Mechanisms of top-down attention

Modeling attention-driven plasticity in auditory cortical receptive fields

To navigate complex acoustic environments, listeners adapt neural processes to focus on behaviorally relevant sounds in the acoustic foreground while minimizing the impact of distractors in the background, an ability referred to as top-down selective attention. Particularly striking examples of attention-driven plasticity have been reported in primary auditory cortex via dynamic reshaping of spectro-temporal receptive fields (STRFs). By enhancing the neural response to features of the foreground while suppressing those to the background, STRFs can act as adaptive contrast matched filters that directly contribute to an improved cognitive segregation between behaviorally relevant and irrelevant sounds. In this study, we propose a novel discriminative framework for modeling attention-driven plasticity of STRFs in primary auditory cortex. The model describes a general strategy for cortical plasticity via an optimization that maximizes discriminability between the foreground and distractors while maintaining a degree of stability in the cortical representation. The first instantiation of the model describes a form of feature-based attention and yields STRF adaptation patterns consistent with a contrast matched filter previously reported in neurophysiological studies. An extension of the model captures a form of object-based attention, where top-down signals act on an abstracted representation of the sensory input characterized in the modulation domain. The object-based model makes explicit predictions in line with limited neurophysiological data currently available but can be readily evaluated experimentally. Finally, we draw parallels between the model and anatomical circuits reported to be engaged during active attention. The proposed model strongly suggests an interpretation of attention-driven plasticity as a discriminative adaptation operating at the level of sensory cortex, in line with similar strategies previously described across different sensory modalities.

Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory

Emotional arousal enhances perception and memory of high-priority information but impairs processing of other information. Here, we propose that, under arousal, local glutamate levels signal the current strength of a representation and interact with norepinephrine (NE) to enhance high priority representations and out-compete or suppress lower priority representations. In our "glutamate amplifies noradrenergic effects" (GANE) model, high glutamate at the site of prioritized representations increases local NE release from the locus coeruleus (LC) to generate "NE hotspots." At these NE hotspots, local glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. In contrast, arousal-induced LC activity inhibits less active representations via two mechanisms: 1) Where there are hotspots, lateral inhibition is amplified; 2) Where no hotspots emerge, NE levels are only high enough to activate low-threshold inhibitory adrenoreceptors. Thus, LC activation promotes a few hotspots of excitation in the context of widespread suppression, enhancing high priority representations while suppressing the rest. Hotspots also help synchronize oscillations across neural ensembles transmitting high-priority information. Furthermore, brain structures that detect stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during, or after encoding enhances synaptic plasticity at NE hotspots, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms promote selective attention and memory under arousal. GANE not only reconciles apparently contradictory findings in the emotion-cognition literature but also extends previous influential theories of LC neuromodulation by proposing specific mechanisms for how LC-NE activity increases neural gain.

A hard-wired priority map in the superior colliculus shaped by asymmetric inhibitory circuitry

The mammalian superior colliculus (SC) is a laminar midbrain structure that translates visual signals into commands to shift the focus of attention and gaze. The SC plays an integral role in selecting targets and ultimately generating rapid eye movements to those targets. In all mammals studied to date, neurons in the SC are arranged topographically such that the location of visual stimuli and the endpoints of orienting movements form organized maps in superficial and deeper layers, respectively. The organization of these maps is thought to underlie attentional priority by assessing which regions of the visual field contain behaviorally relevant information. Using voltage imaging and patch-clamp recordings in parasagittal SC slices from the rat, we found the synaptic circuitry of the visuosensory map in the SC imposes a strong bias. Voltage imaging of responses to electrical stimulation revealed more spread in the caudal direction than the rostral direction. Pharmacological experiments demonstrated that this asymmetry arises from GABAA receptor activation rostral to the site of stimulation. Patch-clamp recordings confirmed this rostrally directed inhibitory circuit and showed that it is contained within the visuosensory layers of the SC. Stimulation of two sites showed that initial stimulation of a caudal site can take priority over subsequent stimulation of a rostral site. Taken together, our data indicate that the circuitry of the visuosensory SC is hard-wired to give higher priority to more peripheral targets, and this property is conferred by a uniquely structured, dedicated inhibitory circuit.

Cognitive penetrability and emotion recognition in human facial expressions

Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration (CP) of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on CP, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept CP in some cases of emotion recognition. Finally, we discuss a recently proposed mechanism for CP in the face-based recognition of emotion.

Building up a Bio-Inspired Visual Attention Model by Integrating Top-Down Shape Bias and Improved Mean Shift Adaptive Segmentation

The driver-assistance system (DAS) becomes quite necessary in-vehicle equipment nowadays due to the large number of road traffic accidents worldwide. An efficient DAS detecting hazardous situations robustly is key to reduce road accidents. The core of a DAS is to identify salient regions or regions of interest relevant to visual attended objects in real visual scenes for further process. In order to achieve this goal, we present a method to locate regions of interest automatically based on a novel adaptive mean shift segmentation algorithm to obtain saliency objects. In the proposed mean shift algorithm, we use adaptive Bayesian bandwidth to find the convergence of all data points by iterations and the k-nearest neighborhood queries. Experiments showed that the proposed algorithm is efficient, and yields better visual salient regions comparing with ground-truth benchmark. The proposed algorithm continuously outperformed other known visual saliency methods, generated higher precision and better recall rates, when challenged with natural scenes collected locally and one of the largest publicly available data sets. The proposed algorithm can also be extended naturally to detect moving vehicles in dynamic scenes once integrated with top-down shape biased cues, as demonstrated in our experiments.

