Role of prefrontal cortex and the midbrain dopamine system in working memory updating

Linking ADHD to the Neural Circuitry of Attention

Attention deficit hyperactivity disorder (ADHD) is a complex condition with a heterogeneous presentation. Current diagnosis is primarily based on subjective experience and observer reports of behavioral symptoms - an approach that has significant limitations. Many studies show that individuals with ADHD exhibit poorer performance on cognitive tasks than neurotypical controls, and at least seven main functional domains appear to be implicated in ADHD. We discuss the underlying neural mechanisms of cognitive functions associated with ADHD, with emphasis on the neural basis of selective attention, demonstrating the feasibility of basic research approaches for further understanding cognitive behavioral processes as they relate to human psychopathology. The study of circuit-level mechanisms underlying executive functions in nonhuman primates holds promise for advancing our understanding, and ultimately the treatment, of ADHD.

Tracking Real-Time Changes in Working Memory Updating and Gating with the Event-Based Eye-Blink Rate

Effective working memory (WM) functioning depends on the gating process that regulates the balance between maintenance and updating of WM. The present study used the event-based eye-blink rate (ebEBR), which presumably reflects phasic striatal dopamine activity, to examine how the cognitive processes of gating and updating separately facilitate flexible updating of WM contents and the potential involvement of dopamine in these processes. Real-time changes in eye blinks were tracked during performance on the reference-back task, in which demands on these two processes were independently manipulated. In all three experiments, trials that required WM updating and trials that required gate switching were both associated with increased ebEBR. These results may support the prefrontal cortex basal ganglia WM model (PBWM) by linking updating and gating to striatal dopaminergic activity. In Experiment 3, the ebEBR was used to determine what triggers gate switching. We found that switching to an updating mode (gate opening) was more stimulus driven and retroactive than switching to a maintenance mode, which was more context driven. Together, these findings show that the ebEBR - an inexpensive, non-invasive, easy-to-use measure - can be used to track changes in WM demands during task performance and, hence, possibly striatal dopamine activity.

Activation of the ventral tegmental area increased wakefulness in mice

The ventral tegmental area (VTA) is crucial for brain functions, such as voluntary movement and cognition; however, the role of VTA in sleep-wake regulation when directly activated or inhibited remains unknown. In this study, we investigated the effects of activation or inhibition of VTA neurons on sleep-wake behavior using the pharmacogenetic “designer receptors exclusively activated by designer drugs (DREADD)” approach. Immunohistochemistry staining was performed to confirm the microinjection sites, and combined with electrophysiological experiments, to determine whether the VTA neurons were activated or inhibited. The hM3Dq-expressing VTA neurons were excited confirmed by clozapine-N-oxide (CNO)-driven c-Fos expression and firing in patch-clamp recordings; whereas the hM4Di-expressing VTA neurons inhibited by reduction of firing. Compared with controls, the activation of VTA neurons at 9:00 (inactive period) produced a 120.1% increase in the total wakefulness amount for 5 h, whereas NREM and REM sleep were decreased by 62.5 and 92.2%, respectively. Similarly, when VTA neurons were excited at 21:00 (active period), the total wakefulness amount increased 81.5%, while NREM and REM sleep decreased 64.6 and 93.8%, respectively, for 8 h. No difference of the amount and EEG power density of the NREM sleep was observed following the arousal effects of CNO. The inhibition of VTA neurons during active or inactive periods gave rise to no change in the time spent in the wakefulness, REM, and NREM sleep compared with control. The results indicated that VTA neurons activated pharmacogentically played important roles in promoting wakefulness.

Activating Developmental Reserve Capacity Via Cognitive Training or Non-invasive Brain Stimulation: Potentials for Promoting Fronto-Parietal and Hippocampal-Striatal Network Functions in Old Age

Existing neurocomputational and empirical data link deficient neuromodulation of the fronto-parietal and hippocampal-striatal circuitries with aging-related increase in processing noise and declines in various cognitive functions. Specifically, the theory of aging neuronal gain control postulates that aging-related suboptimal neuromodulation may attenuate neuronal gain control, which yields computational consequences on reducing the signal-to-noise-ratio of synaptic signal transmission and hampering information processing within and between cortical networks. Intervention methods such as cognitive training and non-invasive brain stimulation, e.g., transcranial direct current stimulation (tDCS), have been considered as means to buffer cognitive functions or delay cognitive decline in old age. However, to date the reported effect sizes of immediate training gains and maintenance effects of a variety of cognitive trainings are small to moderate at best; moreover, training-related transfer effects to non-trained but closely related (i.e., near-transfer) or other (i.e., far-transfer) cognitive functions are inconsistent or lacking. Similarly, although applying different tDCS protocols to reduce aging-related cognitive impairments by inducing temporary changes in cortical excitability seem somewhat promising, evidence of effects on short- and long-term plasticity is still equivocal. In this article, we will review and critically discuss existing findings of cognitive training- and stimulation-related behavioral and neural plasticity effects in the context of cognitive aging, focusing specifically on working memory and episodic memory functions, which are subserved by the fronto-parietal and hippocampal-striatal networks, respectively. Furthermore, in line with the theory of aging neuronal gain control we will highlight that developing age-specific brain stimulation protocols and the concurrent applications of tDCS during cognitive training may potentially facilitate short- and long-term cognitive and brain plasticity in old age.

