Attentional Feedback Research Articles

Optimal feedback improves behavioral focus during self-regulated computer-based work

Distractions are omnipresent and can derail our attention, which is a precious and very limited resource. To achieve their goals in the face of distractions, people need to regulate their attention, thoughts, and behavior; this is known as self-regulation. How can self-regulation be supported or strengthened in ways that are relevant for everyday work and learning activities? To address this question, we introduce and evaluate a desktop application that helps people stay focused on their work and train self-regulation at the same time. Our application lets the user set a goal for what they want to do during a defined period of focused work at their computer, then gives negative feedback when they get distracted, and positive feedback when they reorient their attention towards their goal. After this so-called focus session, the user receives overall feedback on how well they focused on their goal relative to previous sessions. While existing approaches to attention training often use artificial tasks, our approach transforms real-life challenges into opportunities for building strong attention control skills. Our results indicate that optimal attentional feedback can generate large increases in behavioral focus, task motivation, and self-control—benefitting users to successfully achieve their long-term goals.

Modeling apical and basal tree contribution to orientation selectivity in a mouse primary visual cortex layer 2/3 pyramidal cell.

Pyramidal neurons, a mainstay of cortical regions, receive a plethora of inputs from various areas onto their morphologically distinct apical and basal trees. Both trees differentially contribute to the somatic response, defining distinct anatomical and possibly functional sub-units. To elucidate the contribution of each tree to the encoding of visual stimuli at the somatic level, we modeled the response pattern of a mouse L2/3 V1 pyramidal neuron to orientation tuned synaptic input. Towards this goal, we used a morphologically detailed computational model of a single cell that replicates electrophysiological and two-photon imaging data. Our simulations predict a synergistic effect of apical and basal trees on somatic action potential generation: basal tree activity, in the form of either depolarization or dendritic spiking, is necessary for producing somatic activity, despite the fact that most somatic spikes are heavily driven by apical dendritic spikes. This model provides evidence for synergistic computations taking place in the basal and apical trees of the L2/3 V1 neuron along with mechanistic explanations for tree-specific contributions and emphasizes the potential role of predictive and attentional feedback input in these cells.

Comparison of the effect of attention span symptoms and attentional feedback on children's motor skills learning

The aim of this study was to investigate the effect of focus instructions (internal and external)and attention feedback(internal and external) on learning basketball free throw skills in children aged 9 to 11 years.For this purpose,70 female high school students aged 9 to 11 years were selected from District 18 of Tehran and randomly divided into five groups of 14 people,including Experiment One;Group 1.Internal Attention 2. External Attention and Experiment Two;Group 3.Internal attention feedback 4.External attention feedback and 5.Control group were divided.After learning some basic instructions and watching the instructional video, participants participated in a pre-test that included a 10-item set.The acquisition phase consisted of two sessions on two consecutive days and each session consisted of 5 blocks of 10 attempts with two minute of rest between blocks.Immediate retention test was performed immediately after the acquisition phase and delayed retention test was performed 48 hours after the last acquisition session. Data analysis was performed using repeated measures analysis of variance, one-way analysis of variance,LSD post hoc test using SPSS software version 20 and Excel at a significant level (P <0.05).The findings showed;both attention-grabbing and attention-grabbing methods improved children's motor function (P <0.05).In the combination of data related to internal and external attention and external and internal attention feedback, the findings showed that there was a significant difference between the effect of focus and internal and external attention feedback signs on children's motor skills learning.Was observed(P <0.05).Conclusion:The present findings in support of the hypothesis of limited practice in order to learn the motor skills of children's basketball free throw,recommend the use of attention signs and feedback attention inside and outside,especially external signs

Dynamics of coherent activity between cortical areas defines a two-stage process of top-down attention.

Analysing a visual scene requires the brain to briefly keep in memory potentially relevant items of that scene and then direct attention to their locations for detailed processing. To reveal the neuronal basis of the underlying working memory and top-down attention processes, we trained macaques to match two patterns presented with a delay between them. As the above processes are likely to require communication between brain regions, and the parietal cortex is known to be involved in spatial attention, we simultaneously recorded neuronal activities from the interconnected parietal and middle temporal areas. We found that mnemonic information about features of the first pattern was retained in coherent oscillating activity between the two areas in high-frequency bands, followed by coherent activity in lower frequency bands mediating top-down attention on the relevant spatial location. Oscillations maintaining featural information also modulated activity of the cells of the parietal cortex that mediate attention. This could potentially enable transfer of information to organize top-down signals necessary for selective attention. Our results provide evidence in support of a two-stage model of visual attention where the first stage involves creating a saliency map representing a visual scene and at the second stage attentional feedback is provided to cortical areas involved in detailed analysis of the attended parts of a scene.

