The dorsolateral prefrontal cortex (DLPFC) and the frontal eye fields (FEF) have both been implicated in the executive control of saccades, yet possible dissociable roles of each region have not been established. Specifically, both establishing a "task set" as well as suppressing an inappropriate response have been linked to DLPFC and FEF activity, with behavioral outcome measures of these mechanisms mainly being the percentage of pro-saccade errors made on anti-saccade trials. We used continuous theta-burst stimulation (cTBS) to disrupt FEF or DLPFC function in humans during an anti-saccade task to assess the causal role of these regions in these executive control processes, and in programming saccades towards (pro-saccade) or away (anti-saccade) from visual targets. After right FEF cTBS, as compared to control cTBS to the right primary somatosensory cortex (rS1), anti-saccade amplitude of the first saccade decreased and the number of anti-saccades to acquire final position increased; however direction errors to the visual target were not different. In contrast, after left DLPFC cTBS, as compared to left S1 cTBS, subjects displayed greater direction errors for contralateral anti-saccades; however, there were no impairments on the number of saccades or the saccade amplitude. These results are consistent with the notion that DLPFC is necessary for executive control of saccades, whereas FEF is necessary for visuo-motor aspects of anti-saccade programming.

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70-150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58%; p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.

Insidious declines in normal aging are well-established. Emerging evidence suggests that non-pharmacological interventions, specifically cognitive and physical training, may counter diminishing age-related cognitive and brain functions. This randomized trial compared effects of two training protocols: cognitive training (CT) vs. physical training (PT) on cognition and brain function in adults 56-75 years. Sedentary participants (N = 36) were randomized to either CT or PT group for 3 h/week over 12 weeks. They were assessed at baseline-, mid-, and post-training using neurocognitive, MRI, and physiological measures. The CT group improved on executive function whereas PT group's memory was enhanced. Uniquely deploying cerebral blood flow (CBF) and cerebral vascular reactivity (CVR) MRI, the CT cohort showed increased CBF within the prefrontal and middle/posterior cingulate cortex (PCC) without change to CVR compared to PT group. Improvements in complex abstraction were positively associated with increased resting CBF in dorsal anterior cingulate cortex (dACC). Exercisers with higher CBF in hippocampi bilaterally showed better immediate memory. The preliminary evidence indicates that increased cognitive and physical activity improves brain health in distinct ways. Reasoning training enhanced frontal networks shown to be integral to top-down cognitive control and brain resilience. Evidence of increased resting CBF without changes to CVR implicates increased neural health rather than improved vascular response. Exercise did not improve cerebrovascular response, although CBF increased in hippocampi of those with memory gains. Distinct benefits incentivize testing effectiveness of combined protocols to strengthen brain health.

Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We examined vascular risk factors with respect to a cerebrovascular measure of brain functioning in subjects in mid-life, which could represent a marker of brain changes in later life. Breath-hold functional MRI (fMRI) was performed in 541 women and men (mean age 50.4 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Cerebrovascular reactivity (CVR) was quantified as percentage change in blood-oxygen level dependent (BOLD) signal in activated voxels, which was mapped to a common brain template and log-transformed. Mean CVR was calculated for anatomic regions underlying the default-mode network (DMN) - a network implicated in AD and other brain disorders - in addition to areas considered to be relatively spared in the disease (e.g. occipital lobe), which were utilized as reference regions. Mean CVR was significantly reduced in the posterior cingulate/precuneus (β=-0.063, 95% CI: -0.106, -0.020), anterior cingulate (β=-0.055, 95% CI: -0.101, -0.010), and medial frontal lobe (β=-0.050, 95% CI: -0.092, -0.008) relative to mean CVR in the occipital lobe, after adjustment for age, sex, race, education, and smoking status, in subjects with pre-hypertension/hypertension compared to normotensive subjects. By contrast, mean CVR was lower, but not significantly, in the inferior parietal lobe (β=-0.024, 95% CI: -0.062, 0.014) and the hippocampus (β=-0.006, 95% CI: -0.062, 0.050) relative to mean CVR in the occipital lobe. Similar results were observed in subjects with diabetes and dyslipidemia compared to those without these conditions, though the differences were non-significant. Reduced CVR may represent diminished vascular functionality for the DMN for individuals with prehypertension/hypertension in mid-life, and may serve as a preclinical marker for brain dysfunction in later life.

