Determining Excitatory and Inhibitory Neuronal Activity from Multimodal fMRI Data Using a Generative Hemodynamic Model

Characterization of Dnajc12 knockout mice, a model of hypodopaminergia

Homozygous DNAJC12 c.79-2A>G (p. V27Wfs*14) loss-of-function mutations were first reported as a cause of young-onset Parkinson's disease. However, bi-allelic autosomal recessive pathogenic variants in DNAJC12 may lead to an alternative constellation of neurological features including infantile dystonia, developmental delay, intellectual disability and neuropsychiatric disorders. DNAJC12 is understood to co-chaperone aromatic amino acid hydroxylases to enhance the synthesis of biogenic amines. In vitro , we confirm overexpressed DNAJC12 forms a complex with tyrosine hydroxylase, the rate-limiting enzyme in dopamine (DA) synthesis. Now we describe a conditional knockout mouse (cDKO) in which loxP sites flanking Dnajc12 exon 2 enable its excision by cre-recombinase to create a constitutive Dnajc12 knock out (DKO). At three months of age, DKO animals exhibit reduced locomotion and exploratory behavior in automated open-field testing. DKO mice also manifest increased plasma phenylalanine levels, a cardinal feature of patients with DNAJC12 pathogenic variants. In striatal tissue, total DA and serotonin, and their metabolites, are reduced. Biochemical alterations in synaptic proteins and tyrosine hydroxylase are also apparent, with enhanced phosphorylation of pSer31 and pSer40 sites that may reflect biological compensation. Electrically-evoked striatal DA is reduced. Most immediately, cDKO and DKO mice present models to develop and refined therapeutic approaches for the treatment of DNAJC12 dystonia and parkinsonism. These models may also enable the pleiotropic functions of biogenic amines (including DA) to be individually investigated in the brain and periphery.

Label-free photoacoustic computed tomography of visually evoked responses in the primary visual cortex and four subcortical retinorecipient nuclei of anesthetized mice

Significance

Many techniques exist for screening retinal phenotypes in mouse models in vision research, but significant challenges remain for efficiently probing higher visual centers of the brain. Photoacoustic computed tomography (PACT), with optical sensitivity to hemodynamic response (HR) in brain and ultrasound resolution, provides unique advantages in comprehensively assessing higher visual function in the mouse brain.

Aim

We aim to examine the reliability of PACT in the functional phenotyping of mouse models for vision research.

Approach

A PACT-ultrasound (US) parallel imaging system was established with a one-dimensional (1D) US transducer array and a tunable laser. Imaging was performed at three coronal planes of the brain, covering the primary visual cortex and the four subcortical nuclei, including the superior colliculus, the dorsal lateral geniculate nucleus, the suprachiasmatic nucleus, and the olivary pretectal nucleus. The visual-evoked HR was isolated from background signals using an impulse-based data processing protocol. rd1 mice with rod/cone degeneration, melanopsin-knockout (mel-KO) mice with photoreceptive ganglion cells that lack intrinsic photosensitivity, and wild-type mice as controls were imaged. The quantitative characteristics of the visual-evoked HR were compared.

Results

Quantitative analysis of the HRs shows significant differences among the three mouse strains: (1) rd1 mice showed both smaller and slower responses compared with wild type ( n = 10,10 , p < 0.01 ) and (2) mel-KO mice had lower amplitude but not significantly delayed photoresponses than wild-type mice ( n = 10,10 , p < 0.01 ). These results agree with the known visual deficits of the mouse strains.

Conclusions

PACT demonstrated sufficient sensitivity to detecting post-retinal functional deficits.

Lateral Orbitofrontal Cortex Encodes Presence of Risk and Subjective Risk Preference During Decision-Making

Adaptive decision-making requires consideration of objective risks and rewards associated with each option, as well as subjective preference for risky/safe alternatives. Inaccurate risk/reward estimations can engender excessive risk-taking, a central trait in many psychiatric disorders. The lateral orbitofrontal cortex (lOFC) has been linked to many disorders associated with excessively risky behavior and is ideally situated to mediate risky decision-making. Here, we used single-unit electrophysiology to measure neuronal activity from lOFC of freely moving rats performing in a punishment-based risky decision-making task. Subjects chose between a small, safe reward and a large reward associated with either 0% or 50% risk of concurrent punishment. lOFC activity repeatedly encoded current risk in the environment throughout the decision-making sequence, signaling risk before, during, and after a choice. In addition, lOFC encoded reward magnitude, although this information was only evident during action selection. A Random Forest classifier successfully used neural data accurately to predict the risk of punishment in any given trial, and the ability to predict choice via lOFC activity differentiated between and risk-preferring and risk-averse rats. Finally, risk preferring subjects demonstrated reduced lOFC encoding of risk and increased encoding of reward magnitude. These findings suggest lOFC may serve as a central decision-making hub in which external, environmental information converges with internal, subjective information to guide decision-making in the face of punishment risk.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Metabolic energetics underlying attractors in neural models

