Competition between emotional faces in visuospatial working memory.

Visuospatial working memory (VSWM) helps track the identity and location of people during social interactions. Previous work showed better VSWM when all faces at encoding displayed a happy compared to an angry expression, reflecting a prosocial preference for monitoring who was where. However, social environments are not typically uniform, and certain expressions may more strongly compete for and bias face monitoring according to valence and/or arousal properties. Here, we used heterogeneous encoding displays in which two faces shared one emotion and two shared another, and asked participants to relocate a central neutral probe face after a blank delay. When considering the emotion of the probed face independently of the co-occurring emotion at encoding, an overall happy benefit was replicated. However, accuracy was modulated by the nonprobed emotion, with a relocation benefit for angry over sad, happy over fearful, and sad over happy faces. These effects did not depend on encoding fixation time, stimulus arousal, perceptual similarity, or response bias. Thus, emotional competition for faces in VSWM is complex and appears to rely on more than simple arousal- or valence-biased mechanisms. We propose a "social value (SV)" account to better explain when and why certain emotions may be prioritized in VSWM. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fundamental units of numerosity estimation.

Humans can approximately enumerate a large number of objects at a single glance. While several mechanisms have been proposed to account for this ability, the fundamental units over which they operate remain unclear. Previous studies have argued that estimation mechanisms act only on topologically distinct units or on units formed by spatial grouping cues such as proximity and connectivity, but not on units grouped by similarity. Over four experiments, we tested this claim by systematically assessing and demonstrating that similarity grouping leads to underestimation, just as spatial grouping does. Ungrouped objects with the same low-level properties as grouped objects did not cause underestimation. Further, the underestimation caused by spatial and similarity grouping was additive, suggesting that these grouping processes operate independently. These findings argue against the proposal that estimation mechanisms operate solely on topological units. Instead, we conclude that estimation processes act on representations constructed after Gestalt grouping principles, whether similarity based or spatial, have organised incoming visual input.

Estimating neural activity from visual areas using functionally defined EEG templates.

Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.

Theta-phase dependent neuronal coding during sequence learning in human single neurons.

The ability to maintain a sequence of items in memory is a fundamental cognitive function. In the rodent hippocampus, the representation of sequentially organized spatial locations is reflected by the phase of action potentials relative to the theta oscillation (phase precession). We investigated whether the timing of neuronal activity relative to the theta brain oscillation also reflects sequence order in the medial temporal lobe of humans. We used a task in which human participants learned a fixed sequence of pictures and recorded single neuron and local field potential activity with implanted electrodes. We report that spikes for three consecutive items in the sequence (the preferred stimulus for each cell, as well as the stimuli immediately preceding and following it) were phase-locked at distinct phases of the theta oscillation. Consistent with phase precession, spikes were fired at progressively earlier phases as the sequence advanced. These findings generalize previous findings in the rodent hippocampus to the human temporal lobe and suggest that encoding stimulus information at distinct oscillatory phases may play a role in maintaining sequential order in memory.

Human Hippocampal Neurons Track Moments in a Sequence of Events.

An indispensable feature of episodic memory is our ability to temporally piece together different elements of an experience into a coherent memory. Hippocampal time cells-neurons that represent temporal information-may play a critical role in this process. Although these cells have been repeatedly found in rodents, it is still unclear to what extent similar temporal selectivity exists in the human hippocampus. Here, we show that temporal context modulates the firing activity of human hippocampal neurons during structured temporal experiences. We recorded neuronal activity in the human brain while patients of either sex learned predictable sequences of pictures. We report that human time cells fire at successive moments in this task. Furthermore, time cells also signaled inherently changing temporal contexts during empty 10 s gap periods between trials while participants waited for the task to resume. Finally, population activity allowed for decoding temporal epoch identity, both during sequence learning and during the gap periods. These findings suggest that human hippocampal neurons could play an essential role in temporally organizing distinct moments of an experience in episodic memory.SIGNIFICANCE STATEMENT Episodic memory refers to our ability to remember the what, where, and when of a past experience. Representing time is an important component of this form of memory. Here, we show that neurons in the human hippocampus represent temporal information. This temporal signature was observed both when participants were actively engaged in a memory task, as well as during 10-s-long gaps when they were asked to wait before performing the task. Furthermore, the activity of the population of hippocampal cells allowed for decoding one temporal epoch from another. These results suggest a robust representation of time in the human hippocampus.