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson's Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, questioning such role. We hypothesized that this inconsistency is due to the influence of electrophysiological broadband activity -a neurophysiological indicator of synaptic excitation/inhibition ratio- that could confound measurements of beta activity in STN recordings. Here we propose a data-driven, automatic and individualized mathematical model that disentangles beta activity and 1/f broadband activity in the STN power spectrum, and investigate the link between these individual components and motor symptoms in thirteen Parkinsonian patients. We show, using both modeled and actual data, how beta oscillatory activity significantly correlates with motor symptoms (bradykinesia and rigidity) only when broadband activity is not considered in the biomarker estimations, providing solid evidence that oscillatory beta activity does correlate with motor symptoms in untreated PD states as well as the significant impact of broadband activity. These findings emphasize the importance of data-driven models and the identification of better biomarkers for characterizing symptom severity and closed-loop applications.

How does the human brain rapidly process incoming information in working memory? In growing divergence from a single-region focus on the prefrontal cortex (PFC), recent work argues for emphasis on how distributed neural networks are rapidly coordinated in support of this central neurocognitive function. Previously, we showed that working memory for everyday "what," "where," and "when" associations depends on multiplexed oscillatory systems, in which signals of different frequencies simultaneously link the PFC to parieto-occipital and medial temporal regions, pointing to a complex web of sub-second, bidirectional interactions. Here, we used direct brain recordings to delineate the frontoparietal oscillatory correlates of working memory with high spatiotemporal precision. Seven intracranial patients with electrodes simultaneously localized to prefrontal and parietal cortices performed a visuospatial working memory task that operationalizes the types of identity and spatiotemporal information we encounter every day. First, task-induced oscillations in the same delta-theta (2-7 Hz) and alpha-beta (9-24 Hz) frequency ranges previously identified using scalp electroencephalography (EEG) carried information about the contents of working memory. Second, maintenance was linked to directional connectivity from the parietal cortex to the PFC. However, presentation of the test prompt to cue identity, spatial, or temporal information changed delta-theta coordination from a unidirectional, parietal-led system to a bidirectional, frontoparietal system. Third, the processing of spatiotemporal information was more bidirectional in the delta-theta range than was the processing of identity information, where alpha-beta connectivity did not exhibit sensitivity to the contents of working memory. These findings implicate a bidirectional delta-theta mechanism for frontoparietal control over the contents of working memory.

Rapid, flexible reconfiguration of connections across brain regions is thought to underlie successful cognitive control. Two intrinsic networks in particular, the cingulo-opercular (CO) and fronto-parietal (FP), are thought to underlie two operations critical for cognitive control: task-set maintenance/tonic alertness and adaptive, trial-by-trial updating. Using functional magnetic resonance imaging, we directly tested whether the functional connectivity of the CO and FP networks was related to cognitive demands and behavior. We focused on working memory because of evidence that during working memory tasks the entire brain becomes more integrated. When specifically probing the CO and FP cognitive control networks, we found that individual regions of both intrinsic networks were active during working memory and, as expected, integration across the two networks increased during task blocks that required cognitive control. Crucially, increased integration between each of the cognitive control networks and a task-related, non-cognitive control network (the hand somatosensory-motor network; SM) was related to increased accuracy. This implies that dynamic reconfiguration of the CO and FP networks so as to increase their inter-network communication underlies successful working memory.

A critical feature of the human brain that gives rise to complex cognition is its ability to reconfigure its network structure dynamically and adaptively in response to the environment. Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during the performance of a variety of cognitive tasks, there are meaningful differences as well. In this study, we related intrinsic, resting state network organization to reconfigured network organization during the performance of two tasks: a sequence tapping task, which is thought to probe motor execution and likely engages a single brain network, and an n-back task, which is thought to probe working memory and likely requires coordination across multiple networks. We implemented graph theoretical analyses using functional connectivity data from fMRI scans to calculate whole-brain measures of network organization in healthy young adults. We focused on quantifying measures of network segregation (modularity, system segregation, local efficiency, number of provincial hub nodes) and measures of network integration (global efficiency, number of connector hub nodes). Using these measures, we found converging evidence that local, within-network communication is critical for motor execution, whereas integrative, between-network communication is critical for working memory. These results confirm that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition.

