Rémy Schmitz

Age-related changes in visual pseudoneglect

Pseudoneglect is a slight but consistent leftward attentional bias commonly observed in healthy young populations, purportedly explained by right hemispheric dominance. It has been suggested that normal aging might be associated with a decline of the right hemisphere. According to this hypothesis, a few studies have shown that elderly tend to exhibit a rightward attentional bias in line bisection. In the present study, we tested this hypothesis in young and older participants using a perceptual landmark task. Results yield evidence for an age-related shift, from a strong attentional leftward bias in young adults toward a suppressed or even a reversed bias in the elderly. Right hemisphere impairment coupled to a left hemispheric compensation might explain the perceptual shift observed in older adults. However, a decline in corpus callosum function cannot be excluded. Alternatively, these results may be in agreement with the hypothesis of an age-related specific inhibition of return dysfunction, an overt attentional orienting mechanism, and/or a decrease of dopamine.

Selective modulations of attentional asymmetries after sleep deprivation

Pseudoneglect is a slight but consistent misplacement of attention toward the left visual field, commonly observed in young healthy subjects. This leftward attentional bias is thought to result from a right hemispheric dominance in visuospatial processing. Changes in endogenous levels of alertness may modulate attentional asymmetries and pseudoneglect in particular. In line with this hypothesis, it has been shown that sleep deprived shift-workers present a reversal of their attentional bias in a landmark (LDM) task (Manly, T., Dobler, V. B., Dodds, C. M., & George, M. A. (2005). Rightward shift in spatial awareness with declining alertness. Neuropsychologia, 43(12), 1721-1728). However, circadian disturbances and fatigue effects at the end of a shift work may have contributed to this reversal effect. In a first experiment, we show that sleep deprivation (SD) under controlled conditions does not markedly change the leftward bias, observable both at 21:00 and at 07:00 after SD. In a second experiment, we tested the hypothesis that a drastic reduction or inversion in the attentional bias would be present only when both the circadian drive for sleep propensity is maximal (i.e. around 05:00) and homeostatic sleep pressure is high. Thus participants were tested at 21:00 and under SD conditions at 05:00 and 09:00. Additionally, we used the greyscales (GS) task well-known to evidence a leftward bias in luminance judgments. Although results evidenced a consistent leftward bias both in the LDM and GS, we found a suppression of the leftward bias at the circadian nadir of alertness (05:00) after SD only for the GS, but not for the LDM. Noticeably, the leftward bias in the GS vanished at 05:00 after SD but reappeared at 09:00 despite continued SD, suggesting a predominant circadian influence on attentional asymmetries in the GS. Additionally, inter-sessions correlations evidenced a reproducible, consistent bias both in the LDM and GS, with no consistent relationship between the two tasks, suggesting independence of the neural networks subtending performance in LDM and GS. Overall, our results suggest that SD per se does not impede the leftward bias both in LDM and GS, whereas circadian-related variations in vigilance may impact attentional asymmetries in luminance judgments.

Sleep-dependent Neurophysiological Processes in Implicit Sequence Learning

Behavioral studies have cast doubts about the role that posttraining sleep may play in the consolidation of implicit sequence learning. Here, we used event-related fMRI to test the hypothesis that sleep-dependent functional reorganization would take place in the underlying neural circuits even in the possible absence of obvious behavioral changes. Twenty-four healthy human adults were scanned at Day 1 and then at Day 4 during an implicit probabilistic serial RT task. They either slept normally (RS) or were sleep-deprived (SD) on the first posttraining night. Unknown to them, the sequential structure of the material was based on a probabilistic finite-state grammar, with 15% chance on each trial of replacing the rules-based grammatical (G) stimulus with a nongrammatical (NG) one. Results indicated a gradual differentiation across sessions between RTs (faster RTs for G than NG), together with NG-related BOLD responses reflecting sequence learning. Similar behavioral patterns were observed in RS and SD participants at Day 4, indicating time- but not sleep-dependent consolidation of performance. Notwithstanding, we observed at Day 4 in the RS group a diminished differentiation between G- and NG-related neurophysiological responses in a set of cortical and subcortical areas previously identified as being part of the network involved in implicit sequence learning and its offline processing during sleep, indicating a sleep-dependent processing of both regular and deviant stimuli. Our results suggest the sleep-dependent development of distinct neurophysiological processes subtending consolidation of implicit motor sequence learning, even in the absence of overt behavioral differences.

Implicit learning is better at subjectively defined non-optimal time of day.

Individual preferences in morningness-eveningness rhythms modulate temporal fluctuations of cognitive performance over a normal day. Besides enhanced cognitive performance at individuals peak time as derived from morningness-eveningness questionnaires, a few studies have shown increased implicit memory abilities at a non-optimal (NOP) time of day. Various subjective factors might also determine the clock time for high or low cognitive efficiency. Using an artificial grammar learning (AGL) task, we show enhanced implicit learning of high-order information at NOP [vs optimal (OP)] time of day as subjectively defined by participants, irrespective of morningness-eveningness scores. Our results suggest that subjectively defined efficiency periods are a modulating factor in the testing of cognitive functions.