Differences in frontal and limbic brain activation in a small sample of monozygotic twin pairs discordant for severe stressful life events

Monozygotic twin pairs provide a valuable opportunity to control for genetic and shared environmental influences while studying the effects of nonshared environmental influences. The question we address with this design is whether monozygotic twins selected for discordance in exposure to severe stressful life events during development (before age 18) demonstrate differences in brain activation during performance of an emotional word-face Stroop task. In this study, functional magnetic resonance imaging was used to assess brain activation in eighteen young adult twins who were discordant in exposure to severe stress such that one twin had two or more severe events compared to their control co-twin who had no severe events. Twins who experienced higher levels of stress during development, compared to their control co-twins with lower stress, exhibited significant clusters of greater activation in the ventrolateral and medial prefrontal cortex, basal ganglia, and limbic regions. The control co-twins showed only the more typical recruitment of frontoparietal regions thought to be important for executive control of attention and maintenance of task goals. Behavioral performance was not significantly different between twins within pairs, suggesting the twins with stress recruited additional neural resources associated with affective processing and updating working memory when performing at the same level. This study provides a powerful glimpse at the potential effects of stress during development while accounting for shared genetic and environmental influences.

Gender Differences in Verbal and Visuospatial Working Memory Performance and Networks

BACKGROUND

Working memory (WM) has been a matter of intensive basic and clinical research for some decades now. The investigation of WM function and dysfunction may facilitate the understanding of both physiological and pathological processes in the human brain. Though WM paradigms are widely used in neuroscientific and psychiatric research, conclusive knowledge about potential moderating variables such as gender is still missing.

METHODS

We used functional magnetic resonance imaging to investigate the effects of gender on verbal and visuospatial WM maintenance tasks in a large and homogeneous sample of young healthy subjects.

RESULTS

We found significant gender effects on both the behavioral and neurofunctional level. Females exhibited disadvantages with a small effect size in both WM domains accompanied by stronger activations in a set of brain regions (including bilateral substantia nigra/ventral tegmental area and right Broca's area) independent of WM modality. As load and task difficulty effects have been shown for some of these regions, the stronger activations may reflect a slightly lower capacity of both WM domains in females. Males showed stronger bilateral intraparietal activations next to the precuneus which were specific for the visuospatial WM task. Activity in this specific region may be associated with visuospatial short-term memory capacity.

CONCLUSION

These findings provide evidence for a slightly lower capacity in both WM modalities in females.

Frontostriatal Contribution to the Interplay of Flexibility and Stability in Serial Prediction

Surprising events may be relevant or irrelevant for behavior, requiring either flexible adjustment or stabilization of our model of the world and according response strategies. Cognitive flexibility and stability in response to environmental demands have been described as separable cognitive states, associated with activity of striatal and lateral prefrontal regions, respectively. It so far remains unclear, however, whether these two states act in an antagonistic fashion and which neural mechanisms mediate the selection of respective responses, on the one hand, and a transition between these states, on the other. In this study, we tested whether the functional dichotomy between striatal and prefrontal activity applies for the separate functions of updating (in response to changes in the environment, i.e., switches) and shielding (in response to chance occurrences of events violating expectations, i.e., drifts) of current predictions. We measured brain activity using fMRI while 20 healthy participants performed a task that required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press while sequence omissions (drifts) had to be ignored. We further varied the probability of switches and drifts to assess the neural network supporting the transition between flexible and stable cognitive states as a function of recent performance history in response to environmental demands. Flexible switching between models was associated with activation in medial pFC (BA 9 and BA 10), whereas stable maintenance of the internal model corresponded to activation in the lateral pFC (BA 6 and inferior frontal gyrus). Our findings extend previous studies on the interplay of flexibility and stability, suggesting that different prefrontal regions are activated by different types of prediction errors, dependent on their behavioral requirements. Furthermore, we found that striatal activation in response to switches and drifts was modulated by participants' successful behavior toward these events, suggesting the striatum to be responsible for response selections following unpredicted stimuli. Finally, we observed that the dopaminergic midbrain modulates the transition between different cognitive states, thresholded by participants' individual performance history in response to temporal environmental demands.

Dopamine Does Double Duty in Motivating Cognitive Effort

Cognitive control is subjectively costly, suggesting that engagement is modulated in relationship to incentive state. Dopamine appears to play key roles. In particular, dopamine may mediate cognitive effort by two broad classes of functions: (1) modulating the functional parameters of working memory circuits subserving effortful cognition, and (2) mediating value-learning and decision-making about effortful cognitive action. Here, we tie together these two lines of research, proposing how dopamine serves "double duty", translating incentive information into cognitive motivation.

Will big data yield new mathematics? An evolving synergy with neuroscience

New mathematics has often been inspired by new insights into the natural world. Here we describe some ongoing and possible future interactions among the massive data sets being collected in neuroscience, methods for their analysis and mathematical models of the underlying, still largely uncharted neural substrates that generate these data. We start by recalling events that occurred in turbulence modelling when substantial space-time velocity field measurements and numerical simulations allowed a new perspective on the governing equations of fluid mechanics. While no analogous global mathematical model of neural processes exists, we argue that big data may enable validation or at least rejection of models at cellular to brain area scales and may illuminate connections among models. We give examples of such models and survey some relatively new experimental technologies, including optogenetics and functional imaging, that can report neural activity in live animals performing complex tasks. The search for analytical techniques for these data is already yielding new mathematics, and we believe their multi-scale nature may help relate well-established models, such as the Hodgkin-Huxley equations for single neurons, to more abstract models of neural circuits, brain areas and larger networks within the brain. In brief, we envisage a closer liaison, if not a marriage, between neuroscience and mathematics.