Towards the quantitative evaluation of visual attention models

Scores of visual attention models have been developed over the past several decades of research. Differences in implementation, assumptions, and evaluations have made comparison of these models very difficult. Taxonomies have been constructed in an attempt at the organization and classification of models, but are not sufficient at quantifying which classes of models are most capable of explaining available data. At the same time, a multitude of physiological and behavioral findings have been published, measuring various aspects of human and non-human primate visual attention. All of these elements highlight the need to integrate the computational models with the data by (1) operationalizing the definitions of visual attention tasks and (2) designing benchmark datasets to measure success on specific tasks, under these definitions. In this paper, we provide some examples of operationalizing and benchmarking different visual attention tasks, along with the relevant design considerations.

Visual attention model based on statistical properties of neuron responses

Visual attention is a mechanism of the visual system that can select relevant objects from a specific scene. Interactions among neurons in multiple cortical areas are considered to be involved in attentional allocation. However, the characteristics of the encoded features and neuron responses in those attention related cortices are indefinite. Therefore, further investigations carried out in this study aim at demonstrating that unusual regions arousing more attention generally cause particular neuron responses. We suppose that visual saliency is obtained on the basis of neuron responses to contexts in natural scenes. A bottom-up visual attention model is proposed based on the self-information of neuron responses to test and verify the hypothesis. Four different color spaces are adopted and a novel entropy-based combination scheme is designed to make full use of color information. Valuable regions are highlighted while redundant backgrounds are suppressed in the saliency maps obtained by the proposed model. Comparative results reveal that the proposed model outperforms several state-of-the-art models. This study provides insights into the neuron responses based saliency detection and may underlie the neural mechanism of early visual cortices for bottom-up visual attention.

Feature saliency and feedback information interactively impact visual category learning

Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously.

A protocol to examine vision and gait in Parkinson's disease: impact of cognition and response to visual cues

Background

Cognitive and visual impairments are common in Parkinson’s disease (PD) and contribute to gait deficit and falls. To date, cognition and vision in gait in PD have been assessed separately. Impact of both functions (which we term ‘visuo-cognition’) on gait however is likely interactive and can be tested using visual sampling (specifically saccadic eye movements) to provide an online behavioural measure of performance. Although experiments using static paradigms show saccadic impairment in PD, few studies have quantified visual sampling during dynamic motor tasks such as gait.

This article describes a protocol developed for testing visuo-cognition during gait in order to examine the: 1) independent roles of cognition and vision in gait in PD, 2) interaction between both functions, and 3) role of visuo-cognition in gait in PD.

Methods

Two groups of older adults (≥50 years old) were recruited; non-demented people with PD (n=60) and age-matched controls (n=40). Participants attended one session and a sub-group (n=25) attended two further sessions in order to establish mobile eye-tracker reliability. Participants walked in a gait laboratory under different attentional (single and dual task), environmental (walk straight, through a door and turning), and cueing (no visual cues and visual cues) conditions. Visual sampling was recorded using synchronised mobile eye-tracker and electrooculography systems, and gait was measured using 3D motion analysis.

Discussion

This exploratory study examined visuo-cognitive processes and their impact on gait in PD. Improved understanding of the influence of cognitive and visual functions on visual sampling during gait and gait in PD will assist in development of interventions to improve gait and reduce falls risk. This study will also help establish robust mobile eye-tracking methods in older adults and people with PD.

Dawn simulation light impacts on different cognitive domains under sleep restriction

Chronic sleep restriction (SR) has deleterious effects on cognitive performance that can be counteracted by light exposure. However, it is still unknown if naturalistic light settings (dawn simulating light) can enhance daytime cognitive performance in a sustainable matter. Seventeen participants were enrolled in a 24-h balanced cross-over study, subsequent to SR (6-h of sleep). Two different light settings were administered each morning: a) dawn simulating light (DsL; polychromatic light gradually increasing from 0 to 250 lx during 30 min before wake-up time, with light around 250 lx for 20 min after wake-up time) and b) control dim light (DL; <8 lx). Cognitive tests were performed every 2 h during scheduled wakefulness and questionnaires were completed hourly to assess subjective mood. The analyses yielded a main effect of "light condition" for the motor tracking task, sustained attention to response task and a working memory task (visual 1 and 3-back task), as well as for the Simple Reaction Time Task, such that participants showed better task performance throughout the day after morning DsL exposure compared to DL. Furthermore, low performers benefited more from the light effects compared to high performers. Conversely, no significant influences from the DsL were found for the Psychomotor Vigilance Task and a contrary effect was observed for the digit symbol substitution test. No light effects were observed for subjective perception of sleepiness, mental effort, concentration and motivation. Our data indicate that short exposure to artificial morning light may significantly enhance cognitive performance in a domain-specific manner under conditions of mild SR.

A mechanistic approach to cross-domain perceptual narrowing in the first year of life

Language and face processing develop in similar ways during the first year of life. Early in the first year of life, infants demonstrate broad abilities for discriminating among faces and speech. These discrimination abilities then become tuned to frequently experienced groups of people or languages. This process of perceptual development occurs between approximately 6 and 12 months of age and is largely shaped by experience. However, the mechanisms underlying perceptual development during this time, and whether they are shared across domains, remain largely unknown. Here, we highlight research findings across domains and propose a top-down/bottom-up processing approach as a guide for future research. It is hypothesized that perceptual narrowing and tuning in development is the result of a shift from primarily bottom-up processing to a combination of bottom-up and top-down influences. In addition, we propose word learning as an important top-down factor that shapes tuning in both the speech and face domains, leading to similar observed developmental trajectories across modalities. Importantly, we suggest that perceptual narrowing/tuning is the result of multiple interacting factors and not explained by the development of a single mechanism.

