Cognit activation: a mechanism enabling temporal integration in working memory

Inter-individual variability (but intra-individual stability) of overt versus covert rehearsal strategies in a digital Corsi task

The Corsi (block-tapping) paradigm is a classic and well-established visuospatial working memory task in humans involving internal computations (memorizing of item sequences, organizing and updating the memorandum, and recall processes), as well as both overt and covert shifts of attention to facilitate rehearsal, serving to maintain the Corsi sequences during the retention phase. Here, we introduce a novel digital version of a Corsi task in which i) the difficulty of the memorandum (using sequence lengths ranging from 3 to 8) was controlled, ii) the execution of overt and/or covert attention as well as the visuospatial working memory load during the retention phase was manipulated, and iii) shifts of attention were quantified in all experimental phases. With this, we present behavioral data that demonstrate, characterize, and classify the individual effects of overt and covert strategies used as a means of encoding and rehearsal. In a full within-subject design, we tested 28 participants who had to solve three different Corsi conditions. While in condition A neither of the two strategies were restricted, in condition B the overt and in condition C the overt as well as the covert strategies were suppressed. Analyzing Corsi span, (eye) exploration index, and pupil size (change), data clearly show a continuum between overt and covert strategies over all participants (indicating inter-individual variability). Further, all participants showed stable strategy choice (indicating intra-individual stability), meaning that the preferred strategy was maintained in all three conditions, phases, and sequence lengths of the experiment.

Impact of theta transcranial alternating current stimulation on language production in adult classic galactosemia patients

Patients with classic galactosemia (CG), an inborn error of galactose metabolism, suffer from impairments in cognition, including language processing. Potential causes are atypical brain oscillations. Recent electroencephalogram (EEG) showed differences in the P300 event-related-potential (ERP) and alterations in the alpha/theta-range during speech planning. This study investigated whether transcranial alternating current stimulation (tACS) at theta-frequency compared to sham can cause a normalization of the ERP post stimulation and improves language performance. Eleven CG patients and fourteen healthy controls participated in two tACS-sessions (theta 6.5 Hz/sham). They were engaged in an active language task, describing animated scenes at three moments, that is, pre/during/post stimulation. Pre and post stimulation, behavior (naming accuracy, voice-onset-times; VOT) and mean-amplitudes of ERP were compared, by means of a P300 time-window analysis and cluster-based-permutation testing during speech planning. The results showed that theta stimulation, not sham, significantly reduced naming error-percentage in patients, not in controls. Theta did not systematically speed up naming beyond a general learning effect, which was larger for the patients. The EEG analysis revealed a significant pre-post stimulation effect (P300/late positivity), in patients and during theta stimulation only. In conclusion, theta-tACS improved accuracy in language performance in CG patients compared to controls and altered the P300 and late positive ERP-amplitude, suggesting a lasting effect on neural oscillation and behavior.

Episodic memory assessment: effects of sex and age on performance and response time during a continuous recognition task

Introduction

Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer's disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and FA. Prior analyses of MemTrax CRT data show no effects of sex but an effect of age on performance. The number of HITs corresponds to faster RT-HITs more closely than TC, and CRs do not relate to RT-HITs. RT-HITs show a typical skewed distribution, and cumulative RT-HITs fit a negative survival curve (RevEx). Thus, this study aimed to define precisely the effects of sex and age on HITS, CRs, RT-HITs, and the dynamics of RTs in an engaged population.

Methods

MemTrax CRT online data on 18,255 individuals was analyzed for sex, age, and distributions of HITs, CRs, MISSes, FAs, TC, and relationships to both RT-HITs and RT-FAs.

Results

HITs corresponded more closely to RT-HITs than did TC because CRs did not relate to RT-HITs. RT-FAs had a broader distribution than RT-HITs and were faster than RT-HITs in about half of the sample, slower in the other half. Performance metrics for men and women were the same. HITs declined with age as RT-HITs increased. CRs also decreased with age and RT-FAs increased, but with no correlation. The group over aged 50 years had RT-HITs distributions slower than under 50 years. For both age ranges, the RevEx model explained more than 99% of the variance in RT-HITs.

Discussion

The dichotomy of HITs and CRs suggests opposing cognitive strategies: (1) less certainty about recognitions, in association with slower RT-HITs and lower HIT percentages suggests recognition difficulty, leading to more MISSes, and (2) decreased CRs (more FAs) but faster RTs to HITs and FAs, suggesting overly quick decisions leading to errors. MemTrax CRT performance provides an indication of EM (HITs and RT-HITs may relate to function of the temporal lobe), executive function (FAs may relate to function of the frontal lobe), processing speed (RTs), cognitive ability, and age-related changes. This CRT provides potential clinical screening utility for early Alzheimer's disease and other conditions affecting EM, other cognitive functions, and more accurate impairment assessment to track changes over time.

Prospection of Potential Actions during Visual Working Memory Starts Early, Is Flexible, and Predicts Behavior

