Top-down control of visual attention

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

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

Common and distinct neural mechanisms of attention

Despite a constant deluge of sensory stimulation, only a fraction of it is used to guide behavior. This selective processing is generally referred to as attention, and much research has focused on the neural mechanisms controlling it. Recently, research has broadened to include more ways by which different species selectively process sensory information, whether due to the sensory input itself or to different behavioral and brain states. This work has produced a complex and disjointed body of evidence across different species and forms of attention. However, it has also provided opportunities to better understand the breadth of attentional mechanisms. Here, we summarize the evidence that suggests that different forms of selective processing are supported by mechanisms both common and distinct.

Distinct feedforward and feedback pathways for cell-type specific attention effects

Selective attention is thought to depend on enhanced firing activity in extrastriate areas. Theories suggest that this enhancement depends on selective inter-areal communication via gamma (30-80 Hz) phase-locking. To test this, we simultaneously recorded from different cell types and cortical layers of macaque V1 and V4. We find that while V1-V4 gamma phase-locking between local field potentials increases with attention, the V1 gamma rhythm does not engage V4 excitatory-neurons, but only fast-spiking interneurons in L4 of V4. By contrast, attention enhances V4 spike-rates in both excitatory and inhibitory cells, most strongly in L2/3. The rate increase in L2/3 of V4 precedes V1 in time. These findings suggest enhanced signal transmission with attention does not depend on inter-areal gamma phase-locking and show that the endogenous gamma rhythm has cell-type- and layer-specific effects on downstream target areas. Similar findings were made in the mouse visual system, based on opto-tagging of identified interneurons.

Impact of relative and absolute values on orienting attention in time

Reward has been known to render the reward-associated stimulus more salient to block effective attentional orienting in space. However, whether and how reward influences goal-directed attention in time remains unclear. Here, we used a modified attentional cueing paradigm to explore the effect of reward on temporal attention, in which the valid targets were given a low monetary reward and invalid targets were given a high monetary reward. The results showed that the temporal cue validity effect was significantly smaller when the competitive reward structure was employed (Experiment 1), and we ruled out the possibility that the results were due to the practice effect (Experiment 2a) or a reward-promoting effect (Experiment 2b). When further strengthening the intensity of the reward from 1:10 to 1:100 (Experiment 3), we found a similar pattern of results to those in Experiment 1. These results suggest that reward information which was based on relative instead of absolute values can weaken, but not reverse, the orienting attention in time.

Application of transcranial alternating current stimulation to improve eSports-related cognitive performance

Introduction

Electronic Sports (eSports) is a popular and still emerging sport. Multiplayer Online Battle Arena (MOBA) and First/Third Person Shooting Games (FPS/TPS) require excellent visual attention abilities. Visual attention involves specific frontal and parietal areas, and is associated with alpha coherence. Transcranial alternating current stimulation (tACS) is a principally suitable tool to improve cognitive functions by modulation of regional oscillatory cortical networks that alters regional and larger network connectivity.

Methods

In this single-blinded crossover study, 27 healthy college students were recruited and exposed to 10 Hz tACS of the right frontoparietal network. Subjects conducted a Visual Spatial Attention Distraction task in three phases: T0 (pre-stimulation), T1 (during stimulation), T2 (after-stimulation), and an eSports performance task which contained three games ("Exact Aiming," "Flick Aiming," "Press Reaction") before and after stimulation.

Results

The results showed performance improvements in the "Exact Aiming" task and hint for a prevention of reaction time performance decline in the "Press Reaction" task in the real, as compared to the sham stimulation group. We also found a significant decrease of reaction time in the visual spatial attention distraction task at T1 compared to T0 in the real, but not sham intervention group. However, accuracy and inverse efficiency scores (IES) did not differ between intervention groups in this task.

Discussion

These results suggest that 10 Hz tACS over the right frontal and parietal cortex might improve eSports-related skill performance in specific tasks, and also improve visual attention in healthy students during stimulation. This tACS protocol is a potential tool to modulate neurocognitive performance involving tracking targets, and might be a foundation for the development of a new concept to enhance eSports performance. This will require however proof in real life scenarios, as well optimization.

Subcortical contributions to the sense of body ownership

The sense of body ownership (i.e. the feeling that our body or its parts belong to us) plays a key role in bodily self-consciousness and is believed to stem from multisensory integration. Experimental paradigms such as the rubber hand illusion have been developed to allow the controlled manipulation of body ownership in laboratory settings, providing effective tools for investigating malleability in the sense of body ownership and the boundaries that distinguish self from other. Neuroimaging studies of body ownership converge on the involvement of several cortical regions, including the premotor cortex and posterior parietal cortex. However, relatively less attention has been paid to subcortical structures that may also contribute to body ownership perception, such as the cerebellum and putamen. Here, on the basis of neuroimaging and neuropsychological observations, we provide an overview of relevant subcortical regions and consider their potential role in generating and maintaining a sense of ownership over the body. We also suggest novel avenues for future research targeting the role of subcortical regions in making sense of the body as our own.

Time-varying generalized linear models: characterizing and decoding neuronal dynamics in higher visual areas

To create a behaviorally relevant representation of the visual world, neurons in higher visual areas exhibit dynamic response changes to account for the time-varying interactions between external (e.g., visual input) and internal (e.g., reward value) factors. The resulting high-dimensional representational space poses challenges for precisely quantifying individual factors' contributions to the representation and readout of sensory information during a behavior. The widely used point process generalized linear model (GLM) approach provides a powerful framework for a quantitative description of neuronal processing as a function of various sensory and non-sensory inputs (encoding) as well as linking particular response components to particular behaviors (decoding), at the level of single trials and individual neurons. However, most existing variations of GLMs assume the neural systems to be time-invariant, making them inadequate for modeling nonstationary characteristics of neuronal sensitivity in higher visual areas. In this review, we summarize some of the existing GLM variations, with a focus on time-varying extensions. We highlight their applications to understanding neural representations in higher visual areas and decoding transient neuronal sensitivity as well as linking physiology to behavior through manipulation of model components. This time-varying class of statistical models provide valuable insights into the neural basis of various visual behaviors in higher visual areas and hold significant potential for uncovering the fundamental computational principles that govern neuronal processing underlying various behaviors in different regions of the brain.