Subitizing object parts reveals a second stage of individuation.

Humans can efficiently individuate a small number of objects. This subitizing ability is thought to be a consequence of limited attentional resources. However, how and what is selected during the individuation process remain outstanding questions. We investigated these in four experiments by examining if parts of objects are enumerated as efficiently as distinct objects in the presence and absence of distractor objects. We found that distractor presence reduced subitizing efficiency. Crucially, parts connected to multiple objects were enumerated less efficiently than independent objects or parts connected to a single object. These results argue against direct individuation of parts and show that objecthood plays a fundamental role in individuation. Objects are selected first and their components are selected in subsequent steps. This reveals that individuation operates sequentially over multiple levels.

A simple rule to describe interactions between visual categories.

Humans can rapidly categorise visual objects when presented in isolation. However, in everyday life we encounter multiple objects at the same time. Far less is known about how simultaneously active object representations interact. We examined such interactions by asking participants to categorise a target object at the basic (Experiment 1) or the superordinate (Experiment 2) level while the representation of another object was still active. We found that the "prime" object strongly modulated the response to the target implying that the prime's category was rapidly and automatically accessed, influencing subsequent categorical processing. Using drift diffusion modelling, we show that a prime, whose category is different from that of the target, interferes with target processing primarily during the evidence accumulation stage. This suggests that the state of category-processing neurons is altered by an active representation and this modifies the processing of other categories. Interestingly, the strength of interference increases with the similarity between the distractor and the target category. Considering these results and previous studies, we propose a general principle that category interactions are determined by the distance from a distractor's representation to the target's task-relevant categorical boundary. We argue that this principle arises from the specific architectural organisation of categories in the brain.

Neural responses to apparent motion can be predicted by responses to non-moving stimuli.

When two objects are presented in alternation at two locations, they are seen as a single object moving from one location to the other. This apparent motion (AM) percept is experienced for objects located at short and also at long distances. However, current models cannot explain how the brain integrates information over large distances to create such long-range AM. This study investigates the neural markers of AM by parcelling out the contribution of spatial and temporal interactions not specific to motion. In two experiments, participants' EEG was recorded while they viewed two stimuli inducing AM. Different combinations of these stimuli were also shown in a static context to predict an AM neural response where no motion is perceived. We compared the goodness of fit between these different predictions and found consistent results in both experiments. At short-range, the addition of the inhibitory spatial and temporal interactions not specific to motion improved the AM prediction. However, there was no indication that spatial or temporal non-linear interactions were present at long-range. This suggests that short- and long-range AM rely on different neural mechanisms. Importantly, our results also show that at both short- and long-range, responses generated by a moving stimulus could be well predicted from conditions in which no motion is perceived. That is, the EEG response to a moving stimulus is simply a combination of individual responses to non-moving stimuli. This demonstrates a dissociation between the brain response and the subjective percept of motion.

Briefly Flashed Scenes Can Be Stored in Long-Term Memory.