Reward Motivation Enhances Task Coding in Frontoparietal Cortex

Reward motivation often enhances task performance, but the neural mechanisms underlying such cognitive enhancement remain unclear. Here, we used a multivariate pattern analysis (MVPA) approach to test the hypothesis that motivation-related enhancement of cognitive control results from improved encoding and representation of task set information. Participants underwent two fMRI sessions of cued task switching, the first under baseline conditions, and the second with randomly intermixed reward incentive and no-incentive trials. Information about the upcoming task could be successfully decoded from cue-related activation patterns in a set of frontoparietal regions typically associated with task control. More critically, MVPA classifiers trained on the baseline session had significantly higher decoding accuracy on incentive than non-incentive trials, with decoding improvement mediating reward-related enhancement of behavioral performance. These results strongly support the hypothesis that reward motivation enhances cognitive control, by improving the discriminability of task-relevant information coded and maintained in frontoparietal brain regions.

Dysfunctional Striatal Systems in Treatment-Resistant Schizophrenia

The prevalence of treatment-resistant schizophrenia points to a discrete illness subtype, but to date its pathophysiologic characteristics are undetermined. Information transfer from ventral to dorsal striatum depends on both striato-cortico-striatal and striato-nigro-striatal subcircuits, yet although the functional integrity of the former appears to track improvement of positive symptoms of schizophrenia, the latter have received little experimental attention in relation to the illness. Here, in a sample of individuals with schizophrenia stratified by treatment resistance and matched controls, functional pathways involving four foci along the striatal axis were assessed to test the hypothesis that treatment-resistant and non-refractory patients would exhibit contrasting patterns of resting striatal connectivity. Compared with non-refractory patients, treatment-resistant individuals exhibited reduced connectivity between ventral striatum and substantia nigra. Furthermore, disturbance to corticostriatal connectivity was more pervasive in treatment-resistant individuals. The occurrence of a more distributed pattern of abnormality may contribute to the failure of medication to treat symptoms in these individuals. This work strongly supports the notion of pathophysiologic divergence between individuals with schizophrenia classified by treatment-resistance criteria.

Converging roles of ion channels, calcium, metabolic stress, and activity pattern of Substantia nigra dopaminergic neurons in health and Parkinson's disease

Dopamine‐releasing neurons within the Substantia nigra (SN DA) are particularly vulnerable to degeneration compared to other dopaminergic neurons. The age‐dependent, progressive loss of these neurons is a pathological hallmark of Parkinson's disease (PD), as the resulting loss of striatal dopamine causes its major movement‐related symptoms. SN DA neurons release dopamine from their axonal terminals within the dorsal striatum, and also from their cell bodies and dendrites within the midbrain in a calcium‐ and activity‐dependent manner. Their intrinsically generated and metabolically challenging activity is created and modulated by the orchestrated function of different ion channels and dopamine D2‐autoreceptors. Here, we review increasing evidence that the mechanisms that control activity patterns and calcium homeostasis of SN DA neurons are not only crucial for their dopamine release within a physiological range but also modulate their mitochondrial and lysosomal activity, their metabolic stress levels, and their vulnerability to degeneration in PD. Indeed, impaired calcium homeostasis, lysosomal and mitochondrial dysfunction, and metabolic stress in SN DA neurons represent central converging trigger factors for idiopathic and familial PD. We summarize double‐edged roles of ion channels, activity patterns, calcium homeostasis, and related feedback/feed‐forward signaling mechanisms in SN DA neurons for maintaining and modulating their physiological function, but also for contributing to their vulnerability in PD‐paradigms. We focus on the emerging roles of maintained neuronal activity and calcium homeostasis within a physiological bandwidth, and its modulation by PD‐triggers, as well as on bidirectional functions of voltage‐gated L‐type calcium channels and metabolically gated ATP‐sensitive potassium (K‐ATP) channels, and their probable interplay in health and PD.

We propose that SN DA neurons possess several feedback and feed‐forward mechanisms to protect and adapt their activity‐pattern and calcium‐homeostasis within a physiological bandwidth, and that PD‐trigger factors can narrow this bandwidth. We summarize roles of ion channels in this view, and findings documenting that both, reduced as well as elevated activity and associated calcium‐levels can trigger SN DA degeneration.

This article is part of a special issue on Parkinson disease.

Chunking improves symbolic sequence processing and relies on working memory gating mechanisms

Chunking, namely the grouping of sequence elements in clusters, is ubiquitous during sequence processing, but its impact on performance remains debated. Here, we found that participants who adopted a consistent chunking strategy during symbolic sequence learning showed a greater improvement of their performance and a larger decrease in cognitive workload over time. Stronger reliance on chunking was also associated with higher scores in a WM updating task, suggesting the contribution of WM gating mechanisms to sequence chunking. Altogether, these results indicate that chunking is a cost-saving strategy that enhances effectiveness of symbolic sequence learning.

Working Memory: Maintenance, Updating, and the Realization of Intentions

"Working memory" refers to a vast set of mnemonic processes and associated brain networks, relates to basic intellectual abilities, and underlies many real-world functions. Working-memory maintenance involves frontoparietal regions and distributed representational areas, and can be based on persistent activity in reentrant loops, synchronous oscillations, or changes in synaptic strength. Manipulation of content of working memory depends on the dorsofrontal cortex, and updating is realized by a frontostriatal '"gating" function. Goals and intentions are represented as cognitive and motivational contexts in the rostrofrontal cortex. Different working-memory networks are linked via associative reinforcement-learning mechanisms into a self-organizing system. Normal capacity variation, as well as working-memory deficits, can largely be accounted for by the effectiveness and integrity of the basal ganglia and dopaminergic neurotransmission.