Cognitive programs: software for attention's executive

What are the computational tasks that an executive controller for visual attention must solve? This question is posed in the context of the Selective Tuning model of attention. The range of required computations go beyond top-down bias signals or region-of-interest determinations, and must deal with overt and covert fixations, process timing and synchronization, information routing, memory, matching control to task, spatial localization, priming, and coordination of bottom-up with top-down information. During task execution, results must be monitored to ensure the expected results. This description includes the kinds of elements that are common in the control of any kind of complex machine or system. We seek a mechanistic integration of the above, in other words, algorithms that accomplish control. Such algorithms operate on representations, transforming a representation of one kind into another, which then forms the input to yet another algorithm. Cognitive Programs (CPs) are hypothesized to capture exactly such representational transformations via stepwise sequences of operations. CPs, an updated and modernized offspring of Ullman's Visual Routines, impose an algorithmic structure to the set of attentional functions and play a role in the overall shaping of attentional modulation of the visual system so that it provides its best performance. This requires that we consider the visual system as a dynamic, yet general-purpose processor tuned to the task and input of the moment. This differs dramatically from the almost universal cognitive and computational views, which regard vision as a passively observing module to which simple questions about percepts can be posed, regardless of task. Differing from Visual Routines, CPs explicitly involve the critical elements of Visual Task Executive (vTE), Visual Attention Executive (vAE), and Visual Working Memory (vWM). Cognitive Programs provide the software that directs the actions of the Selective Tuning model of visual attention.

Linking attentional processes and conceptual problem solving: visual cues facilitate the automaticity of extracting relevant information from diagrams

This study investigated links between visual attention processes and conceptual problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants' attention to relevant areas to facilitate problem solving. Participants (N = 80) individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants' verbal responses were used to determine their accuracy. This study produced two major findings. First, short duration visual cues which draw attention to solution-relevant information and aid in the organizing and integrating of it, facilitate both immediate problem solving and generalization of that ability to new problems. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers' attention necessarily embodying the solution to the problem, but were instead caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, this study demonstrates that when such cues are used across multiple problems, solvers can automatize the extraction of problem-relevant information extraction. These results suggest that low-level attentional selection processes provide a necessary gateway for relevant information to be used in problem solving, but are generally not sufficient for correct problem solving. Instead, factors that lead a solver to an impasse and to organize and integrate problem information also greatly facilitate arriving at correct solutions.

Salient region detection by fusing bottom-up and top-down features extracted from a single image

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.

Preserved Covert Cognition in Noncommunicative Patients With Severe Brain Injury?

Background. Despite recent evidence suggesting that some severely brain-injured patients retain some capacity for top-down processing (covert cognition), the degree of sparing is unknown. Objective. Top-down attentional processing was assessed in patients in minimally conscious (MCS) and vegetative states (VS) using an active event-related potential (ERP) paradigm. Methods. A total of 26 patients were included (38 ± 12 years old, 9 traumatic, 21 patients >1 year postonset): 8 MCS+, 8 MCS−, and 10 VS patients. There were 14 healthy controls (30 ± 8 years old). The ERP paradigm included (1) a passive condition and (2) an active condition, wherein the participant was instructed to voluntarily focus attention on his/her own name. In each condition, the participant’s own name was presented 100 times (ie, 4 blocks of 25 stimuli). Results. In 5 MCS+ patients as well as in 3 MCS− patients and 1 VS patient, an enhanced P3 amplitude was observed in the active versus passive condition. Relative to controls, patients showed a response that was (1) widely distributed over frontoparietal areas and (2) not present in all blocks (3 of 4). In patients with covert cognition, the amplitude of the response was lower in frontocentral electrodes compared with controls but did not differ from that in the MCS+ group. Conclusion. The results indicate that volitional top-down attention is impaired in patients with covert cognition. Further investigation is crucially needed to better understand top-down cognitive functioning in this population because this may help refine brain-computer interface–based communication strategies.

Decoding of visual attention from LFP signals of macaque MT

The local field potential (LFP) has recently been widely used in brain computer interfaces (BCI). Here we used power of LFP recorded from area MT of a macaque monkey to decode where the animal covertly attended. Support vector machines (SVM) were used to learn the pattern of power at different frequencies for attention to two possible positions. We found that LFP power at both low (<9 Hz) and high (31–120 Hz) frequencies contains sufficient information to decode the focus of attention. Highest decoding performance was found for gamma frequencies (31–120 Hz) and reached 82%. In contrast low frequencies (<9 Hz) could help the classifier reach a higher decoding performance with a smaller amount of training data. Consequently, we suggest that low frequency LFP can provide fast but coarse information regarding the focus of attention, while higher frequencies of the LFP deliver more accurate but less timely information about the focus of attention.

Précis on The Cognitive-Emotional Brain

In The Cognitive-Emotional Brain (Pessoa 2013), I describe the many ways that emotion and cognition interact and are integrated in the brain. The book summarizes five areas of research that support this integrative view and makes four arguments to organize each area. (1) Based on rodent and human data, I propose that the amygdala's functions go beyond emotion as traditionally conceived. Furthermore, the processing of emotion-laden information is capacity limited, thus not independent of attention and awareness. (2) Cognitive-emotional interactions in the human prefrontal cortex (PFC) assume diverse forms and are not limited to mutual suppression. Particularly, the lateral PFC is a focal point for cognitive-emotional interactions. (3) Interactions between motivation and cognition can be seen across a range of perceptual and cognitive tasks. Motivation shapes behavior in specific ways – for example, by reducing response conflict or via selective effects on working memory. Traditional accounts, by contrast, typically describe motivation as a global activation independent of particular control demands. (4) Perception and cognition are directly influenced by information with affective or motivational content in powerful ways. A dual competition model outlines a framework for such interactions at the perceptual and executive levels. A specific neural architecture is proposed that embeds emotional and motivational signals into perception and cognition through multiple channels. (5) A network perspective should supplant the strategy of understanding the brain in terms of individual regions. More broadly, in a network view of brain architecture, “emotion” and “cognition” may be used as labels of certain behaviors, but will not map cleanly into compartmentalized pieces of the brain.