For visual working memory to serve upcoming behavior, it is crucial that we prepare for the potential use of working-memory contents ahead of time. Recent studies have demonstrated how the prospection and planning for an upcoming manual action starts early after visual encoding, and occurs alongside visual retention. Here, we address whether such "output planning" in visual working memory flexibly adapts to different visual-motor mappings, and occurs even when an upcoming action will only potentially become relevant for behavior. Human participants (female and male) performed a visual-motor working memory task in which they remembered one or two colored oriented bars for later (potential) use. We linked, and counterbalanced, the tilt of the visual items to specific manual responses. This allowed us to track planning of upcoming behavior through contralateral attenuation of β band activity, a canonical motor-cortical EEG signature of manual-action planning. The results revealed how action encoding and subsequent planning alongside visual working memory (1) reflect anticipated task demands rather than specific visual-motor mappings, (2) occur even for actions that will only potentially become relevant for behavior, and (3) are associated with faster performance for the encoded item, at the expense of performance to other working-memory content. This reveals how the potential prospective use of visual working memory content is flexibly planned early on, with consequences for the speed of memory-guided behavior.SIGNIFICANCE STATEMENT It is increasingly studied how visual working memory helps us to prepare for the future, in addition to how it helps us to hold onto the past. Recent studies have demonstrated that the planning of prospective actions occurs alongside encoding and retention in working memory. We show that such early "output planning" flexibly adapts to varying visual-motor mappings, occurs both for certain and potential actions, and predicts ensuing working-memory guided behavior. These results highlight the flexible and future-oriented nature of visual working memory, and provide insight into the neural basis of the anticipatory dynamics that translate visual representations into adaptive upcoming behavior.

Thoughts from the forest floor: a review of cognition in the slime mould Physarum polycephalum

Sensing, communication, navigation, decision-making, memory and learning are key components in a standard cognitive tool-kit that enhance an animal's ability to successfully survive and reproduce. However, these tools are not only useful for, or accessible to, animals-they evolved long ago in simpler organisms using mechanisms which may be either unique or widely conserved across diverse taxa. In this article, I review the recent research that demonstrates these key cognitive abilities in the plasmodial slime mould Physarum polycephalum, which has emerged as a model for non-animal cognition. I discuss the benefits and limitations of comparisons drawn between neural and non-neural systems, and the implications of common mechanisms across wide taxonomic divisions. I conclude by discussing future avenues of research that will draw the most benefit from a closer integration of Physarum and animal cognition research.

Differential working memory function between phonological and visuospatial strategies: a magnetoencephalography study using a same visual task

Previous studies have reported that, in working memory, the processing of visuospatial information and phonological information have different neural bases. However, in these studies, memory items were presented via different modalities. Therefore, the modality in which the memory items were presented and the strategy for memorizing them were not rigorously distinguished. In the present study, we explored the neural basis of two working memory strategies. Nineteen right-handed young adults memorized seven sequential directions presented visually in a task in which the memory strategy was either visuospatial or phonological (visuospatial/phonological condition). Source amplitudes of theta-band (5-7 Hz) rhythm were estimated from magnetoencephalography during the maintenance period and further analyzed using cluster-based permutation tests. Behavioral results revealed that the accuracy rates showed no significant differences between conditions, while the reaction time in the phonological condition was significantly longer than that in the visuospatial condition. Theta activity in the phonological condition was significantly greater than that in the visuospatial condition, and the cluster in spatio-temporal matrix with p < 5% difference extended to right prefrontal regions in the early maintenance period and right occipito-parietal regions in the late maintenance period. The theta activity results did not indicate strategy-specific neural bases but did reveal the dynamics of executive function required for phonological processing. The functions seemed to move from attention control and inhibition control in the prefrontal region to inhibition of irrelevant information in the occipito-parietal region.

Nonconscious information can be identified as task-relevant but not prioritized in working memory

Two critical features of working memory are the identification and appropriate use of task-relevant information while avoiding distraction. Here, in 3 experiments, we explored if these features can be achieved also for nonconscious stimuli. Participants performed a delayed match-to-sample task in which task relevance of 2 competing stimuli was indicated by a cue, and continuous flash suppression was used to manipulate the conscious/nonconscious visual experience. Experiment 1 revealed better-than-chance performance with nonconscious stimuli, demonstrating goal-directed use of nonconscious task-relevant information. Experiment 2 demonstrated that the cue that defined task relevance must be conscious to allow such goal-directed use. In Experiment 3, multi-voxel pattern analyses of brain activity revealed that only the target was prioritized and maintained during conscious trials. Conversely, during nonconscious trials, both target and distractor were maintained. However, decoding of task relevance during the probe/test phase demonstrated identification of both target and distractor information. These results show that identification of task-relevant information can operate also on nonconscious material. However, they do not support the prioritization of nonconscious task-relevant information, thus suggesting a mismatch in the attentional mechanisms involved during conscious and nonconscious working memory.

Turning Attention Inside Out: How Working Memory Serves Behavior

Flexible behavior requires guidance not only by sensations that are available immediately but also by relevant mental contents carried forward through working memory. Therefore, selective-attention functions that modulate the contents of working memory to guide behavior (inside-out) are just as important as those operating on sensory signals to generate internal contents (outside-in). We review the burgeoning literature on selective attention in the inside-out direction and underscore its functional, flexible, and future-focused nature. We discuss in turn the purpose (why), targets (what), sources (when), and mechanisms (how) of selective attention inside working memory, using visual working memory as a model. We show how the study of internal selective attention brings new insights concerning the core cognitive processes of attention and working memory and how considering selective attention and working memory together paves the way for a rich and integrated understanding of how mind serves behavior.

Temporal expectation based on the duration variability modulates alpha oscillations during working memory retention

While maintaining information over a delay of time, working memory (WM) also allows individuals to prepare the mnemonic contents for prospective utilisation. However, it remains unclear whether the expectation of the time of WM test could modulate neural responses during the retention interval of WM and subsequent performance. Here, we investigated whether temporal expectations based on the variability of delay duration can modulate 9-13 Hz alpha oscillations during WM retention and whether the expectation-induced alpha activity was associated with WM performance. Participants performed a retro-cueing WM task with magnetoencephalography (MEG) (Experiment 1) and a standard WM task with electroencephalography (EEG) (Experiment 2). The expectation of the timing of the WM test was manipulated by the temporal structure of the tasks with small or large variability in the delay durations. We showed that alpha oscillations during retention interval and WM performance varied with duration variability in both of the MEG and EEG experiments. The novel finding was greater alpha-power attenuation over the left frontal and parietal regions during WM retention when the duration variability was small and the test onset was predictable, compared to when the duration variability was large and the test onset was less predictable. Importantly, we observed a positive relationship in variability difference between the response benefit and alpha-power attenuation in the left posterior parietal regions at both MEG-source and EEG-electrode levels. Finally, we confirmed the behavioural benefit when a condition with a fixed delay-duration was included in a behavioural experiment (Experiment 3). When conjoined, the delay duration enables individuals to anticipate when the relevant information would be put to work, and alpha oscillations track the anticipatory states during WM maintenance.

