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Locomotion requires energy, yet animals need to increase locomotion in order to find and consume food in energy-deprived states. While such energy homeostatic coordination suggests brain origin, whether the central melanocortin 4 receptor (Mc4r) system directly modulates locomotion through motor circuits is unknown. Here, we report that hypothalamic Pomc neurons in zebrafish and mice have long-range projections into spinal cord regions harboring Mc4r-expressing V2a interneurons, crucial components of the premotor networks. Furthermore, in zebrafish, Mc4r activation decreases the excitability of spinal V2a neurons as well as swimming and foraging, while systemic or V2a neuron-specific blockage of Mc4r promotes locomotion. In contrast, in mice, electrophysiological recordings revealed that two-thirds of V2a neurons in lamina X are excited by the Mc4r agonist α-MSH, and acute inhibition of Mc4r signaling reduces locomotor activity. In addition, we found other Mc4r neurons in spinal lamina X that are inhibited by α-MSH, which is in line with previous studies in rodents where Mc4r agonists reduced locomotor activity. Collectively, our studies identify spinal V2a interneurons as evolutionary conserved second-order neurons of the central Mc4r system, providing a direct anatomical and functional link between energy homeostasis and locomotor control systems. The net effects of this modulatory system on locomotor activity can vary between different vertebrate species and, possibly, even within one species. We discuss the biological sense of this phenomenon in light of the ambiguity of locomotion on energy balance and the different living conditions of the different species.

The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research.

Information processing in the brain depends on specialized organization of neurotransmitter receptors and scaffolding proteins within the postsynaptic density. However, how these molecules are organized in situ remains largely unknown. In this study, template-free classification of oversampled sub-tomograms was used to analyze cryo-electron tomograms of hippocampal synapses. We identified type-A GABA receptors (GABAARs) in inhibitory synapses and determined their in situ structure at 19-Å resolution. These receptors are organized hierarchically: from GABAAR super-complexes with a preferred inter-receptor distance of 11 nm but variable relative angles, through semi-ordered, two-dimensional receptor networks with reduced Voronoi entropy, to mesophasic assembly with a sharp phase boundary. These assemblies likely form via interactions among postsynaptic scaffolding proteins and receptors and align with putative presynaptic vesicle release sites. Such mesophasic self-organization might allow synapses to achieve a 'Goldilocks' state, striking a balance between stability and flexibility and enabling plasticity in information processing.

Motor dysfunction in youth at clinical high risk (CHR) for psychosis is thought to reflect abnormal neurodevelopment within cortical-subcortical motor circuits and may be important for understanding clinical trajectories of CHR individuals. However, to date, our perspective of brain-behavior relationships has been informed solely by cross-sectional correlational studies linking behavior in the lab to brain structure or respective resting-state network connectivity. Here, we assess movement dysfunction from 2 perspectives: study 1 investigates the longitudinal progression of handwriting variability and positive symptoms in a sample of 91 CHR and healthy controls during a 12-month follow-up and study 2 involves a multiband functional magnetic resonance imaging task exploring the relationship between power grip force stability and motor network brain activation in a subset of participants. In study 1, we found that greater handwriting variability was a stable feature of CHR participants who experienced worse symptom progression. Study 2 results showed that CHR individuals had greater variability in their grip force and greater variability was related to decreased activation in the associative cortico-striatal network compared to controls. Motor variability may be a stable marker of vulnerability for psychosis risk and possible indicator of a vulnerable cortico-striatal brain network functioning in CHR participants, although the effects of antipsychotic medication should be considered.

BackgroundAlzheimer's disease (AD) is the most frequent and costly neurodegenerative disorder. Although diverse lines of evidence suggest that the amyloid precursor protein (APP) is involved in its causation, the precise mechanisms remain unknown and no treatments are available to prevent or halt the disease. A favorite hypothesis has been that APP contributes to AD pathogenesis through the cerebral accumulation of the amyloid-β peptide (Aβ), which is derived from APP through sequential proteolytic cleavage by BACE1 and γ-secretase. However, inhibitors of these enzymes have failed in clinical trials despite clear evidence for target engagement.MethodsTo further elucidate the roles of APP and its metabolites in AD pathogenesis, we analyzed transgenic mice overexpressing wildtype human APP (hAPP) or hAPP carrying mutations that cause autosomal dominant familial AD (FAD), as well as App knock-in mice that do not overexpress hAPP but have two mouse App alleles with FAD mutations and a humanized Aβ sequence.ResultsAlthough these lines of mice had marked differences in cortical and hippocampal levels of APP, APP C-terminal fragments, soluble Aβ, Aβ oligomers and age-dependent amyloid deposition, they all developed cognitive deficits as well as non-convulsive epileptiform activity, a type of network dysfunction that also occurs in a substantive proportion of humans with AD. Pharmacological inhibition of BACE1 effectively reduced levels of amyloidogenic APP C-terminal fragments (C99), soluble Aβ, Aβ oligomers, and amyloid deposits in transgenic mice expressing FAD-mutant hAPP, but did not improve their network dysfunction and behavioral abnormalities, even when initiated at early stages before amyloid deposits were detectable.ConclusionshAPP transgenic and App knock-in mice develop similar pathophysiological alterations. APP and its metabolites contribute to AD-related functional alterations through complex combinatorial mechanisms that may be difficult to block with BACE inhibitors and, possibly, also with other anti-Aβ treatments.

Degenerative cervical myelopathy (DCM) is the most common cause of spinal cord impairment in adults. Previous supraspinal investigations have primarily focused on cortical changes in this patient population. As the nexus between the brain and the spinal cord, the brainstem has been understudied in patients with DCM. The current study examined the structural and functional connectivity between the brainstem and cortex in DCM patients using probabilistic tractography and resting-state functional MRI. A total of 26 study patients and 32 neurologically intact, healthy volunteers (HCs) participated in this prospective analysis. The study cohort included DCM patients (n = 18), as well as neurologically asymptomatic patients with evidence of cervical spine degenerative changes and spinal cord compression (n = 8). Results of the study demonstrated significant differences in fiber density (FD), fiber cross-section (FDC), and the functional connectivity (FC) between the study cohort and HCs. Through seeding the brainstem, the study cohort showed reductions in FD and FDC along the corticospinal tract, including regions extending through the corona radiata and internal capsule. By correlating FD and FDC with the Neck Disability Index (NDI), and the modified Japanese Orthopaedic Association (mJOA), we identified increasing total volume of projections to the thalamus, basal ganglia, and internal capsule, and increased functional connectivity to visual network and the posterior parietal cortices. These results support our hypothesis that DCM patients tend to have long-term FC reorganization not only localized to sensorimotor regions, but also to regulatory and visual processing regions, designed to ultimately preserve neurological function.