The auditory corticocollicular system: molecular and circuit-level considerations

We live in a world imbued with a rich mixture of complex sounds. Successful acoustic communication requires the ability to extract meaning from those sounds, even when degraded. One strategy used by the auditory system is to harness high-level contextual cues to modulate the perception of incoming sounds. An ideal substrate for this process is the massive set of top-down projections emanating from virtually every level of the auditory system. In this review, we provide a molecular and circuit-level description of one of the largest of these pathways: the auditory corticocollicular pathway. While its functional role remains to be fully elucidated, activation of this projection system can rapidly and profoundly change the tuning of neurons in the inferior colliculus. Several specific issues are reviewed. First, we describe the complex heterogeneous anatomical organization of the corticocollicular pathway, with particular emphasis on the topography of the pathway. We also review the laminar origin of the corticocollicular projection and discuss known physiological and morphological differences between subsets of corticocollicular cells. Finally, we discuss recent findings about the molecular micro-organization of the inferior colliculus and how it interfaces with corticocollicular termination patterns. Given the assortment of molecular tools now available to the investigator, it is hoped that his review will help guide future research on the role of this pathway in normal hearing.

Pharmaco-MEG evidence for attention related hyper-connectivity between auditory and prefrontal cortices in ADHD

The ability to attend to particular stimuli while ignoring others is crucial in goal-directed activities and has been linked with prefrontal cortical regions, including the dorsolateral prefrontal cortex (DLPFC). Both hyper- and hypo-activation in the DLPFC has been reported in patients with attention-deficit/hyperactivity disorder (ADHD) during many different cognitive tasks, but the network-level effects of such aberrant activity remain largely unknown. Using magnetoencephalography (MEG), we examined functional connectivity between regions of the DLPFC and the modality-specific auditory cortices during an auditory attention task in medicated and un-medicated adults with ADHD, and those without ADHD. Participants completed an attention task in two separate sessions (medicated/un-medicated), and each session consisted of two blocks (attend and no-attend). All MEG data were coregistered to structural MRI, corrected for head motion, and projected into source space. Subsequently, we computed the phase coherence (i.e., functional connectivity) between DLPFC regions and the auditory cortices. We found that un-medicated adults with ADHD exhibited greater phase coherence in the beta (14-30Hz) and gamma frequency (30-56Hz) range in attend and no-attend conditions compared to controls. Stimulant medication attenuated these differences, but did not fully eliminate them. These results suggest that aberrant bottom-up processing may engulf executive resources in ADHD.

Optimal attentional modulation of a neural population

Top-down attention has often been separately studied in the contexts of either optimal population coding or biasing of visual search. Yet, both are intimately linked, as they entail optimally modulating sensory variables in neural populations according to top-down goals. Designing experiments to probe top-down attentional modulation is difficult because non-linear population dynamics are hard to predict in the absence of a concise theoretical framework. Here, we describe a unified framework that encompasses both contexts. Our work sheds light onto the ongoing debate on whether attention modulates neural response gain, tuning width, and/or preferred feature. We evaluate the framework by conducting simulations for two tasks: (1) classification (discrimination) of two stimuli s a and s b and (2) searching for a target T among distractors D. Results demonstrate that all of gain, tuning, and preferred feature modulation happen to different extents, depending on stimulus conditions and task demands. The theoretical analysis shows that task difficulty (linked to difference Δ between s a and s b , or T, and D) is a crucial factor in optimal modulation, with different effects in discrimination vs. search. Further, our framework allows us to quantify the relative utility of neural parameters. In easy tasks (when Δ is large compared to the density of the neural population), modulating gains and preferred features is sufficient to yield nearly optimal performance; however, in difficult tasks (smaller Δ), modulating tuning width becomes necessary to improve performance. This suggests that the conflicting reports from different experimental studies may be due to differences in tasks and in their difficulties. We further propose future electrophysiology experiments to observe different types of attentional modulation in a same neuron.

Anterior Cingulate Cortex Cells Identify Process-Specific Errors of Attentional Control Prior to Transient Prefrontal-Cingulate Inhibition

Errors indicate the need to adjust attention for improved future performance. Detecting errors is thus a fundamental step to adjust and control attention. These functions have been associated with the dorsal anterior cingulate cortex (dACC), predicting that dACC cells should track the specific processing states giving rise to errors in order to identify which processing aspects need readjustment. Here, we tested this prediction by recording cells in the dACC and lateral prefrontal cortex (latPFC) of macaques performing an attention task that dissociated 3 processing stages. We found that, across prefrontal subareas, the dACC contained the largest cell populations encoding errors indicating (1) failures of inhibitory control of the attentional focus, (2) failures to prevent bottom-up distraction, and (3) lapses when implementing a choice. Error-locked firing in the dACC showed the earliest latencies across the PFC, emerged earlier than reward omission signals, and involved a significant proportion of putative inhibitory interneurons. Moreover, early onset error-locked response enhancement in the dACC was followed by transient prefrontal-cingulate inhibition, possibly reflecting active disengagement from task processing. These results suggest a functional specialization of the dACC to track and identify the actual processes that give rise to erroneous task outcomes, emphasizing its role to control attentional performance.

Object-based selection modulates top-down attentional shifts

A large body of evidence supports that visual attention – the cognitive process of selectively concentrating on a salient or task-relevant subset of visual information – often works on object-based representation. Recent studies have postulated two possible accounts for the object-specific attentional advantage: attentional spreading and attentional prioritization, each of which modulates a bottom-up signal for sensory processing and a top-down signal for attentional allocation, respectively. It is still unclear which account can explain the object-specific attentional advantage. To address this issue, we examined the influence of object-specific advantage on two types of visual search: parallel search, invoked when a bottom-up signal is fully available at a target location, and serial search, invoked when a bottom-up signal is not enough to guide target selection and a top-down control for shifting of focused attention is required. Our results revealed that the object-specific advantage is given to the serial search but not to the parallel search, suggesting that object-based attention facilitates stimulus processing by affecting the priority of attentional shifts rather than by enhancing sensory signals. Thus, our findings support the notion that the object-specific attentional advantage can be explained by attentional prioritization but not attentional spreading.