Implicit spatial sequential learning facilitates attentional selection in covert visual search. An event-related potentials study

Introduction

While most studies on implicit sequential learning focus on object learning, the hidden structure of target location and onset time can also be a subject of implicitly gathered knowledge. In our study, we wanted to investigate the effect of implicitly learned spatial and temporal sequential predictability on performance in a localization task in a paradigm in which covert selective attention is engaged. We were also interested in the neural mechanism of the facilitating effect of the predictable spatio-temporal context on visual search processes. Specifically, with the use of an event-related potential technique, we wanted to verify whether perceptual, attentional, and motor processes can be enhanced by the predictive spatio-temporal context of visual stimuli.

Methods

We analyzed data from 15 young, healthy adults who took part in an experimental electroencephalographic (EEG) study and performed a visual search localization task. Predictable sequences of four target locations and/or target onset times were presented in separate blocks of trials that formed the Space, Space- Time, and Time conditions. One block of trials with randomly presented stimuli served as a control condition.

Results

The behavioral results revealed that participants successfully learned only the spatial dimension of target predictability. Although spatial predictability was a response-relevant dimension, we found that attentional selection–instead of motor preparation–was the facilitation mechanism in this type of visual search task. This was manifested by a shorter latency and more negative amplitude of the N2pc component and the lack of an effect on the sLRP component. We observed no effect of predictability on perceptual processing (P1 component).

Discussion

We discuss these results with reference to the current knowledge on sequential learning. Our findings also contribute to the current debate on the predictive coding theory.

Biological constraints on neural network models of cognitive function

Neural network models are potential tools for improving our understanding of complex brain functions. To address this goal, these models need to be neurobiologically realistic. However, although neural networks have advanced dramatically in recent years and even achieve human-like performance on complex perceptual and cognitive tasks, their similarity to aspects of brain anatomy and physiology is imperfect. Here, we discuss different types of neural models, including localist, auto-associative, hetero-associative, deep and whole-brain networks, and identify aspects under which their biological plausibility can be improved. These aspects range from the choice of model neurons and of mechanisms of synaptic plasticity and learning to implementation of inhibition and control, along with neuroanatomical properties including areal structure and local and long-range connectivity. We highlight recent advances in developing biologically grounded cognitive theories and in mechanistically explaining, on the basis of these brain-constrained neural models, hitherto unaddressed issues regarding the nature, localization and ontogenetic and phylogenetic development of higher brain functions. In closing, we point to possible future clinical applications of brain-constrained modelling.

Large-scale network dynamics in neural response to emotionally negative stimuli linked to serotonin 1A binding in major depressive disorder

Serotonergic dysfunction is implicated in major depressive disorder (MDD), but the mechanisms of this relationship remain elusive. Serotonin 1A (5-HT_1A) autoreceptors regulate brain-wide serotonin neuron firing and are positioned to assert large-scale effects on negative emotion. Here we investigated the relationship between raphe 5-HT_1A binding and brain-wide network dynamics of negative emotion. 22 healthy-volunteers (HV) and 27 medication-free participants with MDD underwent positron emission tomography (PET) using [¹¹C]CUMI-101 (CUMI) to quantify 5-HT_1A binding in midbrain raphe nuclei and functional magnetic resonance imaging (fMRI) scanning during emotionally negative picture viewing. Causal connectivity across regions responsive to negative emotion was estimated in the fMRI data using a multivariate dynamical systems model. During negative picture viewing, MDD subjects demonstrated significant hippocampal inhibition of amygdala, basal-ganglia, thalamus, orbital frontal cortex, inferior frontal gyrus and dorsomedial prefrontal cortex (IFG, dmPFC). MDD-related connectivity was not associated with raphe 5-HT_1A binding. However, greater hippocampal inhibition of amygdala, thalamus, IFG and dmPFC correlated with hippocampal 5-HT_1A binding. Correlation between hippocampal 5-HT_1A binding and the hippocampal inhibition network was specific to MDD but not HV. MDD and HV groups also differed with respect to the correlation between raphe and hippocampal 5-HT_1A binding which was more pronounced in HV. These findings suggest that increased hippocampal network inhibition in MDD is linked to hippocampal serotonergic dysfunction which may in turn arise from disrupted linkage in raphe to hippocampus serotonergic circuitry.

The application of a neuropsychological measure of executive working memory in older adults with memory impairment

The component of working memory that the frontal cortex subserves is frequently characterized as the executive working memory (EWM). This study applied a neuropsychological measure of EWM (NPM-EWM) in older adults with memory impairment to investigate the EWM. Thirty-two older adults from the community were recruited as older healthy controls (OHCs), and 58 older adults from a memory clinic were diagnosed with mild cognitive impairment (MCI) and mild dementia (MD). Significant differences were found among the three groups in the Clinical Dementia Rating (CDR), the Chinese version of Mini-Mental State Examination (MMSE-C), and the Cognitive Abilities Screening Instrument (CASI). The NPM-EWM was applied by using the learning task of the Comprehensive Nonverbal Memory Test Battery, where the 7 scores were divided into two categories: mnemonic capacity and executive error. All OHCs, more than 50% MCI, and less than 25% of MD patients passed the NPM-EWM. The MCI-passed and MD-passed subgroups showed similar mnemonic capacity and executive errors, and both the subgroups had significantly worse performance than the OHC group. The MD-passed subgroup had a higher Hamilton Depression Rating Scale (HDRS) score than did the MD-failed subgroup. The MCI-failed subgroup had a higher Hierarchy of Care Required (HCR) level in instrumental activities of daily living (IADL) than did the MCI-passed subgroup. These findings indicated that applying the NPM-EWM for older adults with memory impairment may offer precise and tailored care to a whole person, especially for the MCI patients with poorer EWM and the MD patients with relatively intact EWM.