Transcranial Focused Ultrasound Remotely Modulates Extrastriate Visual Cortex with Subregion Specificity

Low-intensity transcranial focused ultrasound (tFUS) has emerged as a powerful neuromodulation tool characterized by its deep penetration and precise spatial targeting to influence neural activity. Our study directed low-intensity tFUS stimulation onto a region of prefrontal cortex (the frontal eye field, or FEF) of a rhesus macaque to examine its impact on a remote site, the extrastriate visual cortex (area V4). This pair of cortical regions form a top-down modulatory circuit that has been studied extensively with electrical microstimulation. To measure the impact of tFUS stimulation, we recorded local field potentials (LFPs) and multi-unit spiking activities from a multi-electrode array implanted in the visual cortex. To deliver tFUS stimulation, we leveraged a customized 128-element random array ultrasound transducer with improved spatial targeting. We observed that tFUS stimulation in FEF produced modulation of V4 neuronal activity, either through enhancement or suppression, dependent on the pulse repetition frequency of the tFUS stimulation. Electronically steering the transcranial ultrasound focus through the targeted FEF cortical region produced changes in the level of modulation, indicating that the tFUS stimulation was spatially targeted within FEF. Modulation of V4 activity was confined to specific frequency bands, and this modulation was dependent on the presence or absence of a visual stimulus during tFUS stimulation. A control study targeting the insula produced no effect, emphasizing the region-specific nature of tFUS neuromodulation. Our findings shed light on the capacity of tFUS to modulate specific neural pathways and provide a comprehensive understanding of its potential applications for neuromodulation within brain networks.

Spatiotemporal dynamics of self-generated imagery reveal a reverse cortical hierarchy from cue-induced imagery

Visual imagery allows for the construction of rich internal experience in our mental world. However, it has remained poorly understood how imagery experience derives volitionally as opposed to being cue driven. Here, using electroencephalography and functional magnetic resonance imaging, we systematically investigate the spatiotemporal dynamics of self-generated imagery by having participants volitionally imagining one of the orientations from a learned pool. We contrast self-generated imagery with cue-induced imagery, where participants imagined line orientations based on associative cues acquired previously. Our results reveal overlapping neural signatures of cue-induced and self-generated imagery. Yet, these neural signatures display substantially differential sensitivities to the two types of imagery: self-generated imagery is supported by an enhanced involvement of the anterior cortex in representing imagery contents. By contrast, cue-induced imagery is supported by enhanced imagery representations in the posterior visual cortex. These results jointly support a reverse cortical hierarchy in generating and maintaining imagery contents in self-generated versus externally cued imagery.

Dynamic top-down biasing implements rapid adaptive changes to individual movements

Complex behaviors depend on the coordinated activity of neural ensembles in interconnected brain areas. The behavioral function of such coordination, often measured as co-fluctuations in neural activity across areas, is poorly understood. One hypothesis is that rapidly varying co-fluctuations may be a signature of moment-by-moment task-relevant influences of one area on another. We tested this possibility for error-corrective adaptation of birdsong, a form of motor learning which has been hypothesized to depend on the top-down influence of a higher-order area, LMAN (lateral magnocellular nucleus of the anterior nidopallium), in shaping moment-by-moment output from a primary motor area, RA (robust nucleus of the arcopallium). In paired recordings of LMAN and RA in singing birds, we discovered a neural signature of a top-down influence of LMAN on RA, quantified as an LMAN-leading co-fluctuation in activity between these areas. During learning, this co-fluctuation strengthened in a premotor temporal window linked to the specific movement, sequential context, and acoustic modification associated with learning. Moreover, transient perturbation of LMAN activity specifically within this premotor window caused rapid occlusion of pitch modifications, consistent with LMAN conveying a temporally localized motor-biasing signal. Combined, our results reveal a dynamic top-down influence of LMAN on RA that varies on the rapid timescale of individual movements and is flexibly linked to contexts associated with learning. This finding indicates that inter-area co-fluctuations can be a signature of dynamic top-down influences that support complex behavior and its adaptation.

A recruitment through coherence theory of working memory

The interactions between prefrontal cortex and other areas during working memory have been studied for decades. Here we outline a conceptual framework describing interactions between these areas during working memory, and review evidence for key elements of this model. We specifically suggest that a top-down signal sent from prefrontal to sensory areas drives oscillations in these areas. Spike timing within sensory areas becomes locked to these working-memory-driven oscillations, and the phase of spiking conveys information about the representation available within these areas. Downstream areas receiving these phase-locked spikes from sensory areas can recover this information via a combination of coherent oscillations and gating of input efficacy based on the phase of their local oscillations. Although the conceptual framework is based on prefrontal interactions with sensory areas during working memory, we also discuss the broader implications of this framework for flexible communication between brain areas in general.

Electrophysiological evidence for increased auditory crossmodal activity in adult ADHD

Background

Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by core symptoms of inattention, and/or impulsivity and hyperactivity. In order to understand the basis for this multifaceted disorder, the investigation of sensory processing aberrancies recently reaches more interest. For example, during the processing of auditory stimuli comparable low sensory thresholds account for symptoms like higher distractibility and auditory hypersensitivity in patients with ADHD. It has further been shown that deficiencies not only exist on an intramodal, but also on a multimodal level. There is evidence that the visual cortex shows more activation during a focused auditory task in adults with ADHD than in healthy controls. This crossmodal activation is interpreted as the reallocation of more attentional resources to the visual domain as well as deficient sensory inhibition. In this study, we used, for the first time, electroencephalography to identify a potential abnormal regulated crossmodal activation in adult ADHD.

Methods

15 adult subjects with clinically diagnosed ADHD and 14 healthy controls comparable in age and gender were included. ERP components P50, P100, N100, P200 and N200 were measured during the performance of a unimodal auditory and visual discrimination task in a block design. Sensory profiles and ADHD symptoms were assessed with inattention as well as childhood ADHD scores. For evaluating intramodal and crossmodal activations, we chose four EEG channels for statistical analysis and group-wise comparison.

Results

At the occipital channel O2 that reflects possible crossmodal activations, a significantly enhanced P200 amplitude was measured in the patient group. At the intramodal channels, a significantly enhanced N200 amplitude was observed in the control group. Statistical analysis of behavioral data showed poorer performance of subjects with ADHD as well as higher discrimination thresholds. Further, the correlation of the assessed sensory profiles with the EEG parameters revealed a negative correlation between the P200 component and sensation seeking behavior.

Conclusion

Our findings show increased auditory crossmodal activity that might reflect an altered stimulus processing resource allocation in ADHD. This might induce consequences for later, higher order attentional deployment. Further, the enhanced P200 amplitude might reflect more sensory registration and therefore deficient inhibition mechanisms in adults with ADHD.

Altered Gaze Control During Emotional Face Exploration in Patients With Amyotrophic Lateral Sclerosis

OBJECTIVES

Up to 50% of patients with amyotrophic lateral sclerosis (ALS) present with cognitive problems and behavioral dysfunctions including recognition of human faces presenting different emotions. We investigated whether impaired processing of emotional faces is associated with abnormal scan paths during visual exploration.