Canonical Organization of Layer 1 Neuron-Led Cortical Inhibitory and Disinhibitory Interneuronal Circuits

Interneurons play a key role in cortical function and dysfunction, yet organization of cortical interneuronal circuitry remains poorly understood. Cortical Layer 1 (L1) contains 2 general GABAergic interneuron groups, namely single bouquet cells (SBCs) and elongated neurogliaform cells (ENGCs). SBCs predominantly make unidirectional inhibitory connections (SBC→) with L2/3 interneurons, whereas ENGCs frequently form reciprocal inhibitory and electric connections (ENGC↔) with L2/3 interneurons. Here, we describe a systematic investigation of the pyramidal neuron targets of L1 neuron-led interneuronal circuits in the rat barrel cortex with simultaneous octuple whole-cell recordings and report a simple organizational scheme of the interneuronal circuits. Both SBCs→ and ENGC ↔ L2/3 interneuronal circuits connect to L2/3 and L5, but not L6, pyramidal neurons. SBC → L2/3 interneuronal circuits primarily inhibit the entire dendritic-somato-axonal axis of a few L2/3 and L5 pyramidal neurons located within the same column. In contrast, ENGC ↔ L2/3 interneuronal circuits generally inhibit the distal apical dendrite of many L2/3 and L5 pyramidal neurons across multiple columns. Finally, L1 interneuron-led circuits target distinct subcellular compartments of L2/3 and L5 pyramidal neurons in a L2/3 interneuron type-dependent manner. These results suggest that L1 neurons form canonical interneuronal circuits to control information processes in both supra- and infragranular cortical layers.

Emotional arousal amplifies the effects of biased competition in the brain

The arousal-biased competition model predicts that arousal increases the gain on neural competition between stimuli representations. Thus, the model predicts that arousal simultaneously enhances processing of salient stimuli and impairs processing of relatively less-salient stimuli. We tested this model with a simple dot-probe task. On each trial, participants were simultaneously exposed to one face image as a salient cue stimulus and one place image as a non-salient stimulus. A border around the face cue location further increased its bottom-up saliency. Before these visual stimuli were shown, one of two tones played: one that predicted a shock (increasing arousal) or one that did not. An arousal-by-saliency interaction in category-specific brain regions (fusiform face area for salient faces and parahippocampal place area for non-salient places) indicated that brain activation associated with processing the salient stimulus was enhanced under arousal whereas activation associated with processing the non-salient stimulus was suppressed under arousal. This is the first functional magnetic resonance imaging study to demonstrate that arousal can enhance information processing for prioritized stimuli while simultaneously impairing processing of non-prioritized stimuli. Thus, it goes beyond previous research to show that arousal does not uniformly enhance perceptual processing, but instead does so selectively in ways that optimizes attention to highly salient stimuli.

Artificially created stimuli produced by a genetic algorithm using a saliency model as its fitness function show that Inattentional Blindness modulates performance in a pop-out visual search paradigm

Salient stimuli are more readily detected than less salient stimuli, and individual differences in such detection may be relevant to why some people fail to notice an unexpected stimulus that appears in their visual field whereas others do notice it. This failure to notice unexpected stimuli is termed 'Inattentional Blindness' and is more likely to occur when we are engaged in a resource-consuming task. A genetic algorithm is described in which artificial stimuli are created using a saliency model as its fitness function. These generated stimuli, which vary in their saliency level, are used in two studies that implement a pop-out visual search task to evaluate the power of the model to discriminate the performance of people who were and were not Inattentionally Blind (IB). In one study the number of orientational filters in the model was increased to check if discriminatory power and the saliency estimation for low-level images could be improved. Results show that the performance of the model does improve when additional filters are included, leading to the conclusion that low-level images may require a higher number of orientational filters for the model to better predict participants' performance. In both studies we found that given the same target patch image (i.e. same saliency value) IB individuals take longer to identify a target compared to non-IB individuals. This suggests that IB individuals require a higher level of saliency for low-level visual features in order to identify target patches.

Adaptive auditory computations

The auditory system analyses acoustic signals, extracting their perceptual attributes, and exploiting them to navigate complex auditory environments. While many of the basic transformations that give rise to the early auditory representations are well studied and understood, little is known about the latter cognitive functions that bind, organize, and give meaning to them. They include the ability to attend to, segregate, and track one of many sound sources, to learn its identity, commit it to memory, robustly recognize it, and utilize it to make decisions. This review hints at the profound adaptive influences and contextual effects induced by cognitive functions during these behaviors, and the need for robust tractable mathematical models to understand them.

Posterior parietal cortex is critical for the encoding, consolidation, and retrieval of a memory that guides attention for learning

Within most contemporary learning theories, reinforcement prediction error, the difference between the obtained and expected reinforcer value, critically influences associative learning. In some theories, this prediction error determines the momentary effectiveness of the reinforcer itself, such that the same physical event produces more learning when its presentation is surprising than when it is expected. In other theories, prediction error enhances attention to potential cues for that reinforcer by adjusting cue-specific associability parameters, biasing the processing of those stimuli so that they more readily enter into new associations in the future. A unique feature of these latter theories is that such alterations in stimulus associability must be represented in memory in an enduring fashion. Indeed, considerable data indicate that altered associability may be expressed days after its induction. Previous research from our laboratory identified brain circuit elements critical to the enhancement of stimulus associability by the omission of an expected event, and to the subsequent expression of that altered associability in more rapid learning. Here, for the first time, we identified a brain region, the posterior parietal cortex, as a potential site for a memorial representation of altered stimulus associability. In three experiments using rats and a serial prediction task, we found that intact posterior parietal cortex function was essential during the encoding, consolidation, and retrieval of an associability memory enhanced by surprising omissions. We discuss these new results in the context of our previous findings and additional plausible frontoparietal and subcortical networks.

