Brain-derived neurotrophic factor (BDNF) modulates the pruning of synaptically silent axonal arbors. The Met allele of the BDNF gene is associated with a reduction in the neurotrophin's activity-dependent release. We used diffusion-weighted imaging to construct structural brain networks for 36 healthy subjects with known BDNF genotypes. Through permutation testing we discovered clear differences in connection strength between subjects carrying the Met allele and those homozygotic for the Val allele. We trained a Gaussian process classifier capable of identifying the subjects' allelic group with 86% accuracy and high predictive value. In Met carriers structural connectivity was greatly increased throughout the forebrain, particularly in connections corresponding to the anterior and superior corona radiata as well as corticothalamic and corticospinal projections from the sensorimotor, premotor, and prefrontal portions of the internal capsule. Interhemispheric connectivity was also increased via the corpus callosum and anterior commissure, and extremely high connectivity values were found between inferior medial frontal polar regions via the anterior forceps. We propose that the decreased availability of BDNF leads to deficits in axonal maintenance in carriers of the Met allele, and that this produces mesoscale changes in white matter architecture.
The development of fast and reproducible motor behavior is a crucial human capacity. The aim of the present study was to address the relationship between the implementation of consistent behavior during initial training on a sequential motor task (the Finger Tapping Task) and subsequent sleep-dependent motor sequence memory consolidation, using functional magnetic resonance imaging (fMRI) and total sleep deprivation protocol. Our behavioral results indicated significant offline gains in performance speed after sleep whereas performance was only stabilized, but not enhanced, after sleep deprivation. At the cerebral level, we previously showed that responses in the caudate nucleus increase, in parallel to a decrease in its functional connectivity with frontal areas, as performance became more consistent. Here, the strength of the competitive interaction, assessed through functional connectivity analyses, between the caudate nucleus and hippocampo-frontal areas during initial training, predicted delayed gains in performance at retest in sleepers but not in sleep-deprived subjects. Moreover, during retest, responses increased in the hippocampus and medial prefrontal cortex in sleepers whereas in sleep-deprived subjects, responses increased in the putamen and cingulate cortex. Our results suggest that the strength of the competitive interplay between the striatum and the hippocampus, participating in the implementation of consistent motor behavior during initial training, conditions subsequent motor sequence memory consolidation. The latter process appears to be supported by a reorganisation of cerebral activity in hippocampo-neocortical networks after sleep.
This study used a proportion congruency manipulation in the Stroop task in order to investigate, at the behavioral and brain substrate levels, the predictions derived from the Dual Mechanisms of Control (DMC) account of two distinct modes of cognitive control depending on the task context. Three experimental conditions were created that varied the proportion congruency: mostly incongruent (MI), mostly congruent (MC), and mostly neutral (MN) contexts. A reactive control strategy, which corresponds to transient interference resolution processes after conflict detection, was expected for the rare conflicting stimuli in the MC context, and a proactive strategy, characterized by a sustained task-relevant focus prior to the occurrence of conflict, was expected in the MI context. Results at the behavioral level supported the proactive/reactive distinction, with the replication of the classic proportion congruent effect (i.e., less interference and facilitation effects in the MI context). fMRI data only partially supported our predictions. Whereas reactive control for incongruent trials in the MC context engaged the expected fronto-parietal network including dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex, proactive control in the MI context was not associated with any sustained lateral prefrontal cortex activations, contrary to our hypothesis. Surprisingly, incongruent trials in the MI context elicited transient activation in common with incongruent trials in the MC context, especially in DLPFC, superior parietal lobe, and insula. This lack of sustained activity in MI is discussed in reference to the possible involvement of item-specific rather than list-wide mechanisms of control in the implementation of a high task-relevant focus.
Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets.
