The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain's low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

Flexible behavior requires gating mechanisms that encode only task-relevant information in working memory. Extant literature supports a theoretical division of labor whereby lateral frontoparietal interactions underlie information maintenance and the striatum enacts the gate. Here, we reveal neocortical gating mechanisms in intracranial EEG patients by identifying rapid, within-trial changes in regional and inter-regional activities that predict subsequent behavioral outputs. Results first demonstrate information accumulation mechanisms that extend prior fMRI (i.e., regional high-frequency activity) and EEG evidence (inter-regional theta synchrony) of distributed neocortical networks in working memory. Second, results demonstrate that rapid changes in theta synchrony, reflected in changing patterns of default mode network connectivity, support filtering. Graph theoretical analyses further linked filtering in task-relevant information and filtering out irrelevant information to dorsal and ventral attention networks, respectively. Results establish a rapid neocortical theta network mechanism for flexible information encoding, a role previously attributed to the striatum.

Working memory (WM) is the ability to retain and manipulate information in mind, which allows mnemonic representations to flexibly guide behavior. Successful WM requires that objects' individual features are bound into cohesive representations, however the mechanisms supporting feature binding remain unclear. Binding errors (or swaps) provide a window into the intrinsic limits in capacity of WM. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and swaps result from its perturbations. Using magnetoencephalography data collected from human subjects, in a task designed to induce swaps, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention. We found that this reduction arises from increased phase-coding variability in the alpha-band, over a distributed network of sensorimotor areas. Our findings support the notion that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.

Transcranial Magnetic Stimulation (TMS) is an important tool for testing causal relationships in cognitive neuroscience research. However, the efficacy of TMS can be variable across individuals and difficult to measure. This variability is especially a challenge when TMS is applied to regions without well-characterized behavioral effects, such as in studies using TMS on multi-modal areas in intrinsic networks. Here, we examined whether perfusion fMRI recordings of Cerebral Blood Flow (CBF), a quantitative measure sensitive to slow functional changes, reliably index variability in the effects of stimulation. Twenty-seven participants each completed four combined TMS-fMRI sessions during which both resting state Blood Oxygen Level Dependent (BOLD) and perfusion Arterial Spin Labeling (ASL) scans were recorded. In each session after the first baseline day, continuous theta-burst TMS (TBS) was applied to one of three locations: left dorsolateral prefrontal cortex (L dlPFC), left anterior insula/frontal operculum (L aI/fO), or left primary somatosensory cortex (L S1). The two frontal targets are components of intrinsic networks and L S1 was used as an experimental control. CBF changes were measured both before and after TMS on each day from a series of interleaved resting state and perfusion scans. Although TBS led to weak selective increases under the coil in CBF measurements across the group, individual subjects showed wide variability in their responses. TBS-induced changes in rCBF were related to TBS-induced changes in functional connectivity of the relevant intrinsic networks measured during separate resting-state BOLD scans. This relationship was selective: CBF and functional connectivity of these networks were not related before TBS or after TBS to the experimental control region (S1). Furthermore, subject groups with different directions of CBF change after TBS showed distinct modulations in the functional interactions of targeted networks. These results suggest that CBF is a marker of individual differences in the effects of TBS.

Higher-level cognition depends on the lateral prefrontal cortex (LPFC), but its functional organization has remained elusive. An influential proposal is that the LPFC is organized hierarchically whereby progressively rostral areas of the LPFC process/represent increasingly abstract information facilitating efficient and flexible cognition. However, support for this theory has been limited. Here, human fMRI data revealed rostral/caudal gradients of abstraction in the LPFC. Dynamic causal modeling revealed asymmetrical LPFC interactions indicative of hierarchical processing. Contrary to dominant assumptions, the relative strength of efferent versus afferent connections positioned mid LPFC as the apex of the hierarchy. Furthermore, cognitive demands induced connectivity modulations towards mid LPFC consistent with a role in integrating information for control operations. Moreover, the strengths of these dynamics were related to trait-measured higher-level cognitive ability. Collectively, these results suggest that the LPFC is hierarchically organized with the mid LPFC positioned to synthesize abstract and concrete information to control behavior.

We present a novel method to measure relative latencies between functionally connected regions using phase-delay of functional magnetic resonance imaging data. Derived from the phase component of coherency, this quantity estimates the linear delay between two time-series. In conjunction with coherence, derived from the magnitude component of coherency, phase-delay can be used to examine the temporal properties of functional networks. In this paper, we apply coherence and phase-delay methods to fMRI data in order to investigate dynamics of the motor network during task and rest periods. Using the supplementary motor area (SMA) as a reference region, we calculated relative latencies between the SMA and other regions within the motor network including the dorsal premotor cortex (PMd), primary motor cortex (M1), and posterior parietal cortex (PPC). During both the task and rest periods, we measured significant delays that were consistent across subjects. Specifically, we found significant delays between the SMA and the bilateral PMd, bilateral M1, and bilateral PPC during the task condition. During the rest condition, we found that the temporal dynamics of the network changed relative to the task period. No significant delays were measured between the SMA and the left PM and left M1; however, the right PM, right M1, and bilateral PPC were significantly delayed with respect to the SMA. Additionally, we observed significant map-wise differences in the dynamics of the network at task compared to the network at rest. These differences were observed in the interaction between the SMA and the left M1, left superior frontal gyrus, and left middle frontal gyrus. These temporal measurements are important in determining how regions within a network interact and provide valuable information about the sequence of cognitive processes within a network.