Effect of Self-Controlled Practice on Neuro-Cortical Dynamics During the Processing of Visual Performance Feedback

Evidence has accumulated that learners participating in self-controlled practice can both acquire skills and process task-relevant information more effectively than those participating in externally controlled practice. However, the impact of self-controlled practice on neuro-cognitive information processing during visual performance-related feedback has received limited investigation. We expected that individuals participating in self-controlled practice would exhibit elevated neuro-cognitive information processing, as assessed via electroencephalography (EEG), compared with those engaged with externally controlled practice. Participants practiced a golf-putting task under self-controlled or externally controlled (yoked) conditions while EEG data were recorded. Results indicated that EEG theta power was maintained at an elevated level during the feedback period in the self-controlled group relative to the yoked group. The yoked group did not display increases in theta power until the time at which the ball stopped. Both groups displayed similar improvement over the course of the experiment. Correlational analyses revealed that performance improvement within each group was related differently to EEG theta power. Specifically, the self-controlled group displayed positive relationships between theta power and performance improvement, while the yoked group displayed negative relationships. These results have implications regarding the relative effectiveness of self-controlled and externally controlled practice and the instances in which they may provide the most benefit.

Distribution of VTA Glutamate and Dopamine Terminals, and their Significance in CA1 Neural Network Activity

Reciprocal connection between the ventral tegmental area (VTA) and the hippocampus forms a loop that controls information entry into long-term memory. Compared with the widely studied VTA dopamine system, VTA glutamate terminals are anatomically dominant in the hippocampus and less understood. The current study employs anterograde and retrograde labeling of VTA dopamine and glutamate neurons to map the distribution of their terminals within the layers of the hippocampus. Also, functional tracing of VTA dopamine and glutamate projections to the hippocampus was performed by photostimulation of VTA cell bodies during CA1 extracellular voltage sampling in vivo. VTA dopamine terminals predominantly innervate the CA1 basal dendrite layer and modulate the firing rate of active putative neurons. In contrast, anatomical dominance of VTA glutamate terminals in the CA1 pyramidal cell and apical dendrite layers suggests the possible involvement of these terminals in excitability regulation. In support of these outcomes, photostimulation of VTA dopamine neurons increased the firing rate but not intrinsic excitability parameters for putative pyramidal units. Conversely, activation of VTA glutamate neurons increased CA1 network firing rate and burst rate. In addition, VTA glutamate inputs reduced the interspike and interburst intervals for putative CA1 neurons. Taken together, we deduced that layer-specific distribution of presynaptic dopamine and glutamate terminals in the hippocampus determinines VTA modulation (dopamine) or regulation (glutamate) of excitability in the CA1 neural network.

How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning

Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.

A sensorimotor control framework for understanding emotional communication and regulation

Our research team was asked to consider the relationship of the neuroscience of sensorimotor control to the language of emotions and feelings. Actions are the principal means for the communication of emotions and feelings in both humans and other animals, and the allostatic mechanisms controlling action also apply to the regulation of emotional states by the self and others. We consider how motor control of hierarchically organised, feedback-based, goal-directed action has evolved in humans, within a context of consciousness, appraisal and cultural learning, to serve emotions and feelings. In our linguistic analysis, we found that many emotion and feelings words could be assigned to stages in the sensorimotor learning process, but the assignment was often arbitrary. The embodied nature of emotional communication means that action words are frequently used, but that the meanings or senses of the word depend on its contextual use, just as the relationship of an action to an emotion is also contextually dependent.

Distinct neural networks for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study

The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

Contributions of Parietal Cortex to the Working Memory of an Obstacle Acquired Visually or Tactilely in the Locomoting Cat

A working memory of obstacles is essential for navigating complex, cluttered terrain. In quadrupeds, it has been proposed that parietal cortical areas related to movement planning and working memory may be important for guiding the hindlegs over an obstacle previously cleared by the forelegs. To test this hypothesis, parietal areas 5 and 7 were reversibly deactivated in walking cats. The working memory of an obstacle was assessed in both a visually dependent and tactilely dependent paradigm. Reversible bilateral deactivation of area 5, but not area 7, altered hindleg stepping in a manner indicating that the animals did not recall the obstacle over which their forelegs had stepped. Similar deficits were observed when area 5 deactivation was restricted to the delay during which obstacle memory must be maintained. Furthermore, partial memory recovery observed when area 5 function was deactivated and restored within this maintenance period suggests that the deactivation may suppress, but not eliminate, the working memory of an obstacle. As area 5 deactivations incurred similar memory deficits in both visual and tactile obstacle working memory paradigms, parietal area 5 is critical for maintaining the working memory of an obstacle acquired via vision or touch that is used to modify stepping for avoidance.

