Neural computations in prosopagnosia.

We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PS's ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PS's early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PS' brain representations with those of deep neural networks (DNN). We found that the computations underlying PS' brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PS's deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics.

Rhythmic Information Sampling in the Brain during Visual Recognition.

When we fixate an object, visual information is continuously received on the retina. Several studies observed behavioral oscillations in perceptual sensitivity across such stimulus time, and these fluctuations have been linked to brain oscillations. However, whether specific brain areas show oscillations across stimulus time (i.e., different time points of the stimulus being more or less processed, in a rhythmic fashion) has not been investigated. Here, we revealed random areas of face images at random moments across time and recorded the brain activity of male and female human participants using MEG while they performed two recognition tasks. This allowed us to quantify how each snapshot of visual information coming from the stimulus is processed across time and across the brain. Oscillations across stimulus time (rhythmic sampling) were mostly visible in early visual areas, at theta, alpha, and low beta frequencies. We also found that they contributed to brain activity more than previously investigated rhythmic processing (oscillations in the processing of a single snapshot of visual information). Nonrhythmic sampling was also visible at later latencies across the visual cortex, either in the form of a transient processing of early stimulus time points or of a sustained processing of the whole stimulus. Our results suggest that successive cycles of ongoing brain oscillations process stimulus information incoming at successive moments. Together, these results advance our understanding of the oscillatory neural dynamics associated with visual processing and show the importance of considering the temporal dimension of stimuli when studying visual recognition.SIGNIFICANCE STATEMENT Several behavioral studies have observed oscillations in perceptual sensitivity over the duration of stimulus presentation, and these fluctuations have been linked to brain oscillations. However, oscillations across stimulus time in the brain have not been studied. Here, we developed an MEG paradigm to quantify how visual information received at each moment during fixation is processed through time and across the brain. We showed that different snapshots of a stimulus are distinctly processed in many brain areas and that these fluctuations are oscillatory in early visual areas. Oscillations across stimulus time were more prevalent than previously studied oscillations across processing time. These results increase our understanding of how neural oscillations interact with the visual processing of temporal stimuli.

Reclassifying guesses to increase signal-to-noise ratio in psychological experiments.

This paper introduces a novel procedure that can increase the signal-to-noise ratio in psychological experiments that use accuracy as a selection variable for another dependent variable. This procedure relies on the fact that some correct responses result from guesses and reclassifies them as incorrect responses using a trial-by-trial reclassification evidence such as response time. It selects the optimal reclassification evidence criterion beyond which correct responses should be reclassified as incorrect responses. We show that the more difficult the task and the fewer the response alternatives, the more to be gained from this reclassification procedure. We illustrate the procedure on behavioral and ERP data from two different datasets (Caplette et al. NeuroImage 218, 116994, 2020; Faghel-Soubeyrand et al. Journal of Experimental Psychology: General 148, 1834-1841, 2019) using response time as reclassification evidence. In both cases, the reclassification procedure increased signal-to-noise ratio by more than 13%. Matlab and Python implementations of the reclassification procedure are openly available ( https://github.com/GroupeLaboGosselin/Reclassification ).

Effects of stand structure and ungulates on understory vegetation in managed and unmanaged forests.