Ultra-high field fMRI reveals origins of feedforward and feedback activity within laminae of human ocular dominance columns

Ultra-high field MRI can functionally image the cerebral cortex of human subjects at the submillimeter scale of cortical columns and laminae. Here, we investigate both in concert, by imaging ocular dominance columns (ODCs) in primary visual cortex (V1) across different cortical depths. We ensured that putative ODC patterns in V1 (a) are stable across runs, sessions, and scanners located in different continents, (b) have a width (~1.3 mm) expected from post-mortem and animal work and (c) are absent at the retinotopic location of the blind spot. We then dissociated the effects of bottom-up thalamo-cortical input and attentional feedback processes on activity in V1 across cortical depth. Importantly, the separation of bottom-up information flows into ODCs allowed us to validly compare attentional conditions while keeping the stimulus identical throughout the experiment. We find that, when correcting for draining vein effects and using both model-based and model-free approaches, the effect of monocular stimulation is largest at deep and middle cortical depths. Conversely, spatial attention influences BOLD activity exclusively near the pial surface. Our findings show that simultaneous interrogation of columnar and laminar dimensions of the cortical fold can dissociate thalamocortical inputs from top-down processing, and allow the investigation of their interactions without any stimulus manipulation.

Flexible Working Memory Through Selective Gating and Attentional Tagging.

Working memory is essential: it serves to guide intelligent behavior of humans and nonhuman primates when task-relevant stimuli are no longer present to the senses. Moreover, complex tasks often require that multiple working memory representations can be flexibly and independently maintained, prioritized, and updated according to changing task demands. Thus far, neural network models of working memory have been unable to offer an integrative account of how such control mechanisms can be acquired in a biologically plausible manner. Here, we present WorkMATe, a neural network architecture that models cognitive control over working memory content and learns the appropriate control operations needed to solve complex working memory tasks. Key components of the model include a gated memory circuit that is controlled by internal actions, encoding sensory information through untrained connections, and a neural circuit that matches sensory inputs to memory content. The network is trained by means of a biologically plausible reinforcement learning rule that relies on attentional feedback and reward prediction errors to guide synaptic updates. We demonstrate that the model successfully acquires policies to solve classical working memory tasks, such as delayed recognition and delayed pro-saccade/anti-saccade tasks. In addition, the model solves much more complex tasks, including the hierarchical 12-AX task or the ABAB ordered recognition task, both of which demand an agent to independently store and updated multiple items separately in memory. Furthermore, the control strategies that the model acquires for these tasks subsequently generalize to new task contexts with novel stimuli, thus bringing symbolic production rule qualities to a neural network architecture. As such, WorkMATe provides a new solution for the neural implementation of flexible memory control.

Are attentional instruction and feedback type affect on learning of postural and supra-postural tasks?

Optimum postural control and balance is dependent on the individual, the environment, and the task limitations. Thus, the present study investigated the effect of attentional instruction and feedback type on postural and supra-postural tasks. The 96 participants aged 11-19years with attention deficit hyperactivity disorder (ADHD) were randomly assigned to one of the eight groups such as attentional instruction (internal and external), feedback (external and internal), and task (postural and supra-postural). Following a pre-test, the participants underwent four training sessions. Each session included 20 trials of 30s with 20s of rest between trials. Twenty-four hours after the training session, they performed two trials of warm-up and then took part in a retention test. Twenty-four hours after the retention test, they again performed two trials of warm-up and then participated in the transfer test. The result showed that the external attentional feedback and external attentional instruction groups performed better on supra-postural and postural tasks than the other experimental groups (P > 0.05). The external attentional instruction group performed better on postural and supra-postural tasks in the delayed retention and transfer tests (P > 0.05). Also, the external feedback group scored highest on postural and supra-postural tasks in the delayed retention and transfer tests. The results suggest that external attentional feedback and instruction is more effective than internal attention when learning supra-postural tasks to maintain balance.

Audio object classification using distributed beliefs and attention.

One of the unique characteristics of human hearing is its ability to recognize acoustic objects even in presence of severe noise and distortions. In this work, we explore two mechanisms underlying this ability: 1) redundant mapping of acoustic waveforms along distributed latent representations and 2) adaptive feedback based on prior knowledge to selectively attend to targets of interest. We propose a bio-mimetic account of acoustic object classification by developing a novel distributed deep belief network validated for the task of robust acoustic object classification using the UrbanSound database. The proposed distributed belief network (DBN) encompasses an array of independent sub-networks trained generatively to capture different abstractions of natural sounds. A supervised classifier then performs a readout of this distributed mapping. The overall architecture not only matches the state of the art system for acoustic object classification but leads to significant improvement over the baseline in mismatched noisy conditions (31.4% relative improvement in 0dB conditions). Furthermore, we incorporate mechanisms of attentional feedback that allows the DBN to deploy local memories of sounds targets estimated at multiple views to bias network activation when attending to a particular object. This adaptive feedback results in further improvement of object classification in unseen noise conditions (relative improvement of 54% over the baseline in 0dB conditions).