RationaleCo-use of cannabis and nicotine is common among adolescents/young adults and is associated with poorer psychological and physical outcomes, compared with single substance use. Little is known about the impact of co-use on the developing brain.ObjectivesPreliminary investigation of the effects of nicotine on white matter (WM) cerebral blood flow (CBF) in adolescents/young adults and its potential moderation by cannabis use.MethodsAdolescent/young adult (16-22 years old) nicotine and tobacco product users (NTP; N = 37) and non-nicotine users (non-NTP; N = 26) underwent a neuroimaging session comprised of anatomical, optimized pseudo-continuous arterial spin labeling, and diffusion tensor imaging scans. Groups were compared on whole-brain WM CBF estimates and their relation to past-year cannabis use. Follow-up analyses assessed correlations between identified CBF clusters and corresponding fractional anisotropy (FA) values.ResultsGroup by cannabis effects were observed in five clusters (voxel-wise alpha < 0.001, cluster-wise alpha < 0.05; ≥ 11 contiguous voxels): non-NTP exhibited positive correlations between CBF and cannabis use in all clusters, whereas no significant relationships were observed for NTP. Greater CBF extracted from one cluster (including portions of right superior longitudinal fasciculus) was associated with reduced FA for non-NTP group only.ConclusionsThis is the first investigation of WM health as indexed by CBF, and its association with FA, in adolescents/young adults with nicotine and/or cannabis use. Results suggest that cannabis use by itself may be related to increased CBF in WM fiber tracts demonstrating poorer structural intergrity, yet the occurrence of even infrequent NTP use (greater than once per month) appears to diminish this relationship.

The central amygdala (CeA) is critically involved in a range of adaptive behaviors, including defensive behaviors. Neurons in the CeA send long-range projections to a number of extra-amygdala targets, but the functions of these projections remain elusive. Here, we report that a previously neglected CeA-to-globus pallidus external segment (GPe) circuit plays an essential role in classical fear conditioning. By anatomic tracing, in situ hybridization and channelrhodopsin (ChR2)-assisted circuit mapping in both male and female mice, we found that a subset of CeA neurons send projections to the GPe, and the majority of these GPe-projecting CeA neurons express the neuropeptide somatostatin. Notably, chronic inhibition of GPe-projecting CeA neurons with the tetanus toxin light chain (TeLC) completely blocks auditory fear conditioning. In vivo fiber photometry revealed that these neurons are selectively excited by the unconditioned stimulus (US) during fear conditioning. Furthermore, transient optogenetic inactivation or activation of these neurons selectively during US presentation impairs or promotes, respectively, fear learning. Our results suggest that a major function of GPe-projecting CeA neurons is to represent and convey US-related information through the CeA-GPe circuit, thereby regulating learning in fear conditioning.SIGNIFICANCE STATEMENT The central amygdala (CeA) has been implicated in the establishment of defensive behaviors toward threats, but the underlying circuit mechanisms remain unclear. Here, we found that a subpopulation of neurons in the CeA, which are mainly those that express the neuropeptide somatostatin, send projections to the globus pallidus external segment (GPe), and this CeA-GPe circuit conveys unconditioned stimulus (US)-related information during classical fear conditioning, thereby having an indispensable role in learning. Our results reveal a previously unknown circuit mechanism for fear learning.

An elemental computation in the brain is to identify the best in a set of options and report its value. It is required for inference, decision-making, optimization, action selection, consensus, and foraging. Neural computing is considered powerful because of its parallelism; however, it is unclear whether neurons can perform this max-finding operation in a way that improves upon the prohibitively slow optimal serial max-finding computation (which takes [Formula: see text] time for N noisy candidate options) by a factor of N, the benchmark for parallel computation. Biologically plausible architectures for this task are winner-take-all (WTA) networks, where individual neurons inhibit each other so only those with the largest input remain active. We show that conventional WTA networks fail the parallelism benchmark and, worse, in the presence of noise, altogether fail to produce a winner when N is large. We introduce the nWTA network, in which neurons are equipped with a second nonlinearity that prevents weakly active neurons from contributing inhibition. Without parameter fine-tuning or rescaling as N varies, the nWTA network achieves the parallelism benchmark. The network reproduces experimentally observed phenomena like Hick's law without needing an additional readout stage or adaptive N-dependent thresholds. Our work bridges scales by linking cellular nonlinearities to circuit-level decision-making, establishes that distributed computation saturating the parallelism benchmark is possible in networks of noisy, finite-memory neurons, and shows that Hick's law may be a symptom of near-optimal parallel decision-making with noisy input.

The "core language network" consists of left frontal and temporal regions that are selectively engaged in linguistic processing. Whereas functional differences among these regions have long been debated, many accounts propose distinctions in terms of representational grain-size-e.g., words vs. phrases/sentences-or processing time-scale, i.e., operating on local linguistic features vs. larger spans of input. Indeed, the topography of language regions appears to overlap with a cortical hierarchy reported by Lerner et al. (2011) wherein mid-posterior temporal regions are sensitive to low-level features of speech, surrounding areas-to word-level information, and inferior frontal areas-to sentence-level information and beyond. However, the correspondence between the language network and this hierarchy of "temporal receptive windows" (TRWs) is difficult to establish because the precise anatomical locations of language regions vary across individuals. To directly test this correspondence, we first identified language regions in each participant with a well-validated task-based localizer, which confers high functional resolution to the study of TRWs (traditionally based on stereotactic coordinates); then, we characterized regional TRWs with the naturalistic story listening paradigm of Lerner et al. (2011), which augments task-based characterizations of the language network by more closely resembling comprehension "in the wild". We find no region-by-TRW interactions across temporal and inferior frontal regions, which are all sensitive to both word-level and sentence-level information. Therefore, the language network as a whole constitutes a unique stage of information integration within a broader cortical hierarchy.