Cross-frequency coupling (CFC) between slow and fast brain rhythms, in the form of phase-amplitude coupling (PAC), is proposed to enable the coordination of neural oscillatory activity required for cognitive processing. PAC has been identified in the neocortex and mesial temporal regions, varying according to the cognitive task being performed and also at rest. PAC has also been observed in the anterior thalamic nucleus (ATN) during memory processing. The thalamus is active during the resting state and has been proposed to be involved in switching between task-free cognitive states such as rest, in which attention is internally-focused, and externally-focused cognitive states, in which an individual engages with environmental stimuli. It is unknown whether PAC is an ongoing phenomenon during the resting state in the ATN, which is modulated during different cognitive states, or whether it only arises during the performance of specific tasks. We analyzed electrophysiological recordings of ATN activity during rest from seven patients who received thalamic electrodes implanted for treatment of pharmacoresistant focal epilepsy. PAC was identified between theta (4-6 Hz) phase and high frequency band (80-150 Hz) amplitude during rest in all seven patients, which diminished during engagement in tasks involving an external focus of attention. The findings are consistent with the proposal that theta-gamma coupling in the ATN is an ongoing phenomenon, which is modulated by task performance.

For decades, oscillatory brain activity has been characterized primarily by measurements of power and phase. While many studies have linked those measurements to cortical excitability, their relationship to each other and to the physiological underpinnings of excitability is unclear. The recently proposed Function-through-Biased-Oscillations (FBO) hypothesis (Schalk, 2015) addressed these issues by suggesting that the voltage potential at the cortical surface directly reflects the excitability of cortical populations, that this voltage is rhythmically driven away from a low resting potential (associated with depolarized cortical populations) towards positivity (associated with hyperpolarized cortical populations). This view explains how oscillatory power and phase together influence the instantaneous voltage potential that directly regulates cortical excitability. This implies that the alternative measurement of instantaneous voltage of oscillatory activity should better predict cortical excitability compared to either of the more traditional measurements of power or phase. Using electrocorticographic (ECoG) data from 28 human subjects, the results of our study confirm this prediction: compared to oscillatory power and phase, the instantaneous voltage explained 20% and 31% more of the variance in broadband gamma, respectively, and power and phase together did not produce better predictions than the instantaneous voltage. These results synthesize the previously separate power- and phase-based interpretations and associate oscillatory activity directly with a physiological interpretation of cortical excitability. This alternative view has implications for the interpretation of studies of oscillatory activity and for current theories of cortical information transmission.

Positron Emission Tomography (PET) imaging allows the estimation of multiple aspects of dopamine function including dopamine synthesis capacity, dopamine release, and D2/3 receptor binding. Though dopaminergic dysregulation characterizes a number of neuropsychiatric disorders including schizophrenia and addiction, there has been relatively little investigation into the nature of relationships across dopamine markers within healthy individuals. Here we used PET imaging in 40 healthy adults to compare, within individuals, the estimates of dopamine synthesis capacity (Ki) using 6-[18F]fluoro-l-m-tyrosine ([18F]FMT; a substrate for aromatic amino acid decarboxylase), baseline D2/3 receptor-binding potential using [11C]raclopride (a weak competitive D2/3 receptor antagonist), and dopamine release using [11C]raclopride paired with oral methylphenidate administration. Methylphenidate increases synaptic dopamine by blocking the dopamine transporter. We estimated dopamine release by contrasting baseline D2/3 receptor binding and D2/3 receptor binding following methylphenidate. Analysis of relationships among the three measurements within striatal regions of interest revealed a positive correlation between [18F]FMT Ki and the baseline (placebo) [11C]raclopride measure, such that participants with greater synthesis capacity showed higher D2/3 receptor-binding potential. In contrast, there was no relationship between [18F]FMT and methylphenidate-induced [11C]raclopride displacement. These findings shed light on the nature of regulation between pre- and postsynaptic dopamine function in healthy adults, which may serve as a template from which to identify and describe alteration with disease.

