Top-down Signals Research Articles

Behavioral Approaches to Study Top-Down Influences on Active Listening.

The massive network of descending corticofugal projections has been long-recognized by anatomists, but their functional contributions to sound processing and auditory-guided behaviors remain a mystery. Most efforts to characterize the auditory corticofugal system have been inductive; wherein function is inferred from a few studies employing a wide range of methods to manipulate varying limbs of the descending system in a variety of species and preparations. An alternative approach, which we focus on here, is to first establish auditory-guided behaviors that reflect the contribution of top-down influences on auditory perception. To this end, we postulate that auditory corticofugal systems may contribute to active listening behaviors in which the timing of bottom-up sound cues can be predicted from top-down signals arising from cross-modal cues, temporal integration, or self-initiated movements. Here, we describe a behavioral framework for investigating how auditory perceptual performance is enhanced when subjects can anticipate the timing of upcoming target sounds. Our first paradigm, studied both in human subjects and mice, reports species-specific differences in visually cued expectation of sound onset in a signal-in-noise detection task. A second paradigm performed in mice reveals the benefits of temporal regularity as a perceptual grouping cue when detecting repeating target tones in complex background noise. A final behavioral approach demonstrates significant improvements in frequency discrimination threshold and perceptual sensitivity when auditory targets are presented at a predictable temporal interval following motor self-initiation of the trial. Collectively, these three behavioral approaches identify paradigms to study top-down influences on sound perception that are amenable to head-fixed preparations in genetically tractable animals, where it is possible to monitor and manipulate particular nodes of the descending auditory pathway with unparalleled precision.

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.

Action Costs Rapidly and Automatically Interfere with Reward-Based Decision-Making in a Reaching Task.

It is widely assumed that we select actions we value the most. While the influence of rewards on decision-making has been extensively studied, evidence regarding the influence of motor costs is scarce. Specifically, how and when motor costs are integrated in the decision process is unclear. Twenty-two right-handed human participants performed a reward-based target selection task by reaching with their right arm toward one of two visual targets. Targets were positioned in different directions according to biomechanical preference, such that one target was systematically associated with a lower motor cost than the other. Only one of the two targets was rewarded, either in a congruent or incongruent manner with respect to the associated motor cost. A timed-response paradigm was used to manipulate participants’ reaction times (RT). Results showed that when the rewarded target carried the highest motor cost, movements produced at short RT (<350 ms) were deviated toward the other (i.e., non-rewarded, low-cost (LC) target). In this context participants needed an additional 150-ms delay to reach the same percentage of rewarded trials as when the LC target was rewarded. Crucially, motor costs affected the total earnings of participants. These results demonstrate a robust interference of motor costs in a simple reward-based decision-making task. They point to the rapid and automatic integration of motor costs at an early stage of processing, potentially through the direct modulation of competing action representations in parieto-frontal regions. The progressive overcoming of this bias with increasing RT is likely achieved through top-down signaling pertaining to expected rewards.

Coordination of top-down influence on V1 responses by interneurons and brain rhythms

Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the representation of visual information in early visual areas such as primary visual cortex (V1). Recent studies have shown further that beta rhythms are responsible for the transmission of behavioral-context information to lower visual areas. However, the mechanism underlying top-down influence and the role of brain rhythms in top-down processing are poorly understood. To address these issues, we focus on experimental studies on top-down influence in visual perceptual tasks. We develop a model of visual system, in which early visual areas are subjected to top-down influence from a recognition area. We show that task-relevant information in early visual areas is regulated by a push-pull effect, produced by somatostatin-expressing interneurons and top-down signal. We also show that task-context information is coordinated by the phase-phase coupling of beta rhythms, while the local, task-relevant stimulus features are enhanced by the phase-amplitude coupling of beta and gamma rhythms. Furthermore, the feedback from a higher visual area such as secondary visual area facilitates the gating of task-relevant information in V1. The results provide insights to understanding the roles of inhibitory interneurons and brain rhythms in top-down influence on information processing in early visual areas.

