Electrophysiological correlates of default-mode processing in macaque posterior cingulate cortex

Large-Scale Network Coupling with the Fusiform Cortex Facilitates Future Social Motivation

Large-scale functional networks, as identified through the coordinated activity of spatially distributed brain regions, have become central objects of study in neuroscience because of their contributions to many processing domains. Yet, it remains unclear how these domain-general networks interact with focal brain regions to coordinate thought and action. Here, we investigated how the default-mode network (DMN) and executive control network (ECN), two networks associated with goal-directed behavior, shape task performance through their coupling with other cortical regions several seconds in advance of behavior. We measured these networks' connectivity during an adaptation of the monetary incentive delay (MID) response-time task in which human participants viewed social and nonsocial images (i.e., pictures of faces and landscapes, respectively) while brain activity was measured using fMRI. We found that participants displayed slower reaction times (RTs) subsequent to social trials relative to nonsocial trials. To examine the neural mechanisms driving this subsequent-RT effect, we integrated independent components analysis (ICA) and a network-based psychophysiological interaction (nPPI) analysis; this allowed us to investigate task-related changes in network coupling that preceded the observed trial-to-trial variation in RT. Strikingly, when subjects viewed social rewards, an area of the fusiform gyrus (FG) consistent with the functionally-defined fusiform face area (FFA) exhibited increased coupling with the ECN (relative to the DMN), and the relative magnitude of coupling tracked the slowing of RT on the following trial. These results demonstrate how large-scale, domain-general networks can interact with focal, domain-specific cortical regions to orchestrate subsequent behavior.

Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc.

Toward a conceptual framework for early brain and behavior development in autism

Studies of infant siblings of older autistic probands, who are at elevated risk for autism, have demonstrated that the defining features of autism are not present in the first year of life but emerge late in the first and into the second year. A recent longitudinal neuroimaging study of high-risk siblings revealed a specific pattern of brain development in infants later diagnosed with autism, characterized by cortical surface area hyper-expansion in the first year followed by brain volume overgrowth in the second year that is associated with the emergence of autistic social deficits. Together with new observations from genetically defined autism risk alleles and rodent model, these findings suggest a conceptual framework for the early, post-natal development of autism. This framework postulates that an increase in the proliferation of neural progenitor cells and hyper-expansion of cortical surface area in the first year, occurring during a pre-symptomatic period characterized by disrupted sensorimotor and attentional experience, leads to altered experience-dependent neuronal development and decreased elimination of neuronal processes. This process is linked to brain volume overgrowth and disruption of the refinement of neural circuit connections and is associated with the emergence of autistic social deficits in the second year of life. A better understanding of the timing of developmental brain and behavior mechanisms in autism during infancy, a period which precedes the emergence of the defining features of this disorder, will likely have important implications for designing rational approaches to early intervention.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness.

Reason's Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames.SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science.

Reentrant Information Flow in Electrophysiological Rat Default Mode Network

Functional MRI (fMRI) studies have demonstrated that the rodent brain shows a default mode network (DMN) activity similar to that in humans, offering a potential preclinical model both for physiological and pathophysiological studies. However, the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we used electrophysiological data to analyze the power spectrum and estimate the directed phase transfer entropy (dPTE) within rat DMN across three vigilance states: wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). We observed decreased gamma powers during SWS compared with WR in most of the DMN regions. Increased gamma powers were found in prelimbic cortex, cingulate cortex, and hippocampus during REMS compared with WR, whereas retrosplenial cortex showed a reverse trend. These changed gamma powers are in line with the local metabolic variation of homologous brain regions in humans. In the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. Our results provide electrophysiological evidence that rat DMN is similar to its human counterpart, and there is a frequency-dependent reentry loop of anterior-posterior information flow within rat DMN, which may offer a mechanism for functional integration, supporting conscious awareness.

The neural substrate of gait and executive function relationship in elderly women: A PET study

AIM

Understanding the relationship between age-related gait impairment, such as slow gait, and executive functioning in seniors may help identify individuals at higher risk of mobility decline, falls, and progression to dementia at earlier stages. We aim to identify brain regions concomitantly associated with poor gait and executive functioning in a cohort of well-functioning elderly women.

METHODS

In total, 149 well-functioning women aged 70.1 ± 6.2 years underwent FDG-PET to evaluate regional cerebral metabolic rates of glucose normalized in reference to cerebellar glucose metabolic value (normalized-rCMRglc) in 16 brain areas. We assessed gait speed, step length and cadence under usual and fast conditions. Executive function was assessed using Trail-Making-Tests (TMT) A and B.

RESULTS

Adjusted multiple regression analyses for potential covariates showed that TMT-B and ΔTMT (TMT B-A) were associated with gait speed and cadence at fast condition. Lower normalized-rCMRglc in the posterior cingulate and primary sensorimotor cortices were associated with longer TMT-B and ΔTMT times (i.e., lower executive function) as well as with slower gait speed and lower cadence at fast condition. Slower gait speed and lower cadence at fast condition were also associated with lower normalized-rCMRglc in the occipital and parietal cortices. There were no other significant associations.