The capacity of human memory is impressive. Previous reports have shown that when asked to memorize images, participants can recognize several thousands of visual objects in great details even with a single viewing of a few seconds per image. In this experiment, we tested recognition performance for natural scenes that participants saw for 20 ms only once (untrained group) or 22 times over many days (trained group) in an unrelated task. 400 images (200 previously viewed and 200 novel images) were flashed one at a time and participants were asked to lift their finger from a pad whenever they thought they had already seen the image (go/no-go paradigm). Compared to previous reports of excellent recognition performance with only single presentations of a few seconds, untrained participants were able to recognize only 64% of the 200 images they had seen few minutes before. On the other hand, trained participants, who had processed the flashed images (20 ms) several times, could correctly recognize 89% of them. EEG recordings confirmed these behavioral results. As early as 230 ms after stimulus onset, a significant event-related-potential (ERP) difference between familiar and new images was observed for the trained but not for the untrained group. These results show that briefly flashed unmasked scenes can be incidentally stored in long-term memory when repeated.

Individuation of objects and object parts rely on the same neuronal mechanism.

Recent results have shown that participants can enumerate multiple parts of a single object as efficiently as multiple distinct objects, suggesting a shared mechanism for individuation of objects and object parts. Here we used the subitizing phenomenon to investigate the neural mechanism underlying the individuation of object parts. In two experiments, we measured a lateralized EEG response (N2pc) previously associated with individuation of multiple objects. In line with the subitizing effect, participants' error rate was low (less than 10%) when enumerating up to approximately three parts of an object but increased for larger numerosities. The N2pc amplitude increased as a function of the number of object parts, and reached an asymptote corresponding to the subitizing limit, replicating previous reports for separate objects. These results invite the inference that the same neural mechanism underlies individuation of multiple distinct objects and multiple parts of a single object.

Learning of anticipatory responses in single neurons of the human medial temporal lobe.

Neuronal processes underlying the formation of new associations in the human brain are not yet well understood. Here human participants, implanted with depth electrodes in the brain, learned arbitrary associations between images presented in an ordered, predictable sequence. During learning we recorded from medial temporal lobe (MTL) neurons that responded to at least one of the pictures in the sequence (the preferred stimulus). We report that as a result of learning, single MTL neurons show asymmetric shifts in activity and start firing earlier in the sequence in anticipation of their preferred stimulus. These effects appear relatively early in learning, after only 11 exposures to the stimulus sequence. The anticipatory neuronal responses emerge while the subjects became faster in reporting the next item in the sequence. These results demonstrate flexible representations that could support learning of new associations between stimuli in a sequence, in single neurons in the human MTL.

Stimulus duration and diversity do not reverse the advantage for superordinate-level representations: the animal is seen before the bird.

Basic-level categorization has long been thought to be the entry level for object representations. However, this view is now challenged. In particular, Macé et al. [M.J.-M. Macé et al. (2009) PLoS One, 4, e5927] showed that basic-level categorization (such as 'bird') requires a longer processing time than superordinate-level categorization (such as 'animal'). It has been argued that this result depends on the brief stimulus presentation times used in their study, which would degrade the visual information available. Here, we used a go/no-go paradigm to test whether the superordinate-level advantage could be observed with longer stimulus durations, and also investigated the impact of manipulating the target and distractor set heterogeneity. Our results clearly show that presentation time had no effect on categorization performance. Both target and distractor diversity influenced performance, but basic-level categories were never accessed faster or with higher accuracy than superordinate-level categories. These results argue in favor of coarse to fine visual processing to access perceptual representations.

A need for more information uptake but not focused attention to access basic-level representations.

Complex visual scenes can be categorized at the superordinate level (e.g., animal/non-animal or vehicle/non-vehicle) without focused attention. However, rapid visual categorization at the basic level (e.g., dog/non-dog or car/non-car) requires additional processing time. Such finer categorization might, thus, require attentional resources. This hypothesis was tested in the current study with a dual-task paradigm in which subjects performed a basic-level categorization task in peripheral vision either alone (single-task condition) or concurrently with an attentionally demanding letter discrimination task (dual-task condition). Our results indicate that basic-level categorization of either biological (dog/non-dog animal) or man-made (car/non-car vehicle) stimuli requires more information uptake but can, nevertheless, be performed when attention is not fully available, presumably because it is supported by hardwired, specialized neuronal networks.