METHODS

Cognitively unimpaired patients with ALS (n = 45) and matched healthy controls (n = 37) underwent neuropsychological assessment and video-based eye tracking. Eye movements were recorded while participants visually explored faces expressing different emotions (neutral, disgusted, happy, fearful, and sad) and houses mimicking faces.

RESULTS

Compared with controls, patients with ALS fixated significantly longer to regions which are not relevant for emotional information when faces expressed fear (p = 0.007) and disgust (p = 0.006), whereas the eyes received less attention in faces expressing disgust (p = 0.041). Fixation duration in any area of interest was not significantly associated with the cognitive state or clinical symptoms of disease severity.

DISCUSSION

In cognitively unimpaired patients with ALS, altered gaze patterns while visually exploring faces expressing different emotions might derive from impaired top-down attentional control with possible involvement of subliminal frontotemporal areas. This may account for indistinctness in emotion recognition reported in previous studies because nonsalient features retrieve more attention compared with salient areas. Current findings may indicate distinct emotion processing dysfunction of ALS pathology, which may be different from, for example, executive dysfunction.

Integrated effects of top-down attention and statistical learning during visual search: An EEG study

The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the "winner" element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

Frontal-occipital phase synchronization predicts occipital alpha power in perceptual decision-making

Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4-30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09862-7.

Task Cortical Connectivity Reveals Different Network Reorganizations between Mild Stroke Patients with Cortical and Subcortical Lesions

Accumulating efforts have been made to investigate cognitive impairment in stroke patients, but little has been focused on mild stroke. Research on the impact of mild stroke and different lesion locations on cognitive impairment is still limited. To investigate the underlying mechanisms of cognitive dysfunction in mild stroke at different lesion locations, electroencephalograms (EEGs) were recorded in three groups (40 patients with cortical stroke (CS), 40 patients with subcortical stroke (SS), and 40 healthy controls (HC)) during a visual oddball task. Power envelope connectivity (PEC) was constructed based on EEG source signals, followed by graph theory analysis to quantitatively assess functional brain network properties. A classification framework was further applied to explore the feasibility of PEC in the identification of mild stroke. The results showed worse behavioral performance in the patient groups, and PECs with significant differences among three groups showed complex distribution patterns in frequency bands and the cortex. In the delta band, the global efficiency was significantly higher in HC than in CS (p = 0.011), while local efficiency was significantly increased in SS than in CS (p = 0.038). In the beta band, the small-worldness was significantly increased in HC compared to CS (p = 0.004). Moreover, the satisfactory classification results (76.25% in HC vs. CS, and 80.00% in HC vs. SS) validate the potential of PECs as a biomarker in the detection of mild stroke. Our findings offer some new quantitative insights into the complex mechanisms of cognitive impairment in mild stroke at different lesion locations, which may facilitate post-stroke cognitive rehabilitation.

Top-down control of human motor thalamic neuronal activity during the auditory oddball task

The neurophysiology of selective attention in visual and auditory systems has been studied in animal models but not with single unit recordings in human. Here, we recorded neuronal activity in the ventral intermediate nucleus as well as the ventral oral anterior, and posterior nuclei of the motor thalamus in 25 patients with parkinsonian (n = 6) and non-parkinsonian tremors (n = 19) prior to insertion of deep brain stimulation electrodes while they performed an auditory oddball task. In this task, patients were requested to attend and count the randomly occurring odd or "deviant" tones, ignore the frequent standard tones and report the number of deviant tones at trial completion. The neuronal firing rate decreased compared to baseline during the oddball task. Inhibition was specific to auditory attention as incorrect counting or wrist flicking to the deviant tones did not produce such inhibition. Local field potential analysis showed beta (13-35 Hz) desynchronization in response to deviant tones. Parkinson's disease patients off medications had more beta power than the essential tremor group but less neuronal modulation of beta power to the attended tones, suggesting that dopamine modulates thalamic beta oscillations for selective attention. The current study demonstrated that ascending information to the motor thalamus can be suppressed during auditory attending tasks, providing indirect evidence for the searchlight hypothesis in humans. These results taken together implicate the ventral intermediate nucleus in non-motor cognitive functions, which has implications for the brain circuitry for attention and the pathophysiology of Parkinson's disease.

Human generalization of internal representations through prototype learning with goal-directed attention

The world is overabundant with feature-rich information obscuring the latent causes of experience. How do people approximate the complexities of the external world with simplified internal representations that generalize to novel examples or situations? Theories suggest that internal representations could be determined by decision boundaries that discriminate between alternatives, or by distance measurements against prototypes and individual exemplars. Each provide advantages and drawbacks for generalization. We therefore developed theoretical models that leverage both discriminative and distance components to form internal representations via action-reward feedback. We then developed three latent-state learning tasks to test how humans use goal-oriented discrimination attention and prototypes/exemplar representations. The majority of participants attended to both goal-relevant discriminative features and the covariance of features within a prototype. A minority of participants relied only on the discriminative feature. Behaviour of all participants could be captured by parameterizing a model combining prototype representations with goal-oriented discriminative attention.

Explaining Integration of Evidence Separated by Temporal Gaps with Frontoparietal Circuit Models

Perceptual decisions rely on accumulating sensory evidence over time. However, the accumulation process is complicated in real life when evidence resulted from separated cues over time. Previous studies demonstrate that participants are able to integrate information from two separated cues to improve their performance invariant to an interval between the cues. However, there is no neural model that can account for accuracy and confidence in decisions when there is a time interval in evidence. We used behavioral and EEG datasets from a visual choice task -Random dot motion- with separated evidence to investigate three candid distributed neural networks. We showed that decisions based on evidence accumulation by separated cues over time are best explained by the interplay of recurrent cortical dynamics of centro-parietal and frontal brain areas while an uncertainty-monitoring module included in the model.

Age-related differences in frontoparietal activation for target and distractor singletons during visual search

Age-related decline in visual search performance has been associated with different patterns of activation in frontoparietal regions using functional magnetic resonance imaging (fMRI), but whether these age-related effects represent specific influences of target and distractor processing is unclear. Therefore, we acquired event-related fMRI data from 68 healthy, community-dwelling adults ages 18-78 years, during both conjunction (T/F target among rotated Ts and Fs) and feature (T/F target among Os) search. Some displays contained a color singleton that could correspond to either the target or a distractor. A diffusion decision analysis indicated age-related increases in sensorimotor response time across all task conditions, but an age-related decrease in the rate of evidence accumulation (drift rate) was specific to conjunction search. Moreover, the color singleton facilitated search performance when occurring as a target and disrupted performance when occurring as a distractor, but only during conjunction search, and these effects were independent of age. The fMRI data indicated that decreased search efficiency for conjunction relative to feature search was evident as widespread frontoparietal activation. Activation within the left insula mediated the age-related decrease in drift rate for conjunction search, whereas this relation in the FEF and parietal cortex was significant only for individuals younger than 30 or 44 years, respectively. Finally, distractor singletons were associated with significant parietal activation, whereas target singletons were associated with significant frontoparietal deactivation, and this latter effect increased with adult age. Age-related differences in frontoparietal activation therefore reflect both the overall efficiency of search and the enhancement from salient targets.