Differential effects of white noise in cognitive and perceptual tasks

Beneficial effects of noise on higher cognition have recently attracted attention. Hypothesizing an involvement of the mesolimbic dopamine system and its functional interactions with cortical areas, the current study aimed to demonstrate a facilitation of dopamine-dependent attentional and mnemonic functions by externally applying white noise in five behavioral experiments including a total sample of 167 healthy human subjects. During working memory, acoustic white noise impaired accuracy when presented during the maintenance period (Experiments 1-3). In a reward based long-term memory task, white noise accelerated perceptual judgments for scene images during encoding but left subsequent recognition memory unaffected (Experiment 4). In a modified Posner task (Experiment 5), the benefit due to white noise in attentional orienting correlated weakly with reward dependence, a personality trait that has been associated with the dopaminergic system. These results suggest that white noise has no general effect on cognitive functions. Instead, they indicate differential effects on perception and cognition depending on a variety of factors such as task demands and timing of white noise presentation.

The DA antagonist tiapride impairs context-related extinction learning in a novel context without affecting renewal

Renewal describes the recovery of an extinguished response if recall is tested in a context different from the extinction context. Behavioral studies demonstrated that attention to relevant context strengthens renewal. Neurotransmitters mediating attention and learning such as the dopaminergic (DA) system presumably modulate extinction learning and renewal. However, the role of DA for non-fear-based extinction learning and renewal in humans has not yet been investigated. This fMRI study investigated effects of DA-antagonism upon context-related extinction in a predictive learning task in which extinction occurred either in a novel (ABA) or an unchanged (AAA) context. The tiapride-treated group (TIA) showed significantly impaired ABA extinction learning and a significant within-group difference between ABA and AAA extinction, compared to placebo (PLAC). Groups did not differ in their level of ABA renewal. In ABA extinction, TIA showed reduced activation in dlPFC and OFC, hippocampus, and temporal regions. Across groups, activation in PFC and hippocampus correlated negatively with ABA extinction errors. Results suggest that in context-related extinction learning DA in PFC and hippocampus is involved in readjusting the cue-outcome relationship in the presence of a novel context. However, relating context to the appropriate association during recall does not appear to rely exclusively on DA signaling.

Cognitive control predicts use of model-based reinforcement learning

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

Reward feedback stimuli elicit high-beta EEG oscillations in human dorsolateral prefrontal cortex

Reward-related feedback stimuli have been observed to elicit a burst of power in the beta frequency range over frontal areas of the human scalp. Recent discussions have suggested possible neural sources for this activity but there is a paucity of empirical evidence on the question. Here we recorded EEG from participants while they navigated a virtual T-maze to find monetary rewards. Consistent with previous studies, we found that the reward feedback stimuli elicited an increase in beta power (20-30 Hz) over a right-frontal area of the scalp. Source analysis indicated that this signal was produced in the right dorsolateral prefrontal cortex (DLPFC). These findings align with previous observations of reward-related beta oscillations in the DLPFC in non-human primates. We speculate that increased power in the beta frequency range following reward receipt reflects the activation of task-related neural assemblies that encode the stimulus-response mapping in working memory.

Information maintenance in working memory: an integrated presentation of cognitive and neural concepts

Working memory (WM) maintains information in a state that it is available for processing. A host of various concepts exist which define this core function at different levels of abstraction. The present article intended to bring together existing cognitive and neural explanatory approaches about the architecture and neural mechanisms of information maintenance in WM. For this, we highlight how existing WM concepts define information retention and present different methodological approaches which led to the assumption that information can exist in various components and states. This view is broadened by neural concepts focussing on various forms of phase synchronization and molecular biological mechanisms relevant for retaining information in an active state. An integrated presentation of different concepts and methodological approaches can deepen our understanding of this central WM function.

Working memory training triggers delayed chromatin remodeling in the mouse corticostriatothalamic circuit

Working memory is a cognitive function serving goal-oriented behavior. In the last decade, working memory training has been shown to improve performance and its efficacy for the treatment of several neuropsychiatric disorders has begun to be examined. Neuroimaging studies have contributed to elucidate the brain areas involved but little is known about the underlying cellular events. A growing body of evidence has provided a link between working memory and relatively long-lasting epigenetic changes. However, the effects elicited by working memory training at the epigenetic level remain unknown. In this study we establish an animal model of working memory training and explore the changes in histone H3 acetylation (H3K9,14Ac) and histone H3 dimethylation on lysine 27 (H3K27Me2) triggered by the procedure in the brain regions of the corticostriatothalamic circuit (prelimbic/infralimbic cortex (PrL/IL), dorsomedial striatum (DMSt) and dorsomedial thalamus (DMTh)). Mice trained on a spontaneous alternation task showed improved alternation scores when tested with a retention interval that disrupts the performance of untrained animals. We then determined the involvement of the brain areas of the corticostriatothalamic circuit in working memory training by measuring the marker of neuronal activation c-fos. We observed increased c-fos levels in PrL/IL and DMSt in trained mice 90min after training. These animals also presented lower immunoreactivity for H3K9,14Ac in DMSt 24h but not 90min after the procedure. Increases in H3K27Me2, a repressive chromatin mark, were found in the DMSt and DMTh 24h after the task. Altogether, we present a mouse model to study the cellular underpinnings of working memory training and provide evidence indicating delayed chromatin remodeling towards repression triggered by the procedure.