Passive distractor filtering in visual search

ABSTRACT Luck, Gaspelin, Folk, Remington, & Theeuwes [(in press). Progress Toward Resolving the Attentional Capture Debate. Visual Cognition] proposes that proactive attentional mechanisms suppress a salient distractor by top-down inhibitory signals. However, considering the abundance of distracting information surrounding us, an automatic and passive distractor filtering system that requires little cognitive resources would benefit. Recent studies showed that passive exposure to distractors (without any competition with a target) before a search task attenuates interference from distractors during the actual visual search, called passive distractor filtering, and suggested that habituation is its core mechanism. This commentary summarizes research on passive distractor filtering, discusses habituation processes, and proposes future directions.

Neural Mechanisms Underlying the Auditory Looming Bias

ABSTRACT Our auditory system constantly keeps track of our environment, informing us about our surroundings and warning us of potential threats. The auditory looming bias is an early perceptual phenomenon, reflecting higher alertness of listeners to approaching auditory objects, rather than to receding ones. Experimentally, this sensation has been elicited by using both intensity-varying stimuli, as well as spectrally varying stimuli with constant intensity. Following the intensity-based approach, recent research delving into the cortical mechanisms underlying the looming bias argues for top-down signaling from the prefrontal cortex to the auditory cortex in order to prioritize approaching over receding sonic motion. We here test the generalizability of that finding to spectrally induced looms by re-analyzing previously published data. Our results indicate the promoted top-down projection but at time points slightly preceding the motion onset and thus considered to reflect a bias driven by anticipation. At time points following the motion onset, our findings show a bottom-up bias along the dorsal auditory pathway directed toward the prefrontal cortex.

Shared mechanisms underlie the control of working memory and attention.

Cognitive control guides behaviour by controlling what, when, and how information is represented in the brain1. For example, attention controls sensory processing; top-down signals from prefrontal and parietal cortex strengthen the representation of task-relevant stimuli2-4. A similar 'selection' mechanism is thought to control the representations held 'in mind'-in working memory5-10. Here we show that shared neural mechanisms underlie the selection of items from working memory and attention to sensory stimuli. We trained rhesus monkeys to switch between two tasks, either selecting one item from a set of items held in working memory or attending to one stimulus from a set of visual stimuli. Neural recordings showed that similar representations in prefrontal cortex encoded the control of both selection and attention, suggesting that prefrontal cortex acts as a domain-general controller. By contrast, both attention and selection were represented independently in parietal and visual cortex. Both selection and attention facilitated behaviour by enhancing and transforming the representation of the selected memory or attended stimulus. Specifically, during the selection task, memory items were initially represented in independent subspaces of neural activity in prefrontal cortex. Selecting an item caused its representation to transform from its own subspace to a new subspace used to guide behaviour. A similar transformation occurred for attention. Our results suggest that prefrontal cortex controls cognition by dynamically transforming representations to control what and when cognitive computations are engaged.

Top-down control of visual cortex by the frontal eye fields through oscillatory realignment

Voluntary allocation of visual attention is controlled by top-down signals generated within the Frontal Eye Fields (FEFs) that can change the excitability of lower-level visual areas. However, the mechanism through which this control is achieved remains elusive. Here, we emulated the generation of an attentional signal using single-pulse transcranial magnetic stimulation to activate the FEFs and tracked its consequences over the visual cortex. First, we documented changes to brain oscillations using electroencephalography and found evidence for a phase reset over occipital sites at beta frequency. We then probed for perceptual consequences of this top-down triggered phase reset and assessed its anatomical specificity. We show that FEF activation leads to cyclic modulation of visual perception and extrastriate but not primary visual cortex excitability, again at beta frequency. We conclude that top-down signals originating in FEF causally shape visual cortex activity and perception through mechanisms of oscillatory realignment.

Cross-Hemispheric Complementary Prefrontal Mechanisms during Task Switching under Perceptual Uncertainty.

