Insulation for daydreams: a role for tonic norepinephrine in the facilitation of internally guided thought

Although consciousness can be brought to bear on both perceptual and internally generated information, little is known about how these different cognitive modes are coordinated. Here we show that between-participant variance in thoughts unrelated to the task being performed (known as task unrelated thought, TUT) is associated with longer response times (RT) when target presentation occurs during periods when baseline Pupil Diameter (PD) is increased. As behavioral interference due to high baseline PD can reflect increased tonic activity in the norepinephrine system (NE), these results might implicate high tonic NE activity in the facilitation of TUTs. Based on these findings, it is hypothesised that high tonic mode NE leads to a generalised de-amplification of task relevant information that prioritses internally generated thought and insulates it from the potentially disruptive events taking place in the external environment.     

The hippocampus is coupled with the default network during memory retrieval but not during memory encoding

The brain's default mode network (DMN) is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding.     

Spontaneous eyeblinks are correlated with responses during the Stroop task

The timing and frequency of spontaneous eyeblinking is thought to be influenced by ongoing internal cognitive or neurophysiological processes, but how precisely these processes influence the dynamics of eyeblinking is still unclear. This study aimed to better understand the functional role of eyeblinking during cognitive processes by investigating the temporal pattern of eyeblinks during the performance of attentional tasks. The timing of spontaneous eyeblinks was recorded from 28 healthy subjects during the performance of both visual and auditory versions of the Stroop task, and the temporal distributions of eyeblinks were estimated in relation to the timing of stimulus presentation and vocal response during the tasks. We found that the spontaneous eyeblink rate increased during Stroop task performance compared with the resting rate. Importantly, the subjects (17/28 during the visual Stroop, 20/28 during the auditory Stroop) were more likely to blink before a vocal response in both tasks (150-250 msec) and the remaining subjects were more likely to blink soon after the vocal response (200-300 msec), regardless of the stimulus type (congruent or incongruent) or task difficulty. These findings show that spontaneous eyeblinks are closely associated with responses during the performance of the Stroop task on a short time scale and suggest that spontaneous eyeblinks likely signal a shift in the internal cognitive or attentional state of the subjects.     

Thalamocortical dynamics of sleep: roles of purinergic neuromodulation

Thalamocortical dynamics, the millisecond to second changes in activity of thalamocortical circuits, are central to perception, action and cognition. Generated by local circuitry and sculpted by neuromodulatory systems, these dynamics reflect the expression of vigilance states. In sleep, thalamocortical dynamics are thought to mediate "offline" functions including memory consolidation and synaptic scaling. Here, I discuss thalamocortical sleep dynamics and their modulation by the ascending arousal system and locally released neurochemicals. I focus on modulation of these dynamics by electrically silent astrocytes, highlighting the role of purinergic signaling in this glial form of communication. Astrocytes modulate cortical slow oscillations, sleep behavior, and sleep-dependent cognitive function. The discovery that astrocytes can modulate sleep dynamics and sleep-related behaviors suggests a new way of thinking about the brain, in which integrated circuits of neurons and glia control information processing and behavioral output.     

Sleep Promotes the Extraction of Grammatical Rules

Grammar acquisition is a high level cognitive function that requires the extraction of complex rules. While it has been proposed that offline time might benefit this type of rule extraction, this remains to be tested. Here, we addressed this question using an artificial grammar learning paradigm. During a short-term memory cover task, eighty-one human participants were exposed to letter sequences generated according to an unknown artificial grammar. Following a time delay of 15 min, 12 h (wake or sleep) or 24 h, participants classified novel test sequences as Grammatical or Non-Grammatical. Previous behavioral and functional neuroimaging work has shown that classification can be guided by two distinct underlying processes: (1) the holistic abstraction of the underlying grammar rules and (2) the detection of sequence chunks that appear at varying frequencies during exposure. Here, we show that classification performance improved after sleep. Moreover, this improvement was due to an enhancement of rule abstraction, while the effect of chunk frequency was unaltered by sleep. These findings suggest that sleep plays a critical role in extracting complex structure from separate but related items during integrative memory processing. Our findings stress the importance of alternating periods of learning with sleep in settings in which complex information must be acquired.     