Neural population modeling, including the role of neural attractors, is a promising tool for understanding many aspects of brain function. We propose a modeling framework to connect the abstract variables used in modeling to recent cellular-level estimates of the bioenergetic costs of different aspects of neural activity, measured in ATP consumed per second per neuron. Based on recent work, an empirical reference for brain ATP use for the awake resting brain was estimated as ∼2 × 109 ATP/s-neuron across several mammalian species. The energetics framework was applied to the Wilson-Cowan (WC) model of two interacting populations of neurons, one excitatory (E) and one inhibitory (I). Attractors were considered to exhibit steady-state behavior and limit cycle behavior, both of which end when the excitatory stimulus ends, and sustained activity that persists after the stimulus ends. The energy cost of limit cycles, with oscillations much faster than the average neuronal firing rate of the population, is tracked more closely with the firing rate than the limit cycle frequency. Self-sustained firing driven by recurrent excitation, though, involves higher firing rates and a higher energy cost. As an example of a simple network in which each node is a WC model, a combination of three nodes can serve as a flexible circuit element that turns on with an oscillating output when input passes a threshold and then persists after the input ends (an "on-switch"), with moderate overall ATP use. The proposed framework can serve as a guide for anchoring neural population models to plausible bioenergetics requirements.NEW & NOTEWORTHY This work bridges two approaches for understanding brain function: cellular-level studies of the metabolic energy costs of different aspects of neural activity and neural population modeling, including the role of neural attractors. The proposed modeling framework connects energetic costs, in ATP consumed per second per neuron, to the more abstract variables used in neural population modeling. In particular, this work anchors potential neural attractors to physiologically plausible bioenergetics requirements.

Inhibitory temporo-parietal effective connectivity is associated with explicit memory performance in older adults

Successful explicit memory encoding is associated with inferior temporal activations and medial parietal deactivations, which are attenuated in aging. Here we used dynamic causal modeling (DCM) of functional magnetic resonance imaging data to elucidate effective connectivity patterns between hippocampus, parahippocampal place area (PPA), and precuneus during encoding of novel visual scenes. In 117 young adults, DCM revealed pronounced activating input from the PPA to the hippocampus and inhibitory connectivity from the PPA to the precuneus during novelty processing, with both being enhanced during successful encoding. This pattern could be replicated in two cohorts (N = 141 and 148) of young and older adults. In both cohorts, older adults selectively exhibited attenuated inhibitory PPA-precuneus connectivity, which correlated negatively with memory performance. Our results provide insight into the network dynamics underlying explicit memory encoding and suggest that age-related differences in memory-related network activity are, at least partly, attributable to altered temporo-parietal neocortical connectivity.

Lysosomal proteomics reveals mechanisms of neuronal apoE4associated lysosomal dysfunction

ApoE4 is the primary risk factor for Alzheimer's Disease. While apoE is primarily expressed by astrocytes, AD pathology including endosomal abnormalities and mitochondrial dysfunction first occurs in neurons. Lysosomes are poised at the convergence point between these features. We find that apoE4-expressing cells exhibit lysosomal alkalinization, reduced lysosomal proteolysis, and impaired mitophagy. To identify driving factors for this lysosomal dysfunction, we performed quantitative lysosomal proteome profiling. This revealed that apoE4 expression results in lysosomal depletion of Lgals3bp and accumulation of Tmed5 in both Neuro-2a cells and postmitotic human neurons. Modulating the expression of both proteins affected lysosomal function, with Tmed5 knockdown rescuing lysosomal alkalinization in apoE4 cells, and Lgals3bp knockdown causing lysosomal alkalinization and reduced lysosomal density in apoE3 cells. Taken together, our work reveals that apoE4 exerts gain-of-toxicity by alkalinizing the lysosomal lumen, pinpointing lysosomal Tmed5 accumulation and Lgals3bp depletion as apoE4-associated drivers for this phenotype.

Regulation of astrocyte metabolism by mitochondrial translocator protein 18kDa

The mitochondrial translocator protein 18kDa (TSPO) has been linked to a variety of functions from steroidogenesis to regulation of cellular metabolism and is an attractive therapeutic target for chronic CNS inflammation. Studies in the periphery using Leydig cells and hepatocytes, as well as work in microglia, indicate that the function of TSPO may vary between cells depending on their specialised roles. Astrocytes are critical for providing trophic and metabolic support in the brain as part of their role in maintaining brain homeostasis. Recent work has highlighted that TSPO expression increases in astrocytes under inflamed conditions and may drive astrocyte reactivity. However, relatively little is known about the role TSPO plays in regulating astrocyte metabolism and whether this protein is involved in immunometabolic processes in these cells. Using TSPO-deficient (TSPO-/-) mouse primary astrocytes in vitro (MPAs) and a human astrocytoma cell line (U373 cells), we performed metabolic flux analyses. We found that loss of TSPO reduced basal astrocyte respiration and increased the bioenergetic response to glucose reintroduction following glucopenia, while increasing fatty acid oxidation (FAO). Lactate production was significantly reduced in TSPO-/- astrocytes. Co-immunoprecipitation studies in U373 cells revealed that TSPO forms a complex with carnitine palmitoyltransferase 1a, which presents a mechanism wherein TSPO may regulate FAO in astrocytes. Compared to TSPO+/+ cells, inflammation induced by 3h lipopolysaccharide (LPS) stimulation of TSPO-/- MPAs revealed attenuated tumour necrosis factor release, which was enhanced in TSPO-/- MPAs at 24h LPS stimulation. Together these data suggest that while TSPO acts as a regulator of metabolic flexibility in astrocytes, loss of TSPO does not appear to modulate the metabolic response of astrocytes to inflammation, at least in response to the stimulus/time course used in this study.