Efficient coding theory of dynamic attentional modulation

Activity of sensory neurons is driven not only by external stimuli but also by feedback signals from higher brain areas. Attention is one particularly important internal signal whose presumed role is to modulate sensory representations such that they only encode information currently relevant to the organism at minimal cost. This hypothesis has, however, not yet been expressed in a normative computational framework. Here, by building on normative principles of probabilistic inference and efficient coding, we developed a model of dynamic population coding in the visual cortex. By continuously adapting the sensory code to changing demands of the perceptual observer, an attention-like modulation emerges. This modulation can dramatically reduce the amount of neural activity without deteriorating the accuracy of task-specific inferences. Our results suggest that a range of seemingly disparate cortical phenomena such as intrinsic gain modulation, attention-related tuning modulation, and response variability could be manifestations of the same underlying principles, which combine efficient sensory coding with optimal probabilistic inference in dynamic environments.

Independent response modulation of visual cortical neurons by attentional and behavioral states

Sensory processing is influenced by cognitive and behavioral states, but how these states interact to modulate responses of individual neurons is unknown. We trained mice in a visual discrimination task wherein they attended to different locations within a hemifield while running or sitting still, enabling us to examine how visual responses are modulated by spatial attention and running behavior. We found that spatial attention improved discrimination performance and strengthened visual responses of excitatory neurons in the primary visual cortex whose receptive fields overlapped with the attended location. Although individual neurons were modulated by both spatial attention and running, the magnitudes of these influences were not correlated. While running-dependent modulation was stable across days, attentional modulation was dynamic, influencing individual neurons to different degrees after repeated changes in attentional states. Thus, despite similar effects on neural responses, spatial attention and running act independently with different dynamics, implying separable mechanisms for their implementation.

The perfect timing for multimodal integration is not the same in all L5 neurons

In this issue of Neuron, Rindner et al. (2022) demonstrate that subclasses of layer 5 pyramidal neurons in the parietal cortex integrate inputs from frontal and sensory areas supralinearly and with distinct temporal dynamics.

A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing

Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3 genes: parvalbumin (PV), somatostatin (SOM), or vasoactive intestinal polypeptide (VIP). This diversity of inhibition allows the flexible regulation of neuronal responses within and between cortical areas. However, the exact roles of these interneuron subtypes and of excitatory pyramidal (Pyr) neurons in regulating neuronal network activity and establishing perception (via interactions between feedforward sensory and feedback attentional signals) remain largely unknown. To explore the regulatory roles of distinct neuronal types in cortical computation, we developed a computational microcircuit model with biologically plausible visual cortex layers 2/3 that combined Pyr neurons and the 3 inhibitory interneuron subtypes to generate network activity. In simulations with our model, inhibitory signals from PV and SOM neurons preferentially induced neuronal firing at gamma (30-80 Hz) and beta (20-30 Hz) frequencies, respectively, in agreement with observed physiological results. Furthermore, our model indicated that rapid inhibition from VIP to SOM subtypes underlies marked attentional modulation for low-gamma frequency (30-50 Hz) in Pyr neuron responses. Our results suggest the distinct but cooperative roles of inhibitory interneuron subtypes in the establishment of visual perception.

Enhancing spiking neural networks with hybrid top-down attention

As the representatives of brain-inspired models at the neuronal level, spiking neural networks (SNNs) have shown great promise in processing spatiotemporal information with intrinsic temporal dynamics. SNNs are expected to further improve their robustness and computing efficiency by introducing top-down attention at the architectural level, which is crucial for the human brain to support advanced intelligence. However, this attempt encounters difficulties in optimizing the attention in SNNs largely due to the lack of annotations. Here, we develop a hybrid network model with a top-down attention mechanism (HTDA) by incorporating an artificial neural network (ANN) to generate attention maps based on the features extracted by a feedforward SNN. The attention map is then used to modulate the encoding layer of the SNN so that it focuses on the most informative sensory input. To facilitate direct learning of attention maps and avoid labor-intensive annotations, we propose a general principle and a corresponding weakly-supervised objective, which promotes the HTDA model to utilize an integral and small subset of the input to give accurate predictions. On this basis, the ANN and the SNN can be jointly optimized by surrogate gradient descent in an end-to-end manner. We comprehensively evaluated the HTDA model on object recognition tasks, which demonstrates strong robustness to adversarial noise, high computing efficiency, and good interpretability. On the widely-adopted CIFAR-10, CIFAR-100, and MNIST benchmarks, the HTDA model reduces firing rates by up to 50% and improves adversarial robustness by up to 10% with comparable or better accuracy compared with the state-of-the-art SNNs. The HTDA model is also verified on dynamic neuromorphic datasets and achieves consistent improvements. This study provides a new way to boost the performance of SNNs by employing a hybrid top-down attention mechanism.

Role of the locus coeruleus and basal forebrain in arousal and attention

Experimental evidence has implicated multiple neurotransmitter systems in either the direct or indirect modulation of cortical arousal and attention circuitry. In this review, we selectively focus on three such systems: 1) norepinephrine (NE)-containing neurons of the locus coeruleus (LC), 2) acetylcholine (ACh)-containing neurons of the basal forebrain (BF), and 3) parvalbumin (PV)-containing gamma-aminobutyric acid neurons of the BF. Whereas BF-PV neurons serve as a rapid and transient arousal system, LC-NE and BF-ACh neuromodulation are typically activated on slower but longer-lasting timescales. Recent findings suggest that the BF-PV system serves to rapidly respond to even subtle sensory stimuli with a microarousal. We posit that salient sensory stimuli, such as those that are threatening or predict the need for a response, will quickly activate the BF-PV system and subsequently activate both the BF-ACh and LC-NE systems if the circumstances require longer periods of arousal and vigilance. We suggest that NE and ACh have overlapping psychological functions with the main difference being the precise internal/environmental sensory situations/contexts that recruit each neurotransmitter system - a goal for future research to determine. Implications of dysfunction of each of these three attentional systems for our understanding of neuropsychiatric conditions are considered. Finally, the contemporary availability of research tools to selectively manipulate and measure the activity of these distinctive neuronal populations promises to answer longstanding questions, such as how various arousal systems influence downstream decision-making and motor responding.