Conduction aphasia is a language disorder characterized by frequent speech errors, impaired verbatim repetition, a deficit in phonological short-term memory, and naming difficulties in the presence of otherwise fluent and grammatical speech output. While traditional models of conduction aphasia have typically implicated white matter pathways, recent advances in lesions reconstruction methodology applied to groups of patients have implicated left temporoparietal zones. Parallel work using functional magnetic resonance imaging (fMRI) has pinpointed a region in the posterior most portion of the left planum temporale, area Spt, which is critical for phonological working memory. Here we show that the region of maximal lesion overlap in a sample of 14 patients with conduction aphasia perfectly circumscribes area Spt, as defined in an aggregate fMRI analysis of 105 subjects performing a phonological working memory task. We provide a review of the evidence supporting the idea that Spt is an interface site for the integration of sensory and vocal tract-related motor representations of complex sound sequences, such as speech and music and show how the symptoms of conduction aphasia can be explained by damage to this system.

The prefrontal cortex (PFC) plays a central role in preparatory and anticipatory attentional processes. To investigate whether subregions of the PFC play differential roles in these processes we investigated the effect of focal lesions to either lateral prefrontal (lateral PFC; n=11) or orbitofrontal cortex (OFC; n=13) on the contingent negative variation (CNV), an electrophysiological index of preparatory brain processes. The CNV was studied using a Go/NoGo delayed response task where an auditory S1 signaled whether or not an upcoming visual S2 was a Go or a NoGo stimulus. Neither early (500-1000 ms) nor late (3200-3700 ms) phase Go trial CNV amplitude was reduced for any of the patient groups in comparison to controls. However, the lateral PFC group showed enhanced Go trial early CNV and reduced late CNV Go/NoGo differentiation. These data suggests that normal orienting and evaluation as reflected by the CNV is intact after OFC lesions. The enhanced early CNV after lateral PFC damage may be due to failure in inhibition and the reduced late CNV difference wave confirms a deficit in preparatory attention after damage to this frontal subregion.

The prefrontal cortex (PFC) develops from birth through late adolescence. This extended developmental trajectory provides many opportunities for experience to shape the structure and function of the PFC. To date, a few studies have reported links between parental socioeconomic status (SES) and prefrontal function in childhood, raising the possibility that aspects of environment associated with SES impact prefrontal function. Considering that behavioral measures of prefrontal function are associated with learning across multiple domains, this is an important area of investigation. In this study, we used fMRI to replicate previous findings, demonstrating an association between parental SES and PFC function during childhood. In addition, we present two hypothetical mechanisms by which SES could come to affect PFC function of this association: language environment and stress reactivity. We measured language use in the home environment and change in salivary cortisol before and after fMRI scanning. Complexity of family language, but not the child's own language use, was associated with both parental SES and PFC activation. Change in salivary cortisol was also associated with both SES and PFC activation. These observed associations emphasize the importance of both enrichment and adversity-reduction interventions in creating good developmental environments for all children.

The inherently multivariate nature of functional brain imaging data affords the unique opportunity to explore how anatomically disparate brain areas interact during cognitive tasks. We introduce a new method for characterizing inter-regional interactions using event-related functional magnetic resonance imaging (fMRI) data. This method's principle advantage over existing analytical techniques is its ability to model the functional connectivity between brain regions during distinct stages of a cognitive task. The method is implemented by using separate covariates to model the activity evoked during each stage of each individual trial in the context of the general linear model (GLM). The resulting parameter estimates (beta values) are sorted according to the stage from which they were derived to form a set of stage-specific beta series. Regions whose beta series are correlated during a given stage are inferred to be functionally interacting during that stage. To validate the assumption that correlated fluctuations in trial-to-trial beta values imply functional connectivity, we applied the method to an event-related fMRI data set in which subjects performed two sequence-tapping tasks. In concordance with previous electrophysiological and fMRI coherence studies, we found that the task requiring greater bimanual coordination induced stronger correlations between motor regions of the two hemispheres. The method was then applied to an event-related fMRI data set in which subjects performed a delayed recognition task. Distinct functional connectivity maps were generated during the component stages of this task, illustrating how important and novel observations of neural networks within the isolated stages of a cognitive task can be obtained.

Although we often encounter circumstances with which we have no prior experience, we rapidly learn how to behave in these novel situations. Such adaptive behavior relies on abstract behavioral rules that are generalizable, rather than concrete rules mapping specific cues to specific responses. Although the frontal cortex is known to support concrete rule learning, less well understood are the neural mechanisms supporting the acquisition of abstract rules. Here, we use a reinforcement learning paradigm to demonstrate that more anterior regions along the rostro-caudal axis of frontal cortex support rule learning at higher levels of abstraction. Moreover, these results indicate that when humans confront new rule learning problems, this rostro-caudal division of labor supports the search for relationships between context and action at multiple levels of abstraction simultaneously.