Physiological modeling of the BOLD signal and implications for effective connectivity: A primer

In this primer, I provide an overview of the physiological processes that contribute to the observed BOLD signal (i.e., the generative biophysical model), including their time course properties within the framework of the physiologically-informed dynamic causal modeling (P-DCM). The BOLD signal is primarily determined by the change in paramagnetic deoxygenated hemoglobin, which results from combination of changes in oxygen metabolism, and cerebral blood flow and volume. Specifically, the physiological origin of the so-called BOLD signal "transients" will be discussed, including the initial overshoot, steady-state activation and the post-stimulus undershoot. I argue that incorrect physiological assumptions in the generative model of the BOLD signal can lead to incorrect inferences pertaining to both local neuronal activity and effective connectivity between brain regions. In addition, I introduce the recent laminar BOLD signal model, which extends P-DCM to cortical depths-resolved BOLD signals, allowing for laminar neuronal activity to be determined using high-resolution fMRI data.

Altered hippocampal connectivity dynamics predicts memory performance in neuropsychiatric lupus: a resting-state fMRI study using cross-recurrence quantification analysis

OBJECTIVE

Τo determine whole-brain and regional functional connectivity (FC) characteristics of patients with neuropsychiatric SLE (NPSLE) or without neuropsychiatric manifestations (non-NPSLE) and examine their association with cognitive performance.

METHODS

Cross-recurrence quantification analysis (CRQA) of resting-state functional MRI (rs-fMRI) data was performed in 44 patients with NPSLE, 20 patients without NPSLE and 35 healthy controls (HCs). Volumetric analysis of total brain and specific cortical and subcortical regions, where significant connectivity changes were identified, was performed. Cognitive status of patients with NPSLE was assessed by neuropsychological tests. Group comparisons on nodal FC, global network metrics and regional volumetrics were conducted, and associations with cognitive performance were estimated (at p<0.05 false discovery rate corrected).

RESULTS

FC in patients with NPSLE was characterised by increased modularity (mean (SD)=0.31 (0.06)) as compared with HCs (mean (SD)=0.27 (0.06); p=0.05), hypoconnectivity of the left (mean (SD)=0.06 (0.018)) and right hippocampi (mean (SD)=0.051 (0.0.16)), and of the right amygdala (mean (SD)=0.091 (0.039)), as compared with HCs (mean (SD)=0.075 (0.022), p=0.02; 0.065 (0.019), p=0.01; 0.14 (0.096), p=0.05, respectively). Hyperconnectivity of the left angular gyrus (NPSLE/HCs: mean (SD)=0.29 (0.26) and 0.10 (0.09); p=0.01), left (NPSLE/HCs: mean (SD)=0.16 (0.09) and 0.09 (0.05); p=0.01) and right superior parietal lobule (SPL) (NPSLE/HCs: mean (SD)=0.25 (0.19) and 0.13 (0.13), p=0.01) was noted in NPSLE versus HC groups. Among patients with NPSLE, verbal episodic memory scores were positively associated with connectivity (local efficiency) of the left hippocampus (r²=0.22, p=0.005) and negatively with local efficiency of the left angular gyrus (r²=0.24, p=0.003). Patients without NPSLE displayed hypoconnectivity of the right hippocampus (mean (SD)=0.056 (0.014)) and hyperconnectivity of the left angular gyrus (mean (SD)=0.25 (0.13)) and SPL (mean (SD)=0.17 (0.12)).

CONCLUSION

By using dynamic CRQA of the rs-fMRI data, distorted FC was found globally, as well as in medial temporal and parietal brain regions in patients with SLE, that correlated significantly and adversely with memory capacity in NPSLE. These results highlight the value of dynamic approaches to assessing impaired brain network function in patients with lupus with and without neuropsychiatric symptoms.

DnaJC7 specifically regulates tau seeding

Neurodegenerative tauopathies are caused by accumulation of toxic tau protein assemblies. This appears to involve template-based seeding events, whereby tau monomer changes conformation and is recruited to a growing aggregate. Several large families of chaperone proteins, including Hsp70s and J domain proteins (JDPs) cooperate to regulate the folding of intracellular proteins such as tau, but the factors that coordinate this activity are not well known. The JDP DnaJC7 binds tau and reduces its intracellular aggregation. However, it is unknown whether this is specific to DnaJC7 or if other JDPs might be similarly involved. We used proteomics within a cell model to determine that DnaJC7 co-purified with insoluble tau and colocalized with intracellular aggregates. We individually knocked out every possible JDP and tested the effect on intracellular aggregation and seeding. DnaJC7 knockout decreased aggregate clearance and increased intracellular tau seeding. This depended on the ability of the J domain (JD) of DnaJC7 to bind to Hsp70, as JD mutations that block binding to Hsp70 abrogated the protective activity. Disease-associated mutations in the JD and substrate binding site of DnaJC7 also abrogated its protective activity. DnaJC7 thus specifically regulates tau aggregation in cooperation with Hsp70.