Cooperative processing in primary somatosensory cortex and posterior parietal cortex during tactile working memory

In the present study, causal roles of both the primary somatosensory cortex (SI) and the posterior parietal cortex (PPC) were investigated in a tactile unimodal working memory (WM) task. Individual magnetic resonance imaging-based single-pulse transcranial magnetic stimulation (spTMS) was applied, respectively, to the left SI (ipsilateral to tactile stimuli), right SI (contralateral to tactile stimuli) and right PPC (contralateral to tactile stimuli), while human participants were performing a tactile-tactile unimodal delayed matching-to-sample task. The time points of spTMS were 300, 600 and 900 ms after the onset of the tactile sample stimulus (duration: 200 ms). Compared with ipsilateral SI, application of spTMS over either contralateral SI or contralateral PPC at those time points significantly impaired the accuracy of task performance. Meanwhile, the deterioration in accuracy did not vary with the stimulating time points. Together, these results indicate that the tactile information is processed cooperatively by SI and PPC in the same hemisphere, starting from the early delay of the tactile unimodal WM task. This pattern of processing of tactile information is different from the pattern in tactile-visual cross-modal WM. In a tactile-visual cross-modal WM task, SI and PPC contribute to the processing sequentially, suggesting a process of sensory information transfer during the early delay between modalities.

Stochastic Dynamics Underlying Cognitive Stability and Flexibility

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences.

In this work we develop a neurophysiologically inspired dynamical model that is capable of solving a complex behavioral task testing cognitive stability and flexibility. We can individually fit the behavior of each of 20 human subjects that conducted this stability-flexibility task during functional magnetic resonance imaging (fMRI). The physiological nature of our model allows us to estimate the energy consumption of the rule-representing module, which we use to predict the hemodynamic fMRI response. Through this model-based prediction, we localize the rule module to a frontoparietal network known to be required for cognitive stability and flexibility. In this way we both validate our model, which is based on noisy attractor dynamics, and specify the computational role of a cortical network that is well-established in human neuroimaging research. Additionally, we quantify the individual stability of the rule-representing states and relate this stability to individual differences in energy consumption during task switching versus distractor inhibition. Hereby we show that the activation of a thalamocorticostriatal network involved in the dopaminergic modulation of cognitive stability is modulated by the model-derived stability of the frontoparietal rule-representing network. Altogether, we show that noisy dynamic systems are likely to implement the basic computations underlying cognitive stability and flexibility.

As Working Memory Grows: A Developmental Account of Neural Bases of Working Memory Capacity in 5- to 8-Year Old Children and Adults

Working memory develops slowly: Even by age 8, children are able to maintain only half the number of items that adults can remember. Neural substrates that support performance on working memory tasks also have a slow developmental trajectory and typically activate to a lesser extent in children, relative to adults. Little is known about why younger participants elicit less neural activation. This may be due to maturational differences, differences in behavioral performance, or both. Here we investigate the neural correlates of working memory capacity in children (ages 5-8) and adults using a visual working memory task with parametrically increasing loads (from one to four items) using fMRI. This task allowed us to estimate working memory capacity limit for each group. We found that both age groups increased the activation of frontoparietal networks with increasing working memory loads, until working memory capacity was reached. Because children's working memory capacity limit was half of that for adults, the plateau occurred at lower loads for children. Had a parametric increase in load not been used, this would have given an impression of less activation overall and less load-dependent activation for children relative to adults. Our findings suggest that young children and adults recruit similar frontoparietal networks at working memory loads that do not exceed capacity and highlight the need to consider behavioral performance differences when interpreting developmental differences in neural activation.

Dopamine D2-receptor blockade enhances decoding of prefrontal signals in humans

The prefrontal cortex houses representations critical for ongoing and future behavior expressed in the form of patterns of neural activity. Dopamine has long been suggested to play a key role in the integrity of such representations, with D2-receptor activation rendering them flexible but weak. However, it is currently unknown whether and how D2-receptor activation affects prefrontal representations in humans. In the current study, we use dopamine receptor-specific pharmacology and multivoxel pattern-based functional magnetic resonance imaging to test the hypothesis that blocking D2-receptor activation enhances prefrontal representations. Human subjects performed a simple reward prediction task after double-blind and placebo controlled administration of the D2-receptor antagonist amisulpride. Using a whole-brain searchlight decoding approach we show that D2-receptor blockade enhances decoding of reward signals in the medial orbitofrontal cortex. Examination of activity patterns suggests that amisulpride increases the separation of activity patterns related to reward versus no reward. Moreover, consistent with the cortical distribution of D2 receptors, post hoc analyses showed enhanced decoding of motor signals in motor cortex, but not of visual signals in visual cortex. These results suggest that D2-receptor blockade enhances content-specific representations in frontal cortex, presumably by a dopamine-mediated increase in pattern separation. These findings are in line with a dual-state model of prefrontal dopamine, and provide new insights into the potential mechanism of action of dopaminergic drugs.

Auditory working memory predicts individual differences in absolute pitch learning

Absolute pitch (AP) is typically defined as the ability to label an isolated tone as a musical note in the absence of a reference tone. At first glance the acquisition of AP note categories seems like a perceptual learning task, since individuals must assign a category label to a stimulus based on a single perceptual dimension (pitch) while ignoring other perceptual dimensions (e.g., loudness, octave, instrument). AP, however, is rarely discussed in terms of domain-general perceptual learning mechanisms. This is because AP is typically assumed to depend on a critical period of development, in which early exposure to pitches and musical labels is thought to be necessary for the development of AP precluding the possibility of adult acquisition of AP. Despite this view of AP, several previous studies have found evidence that absolute pitch category learning is, to an extent, trainable in a post-critical period adult population, even if the performance typically achieved by this population is below the performance of a "true" AP possessor. The current studies attempt to understand the individual differences in learning to categorize notes using absolute pitch cues by testing a specific prediction regarding cognitive capacity related to categorization - to what extent does an individual's general auditory working memory capacity (WMC) predict the success of absolute pitch category acquisition. Since WMC has been shown to predict performance on a wide variety of other perceptual and category learning tasks, we predict that individuals with higher WMC should be better at learning absolute pitch note categories than individuals with lower WMC. Across two studies, we demonstrate that auditory WMC predicts the efficacy of learning absolute pitch note categories. These results suggest that a higher general auditory WMC might underlie the formation of absolute pitch categories for post-critical period adults. Implications for understanding the mechanisms that underlie the phenomenon of AP are also discussed.