Development of spatial suppression surrounding the focus of visual attention.

In adulthood, research has demonstrated that surrounding the spatial location of attentional focus is a suppressive field, resulting from top-down attention promoting the processing of relevant stimuli and inhibiting surrounding distractors (e.g., Hopf et al., 2006). It is not fully known, however, how this phenomenon manifests during development. This is an important question since attention processes are likely even more critical in development because of their potential impact on learning and day-to-day activities. The current study examined whether spatial suppression surrounding the focus of visual attention, a predicted by-product of top-down attentional modulation, is observed in development. A wide age range separated in six incremental age levels was included, allowing for a detailed examination of potential differences in the effect of attention on visual processing across development. Participants between 12 and 27 years of age exhibited spatial suppression surrounding their focus of visual attention. Their accuracy increased as a function of the separation distance between a spatially cued (and attended) target and a second target, suggesting that a ring of suppression surrounded the attended target. Attentional surround suppression was not observed in 8- to 11-years-olds, even with a longer spatial cue presentation time, demonstrating that the lack of the effect at these ages is not due to slowed attentional feedback processes. Our findings demonstrate that top-down attentional processes exhibit functional maturity beginning around 12 years of age with continuing maturation of their expression until 17, which likely impacts education and the diagnosis of visual and cognitive clinical pathologies.

Novel Upper-Limb Rehabilitation System Based on Attention Technology for Post-Stroke Patients: A Preliminary Study

In this paper, we proposed an upper-limb post-stroke rehabilitation system integrating a motion tracking device (MTD), a portable electroencephalogram (EEG) device for an attentional feedback, and interactive virtual reality (VR) game with the goal to assist patients in upper-limb rehabilitation. Fifteen post-stroke patients were recruited and randomly assigned to a control group (A) or one of two experimental groups (B and C). Group B played the game using a MTD and group C played it using a MTD and brain–computer-interface-based attention-monitoring EEG device. In group C, patients’ attention was measured in real time using the EEG while the patients performed tasks; visual and auditory stimuli were emitted when their attention lowered. The primary outcome was a change in score on the upper extremity section of the Fugl–Meyer assessment, which was used to evaluate the severity of motor impairment and indicate any improvement of motor function. Improvement in motor function, associated with game performance, was found in group C. Based on their performance quality during 12 training sessions, the higher performance of group C patients in the VR game was significantly correlated with attention level and motor performance. Higher attention level is associated with higher game performance after 12 training sessions, and our MTD-EEG-VR training system may facilitate the improvement of motor function and assist patients in upper-limb rehabilitation. Our MTD-EEG-VR game with the attentional EEG-feedback device is a potential intervention for improving motor function in patients with stroke.

Coding of spatial attention priorities and object features in the macaque lateral intraparietal cortex.

Primate posterior parietal cortex (PPC) is known to be involved in controlling spatial attention. Neurons in one part of the PPC, the lateral intraparietal area (LIP), show enhanced responses to objects at attended locations. Although many are selective for object features, such as the orientation of a visual stimulus, it is not clear how LIP circuits integrate feature‐selective information when providing attentional feedback about behaviorally relevant locations to the visual cortex. We studied the relationship between object feature and spatial attention properties of LIP cells in two macaques by measuring the cells' orientation selectivity and the degree of attentional enhancement while performing a delayed match‐to‐sample task. Monkeys had to match both the location and orientation of two visual gratings presented separately in time. We found a wide range in orientation selectivity and degree of attentional enhancement among LIP neurons. However, cells with significant attentional enhancement had much less orientation selectivity in their response than cells which showed no significant modulation by attention. Additionally, orientation‐selective cells showed working memory activity for their preferred orientation, whereas cells showing attentional enhancement also synchronized with local neuronal activity. These results are consistent with models of selective attention incorporating two stages, where an initial feature‐selective process guides a second stage of focal spatial attention. We suggest that LIP contributes to both stages, where the first stage involves orientation‐selective LIP cells that support working memory of the relevant feature, and the second stage involves attention‐enhanced LIP cells that synchronize to provide feedback on spatial priorities.