Changes in hemodynamic response function components reveal specific changes in neurovascular coupling in type 2 diabetes

Type 2 Diabetes Mellitus (T2DM) is a metabolic disease that leads to multiple vascular complications with concomitant changes in human neurophysiology, which may lead to long-term cognitive impairment, and dementia. Early impairments of neurovascular coupling can be studied using event-related functional magnetic resonance imaging (fMRI) designs. Here, we aimed to characterize the changes in the hemodynamic response function (HRF) in T2DM to probe components from the initial dip to late undershoot. We investigated whether the HRF morphology is altered throughout the brain in T2DM, by extracting several parameters of the fMRI response profiles in 141 participants (64 patients with T2DM and 77 healthy controls) performing a visual motion discrimination task. Overall, the patients revealed significantly different HRFs, which extended to all brain regions, suggesting that this is a general phenomenon. The HRF in T2DM was found to be more sluggish, with a higher peak latency and lower peak amplitude, relative slope to peak, and area under the curve. It also showed a pronounced initial dip, suggesting that the initial avidity for oxygen is not compensated for, and an absent or less prominent but longer undershoot. Most HRF parameters showed a higher dispersion and variability in T2DM. In sum, we provide a definite demonstration of an impaired hemodynamic response function in the early stages of T2DM, following a previous suggestion of impaired neurovascular coupling. The quantitative demonstration of a significantly altered HRF morphology in separate response phases suggests an alteration of distinct physiological mechanisms related to neurovascular coupling, which should be considered in the future to potentially halt the deterioration of the brain function in T2DM.

Dynamic Effective Connectivity using Physiologically informed Dynamic Causal Model with Recurrent Units: A functional Magnetic Resonance Imaging simulation study

Functional MRI (fMRI) is an indirect reflection of neuronal activity. Using generative biophysical model of fMRI data such as Dynamic Causal Model (DCM), the underlying neuronal activities of different brain areas and their causal interactions (i.e., effective connectivity) can be calculated. Most DCM studies typically consider the effective connectivity to be static for a cognitive task within an experimental run. However, changes in experimental conditions during complex tasks such as movie-watching might result in temporal variations in the connectivity strengths. In this fMRI simulation study, we leverage state-of-the-art Physiologically informed DCM (P-DCM) along with a recurrent window approach and discretization of the equations to infer the underlying neuronal dynamics and concurrently the dynamic (time-varying) effective connectivities between various brain regions for task-based fMRI. Results from simulation studies on 3- and 10-region models showed that functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) responses and effective connectivity time-courses can be accurately predicted and distinguished from faulty graphical connectivity models representing cognitive hypotheses. In summary, we propose and validate a novel approach to determine dynamic effective connectivity between brain areas during complex cognitive tasks by combining P-DCM with recurrent units.

Challenging neurovascular coupling through complex and variable duration cognitive paradigms: A subcomponent analysis

A similar pattern of cerebral blood velocity (CBv) response has been observed for neurovascular coupling (NVC) assessment with cognitive tasks of varying complexity and duration. This lack of specificity could result from parallel changes in arterial blood pressure (BP) and PaCO₂, which could confound the estimates of NVC integrity. Healthy participants (n = 16) underwent recordings at rest (5 min sitting) and during randomized paradigms of different complexity (naming words (NW) beginning with P-, R-, V- words and serial subtractions (SS) of 100-2, 100-7, 1000-17, with durations of 5, 30 and 60 s). Bilateral CBv (middle cerebral arteries, transcranial Doppler), end-tidal CO₂ (EtCO₂, capnography), blood pressure (BP, Finapres) and heart rate (HR, ECG) were recorded continuously. The bilateral CBv response to all paradigms was classified under objective criteria to select only responders, then the repeated data were averaged between visits. Bilateral CBv change to tasks was decomposed into the relative contributions (subcomponents) of arterial BP (V_BP; neurogenic), critical closing pressure (V_CrCP; metabolic) and resistance area product (V_RAP; myogenic). A temporal effect was demonstrated in bilateral V_BP and V_RAP during all tasks (p<0.002), increased V_BP early (between 0 and 10 s) and followed by decreases of V_RAP late (25-35 s) in the response. V_CrCP varied by complexity and duration (p<0.046). The main contributions to CBv responses to cognitive tasks of different complexity and duration were V_BP and V_RAP, whilst a smaller contribution from V_CrCP would suggest sensitivity to metabolic demands. Further studies are needed to assess the influence of different paradigms, ageing and cerebrovascular conditions.