The present study aimed at identifying the neurophysiological responses associated with auditory stimulation during non-rapid eye movement (NREM) sleep using simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) recordings. It was reported earlier that auditory stimuli produce bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and NREM sleep. However, due to the spontaneous membrane potential fluctuations cortical responses may be highly variable during NREM. Here we now examine the modulation of cerebral responses to tones depending on the presence or absence of sleep spindles and the phase of the slow oscillation. Thirteen healthy young subjects were scanned successfully during stage 2–4 NREM sleep in the first half of the night in a 3 T scanner. Subjects were not sleep-deprived and sounds were post hoc classified according to (i) the presence of sleep spindles or (ii) the phase of the slow oscillation during (±300 ms) tone delivery. These detected sounds were then entered as regressors of interest in fMRI analyses. Interestingly wake-like responses – although somewhat altered in size and location – persisted during NREM sleep, except during present spindles (as previously published in Dang-Vu et al., 2011) and the negative going phase of the slow oscillation during which responses became less consistent or even absent. While the phase of the slow oscillation did not alter brain responses in primary sensory cortex, it did modulate responses at higher cortical levels. In addition EEG analyses show a distinct N550 response to tones during the presence of light sleep spindles and suggest that in deep NREM sleep the brain is more responsive during the positive going slope of the slow oscillation. The presence of short temporal windows during which the brain is open to external stimuli is consistent with the fact that even during deep sleep meaningful events can be detected. Altogether, our results emphasize the notion that spontaneous fluctuations of brain activity profoundly modify brain responses to external information across all behavioral states, including deep NREM sleep.
AEP; sleep; spindles; spontaneous activity; slow-wave phase; EEG/fMRI; fMRI; EEG
Memory consolidation benefits from sleep. Besides strengthening some memory traces, another crucial, albeit overlooked, function of memory is also to erase irrelevant information. Directed forgetting is an experimental approach consisting in presenting “to be remembered” and “to be forgotten” information, that allows selectively decreasing or increasing the strength of individual memory traces according to the instruction provided at learning. This paradigm was used in combination with fMRI to determine, in Humans, what specifically triggers at encoding sleep-dependent compared to time-dependent consolidation. Our data indicate that relevant items which subjects strived to memorize are consolidated during sleep to a greater extend than items that participants did not intend to learn. This process appears to depend on a differential activation of the hippocampus at encoding, which acts as a signal for the offline reprocessing of relevant memories during post-learning sleep episodes.
Adult; Analysis of Variance; Brain Mapping; Female; Hippocampus; blood supply; physiology; Humans; Image Processing, Computer-Assisted; methods; Magnetic Resonance Imaging; methods; Male; Mental Recall; physiology; Oxygen; blood; Photic Stimulation; methods; Reaction Time; physiology; Recognition (Psychology); physiology; Sleep; physiology; Sleep Deprivation; physiopathology; Statistics, Nonparametric; Verbal Learning; physiology; Young Adult; sleep; memory consolidation; hippocampus; fMRI; sleep deprivation; directed forgetting
The directed forgetting paradigm is frequently used to determine the ability to voluntarily suppress information. However, little is known about brain areas associated with information to forget. The present study used functional magnetic resonance imaging to determine brain activity during the encoding and retrieval phases of an item-method directed forgetting recognition task with neutral verbal material in order to apprehend all processing stages that information to forget and to remember undergoes. We hypothesized that regions supporting few selective processes, namely recollection and familiarity memory processes, working memory, inhibitory and selection processes should be differentially activated during the processing of to-be-remembered and to-be-forgotten items. Successful encoding and retrieval of items to remember engaged the entorhinal cortex, the hippocampus, the anterior medial prefrontal cortex, the left inferior parietal cortex, the posterior cingulate cortex and the precuneus; this set of regions is well known to support deep and associative encoding and retrieval processes in episodic memory. For items to forget, encoding was associated with higher activation in the right middle frontal and posterior parietal cortex, regions known to intervene in attentional control. Items to forget but nevertheless correctly recognized at retrieval yielded activation in the dorsomedial thalamus, associated with familiarity-based memory processes and in the posterior intraparietal sulcus and the anterior cingulate cortex, involved in attentional processes.
Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions.
We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FA𝕊T”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional magnetic resonance imaging data acquired while a subject is asleep. FA𝕊T tackles three crucial issues typical of this kind of data: (1) data manipulation (viewing, comparing, chunking, etc.) of long continuous M/EEG recordings, (2) rejection of the fMRI-induced artefact in the EEG signal, and (3) manual sleep-scoring of the M/EEG recording. Currently, the toolbox can efficiently deal with these issues via a GUI, SPM8 batching system or hand-written script. The tools developed are, of course, also useful for other EEG applications, for example, involving simultaneous EEG-fMRI acquisition, continuous EEG eye-balling, and manipulation. Even though the toolbox was originally devised for EEG data, it will also gracefully handle MEG data without any problem. “FA𝕊T” is developed in Matlab as an add-on toolbox for SPM8 and, therefore, internally uses its SPM8-meeg data format. “FA𝕊T” is available for free, under the GNU-GPL.