Conventional conservation policies in Europe notably rely on the passive restoration of natural forest dynamics by setting aside forest areas to preserve forest biodiversity. However, since forest reserves cover only a small proportion of the territory, conservation policies also require complementary conservation efforts in managed forests in order to achieve the biodiversity targets set up in the Convention on Biological Diversity. Conservation measures also raise the question of large herbivore management in and around set-asides, particularly regarding their impact on understory vegetation. Although many studies have separately analyzed the effects of forest management, management abandonment, and ungulate pressure on forest biodiversity, their joint effects have rarely been studied in a correlative framework. We studied 212 plots located in 15 strict forest reserves paired with adjacent managed forests in European France. We applied structural equation models to test the effects of management abandonment, stand structure, and ungulate pressure on the abundance, species richness, and diversity of herbaceous vascular plants and terricolous bryophytes. We showed that stand structure indices and plot-level browsing pressure had direct and opposite effects on herbaceous vascular plant species diversity; these effects were linked with the light tolerance of the different species groups. Increasing canopy cover had an overall negative effect on herbaceous vascular plant abundance and species diversity. The effect was two to three times greater in magnitude than the positive effects of browsing pressure on herbaceous plants diversity. On the other hand, a high stand density index had a positive effect on the species richness and diversity of bryophytes, while browsing had no effect. Forest management abandonment had few direct effects on understory plant communities, and mainly indirectly affected herbaceous vascular plant and bryophyte abundance and species richness and diversity through changes in vertical stand structure. Our results show that conservation biologists should rely on foresters and hunters to lead the preservation of understory vegetation communities in managed forests since, respectively, they manipulate stand structure and regulate ungulate pressure. Their management actions should be adapted to the taxa at stake, since bryophytes and vascular plants respond differently to stand and ungulate factors.

Real-world expectations and their affective value modulate object processing.

It is well known that expectations influence how we perceive the world. Yet the neural mechanisms underlying this process remain unclear. Studies about the effects of prior expectations have focused so far on artificial contingencies between simple neutral cues and events. Real-world expectations are however often generated from complex associations between contexts and objects learned over a lifetime. Additionally, these expectations may contain some affective value and recent proposals present conflicting hypotheses about the mechanisms underlying affect in predictions. In this study, we used fMRI to investigate how object processing is influenced by realistic context-based expectations, and how affect impacts these expectations. First, we show that the precuneus, the inferotemporal cortex and the frontal cortex are more active during object recognition when expectations have been elicited a priori, irrespectively of their validity or their affective intensity. This result supports previous hypotheses according to which these brain areas integrate contextual expectations with object sensory information. Notably, these brain areas are different from those responsible for simultaneous context-object interactions, dissociating the two processes. Then, we show that early visual areas, on the contrary, are more active during object recognition when no prior expectation has been elicited by a context. Lastly, BOLD activity was shown to be enhanced in early visual areas when objects are less expected, but only when contexts are neutral; the reverse effect is observed when contexts are affective. This result supports the proposal that affect modulates the weighting of sensory information during predictions. Together, our results help elucidate the neural mechanisms of real-world expectations.

Disentangling presentation and processing times in the brain.

Visual object recognition seems to occur almost instantaneously. However, not only does it require hundreds of milliseconds of processing, but our eyes also typically fixate the object for hundreds of milliseconds. Consequently, information reaching our eyes at different moments is processed in the brain together. Moreover, information received at different moments during fixation is likely to be processed differently, notably because different features might be selectively attended at different moments. Here, we introduce a novel reverse correlation paradigm that allows us to uncover with millisecond precision the processing time course of specific information received on the retina at specific moments. Using faces as stimuli, we observed that processing at several electrodes and latencies was different depending on the moment at which information was received. Some of these variations were caused by a disruption occurring 160-200 â€‹ms after the face onset, suggesting a role of the N170 ERP component in gating information processing; others hinted at temporal compression and integration mechanisms. Importantly, the observed differences were not explained by simple adaptation or repetition priming, they were modulated by the task, and they were correlated with differences in behavior. These results suggest that top-down routines of information sampling are applied to the continuous visual input, even within a single eye fixation.

Trade-offs between carbon stocks and biodiversity in European temperate forests.