Reduced brain activity during a working memory task in middle-aged apolipoprotein E ε4 carriers with overweight/obesity

Objective

The apolipoprotein E ε4 (APOE ε4) allele and midlife obesity are independent risk factors for Alzheimer's disease (AD). Both of these risk factors are also associated with differences in brain activation, as measured by blood oxygenation level-dependent (BOLD) responses, in the absence of detectable cognitive deficits. Although the presence of these risk factors may influence brain activity during working memory tasks, no study to date has examined whether the presence of the ε4 allele explains variation in working memory brain activity while matching for levels of overweight/obesity. The primary aim of this study was to determine whether the presence of the ε4 allele is associated with differences in task-functional magnetic resonance imaging (fMRI) brain activation in adults with overweight/obesity. We predicted that ε4 carriers would have greater brain activation in regions that support working memory.

Methods

This ancillary study included 48 (n = 24 APOE ε4 carriers; n = 24 APOE ε4 non-carriers), sedentary middle-aged adults (Mean age = 44.63 ± 8.36 years) with overweight/obesity (Mean BMI = 32.43 ± 4.12 kg/m²) who were matched on demographic characteristics. Participants were a subsample enrolled in 12-month randomized clinical trial examining the impact of energy-restricted diet and exercise on cardiovascular health outcomes. Participants completed a n-back working memory task with fMRI, which were completed within one month of the start of the intervention. Participants also underwent pseudo-continuous arterial spin labeling scans, a MRI measure of cerebral blood flow (CBF).

Results

Compared to non-ε4 carriers with overweight/obesity, ε4 carriers with overweight/obesity had lower fMRI brain activity in the middle frontal gyrus, pre and post central gyrus, supramarginal gyrus, superior temporal gyrus, lateral occipital cortex, and angular gyrus (z range = 2.52-3.56) during the n-back working memory task. Differences persisted even when controlling for CBF in these brain regions.

Conclusion

These results indicate that presence of the APOE ε4 allele in middle-aged adults with overweight/obesity is related to altered brain activity during a working memory paradigm, which may confer risk for accelerated neurocognitive decline in late adulthood. Future research is needed to clarify the clinical implications of these findings in the context of risk for AD.

Multi-Echo Investigations of Positive and Negative CBF and Concomitant BOLD Changes: Positive and negative CBF and BOLD changes

Unlike the positive blood oxygenation level-dependent (BOLD) response (PBR), commonly taken as an indication of an 'activated' brain region, the physiological origin of negative BOLD signal changes (i.e. a negative BOLD response, NBR), also referred to as 'deactivation' is still being debated. In this work, an attempt was made to gain a better understanding of the underlying mechanism by obtaining a comprehensive measure of the contributing cerebral blood flow (CBF) and its relationship to the NBR in the human visual cortex, in comparison to a simultaneously induced PBR in surrounding visual regions. To overcome the low signal-to-noise ratio (SNR) of CBF measurements, a newly developed multi-echo version of a center-out echo planar-imaging (EPI) readout was employed with pseudo-continuous arterial spin labeling (pCASL). It achieved very short echo and inter-echo times and facilitated a simultaneous detection of functional CBF and BOLD changes at 3 T with improved sensitivity. Evaluations of the absolute and relative changes of CBF and the effective transverse relaxation rate,R₂^* the coupling ratios, and their dependence on CBF at rest, CBF_rest indicated differences between activated and deactivated regions. Analysis of the shape of the respective functional responses also revealed faster negative responses with more pronounced post-stimulus transients. Resulting differences in the flow-metabolism coupling ratios were further examined for potential distinctions in the underlying neuronal contributions.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

mGlu1 potentiation enhances prelimbic somatostatin interneuron activity to rescue schizophrenia-like physiological and cognitive deficits

Evidence for prefrontal cortical (PFC) GABAergic dysfunction is one of the most consistent findings in schizophrenia and may contribute to cognitive deficits. Recent studies suggest that the mGlu1 subtype of metabotropic glutamate receptor regulates cortical inhibition; however, understanding the mechanisms through which mGlu1 positive allosteric modulators (PAMs) regulate PFC microcircuit function and cognition is essential for advancing these potential therapeutics toward the clinic. We report a series of electrophysiology, optogenetic, pharmacological magnetic resonance imaging, and animal behavior studies demonstrating that activation of mGlu1 receptors increases inhibitory transmission in the prelimbic PFC by selective excitation of somatostatin-expressing interneurons (SST-INs). An mGlu1 PAM reverses cortical hyperactivity and concomitant cognitive deficits induced by N-methyl-d-aspartate (NMDA) receptor antagonists. Using in vivo optogenetics, we show that prelimbic SST-INs are necessary for mGlu1 PAM efficacy. Collectively, these findings suggest that mGlu1 PAMs could reverse cortical GABAergic deficits and exhibit efficacy in treating cognitive dysfunction in schizophrenia.