The brain is an endocrine organ, sensitive to the rhythmic changes in sex hormone production that occurs in most mammalian species. In rodents and nonhuman primates, estrogen and progesterone's impact on the brain is evident across a range of spatiotemporal scales. Yet, the influence of sex hormones on the functional architecture of the human brain is largely unknown. In this dense-sampling, deep phenotyping study, we examine the extent to which endogenous fluctuations in sex hormones alter intrinsic brain networks at rest in a woman who underwent brain imaging and venipuncture for 30 consecutive days. Standardized regression analyses illustrate estrogen and progesterone's widespread associations with functional connectivity. Time-lagged analyses examined the temporal directionality of these relationships and suggest that cortical network dynamics (particularly in the Default Mode and Dorsal Attention Networks, whose hubs are densely populated with estrogen receptors) are preceded-and perhaps driven-by hormonal fluctuations. A similar pattern of associations was observed in a follow-up study one year later. Together, these results reveal the rhythmic nature in which brain networks reorganize across the human menstrual cycle. Neuroimaging studies that densely sample the individual connectome have begun to transform our understanding of the brain's functional organization. As these results indicate, taking endocrine factors into account is critical for fully understanding the intrinsic dynamics of the human brain.

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

Stable representations of past experience are thought to depend on processes that unfold after events are initially encoded into memory. Post-encoding reactivation and hippocampal-cortical interactions are leading candidate mechanisms thought to support memory retention and stabilization across hippocampal-cortical networks. Although putative consolidation mechanisms have been observed during sleep and periods of awake rest, the direct causal contribution of awake consolidation mechanisms to later behavior is unclear, especially in humans. Moreover, it has been argued that observations of putative consolidation processes are epiphenomenal and not causally important, yet there are few tools to test the functional contribution of these mechanisms in humans. Here, we combined transcranial magnetic stimulation (TMS) and fMRI to test the role of awake consolidation processes by targeting hippocampal interactions with lateral occipital cortex (LOC). We applied theta-burst TMS to LOC (and a control site) to interfere with an extended window (approximately 30-50 min) after memory encoding. Behaviorally, post-encoding TMS to LOC selectively impaired associative memory retention compared to multiple control conditions. In the control TMS condition, we replicated prior reports of post-encoding reactivation and memory-related hippocampal-LOC interactions during periods of awake rest using fMRI. However, post-encoding LOC TMS reduced these processes, such that post-encoding reactivation in LOC and memory-related hippocampal-LOC functional connectivity were no longer present. By targeting and manipulating post-encoding neural processes, these findings highlight the direct contribution of awake time periods to episodic memory consolidation. This combined TMS-fMRI approach provides an opportunity for causal manipulations of human memory consolidation.

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

Brain activity typically increases with increasing working memory (WM) load, regardless of age, before reaching an apparent ceiling. However, older adults exhibit greater brain activity and reach ceiling at lower loads than younger adults, possibly reflecting compensation at lower loads and dysfunction at higher loads. We hypothesized that WM training would bolster neural efficiency, such that the activation peak would shift towards higher memory loads after training. Pre-training, older adults showed greater recruitment of the WM network than younger adults across all loads, with decline at the highest load. Ten days of adaptive training on a verbal WM task improved performance and led to greater brain responsiveness at higher loads for both groups. For older adults the activation peak shifted rightward towards higher loads. Finally, training increased task-related functional connectivity in older adults, both within the WM network and between this task-positive network and the task-negative/default-mode network. These results provide new evidence for functional plasticity with training in older adults and identify a potential signature of improvement at the neural level.

Resting-state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partitioned heritability analysis for multidimensional functional connectivity patterns, which revealed the common and unique enrichment patterns of the genetic contributions to brain connectivity patterns for several gene sets linked to brain functions, including the genes expressed preferentially in the central nervous system and those associated with intelligence, educational attainment, attention-deficit/hyperactivity disorder, and schizophrenia. These results for the first time reveal the genetic architecture of multidimensional brain connectivity patterns across different networks and advance our understanding of the complex relationship between gene sets, neural networks, and behaviors.

The relationship between the brain's structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed-form solution for the structure-function problem, specified by the graph spectrum of the structural connectome's Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. The resulting parsimonious and analytical solution stands in contrast to complex numerical simulations of high dimensional coupled nonlinear neural field models. This spectral graph model accurately predicts spatial and spectral features of neural oscillatory activity across the brain and was successful in simultaneously reproducing empirically observed spatial and spectral patterns of alpha-band (8-12 Hz) and beta-band (15-30 Hz) activity estimated from source localized magnetoencephalography (MEG). This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole-brain dynamics. .

This study examined global resting-state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band-dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.

Single-cell transcriptomics of neocortical neurons have revealed more than 100 clusters corresponding to putative cell types. For inhibitory and subcortical projection neurons (SCPNs), there is a strong concordance between clusters and anatomical descriptions of cell types. In contrast, cortico-cortical projection neurons (CCPNs) separate into surprisingly few transcriptomic clusters, despite their diverse anatomical projection types. We used projection-dependent single-cell transcriptomic analyses and monosynaptic rabies tracing to compare mouse primary visual cortex CCPNs projecting to different higher visual areas. We find that layer 2/3 CCPNs with different anatomical projections differ systematically in their gene expressions, despite forming only a single genetic cluster. Furthermore, these neurons receive feedback selectively from the same areas to which they project. These findings demonstrate that gene-expression analysis in isolation is insufficient to identify neuron types and have important implications for understanding the functional role of cortical feedback circuits.