Flexible adaptation to changing environments is a representative executive control function implicated in the frontoparietal network that requires appropriate extraction of goal-relevant information through perception of the external environment. It remains unclear, however, how the flexibility is achieved under situations where goal-relevant information is uncertain. To address this issue, the current study examined neural mechanisms for task switching in which task-relevant information involved perceptual uncertainty. Twenty-eight human participants of both sexes alternated behavioral tasks in which they judged motion direction or color of visually presented colored dot stimuli that moved randomly. Task switching was associated with frontoparietal regions in the left hemisphere, and perception of ambiguous stimuli involved contralateral homologous frontoparietal regions. On the other hand, in stimulus-modality-dependent occipitotemporal regions, task coding information was increased during task switching. Effective connectivity analysis revealed that the frontal regions signaled toward the modality-dependent occipitotemporal regions when a relevant stimulus was more ambiguous, whereas the occipitotemporal regions signaled toward the frontal regions when the stimulus was more distinctive. These results suggest that complementary prefrontal mechanisms in the left and right hemispheres help to achieve a behavioral goal when the external environment involves perceptual uncertainty.SIGNIFICANCE STATEMENT In our daily life, environmental information to achieve a goal is not always certain, but we make judgments in such situations, and change our behavior accordingly. This study examined how the flexibility of behavior is achieved in a situation where goal-relevant information involves perceptual uncertainty. fMRI revealed that the lateral prefrontal cortex (PFC) in the left hemisphere is associated with behavioral flexibility, and the perception of ambiguous stimuli involves the PFC in the right hemisphere. These bilateral PFC signaled to stimulus-modality-dependent occipitotemporal regions, depending on perceptual uncertainty and the task to be performed. These top-down signals supplement task coding in the occipitotemporal regions, and highlight interhemispheric prefrontal mechanisms involved in executive control and perceptual decision-making.

Complementary interactions between classical and top-down driven inhibitory mechanisms of attention

Selective attention informs decision-making by biasing perceptual processing towards task-relevant stimuli. In experimental and computational literature, this is most often implemented through top-down excitation of selected stimuli. However, physiological and anatomical evidence shows that in certain situations, top-down signals could instead be inhibitory. In this study, we investigated how such an inhibitory mechanism of top-down attention compares with an excitatory one. We did so in a neurorobotics context where the agent was controlled using an established hierarchical architecture. We augmented the architecture with an attentional system that implemented top-down attention biasing as connection gains. We tested four models of top-down attention on the simulated agent performing a foraging task: without top-down biasing, with only excitatory top-down gain, with only inhibitory top-down gain, and with both excitatory and inhibitory top-down gain. We manipulated the reward-distractor ratio that was presented and assessed the agent's performance using accumulated rewards and the latency of the selection. Using these measures, we provide evidence that excitatory and inhibitory mechanisms of attention complement each other.

Higher-order thalamus input to the cortex

Neuroscience Sensory information can only be used meaningfully in the brain when integrated with and compared with internally generated top-down signals. However, we know little about the brainwide afferents that convey such top-down signals, their information content, and learning-related plasticity. Pardi et al. identified the higher-order thalamus as a major source of top-down input to mouse auditory cortex and investigated a circuit in cortical layer 1 that facilitates plastic changes and flexible responses. These results demonstrate how top-down feedback information can reach cortical areas through a noncortical structure that has received little attention despite its widespread connections with the cortex. Science , this issue p. [844][1] [1]: /lookup/doi/10.1126/science.abc2399

What shapes public support for climate change mitigation policies? The role of descriptive social norms and elite cues

AbstractWhat are the roles of bottom-up and top-down signals in the formation of climate change policy preferences? Using a large sample of American residents (n = 1520) and combining an experimental manipulation of descriptive social norms with two choice experiments, we investigate the effects of descriptive norms and policy endorsements by key political actors on climate policy support. We study these questions in two areas considered to be central in a number of decarbonization pathways: the phase-out of fossil fuel-powered cars and the deployment of carbon capture and storage. Our study provides two important results. First, social norm interventions may be no silver bullet for increasing citizens’ support for ambitious climate policies. In fact, we not only find that climate policy support is unaffected by norm messages communicating an increased diffusion of pro-environmental behaviors, but also that norm messages communicating the prevalence of non-sustainable behaviors decrease policy support. Second, in the presence of policy endorsements by political parties, citizens’ trust in these parties influences their support for climate policies. This study contributes to research in behavioral climate policy by examining the impact of descriptive norms and elite cues on climate policy support.