Identification of Negative BOLD Responses in Epilepsy Using Windkessel Models

Alongside positive blood oxygenation level–dependent (BOLD) responses associated with interictal epileptic discharges, a variety of negative BOLD responses (NBRs) are typically found in epileptic patients. Previous studies suggest that, in general, up to four mechanisms might underlie the genesis of NBRs in the brain: (i) neuronal disruption of network activity, (ii) altered balance of neurometabolic/vascular couplings, (iii) arterial blood stealing, and (iv) enhanced cortical inhibition. Detecting and classifying these mechanisms from BOLD signals are pivotal for the improvement of the specificity of the electroencephalography–functional magnetic resonance imaging (EEG-fMRI) image modality to identify the seizure-onset zones in refractory local epilepsy. This requires models with physiological interpretation that furnish the understanding of how these mechanisms are fingerprinted by their BOLD responses. Here, we used a Windkessel model with viscoelastic compliance/inductance in combination with dynamic models of both neuronal population activity and tissue/blood O₂ to classify the hemodynamic response functions (HRFs) linked to the above mechanisms in the irritative zones of epileptic patients. First, we evaluated the most relevant imprints on the BOLD response caused by variations of key model parameters. Second, we demonstrated that a general linear model is enough to accurately represent the four different types of NBRs. Third, we tested the ability of a machine learning classifier, built from a simulated ensemble of HRFs, to predict the mechanism underlying the BOLD signal from irritative zones. Cross-validation indicates that these four mechanisms can be classified from realistic fMRI BOLD signals. To demonstrate proof of concept, we applied our methodology to EEG-fMRI data from five epileptic patients undergoing neurosurgery, suggesting the presence of some of these mechanisms. We concluded that a proper identification and interpretation of NBR mechanisms in epilepsy can be performed by combining general linear models and biophysically inspired models.

Voltage-Sensitive Dye versus Intrinsic Signal Optical Imaging: Comparison of Tactile Responses in Primary and Secondary Somatosensory Cortices of Rats

Studies using functional magnetic resonance imaging assume that hemodynamic responses have roughly linear relationships with underlying neural activity. However, to accurately investigate the neurovascular transfer function and compare its variability across brain regions, it is necessary to obtain full-field imaging of both electrophysiological and hemodynamic responses under various stimulus conditions with superior spatiotemporal resolution. Optical imaging combined with voltage-sensitive dye (VSD) and intrinsic signals (IS) is a powerful tool to address this issue. We performed VSD and IS imaging in the primary (S1) and secondary (S2) somatosensory cortices of rats to obtain optical maps of whisker-evoked responses. There were characteristic differences in sensory responses between the S1 and S2 cortices: VSD imaging revealed more localized excitatory and stronger inhibitory neural activity in S1 than in S2. IS imaging revealed stronger metabolic responses in S1 than in S2. We calculated the degree of response to compare the sensory responses between cortical regions and found that the ratio of the degree of response of S2 to S1 was similar, irrespective of whether the ratio was determined by VSD or IS imaging. These results suggest that neurovascular coupling does not vary between the S1 and S2 cortices.

Ageing and the Ipsilateral M1 BOLD Response: A Connectivity Study

Young people exhibit a negative BOLD response in ipsilateral primary motor cortex (M1) when making unilateral movements, such as button presses. This negative BOLD response becomes more positive as people age. In this study, we investigated why this occurs, in terms of the underlying effective connectivity and haemodynamics. We applied dynamic causal modeling (DCM) to task fMRI data from 635 participants aged 18-88 from the Cam-CAN dataset, who performed a cued button pressing task with their right hand. We found that connectivity from contralateral supplementary motor area (SMA) and dorsal premotor cortex (PMd) to ipsilateral M1 became more positive with age, explaining 44% of the variability across people in ipsilateral M1 responses. In contrast, connectivity from contralateral M1 to ipsilateral M1 was weaker and did not correlate with individual differences in rM1 BOLD. Neurovascular and haemodynamic parameters in the model were not able to explain the age-related shift to positive BOLD. Our results add to a body of evidence implicating neural, rather than vascular factors as the predominant cause of negative BOLD-while emphasising the importance of inter-hemispheric connectivity. This study provides a foundation for investigating the clinical and lifestyle factors that determine the sign and amplitude of the M1 BOLD response in ageing, which could serve as a proxy for neural and vascular health, via the underlying neurovascular mechanisms.

Determining laminar neuronal activity from BOLD fMRI using a generative model

Laminar fMRI using the BOLD contrast enables the non-invasive investigation of mesoscopic functional circuits in the human brain. However, the laminar neuronal activity is spatiotemporally biased in the observed cortical depth profiles of the BOLD signal. In this study, we propose a generative fMRI signal model, comprehensively covering the relationship between cortical depth-dependent changes in excitatory and inhibitory neuronal activity with the sampling of the BOLD signal with finite voxels. The generative model allowed us to investigate pertinent questions regarding the accuracy of the laminar BOLD signal relative to the neuronal activity, and we found that: a) condition differences in laminar BOLD signals may be more reflective of neuronal activity than single condition BOLD signal depth profiles; b) angular dependence of the BOLD signal induces significant signal variability, which can mask underlying activity profiles; c) even if only three neuronal depths are of interest, more BOLD signal depths should be considered in the analysis. In addition, we recommend that the laminar BOLD data should be displayed using the centroid method to appreciate its spatial distribution in the original resolution. Finally, we showed that Bayesian model inversion of the generative model can improve sensitivity and specificity of assessing depth-dependent neuronal changes both for steady-state and dynamically.

Association of amyloid-β CSF/PET discordance and tau load 5 years later

OBJECTIVE

To investigate the association between discordant β-amyloid (Aβ) PET and CSF biomarkers at baseline and the emergence of tau pathology 5 years later.