Lateralized implicit sequence learning in uni- and bi-manual conditions

It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT), we tested whether participants trained in a divided visual field condition primarily stimulating the RH would learn the implicit regularities embedded in sequential material faster than participants in a condition favoring LH processing. In the first study, half of participants were presented sequences in the left (vs. right) visual field, and had to respond using their ipsilateral hand (unimanual condition), hence making visuo-motor processing possible within the same hemisphere. Results showed successful implicit sequence learning, as indicated by increased reaction time for a transfer sequence in both hemispheric conditions and lack of conscious knowledge in a generation task. There was, however, no evidence of interhemispheric differences. In the second study, we hypothesized that a bimanual response version of the lateralized SRT, which requires interhemispheric communication and increases computational and cognitive processing loads, would favor RH-dependent visuospatial/attentional processes. In this bimanual condition, our results revealed a much higher transfer effect in the RH than in the LH condition, suggesting higher RH sensitivity to the processing of novel sequential material. This LH/RH difference was interpreted within the framework of the Novelty-Routinization model [Goldberg, E., & Costa, L. D. (1981). Hemisphere differences in the acquisition and use of descriptive systems. Brain and Language, 14(1), 144-173] and interhemispheric interactions in attentional processing [Banich, M. T. (1998). The missing link: the role of interhemispheric interaction in attentional processing. Brain and Cognition, 36(2), 128-157].

Sleep and memory consolidation: Motor performance and proactive interference effects in sequence learning

That post-training sleep supports the consolidation of sequential motor skills remains debated. Performance improvement and sensitivity to proactive interference are both putative measures of long-term memory consolidation. We tested sleep-dependent memory consolidation for visuo-motor sequence learning using a proactive interference paradigm. Thirty-three young adults were trained on sequence A on Day 1, then had Regular Sleep (RS) or were Sleep Deprived (SD) on the night after learning. After two recovery nights, they were tested on the same sequence A, then had to learn a novel, potentially competing sequence B. We hypothesized that proactive interference effects on sequence B due to the prior learning of sequence A would be higher in the RS condition, considering that proactive interference is an indirect marker of the robustness of sequence A, which should be better consolidated over post-training sleep. Results highlighted sleep-dependent improvement for sequence A, with faster RTs overnight for RS participants only. Moreover, the beneficial impact of sleep was specific to the consolidation of motor but not sequential skills. Proactive interference effects on learning a new material at Day 4 were similar between RS and SD participants. These results suggest that post-training sleep contributes to optimizing motor but not sequential components of performance in visuo-motor sequence learning.

Afternoon Nap and Bright Light Exposure Improve Cognitive Flexibility Post Lunch

Beneficial effects of napping or bright light exposure on cognitive performance have been reported in participants exposed to sleep loss. Nonetheless, few studies investigated the effect of these potential countermeasures against the temporary drop in performance observed in mid-afternoon, and even less so on cognitive flexibility, a crucial component of executive functions. This study investigated the impact of either an afternoon nap or bright light exposure on post-prandial alterations in task switching performance in well-rested participants. Twenty-five healthy adults participated in two randomized experimental conditions, either wake versus nap (n=15), or bright light versus placebo (n=10). Participants were tested on a switching task three times (morning, post-lunch and late afternoon sessions). The interventions occurred prior to the post-lunch session. In the nap/wake condition, participants either stayed awake watching a 30-minute documentary or had the opportunity to take a nap for 30 minutes. In the bright light/placebo condition, participants watched a documentary under either bright blue light or dim orange light (placebo) for 30 minutes. The switch cost estimates cognitive flexibility and measures task-switching efficiency. Increased switch cost scores indicate higher difficulties to switch between tasks. In both control conditions (wake or placebo), accuracy switch-cost score increased post lunch. Both interventions (nap or bright light) elicited a decrease in accuracy switch-cost score post lunch, which was associated with diminished fatigue and decreased variability in vigilance. Additionally, there was a trend for a post-lunch benefit of bright light with a decreased latency switch-cost score. In the nap group, improvements in accuracy switch-cost score were associated with more NREM sleep stage N1. Thus, exposure to bright light during the post-lunch dip, a countermeasure easily applicable in daily life, results in similar beneficial effects as a short nap on performance in the cognitive flexibility domain with possible additional benefits on latency switch-cost scores.