Sensation-to-cognition cortical streams in attention-deficit/hyperactivity disorder

We sought to determine whether functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits are atypical in attention-deficit/hyperactivity disorder (ADHD). We applied a graph-theory method to the resting-state functional magnetic resonance imaging data of 120 children with ADHD and 120 age-matched typically developing children (TDC). Starting in unimodal primary cortex-visual, auditory, and somatosensory-we used stepwise functional connectivity to calculate functional connectivity paths at discrete numbers of relay stations (or link-step distances). First, we characterized the functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits in TDC and found that systems do not reach the level of integration achieved by adults. Second, we searched for stepwise functional connectivity differences between children with ADHD and TDC. We found that, at the initial steps of sensory functional connectivity streams, patients display significant enhancements of connectivity degree within neighboring areas of primary cortex, while connectivity to attention-regulatory areas is reduced. Third, at subsequent link-step distances from primary sensory cortex, children with ADHD show decreased connectivity to executive processing areas and increased degree of connections to default mode regions. Fourth, in examining medication histories in children with ADHD, we found that children medicated with psychostimulants present functional connectivity streams with higher degree of connectivity to regions subserving attentional and executive processes compared to medication-naïve children. We conclude that predominance of local sensory processing and lesser influx of information to attentional and executive regions may reduce the ability to organize and control the balance between external and internal sources of information in ADHD.

The subcortical cocktail problem; mixed signals from the subthalamic nucleus and substantia nigra

The subthalamic nucleus and the directly adjacent substantia nigra are small and important structures in the basal ganglia. Functional magnetic resonance imaging studies have shown that the subthalamic nucleus and substantia nigra are selectively involved in response inhibition, conflict processing, and adjusting global and selective response thresholds. However, imaging these nuclei is complex, because they are in such close proximity, they can vary in location, and are very small relative to the resolution of most fMRI sequences. Here, we investigated the consistency in localization of these nuclei in BOLD fMRI studies, comparing reported coordinates with probabilistic atlas maps of young human participants derived from ultra-high resolution 7T MRI scanning. We show that the fMRI signal reported in previous studies is likely not unequivocally arising from the subthalamic nucleus but represents a mixture of subthalamic nucleus, substantia nigra, and surrounding tissue. Using a simulation study, we also tested to what extent spatial smoothing, often used in fMRI preprocessing pipelines, influences the mixture of BOLD signals. We propose concrete steps how to analyze fMRI BOLD data to allow inferences about the functional role of small subcortical nuclei like the subthalamic nucleus and substantia nigra.

Multiple gates on working memory

The contexts for action may be only transiently visible, accessible, and relevant. The corticobasal ganglia (BG) circuit addresses these demands by allowing the right motor plans to drive action at the right times, via a BG-mediated gate on motor representations. A long-standing hypothesis posits these same circuits are replicated in more rostral brain regions to support gating of cognitive representations. Key evidence now supports the prediction that BG can act as a gate on the input to working memory, as a gate on its output, and as a means of reallocating working memory representations rendered irrelevant by recent events. These discoveries validate key tenets of many computational models, circumscribe motor and cognitive models of recurrent cortical dynamics alone, and identify novel directions for research on the mechanisms of higher-level cognition.

The Organization of Right Prefrontal Networks Reveals Common Mechanisms of Inhibitory Regulation Across Cognitive, Emotional, and Motor Processes

Inhibitory control/regulation is critical to adapt behavior in accordance with changing environmental circumstances. Dysfunctional inhibitory regulation is ubiquitous in neurological and psychiatric populations. These populations exhibit dysfunction across psychological domains, including memory/thought, emotion/affect, and motor response. Although investigation examining inhibitory regulation within a single domain has begun outlining the basic neural mechanisms supporting regulation, it is unknown how the neural mechanisms of these domains interact. To investigate the organization of inhibitory neural networks within and across domains, we used neuroimaging to outline the functional and anatomical pathways that comprise inhibitory neural networks regulating cognitive, emotional, and motor processes. Networks were defined at the group level using an array of analyses to indicate their intrinsic pathway structure, which was subsequently assessed to determine how the pathways explained individual differences in behavior. Results reveal how neural networks underlying inhibitory regulation are organized both within and across domains, and indicate overlapping/common neural elements.

Emotional task management: neural correlates of switching between affective and non-affective task-sets

Although task-switching has been investigated extensively, its interaction with emotionally salient task content remains unclear. Prioritized processing of affective stimulus content may enhance accessibility of affective task-sets and generate increased interference when switching between affective and non-affective task-sets. Previous research has demonstrated that more dominant task-sets experience greater switch costs, as they necessitate active inhibition during performance of less entrenched tasks. Extending this logic to the affective domain, the present experiment examined (a) whether affective task-sets are more dominant than non-affective ones, and (b) what neural mechanisms regulate affective task-sets, so that weaker, non-affective task-sets can be executed. While undergoing functional magnetic resonance imaging, participants categorized face stimuli according to either their gender (non-affective task) or their emotional expression (affective task). Behavioral results were consistent with the affective task dominance hypothesis: participants were slower to switch to the affective task, and cross-task interference was strongest when participants tried to switch from the affective to the non-affective task. These behavioral costs of controlling the affective task-set were mirrored in the activation of a right-lateralized frontostriatal network previously implicated in task-set updating and response inhibition. Connectivity between amygdala and right ventrolateral prefrontal cortex was especially pronounced during cross-task interference from affective features.