Attention driven foveated video quality assessment

Contrast sensitivity of the human visual system to visual stimuli can be significantly affected by several mechanisms, e.g., vision foveation and attention. Existing studies on foveation based video quality assessment only take into account static foveation mechanism. This paper first proposes an advanced foveal imaging model to generate the perceived representation of video by integrating visual attention into the foveation mechanism. For accurately simulating the dynamic foveation mechanism, a novel approach to predict video fixations is proposed by mimicking the essential functionality of eye movement. Consequently, an advanced contrast sensitivity function, derived from the attention driven foveation mechanism, is modeled and then integrated into a wavelet-based distortion visibility measure to build a full reference attention driven foveated video quality (AFViQ) metric. AFViQ exploits adequately perceptual visual mechanisms in video quality assessment. Extensive evaluation results with respect to several publicly available eye-tracking and video quality databases demonstrate promising performance of the proposed video attention model, fixation prediction approach, and quality metric.

The interplay of bottom-up and top-down mechanisms in visual guidance during object naming

An ongoing issue in visual cognition concerns the roles played by low- and high-level information in guiding visual attention, with current research remaining inconclusive about the interaction between the two. In this study, we bring fresh evidence into this long-standing debate by investigating visual saliency and contextual congruency during object naming (Experiment 1), a task in which visual processing interacts with language processing. We then compare the results of this experiment to data of a memorization task using the same stimuli (Experiment 2). In Experiment 1, we find that both saliency and congruency influence visual and naming responses and interact with linguistic factors. In particular, incongruent objects are fixated later and less often than congruent ones. However, saliency is a significant predictor of object naming, with salient objects being named earlier in a trial. Furthermore, the saliency and congruency of a named object interact with the lexical frequency of the associated word and mediate the time-course of fixations at naming. In Experiment 2, we find a similar overall pattern in the eye-movement responses, but only the congruency of the target is a significant predictor, with incongruent targets fixated less often than congruent targets. Crucially, this finding contrasts with claims in the literature that incongruent objects are more informative than congruent objects by deviating from scene context and hence need a longer processing. Overall, this study suggests that different sources of information are interactively used to guide visual attention on the targets to be named and raises new questions for existing theories of visual attention.

Explicit semantic stimulus categorization interferes with implicit emotion processing

Previous functional magnetic resonance imaging and event-related brain potential studies revealed that performing a cognitive task may suppress the preferential processing of emotional stimuli. However, these studies utilized simple and artificial tasks (i.e. letter, shape or orientation discrimination tasks), unfamiliar to the participants. The present event-related potential study examined the emotion-attention interaction in the context of a comparably more natural scene categorization task. Deciding whether a natural scene contains an animal or not is a familiar and meaningful task to the participants and presumed to require little attentional resources. The task images were presented centrally and were overlaid upon emotional or neutral background pictures. Thus, implicit emotion and explicit semantic categorization may compete for processing resources in neural regions implicated in object recognition. Additionally, participants passively viewed the same stimulus materials without the demand to categorize task images. Significant interactions between task condition and emotional picture valence were observed for the occipital negativity and late positive potential. In the passive viewing condition, emotional background images elicited an increased occipital negativity followed by an increased late positive potential. In contrast, during the animal-/non-animal-categorization task, emotional modulation effects were replaced by strong target categorization effects. These results suggest that explicit semantic categorization interferes with implicit emotion processing when both processes compete for shared resources.

Neurocognitive enhancement in older adults: comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity

The ultimate goal of cognitive enhancement as an intervention for age-related cognitive decline is transfer to everyday cognitive functioning. Development of training methods that transfer broadly to untrained cognitive tasks (far transfer) requires understanding of the neural bases of training and far transfer effects. We used cognitive training to test the hypothesis that far transfer is associated with altered attentional control demands mediated by the dorsal attention network and trained sensory cortex. In an exploratory study, we randomly assigned 42 healthy older adults to six weeks of training on Brain Fitness (BF-auditory perception), Space Fortress (SF-visuomotor/working memory), or Rise of Nations (RON-strategic reasoning). Before and after training, cognitive performance, diffusion-derived white matter integrity, and functional connectivity of the superior parietal cortex (SPC) were assessed. We found the strongest effects from BF training, which transferred to everyday problem solving and reasoning and selectively changed integrity of occipito-temporal white matter associated with improvement on untrained everyday problem solving. These results show that cognitive gain from auditory perception training depends on heightened white matter integrity in the ventral attention network. In BF and SF (which also transferred positively), a decrease in functional connectivity between SPC and inferior temporal lobe (ITL) was observed compared to RON-which did not transfer to untrained cognitive function. These findings highlight the importance for cognitive training of top-down control of sensory processing by the dorsal attention network. Altered brain connectivity - observed in the two training tasks that showed far transfer effects - may be a marker for training success.

Prefrontal neurons of opposite spatial preference display distinct target selection dynamics

Neurons in the primate dorsolateral prefrontal cortex (dlPFC) of one hemisphere are selective for the location of attended targets in both visual hemifields. Whether dlPFC neurons with selectivity for opposite hemifields directly compete with each other for target selection or instead play distinct roles during the allocation of attention remains unclear. We explored this issue by recording neuronal responses in the right dlPFC of two macaques while they allocated attention to a target in one hemifield and ignored a distracter on the opposite side. Forty-nine percent of the recorded neurons were target location selective. Neurons selective for contralateral targets (58%) systematically discriminated targets from distracters faster than neurons selective for ipsilateral targets (42%). Additionally, during trials in which sensory stimulation remained the same but both stimuli were task irrelevant and animals were required to detect a change in the color of a fixation spot, contralateral neurons still reliably discriminated the putative target from the distracter, whereas ipsilateral neurons did not. The latter result indicates that target-distracter discrimination by contralateral neurons could occur independently of discrimination by ipsilateral cells; thus, the two cell types may represent two different components of the prefrontal circuitry underlying the allocation of attention to targets in the presence of distracters. Moreover, the response of both contralateral and ipsilateral neurons to a single target was substantially reduced by the presence of a distracter in the contralateral hemifield. This result suggests that the presence of the distracter triggered inhibitory interactions within the dlPFC circuitry that suppressed responses to the attended target.