Sleep and Forgetting

Forgetting is a common, often troubling, experience. Failing to remember where we left our keys, the name of a colleague, the meaning of a word we once knew, or an errand that needed to be done on the way home, can be embarrassing and, at times, quite costly. Not all instances of forgetting are unpleasant, however. More often than we realize our goal is actually to forget, rather than remember. For example, forgetting is adaptive when we move and must unlearn information that is no longer relevant, such as our old phone number and address. Similarly, workers who must repeat similar activities throughout a workday, such as a waiter who takes many similar orders in a shift, would likely be better off if they could forget the orders from earlier in the day. Thus, while many of us desire to have a perfect memory, in many ways we would be disadvantaged if we were to remember every experience. Why do we forget? This question was once one of the most prominent topics of research on memory, with much of the original work inspired by Ebbinghaus (1885/1913), who carefully documented the rate at which he forgot nonsense syllables. Early accounts pitted the idea that memories passively decay over time against the notion that subsequent learning interferes with our prior experiences, either by disrupting the consolidation of those traces into durable memories or by interfering with our ability to retrieve them. Over time, each of these theories has experienced difficulty explaining some aspects of forgetting and, thus, none has been able to provide a unified account of forgetting. Regrettably, this has meant that the field has never settled on a cohesive theory of forgetting, with modern overviews tending to focus on describing a set of experimental results without a clear theoretical account of why forgetting occurs. Given the ubiquity of forgetting in everyday life, however, a comprehensive understanding of its causes is of prime importance to theories of memory. Perhaps the primary failing of these earlier theories was the implicit assumption that forgetting is produced by a single mechanism. Instead, forgetting may arise from a disruption to any of the events that promote successful memory. Here we propose five distinct mechanisms that produce forgetting, none of which alone is sufficient to account for all types of forgetting. In the following sections, we describe the behavioral and neuroimaging evidence supporting the existence of each ofWhy do we sleep? Even after decades of investigation, this simple question remains an open issue. Indeed, there is no single answer, and complementary functional hypotheses have been suggested. For instance, it has been proposed that we sleep in order to preserve energy (Berger & Phillips, 1995), to keep cerebral thermoregulation constant (McGinty & Szymusiak, 1990), to detoxify neural cells (Inoue, Honda, & Komoda, 1995), to restore tissues (Adam & Oswald, 1977), and to preserve genetically programmed behavioural patterns (Jouvet, 1991). An additional hypothesis of interest is that sleep aids the long-term storage of memories recently acquired during wakefulness, and thus that it helps to prevent forgetting. Quintilien raised a similar idea in the 1st century AD (see Dudai, 2004). However, it was not until the beginning of the 20th century that this hypothesis was tested empirically. The first known experimental study on this matter was performed by Jenkins and Dallenbach in 1924. They showed that the classical Ebbinghaus forgetting curve for nonsense syllables was markedly dampened if the time between learning and recall was spent asleep, as opposed to time spent in the waking state. However, according to these authors and their immediate successors (e.g., Newman, 1939; Van Ormer, 1933), sleep merely had a passive role in the prevention of oblivion, by protecting novel memories from the intrusion of interfering information arising during wakefulness. A more active role for sleep was advocated 50 years later by the Nobel Prize recipient Francis Crick, who proposed with Mitchison (1983) that sleep allows us to forget undesirable memories. In their view, which is rooted in the connectionism framework, memories are specific configurations of synaptic strengths within neuronal network assemblies, and learning can be defined as the ongoing modification of these synaptic strengths. According to Crick and

Recurrent boosting effects of short inactivity delays on performance: an ERPs study

BackgroundRecent studies investigating off-line processes of consolidation in motor learning have demonstrated a sudden, short-lived improvement in performance after 5–30 minutes of post-training inactivity. Here, we investigated further this behavioral boost in the context of the probabilistic serial reaction time task, a paradigm of implicit sequence learning. We looked both at the electrophysiological correlates of the boost effect and whether this phenomenon occurs at the initial training session only.FindingsReaction times consistently improved after a 30-minute break within two sessions spaced four days apart, revealing the reproducibility of the boost effect. Importantly, this improvement was unrelated to the acquisition of the sequential regularities in the material. At both sessions, event-related potentials (ERPs) analyses disclosed a boost-associated increased amplitude of a first negative component, and shorter latencies for a second positive component.ConclusionBehavioral and ERP data suggest increased processing fluency after short delays, which may support transitory improvements in attentional and/or motor performance and participate in the final setting up of the neural networks involved in the acquisition of novel skills.

MEG Correlates of Learning Novel Objects Properties in Children

Learning the functional properties of objects is a core mechanism in the development of conceptual, cognitive and linguistic knowledge in children. The cerebral processes underlying these learning mechanisms remain unclear in adults and unexplored in children. Here, we investigated the neurophysiological patterns underpinning the learning of functions for novel objects in 10-year-old healthy children. Event-related fields (ERFs) were recorded using magnetoencephalography (MEG) during a picture-definition task. Two MEG sessions were administered, separated by a behavioral verbal learning session during which children learned short definitions about the “magical” function of 50 unknown non-objects. Additionally, 50 familiar real objects and 50 other unknown non-objects for which no functions were taught were presented at both MEG sessions. Children learned at least 75% of the 50 proposed definitions in less than one hour, illustrating childrens powerful ability to rapidly map new functional meanings to novel objects. Pre- and post-learning ERFs differences were analyzed first in sensor then in source space. Results in sensor space disclosed a learning-dependent modulation of ERFs for newly learned non-objects, developing 500–800 msec after stimulus onset. Analyses in the source space windowed over this late temporal component of interest disclosed underlying activity in right parietal, bilateral orbito-frontal and right temporal regions. Altogether, our results suggest that learning-related evolution in late ERF components over those regions may support the challenging task of rapidly creating new semantic representations supporting the processing of the meaning and functions of novel objects in children.