Neuroimaging studies have reported increased prefrontal cortex (PFC) activity during temporal context retrieval versus recognition memory. However, it remains unclear if these activations reflect PFC contributions to domain-general executive control processes or domain-specific retrieval processes. To gain a better understanding of the functional roles of these various PFC regions during temporal context retrieval we propose it is necessary to examine PFC activity across tasks from different domains, in which parallel manipulations are included targeting specific cognitive processes. In the current fMRI study, we examined domain-general and domain-specific PFC contributions to temporal context retrieval by increasing stimulus (but maintaining response number) and increasing response number (but maintaining stimulus number) across temporal context memory and ordering control tasks, for faces. The control task required subjects to order faces from youngest to oldest. Our behavioral results indicate that the combination of increased stimulus and response numbers significantly increased task difficulty for temporal context retrieval and ordering tasks. Across domains, increasing stimulus number, while maintaining response numbers, caused greater right lateral premotor cortex (BA 6/8) activity; whereas increasing response number, while maintaining stimulus number, caused greater domain-general left DLPFC (BA 9) and VLPFC (BA 44/45) activity. In addition, we found domain-specific right DLPFC (BA 9) activity only during retrieval events. These results highlight the functional heterogeneity of frontal cortex, and suggest its involvement in temporal context retrieval is related to its role in various cognitive control processes.

Intracranial electroencephalography (iEEG) is clinically indicated for medically refractory epilepsy and is a promising approach for developing neural prosthetics. These recordings also provide valuable data for cognitive neuroscience research. Accurate localization of iEEG electrodes is essential for evaluating specific brain regions underlying the electrodes that indicate normal or pathological activity, as well as for relating research findings to neuroimaging and lesion studies. However, electrodes are frequently tucked underneath the edge of a craniotomy, inserted via a burr hole, or placed deep within the brain, where their locations cannot be verified visually or with neuronavigational systems. We show that one existing method, registration of postimplant computed tomography (CT) with preoperative magnetic resonance imaging (MRI), can result in errors exceeding 1cm. We present a novel method for localizing iEEG electrodes using routinely acquired surgical photographs, X-ray radiographs, and magnetic resonance imaging scans. Known control points are used to compute projective transforms that link the different image sets, ultimately allowing hidden electrodes to be localized, in addition to refining the location of manually registered visible electrodes. As the technique does not require any calibration between the different image modalities, it can be applied to existing image databases. The final result is a set of electrode positions on the patient's rendered MRI yielding locations relative to sulcal and gyral landmarks on individual anatomy, as well as MNI coordinates. We demonstrate the results of our method in eight epilepsy patients implanted with electrode grids spanning the left hemisphere.

Brain network definitions typically assume nonoverlap or minimal overlap, ignoring regions' connections to multiple networks. However, new methods are emerging that emphasize network overlap. Here, we investigated the reliability and validity of one assignment method, the mixed membership algorithm, and explored its potential utility for identifying gaps in existing network models of cognition. We first assessed between-sample reliability of overlapping assignments with a split-half design; a bootstrapped Dice similarity analysis demonstrated good agreement between the networks from the two subgroups. Next, we assessed whether overlapping networks captured expected nonoverlapping topographies; overlapping networks captured portions of one to three nonoverlapping topographies, which aligned with canonical network definitions. Following this, a relative entropy analysis showed that a majority of regions participated in more than one network, as is seen biologically, and many regions did not show preferential connection to any one network. Finally, we explored overlapping network membership in regions of the dual-networks model of cognitive control, showing that almost every region was a member of multiple networks. Thus, the mixed membership algorithm produces consistent and biologically plausible networks, which presumably will allow for the development of more complete network models of cognition.

Inter-species comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein performance requires the inference of a changing rule given ambiguous feedback. We found that well-trained monkeys rapidly infer rules but are three times slower than humans. Model fits to their choices revealed hidden states akin to feature-based attention in both species, and decision processes that resembled a Win-stay lose-shift strategy with key differences. Monkeys and humans test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidates. An attention-set based learning stage categorization revealed that perseveration, random exploration and poor sensitivity to negative feedback explain the under-performance in monkeys.