Visual Attention in the Prefrontal Cortex

Voluntary attention selects behaviorally relevant signals for further processing while filtering out distracter signals. Neural correlates of voluntary visual attention have been reported across multiple areas of the primate visual processing streams, with the earliest and strongest effects isolated in the prefrontal cortex. In this article, I review evidence supporting the hypothesis that signals guiding the allocation of voluntary attention emerge in areas of the prefrontal cortex and reach upstream areas to modulate the processing of incoming visual information according to its behavioral relevance. Areas located anterior and dorsal to the arcuate sulcus and the frontal eye fields produce signals that guide the allocation of spatial attention. Areas located anterior and ventral to the arcuate sulcus produce signals for feature-based attention. Prefrontal microcircuits are particularly suited to supporting voluntary attention because of their ability to generate attentional template signals and implement signal gating and their extensive connectivity with the rest of the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Sequence learning, prediction, and replay in networks of spiking neurons

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

Essentially all data processed by mammals and many other living organisms is sequential. This holds true for all types of sensory input data as well as motor output activity. Being able to form memories of such sequential data, to predict future sequence elements, and to replay learned sequences is a necessary prerequisite for survival. It has been hypothesized that sequence learning, prediction and replay constitute the fundamental computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) constitutes an abstract powerful algorithm implementing this form of computation and has been proposed to serve as a model of neocortical processing. In this study, we are reformulating this algorithm in terms of known biological ingredients and mechanisms to foster the verifiability of the HTM hypothesis based on electrophysiological and behavioral data. The proposed model learns continuously in an unsupervised manner by biologically plausible, local plasticity mechanisms, and successfully predicts and replays complex sequences. Apart from establishing contact to biology, the study sheds light on the mechanisms determining at what speed we can process sequences and provides an explanation of fast sequence replay observed in the hippocampus and in the neocortex.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Concurrent frontal and parietal network TMS for modulating attention

Transcranial magnetic stimulation (TMS) has been applied to frontal eye field (FEF) and intraparietal sulcus (IPS) in isolation, to study their role in attention. However, these nodes closely interact in a "dorsal attention network". Here, we compared effects of inhibitory TMS applied to individually fMRI-localized FEF or IPS (single-node TMS), to effects of simultaneously inhibiting both regions ("network TMS"), and sham. We assessed attention performance using the lateralized attention network test, which captures multiple facets of attention: spatial orienting, alerting, and executive control. TMS showed no effects on alerting and executive control. For spatial orienting, only network TMS showed a reduction of the orienting effect in the right hemifield compared to the left hemifield, irrespective of the order of TMS application (IPS→FEF or FEF→IPS). Network TMS might prevent compensatory mechanisms within a brain network, which is promising for both research and clinical applications to achieve superior neuromodulation effects.

School-aged children diagnosed with an FASD exhibit visuo-cortical network disturbance: A magnetoencephalography (MEG) study

Children with prenatal alcohol exposure (PAE) often suffer from cognitive and neurobehavioral dysfunction throughout their lives, which may rise to a level of concern such that children receive a diagnosis under the fetal alcohol spectrum disorders (FASD) umbrella. Magnetoencephalography (MEG) contributes direct insight into neural processing and functional connectivity measures with temporal precision to understand cortical processing disorders that manifest during development. The impairment of perception may become more consequential among school-aged children with an FASD in the process of intellectual functioning and behavioral maturation. Fifty participants with the age range of 8-13 years participated in our study following parental informed consent and child assent. For each participant, visual responses were recorded using magnetoencephalography (MEG) while performing a prosaccade task with central stimuli (fovea centralis) and peripheral stimuli (left and right of central) presented on a screen, requiring participants to shift their gaze to the stimuli. After source analysis using minimum norm estimation (MNE), we investigated visual responses from each participant by measuring the latency and amplitude of visual evoked fields. Delayed peak latency of the visual response was identified in the primary visual area (calcarine fissure) and visual association areas (v2, v3) in young children with an FASD for both stimulus types (central and peripheral). But the difference in visual response latency was only statistically significant (p ≤ 0.01) for the peripheral (right) stimulus. We also observed reduced amplitude (p ≤ 0.006) of visual evoked response in children with an FASD for the central stimulus type in both primary and visual association areas. Multiple visual areas show impairment in children with an FASD, with visual delay and conduction disturbance more prominent in response to peripheral stimuli. Children with an FASD also exhibit significantly reduced amplitude of neural activation to central stimuli. These sensory deficits may lead to slow cognitive processing speed through continued intra-cortical network disturbance in children with an FASD.

Gender moderates the association between chronic academic stress with top-down and bottom-up attention

Research on the relationship between chronic stress and cognition is limited by a lack of concurrent measurement of state-anxiety, physiological arousal, and gender. For the first time, we assessed the impact of these factors on top-down/conscious (simple and choice reaction time) and bottom-up/reflexive (saccadic reaction time) measures of attention using CONVIRT virtual-reality cognitive tests. Participants (N = 163) completed measures of academic stress (effort-reward imbalance; ERI) and state-anxiety while heart-rate variability was recorded continuously throughout the experiment. Gender moderated the association between academic stress with the top-down measures (b = -0.002, t = -2.023, p = .045; b = -0.063, t = -3.080, p = .002) and higher academic stress was associated with poorer/slower reaction times only for male participants. For bottom-up attention, heart rate variability moderated the relationship between academic stress and saccadic reaction time (b = 0.092, t = 1.991, p = .048), and only female participants who were more stressed (i.e., ERI ≥ 1) and displayed stronger sympathetic dominance had slower reaction times. Our findings align with emerging evidence that chronic stress is related to hyperarousal in women and cognitive decrements in men. Our findings suggest that higher ERI and sympathetic dominance during cognitive testing was associated with poorer bottom-up attention in women, whereas for men, academic stress was related with poorer top-down attention irrespective of sympathovagal balance.

How structural and functional MRI can inform dual-site tACS parameters: A case study in a clinical population and its pragmatic implications

BACKGROUND

Abnormalities in frontoparietal network (FPN) were observed in many neuropsychiatric diseases including substance use disorders. A growing number of studies are using dual-site-tACS with frontoparietal synchronization to engage this network. However, a computational pathway to inform and optimize parameter space for frontoparietal synchronization is still lacking. In this case study, in a group of participants with methamphetamine use disorders, we proposed a computational pathway to extract optimal electrode montage while accounting for stimulation intensity using structural and functional MRI.