CONCLUSIONS

In healthy elderly women without impending disability or cognitive impairment, reduced glucose metabolism in the posterior cingulate and primary sensorimotor cortices were associated with both lower gait performance and executive functioning. Our results suggest that gait control and executive functions might share the same neural substrate. Geriatr Gerontol Int 2017; 17: 1873-1880.

Brain functional connectivity abnormalities in attention-deficit hyperactivity disorder

INTRODUCTION

Recent evidence suggests that attention-deficit hyperactivity disorder (ADHD) is associated with brain functional connectivity (FC) abnormalities.

METHODS

In this study, we use steady-state visually evoked potential event-related partial coherence as a measure of brain FC to examine functional connectivity differences between a typically developing (TD) group of 25 boys and an age/IQ-matched group of 42 drug naive boys newly diagnosed with ADHD (ADHD group). Functional connectivity was estimated while both groups performed a low-demand reference task and the A-X version of the continuous performance task (CPT A-X).

RESULTS

While the TD and ADHD groups exhibited similar prefrontal FC increases prior to the appearance of the target in the reference task, these groups demonstrated significant FC differences in the interval preceding the appearance of the target in the CPT A-X task. Specifically, the ADHD group exhibited robust prefrontal and parieto-frontal FC increases that were not apparent in the TD group.

CONCLUSION

The FC differences observed in the ADHD group are discussed in the context of inadequate suppression of cortical networks that may interfere with task performance.

Hyperdeactivation of the Default Mode Network in People With Schizophrenia When Focusing Attention in Space

When studying selective attention in people with schizophrenia (PSZ), a counterintuitive but replicated finding has been that PSZ display larger performance benefits than healthy control subjects (HCS) by cues that predicts the location of a target stimulus relative to non-predictive cues. Possible explanations are that PSZ hyperfocus attention in response to predictive cues, or that an inability to maintain a broad attentional window impairs performance when the cue is non-predictive. Over-recruitment of regions involved in top-down focusing of spatial attention in response to predictive cues would support the former possibility, and an inappropriate recruitment of these regions in response to non-predictive cues the latter. We probed regions of the dorsal attention network while PSZ (N = 20) and HCS (N = 20) performed a visuospatial attention task. A central cue either predicted at which of 4 peripheral locations a target signal would appear, or it gave no information about the target location. As observed previously, PSZ displayed a larger reaction time difference between predictive and non-predictive cue trials than HCS. Activity in frontoparietal and occipital regions was greater for predictive than non-predictive cues. This effect was almost identical between PSZ and HCS. There was no sign of over-recruitment when the cue was predictive, or of inappropriate recruitment when the cue was non-predictive. However, PSZ differed from HCS in their cue-dependent deactivation of the default mode network. Unexpectedly, PSZ displayed significantly greater deactivation than HCS in predictive cue trials, which may reflect a tendency to expend more processing resources when focusing attention in space.

Prefrontal Parvalbumin Neurons in Control of Attention

While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top-down control of attention are largely unknown. Using chronic recordings in mice, we found that fast-spiking parvalbumin (FS-PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal-driven attentional processing, correlating to the level of attention. Elevated activity of FS-PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS-PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase-locked pyramidal neurons showed gamma-phase-dependent rate modulation during successful attentional processing. Optogenetic silencing of FS-PV neurons deteriorated attentional processing, while optogenetic synchronization of FS-PV neurons at gamma frequencies had pro-cognitive effects and improved goal-directed behavior. FS-PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal-driven attentional processing.

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Increased firing of mPFC PV interneurons is a signature of top-down attention

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Attention is characterized by synchronization of mPFC PV neurons and elevated gamma

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Local pyramidal neurons show gamma-phase-dependent rate modulation during attention

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Synchronization of mPFC PV neurons at gamma frequencies has pro-cognitive effects

Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies-e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively-each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904-2917, 2016. © 2016 Wiley Periodicals, Inc.

Sex-specific neural activity when resolving cognitive interference in individuals with or without prior internalizing disorders

The processing of cognitive interference is a self-regulatory capacity that is impaired in persons with internalizing disorders. This investigation was to assess sex differences in the neural correlates of cognitive interference in individuals with and without an illness history of an internalizing disorder. We compared functional magnetic resonance imaging blood-oxygenation-level-dependent responses in both males (n=63) and females (n=80) with and without this illness history during performance of the Simon task. Females deactivated superior frontal gyrus, inferior parietal lobe, and posterior cingulate cortex to a greater extent than males. Females with a prior history of internalizing disorder also deactivated these regions more compared to males with that history, and they additionally demonstrated greater activation of right inferior frontal gyrus. These group differences were represented in a significant sex-by-illness interaction in these regions. These deactivated regions compose a task-negative or default mode network, whereas the inferior frontal gyrus usually activates when performing an attention-demanding task and is a key component of a task-positive network. Our findings suggest that a prior history of internalizing disorders disproportionately influences functioning of the default mode network and is associated with an accompanying activation of the task-positive network in females during the resolution of cognitive interference.