Policies to mitigate climate change and biodiversity loss often assume that protecting carbon-rich forests provides co-benefits in terms of biodiversity, due to the spatial congruence of carbon stocks and biodiversity at biogeographic scales. However, it remains unclear whether this holds at the scales relevant for management, and particularly large knowledge gaps exist for temperate forests and for taxa other than trees. We built a comprehensive dataset of Central European temperate forest structure and multi-taxonomic diversity (beetles, birds, bryophytes, fungi, lichens, and plants) across 352 plots. We used Boosted Regression Trees (BRTs) to assess the relationship between above-ground live carbon stocks and (a) taxon-specific richness, (b) a unified multidiversity index. We used Threshold Indicator Taxa ANalysis to explore individual species' responses to changing above-ground carbon stocks and to detect change-points in species composition along the carbon-stock gradient. Our results reveal an overall weak and highly variable relationship between richness and carbon stock at the stand scale, both for individual taxonomic groups and for multidiversity. Similarly, the proportion of win-win and trade-off species (i.e., species favored or disadvantaged by increasing carbon stock, respectively) varied substantially across taxa. Win-win species gradually replaced trade-off species with increasing carbon, without clear thresholds along the above-ground carbon gradient, suggesting that community-level surrogates (e.g., richness) might fail to detect critical changes in biodiversity. Collectively, our analyses highlight that leveraging co-benefits between carbon and biodiversity in temperate forest may require stand-scale management that prioritizes either biodiversity or carbon in order to maximize co-benefits at broader scales. Importantly, this contrasts with tropical forests, where climate and biodiversity objectives can be integrated at the stand scale, thus highlighting the need for context-specificity when managing for multiple objectives. Accounting for critical change-points of target taxa can help to deal with this specificity, by defining a safe operating space to manipulate carbon while avoiding biodiversity losses.

Use of Face Information Varies Systematically From Developmental Prosopagnosics to Super-Recognizers.

Face-recognition abilities differ largely in the neurologically typical population. We examined how the use of information varies with face-recognition ability from developmental prosopagnosics to super-recognizers. Specifically, we investigated the use of facial features at different spatial scales in 112 individuals, including 5 developmental prosopagnosics and 8 super-recognizers, during an online famous-face-identification task using the bubbles method. We discovered that viewing of the eyes and mouth to identify faces at relatively high spatial frequencies is strongly correlated with face-recognition ability, evaluated from two independent measures. We also showed that the abilities of developmental prosopagnosics and super-recognizers are explained by a model that predicts face-recognition ability from the use of information built solely from participants with intermediate face-recognition abilities ( n = 99). This supports the hypothesis that the use of information varies quantitatively from developmental prosopagnosics to super-recognizers as a function of face-recognition ability.

Ecological research and environmental management: We need different interfaces based on different knowledge types.

The role of ecological science in environmental management has been discussed by many authors who recognize that there is a persistent gap between ecological science and environmental management. Here we develop theory through different perspectives based on knowledge types, research categories and research-management interface types, which we combine into a common framework. To draw out insights for bridging this gap, we build our case by:We point out the complementarities as well as the specificities and limitations of the different types of ecological research, ecological knowledge and research-management interfaces, which is of major importance for environmental management and research policies.

Stationary Objects Flashed Periodically Appear to Move During Smooth Pursuit Eye Movement.

We discovered that a white disc flashed twice at the same location appears to move during smooth pursuit eye tracking in the direction opposite to that of the eye movement. We called this novel phenomenon movement-induced apparent motion (MIAM). Using the method of constant stimuli, we measured the required displacement of the second appearance of the disc in the pursuit direction to null the effect during the closed-loop stage of smooth pursuit eye tracking. We observed a strong linear relationship between the points of subjective stationarity and the inter-stimuli intervals for four smooth pursuit eye movement speeds. The slopes and y-intercepts of these linear fits were well predicted by the hypothesis according to which subjects saw illusory motion from the first to the second retinal projections of the flashed disc during smooth pursuit eye movement, with no extra-retinal signal compensation.

The influence of natural contour and face size on the spatial frequency tuning for identifying upright and inverted faces.