METHODS

We included 730 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants without dementia (282 cognitively normal, 448 mild cognitive impairment) with baseline [18F]florbetapir PET and CSF Aβ42 available. Aβ CSF/PET status was determined at baseline using established cutoffs. Longitudinal data were available for [18F]florbetapir (Aβ) PET (baseline to 4.3 ± 1.9 years), CSF (p)tau (baseline to 2.0 ± 0.1 years), cognition (baseline to 4.3 ± 2.0 years), and [18F]flortaucipir (tau) PET (measured 5.2 ± 1.2 years after baseline to 1.6 ± 0.7 years later). We used linear mixed modeling to study the association between Aβ CSF/PET status and tau pathology measured in CSF or using PET. We calculated the proportion of CSF+/PET- participants who during follow-up (1) progressed to Aβ CSF+/PET+ or (2) became tau-positive based on [18F]flortaucipir PET.

RESULTS

Aβ CSF+/PET+ (n = 318) participants had elevated CSF (p)tau levels and worse cognitive performance at baseline, while CSF+/PET- (n = 80) participants were overall similar to the CSF-/PET- (N = 306) group. Five years after baseline, [18F]flortaucipir PET uptake in the CSF+/PET- group (1.20 ± 0.13) did not differ from CSF-/PET- (1.18 ± 0.08, p = 0.69), but was substantially lower than CSF+/PET+ (1.48 ± 0.44, p < 0.001). Of the CSF+/PET- participants, 21/64 (33%) progressed to Aβ CSF+/PET+, whereas only one (3%, difference p < 0.05) became tau-positive based on [18F]flortaucipir PET.

CONCLUSIONS

Aβ load detectable by both CSF and PET seems to precede substantial tau deposition. Compared to participants with abnormal Aβ levels on both PET and CSF, the CSF+/PET- group has a distinctly better prognosis.

Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: A Multifiber Diffusion MRI Modeling and Tractography Study

BACKGROUND AND PURPOSE

Polymicrogyria and lissencephaly may be associated with abnormal organization of the undelying white matter tracts that have been rarely investigated so far. Our aim was to characterize white matter tract organization in polymicrogyria and lissencephaly using constrained spherical deconvolution, a multifiber diffusion MR imaging modeling technique for white matter tractography reconstruction.

MATERIALS AND METHODS

We retrospectively reviewed 50 patients (mean age, 8.3 ± 5.4 years; range, 1.4-21.2 years; 27 males) with different polymicrogyria (n = 42) and lissencephaly (n = 8) subtypes. The fiber direction-encoded color maps and 6 different white matter tracts reconstructed from each patient were visually compared with corresponding images reconstructed from 7 age-matched, healthy control WM templates. Each white matter tract was assessed by 2 experienced pediatric neuroradiologists and scored in consensus on the basis of the severity of the structural abnormality, ranging from the white matter tracts being absent to thickened. The results were summarized by different polymicrogyria and lissencephaly subgroups.

RESULTS

More abnormal-appearing white matter tracts were identified in patients with lissencephaly compared with those with polymicrogyria (79.2% versus 37.3%). In lissencephaly, structural abnormalities were identified in all studied white matter tracts. In polymicrogyria, the more frequently affected white matter tracts were the cingulum, superior longitudinal fasciculus, inferior longitudinal fasciculus, and optic radiation-posterior corona radiata. The severity of superior longitudinal fasciculus and cingulum abnormalities was associated with the polymicrogyria distribution and extent. A thickened superior fronto-occipital fasciculus was demonstrated in 3 patients.

CONCLUSIONS

We demonstrated a range of white matter tract structural abnormalities in patients with polymicrogyria and lissencephaly. The patterns of white matter tract involvement are related to polymicrogyria and lissencephaly subgroups, distribution, and, possibly, their underlying etiologies.

Spectro-Temporal Processing in a Two-Stream Computational Model of Auditory Cortex

Neural processing of sounds in the dorsal and ventral streams of the (human) auditory cortex is optimized for analyzing fine-grained temporal and spectral information, respectively. Here we use a Wilson and Cowan firing-rate modeling framework to simulate spectro-temporal processing of sounds in these auditory streams and to investigate the link between neural population activity and behavioral results of psychoacoustic experiments. The proposed model consisted of two core (A1 and R, representing primary areas) and two belt (Slow and Fast, representing rostral and caudal processing respectively) areas, differing in terms of their spectral and temporal response properties. First, we simulated the responses to amplitude modulated (AM) noise and tones. In agreement with electrophysiological results, we observed an area-dependent transition from a temporal (synchronization) to a rate code when moving from low to high modulation rates. Simulated neural responses in a task of amplitude modulation detection suggested that thresholds derived from population responses in core areas closely resembled those of psychoacoustic experiments in human listeners. For tones, simulated modulation threshold functions were found to be dependent on the carrier frequency. Second, we simulated the responses to complex tones with missing fundamental stimuli and found that synchronization of responses in the Fast area accurately encoded pitch, with the strength of synchronization depending on number and order of harmonic components. Finally, using speech stimuli, we showed that the spectral and temporal structure of the speech was reflected in parallel by the modeled areas. The analyses highlighted that the Slow stream coded with high spectral precision the aspects of the speech signal characterized by slow temporal changes (e.g., prosody), while the Fast stream encoded primarily the faster changes (e.g., phonemes, consonants, temporal pitch). Interestingly, the pitch of a speaker was encoded both spatially (i.e., tonotopically) in Slow area and temporally in Fast area. Overall, performed simulations showed that the model is valuable for generating hypotheses on how the different cortical areas/streams may contribute toward behaviorally relevant aspects of auditory processing. The model can be used in combination with physiological models of neurovascular coupling to generate predictions for human functional MRI experiments.

fMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application

Dynamic causal modeling (DCM)-a framework for inferring hidden neuronal states from brain activity measurements (e. g., fMRI) and their context-dependent modulation-was developed for human neuroimaging, and has not been optimized for non-human primate (NHP) studies, which are usually done under anesthesia. Animal neuroimaging studies offer the potential to improve effective connectivity modeling using DCM through combining functional imaging with invasive procedures such as in vivo optogenetic or electrical stimulation. Employing a Bayesian approach, model parameters are estimated based on prior knowledge of conditions that might be related to neural and BOLD dynamics (e.g., requires empirical knowledge about the range of plausible parameter values). As such, we address the following questions in this review: What factors need to be considered when applying DCM to NHP data? What differences in functional networks, cerebrovascular architecture and physiology exist between human and NHPs that are relevant for DCM application? How do anesthetics affect vascular physiology, BOLD contrast, and neural dynamics-particularly, effective communication within, and between networks? Considering the factors that are relevant for DCM application to NHP neuroimaging, we propose a strategy for modeling effective connectivity under anesthesia using an integrated physiologic-stochastic DCM (IPS-DCM).

Increasing robustness of pairwise methods for effective connectivity in magnetic resonance imaging by using fractional moment series of BOLD signal distributions

Estimating causal interactions in the brain from functional magnetic resonance imaging (fMRI) data remains a challenging task. Multiple studies have demonstrated that all current approaches to determine direction of connectivity perform poorly when applied to synthetic fMRI datasets. Recent advances in this field include methods for pairwise inference, which involve creating a sparse connectome in the first step, and then using a classifier in order to determine the directionality of connection between every pair of nodes in the second step. In this work, we introduce an advance to the second step of this procedure, by building a classifier based on fractional moments of the BOLD distribution combined into cumulants. The classifier is trained on datasets generated under the dynamic causal modeling (DCM) generative model. The directionality is inferred based on statistical dependencies between the two-node time series, for example, by assigning a causal link from time series of low variance to time series of high variance. Our approach outperforms or performs as well as other methods for effective connectivity when applied to the benchmark datasets. Crucially, it is also more resilient to confounding effects such as differential noise level across different areas of the connectome.

Quantitative relations between transient BOLD responses, cortical energetics, and impulse firing in different cortical regions

The blood oxygen level-dependent (BOLD) functional magnetic resonance imaging signal arises as a consequence of changes in blood flow (cerebral blood flow) and oxygen usage (cerebral metabolic rate of oxygen) that in turn are modulated by changes in neuronal activity. Much attention has been given to both theoretical and experimental aspects of the energetics but not to the neuronal activity. Here we use our previous theory relating the steady-state BOLD signal to neuronal activity and amalgamate it with the standard dynamic causal model (DCM, Friston) theory to produce a quantitative model relating the time-dependent BOLD signal to the underlying neuronal activity. Unlike existing treatments, this new theory incorporates a nonzero baseline activity in a completely consistent way and is thus able to account for both positive and negative BOLD signals. It can reproduce a wide variety of experimental BOLD signals reported in the literature solely by adjusting the neuronal input activity. In this way it provides support for the claim that the main features of the signals, including poststimulus undershoot and overshoot, are principally a result of changes in neuronal activity.NEW & NOTEWORTHY A previous model relating the steady-state blood oxygen level-dependent (BOLD) signal to neuronal activity, both above and below baseline, is extended to account for transient BOLD signals. This allows for a detailed investigation of the role neuronal activity can play in such signals and also encompasses poststimulus undershoot and overshoot. A wide variety of experimental BOLD signals are reproduced solely by adjusting the neuronal input activity, including recent results regarding the BOLD signal in patients with schizophrenia.

Translating the hemodynamic response: why focused interdisciplinary integration should matter for the future of functional neuroimaging

The amount of information acquired with functional neuroimaging techniques, particularly fNIRS and fMRI, is rapidly growing and has enormous potential for studying human brain functioning. Therefore, many scientists focus on solving computational neuroimaging and Big Data issues to advance the discipline. However, the main obstacle—the accurate translation of the hemodynamic response (HR) by the investigation of a physiological phenomenon called neurovascular coupling—is still not fully overcome and, more importantly, often overlooked in this context. This article provides a brief and critical overview of significant findings from cellular biology and in vivo brain physiology with a focus on advancing existing HR modelling paradigms. A brief historical timeline of these disciplines of neuroscience is presented for readers to grasp the concept better, and some possible solutions for further scientific discussion are provided.