The Causal Role of the Prefrontal Cortex and Somatosensory Cortex in Tactile Working Memory

In the present study, we searched for causal evidence linking activity in the bilateral primary somatosensory cortex (SI), posterior parietal cortex (PPC), and prefrontal cortex (PFC) with behavioral performance in vibrotactile working memory. Participants performed a vibrotactile delayed matching-to-sample task, while single-pulse transcranial magnetic stimulation (sp-TMS) was applied over these cortical areas at 100, 200, 300, 600, 1600, and 1900 ms after the onset of vibrotactile stimulation (200 ms duration). In our experiments, sp-TMS over the contralateral SI at the early delay (100 and 200 ms) deteriorated the accuracy of task performance, and over the ipsilateral SI at the late delay (1600 and 1900 ms) also induced such deteriorating effects. Furthermore, deteriorating effects caused by sp-TMS over the contralateral DLPFC at the same maintenance stage (1600 ms) were correlated with the effects caused by sp-TMS over the ipsilateral SI, indicating that information retained in the ipsilateral SI during the late delay may be associated with the DLPFC. Taken together, these results suggest that both the contralateral and ipsilateral SIs are involved in tactile WM, and the contralateral DLPFC bridges the contralateral SI and ipsilateral SI for goal-directed action.

Effects of Exercise Modes on Neural Processing of Working Memory in Late Middle-Aged Adults: An fMRI Study

Recent studies have highlighted the importance of regular exercise on cognitive function in aging populations, with aerobic exercise and cardiovascular fitness having received the largest amount of research attention. However, the relationship between exercise mode and cognitive function underlying behavioral modification and neural activation remains unknown. The present study, therefore, sought to examine the associations between different exercise modes and the working memory (WM) aspect of executive function as well as its task-evoked brain activation in the late middle-aged population. Seventy late middle-aged adults were classified into open-skill, closed-skill, or irregular exercise groups based on their participation in exercise activities prior to the study and then performed a spatial working memory (SWM) task while undergoing functional magnetic resonance imaging (fMRI) scanning. The results revealed that exercise groups, regardless of exercise modes, showed better SWM and physical fitness performance. Additionally, the open-skill group exhibited greater brain activation in the prefrontal lobe, anterior cingulate cortex/supplementary motor area (ACC/SMA), and hippocampus than those in the closed-skill group, suggesting a mode-sensitive compensatory mechanism in late middle-aged adults. These findings indicate that exercise promotes cognitive health, improves WM, and enhances neurocognitive scaffolding in late middle-aged adults and further suggest that various exercise modes can effectively modulate frontal and hippocampal function in the face of age-related neurocognitive declines, implications that may inform the development of exercise programs for the elderly.

Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks

Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, interactions among multiple (e.g., triple and quadruple) areas cannot be reduced to pairwise interactions. Such higher order interactions (HOIs), e.g., exclusive-or (XOR) operation, are widely implemented in computation systems and are crucial for effective information processing. However, it is currently unclear whether any HOIs are present in large-scale brain functional networks when subjects are executing specific tasks. Here we analyzed functional magnetic resonance imaging (fMRI) data collected from human subjects executing various perceptual, motor, and cognitive tasks. We found that HOI strength in the macroscopic functional networks was very weak for all tasks, suggesting that major brain activities do not rely on HOIs on the macroscopic level at the timescale of hundreds of milliseconds. These weak HOIs during tasks were further investigated with a neural network model activated by external inputs, which suggested that weak pairwise interactions among brain areas organized the system without involving HOIs. Taken together, these results demonstrated the dominance of pairwise interactions in organizing coordinated activities among different brain areas to support various brain functions.

Human Brain/Cloud Interface

The Internet comprises a decentralized global system that serves humanity's collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a "human brain/cloud interface" ("B/CI"), would be based on technologies referred to here as "neuralnanorobotics." Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain's ∼86 × 109 neurons and ∼2 × 1014 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood-brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ∼6 × 1016 bits per second of synaptically processed and encoded human-brain electrical information via auxiliary nanorobotic fiber optics (30 cm3) with the capacity to handle up to 1018 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as "transparent shadowing" (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.

A SENtence Supramodal Areas AtlaS (SENSAAS) based on multiple task-induced activation mapping and graph analysis of intrinsic connectivity in 144 healthy right-handers

We herein propose an atlas of 32 sentence-related areas based on a 3-step method combining the analysis of activation and asymmetry during multiple language tasks with hierarchical clustering of resting-state connectivity and graph analyses. 144 healthy right-handers performed fMRI runs based on language production, reading and listening, both with sentences and lists of over-learned words. Sentence minus word-list BOLD contrast and left-minus-right BOLD asymmetry for each task were computed in pairs of homotopic regions of interest (hROIs) from the AICHA atlas. Thirty-two hROIs were identified that were conjointly activated and leftward asymmetrical in each of the three language contrasts. Analysis of resting-state temporal correlations of BOLD variations between these 32 hROIs allowed the segregation of a core network, SENT_CORE including 18 hROIs. Resting-state graph analysis applied to SENT_CORE hROIs revealed that the pars triangularis of the inferior frontal gyrus and the superior temporal sulcus were hubs based on their degree centrality (DC), betweenness, and participation values corresponding to epicentres of sentence processing. Positive correlations between DC and BOLD activation values for SENT_CORE hROIs were observed across individuals and across regions regardless of the task: the more a SENT_CORE area is connected at rest the stronger it is activated during sentence processing. DC measurements in SENT_CORE may thus be a valuable index for the evaluation of inter-individual variations in language areas functional activity in relation to anatomical or clinical patterns in large populations. SENSAAS (SENtence Supramodal Areas AtlaS), comprising the 32 supramodal sentence areas, including SENT_CORE network, can be downloaded at http://www.gin.cnrs.fr/en/tools/ .