It has previously been proposed that holistic face processing is based on low spatial frequencies (SFs) whereas featural processing relies on higher SFs, a hypothesis still widespread in the face processing literature today (e.g. Peters et al. in Eur J Neurosci 37(9):1448-1457, 2013). Since upright faces are supposedly recognized through holistic processing and inverted faces, using features, it is easy to take the leap to suggest a qualitatively different SF tuning for the identification of upright and vs. inverted faces. However, two independent studies (e.g. Gaspar et al. in Vision Res 48(28):2817-2826, 2008; Willenbockel et al. in J Exp Psychol Human 36(1):122-135, 2010a) found the same SF tuning for both stimulus presentations. Since these authors used relatively small faces hiding the natural facial contour, it is possible that differences in the SF tuning for identifying upright and inverted faces were missed. The present study thus revisits the SF tuning for upright and inverted faces face identification using the SF Bubbles technique. Our results still indicate that the same SFs are involved in both upright and inverted face recognition regardless of these additional parameters (contour and size), thus contrasting with previous data obtained using different methods (e.g. Oruc and Barton in J Vis 10(12):20, 1-12, 2010). The possible reasons subtending this divergence are discussed.

Orientations for the successful categorization of facial expressions and their link with facial features.

Horizontal information was recently suggested to be crucial for face identification. In the present paper, we expand on this finding and investigate the role of orientations for all the basic facial expressions and neutrality. To this end, we developed orientation bubbles to quantify utilization of the orientation spectrum by the visual system in a facial expression categorization task. We first validated the procedure in Experiment 1 with a simple plaid-detection task. In Experiment 2, we used orientation bubbles to reveal the diagnostic-i.e., task relevant-orientations for the basic facial expressions and neutrality. Overall, we found that horizontal information was highly diagnostic for expressions-surprise excepted. We also found that utilization of horizontal information strongly predicted performance level in this task. Despite the recent surge of research on horizontals, the link with local features remains unexplored. We were thus also interested in investigating this link. In Experiment 3, location bubbles were used to reveal the diagnostic features for the basic facial expressions. Crucially, Experiments 2 and 3 were run in parallel on the same participants, in an interleaved fashion. This way, we were able to correlate individual orientation and local diagnostic profiles. Our results indicate that individual differences in horizontal tuning are best predicted by utilization of the eyes.

Statistical ecology comes of age.

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Paper features: a neglected source of information for letter recognition.

Adult observers have surprisingly low calculation efficiencies for letter recognition (see, e.g., Pelli, Burns, Farell, & Moore-Page, 2006). Here, we examine the possibility that this is partly due to observers' neglecting paper features (e.g., the absence of ascenders and descenders in 'o'). Each of 16 observers completed 5,000 trials of a single-letter two-alternative forced-choice detection task. Using a combination of classification image analyses and Bayesian statistical analyses, we argue that between 60% and 75% of our participants indeed neglected paper features.

Decoding face recognition abilities in the human brain.

Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilities-super-recognizers-and typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1 s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain.

The informational correlates of conscious and nonconscious face-gender perception.

We used a face-gender repetition priming paradigm to precisely map the spatial frequencies (SFs) that influence observers' responses under different prime awareness conditions. A visible prime condition was set up by presenting the stimulus sequence mask-blank-prime-blank-mask-target and an invisible prime condition by switching the order of the masks and the blanks (see also Dehaene et al., 2001). The prime faces (~4.6° × 3.1°) were randomly filtered trial-by-trial according to the SF bubbles technique (Willenbockel, Fiset et al., 2010). Classification vectors, derived by summing the SF filters from each trial weighted by observers' transformed response times, revealed that SFs around 12 cycles per face width modulated responses in both prime awareness conditions. The significant SFs closely matched those optimal for accurate performance in a direct face-gender classification paradigm. Surprisingly, the significant SFs facilitated observers' responses in the visible prime condition, whereas they slowed responses in the invisible prime condition. Our findings suggest that SF tuning per se remains robust under different prime awareness conditions but that diagnostic visual cues might be utilized in a qualitatively different fashion as a function of awareness.

Subjectively homogeneous noise over written text as a tool to investigate the perceptual mechanisms involved in reading.