Tunnel vision: sharper gradient of spatial attention in autism

Enhanced perception of detail has long been regarded a hallmark of autism spectrum conditions (ASC), but its origins are unknown. Normal sensitivity on all fundamental perceptual measures-visual acuity, contrast discrimination, and flicker detection-is strongly established in the literature. If individuals with ASC do not have superior low-level vision, how is perception of detail enhanced? We argue that this apparent paradox can be resolved by considering visual attention, which is known to enhance basic visual sensitivity, resulting in greater acuity and lower contrast thresholds. Here, we demonstrate that the focus of attention and concomitant enhancement of perception are sharper in human individuals with ASC than in matched controls. Using a simple visual acuity task embedded in a standard cueing paradigm, we mapped the spatial and temporal gradients of attentional enhancement by varying the distance and onset time of visual targets relative to an exogenous cue, which obligatorily captures attention. Individuals with ASC demonstrated a greater fall-off in performance with distance from the cue than controls, indicating a sharper spatial gradient of attention. Further, this sharpness was highly correlated with the severity of autistic symptoms in ASC, as well as autistic traits across both ASC and control groups. These findings establish the presence of a form of "tunnel vision" in ASC, with far-reaching implications for our understanding of the social and neurobiological aspects of autism.

Evolution of working memory

Working memory (WM) is fundamental to many aspects of human life, including learning, speech and text comprehension, prospection and future planning, and explicit "system 2" forms of reasoning, as well as overlapping heavily with fluid general intelligence. WM has been intensively studied for many decades, and there is a growing consensus about its nature, its components, and its signature limits. Remarkably, given its central importance in human life, there has been very little comparative investigation of WM abilities across species. Consequently, much remains unknown about the evolution of this important human capacity. Some questions can be tentatively answered from the existing comparative literature. Even studies that were not intended to do so can nonetheless shed light on the WM capacities of nonhuman animals. However, many questions remain.

Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events

Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning.

Functional properties of cortical feedback projections to the olfactory bulb

Sensory perception is not a simple feed-forward process, and higher brain areas can actively modulate information processing in "lower" areas. We used optogenetic methods to examine how cortical feedback projections affect circuits in the first olfactory processing stage, the olfactory bulb. Selective activation of back projections from the anterior olfactory nucleus/cortex (AON) revealed functional glutamatergic synaptic connections on several types of bulbar interneurons. Unexpectedly, AON axons also directly depolarized mitral cells (MCs), enough to elicit spikes reliably in a time window of a few milliseconds. MCs received strong disynaptic inhibition, a third of which arises in the glomerular layer. Activating feedback axons in vivo suppressed spontaneous as well as odor-evoked activity of MCs, sometimes preceded by a temporally precise increase in firing probability. Our study indicates that cortical feedback can shape the activity of bulbar output neurons by enabling precisely timed spikes and enforcing broad inhibition to suppress background activity.

Viewing the dynamics and control of visual attention through the lens of electrophysiology

How we find what we are looking for in complex visual scenes is a seemingly simple ability that has taken half a century to unravel. The first study to use the term visual search showed that as the number of objects in a complex scene increases, observers' reaction times increase proportionally (Green & Anderson, 1956). This observation suggests that our ability to process the objects in the scenes is limited in capacity. However, if it is known that the target will have a certain feature attribute, for example, that it will be red, then only an increase in the number of red items increases reaction time. This observation suggests that we can control which visual inputs receive the benefit of our limited capacity to recognize the objects, such as those defined by the color red, as the items we seek. The nature of the mechanisms that underlie these basic phenomena in the literature on visual search have been more difficult to definitively determine. In this paper, I discuss how electrophysiological methods have provided us with the necessary tools to understand the nature of the mechanisms that give rise to the effects observed in the first visual search paper. I begin by describing how recordings of event-related potentials from humans and nonhuman primates have shown us how attention is deployed to possible target items in complex visual scenes. Then, I will discuss how event-related potential experiments have allowed us to directly measure the memory representations that are used to guide these deployments of attention to items with target-defining features.

The organization of two new cortical interneuronal circuits

Deciphering the interneuronal circuitry is central to understanding brain functions, yet it remains a challenging task in neurobiology. Using simultaneous quadruple-octuple in vitro and dual in vivo whole-cell recordings, we found two previously unknown interneuronal circuits that link cortical layer 1-3 (L1-3) interneurons and L5 pyramidal neurons in the rat neocortex. L1 single-bouquet cells (SBCs) preferentially formed unidirectional inhibitory connections on L2/3 interneurons that inhibited the entire dendritic-somato-axonal axis of ∼1% of L5 pyramidal neurons located in the same column. In contrast, L1 elongated neurogliaform cells (ENGCs) frequently formed mutual inhibitory and electric connections with L2/3 interneurons, and these L1-3 interneurons inhibited the distal apical dendrite of >60% of L5 pyramidal neurons across multiple columns. Functionally, SBC→L2/3 interneuron→L5 pyramidal neuronal circuits disinhibited and ENGC↔L2/3 interneuron→L5 pyramidal neuronal circuits inhibited the initiation of dendritic complex spikes in L5 pyramidal neurons. As dendritic complex spikes can serve coincidence detection, these cortical interneuronal circuits may be essential for salience selection.

State-of-the-art in visual attention modeling

Modeling visual attention--particularly stimulus-driven, saliency-based attention--has been a very active research area over the past 25 years. Many different models of attention are now available which, aside from lending theoretical contributions to other fields, have demonstrated successful applications in computer vision, mobile robotics, and cognitive systems. Here we review, from a computational perspective, the basic concepts of attention implemented in these models. We present a taxonomy of nearly 65 models, which provides a critical comparison of approaches, their capabilities, and shortcomings. In particular, 13 criteria derived from behavioral and computational studies are formulated for qualitative comparison of attention models. Furthermore, we address several challenging issues with models, including biological plausibility of the computations, correlation with eye movement datasets, bottom-up and top-down dissociation, and constructing meaningful performance measures. Finally, we highlight current research trends in attention modeling and provide insights for future.