The multimodal Ganzfeld-induced altered state of consciousness induces decreased thalamo-cortical coupling

Different pharmacologic agents have been used to investigate the neuronal underpinnings of alterations in consciousness states, such as psychedelic substances. Special attention has been drawn to the role of thalamic filtering of cortical input. Here, we investigate the neuronal mechanisms underlying an altered state of consciousness (ASC) induced by a non-pharmacological procedure. During fMRI scanning, N = 19 human participants were exposed to multimodal Ganzfeld stimulation, a technique of perceptual deprivation where participants are exposed to intense, unstructured, homogenous visual and auditory stimulation. Compared to pre- and post-resting-state scans, the Ganzfeld data displayed a progressive decoupling of the thalamus from the cortex. Furthermore, the Ganzfeld-induced ASC was characterized by increased eigenvector centrality in core regions of the default mode network (DMN). Together, these findings can be interpreted as an imbalance of sensory bottom-up signaling and internally-generated top-down signaling. This imbalance is antithetical to psychedelic-induced ASCs, where increased thalamo-cortical coupling and reduced DMN activity were observed.

Value-guided remapping of sensory cortex by lateral orbitofrontal cortex

Adaptive behaviour crucially depends on flexible decision-making, which in mammals relies on the frontal cortex, specifically the orbitofrontal cortex (OFC)1-9. How OFC encodes decision variables and instructs sensory areas to guide adaptive behaviour are key open questions. Here we developed a reversal learning task for head-fixed mice, monitored the activity of neurons of the lateral OFC using two-photon calcium imaging and investigated how OFC dynamically interacts with primary somatosensory cortex (S1). Mice learned to discriminate 'go' from 'no-go' tactile stimuli10,11 and adapt their behaviour upon reversal of stimulus-reward contingency ('rule switch'). Imaging individual neurons longitudinally across all behavioural phases revealed a distinct engagement of S1 and lateral OFC, with S1 neural activity reflecting initial task learning, whereas lateral OFC neurons responded saliently and transiently to the rule switch. We identified direct long-range projections from lateral OFC to S1 that can feed this activity back to S1 as value prediction error. This top-down signal updated sensory representations in S1 by functionally remapping responses in a subpopulation of neurons that was sensitive to reward history. Functional remapping crucially depended on top-down feedback as chemogenetic silencing of lateral OFC neurons disrupted reversal learning, as well as plasticityin S1. The dynamic interaction of lateral OFC with sensory cortex thus implements computations criticalfor value prediction that are history dependent and error based, providing plasticity essential for flexible decision-making.

Tuning of olfactory cortex ventral tenia tecta neurons to distinct task elements of goal-directed behavior

The ventral tenia tecta (vTT) is a component of the olfactory cortex and receives both bottom-up odor signals and top-down signals. However, the roles of the vTT in odor-coding and integration of inputs are poorly understood. Here, we investigated the involvement of the vTT in these processes by recording the activity from individual vTT neurons during the performance of learned odor-guided reward-directed tasks in mice. We report that individual vTT cells are highly tuned to a specific behavioral epoch of learned tasks, whereby the duration of increased firing correlated with the temporal length of the behavioral epoch. The peak time for increased firing among recorded vTT cells encompassed almost the entire temporal window of the tasks. Collectively, our results indicate that vTT cells are selectively activated during a specific behavioral context and that the function of the vTT changes dynamically in a context-dependent manner during goal-directed behaviors.

Temporal learning of bottom-up connections via spatially nonspecific top-down inputs

In the brain, high-order and low-order areas are connected via bottom-up connections (from low-order to high-order areas) and top-down connections (from high-order to low-order areas). While bottom-up signals are thought to be critical in generating perception, functions of top-down signals have not been clearly delineated. One popular theory is that top-down inputs modify the activity of specific cell assemblies to modulate responses to bottom-up inputs. However, a different line of studies proposes that not all top-down inputs are specifically delivered. As the leading theories cannot account for nonspecific top-down inputs, we seek potential functions of nonspecific top-down signals using network models in our study. Our simulation results suggest that top-down inputs can regulate low-order area responses by providing temporal information even without spatial specificity. Specifically, the temporal information in nonspecific top-down inputs can weaken the undesired bottom-up connections, contributing to bottom-up connections’ learning. Further, we found that cortical rhythms (synchronous oscillatory neural responses) are critical in the proposed learning process of bottom-up connections in our model.

Spike Phase Shift Relative to Beta Oscillations Mediates Modality Selection.