Recent functional imaging studies of working memory (WM) have suggested a relationship between the requirement for response selection and activity in dorsolateral prefrontal (DLPFC) and parietal regions. Although a number of WM operations are likely to occur during response selection, the current study was particularly interested in the contribution of this neural network to WM-based response selection when compared to the selection of an item from a list being maintained in memory, during a verbal learning task. The design manipulated stimulus-response mappings so that selecting an item from memory was not always accompanied with selecting a motor response. Functional activation during selection supported previous findings of fronto-parietal involvement, although in contrast to previous findings left, rather than right, DLPFC activity was significantly more active for selecting a memory-guided motor response, when compared to selecting an item currently maintained in memory or executing a memory-guided response. Our results contribute to the debate over the role of fronto-parietal activity during WM tasks, suggesting that this activity appears particularly related to response selection, potentially supporting the hypothesized role of prefrontal activity in biasing attention toward task-relevant material in more posterior regions.

Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults (N = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, especially in low-performing individuals, global network properties can capture individual differences in neuroplasticity.

Recent experiments have shown that visual cognition blends current input with that from the recent past to guide ongoing decision making. This serial dependence appears to exploit the temporal autocorrelation normally present in visual scenes to promote perceptual stability. While this benefit has been assumed, evidence that serial dependence directly alters stimulus perception has been limited. In the present study, we parametrically vary the delay between stimulus and response in a spatial delayed response task to explore the trajectory of serial dependence from the moment of perception into post-perceptual visual working memory. We find that behavioral responses made immediately after viewing a stimulus show evidence of adaptation, but not attractive serial dependence. Only as the memory period lengthens is a blending of past and present information apparent in behavior, reaching its maximum with a delay of six seconds. These results dovetail with other recent findings to bolster the interpretation that serial dependence is a phenomenon of mnemonic rather than perceptual processes. However, even while this pattern of effects in group-averaged data has now been found consistently, we show that the relative strengths of adaptation and serial dependence vary widely across individuals. Finally, we demonstrate that when leading mathematical models of working memory are adjusted to account for these trial-history effects, their fit to behavioral data is substantially improved.

Serial dependence is an attractive pull that recent perceptual history exerts on current judgments. Theory suggests that this bias is due to a form of short-term plasticity prevalent specifically in the frontal lobe. We sought to test the importance of the frontal lobe to serial dependence by disrupting neural activity along its lateral surface during two tasks with distinct perceptual and motor demands. In our first experiment, stimulation of the lateral prefrontal cortex (LPFC) during an oculomotor delayed response task decreased serial dependence only in the first saccade to the target, whereas stimulation posterior to the LPFC decreased serial dependence only in adjustments to eye position after the first saccade. In our second experiment, which used an orientation discrimination task, stimulation anterior to, in, and posterior to the LPFC all caused equivalent decreases in serial dependence. In this experiment, serial dependence occurred only between stimuli at the same location; an alternation bias was observed across hemifields. Frontal stimulation had no effect on the alternation bias. Transcranial magnetic stimulation to parietal cortex had no effect on serial dependence in either experiment. In summary, our experiments provide evidence for both functional differentiation (Experiment 1) and redundancy (Experiment 2) in frontal cortex with respect to serial dependence.

Cognitive training interventions are a promising approach to mitigate cognitive deficits common in aging and, ultimately, to improve functioning in older adults. Baseline neural factors, such as properties of brain networks, may predict training outcomes and can be used to improve the effectiveness of interventions. Here, we investigated the relationship between baseline brain network modularity, a measure of the segregation of brain sub-networks, and training-related gains in cognition in older adults. We found that older adults with more segregated brain sub-networks (i.e., more modular networks) at baseline exhibited greater training improvements in the ability to synthesize complex information. Further, the relationship between modularity and training-related gains was more pronounced in sub-networks mediating "associative" functions compared with those involved in sensory-motor processing. These results suggest that assessments of brain networks can be used as a biomarker to guide the implementation of cognitive interventions and improve outcomes across individuals. More broadly, these findings also suggest that properties of brain networks may capture individual differences in learning and neuroplasticity. Trail Registration: ClinicalTrials.gov, NCT#00977418.

Humans have a capacity for hierarchical cognitive control-the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4-8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80-150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.

To date, few studies have explored the neurochemical mechanisms supporting individual differences in food preference in humans. Here we investigate how dorsal striatal dopamine, as measured by the positron emission tomography (PET) tracer [(18)F]fluorometatyrosine (FMT), correlates with food-related decision-making, as well as body mass index (BMI) in 16 healthy-weight to moderately obese individuals. We find that lower PET FMT dopamine synthesis binding potential correlates with higher BMI, greater preference for perceived "healthy" foods, but also greater healthiness ratings for food items. These findings further substantiate the role of dorsal striatal dopamine in food-related behaviors and shed light on the complexity of individual differences in food preference.

