Combined contributions of feedforward and feedback inputs to bottom-up attention

Reaction time for correct identification of vowels in consonant-vowel syllables and of vowel segments

Reaction times for correct vowel identification were measured to determine the effects of intertrial intervals, vowel, and cue type. Thirteen adults with normal hearing, aged 20-38 years old, participated. Stimuli included three naturally produced syllables (/ba/ /bi/ /bu/) presented whole or segmented to isolate the formant transition or static formant center. Participants identified the vowel presented via loudspeaker by mouse click. Results showed a significant effect of intertrial intervals, no significant effect of cue type, and a significant vowel effect-suggesting that feedback occurs, vowel identification may depend on cue duration, and vowel bias may stem from focal structure.

Cortico-cortical connectivity behind acoustic information transfer to mouse orbitofrontal cortex is sensitive to neuromodulation and displays local sensory gating: relevance in disorders with auditory hallucinations?

BACKGROUND

Auditory hallucinations (which occur when the distinction between thoughts and perceptions is blurred) are common in psychotic disorders. The orbitofrontal cortex (OFC) may be implicated, because it receives multiple inputs, including sound and affective value via the amygdala, orchestrating complex emotional responses. We aimed to elucidate the circuit and neuromodulatory mechanisms that underlie the processing of emotionally salient auditory stimuli in the OFC — mechanisms that may be involved in auditory hallucinations.

METHODS

We identified the cortico-cortical connectivity conveying auditory information to the mouse OFC; its sensitivity to neuromodulators involved in psychosis and postpartum depression, such as dopamine and neurosteroids; and its sensitivity to sensory gating (defective in dysexecutive syndromes).

RESULTS

Retrograde tracers in OFC revealed input cells in all auditory cortices. Acoustic responses were abolished by pharmacological and chemogenetic inactivation of the above-identified pathway. Acoustic responses in the OFC were reduced by local dopaminergic agonists and neurosteroids. Noticeably, apomorphine action lasted longer in the OFC than in auditory areas, and its effect was modality-specific (augmentation for visual responses), whereas neurosteroid action was sex-specific. Finally, acoustic responses in the OFC reverberated to the auditory association cortex via feedback connections and displayed sensory gating, a phenomenon of local origin, given that it was not detectable in input auditory cortices.

LIMITATIONS

Although our findings were for mice, connectivity and sensitivity to neuromodulation are conserved across mammals.

CONCLUSION

The corticocortical loop from the auditory association cortex to the OFC is dramatically sensitive to dopamine and neurosteroids. This suggests a clinically testable circuit behind auditory hallucinations. The function of OFC input–output circuits can be studied in mice with targeted and clinically relevant mutations related to their response to emotionally salient sounds.

Attention reinforces human corticofugal system to aid speech perception in noise

Perceiving speech-in-noise (SIN) demands precise neural coding between brainstem and cortical levels of the hearing system. Attentional processes can then select and prioritize task-relevant cues over competing background noise for successful speech perception. In animal models, brainstem-cortical interplay is achieved via descending corticofugal projections from cortex that shape midbrain responses to behaviorally-relevant sounds. Attentional engagement of corticofugal feedback may assist SIN understanding but has never been confirmed and remains highly controversial in humans. To resolve these issues, we recorded source-level, anatomically constrained brainstem frequency-following responses (FFRs) and cortical event-related potentials (ERPs) to speech via high-density EEG while listeners performed rapid SIN identification tasks. We varied attention with active vs. passive listening scenarios whereas task difficulty was manipulated with additive noise interference. Active listening (but not arousal-control tasks) exaggerated both ERPs and FFRs, confirming attentional gain extends to lower subcortical levels of speech processing. We used functional connectivity to measure the directed strength of coupling between levels and characterize "bottom-up" vs. "top-down" (corticofugal) signaling within the auditory brainstem-cortical pathway. While attention strengthened connectivity bidirectionally, corticofugal transmission disengaged under passive (but not active) SIN listening. Our findings (i) show attention enhances the brain's transcription of speech even prior to cortex and (ii) establish a direct role of the human corticofugal feedback system as an aid to cocktail party speech perception.

Inherent Importance of Early Visual Features in Attraction of Human Attention

Local contrasts attract human attention to different areas of an image. Studies have shown that orientation, color, and intensity are some basic visual features which their contrasts attract our attention. Since these features are in different modalities, their contribution in the attraction of human attention is not easily comparable. In this study, we investigated the importance of these three features in the attraction of human attention in synthetic and natural images. Choosing 100% percent detectable contrast in each modality, we studied the competition between different features. Psychophysics results showed that, although single features can be detected easily in all trials, when features were presented simultaneously in a stimulus, orientation always attracts subject's attention. In addition, computational results showed that orientation feature map is more informative about the pattern of human saccades in natural images. Finally, using optimization algorithms we quantified the impact of each feature map in construction of the final saliency map.