METHODS

Sixty methamphetamine users completed an fMRI drug cue-reactivity task. Four main steps were taken to define electrode montage and adjust stimulation intensity using 4x1 high-definition (HD) electrodes for a dual-site-tACS; (1) Frontal seed was defined based on the maximum electric fields (EF) predicted by simulation of HD montage over DLPFC (F3/F4 in EEG 10-20), (2) frontal seed-to-whole brain context-dependent correlation was calculated to determine connected regions to frontal seeds, (3) center of connected cluster in parietal cortex was selected as a location for placing the second set of HD electrodes to shape the informed montage, (4) individualized head models were used to determine optimal stimulation intensity considering underlying brain structure. The informed montage was compared to montages with large electrodes and classic frontoparietal HD montages (F3-P3/F4-P4) in terms of tACS-induced EF and ROI-to-ROI task-based/resting-state connectivity.

RESULTS

Compared to the large electrodes, HD frontoparietal montages allow for a finer control of the spatial peak fields in the main nodes of the FPN at the cost of lower maximum EF (large-pad/HD: max EF[V/m] = 0.37/0.11, number of cortical sub-regions that EF exceeds 50% of the max = 77/13). For defining stimulation targets based on EF patterns, using group-level head models compared to a single standard head model results in comparable but significantly different seed locations (6.43mm Euclidean distance between the locations of the frontal maximum EF in standard-space). As expected, significant task-based/resting-state connections were only found between frontal-parietal locations in the informed montage. Cue-induced craving score was correlated with frontoparietal connectivity only in the informed montage (r = -0.24). Stimulation intensity in the informed montage, and not in the classic HD montage, needs 40% reduction in the parietal site to reduce the disparity in EF between sites.

CONCLUSION

This study provides some empirical insights to montage and dose selection in dual-site-tACS using individual brain structures and functions and proposes a computational pathway to use head models and functional MRI to define (1) optimum electrode montage for targeting FPN in a context of interest (drug-cue-reactivity) and (2) proper transcranial stimulation intensity.

Cognitive performance during adulthood in a rat model of neonatal diffuse white matter injury

RATIONALE

Infants born prematurely risk developing diffuse white matter injury (WMI), which is associated with impaired cognitive functioning and an increased risk of autism spectrum disorder. Recently, our rat model of preterm diffuse WMI induced by combined fetal inflammation and postnatal hypoxia showed impaired motor performance, anxiety-like behaviour and autism-like behaviour in juvenile rats, especially males. Immunohistochemistry showed delayed myelination in the sensory cortex and impaired oligodendrocyte differentiation.

OBJECTIVE

To assess long-term cognitive deficits in this double-hit rat model of diffuse WMI, animals were screened on impulsivity, attention and cognitive flexibility in adulthood using the 5-choice serial reaction time task (5CSRTT) and a probabilistic reversal learning task, tests that require a proper functioning prefrontal cortex. Thereafter, myelination deficits were evaluated by immunofluorescent staining in adulthood.

RESULTS

Overall, little effect of WMI or sex was found in the cognitive tasks. WMI animals showed subtle differences in performance in the 5CSRTT. Manipulating 5CSRTT parameters resulted in performance patterns previously seen in the literature. Sex differences were found in perseverative responses and omitted trials: female WMI rats seem to be less flexible in the 5CSRTT but not in the reversal learning task. Males collected rewards faster in the probabilistic reversal learning task. These findings are explained by temporally rather than permanently affected myelination and by the absence of extensive injury to prefrontal cortical subregions, confirmed by immunofluorescent staining in both adolescence and adulthood.

CONCLUSION

This rat model of preterm WMI does not lead to long-term cognitive deficits as observed in prematurely born human infants.

The diachronic account of attentional selectivity

Many models of attention assume that attentional selection takes place at a specific moment in time that demarcates the critical transition from pre-attentive to attentive processing of sensory input. We argue that this intuitively appealing standard account of attentional selectivity is not only inaccurate, but has led to substantial conceptual confusion. As an alternative, we offer a 'diachronic' framework that describes attentional selectivity as a process that unfolds over time. Key to this view is the concept of attentional episodes, brief periods of intense attentional amplification of sensory representations that regulate access to working memory and response-related processes. We describe how attentional episodes are linked to earlier attentional mechanisms and to recurrent processing at the neural level. We review studies that establish the existence of attentional episodes, delineate the factors that determine if and when they are triggered, and discuss the costs associated with processing multiple events within a single episode. Finally, we argue that this framework offers new solutions to old problems in attention research that have never been resolved. It can provide a unified and conceptually coherent account of the network of cognitive and neural processes that produce the goal-directed selectivity in perceptual processing that is commonly referred to as 'attention'.

Prefrontal Control of Proactive and Reactive Mechanisms of Visual Suppression

In everyday life, we are continuously struggling at focusing on our current goals while at the same time avoiding distractions. Attention is the neuro-cognitive process devoted to the selection of behaviorally relevant sensory information while at the same time preventing distraction by irrelevant information. Distraction can be prevented proactively, by strategically prioritizing task-relevant information at the expense of irrelevant information, or reactively, by suppressing the ongoing processing of distractors. The distinctive neuronal signature of these suppressive mechanisms is still largely unknown. Thanks to machine-learning decoding methods applied to prefrontal cortical activity, we monitor the dynamic spatial attention with an unprecedented spatial and temporal resolution. We first identify independent behavioral and neuronal signatures for long-term (learning-based spatial prioritization) and short-term (dynamic spatial attention) mechanisms. We then identify distinct behavioral and neuronal signatures for proactive and reactive suppression mechanisms. We find that while distracting task-relevant information is suppressed proactively, task-irrelevant information is suppressed reactively. Critically, we show that distractor suppression, whether proactive or reactive, strongly depends on the implementation of both long-term and short-term mechanisms of selection. Overall, we provide a unified neuro-cognitive framework describing how the prefrontal cortex deals with distractors in order to flexibly optimize behavior in dynamic environments.

Spectrum power and brain functional connectivity of different EEG frequency bands in attention network tests

There have been many previous studies on brain electrical activity and attention function, but the research on observing the cognitive function of attention from frequency brain electrical indicators remains insufficient. This study proposed an attentional network test (ANT) of Chinese version and used frequency analysis methods to observe the power spectrum activity and functional connectivity of delta (δ), theta (θ), alpha (α) bands of EEG signals to further understand their relationship with attention networks. The attentional network test was composed of alerting network, orienting network and execute conflict network, and these networks were compared with the resting state in different frequency bands. The results showed that α band activity was significantly suppressed in all three attentional states, and the power of θ band activity dramatically increased for the execute conflict network. The negative connection of α band in the long distance (frontal lobe to parietal lobe or occipital lobe) might be a sign of resting state network, and the positive connections between δ and θ band in similar areas could be an indicator of execute conflict network. This pilot study suggests that the frequency domain analysis of EEG signals could be a great tool to visualize the brain activities in response to different attentional networks.Clinical Relevance- This pilot study proved that the frequency bands activity might be suitable objective neuro-markers to distinguish different attention states.