Regions in the medial temporal lobes (MTL) have long been implicated in the formation of new memories for events, however, it is unclear whether different MTL subregions support different memory processes. Here, we used event-related functional magnetic resonance imaging (fMRI) to examine the degree to which two recognition memory processes-recollection and familiarity-were supported by different MTL subregions. Results showed that encoding activity in the rhinal cortex selectively predicted familiarity-based recognition, whereas, activity in the hippocampus and posterior parahippocampal cortex selectively predicted recollection. Collectively, these results support the view that different subregions within the MTL memory system implement unique encoding processes that differentially support familiarity and recollection.

Current models of executive function hold that the internal representations of stimuli used during reflective thought are maintained in the same posterior cortical regions initially activated during perception, and that activity in such regions is modulated by top-down signals originating in prefrontal cortex. In an event-related functional magnetic resonance imaging study, we presented participants with two pictures simultaneously, a face and a scene, immediately followed either by a repetition of one of the pictures (perception) or by a cue to think briefly of one of the just-seen, but no longer present, pictures (refreshing, a reflective act). Refreshing faces and scenes modulated activity in the fusiform face area (FFA) and parahippocampal place area (PPA), respectively, as well as other regions exhibiting relative perceptual selectivity for either faces or scenes. Four scene-selective regions (lateral precuneus, retrosplenial cortex, PPA, and middle occipital gyrus) showed an anatomical gradient of responsiveness to top-down reflective influences versus bottom-up perceptual influences. These results demonstrate that a brief reflective act can modulate posterior cortical activity in a stimulus-specific manner, suggesting that such modulatory mechanisms are engaged even during transient ongoing thought. Our findings are consistent with the hypothesis that refreshing is a component of more complex modulatory operations such as working memory and mental imagery, and that refresh-related activity may thus contribute to the common activation patterns seen across different cognitive tasks.

Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local and long-distance neuronal communication. Current techniques for calculating PAC provide a numerical index that represents an average value across an arbitrarily long time period. This requires researchers to rely on block design experiments and temporal concatenation at the cost of the sub-second temporal resolution afforded by electrophysiological recordings. Here we present a method for calculating event-related phase/amplitude coupling (ERPAC) designed to capture the temporal evolution of task-related changes in PAC across events or between distant brain regions that is applicable to human or animal electromagnetic recording.

We investigated the effect of bromocriptine, a dopamine agonist, on individual differences in behavior as well as frontal-striatal connectivity during a working memory task. After dopaminergic augmentation, frontal-striatal connectivity in low working memory capacity individuals increases, corresponding with behavioral improvement whereas decreases in connectivity in high working memory capacity individuals are associated with poorer behavioral performance. These findings corroborate an inverted U-shape response of dopamine function in behavioral performance and provide insight on the corresponding neural mechanisms.

Does tuning to one's native language explain the "sensitive period" for language learning? We explore the idea that tuning to (or becoming more selective for) the properties of one's native-language could result in being less open (or plastic) for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure) has an impact on the neural representation of a later-learned aspect (grammar). English-speaking adults learned one of two miniature artificial languages (MALs) over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG) to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG). Across learners, recruitment of IFG (but not STG) predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults' difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language.

IT HAS BEEN PROPOSED THAT TWO RELATIVELY INDEPENDENT COGNITIVE CONTROL NETWORKS EXIST IN THE BRAIN: the cingulo-opercular network (CO) and the fronto-parietal network (FP). Past work has shown that chronic brain lesions affect these networks independently. It remains unclear, however, how these two networks are affected by acute brain disruptions. To examine this, we conducted a within-subject theta-burst transcranial magnetic stimulation (TBS) experiment in healthy individuals that targeted left anterior insula/frontal operculum (L aI/fO, a region in the CO network), left dorsolateral prefrontal cortex (L dlPFC, a region in the FP network), or left primary somatosensory cortex (L S1, an experimental control region). Functional connectivity (FC) was measured in resting state fMRI scans collected before and after continuous TBS on each day. We found that TBS was accompanied by generalized increases in network connectivity, especially FP network connectivity, after TBS to either region involved in cognitive control. Whole-brain analyses demonstrated that the L dlPFC and L aI/fO showed increased connectivity with regions in frontal, parietal, and cingulate cortex after TBS to either L dlPFC or L aI/fO, but not to L S1. These results suggest that acute disruption by TBS to cognitive control regions causes widespread changes in network connectivity not limited to the targeted networks.

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should therefore be a key component of the biologist's toolkit. But, classic chaos-detection tools are highly sensitive to measurement noise and break down for common edge cases, making it difficult to detect chaos in domains, like biology, where measurements are noisy. However, newer tools promise to overcome these limitations. Here, we combine several such tools into an automated processing pipeline, and show that our pipeline can detect the presence (or absence) of chaos in noisy recordings, even for difficult edge cases. As a first-pass application of our pipeline, we show that heart rate variability is not chaotic as some have proposed, and instead reflects a stochastic process in both health and disease. Our tool is easy-to-use and freely available.