Theta oscillations promote temporal sequence learning

Many theoretical models suggest that neural oscillations play a role in learning or retrieval of temporal sequences, but the extent to which oscillations support sequence representation remains unclear. To address this question, we used scalp electroencephalography (EEG) to examine oscillatory activity over learning of different object sequences. Participants made semantic decisions on each object as they were presented in a continuous stream. For three "Consistent" sequences, the order of the objects was always fixed. Activity during Consistent sequences was compared to "Random" sequences that consisted of the same objects presented in a different order on each repetition. Over the course of learning, participants made faster semantic decisions to objects in Consistent, as compared to objects in Random sequences. Thus, participants were able to use sequence knowledge to predict upcoming items in Consistent sequences. EEG analyses revealed decreased oscillatory power in the theta (4-7 Hz) band at frontal sites following decisions about objects in Consistent sequences, as compared with objects in Random sequences. The theta power difference between Consistent and Random only emerged in the second half of the task, as participants were more effectively able to predict items in Consistent sequences. Moreover, we found increases in parieto-occipital alpha (10-13 Hz) and beta (14-28 Hz) power during the pre-response period for objects in Consistent sequences, relative to objects in Random sequences. Linear mixed effects modeling revealed that single trial theta oscillations were related to reaction time for future objects in a sequence, whereas beta and alpha oscillations were only predictive of reaction time on the current trial. These results indicate that theta and alpha/beta activity preferentially relate to future and current events, respectively. More generally our findings highlight the importance of band-specific neural oscillations in the learning of temporal order information.

The case of CAUSE: neurobiological mechanisms for grounding an abstract concept

How can we understand causal relationships and how can we understand words such as 'cause'? Some theorists assume that the underlying abstract concept is given to us, and that perceptual correlation provides the relevant hints towards inferring causation from perceived real-life events. A different approach emphasizes the role of actions and their typical consequences for the emergence of the concept of causation and the application of the related term. A model of causation is proposed that highlights the family resemblance between causal actions and postulates that symbols are necessary for binding together the different partially shared semantic features of subsets of causal actions and their goals. Linguistic symbols are proposed to play a key role in binding the different subsets of semantic features of the abstract concept. The model is spelt out at the neuromechanistic level of distributed cortical circuits and the cognitive functions they carry. The model is discussed in light of behavioural and neuroscience evidence, and questions for future research are highlighted. In sum, taking causation as a concrete example, I argue that abstract concepts and words can be learnt and grounded in real-life interaction, and that the neurobiological mechanisms realizing such abstract semantic grounding are within our grasp.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Dorsolateral prefrontal cortex bridges bilateral primary somatosensory cortices during cross-modal working memory

Neural activity in the dorsolateral prefrontal cortex (DLPFC) has been suggested to integrate information from distinct sensory areas. However, how the DLPFC interacts with the bilateral primary somatosensory cortices (SIs) in tactile-visual cross-modal working memory has not yet been established. In the present study, we applied single-pulse transcranial magnetic stimulation (sp-TMS) over the contralateral DLPFC and bilateral SIs of human participants at various time points, while they performed a tactile-visual delayed matching-to-sample task with a 2-second delay. sp-TMS over the contralateral DLPFC or the contralateral SI at either an sensory encoding stage [i.e. 100 ms after the onset of a vibrotactile sample stimulus (200-ms duration)] or an early maintenance stage (i.e. 300 ms after the onset), significantly impaired the accuracy of task performance; sp-TMS over the contralateral DLPFC or the ipsilateral SI at a late maintenance stage (1600 ms and 1900 ms) also significantly disrupted the performance. Furthermore, at 300 ms after the onset of the vibrotactile sample stimulus, there was a significant correlation between the deteriorating effects of sp-TMS over the contralateral SI and the contralateral DLPFC. These results imply that the DLPFC and the bilateral SIs play causal roles at distinctive stages during cross-modal working memory, while the contralateral DLPFC communicates with the contralateral SI in the early delay, and cooperates with the ipsilateral SI in the late delay.

Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study

Exact low resolution electromagnetic tomography (eLORETA) was recorded from nineteen EEG channels in nine patients with myalgic encephalomyelitis (ME) and 9 healthy controls to assess current source density and functional connectivity, a physiological measure of similarity between pairs of distributed regions of interest, between groups. Current source density and functional connectivity were measured using eLORETA software. We found significantly decreased eLORETA source analysis oscillations in the occipital, parietal, posterior cingulate, and posterior temporal lobes in Alpha and Alpha-2. For connectivity analysis, we assessed functional connectivity within Menon triple network model of neuropathology. We found support for all three networks of the triple network model, namely the central executive network (CEN), salience network (SN), and the default mode network (DMN) indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls. In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a neurobiological feature of the disorder, representing underlying neural dysfunction.

What Is the Evidence for Inter-laminar Integration in a Prefrontal Cortical Minicolumn?

The objective of this perspective article is to examine columnar inter-laminar integration during the executive control of behavior. The integration hypothesis posits that perceptual and behavioral signals are integrated within the prefrontal cortical inter-laminar microcircuits. Inter-laminar minicolumnar activity previously recorded from the dorsolateral prefrontal cortex (dlPFC) of nonhuman primates, trained in a visual delay match-to-sample (DMS) task, was re-assessed from an integrative perspective. Biomorphic multielectrode arrays (MEAs) played a unique role in the in vivo recording of columnar cell firing in the dlPFC layers 2/3 and 5/6. Several integrative aspects stem from these experiments: 1. Functional integration of perceptual and behavioral signals across cortical layers during executive control. The integrative effect of dlPFC minicolumns was shown by: (i) increased correlated firing on correct vs. error trials; (ii) decreased correlated firing when the number of non-matching images increased; and (iii) similar spatial firing preference across cortical-striatal cells during spatial-trials, and less on object-trials. 2. Causal relations to integration of cognitive signals by the minicolumnar turbo-engines. The inter-laminar integration between the perceptual and executive circuits was facilitated by stimulating the infra-granular layers with firing patterns obtained from supra-granular layers that enhanced spatial preference of percent correct performance on spatial trials. 3. Integration across hierarchical levels of the brain. The integration of intention signals (visual spatial, direction) with movement preparation (timing, velocity) in striatum and with the motor command and posture in midbrain is also discussed. These findings provide evidence for inter-laminar integration of executive control signals within brain's prefrontal cortical microcircuits.