How does the brain selectively process signals from stimuli of different modalities? Coherent oscillations may function in coordinating communication between neuronal populations simultaneously involved in such cognitive behavior. Beta power (12-30Hz) is implicated in top-down cognitive processes. Here we test the hypothesis that the brain increases encoding and behavioral influence of a target modality by shifting the relationship of neuronal spike phases relative to beta oscillations between primary sensory cortices and higher cortices. We simultaneously recorded neuronal spike and local field potentials in the posterior parietal cortex (PPC) and the primary auditory cortex (A1) when male rats made choices to either auditory or visual stimuli. Neuronal spikes exhibited modality-related phase locking to beta oscillations during stimulus sampling, and the phase shift between neuronal subpopulations demonstrated faster top-down signaling from PPC to A1 neurons when animals attended to auditory rather than visual stimuli. Importantly, complementary to spike timing, spike phase predicted rats' attended-to target in single trials, which was related to the animals' performance. Our findings support a candidate mechanism that cortices encode targets from different modalities by shifting neuronal spike phase. This work may extend our understanding of the importance of spike phase as a coding and readout mechanism.

The role of the subgenual anterior cingulate cortex in dorsomedial prefrontal-amygdala neural circuitry during positive-social emotion regulation.

Positive‐social emotions mediate one's cognitive performance, mood, well‐being, and social bonds, and represent a critical variable within therapeutic settings. It has been shown that the upregulation of positive emotions in social situations is associated with increased top‐down signals that stem from the prefrontal cortices (PFC) which modulate bottom‐up emotional responses in the amygdala. However, it remains unclear if positive‐social emotion upregulation of the amygdala occurs directly through the dorsomedial PFC (dmPFC) or indirectly linking the bilateral amygdala with the dmPFC via the subgenual anterior cingulate cortex (sgACC), an area which typically serves as a gatekeeper between cognitive and emotion networks. We performed functional MRI (fMRI) experiments with and without effortful positive‐social emotion upregulation to demonstrate the functional architecture of a network involving the amygdala, the dmPFC, and the sgACC. We found that effortful positive‐social emotion upregulation was associated with an increase in top‐down connectivity from the dmPFC on the amygdala via both direct and indirect connections with the sgACC. Conversely, we found that emotion processes without effortful regulation increased network modulation by the sgACC and amygdala. We also found that more anxious individuals with a greater tendency to suppress emotions and intrusive thoughts, were likely to display decreased amygdala, dmPFC, and sgACC activity and stronger connectivity strength from the sgACC onto the left amygdala during effortful emotion upregulation. Analyzed brain network suggests a more general role of the sgACC in cognitive control and sheds light on neurobiological informed treatment interventions.

The lateral prefrontal cortex of primates encodes stimulus colors and their behavioral relevance during a match-to-sample task

The lateral prefrontal cortex of primates (lPFC) plays a central role in complex cognitive behavior, in decision-making as well as in guiding top-down attention. However, how and where in lPFC such behaviorally relevant signals are computed is poorly understood. We analyzed neural recordings from chronic microelectrode arrays implanted in lPFC region 8Av/45 of two rhesus macaques. The animals performed a feature match-to-sample task requiring them to match both motion and color information in a test stimulus. This task allowed to separate the encoding of stimulus motion and color from their current behavioral relevance on a trial-by-trial basis. We found that upcoming motor behavior can be robustly predicted from lPFC activity. In addition, we show that 8Av/45 encodes the color of a visual stimulus, regardless of its behavioral relevance. Most notably, whether a color matches the searched-for color can be decoded independent of a trial’s motor outcome and while subjects detect unique feature conjunctions of color and motion. Thus, macaque area 8Av/45 computes, among other task-relevant information, the behavioral relevance of visual color features. Such a signal is most critical for both the selection of responses as well as the deployment of top-down modulatory signals, like feature-based attention.

A Computational Role for Top-Down Modulation from Frontal Cortex in Infancy.

Recent findings have shown that full-term infants engage in top-down sensory prediction, and these predictions are impaired as a result of premature birth. Here, we use an associative learning model to uncover the neuroanatomical origins and computational nature of this top-down signal. Infants were exposed to a probabilistic audiovisual association. We find that both groups (full term, preterm) have a comparable stimulus-related response in sensory and frontal lobes and track prediction error in their frontal lobes. However, preterm infants differ from their full-term peers in weaker tracking of prediction error in sensory regions. We infer that top-down signals from the frontal lobe to the sensory regions carry information about prediction error. Using computational learning models and comparing neuroimaging results from full-term and preterm infants, we have uncovered the computational content of top-down signals in young infants when they are engaged in a probabilistic associative learning.