Differential Processing of Isolated Object and Multi-item Pop-Out Displays in LIP and PFC

Objects that are highly distinct from their surroundings appear to visually "pop-out." This effect is present for displays in which: (1) a single cue object is shown on a blank background, and (2) a single cue object is highly distinct from surrounding objects; it is generally assumed that these 2 display types are processed in the same way. To directly examine this, we applied a decoding analysis to neural activity recorded from the lateral intraparietal (LIP) area and the dorsolateral prefrontal cortex (dlPFC). Our analyses showed that for the single-object displays, cue location information appeared earlier in LIP than in dlPFC. However, for the display with distractors, location information was substantially delayed in both brain regions, and information first appeared in dlPFC. Additionally, we see that pattern of neural activity is similar for both types of displays and across different color transformations of the stimuli, indicating that location information is being coded in the same way regardless of display type. These results lead us to hypothesize that 2 different pathways are involved processing these 2 types of pop-out displays.

Influence of learning strategy on response time during complex value-based learning and choice

Measurements of response time (RT) have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning). Alternatively, they could learn reward values of options' features (e.g. color, shape) and combine these values to estimate reward values for individual options (feature-based learning). We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach) adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

Feature-based learning improves adaptability without compromising precision

Learning from reward feedback is essential for survival but can become extremely challenging with myriad choice options. Here, we propose that learning reward values of individual features can provide a heuristic for estimating reward values of choice options in dynamic, multi-dimensional environments. We hypothesize that this feature-based learning occurs not just because it can reduce dimensionality, but more importantly because it can increase adaptability without compromising precision of learning. We experimentally test this hypothesis and find that in dynamic environments, human subjects adopt feature-based learning even when this approach does not reduce dimensionality. Even in static, low-dimensional environments, subjects initially adopt feature-based learning and gradually switch to learning reward values of individual options, depending on how accurately objects’ values can be predicted by combining feature values. Our computational models reproduce these results and highlight the importance of neurons coding feature values for parallel learning of values for features and objects.

Learning about a rewarded outcome is complicated by the fact that a choice often incorporates multiple features with differing association with the reward. Here the authors demonstrate that feature-based learning is an efficient and adaptive strategy in dynamically changing environments.

Social Saliency of the Cue Slows Attention Shifts

Eye gaze is a powerful cue that indicates where another person's attention is directed in the environment. Seeing another person's eye gaze shift spontaneously and reflexively elicits a shift of one's own attention to the same region in space. Here, we investigated whether reallocation of attention in the direction of eye gaze is modulated by personal familiarity with faces. On the one hand, the eye gaze of a close friend should be more effective in redirecting our attention as compared to the eye gaze of a stranger. On the other hand, the social relevance of a familiar face might itself hold attention and, thereby, slow lateral shifts of attention. To distinguish between these possibilities, we measured the efficacy of the eye gaze of personally familiar and unfamiliar faces as directional attention cues using adapted versions of the Posner paradigm with saccadic and manual responses. We found that attention shifts were slower when elicited by a perceived change in the eye gaze of a familiar individual as compared to attention shifts elicited by unfamiliar faces at short latencies (100 ms). We also measured simple detection of change in direction of gaze in personally familiar and unfamiliar faces to test whether slower attention shifts were due to slower detection. Participants detected changes in eye gaze faster for familiar faces than for unfamiliar faces. Our results suggest that personally familiar faces briefly hold attention due to their social relevance, thereby slowing shifts of attention, even though the direction of eye movements are detected faster in familiar faces.

Sites of overt and covert attention define simultaneous spatial reference centers for visuomotor response

The site of overt attention (fixation point) defines a spatial reference center that affects visuomotor response as indicated by the stimulus-response-compatibility (SRC) effect: When subjects press, e.g., a left key to report stimuli, their reaction time is shorter when stimuli appear to the left than to the right of the fixation. Covert attention to a peripheral site appears to define a similar reference center but previous studies did not control for confounding spatiotemporal factors or investigate the relationship between overt- and covert-attention-defined centers. Using an eye tracker to monitor fixation, we found an SRC effect relative to the site of covert attention induced by a flashed cue dot, and a concurrent reduction, but not elimination, of the overt-attention SRC effect. The two SRC effects jointly determined the overall motor reaction time. Since trials with different cue locations were randomly interleaved, the integration of the two reference centers must be updated online. When the cue was invalid and diminished covert attention, the covert-attention SRC effect disappeared and the overt-attention SRC effect retained full strength, excluding non-attention-based interpretations. We conclude that both covert- and overt-attention sites define visual reference centers that simultaneously contribute to motor response.