In an effort to understand the factors influencing text legibility in natural reading, we adapted the visual spread method (Poirier, Gosselin, & Arguin, 2008) to natural text. Stimuli were sentences conforming to MNREAD standards (Legge, Ross, Luebker, & LaMay 1989) mixed with dynamic probabilistic noise-i.e., each pixel in the image is associated with a probability that its polarity is inverted on a given refresh cycle of the display screen. Noise level varied continuously over the image as initially determined by Gaussian-filtered noise. Participants adjusted noise levels in the text using the mouse until the text appeared homogenously noisy. We assume that participants increased (or decreased) noise at locations where stimulus features were easy (or difficult) to encode and thus that local noise settings correlate with legibility. Data from 11 participants and 30 sentences revealed interesting effects, demonstrating the validity of the method for assessing the impact of various factors on noise resistance in natural text. For example, participants increased noise over (a) spaces and adjacent letters, (b) the second half of words, (c) words with more orthographic neighbors but fewer phonological neighbors, (d) less useful word types, (e) less complex letters, and (f) diagnostic letters (a novel metric). Our observations also offer significant insights on constraints acting upon letter identification as well as on higher-level processes that are involved in reading.

Reading laterally: the cerebral hemispheric use of spatial frequencies in visual word recognition.

It is generally accepted that the left hemisphere (LH) is more capable for reading than the right hemisphere (RH). Left hemifield presentations (initially processed by the RH) lead to a globally higher error rate, slower word identification, and a significantly stronger word length effect (i.e., slower reaction times for longer words). Because the visuo-perceptual mechanisms of the brain for word recognition are primarily localized in the LH (Cohen et al., 2003), it is possible that this part of the brain possesses better spatial frequency (SF) tuning for processing the visual properties of words than the RH. The main objective of this study is to determine the SF tuning functions of the LH and RH for word recognition. Each word image was randomly sampled in the SF domain using the SF bubbles method (Willenbockel et al., 2010) and was presented laterally to the left or right visual hemifield. As expected, the LH requires less visual information than the RH to reach the same level of performance, illustrating the well-known LH advantage for word recognition. Globally, the SF tuning of both hemispheres is similar. However, these seemingly identical tuning functions hide important differences. Most importantly, we argue that the RH requires higher SFs to identify longer words because of crowding.

Untangling the impact of plantation type and functional traits on ecosystem nutrient stocks in an experimentally restored forest ecosystem.

The primary objective of ecological restoration is recovering biodiversity and ecosystem functioning. While a functional trait-based approach can help understand community assembly and ecosystem function recovery during ecological restoration, there still exists a knowledge gap in assessing how functional traits indicate the mediating roles of the plant community in response to forest restoration effects on ecosystem functions. This study applied the "response-effect trait" framework to investigate experimentally whether the treatment of plantation type has an impact on community trait compositions, which in turn could affect forest ecosystem nutrient stocks - here, carbon (C) and nitrogen (N) and phosphorus (P) stocks in tree, understory, litter and soil pools at an experimental station in subtropical China. We used structural equation models (SEMs) to examine the relationships among plantation type, community weighted mean of traits, and nutrient stocks in each pool. Our results show that most of the tree and understory traits studied were response traits to plantation type. Moreover, certain traits played a significant role in mediating plantation-type effects on C, N and P stocks for understory pool (e.g., understory stem specific density and specific leaf area, tree leaf phosphorus content), and for litter and soil pools (e.g., tree leaf carbon or phosphorus content, understory specific leaf area, leaf nitrogen or phosphorus content), known as "response-effect traits". For the tree pool, only effect traits, and no "response-effect" tree traits, were found for the N stock. Total effects of SEMs indicated that, understory or tree traits can have a greater impact than plantation type on understory or litter C, N or P stocks. After approximately 35 years of natural restoration, exotic plantations exhibited a different community trait characteristic from native plantations. The important roles of traits in mediating the effects of plantation type on non-tree pool C, N and P stocks were highlighted.