Delay Period Activity of the Substantia Nigra during Proactive Control of Response Selection as Determined by a Novel fMRI Localization Method

The ability to proactively control motor responses, particularly to overcome overlearned or automatic actions, is an essential prerequisite for adaptive, goal-oriented behavior. The substantia nigra (SN), an element of the BG, has figured prominently in current models of response selection. However, because of its small size and proximity to functionally distinct subcortical structures, it has been challenging to test the SN's involvement in response selection using conventional in vivo functional neuroimaging approaches. We developed a new fMRI localization method for directly distinguishing, on echo-planar images, the SN BOLD signal from that of neighboring structures, including the subthalamic nucleus (STN). Using this method, we tested the hypothesis that the SN supports the proactive control of response selection. We acquired high-resolution EPI volumes at 3 T from 16 healthy participants while they completed the Preparing to Overcome Prepotency task of proactive control. There was significantly elevated delay period signal selectively during high- compared with low-control trials in the SN. The STN did not show delay period activity in either condition. SN delay period signal was significantly inversely associated with task performance RTs across participants. These results suggest that our method offers a novel means for measuring SN BOLD responses, provides unique evidence of SN involvement in cognitive control in humans, and suggests a novel mechanism for proactive response selection.

Task-evoked substantia nigra hyperactivity associated with prefrontal hypofunction, prefrontonigral disconnectivity and nigrostriatal connectivity predicting psychosis severity in medication naïve first episode schizophrenia

The widely cited prefrontal dysfunction - excess subcortical dopamine model of schizophrenia posits that prefrontal deficits give rise to cognitive impairments and the disinhibition of subcortical dopamine release underlying psychosis. While this has been one of the most influential schizophrenia models, only a handful of studies have provided evidence supporting it directly in patients with schizophrenia. We previously demonstrated task-evoked substantia nigra hyperactivity in the context of prefrontal hypofunction and prefrontonigral functional disconnectivity. In addition, nigrostriatal functional connectivity was identified as a potential marker of psychosis. Because patients in this prior study had chronic schizophrenia and were treated with antipsychotics, in the present study we tested whether these findings were confounded by illness chronicity and medication effects by seeking to reproduce these findings in an independent sample of antipsychotic naïve, first episode (FE) patients. We compared event-related fMRI activations from 12 FE patients with 15 demographically matched healthy control subjects during cognitive testing. We found substantia nigra hyperactivity associated with prefrontal hypofunction and prefrontonigral functional disconnectivity, as well as the magnitude of nigrostriatal functional connectivity positively correlating with severity of psychosis. This study adds to the body of evidence supporting the prefrontal-dopamine model of schizophrenia and further validates nigrostriatal functional connectivity as a marker of psychosis.

A dual-systems perspective on addiction: contributions from neuroimaging and cognitive training

Dual-systems theories explain lapses in self-control in terms of a conflict between automatic and deliberative modes of behavioral control. Numerous studies have now tested whether the brain areas that control behavior are organized in a manner consistent with dual-systems models. Brain regions directly associated with the mesolimbic dopamine system, the nucleus accumbens and ventromedial prefrontal cortex in particular, capture some of the features assumed by automatic processing. Regions in the lateral prefrontal cortex are more closely linked to deliberative processing and the exertion of self-control in the suppression of impulses. While identifying these regions crudely supports dual-systems theories, important modifications to what constitutes automatic and deliberative behavioral control are also suggested. Experiments have identified various means by which automatic processes may be sculpted. Additional work decomposes deliberative processes into component functions such as generalized working memory, reappraisal of emotional stimuli, and prospection. The importance of deconstructing dual-systems models into specific cognitive processes is clear for understanding and treating addiction. We discuss intervention possibilities suggested by recent research, and focus in particular on cognitive training approaches to bolster deliberative control processes that may aid quit attempts.

Modifying cognition and behavior with electrical microstimulation: implications for cognitive prostheses

A fundamental goal of cognitive neuroscience is to understand how brain activity generates complex mental states and behaviors. While neuronal activity may predict or correlate with behavioral responses in a cognitive task, the use of electrical microstimulation presents the possibility to augment such correlational findings with direct evidence for causal relationships. Although microstimulation has been used for many years as a tool for mapping sensory and motor function, its role in learning, memory and decision-making has emerged only recently. Focal microstimulation of higher cortical areas can produce complex mental states and sequences of action. However, the relationship between the locus of stimulation and the percepts or actions evoked is often stereotyped and inflexible. The challenge is to develop stimulation systems that do not have fixed output but can flexibly contribute to complex cognitive and behavioral tasks. We discuss how microstimulation has been instrumental in manipulating a wide spectrum of cognitive functions including working memory, perceptual decisions and executive control by enhancing attention, re-ordering temporal sequence of saccades, improving associative learning or cognitive performance. For example, stimulation in prefrontal, parietal and sensory cortices may establish causal effects on decision-making, while microstimulation of inferotemporal cortex or caudate nucleus enhances associative learning. Building cognitive prosthetics based on the insights gleaned from such studies may depend on the development of multiple-input, multiple-output (MIMO) devices that allow subjects to control stimulation with their own thoughts in a closed-loop system.