Variation in key genes of serotonin and norepinephrine function predicts gamma-band activity during goal-directed attention

Recent evidence shows that genetic variations in key regulators of serotonergic (5-HT) signaling explain variance in executive tasks, which suggests modulatory actions of 5-HT on goal-directed selective attention as one possible underlying mechanism. To investigate this link, 130 volunteers were genotyped for the 5-HT transporter gene-linked polymorphic region (5-HTTLPR) and for a variation (TPH2-703 G/T) of the TPH2 gene coding for the rate-limiting enzyme of 5-HT synthesis in the brain. Additionally, a functional polymorphism of the norepinephrine transporter gene (NET -3081 A/T) was considered, which was recently found to predict attention and working memory processes in interaction with serotonergic genes. The flanker-based Attention Network Test was used to assess goal-directed attention and the efficiency of attentional networks. Event-related gamma-band activity served to indicate selective attention at the intermediate phenotype level. The main findings were that 5-HTTLPR s allele and TPH2 G-allele homozygotes showed increased induced gamma-band activity during target processing when combined with the NET A/A genotype compared with other genotype combinations, and that gamma activity mediates the genotype-specific effects on task performance. The results further support a modulatory role of 5-HT and NE function in the top-down attentional selection of motivationally relevant over competing or irrelevant sensory input.

Brain plasticity through the life span: learning to learn and action video games

The ability of the human brain to learn is exceptional. Yet, learning is typically quite specific to the exact task used during training, a limiting factor for practical applications such as rehabilitation, workforce training, or education. The possibility of identifying training regimens that have a broad enough impact to transfer to a variety of tasks is thus highly appealing. This work reviews how complex training environments such as action video game play may actually foster brain plasticity and learning. This enhanced learning capacity, termed learning to learn, is considered in light of its computational requirements and putative neural mechanisms.

Attention, learning, and the value of information

Despite many studies on selective attention, fundamental questions remain about its nature and neural mechanisms. Here I draw from the animal and machine learning fields that describe attention as a mechanism for active learning and uncertainty reduction and explore the implications of this view for understanding visual attention and eye movement control. I propose that a closer integration of these different views has the potential greatly to expand our understanding of oculomotor control and our ability to use this system as a window into high level but poorly understood cognitive functions, including the capacity for curiosity and exploration and for inferring internal models of the external world.

Reward modulates the neural dynamics of early visual category processing

Converging evidence suggests that visual brain regions are part of a widespread network that signals forthcoming reward. However, the precise temporal dynamics underlying the interaction between reward and visual information processing remain unclear. To further investigate this issue, we used magnetoencephalography (MEG) in combination with two versions of a face/scene discrimination task followed by a recognition memory test. In experiment 1, the distinction between faces and scenes was associated with monetary reward prospect, whereas in experiment 2 subjects distinguished between both categories in the absence of reward. In both experiments characteristic neural category effects (i.e., differences between faces and scenes) were observed in the event-related magnetic fields (ERF) at ~100 ms (M100) and ~170 ms (M170) after stimulus onset. Importantly, both ERF components (M100 and M170) were amplified in the context of reward (i.e., experiment 1) and this interaction could be source localized to the lateral occipital cortex (~100 ms) and fusiform gyrus (~170 ms). Furthermore, neural effects of reward prediction emerged over frontal sensors at ~300 ms after stimulus onset which reliably correlated with subsequent recognition memory performance. These results demonstrate that reward motivation can modulate early neural computations of complex visual information, possibly by tuning sensory neurons within the visual cortex.

Coding of saliency by ensemble bursting in the amygdala of primates

Salient parts of a visual scene attract longer and earlier fixations of the eyes. Saliency is driven by bottom-up (image dependent) factors and top-down factors such as behavioral relevance, goals, and expertise. It is currently assumed that a saliency map defining eye fixation priorities is stored in neural structures that remain to be determined. Lesion studies support a role for the amygdala in detecting saliency. Here we show that neurons in the amygdala of primates fire differentially when the eyes approach to or fixate behaviorally relevant parts of visual scenes. Ensemble bursting in the amygdala accurately predicts main fixations during the free-viewing of natural images. However, fixation prediction is significantly better for faces—where a bottom-up computational saliency model fails—compared to unfamiliar objects and landscapes. On this basis we propose the amygdala as a locus for a saliency map and ensemble bursting as a saliency coding mechanism.

Visual short-term memory: activity supporting encoding and maintenance in retinotopic visual cortex

Recent studies have demonstrated that retinotopic cortex maintains information about visual stimuli during retention intervals. However, the process by which transient stimulus-evoked sensory responses are transformed into enduring memory representations is unknown. Here, using fMRI and short-term visual memory tasks optimized for univariate and multivariate analysis approaches, we report differential involvement of human retinotopic areas during memory encoding of the low-level visual feature orientation. All visual areas show weaker responses when memory encoding processes are interrupted, possibly due to effects in orientation-sensitive primary visual cortex (V1) propagating across extrastriate areas. Furthermore, intermediate areas in both dorsal (V3a/b) and ventral (LO1/2) streams are significantly more active during memory encoding compared with non-memory (active and passive) processing of the same stimulus material. These effects in intermediate visual cortex are also observed during memory encoding of a different stimulus feature (spatial frequency), suggesting that these areas are involved in encoding processes on a higher level of representation. Using pattern-classification techniques to probe the representational content in visual cortex during delay periods, we further demonstrate that simply initiating memory encoding is not sufficient to produce long-lasting memory traces. Rather, active maintenance appears to underlie the observed memory-specific patterns of information in retinotopic cortex.