The default mode network (DMN) is a set of brain regions that consistently shows higher activity at rest compared to tasks requiring sustained focused attention toward externally presented stimuli. The cognitive processes that the DMN possibly underlies remain a matter of debate. It has alternately been proposed that DMN activity reflects unfocused attention toward external stimuli or the occurrence of internally generated thoughts. The present study aimed at clarifying this issue by investigating the neural correlates of the various kinds of conscious experiences that can occur during task performance. Four classes of conscious experiences (i.e., being fully focused on the task, distractions by irrelevant sensations/perceptions, interfering thoughts related to the appraisal of the task, and mind-wandering) that varied along two dimensions (“task-relatedness” and “stimulus-dependency”) were sampled using thought-probes while the participants performed a go/no-go task. Analyses performed on the intervals preceding each probe according to the reported subjective experience revealed that both dimensions are relevant to explain activity in several regions of the DMN, namely the medial prefrontal cortex, posterior cingulate cortex/precuneus, and posterior inferior parietal lobe. Notably, an additive effect of the two dimensions was demonstrated for midline DMN regions. On the other hand, lateral temporal regions (also part of the DMN) were specifically related to stimulus-independent reports. These results suggest that midline DMN regions underlie cognitive processes that are active during both internal thoughts and external unfocused attention. They also strengthen the view that the DMN can be fractionated into different subcomponents and reveal the necessity to consider both the stimulus-dependent and the task-related dimensions of conscious experiences when studying the possible functional roles of the DMN.
The ‘default network’ is defined as a set of areas, encompassing posterior-cingulate/precuneus, anterior cingulate/mesiofrontal cortex and temporo-parietal junctions, that show more activity at rest than during attention-demanding tasks. Recent studies have shown that it is possible to reliably identify this network in the absence of any task, by resting state functional magnetic resonance imaging connectivity analyses in healthy volunteers. However, the functional significance of these spontaneous brain activity fluctuations remains unclear. The aim of this study was to test if the integrity of this resting-state connectivity pattern in the default network would differ in different pathological alterations of consciousness. Fourteen non-communicative brain-damaged patients and 14 healthy controls participated in the study. Connectivity was investigated using probabilistic independent component analysis, and an automated template-matching component selection approach. Connectivity in all default network areas was found to be negatively correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative then coma patients. Furthermore, precuneus connectivity was found to be significantly stronger in minimally conscious patients as compared with unconscious patients. Locked-in syndrome patient’s default network connectivity was not significantly different from controls. Our results show that default network connectivity is decreased in severely brain-damaged patients, in proportion to their degree of consciousness impairment. Future prospective studies in a larger patient population are needed in order to evaluate the prognostic value of the presented methodology.
Default mode; fMRI; coma; vegetative state; minimally conscious state
From a behavioral as well as neurobiological point of view, sleep and consciousness are intimately connected. A better understanding of sleep cycles and sleep architecture of patients suffering from disorders of consciousness (DOC) might therefore improve the clinical care for these patients as well as our understanding of the neural correlations of consciousness. Defining sleep in severely brain-injured patients is however problematic as both their electrophysiological and sleep patterns differ in many ways from healthy individuals. This paper discusses the concepts involved in the study of sleep of patients suffering from DOC and critically assesses the applicability of standard sleep criteria in these patients. The available literature on comatose and vegetative states as well as that on locked-in and related states following traumatic or non-traumatic severe brain injury will be reviewed. A wide spectrum of sleep disturbances ranging from almost normal patterns to severe loss and architecture disorganization are reported in cases of DOC and some patterns correlate with diagnosis and prognosis. At the present time the interactions of sleep and consciousness in brain-injured patients are a little studied subject but, the authors suggest, a potentially very interesting field of research.