The growing amount of screen time among adolescents has raised concerns about the effects it may have on their physical and psychological health. Although the literature is divided on whether the effects are mostly positive, neutral, or mostly negative, it is likely that the impacts will be highly individualized with a mixture of good and bad consequences for each person. Understanding behavioral and neurobiological phenomena of adolescence may help to guide research and interventions to optimize the benefits and minimize the risks. Particular aspects of adolescent development relevant to the issue include: (i) hunger for human connectedness; (ii) appetite for adventure; and (iii) desire for data.
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The human brain is asymmetrically lateralized for certain functions (such as language processing) to regions in one hemisphere relative to the other. Asymmetries are measured with a laterality index (LI). However, traditional LI measures are limited by a lack of consensus on metrics used for its calculation. To address this limitation, source-based laterality (SBL) leverages an independent component analysis for the identification of laterality-specific alterations, identifying covarying components between hemispheres across subjects. SBL is successfully implemented with simulated data with inherent differences in laterality. SBL is then compared with a voxel-wise analysis utilizing structural data from a sample of patients with schizophrenia and controls without schizophrenia. SBL group comparisons identified three distinct temporal regions and one cerebellar region with significantly altered laterality in patients with schizophrenia relative to controls. Previous work highlights reductions in laterality (ie, reduced left gray matter volume) in patients with schizophrenia compared with controls without schizophrenia. Results from this pilot SBL project are the first, to our knowledge, to identify covarying laterality differences within discrete temporal brain regions. The authors argue SBL provides a unique focus to detect covarying laterality differences in patients with schizophrenia, facilitating the discovery of laterality aspects undetected in previous work.

OBJECTIVE: Functional connectivity networks (FCNs) based on interictal electroencephalography (EEG) can identify pathological brain networks associated with epilepsy. FCNs are altered by interictal epileptiform discharges (IEDs), but it is unknown whether this is due to the morphology of the IED or the underlying pathological activity. Therefore, we characterized the impact of IEDs on the FCN through simulations and EEG analysis. METHODS: We introduced simulated IEDs to sleep EEG recordings of eight healthy controls and analyzed the effect of IED amplitude and rate on the FCN. We then generated FCNs based on epochs with and without IEDs and compared them to the analogous FCNs from eight subjects with infantile spasms (IS), based on 1340 visually marked IEDs. Differences in network structure and strength were assessed. RESULTS: IEDs in IS subjects caused increased connectivity strength but no change in network structure. In controls, simulated IEDs with physiological amplitudes and rates did not alter network strength or structure. CONCLUSIONS: Increases in connectivity strength in IS subjects are not artifacts caused by the interictal spike waveform and may be related to the underlying pathophysiology of IS. SIGNIFICANCE: Dynamic changes in EEG-based FCNs during IEDs may be valuable for identification of pathological networks associated with epilepsy.

Electroconvulsive therapy is regarded as the most effective antidepressant treatment for severe and treatment-resistant depressive episodes. Despite the efficacy of electroconvulsive therapy, the neurobiological underpinnings and mechanisms underlying electroconvulsive therapy induced antidepressant effects remain unclear. The objective of this investigation was to identify electroconvulsive therapy treatment responsive multimodal biomarkers with the 17-item Hamilton Depression Rating Scale guided brain structure-function fusion in 118 patients with depressive episodes and 60 healthy controls. Results show that reduced fractional amplitude of low frequency fluctuations in the prefrontal cortex, insula and hippocampus, linked with increased gray matter volume in anterior cingulate, medial temporal cortex, insula, thalamus, caudate and hippocampus represent electroconvulsive therapy responsive covarying functional and structural brain networks. In addition, relative to nonresponders, responder-specific electroconvulsive therapy related brain networks occur in frontal-limbic network and are associated with successful therapeutic outcomes. Finally, electroconvulsive therapy responsive brain networks were unrelated to verbal declarative memory. Using a data-driven, supervised-learning method, we demonstrated that electroconvulsive therapy produces a remodeling of brain functional and structural covariance that was unique to antidepressant symptom response, but not linked to memory impairment.

Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

The locus coeruleus (LC) regulates attention via the release of norepinephrine (NE), with levels of tonic LC activity constraining the intensity of phasic LC responses. In the current fMRI study, we used isometric handgrip to modulate tonic LC-NE activity in older women and in young women with different hormone statuses during the time period immediately after the handgrip. During this post-handgrip time, an oddball detection task was used to probe how changes in tonic arousal influenced functional coordination between the LC and a right frontoparietal network that supports attentional selectivity. As expected, the frontoparietal network responded more to infrequent target and novel sounds than to frequent sounds. Across participants, greater LC-frontoparietal functional connectivity, pupil dilation, and faster oddball detection were all positively associated with LC MRI structural contrast from a neuromelanin-sensitive scan. Thus, LC structure was related to LC functional dynamics and attentional performance during the oddball task. We also found that handgrip influenced pupil and attentional processing during a subsequent oddball task. Handgrip decreased subsequent tonic pupil size, increased phasic pupil responses to oddball sounds, speeded oddball detection speed, and increased frontoparietal network activation, suggesting that inducing strong LC activity benefits attentional performance in the next few minutes, potentially due to reduced tonic LC activity. In addition, older women showed a similar benefit of handgrip on frontoparietal network activation as younger women, despite showing lower frontoparietal network activation overall. Together these findings suggest that a simple exercise may improve selective attention in healthy aging, at least for several minutes afterwards.

People often behave differently when they know they are being watched. Here, we report the first investigation of whether such social presence effects also include brain monitoring technology, and also their impacts on the measured neural activity. We demonstrate that merely informing participants that fMRI has the potential to observe (thought-related) brain activity is sufficient to trigger changes in functional connectivity within and between relevant brain networks that have been previously associated selectively with executive and attentional control as well as self-relevant processing, social cognition, and theory of mind. These results demonstrate that an implied social presence, mediated here by recording brain activity with fMRI, can alter brain functional connectivity. These data provide a new manipulation of social attention, as well as shining light on a methodological hazard for researchers using equipment to monitor brain activity.

BACKGROUND: Multiple psychopathologies feature impaired clinical insight. Emerging evidence suggests that insight problems may similarly characterize addiction, perhaps due to aberrant functioning of self-referential brain circuitry, including the rostral anterior cingulate and ventromedial prefrontal cortices (rACC/vmPFC). We developed a new fMRI task to probe whether rACC/vmPFC abnormalities in cocaine use disorder (CUD) constitute neural correlates of readiness to change, one facet of insight. METHODS: Eighteen individuals with current CUD and 15 healthy controls responded about their own need to change their drug use and eating behavior (control condition) and the need for a named acquaintance to do the same (two additional control conditions). Measures of simulated drug-choice behavior, addiction severity, and neuropsychological function were collected outside the scanner. RESULTS: CUD participants perceived a greater need for behavior change than controls (as expected, given their diagnosis), but fell short of agreeing to a need for change; in CUD, lower perceived need correlated with higher simulated drug-choice behavior, a proxy measure of drug-seeking. During drug-related insight judgments, CUD participants had higher activation than controls in an anatomically-defined region of interest (ROI) in the medial orbitofrontal cortex, part of the rACC/vmPFC. Although not showing group differences, activation in an anatomically-defined ACC ROI correlated with insight-related task behavior (in all participants) and memory performance (in CUD). CONCLUSIONS: As a group, individuals with current CUD appear to show mild insight problems and rACC/vmPFC abnormalities vis-à-vis readiness to change behavior. With replication and extension of these results, insight-related circuitry may emerge as a novel therapeutic target.