Resting-state functional connectivity of the human habenula in healthy individuals: Associations with subclinical depression

INTRODUCTION

The habenula (Hb) is postulated to play a critical role in reward and aversion processing across species, including humans, and has been increasingly implicated in depression. However, technical constraints have limited in vivo investigation of the human Hb, and its function remains poorly characterized. We sought to overcome these challenges by examining the whole-brain resting-state functional connectivity of the Hb and its possible relationship to depressive symptomatology using the high-resolution WU-Minn Human Connectome Project (HCP) dataset.

METHODS

Anatomical and resting-state functional MRI data from 50 healthy subjects with low or high subclinical depression scores (n = 25 each) were analyzed. Using novel semi-automated segmentation and optimization techniques, we generated individual-specific Hb seeds and calculated whole-brain functional connectivity for the entire cohort and the contrast of high vs. low depression groups.

RESULTS

In the entire cohort, the Hb exhibited significant connectivity with key brainstem structures (i.e., ventral tegmental area, substantia nigra, pons) as well as the anterior and posterior cingulate cortices, precuneus, thalamus, and sensorimotor cortex. Multiple regions showed differential Hb connectivity based on subclinical depression scores, including the amygdala, insula, and prefrontal, mid-cingulate, and entorhinal cortices.

CONCLUSIONS

Hb connectivity findings converged on areas associated with salience processing, sensorimotor systems, and the default mode network. We also detected substantial Hb-brainstem connectivity, consistent with prior histological and animal research. High and low subclinical depression groups exhibited differences in Hb connectivity with multiple regions previously linked to depression, suggesting the relationship between these structures as a potential target for future research and treatment. Hum Brain Mapp 37:2369-2384, 2016. © 2016 Wiley Periodicals, Inc.

Spontaneous Neural Dynamics and Multi-scale Network Organization

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

Using fMRI to study reward processing in humans: past, present, and future

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for1) the corroboration of significant animal findings in the human brain, and2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies.

Splenium development and early spoken language in human infants

The association between developmental trajectories of language-related white matter fiber pathways from 6 to 24 months of age and individual differences in language production at 24 months of age was investigated. The splenium of the corpus callosum, a fiber pathway projecting through the posterior hub of the default mode network to occipital visual areas, was examined as well as pathways implicated in language function in the mature brain, including the arcuate fasciculi, uncinate fasciculi, and inferior longitudinal fasciculi. The hypothesis that the development of neural circuitry supporting domain-general orienting skills would relate to later language performance was tested in a large sample of typically developing infants. The present study included 77 infants with diffusion weighted MRI scans at 6, 12 and 24 months and language assessment at 24 months. The rate of change in splenium development varied significantly as a function of language production, such that children with greater change in fractional anisotropy (FA) from 6 to 24 months produced more words at 24 months. Contrary to findings from older children and adults, significant associations between language production and FA in the arcuate, uncinate, or left inferior longitudinal fasciculi were not observed. The current study highlights the importance of tracing brain development trajectories from infancy to fully elucidate emerging brain-behavior associations while also emphasizing the role of the splenium as a key node in the structural network that supports the acquisition of spoken language.

Implications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI

Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies often report inconsistent findings, probably due to brain properties such as balanced excitation and inhibition and functional heterogeneity. These properties indicate that different neurons in the same voxels may show variable activities including concurrent activation and deactivation, that the relationships between BOLD signal and neural activity (i.e., neurovascular coupling) are complex, and that increased BOLD signal may reflect reduced deactivation, increased activation, or both. The traditional general-linear-model-based-analysis (GLM-BA) is a univariate approach, cannot separate different components of BOLD signal mixtures from the same voxels, and may contribute to inconsistent findings of fMRI. Spatial independent component analysis (sICA) is a multivariate approach, can separate the BOLD signal mixture from each voxel into different source signals and measure each separately, and thus may reconcile previous conflicting findings generated by GLM-BA. We propose that methods capable of separating mixed signals such as sICA should be regularly used for more accurately and completely extracting information embedded in fMRI datasets.

Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment

AIMS

Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown.

METHODS

We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks.

RESULTS

Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients.

CONCLUSION

Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI.

Neurochemical Modulation in Posteromedial Default-mode Network Cortex Induced by Transcranial Magnetic Stimulation

BACKGROUND

The Default Mode Network (DMN) is severely compromised in several psychiatric and neurodegenerative disorders where plasticity alterations are observed. Glutamate and GABA are the major excitatory and inhibitory brain neurotransmitters respectively and are strongly related to plasticity responses and large-scale network expression.