A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network

Goal-directed behavior often involves temporal separation and flexible context-dependent association between sensory input and motor output. The control of goal-directed behavior is proposed to lie in the frontoparietal network, but the computational architecture of this network remains elusive. Based on recent rodent studies that measured and manipulated projection neurons in the frontoparietal network together with findings from earlier primate studies, we propose a canonical scheme of information flows in this network. The parietofrontal pathway transmits the spatial information of a sensory stimulus or internal motor bias to drive motor programs in the frontal areas. This pathway might consist of multiple parallel connections, each controlling distinct motor effectors. The frontoparietal pathway sends the spatial information of cognitively processed motor plans through multiple parallel connections. Each of these connections could support distinct spatial functions that use the motor target information, including attention allocation, multi-body part coordination, and forward estimation of movement state (i.e., forward models). The parallel pathways in the frontoparietal network enable dynamic interactions between regions that are tuned for specific goal-directed behaviors. This scheme offers a promising framework within which the computational architecture of the frontoparietal network and the underlying circuit mechanisms can be delineated in a systematic way, providing a holistic understanding of information processing in this network. Clarifying this network may also improve the diagnosis and treatment of behavioral deficits associated with dysfunctional frontoparietal connectivity in various neurological disorders including Alzheimer's disease.

The Alerting and Orienting Systems of Attention Are Modified by Cannabis Dependence

Attention allows us to select relevant information from the background. Although several studies have described that cannabis use induces deleterious effects on attention, it remains unclear if cannabis dependence affects the attention network systems differently.

OBJECTIVES

To evaluate whether customary consumption of cannabis or cannabis dependence impacts the alerting, orienting, and executive control systems in young adults; to find out whether it is related to tobacco or alcohol dependence and if cannabis use characteristics are associated with the attention network systems.

METHOD

One-hundred and fifty-four healthy adults and 102 cannabis users performed the Attention Network Test (ANT) to evaluate the alerting, orienting, and executive control systems.

RESULTS

Cannabis use enhanced the alerting system but decreased the orienting system. Moreover, those effects seem to be associated with cannabis dependence. Out of all the cannabis-using variables, only the age of onset of cannabis use significantly predicted the efficiency of the orienting and executive control systems.

CONCLUSION

Cannabis dependence favors tonic alertness but reduces selective attention ability; earlier use of cannabis worsens the efficiency of selective attention and resolution of conflicts.

Adapting non-invasive human recordings along multiple task-axes shows unfolding of spontaneous and over-trained choice

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here, we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to three task-axes, relevant and irrelevant sensory inputs and response direction, in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a progression from processing sensory input to processing the response. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive over-training common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after over-training.

Neurochemistry of Visual Attention

Visual attention is the cognitive process that mediates the selection of important information from the environment. This selection is usually controlled by bottom-up and top-down attentional biasing. Since for most humans vision is the dominant sense, visual attention is critically important for higher-order cognitive functions and related deficits are a core symptom of many neuropsychiatric and neurological disorders. Here, we summarize the importance and relative contributions of different neuromodulators and neurotransmitters to the neural mechanisms of top-down and bottom-up attentional control. We will not only review the roles of widely accepted neuromodulators, such as acetylcholine, dopamine and noradrenaline, but also the contributions of other modulatory substances. In doing so, we hope to shed some light on the current understanding of the role of neurochemistry in shaping neuron properties contributing to the allocation of attention in the visual field.

Allele-dosage genetic polymorphisms of cannabinoid receptor 1 predict attention, but not working memory performance in humans

Attention and working memory (WM) are under high genetic regulation. Single nucleotide polymorphisms (SNPs) of the CNR1 gene, that encode for CB1R, have previously been shown to be related with individual differences in attentional control and WM. However, it remains unclear whether there is an allele-dosage or a dominant contribution of polymorphisms of CNR1 affecting attention and WM performance. This study evaluated the associations between attention and WM performance and three SNPs of CNR1: rs1406977, rs2180619, and rs1049353, previously associated with both processes. Healthy volunteers (n = 127) were asked to perform the Attention Network Task (ANT) to evaluate their overall attention and alerting, orienting, and executive systems, and the n-back task for evaluating their WM. All subjects were genotyped using qPCR with TaqMan assays; and dominant and additive models were assessed using the risk alleles of each SNP as the predictor variable. Results showed an individual association of the three SNPs with attention performance, but the composite genotype by the three alleles had the greatest contribution. Moreover, the additive-dosage model showed that for each G-allele added to the genotypic configuration, there was an increase in the percentage of correct responses respect to carriers who have no risk alleles in their genotypic configuration. The number of risk alleles in the genotypic configurations did not predict efficiency in any of the attention systems, nor in WM performance. Our model showed a contribution of three single nucleotide polymorphisms of the CNR1 gene to explain 9% of the variance of attention in an additive manner.

Transcranial magnetic stimulation over the right dorsolateral prefrontal cortex modulates visuospatial distractor suppression

Visual selective attention allows us to filter relevant inputs from irrelevant inputs during visual processing. In contrast to rich research exploring how the brain facilitates task‐relevant inputs, less is known about how the brain suppresses irrelevant inputs. In this study, we used transcranial magnetic stimulation (TMS) to investigate the causal role of the right dorsolateral prefrontal cortex (DLPFC), a crucial brain area for attentional control, in distractor suppression. Specifically, 10‐Hz repetitive TMS (rTMS) was applied to the right DLPFC and Vertex at the stimuli onset (stimuli‐onset TMS) or 500 ms prior to the stimuli onset (prestimuli TMS). In a variant of the Posner cueing task, participants were instructed to identify the shape of a white target while ignoring a white or colored distractor whose location was either cued in advance or uncued. As anticipated, either the location cue or the colored distractor led to faster responses. Notably, the location cueing effect was eliminated by stimuli‐onset TMS to the right DLPFC, but not by prestimuli TMS. Further analyses showed that stimuli‐onset TMS quickened responses to uncued trials, and this TMS effect was derived from the inhibition at the distractor in both visual fields. In addition, TMS over the right DLPFC had no specific effect on the colored distractor compared to the white one. Considered collectively, these findings indicate that the DLPFC plays a crucial role in visuospatial distractor suppression and acts upon stimuli presentation. Besides, it seems the DLPFC contributes more to location‐based distractor suppression than to color‐based one.