Consciousness; Coma; Vegetative state; Minimally conscious state; Locked-in syndrome; Brain injury; Sleep; Arousal; Polysomnography
The processing of personal changes across time and the ability to differentiate between representations of present and past selves are crucial for developing a mature sense of identity. In this study, we explored the neural correlates of self-reflection across time using functional magnetic resonance imaging (fMRI). College undergraduates were asked to reflect on their own psychological characteristics and those of an intimate other, for both the present time period (i.e. at college) and a past time period (i.e. high school years) that involved significant personal changes. Cortical midline structures (CMS) were commonly recruited by the four reflective tasks (reflecting on the present self, past self, present other and past other), relative to a control condition (making valence judgments). More importantly, however, the degree of activity in CMS also varied significantly according to the target of reflection, with the ventral and dorsal medial prefrontal cortex and the posterior cingulate cortex being more recruited when reflecting on the present self than when reflecting on the past self or when reflecting on the other person. These findings suggest that CMS may contribute to differentiate between representations of present and past selves.
self; fMRI; medial prefrontal cortex; time
Recent 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.
Reaction 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.
Behavioral 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.
Newborn granule neurons are generated from proliferating neural stem/progenitor cells and integrated into mature synaptic networks in the adult dentate gyrus of the hippocampus. Since light/dark variations of the mitotic index and DNA synthesis occur in many tissues, we wanted to unravel the role of the clock-controlled Period2 gene (mPer2) in timing cell cycle kinetics and neurogenesis in the adult DG.
In contrast to the suprachiasmatic nucleus, we observed a non-rhythmic constitutive expression of mPER2 in the dentate gyrus. We provide evidence that mPER2 is expressed in proliferating neural stem/progenitor cells (NPCs) and persists in early post-mitotic and mature newborn neurons from the adult DG. In vitro and in vivo analysis of a mouse line mutant in the mPer2 gene (Per2Brdm1), revealed a higher density of dividing NPCs together with an increased number of immature newborn neurons populating the DG. However, we showed that the lack of mPer2 does not change the total amount of mature adult-generated hippocampal neurons, because of a compensatory increase in neuronal cell death.
Taken together, these data demonstrated a functional link between the constitutive expression of mPER2 and the intrinsic control of neural stem/progenitor cells proliferation, cell death and neurogenesis in the dentate gyrus of adult mice.
It is known that sleep reshapes the neural representations that subtend the memories acquired while navigating in a virtual environment. However, navigation is not process-pure, as manifold learning components contribute to performance, notably the spatial and contextual memory constituents. In this context, it remains unclear whether post-training sleep globally promotes consolidation of all of the memory components embedded in virtual navigation, or rather favors the development of specific representations. Here, we investigated the effect of post-training sleep on the neural substrates of the consolidation of spatial and contextual memories acquired while navigating in a complex 3D, naturalistic virtual town. Using fMRI, we mapped regional cerebral activity during various tasks designed to tap either the spatial or the contextual memory component, or both, 72 h after encoding with or without sleep deprivation during the first post-training night. Behavioral performance was not dependent upon post-training sleep deprivation, neither in a natural setting that engages both spatial and contextual memory processes nor when looking more specifically at each of these memory representations. At the neuronal level however, analyses that focused on contextual memory revealed distinct correlations between performance and neuronal activity in frontal areas associated with recollection processes after post-training sleep, and in the parahippocampal gyrus associated with familiarity processes in sleep-deprived participants. Likewise, efficient spatial memory was associated with posterior cortical activity after sleep whereas it correlated with parahippocampal/medial temporal activity after sleep deprivation. Finally, variations in place-finding efficiency in a natural setting encompassing spatial and contextual elements were associated with caudate activity after post-training sleep, suggesting the automation of navigation. These data indicate that post-training sleep modulates the neural substrates of the consolidation of both the spatial and contextual memories acquired during virtual navigation.
To identify the biochemical changes induced by sleep deprivation at a proteomic level, we compared the hippocampal proteome of rats either after 4 hours of sleep or sleep deprivation obtained by gentle handling. Because sleep deprivation might induce some stress, we also analyzed proteomic changes in rat adrenals in the same conditions. After sleep deprivation, proteins from both tissues were extracted and subjected to 2D-DIGE analysis followed by protein identification through mass spectrometry and database search.