Unexpected Dual Task Benefits on Cycling in Parkinson Disease and Healthy Adults: A Neuro-Behavioral Model

BackgroundWhen performing two tasks at once, a dual task, performance on one or both tasks typically suffers. People with Parkinson’s disease (PD) usually experience larger dual task decrements on motor tasks than healthy older adults (HOA). Our objective was to investigate the decrements in cycling caused by performing cognitive tasks with a range of difficulty in people with PD and HOAs.MethodsTwenty-eight participants with Parkinson’s disease and 20 healthy older adults completed a baseline cycling task with no secondary tasks and then completed dual task cycling while performing 12 tasks from six cognitive domains representing a wide range of difficulty.ResultsCycling was faster during dual task conditions than at baseline, and was significantly faster for six tasks (all p<.02) across both groups. Cycling speed improved the most during the easiest cognitive tasks, and cognitive performance was largely unaffected. Cycling improvement was predicted by task difficulty (p<.001). People with Parkinson’s disease cycled slower (p<.03) and showed reduced dual task benefits (p<.01) than healthy older adults.ConclusionsUnexpectedly, participants’ motor performance improved during cognitive dual tasks, which cannot be explained in current models of dual task performance. To account for these findings, we propose a model integrating dual task and acute exercise approaches which posits that cognitive arousal during dual tasks increases resources to facilitate motor and cognitive performance, which is subsequently modulated by motor and cognitive task difficulty. This model can explain both the improvement observed on dual tasks in the current study and more typical dual task findings in other studies.     

Representing Representation: Integration between the Temporal Lobe and the Posterior Cingulate Influences the Content and Form of Spontaneous Thought

When not engaged in the moment, we often spontaneously represent people, places and events that are not present in the environment. Although this capacity has been linked to the default mode network (DMN), it remains unclear how interactions between the nodes of this network give rise to particular mental experiences during spontaneous thought. One hypothesis is that the core of the DMN integrates information from medial and lateral temporal lobe memory systems, which represent different aspects of knowledge. Individual differences in the connectivity between temporal lobe regions and the default mode network core would then predict differences in the content and form of people’s spontaneous thoughts. This study tested this hypothesis by examining the relationship between seed-based functional connectivity and the contents of spontaneous thought recorded in a laboratory study several days later. Variations in connectivity from both medial and lateral temporal lobe regions was associated with different patterns of spontaneous thought and these effects converged on an overlapping region in the posterior cingulate cortex. We propose that the posterior core of the DMN acts as a representational hub that integrates information represented in medial and lateral temporal lobe and this process is important in determining the content and form of spontaneous thought.     

Offline persistence of memory-related cerebral activity during active wakefulness

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.     

Involuntary autobiographical memories and their relation to other forms of spontaneous thoughts

Involuntary autobiographical memories are memories of personal events that come to mind spontaneously—that is, with no conscious initiation of the retrieval process. Such spontaneously arising memories were long ignored in cognitive psychology, which generally has focused on controlled and strategic forms of remembering, studied in laboratory settings. Recent evidence shows that involuntary memories of past events are highly frequent in daily life, and that they represent a context-sensitive, and associative way of recollecting past events that involves little executive control. They operate by constraints that favour recent events and events with a distinct feature overlap to the current situation, which optimizes the probability of functional relevance to the ongoing situation. In addition to adults, they are documented in young children and great apes and may be an ontogenetic and evolutionary forerunner of strategic retrieval of past events. Findings suggest that intrusive involuntary memories observed clinically after traumatic events should be viewed as a dysfunctional subclass of otherwise functional involuntary autobiographical memories. Because of their highly constrained, situation-dependent and automatic nature, involuntary autobiographical memories form a distinct category of spontaneous thought that cannot be equated with mind wandering.This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.     

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model’s prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.     

Neural correlates of ongoing conscious experience: both task-unrelatedness and stimulus-independence are related to default network activity

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.     

Dual-task and anticipation impact lower limb biomechanics during a single-leg cut with body borne load

This study quantified how a dual cognitive task impacts lower limb biomechanics during anticipated and unanticipated single-leg cuts with body borne load. Twenty-four males performed anticipated and unanticipated cuts with and without a dual cognitive task with three load conditions: no load (∼6 kg), medium load (15% of BW), and heavy load (30% of BW). Lower limb biomechanics were submitted to a repeated measures linear mixed model to test the main and interaction effects of load, anticipation, and dual task. With body borne load, participants increased peak stance (PS) hip flexion (p = .004) and hip internal rotation (p = .001) angle, and PS hip flexion (p = .001) and internal rotation (p = .018), and knee flexion (p = .016) and abduction (p = .001) moments. With the dual task, participants decreased PS knee flexion angle (p < .001) and hip flexion moment (p = .027), and increased PS knee external rotation angle (p = .034). During the unanticipated cut, participants increased PS hip (p = .040) and knee flexion angle (p < .001), and decreased PS hip adduction (p = .001), and knee abduction (p = .005) and external rotation (p = .026) moments. Adding body borne load produces lower limb biomechanical adaptations thought to increase risk of musculoskeletal injury, but neither anticipation nor dual task exaggerated those biomechanical adaptations. With a dual task, participants adopted biomechanics known to increase injury risk; whereas, participants used lower limb biomechanics thought to decrease injury risk during unanticipated cuts.     

Distinct neural activity associated with focused-attention meditation and loving-kindness meditation

This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing.     

Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation

Despite many prior studies demonstrating offline behavioral gains in motor skills after sleep, the underlying neural mechanisms remain poorly understood. To investigate the neurophysiological basis for offline gains, we performed single-unit recordings in motor cortex as rats learned a skilled upper-limb task. We found that sleep improved movement speed with preservation of accuracy. These offline improvements were linked to both replay of task-related ensembles during non-rapid eye movement (NREM) sleep and temporal shifts that more tightly bound motor cortical ensembles to movements; such offline gains and temporal shifts were not evident with sleep restriction. Interestingly, replay was linked to the coincidence of slow-wave events and bursts of spindle activity. Neurons that experienced the most consistent replay also underwent the most significant temporal shift and binding to the motor task. Significantly, replay and the associated performance gains after sleep only occurred when animals first learned the skill; continued practice during later stages of learning (i.e., after motor kinematics had stabilized) did not show evidence of replay. Our results highlight how replay of synchronous neural activity during sleep mediates large-scale neural plasticity and stabilizes kinematics during early motor learning.     

Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks

Cortical neural networks exhibit high internal variability in spontaneous dynamic activities and they can robustly and reliably respond to external stimuli with multilevel features–from microscopic irregular spiking of neurons to macroscopic oscillatory local field potential. A comprehensive study integrating these multilevel features in spontaneous and stimulus–evoked dynamics with seemingly distinct mechanisms is still lacking. Here, we study the stimulus–response dynamics of biologically plausible excitation–inhibition (E–I) balanced networks. We confirm that networks around critical synchronous transition states can maintain strong internal variability but are sensitive to external stimuli. In this dynamical region, applying a stimulus to the network can reduce the trial-to-trial variability and shift the network oscillatory frequency while preserving the dynamical criticality. These multilevel features widely observed in different experiments cannot simultaneously occur in non-critical dynamical states. Furthermore, the dynamical mechanisms underlying these multilevel features are revealed using a semi-analytical mean-field theory that derives the macroscopic network field equations from the microscopic neuronal networks, enabling the analysis by nonlinear dynamics theory and linear noise approximation. The generic dynamical principle revealed here contributes to a more integrative understanding of neural systems and brain functions and incorporates multimodal and multilevel experimental observations. The E–I balanced neural network in combination with the effective mean-field theory can serve as a mechanistic modeling framework to study the multilevel neural dynamics underlying neural information and cognitive processes.     

Thalamic bursts modulate cortical synchrony locally to switch between states of global functional connectivity in a cognitive task

Performing a cognitive task requires going through a sequence of functionally diverse stages. Although it is typically assumed that these stages are characterized by distinct states of cortical synchrony that are triggered by sub-cortical events, little reported evidence supports this hypothesis. To test this hypothesis, we first identified cognitive stages in single-trial MEG data of an associative recognition task, showing with a novel method that each stage begins with local modulations of synchrony followed by a state of directed functional connectivity. Second, we developed the first whole-brain model that can simulate cortical synchrony throughout a task. The model suggests that the observed synchrony is caused by thalamocortical bursts at the onset of each stage, targeted at cortical synapses and interacting with the structural anatomical connectivity. These findings confirm that cognitive stages are defined by distinct states of cortical synchrony and explains the network-level mechanisms necessary for reaching stage-dependent synchrony states.     