Targeting mitochondrial ion homeostasis using Kaempferol, a mitochondrial Ca2+ uniporter channel activator, improves energy metabolism and behavior soon after a traumatic brain injury (TBI) in developing rats. Because of broad TBI pathophysiology and brain mitochondrial heterogeneity, Kaempferol-mediated early-stage behavioral and brain metabolic benefits may accrue from diverse sources within the brain. We hypothesized that Kaempferol influences TBI outcome by differentially impacting the neural, vascular, and synaptic/axonal compartments. After TBI at early development (P31), functional magnetic resonance imaging and diffusion tensor imaging (DTI) were applied to determine imaging outcomes at adolescence (2 months post-injury). Vehicle and Kaempferol treatments were made at 1, 24, and 48 h post-TBI, and their effects were assessed at adolescence. A significant increase in neural connectivity was observed after Kaempferol treatment as assessed by the spatial extent and strength of the somatosensory cortical and hippocampal resting-state functional connectivity (RSFC) networks. However, no significant RSFC changes were observed in the thalamus. DTI measures of fractional anisotropy (FA) and apparent diffusion coefficient, representing synaptic/axonal and microstructural integrity, showed significant improvements after Kaempferol treatment, with highest changes in the frontal and parietal cortices and hippocampus. Kaempferol treatment also increased corpus callosal FA, indicating measurable improvement in the interhemispheric structural connectivity. TBI prognosis was significantly altered at adolescence by early Kaempferol treatment, with improved neural connectivity, neurovascular coupling, and parenchymal microstructure in select brain regions. However, Kaempferol failed to improve vasomotive function across the whole brain, as measured by cerebrovascular reactivity. The differential effects of Kaempferol treatment on various brain functional compartments support diverse cellular-level mitochondrial functional outcomes in vivo.

Negative symptoms are core contributors to vocational and social deficits in schizophrenia (SZ). Available antipsychotic medications typically fail to reduce these symptoms. The neurohormone oxytocin (OT) is a promising treatment for negative symptoms, given its role in complex social behaviors mediated by the amygdala. In sample 1, we used a double-blind, placebo-controlled, crossover design to test the effects of a single dose of intranasal OT on amygdala resting-state functional connectivity (rsFC) in SZ (n = 22) and healthy controls (HC, n = 24) using a whole-brain corrected approach: we identified regions for which OT modulated SZ amygdala rsFC, assessed whether OT-modulated circuits were abnormal in SZ relative to HC on placebo, and evaluated whether connectivity on placebo and OT-induced connectivity changes correlated with baseline negative symptoms in SZ. Given our modest sample size, we used a second SZ (n = 183) and HC (n = 178) sample to replicate any symptom correlations. In sample 1, OT increased rsFC between the amygdala and left middle temporal gyrus, superior temporal sulcus, and angular gyrus (MTG/STS/AngG) in SZ compared to HC. Further, SZ had hypo-connectivity in this circuit compared to HC on placebo. More severe negative symptoms correlated with less amygdala-to-left-MTG/STS/AngG connectivity on placebo and with greater OT-induced connectivity increases. In sample 2, we replicated the correlation between amygdala-left-MTG/STS/AngG hypo-connectivity and negative symptoms, finding a specific association with expressive negative symptoms. These data suggest intranasal OT can normalize functional connectivity in an amygdala-to-left-MTG/STS/AngG circuit that contributes to negative symptoms in SZ.

Ketamine infusion therapy can produce fast-acting antidepressant effects in patients with major depressive disorder (MDD). Yet, how single and repeated ketamine treatment induces brain systems-level neuroplasticity underlying symptom improvement is unknown. Advanced multiband imaging (MB) pseudo-continuous arterial spin labeling (pCASL) perfusion MRI data was acquired from patients with treatment resistant depression (TRD) (N = 22, mean age=35.2 ± 9.95 SD, 27% female) at baseline, and 24 h after receiving single, and four subanesthetic (0.5 mg/kg) intravenous ketamine infusions. Changes in global and regional CBF were compared across time points, and relationships with overall mood, anhedonia and apathy were examined. Comparisons between patients at baseline and controls (N = 18, mean age=36.11 ± 14.5 SD, 57% female) established normalization of treatment effects. Results showed increased regional CBF in the cingulate and primary and higher-order visual association regions after first ketamine treatment. Baseline CBF in the fusiform, and acute changes in CBF in visual areas were related to symptom improvement after single and repeated ketamine treatment, respectively. In contrast, after serial infusion therapy, decreases in regional CBF were observed in the bilateral hippocampus and right insula with ketamine treatment. Findings demonstrate that neurophysiological changes occurring with single and repeated ketamine treatment follow both a regional and temporal pattern including sensory and limbic regions. Initial changes are observed in the posterior cingulate and precuneus and primary and higher-order visual areas, which relate to clinical responses. However, repeated exposure to ketamine, though not relating to clinical outcome, appears to engage deeper limbic structures and insula. ClinicalTrials.gov: Biomarkers of Fast Acting Therapies in Major Depression, https://clinicaltrials.gov/ct2/show/NCT02165449, NCT02165449.

Neurological disorders affecting human memory present a major scientific, medical, and societal challenge. Direct or indirect deep brain stimulation (DBS) of the entorhinal-hippocampal system, the brain's major memory hub, has been studied in people with epilepsy or Alzheimer's disease, intending to enhance memory performance or slow memory decline. Variability in the spatiotemporal parameters of stimulation employed to date notwithstanding, it is likely that future DBS for memory will employ closed-loop, nuanced approaches that are synergistic with native physiological processes. The potential for editing human memory-decoding, enhancing, incepting, or deleting specific memories-suggests exciting therapeutic possibilities but also raises considerable ethical concerns.