In the hippocampus, 87 spots showed significant variation between sleep and sleep deprivation, with more proteins showing higher abundance in the latter case. Of these, 16 proteins were present in sufficient amount for a sequencing attempt and among the 12 identified proteins, inferred affected cellular functions include cell metabolism, energy pathways, transport and vesicle trafficking, cytoskeleton and protein processing. Although we did not observe classical, macroscopic effect of stress in sleep-deprived rats, 47 protein spots showed significant variation in adrenal tissue between sleep and sleep deprivation, with more proteins showing higher abundance following sleep. Of these, 16 proteins were also present in sufficient amount for a sequencing attempt and among the 13 identified proteins, the most relevant cellular function that was affected was cell metabolism.
At a proteomic level, short term sleep deprivation is characterized by a higher expression of some proteins in the hippocampus and a lower abundance of other proteins in the adrenals (compared to normal sleep control). Altogether, this could indicate a general activation of a number of cellular mechanisms involved in the maintenance of wakefulness and in increased energy expenditure during sleep deprivation. These findings are relevant to suggested functions of sleep like energy repletion and the restoration of molecular stocks or a more global homeostasis of synaptic processes.
Relatively long duration retinal light exposure elicits nonvisual responses in humans, including modulation of alertness and cognition. These responses are thought to be mediated in part by melanopsin-expressing retinal ganglion cells which are more sensitive to blue light than violet or green light. The contribution of the melanopsin system and the brain mechanisms involved in the establishment of such responses to light remain to be established.
We exposed 15 participants to short duration (50 s) monochromatic violet (430 nm), blue (473 nm), and green (527 nm) light exposures of equal photon flux (1013ph/cm2/s) while they were performing a working memory task in fMRI. At light onset, blue light, as compared to green light, increased activity in the left hippocampus, left thalamus, and right amygdala. During the task, blue light, as compared to violet light, increased activity in the left middle frontal gyrus, left thalamus and a bilateral area of the brainstem consistent with activation of the locus coeruleus.
These results support a prominent contribution of melanopsin-expressing retinal ganglion cells to brain responses to light within the very first seconds of an exposure. The results also demonstrate the implication of the brainstem in mediating these responses in humans and speak for a broad involvement of light in the regulation of brain function.
Emotional events are usually better remembered than neutral ones. This effect is mediated in part by a modulation of the hippocampus by the amygdala. Sleep plays a role in the consolidation of declarative memory. We examined the impact of sleep and lack of sleep on the consolidation of emotional (negative and positive) memories at the macroscopic systems level. Using functional MRI (fMRI), we compared the neural correlates of successful recollection by humans of emotional and neutral stimuli, 72 h after encoding, with or without total sleep deprivation during the first post-encoding night. In contrast to recollection of neutral and positive stimuli, which was deteriorated by sleep deprivation, similar recollection levels were achieved for negative stimuli in both groups. Successful recollection of emotional stimuli elicited larger responses in the hippocampus and various cortical areas, including the medial prefrontal cortex, in the sleep group than in the sleep deprived group. This effect was consistent across subjects for negative items but depended linearly on individual memory performance for positive items. In addition, the hippocampus and medial prefrontal cortex were functionally more connected during recollection of either negative or positive than neutral items, and more so in sleeping than in sleep-deprived subjects. In the sleep-deprived group, recollection of negative items elicited larger responses in the amygdala and an occipital area than in the sleep group. In contrast, no such difference in brain responses between groups was associated with recollection of positive stimuli. The results suggest that the emotional significance of memories influences their sleep-dependent systems-level consolidation. The recruitment of hippocampo-neocortical networks during recollection is enhanced after sleep and is hindered by sleep deprivation. After sleep deprivation, recollection of negative, potentially dangerous, memories recruits an alternate amygdalo-cortical network, which would keep track of emotional information despite sleep deprivation.
Declarative memories, which can be consciously and verbally retrieved, are initially critically dependent on the hippocampus. However, reliable retrieval of long-term memory depends on a process of consolidation, which partly occurs during sleep, when memories are thought to be progressively transferred to long-term cortical stores. Because people tend to remember emotional memories better than neutral ones, we wondered whether the emotional significance of a memory would enhance its consolidation in a sleep-dependent manner. During a first session, participants viewed pictures with neutral and emotional content without realizing that their memory of the pictures and their content would be tested later (called incidental encoding). Three days later, during a functional MRI scanning session, subjects indicated whether they recognized previously viewed and new pictures. Half of the subjects were totally sleep deprived during the first post-encoding night, but all subjects slept as usual during the second and third post-encoding nights. We show here that the recollection of emotional stimuli elicited larger responses in the hippocampus and various cortical areas in the well-rested group than in the sleep-deprived group, suggesting that emotional significance boosts memory consolidation of the information during sleep. Interestingly, in sleep-deprived subjects, recollection of negative items recruited another network including the amygdala, as if an alternate consolidation process allowed them to keep track of negative, potentially dangerous, information despite the cognitive aftermath of sleep deprivation.