Attentional spreading over feature attributes and feature dimensions:Distributed top-down modulation or joint neural coding?

Attention is an important prerequisite for visual information processing. It allows the brain to focus on particular aspects of a visual scene, and enables or enhances perception of complex shapes and objects. However, attentional selection is an intricate computational problem, since the target of attentional deployment is often given by an arbitrary combination of features such as the location of an object having a conjunction of particular properties (features), and it is subjected to various neural constraints such as a given anatomical connectivity and broad tuning of neurons. How the brain solves this problem to boost the processing of combinations of different features that are represented across multiple neural areas is largely unknown. Recently, progress in understanding the properties of joint attentional selection was made in a psychophysical study investigating attentional spreading within and across objects [1]: Subjects were asked to report color and speed changes on one of two overlapping random dot patterns. Only one of the features was unique for each object, while the other was shared by both. Reaction times (RTs) recorded under different cueing conditions demonstrated the co-selection of unattended features, with attention spreading from the attended feature attribute in a particular feature dimension to other feature attributes and other feature dimensions. Importantly, this processing benefit was not restricted to the task-relevant object but extended to the unattended object. It is an open question how these observations can be modeled and understood in a coherent framework. In our contribution, we propose two structurally simple models, implementing two complementary neural mechanisms: The first model assumes that the specificity of anatomical connections providing attentional feedback from higher cortical areas is constrained. Consequently, top-down modulation of neural activity in lower visual areas is broadly tuned, targeting all cells representing the cued feature dimension(s) with only a weak preference for the cued feature attribute(s). As a result, attention spreads to uncued feature attributes and to jointly cued feature dimensions. In the second model we assume joint coding of stimulus features such that neurons having a preference for a particular motion direction also have a preference for a specific color. We also assume that neurons are not always perfectly tuned to their preferred feature(s), thus providing a (small) response to non-preferred feature values as well. Attentional feedback in this model precisely targets cells tuned for the cued feature attribute, or the combination of attributes. In this approach, attentional spreading to uncued feature dimensions is mediated by joint tuning, whereas spreading to uncued feature attributes in the same feature dimension is mediated by imperfect tuning. It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1). The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.

External-Focus Feedback Benefits Free-Throw Learning in Children

Purpose: Considerable research supports the motor-learning advantage associated with an external focus of attention; however, very few studies have attempted to generalize these findings to children especially with attentional focus feedback. Therefore, the purpose of this study was to determine the effect of attentional focus feedback on motor learning in children. Method: Boys (n = 14) and girls (n = 14) aged 9 to 11 years old were randomly assigned to 1 of 2 gender-stratified groups: (a) internal-focus feedback or (b) external-focus feedback. Following initial instructions and task demonstration, participants performed 100 modified free throws over 2 days while receiving feedback statements respective to their attentional focus condition. Approximately 24 hr later, participants performed a retention test consisting of 20 additional free throws. Participants were also asked to respond to a retrospective verbal report at the end of each day to serve as a manipulation check. Results: Results of the analysis revealed a statistically significant learning advantage for participants receiving external-focus feedback, and retrospective verbal reports provide support for the self-invoking trigger and constrained action hypotheses. Conclusions: Future research should continue to incorporate retrospective verbal reports and explore potential causal links between internal attentional focus and self-evaluation.

How attention can create synaptic tags for the learning of working memories in sequential tasks.

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions.

Attention alters orientation processing in the human lateral geniculate nucleus.

Orientation selectivity is a cornerstone property of vision, commonly believed to emerge in the primary visual cortex (V1). Here, we demonstrate that reliable orientation information can be detected even earlier, in the human lateral geniculate nucleus (LGN), and that attentional feedback selectively alters these orientation responses. This attentional modulation may allow the visual system to modify incoming feature-specific signals at the earliest possible processing site.

A learning rule that explains how rewards teach attention

Many theories propose that top-down attentional signals control processing in sensory cortices by modulating neural activity. But who controls the controller? Here we investigate how a biologically plausible neural reinforcement learning scheme can create higher order representations and top-down attentional signals. The learning scheme trains neural networks using two factors that gate Hebbian plasticity: (1) an attentional feedback signal from the response-selection stage to earlier processing levels; and (2) a globally available neuromodulator that encodes the reward prediction error. We demonstrate how the neural network learns to direct attention to one of two coloured stimuli that are arranged in a rank-order. Like monkeys trained on this task, the network develops units that are tuned to the rank-order of the colours and it generalizes this newly learned rule to previously unseen colour combinations. These results provide new insight into how individuals can learn to control attention as a function of reward contingency.

