dynamics of combined attentional shifts. For this purpose, orange- and blue-frequency-tagged spatially overlapping Random Dot Kinematograms were presented in the left and right visual hemifield to elicit continuous steady-state-visual-evoked-potentials. After being initially engaged in a fixation cross task, participants were at some point in time cued to shift attention to one of the Random Dot Kinematograms, to detect and respond to brief coherent motion events, while ignoring all such events in other Random Dot Kinematograms. The analysis of steady-state visual-evoked potentials allowed us to map time courses and dynamics of early sensory-gain modulations by attention. This revealed a time-invariant amplification of the to-be attended color both at the attended and the unattended side, followed by suppression for the to-be-ignored color at attended and unattended sides. Across all experiments, global and obligatory feature-based selection dominated early sensory gain modulations, whereas spatial attention played a minor modulatory role. However, analyses of behavior and neural markers such as alpha-band activity and event-related potentials to target- and distractor-event processing, revealed clear modulations by spatial attention.

Feedforward attentional selection in sensory cortex

Salient objects grab attention because they stand out from their surroundings. Whether this phenomenon is accomplished by bottom-up sensory processing or requires top-down guidance is debated. We tested these alternative hypotheses by measuring how early and in which cortical layer(s) neural spiking distinguished a target from a distractor. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of male macaque monkeys performing visual search for a color singleton. A neural signature of attentional capture was observed in the earliest response in the input layer 4. The magnitude of this response predicted response time and accuracy. Errant behavior followed errant selection. Because this response preceded top-down influences and arose in the cortical layer not targeted by top-down connections, these findings demonstrate that feedforward activation of sensory cortex can underlie attentional priority.

Differential cortical and subcortical visual processing with eyes shut

Closing our eyes largely shuts down our ability to see. That said, our eyelids still pass some light, allowing our visual system to coarsely process information about visual scenes, such as changes in luminance. However, the specific impact of eye closure on processing within the early visual system remains largely unknown. To understand how visual processing is modulated when eyes are shut, we used functional magnetic resonance imaging (fMRI) to measure responses to a flickering visual stimulus at high (100%) and low (10%) temporal contrasts, while participants viewed the stimuli with their eyes open or closed. Interestingly, we discovered that eye closure produced a qualitatively distinct pattern of effects across the visual thalamus and visual cortex. We found that with eyes open, low temporal contrast stimuli produced smaller responses, across the lateral geniculate nucleus (LGN), primary (V1) and extrastriate visual cortex (V2). However, with eyes closed, we discovered that the LGN and V1 maintained similar BOLD responses as the eyes open condition, despite the suppressed visual input through the eyelid. In contrast, V2 and V3 had strongly attenuated BOLD response when eyes were closed, regardless of temporal contrast. Our findings reveal a qualitative distinct pattern of visual processing when the eyes are closed - one that is not simply an overall attenuation, but rather reflects distinct responses across visual thalamocortical networks, wherein the earliest stages of processing preserves information about stimuli but is then gated off downstream in visual cortex.

A "Bandwidth" in cortical representations of multiple faces

The human ability to process multiple items simultaneously can be constrained by the extent to which those items are represented by distinct neural populations. In the current study, we used fMRI to investigate the cortical representation of multiple faces. We found that the addition of a second face to occupy both visual hemifields led to an increased response, whereas a further addition of faces within the same visual hemifield resulted in a decreased response. This pattern was widely observed in the occipital visual cortex, the intraparietal sulcus, and extended to the posterior inferotemporal cortex. A parallel trend was found in a behavioral change-detection task, revealing a perceptual "bandwidth" of multiface processing. The sensitivity to face clutter gradually decreased along the ventral pathway, supporting the notion of a buildup of clutter-tolerance representation. These cortical response patterns to face clutters suggest that adding signals with nonoverlapping cortical representation enhanced perception, while adding signals that competed for representation resources impaired perception.