ObjectivesAdult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy.MethodsThe authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region.ResultsPrincipal component 3 was a statistically significant predictor of the presence of depressive symptoms (R2=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power.ConclusionsThese finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.

BackgroundMultiple psychopathologies feature impaired clinical insight. Emerging evidence suggests that insight problems may similarly characterize addiction, perhaps due to aberrant functioning of self-referential brain circuitry, including the rostral anterior cingulate and ventromedial prefrontal cortices (rACC/vmPFC). We developed a new fMRI task to probe whether rACC/vmPFC abnormalities in cocaine use disorder (CUD) constitute neural correlates of readiness to change, one facet of insight.MethodsEighteen individuals with current CUD and 15 healthy controls responded about their own need to change their drug use and eating behavior (control condition) and the need for a named acquaintance to do the same (two additional control conditions). Measures of simulated drug-choice behavior, addiction severity, and neuropsychological function were collected outside the scanner.ResultsCUD participants perceived a greater need for behavior change than controls (as expected, given their diagnosis), but fell short of "agreeing" to a need for change; in CUD, lower perceived need correlated with higher simulated drug-choice behavior, a proxy measure of drug-seeking. During drug-related insight judgments, CUD participants had higher activation than controls in an anatomically-defined region of interest (ROI) in the medial orbitofrontal cortex, part of the rACC/vmPFC. Although not showing group differences, activation in an anatomically-defined ACC ROI correlated with insight-related task behavior (in all participants) and memory performance (in CUD).ConclusionsAs a group, individuals with current CUD appear to show mild insight problems and rACC/vmPFC abnormalities vis-à-vis readiness to change behavior. With replication and extension of these results, insight-related circuitry may emerge as a novel therapeutic target.

Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.

Epidemiological studies suggest that insulin resistance accelerates progression of age-based cognitive impairment, which neuroimaging has linked to brain glucose hypometabolism. As cellular inputs, ketones increase Gibbs free energy change for ATP by 27% compared to glucose. Here we test whether dietary changes are capable of modulating sustained functional communication between brain regions (network stability) by changing their predominant dietary fuel from glucose to ketones. We first established network stability as a biomarker for brain aging using two large-scale (n = 292, ages 20 to 85 y; n = 636, ages 18 to 88 y) 3 T functional MRI (fMRI) datasets. To determine whether diet can influence brain network stability, we additionally scanned 42 adults, age < 50 y, using ultrahigh-field (7 T) ultrafast (802 ms) fMRI optimized for single-participant-level detection sensitivity. One cohort was scanned under standard diet, overnight fasting, and ketogenic diet conditions. To isolate the impact of fuel type, an independent overnight fasted cohort was scanned before and after administration of a calorie-matched glucose and exogenous ketone ester (d-β-hydroxybutyrate) bolus. Across the life span, brain network destabilization correlated with decreased brain activity and cognitive acuity. Effects emerged at 47 y, with the most rapid degeneration occurring at 60 y. Networks were destabilized by glucose and stabilized by ketones, irrespective of whether ketosis was achieved with a ketogenic diet or exogenous ketone ester. Together, our results suggest that brain network destabilization may reflect early signs of hypometabolism, associated with dementia. Dietary interventions resulting in ketone utilization increase available energy and thus may show potential in protecting the aging brain.

Compulsive eating characterizes many binge-related eating disorders, yet its neurobiological basis is poorly understood. The insular cortex subserves visceral-emotional functions, including taste processing, and is implicated in drug craving and relapse. Here, via optoinhibition, we implicate projections from the anterior insular cortex to the nucleus accumbens as modulating highly compulsive-like food self-administration behaviors that result from intermittent access to a palatable, high-sucrose diet. We identified compulsive-like eating behavior in female rats through progressive ratio schedule self-administration and punishment-resistant responding, food reward tolerance and escalation of intake through 24-h energy intake and fixed-ratio operant self-administration sessions, and withdrawal-like irritability through the bottle brush test. We also identified an endocrine profile of heightened GLP-1 and PP but lower ghrelin that differentiated rats with the most compulsive-like eating behavior. Measures of compulsive eating severity also directly correlated to leptin, body weight and adiposity. Collectively, this novel model of compulsive-like eating symptoms demonstrates adaptations in insula-ventral striatal circuitry and metabolic regulatory hormones that warrant further study.

Auditory cortex neurons nonlinearly integrate synaptic inputs from the thalamus and cortex, and generate spiking outputs for simple and complex sounds. Directly comparing synaptic and spiking activity can determine whether this input-output transformation is stimulus-dependent. We employ in vivo whole-cell recordings in the mouse primary auditory cortex, using pure tones and broadband dynamic moving ripple stimuli, to examine properties of functional integration in tonal (TRFs) and spectrotemporal (STRFs) receptive fields. Spectral tuning in STRFs derived from synaptic, subthreshold and spiking responses proves to be substantially more selective than for TRFs. We describe diverse spectral and temporal modulation preferences and distinct nonlinearities, and their modifications between the input and output stages of neural processing. These results characterize specific processing differences at the level of synaptic convergence, integration and spike generation resulting in stimulus-dependent transformation patterns in the primary auditory cortex.

Severe loss of excitatory synapses in key brain regions is thought to be one of the major mechanisms underlying stress-induced cognitive impairment. To date, however, the identity of the affected circuits remains elusive. Here we examined the effect of exposure to repeated multiple concurrent stressors (RMS) on the connectivity of the posterior parietal cortex (PPC) in adolescent male mice. We found that RMS led to layer-specific elimination of excitatory synapses with the most pronounced loss observed in deeper cortical layers. Quantitative analysis of cortical projections to the PPC revealed a significant loss of sensory and retrosplenial inputs to the PPC while contralateral and frontal projections were preserved. These results were confirmed by decreased synaptic strength from sensory, but not from contralateral, projections in stress-exposed animals. Functionally, RMS disrupted visuospatial working memory performance, implicating disrupted higher-order visual processing. These effects were not observed in mice subjected to restraint-only stress for an identical period of time. The PPC is considered to be a cortical hub for multisensory integration, working memory, and perceptual decision-making. Our data suggest that sensory information streams targeting the PPC may be impacted by recurring stress, likely contributing to stress-induced cognitive impairment.SIGNIFICANCE STATEMENT Repeated exposure to stress profoundly impairs cognitive functions like memory, attention, or decision-making. There is emerging evidence that stress not only impacts high-order regions of the brain, but may affect earlier stages of cognitive processing. Our work focuses on the posterior parietal cortex, a brain region supporting short-term memory, multisensory integration, and decision-making. We show evidence that repeated stress specifically damages sensory inputs to this region. This disruption of synaptic connectivity is linked to working memory impairment and is specific to repeated exposure to multiple stressors. Altogether, our data provide a potential alternative explanation to ailments previously attributed to downstream, cognitive brain structures.

Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8-22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.

ObjectiveTo investigate the topographic arrangement and strength of whole-brain white matter (WM) structural connectivity in patients with early-stage drug-naive Parkinson disease (PD).MethodsWe employed a model-free data-driven approach for computing whole-brain WM topologic arrangement and connectivity strength between brain regions by utilizing diffusion MRI of 70 participants with early-stage drug-naive PD and 41 healthy controls. Subsequently, we generated a novel group-specific WM anatomical network by minimizing variance in anatomical connectivity of each group. Global WM connectivity strength and network measures were computed on this group-specific WM anatomical network and were compared between the groups. We tested correlations of these network measures with clinical measures in PD to assess their pathophysiologic relevance.ResultsPD-relevant cortical and subcortical regions were identified in the novel PD-specific WM anatomical network. Impaired modular organization accompanied by a correlation of network measures with multiple clinical variables in early PD were revealed. Furthermore, disease duration was negatively correlated with global connectivity strength of the PD-specific WM anatomical network.ConclusionBy minimizing variance in anatomical connectivity, this study found the presence of a novel WM structural connectome in early PD that correlated with clinical symptoms, despite the lack of a priori analytic assumptions. This included the novel finding of increased structural connectivity between known PD-relevant brain regions. The current study provides a framework for further investigation of WM structural changes underlying the clinical and pathologic heterogeneity of PD.

Memories of positive experiences link places, events, and reward outcomes. These memories recruit interactions between the hippocampus and nucleus accumbens (NAc). Both dorsal and ventral hippocampus (dH and vH) project to the NAc, but it remains unknown whether dH and vH act in concert or separately to engage NAc representations related to space and reward. We recorded simultaneously from the dH, vH, and NAc of rats during an appetitive spatial task and focused on hippocampal sharp-wave ripples (SWRs) to identify times of memory reactivation across brain regions. Here, we show that dH and vH awake SWRs occur asynchronously and activate distinct and opposing patterns of NAc spiking. Only NAc neurons activated during dH SWRs were tuned to task- and reward-related information. These temporally and anatomically separable hippocampal-NAc interactions point to distinct channels of mnemonic processing in the NAc, with the dH-NAc channel specialized for spatial task and reward information. VIDEO ABSTRACT.

The functional organization of the hippocampus is distributed as a gradient along its longitudinal axis that explains its differential interaction with diverse brain systems. We show that the location of human tissue samples extracted along the longitudinal axis of the adult human hippocampus can be predicted within 2mm using the expression pattern of less than 100 genes. Futhermore, this model generalizes to an external set of tissue samples from prenatal human hippocampi. We examine variation in this specific gene expression pattern across the whole brain, finding a distinct anterioventral-posteriodorsal gradient. We find frontal and anterior temporal regions involved in social and motivational behaviors, and more functionally connected to the anterior hippocampus, to be clearly differentiated from posterior parieto-occipital regions involved in visuospatial cognition and more functionally connected to the posterior hippocampus. These findings place the human hippocampus at the interface of two major brain systems defined by a single molecular gradient.

Previous work suggests that sleep disruption can contribute to poor pain modulation. Here, we used experimental sleep disruption to examine the relationship between sleep disruption-induced pain sensitivity and functional connectivity (FC) of cognitive networks contributing to pain modulation. Nineteen healthy individuals underwent two counterbalanced experimental sleep conditions for one night each: uninterrupted sleep versus sleep disruption. Following each condition, participants completed functional MRI including a simple motor task and a noxious thermal stimulation task. Pain ratings and stimulus temperatures from the latter task were combined to calculate a pain sensitivity change score following sleep disruption. This change score was used as a predictor of simple motor task FC changes using bilateral executive control networks (RECN, LECN) and the default mode network (DMN) masks as seed regions of interest (ROIs). Increased pain sensitivity after sleep disruption was positively associated with increased RECN FC to ROIs within the DMN and LECN (F(4,14) = 25.28, pFDR = 0.05). However, this pain sensitivity change score did not predict FC changes using LECN and DMN masks as seeds (pFDR > 0.05). Given that only RECN FC was associated with sleep loss-induced hyperalgesia, findings suggest that cognitive networks only partially contribute to the sleep-pain dyad.

Intrinsic connectivity networks (ICNs) identified through task-free fMRI (tf-fMRI) offer the opportunity to investigate human brain circuits involved in language processes without requiring participants to perform challenging cognitive tasks. In this study, we assessed the ability of tf-fMRI to isolate reproducible networks critical for specific language functions and often damaged in primary progressive aphasia (PPA). First, we performed whole-brain seed-based correlation analyses on tf-fMRI data to identify ICNs anchored in regions known for articulatory, phonological, and semantic processes in healthy male and female controls (HCs). We then evaluated the reproducibility of these ICNs in an independent cohort of HCs, and recapitulated their functional relevance with a post hoc meta-analysis on task-based fMRI. Last, we investigated whether atrophy in these ICNs could inform the differential diagnosis of nonfluent/agrammatic, semantic, and logopenic PPA variants. The identified ICNs included a dorsal articulatory-phonological network involving inferior frontal and supramarginal regions; a ventral semantic network involving anterior middle temporal and angular gyri; a speech perception network involving superior temporal and sensorimotor regions; and a network between posterior inferior temporal and intraparietal regions likely linking visual, phonological, and attentional processes for written language. These ICNs were highly reproducible across independent groups and revealed areas consistent with those emerging from task-based meta-analysis. By comparing ICNs' spatial distribution in HCs with patients' atrophy patterns, we identified ICNs associated with each PPA variant. Our findings demonstrate the potential use of tf-fMRI to investigate the functional status of language networks in patients for whom activation studies can be methodologically challenging.SIGNIFICANCE STATEMENT We showed that a single, short, task-free fMRI acquisition is able to identify four reproducible and relatively segregated intrinsic left-dominant networks associated with articulatory, phonological, semantic, and multimodal orthography-to-phonology processes, in HCs. We also showed that these intrinsic networks relate to syndrome-specific atrophy patterns in primary progressive aphasia. Collectively, our results support the application of task-free fMRI in future research to study functionality of language circuits in patients for whom tasked-based activation studies might be methodologically challenging.