Increased functional connectivity within mesocortical networks in open people

Openness is a personality trait reflecting absorption in sensory experience, preference for novelty, and creativity, and is thus considered a driving force of human evolution. At the brain level, a relation between openness and dopaminergic circuits has been proposed, although evidence to support this hypothesis is lacking. Recent behavioral research has also found that people with mania, a psychopathological condition linked to dopaminergic dysfunctions, may display high levels of openness. However, whether openness is related to dopaminergic circuits has not been determined thus far. We addressed this issue via three functional magnetic resonance imaging (fMRI) experiments in n=46 healthy volunteers. In the first experiment participants lied at rest in the scanner while in the other two experiments they performed active tasks that included the presentation of pleasant odors and pictures of food. Individual differences in openness and other personality traits were assessed via the NEO-PI-R questionnaire (NEO-Personality Inventory-Revised), a widely employed measure of the five-factor model personality traits. Correlation between fMRI and personality data was analyzed via state-of-art methods assessing resting-state and task-related functional connectivity within specific brain networks. Openness was positively associated with the functional connectivity between the right substantia nigra/ventral tegmental area, the major source of dopaminergic inputs in the brain, and the ipsilateral dorsolateral prefrontal cortex (DLPFC), a key region in encoding, maintaining, and updating information that is relevant for adaptive behaviors. Of note, the same connectivity pattern was consistently found across all of the three fMRI experiments. Given the critical role of dopaminergic signal in gating information in DLPFC, the increased functional connectivity within mesocortical networks in open people may explain why these individuals display a wide "mental permeability" to salient stimuli and an increased absorption in sensory experience.

A neural network model of individual differences in task switching abilities

We use a biologically grounded neural network model to investigate the brain mechanisms underlying individual differences specific to the selection and instantiation of representations that exert cognitive control in task switching. Existing computational models of task switching do not focus on individual differences and so cannot explain why task switching abilities are separable from other executive function (EF) abilities (such as response inhibition). We explore hypotheses regarding neural mechanisms underlying the "Shifting-Specific" and "Common EF" components of EF proposed in the Unity/Diversity model (Miyake & Friedman, 2012) and similar components in related theoretical frameworks. We do so by adapting a well-developed neural network model of working memory (Prefrontal cortex, Basal ganglia Working Memory or PBWM; Hazy, Frank, & O'Reilly, 2007) to task switching and the Stroop task, and comparing its behavior on those tasks under a variety of individual difference manipulations. Results are consistent with the hypotheses that variation specific to task switching (i.e., Shifting-Specific) may be related to uncontrolled, automatic persistence of goal representations, whereas variation general to multiple EFs (i.e., Common EF) may be related to the strength of PFC representations and their effect on processing in the remainder of the cognitive system. Moreover, increasing signal to noise ratio in PFC, theoretically tied to levels of tonic dopamine and a genetic polymorphism in the COMT gene, reduced Stroop interference but increased switch costs. This stability-flexibility tradeoff provides an explanation for why these two EF components sometimes show opposing correlations with other variables such as attention problems and self-restraint.

Dopamine modulation of learning and memory in the prefrontal cortex: insights from studies in primates, rodents, and birds

In this review, we provide a brief overview over the current knowledge about the role of dopamine transmission in the prefrontal cortex during learning and memory. We discuss work in humans, monkeys, rats, and birds in order to provide a basis for comparison across species that might help identify crucial features and constraints of the dopaminergic system in executive function. Computational models of dopamine function are introduced to provide a framework for such a comparison. We also provide a brief evolutionary perspective showing that the dopaminergic system is highly preserved across mammals. Even birds, following a largely independent evolution of higher cognitive abilities, have evolved a comparable dopaminergic system. Finally, we discuss the unique advantages and challenges of using different animal models for advancing our understanding of dopamine function in the healthy and diseased brain.

Cognitive disorders in pediatric medulloblastoma: what neuroimaging has to offer

Medulloblastomas are the most common malignant childhood brain tumors arising in the posterior fossa. Treatment improvements for these tumors have meant that there are a greater number of survivors, but this long-term patient survival has increased the awareness of resulting neurocognitive deficits. Impairments in attention, memory, executive functions, and intelligence quotient demonstrate that the cerebellum likely plays a significant role in numerous higher cognitive functions such as language, cognitive, and emotional functions. In addition, children with medulloblastoma not only have cerebellar lesions but also brain white matter damages due to radiation and chemotherapy. Functional neuroimaging, a noninvasive method with many advantages, has become the standard tool in clinical and cognitive neuroscience research. By reviewing functional neuroimaging studies, this review aims to clarify the role of the cerebellum in cognitive function and explain more clearly cognitive sequelae due to polytherapy in children with medulloblastoma. This review suggests that the posterior cerebellar lobes are crucial to maintaining cognitive performance. Clinical investigations could help to better assess the involvement of these lobes in cognitive functions.

Working memory updating and the development of rule-guided behavior

The transition from middle childhood into adolescence is marked by both increasing independence and also extensive change in the daily requirements of familial demands, social pressures, and academic achievement. To manage this increased complexity, children must develop the ability to use abstract rules that guide the choice of behavior across a range of circumstances. Here, we tested children through adults in a task that requires increasing levels of rule abstraction, while separately manipulating competition among alternatives in working memory. We found that age-related differences in rule-guided behavior can be explained in terms of improvement in rule abstraction, which we suggest involves a working memory updating mechanism. Furthermore, family socioeconomic status (SES) predicted change in rule-guided behavior, such that higher SES predicted better performance with development. We discuss these results within a working memory gating framework for abstract rule-guided behavior.