Post-error recruitment of frontal sensory cortical projections promotes attention in mice

The frontal cortex, especially the anterior cingulate cortex area (ACA), is essential for exerting cognitive control after errors, but the mechanisms that enable modulation of attention to improve performance after errors are poorly understood. Here we demonstrate that during a mouse visual attention task, ACA neurons projecting to the visual cortex (VIS; ACA_VIS neurons) are recruited selectively by recent errors. Optogenetic manipulations of this pathway collectively support the model that rhythmic modulation of ACA_VIS neurons in anticipation of visual stimuli is crucial for adjusting performance following errors. 30-Hz optogenetic stimulation of ACA_VIS neurons in anesthetized mice recapitulates the increased gamma and reduced theta VIS oscillatory changes that are associated with endogenous post-error performance during behavior and subsequently increased visually evoked spiking, a hallmark feature of visual attention. This frontal sensory neural circuit links error monitoring with implementing adjustments of attention to guide behavioral adaptation, pointing to a circuit-based mechanism for promoting cognitive control.

Frontotemporal coordination predicts working memory performance and its local neural signatures

Neurons in some sensory areas reflect the content of working memory (WM) in their spiking activity. However, this spiking activity is seldom related to behavioral performance. We studied the responses of inferotemporal (IT) neurons, which exhibit object-selective activity, along with Frontal Eye Field (FEF) neurons, which exhibit spatially selective activity, during the delay period of an object WM task. Unlike the spiking activity and local field potentials (LFPs) within these areas, which were poor predictors of behavioral performance, the phase-locking of IT spikes and LFPs with the beta band of FEF LFPs robustly predicted successful WM maintenance. In addition, IT neurons exhibited greater object-selective persistent activity when their spikes were locked to the phase of FEF LFPs. These results reveal that the coordination between prefrontal and temporal cortex predicts the successful maintenance of visual information during WM.

Anxious attachment is associated with heightened responsivity of a parietofrontal cortical network that monitors peri-personal space

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A parietofrontal cortical network is more active when stimuli are near the body.

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Responses of this network were positively correlated with “attachment anxiety”.

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No other types of attachment or symptoms accounted for this association.

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Connectivity strength within this network was not linked with attachment anxiety.

Background

Attachment, or affiliative bonding among conspecifics, is thought to involve neural mechanisms underlying behavioral responses to threat and reward-related social signals. However, attachment-oriented responses may also rely on basic sensorimotor processes. One sensorimotor system that may play a role in attachment is the parietofrontal cortical network that responds to stimuli that are near or approaching the body, the peripersonal space (PPS) monitoring system. We hypothesized that this network may vary in responsivity to such potentially harmful stimuli, particularly those with social salience, based on individual differences in attachment styles.

Methods

Young adults viewed images of human faces or cars that appeared to move towards or away from them, while functional magnetic resonance imaging data were collected. Correlations between each of four adult attachment styles, measured using the Relationship Questionnaire, and responses of the PPS network to approaching (versus withdrawing) stimuli were measured.

Results

A region-of-interest (ROI) analysis, focused on six cortical regions of the PPS network that showed significant responses to approaching versus withdrawing face stimuli in an independent sample (n = 80), revealed that anxious attachment style (but not the other 3 attachment styles) was significantly positively correlated with responses to faces (but not to cars) in all six ROIs (r = 0.33–0.49, p = 0.01–0.0001, n = 50).

Conclusions

These findings suggest that anxious attachment is associated with over-responsivity of a sensorimotor network involved in attending to social stimuli near the body.

Neuronal oscillations and the mouse prefrontal cortex

The mouse prefrontal cortex (PFC) encompasses a collection of agranual brain regions in the rostral neocortex and is considered to be critically involved in the neuronal computations underlying intentional behaviors. Flexible behavioral responses demand coordinated integration of sensory inputs with state, goal and memory information in brain-wide neuronal networks. Neuronal oscillations are proposed to provide a temporal scaffold for coordination of neuronal network activity and routing of information. In the present book chapter, we review findings on the role neuronal oscillations in prefrontal functioning, with a specific focus on research in mice. We discuss discoveries pertaining to local prefrontal processing, as well to interactions with other brain regions. We also discuss how the recent discovery of brain-wide respiration-entrained rhythms (RR) warrant re-evaluation of certain findings on slow oscillations (<10Hz) in prefrontal functioning.

Cortical Hemodynamic Response Associated with Spatial Coding: A Near-Infrared Spectroscopy Study

Allocentric and egocentric are two types of spatial coding. Previous studies reported the dorsal attention network's involvement in both types. To eliminate possible paradigm-specific confounds in the results, this study employed fine-grained cue-to-target paradigm to dissociate allocentric (aSC) and egocentric (eSC) spatial coding. Twenty-two participants completed a custom visuospatial task, and changes in the concentration of oxygenated hemoglobin (O₂-Hb) were recorded using functional near-infrared spectroscopy (fNIRS). The least absolute shrinkage and selection operator-regularized principal component (LASSO-RPC) algorithm was used to identify cortical sites that predicted the aSC and eSC conditions' reaction times. Significant changes in O₂-Hb concentration in the right inferior parietal lobule (IPL) and post-central gyrus regions were common in both aSC and eSC. Results of inter-channel correlations further substantiate cortical activities in both conditions were predominantly over the right parieto-frontal areas. Together with right superior frontal gyrus areas be the reaction time neural correlates, the results suggest top-down attention and response-mapping processes are common to both spatial coding types. Changes unique to aSC were in clusters over the right intraparietal sulcus, right temporo-parietal junction, and left IPL. With the left pre-central gyrus region, be the reaction time neural correlate, aSC is likely to involve more orienting attention, updating of spatial information, and object-based response selection and inhibition than eSC. Future studies will use other visuospatial task designs for testing the robustness of the findings on spatial coding processes.

Rules warp feature encoding in decision-making circuits

We have the capacity to follow arbitrary stimulus-response rules, meaning simple policies that guide our behavior. Rule identity is broadly encoded across decision-making circuits, but there are less data on how rules shape the computations that lead to choices. One idea is that rules could simplify these computations. When we follow a rule, there is no need to encode or compute information that is irrelevant to the current rule, which could reduce the metabolic or energetic demands of decision-making. However, it is not clear if the brain can actually take advantage of this computational simplicity. To test this idea, we recorded from neurons in 3 regions linked to decision-making, the orbitofrontal cortex (OFC), ventral striatum (VS), and dorsal striatum (DS), while macaques performed a rule-based decision-making task. Rule-based decisions were identified via modeling rules as the latent causes of decisions. This left us with a set of physically identical choices that maximized reward and information, but could not be explained by simple stimulus-response rules. Contrasting rule-based choices with these residual choices revealed that following rules (1) decreased the energetic cost of decision-making; and (2) expanded rule-relevant coding dimensions and compressed rule-irrelevant ones. Together, these results suggest that we use rules, in part, because they reduce the costs of decision-making through a distributed representational warping in decision-making circuits.