A review of the mechanisms by which attentional feedback shapes visual selectivity.

The glut of information available for the brain to process at any given moment necessitates an efficient attentional system that can 'pick and choose' what information receives prioritized processing. A growing body of work, spanning numerous methodologies and species, reveals that one powerful way in which attending to an item separates the wheat from the chaff is by altering a basic response property in the brain: neuronal selectivity. Selectivity is a cornerstone response property, largely dictating our ability to represent and interact with the environment. Although it is likely that selectivity is altered throughout many brain areas, here we focus on how directing attention to an item affects selectivity in the visual system, where this response property is generally more well characterized. First, we review the neural architecture supporting selectivity, and then discuss the various changes that could occur in selectivity for an attended item. In a survey of the literature, spanning neurophysiology, neuroimaging and psychophysics, we reveal that there is general convergence regarding the manner with which selectivity is shaped by attentional feedback. In a nutshell, the literature suggests that the type of changes in selectivity that manifest appears to depend on the type of attention being deployed: whereas directing spatial attention towards an item only alters spatial selectivity, directing feature-based attention can alter the selectivity of attended features.

Lesions of prefrontal cortex reduce attentional modulation of neuronal responses and synchrony in V4.

It is widely held that the frontal eye field (FEF) in prefrontal cortex (PFC) modulates processing in visual cortex with attention, although the evidence for a necessary role is equivocal. To help identify critical sources of attentional feedback to area V4, we surgically removed the entire lateral PFC, including the FEF, in one hemisphere and transected the corpus callosum and anterior commisure in two macaques. This deprived V4 of PFC input in one hemisphere while keeping the other hemisphere intact. In the absence of PFC, attentional effects on neuronal responses and synchrony in V4 were significantly reduced and the remaining effects of attention were delayed in time indicating a critical role of PFC. Conversely, distracters captured attention and influenced V4 responses. However, because the effects of attention in V4 were not eliminated by PFC lesions, other sources of top-down attentional control signals to visual cortex must exist outside of PFC.

Functional size of human visual area V1: A neural correlate of top–down attention

Heavy demands are placed on the brain's attentional capacity when selecting a target item in a cluttered visual scene, or when reading. It is widely accepted that such attentional selection is mediated by top–down signals from higher cortical areas to early visual areas such as the primary visual cortex (V1). Further, it has also been reported that there is considerable variation in the surface area of V1. This variation may impact on either the number or specificity of attentional feedback signals and, thereby, the efficiency of attentional mechanisms. In this study, we investigated whether individual differences between humans performing attention-demanding tasks can be related to the functional area of V1. We found that those with a larger representation in V1 of the central 12° of the visual field as measured using BOLD signals from fMRI were able to perform a serial search task at a faster rate. In line with recent suggestions of the vital role of visuo-spatial attention in reading, the speed of reading showed a strong positive correlation with the speed of visual search, although it showed little correlation with the size of V1. The results support the idea that the functional size of the primary visual cortex is an important determinant of the efficiency of selective spatial attention for simple tasks, and that the attentional processing required for complex tasks like reading are to a large extent determined by other brain areas and inter-areal connections.

Reading into neuronal oscillations in the visual system: implications for developmental dyslexia.

While phonological impairments are common in developmental dyslexia, there has recently been much debate as to whether there is a causal link between the phonological difficulties and the reading problem. An alternative suggestion has been gaining ground that the core deficit in dyslexia is in visual attentional mechanisms. If so, the visual aetiology may be at any of a number of sites along the afferent magnocellular pathway or in the dorsal cortical stream that are all essential for a visuo-spatial attentional feedback to the primary visual cortex. It has been suggested that the same circuits and pathways of top-down attention used for serial visual search are used for reading. Top-down signals from the dorsal parietal areas to primary visual cortex serially highlight cortical locations representing successive letters in a text before they can be recognized and concatenated into a word. We had shown in non-human primates that the mechanism of such a top-down feedback in a visual attention task uses synchronized neuronal oscillations at the lower end of the gamma frequency range. It is no coincidence that reading graphemes in a text also happens at the low gamma frequencies. The basic proposal here is that each cycle of gamma oscillation focuses an attentional spotlight on the primary visual cortical representation of just one or two letters before sequential recognition of letters and their concatenation into word strings. The timing, period, envelope, amplitude, and phase of the synchronized oscillations modulating the incoming signals in the striate cortex would have a profound influence on the accuracy and speed of reading. Thus, the general temporal sampling difficulties in dyslexic subjects may impact reading not necessarily by causing phonological deficits, but by affecting the spatio-temporal parsing of the visual input within the visual system before these signals are used for letter and word recognition.