OBJECTIVE

To investigate whether regional Glx (Glutamate + Glutamine) and GABA could be modulated within the DMN after experimentally-controlled induction of plasticity and to study the effect of intrinsic connectivity over brain responses to stimulation.

METHODS

We applied individually-guided neuronavigated Theta Burst Stimulation (TBS) to the left inferior parietal lobe (IPL) in-between two magnetic resonance spectroscopy (MRS) acquisitions to 36 young subjects. A resting-state fMRI sequence was also acquired before stimulation.

RESULTS

After intermittent TBS, distal GABA increases in posteromedial DMN areas were observed. Instead, no significant changes were detected locally, in left IPL areas. Neurotransmitter modulation in posteromedial areas was related to baseline fMRI connectivity between this region and the TBS-targeted area.

CONCLUSIONS

The prediction of neurotransmitter modulation by connectivity highlights the relevance of connectivity patterns to understand brain responses to plasticity-inducing protocols. The ability to modulate GABA in a key core of the DMN by means of TBS may open new avenues to evaluate plasticity mechanisms in a key area for major neurodegenerative and psychiatric conditions.

Making decisions based on autobiographical memories

A new human intracranial study by Foster et al. (2015) sheds light on the electrophysiological correlates of intrinsic and task-evoked functional connectivity in lateral and medial parietal cortex.

Exploring spatiotemporal network transitions in task functional MRI

A critical question for cognitive neuroscience regards how transitions between cognitive states emerge from the dynamic activity of functional brain networks. Here we combine a simple data reorganization with spatial independent component analysis (ICA), enabling a spatiotemporal ICA (stICA) which captures the consistent evolution of networks during the onset and offset of a task. The technique was applied to functional magnetic resonance imaging (MRI) (FMRI) datasets involving alternating between rest and task, and to simple synthetic data. Starting and finishing time-points of periods of interest (anchors) were defined at task block onsets and offsets. For each subject, the 10 volumes following each anchor were extracted and concatenated spatially, producing a single 3D sample. Samples for all anchors and subjects were concatenated along the fourth dimension. This 4D dataset was decomposed using ICA into spatiotemporal components. One component exhibited the transition with task onset from a default mode network (DMN) becoming less active to a frontoparietal control network becoming more active. We observed other changes with relevance to understanding network dynamics, for example, the DMN showed a changing spatial distribution, shifting to an anterior/superior pattern of deactivation during task from a posterior/inferior pattern during rest. By anchoring analyses to periods associated with the onsets and offsets of task, our approach reveals novel aspects of the dynamics of network activity accompanying these transitions. Importantly, these findings were observed without specifying a priori either the spatial networks or the task time courses.

Oxygen Level and LFP in Task-Positive and Task-Negative Areas: Bridging BOLD fMRI and Electrophysiology

The human default mode network (DMN) shows decreased blood oxygen level dependent (BOLD) signals in response to a wide range of attention-demanding tasks. Our understanding of the specifics regarding the neural activity underlying these "task-negative" BOLD responses remains incomplete. We paired oxygen polarography, an electrode-based oxygen measurement technique, with standard electrophysiological recording to assess the relationship of oxygen and neural activity in task-negative posterior cingulate cortex (PCC), a hub of the DMN, and visually responsive task-positive area V3 in the awake macaque. In response to engaging visual stimulation, oxygen, LFP power, and multi-unit activity in PCC showed transient activation followed by sustained suppression. In V3, oxygen, LFP power, and multi-unit activity showed an initial phasic response to the stimulus followed by sustained activation. Oxygen responses were correlated with LFP power in both areas, although the apparent hemodynamic coupling between oxygen level and electrophysiology differed across areas. Our results suggest that oxygen responses reflect changes in LFP power and multi-unit activity and that either the coupling of neural activity to blood flow and metabolism differs between PCC and V3 or computing a linear transformation from a single LFP band to oxygen level does not capture the true physiological process.

Subspecialization in the human posterior medial cortex

The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-unconstrained but not task-constrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications.

Social closeness and feedback modulate susceptibility to the framing effect

Although we often seek social feedback (SFB) from others to help us make decisions, little is known about how SFB affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision-making is modulated by SFB valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment. Periodically, participants were provided with positive (e.g., "Nice!") or negative (e.g., "Lame!") feedback about their choices. Such feedback was provided by either a confederate (Experiment 1) or a gender-matched close friend (Experiment 2). As expected, the framing effect was observed in both experiments. Critically, an individual's susceptibility to the framing effect was modulated by the valence of the SFB, but only when the feedback provider was a close friend. This effect was reflected in the activation patterns of ventromedial prefrontal cortex and posterior cingulate cortex, regions involved in complex decision-making. Taken together, these results highlight social closeness as an important factor in understanding the impact of SFB on neural mechanisms of decision-making.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity.

Binge alcohol consumption in emerging adults: anterior cingulate cortical "thinness" is associated with alcohol use patterns

BACKGROUND

The brain undergoes dynamic and requisite changes into the early 20s that are associated with improved cognitive efficiency, particularly in prefrontal regions that are still undergoing neuromaturation. As alcohol consumption is typically initiated and progresses to binge drinking (BD) during this time, the objective of the present study was to investigate the impact of binge alcohol consumption on frontal lobe cortical thickness in emerging adults.

METHODS

Twenty-three binge drinking (11 females, mean age 22.0 ± 1.2) and 31 light drinking (15 females, mean age 21.5 ± 1.6) emerging adults underwent high-resolution magnetic resonance imaging at 3 Tesla. Cortical surface reconstruction and thickness estimation were performed using FreeSurfer for 3 a priori brain regions of interest: bilateral anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and parieto-occipital sulcus (POS). Cortical thickness measurements were then compared between binge drinker (BD) and light drinker (LD) groups.

RESULTS

Cortical thickness was significantly lower in BD than LD in the right middle ACC (mid-ACC; p ≤ 0.05) and in the left dorsal PCC (dPCC; p ≤ 0.01). No significant differences in cortical thickness were observed in the POS. Cortical thickness in the mid-ACC correlated negatively with higher quantity and frequency of drinks consumed (p < 0.01) and positively with the number of days elapsed since most recent use (p < 0.05). Furthermore, less cortical thickness in the mid-ACC in the BD group alone correlated with reported patterns of high quantity and frequency of alcohol consumption (p ≤ 0.05).

CONCLUSIONS

Findings suggest that past and recent patterns of intermittent heavy alcohol consumption are associated with less frontal cortical thickness (i.e., "thinness") of the right mid-ACC and left dPCC in emerging adults, but not the POS. While cortical thinness could have predated binge drinking, this pattern of maladaptive consumption may have acute neurotoxic effects that interfere with the finalization of neuromaturational processes in the vulnerable frontal cortex, resulting in increased microarchitectural pruning.

Functional magnetic resonance imaging of intrinsic brain networks for translational drug discovery

Developing translational biomarkers is a priority for psychiatry research. Task-independent functional brain imaging is a relatively novel technique that allows examination of the brain's intrinsic networks, defined as functionally and (often) structurally connected populations of neurons whose properties reflect fundamental neurobiological organizational principles of the central nervous system. The ability to study the activity and organization of these networks has opened a promising new avenue for translational investigation, because they can be analogously examined across species and disease states. Interestingly, imaging studies have revealed shared spatial and functional characteristics of the intrinsic network architecture of the brain across species, including mice, rats, non-human primates, and humans. Using schizophrenia as an example, we show how intrinsic networks may show similar abnormalities in human diseases and animal models of these diseases, supporting their use as biomarkers in drug development.

A spatially nonselective baseline signal in parietal cortex reflects the probability of a monkey's success on the current trial

We recorded the activity of neurons in the lateral intraparietal area of two monkeys while they performed two similar visual search tasks, one difficult, one easy. Each task began with a period of fixation followed by an array consisting of a single capital T and a number of lowercase t's. The monkey had to find the capital T and report its orientation, upright or inverted, with a hand movement. In the easy task the monkey could explore the array with saccades. In the difficult task the monkey had to continue fixating and find the capital T in the visual periphery. The baseline activity measured during the fixation period, at a time in which the monkey could not know if the impending task would be difficult or easy or where the target would appear, predicted the monkey's probability of success or failure on the task. The baseline activity correlated inversely with the monkey's recent history of success and directly with the intensity of the response to the search array on the current trial. The baseline activity was unrelated to the monkey's spatial locus of attention as determined by the location of the cue in a cued visual reaction time task. We suggest that rather than merely reflecting the noise in the system, the baseline signal reflects the cortical manifestation of modulatory state, motivational, or arousal pathways, which determine the efficiency of cortical sensorimotor processing and the quality of the monkey's performance.

Brain functional connectivity changes in children that differ in impulsivity temperamental trait

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

Respiration phase-locks to fast stimulus presentations: implications for the interpretation of posterior midline "deactivations"

The posterior midline region (PMR)-considered a core of the default mode network-is deactivated during successful performance in different cognitive tasks. The extent of PMR-deactivations is correlated with task-demands and associated with successful performance in various cognitive domains. In the domain of episodic memory, functional MRI (fMRI) studies found that PMR-deactivations reliably predict learning (successful encoding). Yet it is unclear what explains this relation. One intriguing possibility is that PMR-deactivations are partially mediated by respiratory artifacts. There is evidence that the fMRI signal in PMR is particularly prone to respiratory artifacts, because of its large surrounding blood vessels. As respiratory fluctuations have been shown to track changes in attention, it is critical for the general interpretation of fMRI results to clarify the relation between respiratory fluctuations, cognitive performance, and fMRI signal. Here, we investigated this issue by measuring respiration during word encoding, together with a breath-holding condition during fMRI-scanning. Stimulus-locked respiratory analyses showed that respiratory fluctuations predicted successful encoding via a respiratory phase-locking mechanism. At the same time, the fMRI analyses showed that PMR-deactivations associated with learning were reduced during breath-holding and correlated with individual differences in the respiratory phase-locking effect during normal breathing. A left frontal region--used as a control region--did not show these effects. These findings indicate that respiration is a critical factor in explaining the link between PMR-deactivation and successful cognitive performance. Further research is necessary to demonstrate whether our findings are restricted to episodic memory encoding, or also extend to other cognitive domains.

Precuneus is a functional core of the default-mode network

Efforts to understand the functional architecture of the brain have consistently identified multiple overlapping large-scale neural networks that are observable across multiple states. Despite the ubiquity of these networks, it remains unclear how regions within these large-scale neural networks interact to orchestrate behavior. Here, we collected functional magnetic resonance imaging data from 188 human subjects who engaged in three cognitive tasks and a resting-state scan. Using multiple tasks and a large sample allowed us to use split-sample validations to test for replication of results. We parceled the task-rest pairs into functional networks using a probabilistic spatial independent components analysis. We examined changes in connectivity between task and rest states using dual-regression analysis, which quantifies voxelwise connectivity estimates for each network of interest while controlling for the influence of signals arising from other networks and artifacts. Our analyses revealed systematic state-dependent functional connectivity in one brain region: the precuneus. Specifically, task performance led to increased connectivity (compared to rest) between the precuneus and the left frontoparietal network (lFPN), whereas rest increased connectivity between the precuneus and the default-mode network (DMN). The absolute magnitude of this effect was greater for DMN, suggesting a heightened specialization for resting-state cognition. All results replicated within the two independent samples. Our results indicate that the precuneus plays a core role not only in DMN, but also more broadly through its engagement under a variety of processing states.

Causal evidence of performance monitoring by neurons in posterior cingulate cortex during learning

The posterior cingulate cortex (CGp) is a major hub of the default mode network (DMN), a set of cortical areas with high resting activity that declines during task performance. This relationship suggests that DMN activity contributes to mental processes that are antagonistic to performance. Alternatively, DMN may detect conditions under which performance is poor and marshal cognitive resources for improvement. To test this idea, we recorded activity of CGp neurons in monkeys performing a learning task while varying reward size and novelty. We found that CGp neurons responded to errors, and this activity was magnified by small reward and novel stimuli. Inactivating CGp with muscimol impaired new learning when rewards were small but had no effect when rewards were large; inactivation did not affect performance on well-learned associations. Thus, CGp, and by extension the DMN, may support learning, and possibly other cognitive processes, by monitoring performance and motivating exploration.

All that glitters is not BOLD: inconsistencies in functional MRI

The blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal is a widely-accepted marker of brain activity. The acquisition parameters (APs) of fMRI aim at maximizing the signals related to neuronal activity while minimizing unrelated signal fluctuations. Currently, a diverse set of APs is used to acquire BOLD fMRI data. Here we demonstrate that some fMRI responses are alarmingly inconsistent across APs, ranging from positive to negative, or disappearing entirely, under identical stimulus conditions. These discrepancies, resulting from non-BOLD effects masquerading as BOLD signals, have remained largely unnoticed because studies rarely employ more than one set of APs. We identified and characterized non-BOLD responses in several brain areas, including posterior cingulate cortex and precuneus, as well as AP-dependence of both the signal time courses and of seed-based functional networks, noticing that AP manipulation can inform about the origin of the measured signals.

The default mode network in chimpanzees (Pan troglodytes) is similar to that of humans

The human default mode network (DMN), comprising medial prefrontal cortex, precuneus, posterior cingulate cortex, lateral parietal cortex, and medial temporal cortex, is highly metabolically active at rest but deactivates during most focused cognitive tasks. The DMN and social cognitive networks overlap significantly in humans. We previously demonstrated that chimpanzees (Pan troglodytes) show highest resting metabolic brain activity in the cortical midline areas of the human DMN. Human DMN is defined by task-induced deactivations, not absolute resting metabolic levels; ergo, resting activity is insufficient to define a DMN in chimpanzees. Here, we assessed the chimpanzee DMN's deactivations relative to rest during cognitive tasks and the effect of social content on these areas' activity. Chimpanzees performed a match-to-sample task with conspecific behavioral stimuli of varying sociality. Using [(18)F]-FDG PET, brain activity during these tasks was compared with activity during a nonsocial task and at rest. Cortical midline areas in chimpanzees deactivated in these tasks relative to rest, suggesting a chimpanzee DMN anatomically and functionally similar to humans. Furthermore, when chimpanzees make social discriminations, these same areas (particularly precuneus) are highly active relative to nonsocial tasks, suggesting that, as in humans, the chimpanzee DMN may play a role in social cognition.

Linking neural activity to complex decisions

In the 1990s, seminal work from Newsome and colleagues made it possible to study the neuronal mechanisms of simple perceptual decisions. The key strength of this work was the clear and direct link between neuronal activity and choice processes. Since then, a great deal of research has extended these initial discoveries to more complex forms of decision making, with the goal of bringing the same strength of linkage between neural and psychological processes. Here, we discuss the progress of two such research programs, namely our own, that are aimed at understanding memory-guided decisions and reward-guided decisions. These problems differ in the relevant brain areas, in the progress that has been achieved, and in the extent of broader understanding achieved so far. However, they are unified by the use of theoretical insights about how to link neuronal activity to decisions.

The role of the posterior cingulate cortex in cognition and disease

The posterior cingulate cortex is a highly connected and metabolically active brain region. Recent studies suggest it has an important cognitive role, although there is no consensus about what this is. The region is typically discussed as having a unitary function because of a common pattern of relative deactivation observed during attentionally demanding tasks. One influential hypothesis is that the posterior cingulate cortex has a central role in supporting internally-directed cognition. It is a key node in the default mode network and shows increased activity when individuals retrieve autobiographical memories or plan for the future, as well as during unconstrained 'rest' when activity in the brain is 'free-wheeling'. However, other evidence suggests that the region is highly heterogeneous and may play a direct role in regulating the focus of attention. In addition, its activity varies with arousal state and its interactions with other brain networks may be important for conscious awareness. Understanding posterior cingulate cortex function is likely to be of clinical importance. It is well protected against ischaemic stroke, and so there is relatively little neuropsychological data about the consequences of focal lesions. However, in other conditions abnormalities in the region are clearly linked to disease. For example, amyloid deposition and reduced metabolism is seen early in Alzheimer's disease. Functional neuroimaging studies show abnormalities in a range of neurological and psychiatric disorders including Alzheimer's disease, schizophrenia, autism, depression and attention deficit hyperactivity disorder, as well as ageing. Our own work has consistently shown abnormal posterior cingulate cortex function following traumatic brain injury, which predicts attentional impairments. Here we review the anatomy and physiology of the region and how it is affected in a range of clinical conditions, before discussing its proposed functions. We synthesize key findings into a novel model of the region's function (the 'Arousal, Balance and Breadth of Attention' model). Dorsal and ventral subcomponents are functionally separated and differences in regional activity are explained by considering: (i) arousal state; (ii) whether attention is focused internally or externally; and (iii) the breadth of attentional focus. The predictions of the model can be tested within the framework of complex dynamic systems theory, and we propose that the dorsal posterior cingulate cortex influences attentional focus by 'tuning' whole-brain metastability and so adjusts how stable brain network activity is over time.

The critical roles of localization and physiology for understanding parietal contributions to memory retrieval

Functional magnetic resonance imaging (fMRI) studies of recognition memory ubiquitously demonstrate retrieval-related activity in left lateral parietal cortex (LLPC) when contrasting studied ("old") items with unstudied ("new") items. Recent work demonstrates that there is considerable functional-anatomical heterogeneity in LLPC. One implication of this observation is that single- or dual-process models fall short of characterizing LLPC contributions to memory retrieval. Instead of considering LLPC as a single entity, functional accounts must be given for each of the distinct regions that show retrieval-related effects; we posit there are a minimum of four such regions and very likely more. Identification of these LLPC regions requires careful analysis to map the boundaries and the extent of the regions precisely. In addition, characterizing the functional responses as activations or deactivations relative to baseline will be crucial in understanding the underlying cognitive processes. Considering LLPC in both memory and "nonmemory" domains will also illuminate the contribution of these regions, because it is certainly unlikely they serve only the domain of memory retrieval.

EEG correlates of self-referential processing

Self-referential processing has been principally investigated using functional magnetic resonance imaging (fMRI). However, understanding of the brain functioning is not possible without careful comparison of the evidence coming from different methodological domains. This paper aims to review electroencephalographic (EEG) studies of self-referential processing and to evaluate how they correspond, complement, or contradict the existing fMRI evidence. There are potentially two approaches to the study of EEG correlates of self-referential processing. Firstly, because simultaneous registration of EEG and fMRI has become possible, the degree of overlap between these two signals in brain regions related to self-referential processing could be determined. Second and more direct approach would be the study of EEG correlates of self-referential processing per se. In this review, I discuss studies, which employed both these approaches and show that in line with fMRI evidence, EEG correlates of self-referential processing are most frequently found in brain regions overlapping with the default network, particularly in the medial prefrontal cortex. In the time domain, the discrimination of self- and others-related information is mostly associated with the P300 ERP component, but sometimes is observed even earlier. In the frequency domain, different frequency oscillations have been shown to contribute to self-referential processing, with spontaneous self-referential mentation being mostly associated with the alpha frequency band.

Increased neuronal firing in resting and sleep in areas of the macaque medial prefrontal cortex

The medial prefrontal cortex (mPFC) of humans and macaques is an integral part of the default mode network and is a brain region that shows increased activation in the resting state. A previous paper from our laboratory reported significantly increased firing rates of neurons in the macaque subgenual cingulate cortex, Brodmann area (BA) 25, during disengagement from a task and also during slow wave sleep [E.T. Rolls et al. (2003) J. Neurophysiology, 90, 134-142]. Here we report the finding that there are neurons in other areas of mPFC that also increase their firing rates during disengagement from a task, drowsiness and eye-closure. During the neurophysiological recording of single mPFC cells (n = 249) in BAs 9, 10, 13 m, 14c, 24b and especially pregenual area 32, populations of neurons were identified whose firing rates altered significantly with eye-closure compared with eye-opening. Three types of neuron were identified: Type 1 cells (28.1% of the total population) significantly increased (mean + 329%; P ≪ 0.01) their average firing rate with eye-closure, from 3.1 spikes/s when awake to 10.2 spikes/s when asleep; Type 2 cells (6.0%) significantly decreased (mean -68%; P < 0.05) their firing rate on eye-closure; and Type 3 cells (65.9%) were unaffected. Thus, in many areas of mPFC, implicated in the anterior default mode network, there is a substantial population of neurons that significantly increase their firing rates during periods of eye-closure. Such neurons may be part of an interconnected network of distributed brain regions that are more active during periods of relaxed wakefulness than during attention-demanding tasks.

The encoding/retrieval flip: interactions between memory performance and memory stage and relationship to intrinsic cortical networks

fMRI studies have linked the posteromedial cortex to episodic learning (encoding) and remembering (retrieval) processes. The posteromedial cortex is considered part of the default network and tends to deactivate during encoding but activate during retrieval, a pattern known as the encoding/retrieval flip. Yet, the exact relationship between the neural correlates of memory performance (hit/miss) and memory stage (encoding/retrieval) and the extent of overlap with intrinsic cortical networks remains to be elucidated. Using task-based fMRI, we isolated the pattern of activity associated with memory performance, memory stage, and the interaction between both. Using resting-state fMRI, we identified which intrinsic large-scale functional networks overlapped with regions showing task-induced effects. Our results demonstrated an effect of successful memory performance in regions associated with the control network and an effect of unsuccessful memory performance in the ventral attention network. We found an effect of memory retrieval in brain regions that span the default and control networks. Finally, we found an interaction between memory performance and memory stage in brain regions associated with the default network, including the posteromedial cortex, posterior parietal cortex, and parahippocampal cortex. We discuss these findings in relation to the encoding/retrieval flip. In general, the findings demonstrate that task-induced effects cut across intrinsic cortical networks. Furthermore, regions within the default network display functional dissociations, and this may have implications for the neural underpinnings of age-related memory disorders.

The role of default network deactivation in cognition and disease

A considerable body of evidence has accumulated over recent years on the functions of the default-mode network (DMN)--a set of brain regions whose activity is high when the mind is not engaged in specific behavioral tasks and low during focused attention on the external environment. In this review, we focus on DMN suppression and its functional role in health and disease, summarizing evidence that spans several disciplines, including cognitive neuroscience, pharmacological neuroimaging, clinical neuroscience, and theoretical neuroscience. Collectively, this research highlights the functional relevance of DMN suppression for goal-directed cognition, possibly by reducing goal-irrelevant functions supported by the DMN (e.g., mind-wandering), and illustrates the functional significance of DMN suppression deficits in severe mental illness.

Rates and rhythms: a synergistic view of frequency and temporal coding in neuronal networks

In the CNS, activity of individual neurons has a small but quantifiable relationship to sensory representations and motor outputs. Coactivation of a few 10s to 100s of neurons can code sensory inputs and behavioral task performance within psychophysical limits. However, in a sea of sensory inputs and demand for complex motor outputs how is the activity of such small subpopulations of neurons organized? Two theories dominate in this respect: increases in spike rate (rate coding) and sharpening of the coincidence of spiking in active neurons (temporal coding). Both have computational advantages and are far from mutually exclusive. Here, we review evidence for a bias in neuronal circuits toward temporal coding and the coexistence of rate and temporal coding during population rhythm generation. The coincident expression of multiple types of gamma rhythm in sensory cortex suggests a mechanistic substrate for combining rate and temporal codes on the basis of stimulus strength.

NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia

Glutamatergic neurotransmission mediated by N-methyl-d-aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain's global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate's role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.