A new fMRI study reveals that emotional memories are consolidated by different brain networks in humans who receive a normal amount of sleep, compared with those who are sleep deprived.
Measurement of locomotor activity is a valuable tool for analysing factors influencing behaviour and for investigating brain function. Several methods have been described in the literature for measuring the amount of animal movement but most are flawed or expensive. Here, we describe an open source, modular, low-cost, user-friendly, highly sensitive, non-invasive system that records all the movements of a rat in its cage.
Our activity monitoring system quantifies overall free movements of rodents without any markers, using a commercially available CCTV and a newly designed motion detection software developed on a GNU/Linux-operating computer. The operating principle is that the amount of overall movement of an object can be expressed by the difference in total area occupied by the object in two consecutive picture frames. The application is based on software modules that allow the system to be used in a high-throughput workflow. Documentation, example files, source code and binary files can be freely downloaded from the project website at .
In a series of experiments with objects of pre-defined oscillation frequencies and movements, we documented the sensitivity, reproducibility and stability of our system. We also compared data obtained with our system and data obtained with an Actiwatch device. Finally, to validate the system, results obtained from the automated observation of 6 rats during 7 days in a regular light cycle are presented and are accompanied by a stability test. The validity of this system is further demonstrated through the observation of 2 rats in constant dark conditions that displayed the expected free running of their circadian rhythm.
The present study describes a system that relies on video frame differences to automatically quantify overall free movements of a rodent without any markers. It allows the monitoring of rats in their own environment for an extended period of time. By using a low-cost, open source hardware/software solution, laboratories can greatly simplify their data acquisition and analysis pipelines and improve their workload.
Predicting the chances of recovery of consciousness and communication in patients who survive their coma but transit in a vegetative state or minimally conscious state (MCS) remains a major challenge for their medical caregivers. Very few studies have examined the slow neuronal changes underlying functional recovery of consciousness from severe chronic brain damage. A case study in this issue of the JCI reports an extraordinary recovery of functional verbal communication and motor function in a patient who remained in MCS for 19 years (see the related article beginning on page 2005). Diffusion tensor MRI showed increased fractional anisotropy (assumed to reflect myelinated fiber density) in posteromedial cortices, encompassing cuneus and precuneus. These same areas showed increased glucose metabolism as studied by PET scanning, likely reflecting the neuronal regrowth paralleling the patient’s clinical recovery. This case shows that old dogmas need to be oppugned, as recovery with meaningful reduction in disability continued in this case for nearly 2 decades after extremely severe traumatic brain injury.
Much remains to be discovered about the fate of recent memories in the human brain. Several studies have reported the reactivation of learning-related cerebral activity during post-training sleep, suggesting that sleep plays a role in the offline processing and consolidation of memory. However, little is known about how new information is maintained and processed during post-training wakefulness before sleep, while the brain is actively engaged in other cognitive activities. We show, using functional magnetic resonance imaging, that brain activity elicited during a new learning episode modulates brain responses to an unrelated cognitive task, during the waking period following the end of training. This post-training activity evolves in learning-related cerebral structures, in which functional connections with other brain regions are gradually established or reinforced. It also correlates with behavioral performance. These processes follow a different time course for hippocampus-dependent and hippocampus-independent memories. Our experimental approach allowed the characterization of the offline evolution of the cerebral correlates of recent memories, without the confounding effect of concurrent practice of the learned material. Results indicate that the human brain has already extensively processed recent memories during the first hours of post-training wakefulness, even when simultaneously coping with unrelated cognitive demands.
A human fMRI study showing how learning selectively modulates brain activity during wakefulness, providing novel evidence that "offline" activation patterns differ according to the preceding memory task and memory performance.