Cognitive faculties such as imagination, planning, and decision-making entail the ability to represent hypothetical experience. Crucially, animal behavior in natural settings implies that the brain can represent hypothetical future experience not only quickly but also constantly over time, as external events continually unfold. To determine how this is possible, we recorded neural activity in the hippocampus of rats navigating a maze with multiple spatial paths. We found neural activity encoding two possible future scenarios (two upcoming maze paths) in constant alternation at 8 Hz: one scenario per ∼125-ms cycle. Further, we found that the underlying dynamics of cycling (both inter- and intra-cycle dynamics) generalized across qualitatively different representational correlates (location and direction). Notably, cycling occurred across moving behaviors, including during running. These findings identify a general dynamic process capable of quickly and continually representing hypothetical experience, including that of multiple possible futures.

Higher cognitive functioning is supported by adaptive reconfiguration of large-scale functional brain networks. Cognitive control (CC), which plays a vital role in flexibly guiding cognition and behavior in accordance with our goals, supports a range of executive functions via distributed brain networks. These networks process information dynamically and can be represented as functional connectivity changes between network elements. Using graph theory, we explored context-dependent network reorganization in 56 healthy adults performing fMRI tasks from two cognitive domains that varied in CC and episodic-memory demands. We examined whole-brain modular structure during the DPX task, which engages proactive CC in the frontal-parietal cognitive-control network (FPN), and the RiSE task, which manipulates CC demands at encoding and retrieval during episodic-memory processing, and engages FPN, the medial-temporal lobe and other memory-related networks in a context dependent manner. Analyses revealed different levels of network integration and segregation. Modularity analyses revealed greater brain-wide integration across tasks in high CC conditions compared to low CC conditions. Greater network reorganization occurred in the RiSE memory task, which is thought to require coordination across multiple brain networks, than in the DPX cognitive-control task. Finally, FPN, ventral attention, and visual systems showed within network connectivity effects of cognitive control; however, these cognitive systems displayed varying levels of network reorganization. These findings provide insight into how brain networks reorganize to support differing task contexts, suggesting that the FPN flexibly segregates during focused proactive control and integrates to support control in other domains such as episodic memory.

Endel Tulving's proposal that episodic memory is distinct from other memory systems like semantic memory remains an extremely influential idea in cognitive neuroscience research. As originally suggested by Tulving, episodic memory involves three key components that differentiate it from all other memory systems: spatiotemporal binding, mental time travel, and autonoetic consciousness. Here, we focus on the idea of spatiotemporal binding in episodic memory and, in particular, how consideration of the precision of spatiotemporal context helps expand our understanding of episodic memory. Precision also helps shed light on another key issue in cognitive neuroscience, the role of the hippocampus outside of episodic memory in perception, attention, and working memory. By considering precision alongside item-context bindings, we attempt to shed new light on both the nature of how we represent context and what roles the hippocampus plays in episodic memory and beyond.

Much research in cognitive neuroscience supports prediction as a canonical computation of cognition across domains. Is such predictive coding implemented by feedback from higher-order domain-general circuits, or is it locally implemented in domain-specific circuits? What information sources are used to generate these predictions? This study addresses these two questions in the context of language processing. We present fMRI evidence from a naturalistic comprehension paradigm (1) that predictive coding in the brain's response to language is domain-specific, and (2) that these predictions are sensitive both to local word co-occurrence patterns and to hierarchical structure. Using a recently developed continuous-time deconvolutional regression technique that supports data-driven hemodynamic response function discovery from continuous BOLD signal fluctuations in response to naturalistic stimuli, we found effects of prediction measures in the language network but not in the domain-general multiple-demand network, which supports executive control processes and has been previously implicated in language comprehension. Moreover, within the language network, surface-level and structural prediction effects were separable. The predictability effects in the language network were substantial, with the model capturing over 37% of explainable variance on held-out data. These findings indicate that human sentence processing mechanisms generate predictions about upcoming words using cognitive processes that are sensitive to hierarchical structure and specialized for language processing, rather than via feedback from high-level executive control mechanisms.

Although both resting and task-induced functional connectivity (FC) have been used to characterize the human brain and cognitive abilities, the potential of task-induced FCs in individualized prediction for out-of-scanner cognitive traits remains largely unexplored. A recent study Greene et al. (2018) predicted the fluid intelligence scores using FCs derived from rest and multiple task conditions, suggesting that task-induced brain state manipulation improved prediction of individual traits. Here, using a large dataset incorporating fMRI data from rest and 7 distinct task conditions, we replicated the original study by employing a different machine learning approach, and applying the method to predict two reading comprehension-related cognitive measures. Consistent with their findings, we found that task-based machine learning models often outperformed rest-based models. We also observed that combining multi-task fMRI improved prediction performance, yet, integrating the more fMRI conditions can not necessarily ensure better predictions. Compared with rest, the predictive FCs derived from language and working memory tasks were highlighted with more predictive power in predominantly default mode and frontoparietal networks. Moreover, prediction models demonstrated high stability to be generalizable across distinct cognitive states. Together, this replication study highlights the benefit of using task-based FCs to reveal brain-behavior relationships, which may confer more predictive power and promote the detection of individual differences of connectivity patterns underlying relevant cognitive traits, providing strong evidence for the validity and robustness of the original findings.

Background/objectivesThe salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function.Subjects/methodsMonozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin, and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders.ResultsSN connectivity was reduced by a meal ingestion (β = -0.20; P