Decision-making without a brain: how an amoeboid organism solves the two-armed bandit

Several recent studies hint at shared patterns in decision-making between taxonomically distant organisms, yet few studies demonstrate and dissect mechanisms of decision-making in simpler organisms. We examine decision-making in the unicellular slime mould Physarum polycephalum using a classical decision problem adapted from human and animal decision-making studies: the two-armed bandit problem. This problem has previously only been used to study organisms with brains, yet here we demonstrate that a brainless unicellular organism compares the relative qualities of multiple options, integrates over repeated samplings to perform well in random environments, and combines information on reward frequency and magnitude in order to make correct and adaptive decisions. We extend our inquiry by using Bayesian model selection to determine the most likely algorithm used by the cell when making decisions. We deduce that this algorithm centres around a tendency to exploit environments in proportion to their reward experienced through past sampling. The algorithm is intermediate in computational complexity between simple, reactionary heuristics and calculation-intensive optimal performance algorithms, yet it has very good relative performance. Our study provides insight into ancestral mechanisms of decision-making and suggests that fundamental principles of decision-making, information processing and even cognition are shared among diverse biological systems.

Multistable Perception and the Role of the Frontoparietal Cortex in Perceptual Inference

A given pattern of optical stimulation can arise from countless possible real-world sources, creating a dilemma for vision: What in the world actually gives rise to the current pattern? This dilemma was pointed out centuries ago by the astronomer and mathematician Ibn Al-Haytham and was forcefully restated 150 years ago when von Helmholtz characterized perception as unconscious inference. To buttress his contention, von Helmholtz cited multistable perception: recurring changes in perception despite unchanging sensory input. Recent neuroscientific studies have exploited multistable perception to identify brain areas uniquely activated in association with these perceptual changes, but the specific roles of those activations remain controversial. This article provides an overview of theoretical models of multistable perception, a review of recent neuroimaging and brain stimulation studies focused on mechanisms associated with these perceptual changes, and a synthesis of available evidence within the context of current notions about Bayesian inference that find their historical roots in von Helmholtz's work.

Neural reuse of action perception circuits for language, concepts and communication

Neurocognitive and neurolinguistics theories make explicit statements relating specialized cognitive and linguistic processes to specific brain loci. These linking hypotheses are in need of neurobiological justification and explanation. Recent mathematical models of human language mechanisms constrained by fundamental neuroscience principles and established knowledge about comparative neuroanatomy offer explanations for where, when and how language is processed in the human brain. In these models, network structure and connectivity along with action- and perception-induced correlation of neuronal activity co-determine neurocognitive mechanisms. Language learning leads to the formation of action perception circuits (APCs) with specific distributions across cortical areas. Cognitive and linguistic processes such as speech production, comprehension, verbal working memory and prediction are modelled by activity dynamics in these APCs, and combinatorial and communicative-interactive knowledge is organized in the dynamics within, and connections between APCs. The network models and, in particular, the concept of distributionally-specific circuits, can account for some previously not well understood facts about the cortical 'hubs' for semantic processing and the motor system's role in language understanding and speech sound recognition. A review of experimental data evaluates predictions of the APC model and alternative theories, also providing detailed discussion of some seemingly contradictory findings. Throughout, recent disputes about the role of mirror neurons and grounded cognition in language and communication are assessed critically.

Memory Takes Time

Memory is an adaptation to particular temporal properties of past events, such as the frequency of occurrence of a stimulus or the coincidence of multiple stimuli. In neurons, this adaptation can be understood in terms of a hierarchical system of molecular and cellular time windows, which collectively retain information from the past. We propose that this system makes various timescales of past experience simultaneously available for future adjustment of behavior. More generally, we propose that the ability to detect and respond to temporally structured information underlies the nervous system's capacity to encode and store a memory at molecular, cellular, synaptic, and circuit levels.

Mechanisms of automaticity and anticipatory control in fluid intelligence

The constructs of fluid (Gf) and crystalized (Gc) intelligence represent an early attempt to describe the mechanisms of problem solving in the vertebrate brain. Modern neuroscience demonstrates that problem solving involves interplay between the mechanisms of automaticity and anticipatory control, enabling nature's elegant solution to the challenges animals face in their environment. Studies of neural functioning are making clear the primary role of cortical-subcortical interactions in the manifestation of intelligent behavior in humans and other vertebrates. A tridimensional model of intelligent problem solving is explored, wherein the basal ganglia system (BGS) and cerebrocerebellar system (CCS) interact within large scale brain networks. The BGS and CCS work together to enable automaticity to occur. The BGS enables the organism to learn what to do through a powerful instrumental learning system. The BGS also regulates when behavior is released through an inhibitory system which is incredibly sensitive to context. The CCS enables the organism to learn how to perform adaptive behaviors. Internal cerebellar models enable gradual improvements in the quality of behavioral output. The BGS and CCS interact within large scale brain networks, including the dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN) and frontoparietal network (FPN). The interactions of these systems enable vertebrate organisms to develop a vast array of complex adaptive behaviors. The benefits and importance of developing clinical tests to measure the integrity of these systems is considered.