Differential Neural Activation Patterns in Patients with Parkinson's Disease and Freezing of Gait in Response to Concurrent Cognitive and Motor Load

Freezing of gait is a devastating symptom of Parkinson''s disease (PD) that is exacerbated by the processing of cognitive information whilst walking. To date, no studies have explored the neural correlates associated with increases in cognitive load whilst performing a motor task in patients with freezing. In this experiment, 14 PD patients with and 15 PD patients without freezing of gait underwent 3T fMRI while performing a virtual reality gait task. Directions to walk and stop were presented on the viewing screen as either direct cues or as more cognitively indirect pre-learned cues. Both groups showed a consistent pattern of BOLD response within the Cognitive Control Network during performance of the paradigm. However, a between group comparison revealed that those PD patients with freezing of gait were less able to recruit the bilateral anterior insula, ventral striatum and the pre-supplementary motor area, as well as the left subthalamic nucleus when responding to indirect cognitive cues whilst maintaining a motor output. These results suggest that PD patients with freezing of gait are unable to properly recruit specific cortical and subcortical regions within the Cognitive Control Network during the performance of simultaneous motor and cognitive functions.     

Cognitive Dysfunction Precedes the Onset of Motor Symptoms in the MitoPark Mouse Model of Parkinson’s Disease

Parkinson’s disease (PD) is a neurodegenerative disorder primarily characterized by progressive loss of dopamine neurons, leading to loss of motor coordination. However, PD is associated with a high rate of non-motor neuropsychiatric comorbities that often develop before the onset of movement symptoms. The MitoPark transgenic mouse model is the first to recapitulate the cardinal clinical features, namely progressive neurodegeneration and death of neurons, loss of motor function and therapeutic response to L-DOPA. To investigate whether MitoPark mice exhibit early onset of cognitive impairment, a non-motor neuropsychiatric comorbidity, we measured performance on a spatial learning and memory task before (∼8 weeks) or after (∼20 weeks) the onset of locomotor decline in MitoPark mice or in littermate controls. Consistent with previous studies, we established that a progressive loss of spontaneous locomotor activity began at 12 weeks of age, which was followed by progressive loss of body weight beginning at 16–20 weeks. Spatial learning and memory was measured using the Barnes Maze. By 20 weeks of age, MitoPark mice displayed a substantial reduction in overall locomotor activity that impaired their ability to perform the task. However, in the 8-week-old mice, locomotor activity was no different between genotypes, yet MitoPark mice took longer, traveled further and committed more errors than same age control mice, while learning to successfully navigate the maze. The modest between-day learning deficit of MitoPark mice was characterized by impaired within-day learning during the first two days of testing. No difference was observed between genotypes during probe trials conducted one or twelve days after the final acquisition test. Additionally, 8-week-old MitoPark mice exhibited impaired novel object recognition when compared to control mice. Together, these data establish that mild cognitive impairment precedes the loss of motor function in a novel rodent model of PD, which may provide unique opportunities for therapeutic development.     

The Default Mode Network and the Working Memory Network Are Not Anti-Correlated during All Phases of a Working Memory Task

Introduction

The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time.

Methods

To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks.

Results

We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks.

Conclusions

Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.     

A model of the effects of cognitive load on the subjective estimation and production of time intervals

How and where the brain calculates elapsing time is not known, and one or more internal pacemakers or others timekeeping systems have been suggested. Experiments have shown that the accuracy in estimating or producing time intervals depends on many factors and, in particular, both on the length of the intervals to be estimated and on the additional, and unrelated, cognitive load required during the task. The psychological 'attentional approach' is able to explain the experimental data in terms of perturbations of a cognitive timer. However, the basic biophysical mechanisms that could be involved at the single neuron level are still not clear. Here we propose a computational model suggesting how the process to focus the attention on a non-temporal task could alter the perception of time intervals as observed in the experiments. The model suggests that an attention-based excitatory and/or inhibitory background synaptic noise, impinging on the pacemaker circuit, could represent both qualitative and quantitative features of the cognitive load. These effects are predicted to be independent of the number, location or specific implementations of the internal timing systems.