Neurocomputational Consequences of Evolutionary Connectivity Changes in Perisylvian Language Cortex

The human brain sets itself apart from that of its primate relatives by specific neuroanatomical features, especially the strong linkage of left perisylvian language areas (frontal and temporal cortex) by way of the arcuate fasciculus (AF). AF connectivity has been shown to correlate with verbal working memory-a specifically human trait providing the foundation for language abilities-but a mechanistic explanation of any related causal link between anatomical structure and cognitive function is still missing. Here, we provide a possible explanation and link, by using neurocomputational simulations in neuroanatomically structured models of the perisylvian language cortex. We compare networks mimicking key features of cortical connectivity in monkeys and humans, specifically the presence of relatively stronger higher-order "jumping links" between nonadjacent perisylvian cortical areas in the latter, and demonstrate that the emergence of working memory for syllables and word forms is a functional consequence of this structural evolutionary change. We also show that a mere increase of learning time is not sufficient, but that this specific structural feature, which entails higher connectivity degree of relevant areas and shorter sensorimotor path length, is crucial. These results offer a better understanding of specifically human anatomical features underlying the language faculty and their evolutionary selection advantage.SIGNIFICANCE STATEMENT Why do humans have superior language abilities compared to primates? Recently, a uniquely human neuroanatomical feature has been demonstrated in the strength of the arcuate fasciculus (AF), a fiber pathway interlinking the left-hemispheric language areas. Although AF anatomy has been related to linguistic skills, an explanation of how this fiber bundle may support language abilities is still missing. We use neuroanatomically structured computational models to investigate the consequences of evolutionary changes in language area connectivity and demonstrate that the human-specific higher connectivity degree and comparatively shorter sensorimotor path length implicated by the AF entail emergence of verbal working memory, a prerequisite for language learning. These results offer a better understanding of specifically human anatomical features for language and their evolutionary selection advantage.

The effects of item familiarity on the neural correlates of successful associative memory encoding

Associative memory is considered to be resource-demanding, requiring individuals to learn individual items and the specific relationships between those items. Previous research has shown that prior studying of items aids in associative memory for pairs composed of those same items, as compared to pairs of items that have not been prelearned (e.g., Kilb & Naveh-Benjamin, 2011). In the present study, we sought to elucidate the neural correlates mediating this memory facilitation. After being trained on individual items, participants were scanned while encoding item pairs composed of items from the pretrained phase (familiarized-item pairs) and pairs whose items had not been previously learned (unfamiliarized-item pairs). Consistent with previous findings, the overall subsequent recollection showed the engagement of bilateral parahippocampal gyrus (PHG) and hippocampus, when compared to subsequent forgetting. However, a direct comparison between familiarized- and unfamiliarized-item pairs showed that subsequently recollected familiarized-item pairs were associated with decreased activity across much of the encoding network, including bilateral PHG, hippocampus, prefrontal cortex, and regions associated with item-specific processing within occipital cortex. Increased activity for familiarized-item pairs was found in a more limited set of regions, including bilateral parietal cortex, which has been associated with the formation of novel associations. Additionally, activity in the right parietal cortex correlated with associative memory success in the familiarized condition. Taken together, these results suggest that prior exposure to items can reduce the demands incurred on neural processing throughout the associative encoding network and can enhance associative memory performance by focusing resources within regions supporting the formation of associative links.

Top-Down Dysregulation-From ADHD to Emotional Instability

Deficient cognitive top-down executive control has long been hypothesized to underlie inattention and impulsivity in attention-deficit/hyperactivity disorder (ADHD). However, top-down cognitive dysfunction explains a modest proportion of the ADHD phenotype whereas the salience of emotional dysregulation is being noted increasingly. Together, these two types of dysfunction have the potential to account for more of the phenotypic variance in patients diagnosed with ADHD. We develop this idea and suggest that top-down dysregulation constitutes a gradient extending from mostly non-emotional top-down control processes (i.e., “cool” executive functions) to mainly emotional regulatory processes (including “hot” executive functions). While ADHD has been classically linked primarily to the former, conditions involving emotional instability such as borderline and antisocial personality disorder are closer to the other. In this model, emotional subtypes of ADHD are located at intermediate levels of this gradient. Neuroanatomically, gradations in “cool” processing appear to be related to prefrontal dysfunction involving dorsolateral prefrontal cortex (dlPFC) and caudal anterior cingulate cortex (cACC), while “hot” processing entails orbitofrontal cortex and rostral anterior cingulate cortex (rACC). A similar distinction between systems related to non-emotional and emotional processing appears to hold for the basal ganglia (BG) and the neuromodulatory effects of the dopamine system. Overall we suggest that these two systems could be divided according to whether they process non-emotional information related to the exteroceptive environment (associated with “cool” regulatory circuits) or emotional information related to the interoceptive environment (associated with “hot” regulatory circuits). We propose that this framework can integrate ADHD, emotional traits in ADHD, borderline and antisocial personality disorder into a related cluster of mental conditions.

Causal evidence for frontal cortex organization for perceptual decision making

Although recent research has shown that the frontal cortex has a critical role in perceptual decision making, an overarching theory of frontal functional organization for perception has yet to emerge. Perceptual decision making is temporally organized such that it requires the processes of selection, criterion setting, and evaluation. We hypothesized that exploring this temporal structure would reveal a large-scale frontal organization for perception. A causal intervention with transcranial magnetic stimulation revealed clear specialization along the rostrocaudal axis such that the control of successive stages of perceptual decision making was selectively affected by perturbation of successively rostral areas. Simulations with a dynamic model of decision making suggested distinct computational contributions of each region. Finally, the emergent frontal gradient was further corroborated by functional MRI. These causal results provide an organizational principle for the role of frontal cortex in the control of perceptual decision making and suggest specific mechanistic contributions for its different subregions.

Spontaneous Neural Dynamics and Multi-scale Network Organization

Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire.