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Background: 18F-flortaucipir PET received FDA approval to visualize aggregated neurofibrillary tangles (NFTs) in brains of adult patients with cognitive impairment being evaluated for Alzheimer’s disease (AD). However, manufacturer’s guidelines for visual interpretation of 18F-flortaucipir PET differ from how 18F-flortaucipir PET has been measured in research settings using standardized uptake value ratios (SUVRs). How visual interpretation relates to 18F-flortaucipir PET SUVR, cerebrospinal fluid (CSF) biomarkers, or longitudinal clinical assessment is not well understood. Objective: We compare various diagnostic methods in participants enrolled in longitudinal observational studies of aging and memory (n = 189, 23 were cognitively impaired). Methods: Participants had tau PET, Aβ PET, MRI, and clinical and cognitive evaluation within 18 months (n = 189); the majority (n = 144) also underwent lumbar puncture. Two radiologists followed manufacturer’s guidelines for 18F-flortaucipir PET visual interpretation. Results: Visual interpretation had high agreement with SUVR (98.4%)and moderate agreement with CSF p-tau181 (86.1%). Two participants demonstrated 18F-flortaucipir uptake from meningiomas. Visual interpretation could not predict follow-up clinical assessment in 9.52% of cases. Conclusion: Visual interpretation was highly consistent with SUVR (discordant participants had hemorrhagic infarcts or occipital-predominant AD NFT deposition) and moderately consistent with CSF p-tau181 (discordant participants had AD pathophysiology not detectable on tau PET). However, close association between AD NFT deposition and clinical onset in group-level studies does not necessarily hold at the individual level, with discrepancies arising from atypical AD, vascular dementia, or frontotemporal dementia. A better understanding of relationships across imaging, CSF biomarkers, and clinical assessment is needed to provide appropriate diagnoses for these individuals.

18F-flortaucipir-PET received FDA approval to visualize tauopathy in the brains of adult patients with cognitive impairment being evaluated for Alzheimer disease (AD). However, manufacturer’s guidelines for the visual interpretation of18F-flortaucipir-PET differs greatly from how18F-flortaucipir-PET has been measured in research settings using standardized uptake value ratios (SUVRs). How visual interpretation relates to18F-flortaucipir-PET SUVR, CSF biomarkers, or longitudinal clinical assessment is not well understood. Here we compare these various diagnostic methods in participants enrolled in studies of aging and memory (n=189, of whom 23 were cognitively impaired). Visual interpretation had high agreement with SUVR (98.4%); discordant participants had hemorrhagic infarcts or atypical AD tauopathies. Visual interpretation had moderate agreement with CSF p-tau181 (86.1%). Two participants demonstrated18F-flortaucipir uptake from meningiomas. Visual interpretation could not predict follow-up clinical assessment in 9.52% of cases. We conclude that close association between AD tauopathy and clinical onset in group-level studies does not always hold at the individual level, with discrepancies arising from atypical AD, vascular dementia, or frontotemporal dementia. A better understanding of relationships across imaging, CSF biomarkers, and clinical assessment is needed to provide appropriate diagnoses for these individuals.

The apolipoprotein E ( APOE ) ε4 allele is strongly linked with cerebral β-amyloidosis, but its relationship with tauopathy is less established. We investigated the relationship between APOE ε4 carrier status, regional amyloid-β (Aβ), magnetic resonance imaging (MRI) volumetrics, tau positron emission tomography (PET), APOE messenger RNA (mRNA) expression maps, and cerebrospinal fluid phosphorylated tau (CSF ptau 181 ). Three hundred fifty participants underwent imaging, and 270 had ptau 181 . We used computational models to evaluate the main effect of APOE ε4 carrier status on regional neuroimaging values and then the interaction of ε4 status and global Aβ on regional tau PET and brain volumes as well as CSF ptau 181 . Separately, we also examined the additional interactive influence of sex. We found that, for the same degree of Aβ burden, APOE ε4 carriers showed greater tau PET signal relative to noncarriers in temporal regions, but no interaction was present for MRI volumes or CSF ptau 181 . This potentiation of tau aggregation irrespective of sex occurred in brain regions with high APOE mRNA expression, suggesting local vulnerabilities to tauopathy. There were greater effects of APOE genotype in females, although the interactive sex effects did not strongly mirror mRNA expression. Pathology is not homogeneously expressed throughout the brain but mirrors underlying biological patterns such as gene expression.

Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p0·0001) and in people with Down syndrome (n=32; r=-0·801; p0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.

While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect.Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes.Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes.Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases.We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies.Dose-dependent treatment effects were observed in some biomarkers.No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations.

Rates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross-sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN-Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini-Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®-SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4-year trial with annual assessments; 80% power; α = 0.05).ResultsPSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = -0.42[0.1], p=0.002), CDR®-SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = -58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.

Tauopathy is a hallmark pathology of Alzheimer’s disease with a strong relationship with cognitive impairment. As such, understanding tau may be a key to clinical interventions. In vivo tauopathy has been measured using cerebrospinal fluid assays, but these do not provide information about where pathology is in the brain. The introduction of PET ligands that bind to paired helical filaments provides the ability to measure the amount and distribution of tau pathology. The heritability of the age of dementia onset tied to the specific mutations found in autosomal dominant Alzheimer’s disease families provides an elegant model to study the spread of tau across the course of the disease as well as the cross-modal relationship between tau and other biomarkers. To better understand the pathobiology of Alzheimer’s disease we measured levels of tau PET binding in individuals with dominantly inherited Alzheimer’s disease using data from the Dominantly Inherited Alzheimer Network (DIAN). We examined cross-sectional measures of amyloid-β, tau, glucose metabolism, and grey matter degeneration in 15 cognitively normal mutation non-carriers, 20 asymptomatic carriers, and 15 symptomatic mutation carriers. Linear models examined the association of pathology with group, estimated years to symptom onset, as well as cross-modal relationships. For comparison, tau PET was acquired on 17 older adults with sporadic, late onset Alzheimer disease. Tau PET binding was starkly elevated in symptomatic DIAN individuals throughout the cortex. The brain areas demonstrating elevated tau PET binding overlapped with those seen in sporadic Alzheimer’s disease, but with a greater cortical involvement and greater levels of binding despite similar cognitive impairment. Tau PET binding was elevated in the temporal lobe, but the most prominent loci of pathology were in the precuneus and lateral parietal regions. Symptomatic mutation carriers also demonstrated elevated tau PET binding in the basal ganglia, consistent with prior work with amyloid-β. The degree of tau tracer binding in symptomatic individuals was correlated to other biomarkers, particularly markers of neurodegeneration. In addition to the differences seen with tau, amyloid-β was increased in both asymptomatic and symptomatic groups relative to non-carriers. Glucose metabolism showed decline primarily in the symptomatic group. MRI indicated structural degeneration in both asymptomatic and symptomatic cohorts. We demonstrate that tau PET binding is elevated in symptomatic individuals with dominantly inherited Alzheimer’s disease. Tau PET uptake was tied to the onset of cognitive dysfunction, and there was a higher amount, and different regional pattern of binding compared to late onset, non-familial Alzheimer’s disease.

Pittsburgh compound B (PiB) radiotracer for positron emission tomography (PET) imaging can bind to different types of amyloid-β plaques and blood vessels (cerebral amyloid angiopathy). However, the relative contributions of different plaque subtypes (diffuse versus cored/compact) to in vivo PiB PET signal on a region-by-region basis are incompletely understood. Of particular interest is whether the same staging schemes for summarizing amyloid-β burden are appropriate for both late-onset and autosomal dominant forms of Alzheimer disease (LOAD and ADAD). Here, we compared antemortem PiB PET with follow-up postmortem estimation of amyloid-β burden using stereologic methods to estimate the relative area fraction of diffuse and cored/compact amyloid-β plaques across 16 brain regions in 15 individuals with ADAD and 14 individuals with LOAD. In ADAD, we found that PiB PET correlated with diffuse plaques in the frontal, parietal, temporal, and striatal regions commonly used to summarize amyloid-β burden in PiB PET, and correlated with both diffuse and cored/compact plaques in the occipital lobe and parahippocampal gyrus. In LOAD, we found that PiB PET correlated with both diffuse and cored/compact plaques in the anterior cingulate, frontal lobe (middle frontal gyrus), and parietal lobe, and showed additional correlations with diffuse plaque in the amygdala and occipital lobe, and with cored/compact plaque in the temporal lobe. Thus, commonly used PiB PET summary regions predominantly reflect diffuse plaque burden in ADAD and a mixture of diffuse and cored/compact plaque burden in LOAD. In direct comparisons of ADAD and LOAD, postmortem stereology identified much greater mean amyloid-β plaque burdens in ADAD versus LOAD across almost all brain regions studied. However, standard PiB PET did not recapitulate these stereologic findings, likely due to non-trivial amyloid-β plaque burdens in ADAD within the cerebellum and brainstem-commonly used reference regions in PiB PET. Our findings suggest that PiB PET summary regions correlate with amyloid-β plaque burden in both ADAD and LOAD; however, they might not be reliable in direct comparisons of regional amyloid-β plaque burden between the two forms of AD.

SUMMARYFrontotemporal dementia (FTD) due to MAPT mutation causes pathological accumulation of tau and glutamatergic cortical neuronal death by unknown mechanisms. We used human induced pluripotent stem cell (iPSC)-derived cerebral organoids expressing tau-V337M and isogenic corrected controls to discover early alterations due to the mutation that precede neurodegeneration. At 2 months, mutant organoids show upregulated expression of MAPT, and glutamatergic signaling pathways and regulators including the RNA-binding protein ELAVL4. Over the following 4 months, mutant organoids accumulate splicing changes, disruption of autophagy function and build-up of tau and P-tau S396. By 6 months, tau-V337M organoids show specific loss of glutamatergic neurons of layers affected in patients. Mutant neurons are susceptible to glutamate toxicity which was rescued pharmacologically by treatment with the PIKFYVE kinase inhibitor apilimod. Our results demonstrate a sequence of events that precede cell death, revealing molecular pathways associated with glutamate signaling as potential targets for therapeutic intervention in FTD.

ObjectiveTo evaluate temporal correlations between CSF and neuroimaging (PET and MRI) measures of amyloid, tau, and neurodegeneration in relation to Alzheimer disease (AD) progression.MethodsA total of 371 cognitively unimpaired and impaired participants enrolled in longitudinal studies of AD had both CSF (β-amyloid [Aβ]42, phosphorylated tau181, total tau, and neurofilament light chain) and neuroimaging (Pittsburgh compound B [PiB] PET, flortaucipir PET, and structural MRI) measures. The pairwise time interval between CSF and neuroimaging measures was binned into 2-year periods. Spearman correlations identified the time bin when CSF and neuroimaging measures most strongly correlated. CSF and neuroimaging measures were then binarized as biomarker-positive or biomarker-negative using Gaussian mixture modeling. Cohen kappa coefficient identified the time bin when CSF measures best agreed with corresponding neuroimaging measures when determining amyloid, tau, and neurodegeneration biomarker positivity.ResultsCSF Aβ42 and PiB PET showed maximal correlation when collected within 6 years of each other (R ≈ −0.5). CSF phosphorylated tau181 and flortaucipir PET showed maximal correlation when CSF was collected 4 to 8 years prior to PET (R ≈ 0.4). CSF neurofilament light chain and cortical thickness showed low correlation, regardless of time interval (Ravg ≈ −0.3). Similarly, CSF total tau and cortical thickness had low correlation, regardless of time interval (Ravg < −0.2).ConclusionsCSF Aβ42 and PiB PET best agree when acquired in close temporal proximity, whereas CSF phosphorylated tau precedes flortaucipir PET by 4 to 8 years. CSF and neuroimaging measures of neurodegeneration have low correspondence and are not interchangeable at any time interval.

Antemortem tau positron emission tomography imaging suggests elevated tau pathology in autosomal dominant versus late‐onset Alzheimer’s disease at equivalent clinical stages, but does not implicate the specific tau pathologies responsible. Here we made stereological measurements of tau neurofibrillary tangles, neuritic plaques, and neuropil threads and found compared to late‐onset Alzheimer’s disease, autosomal dominant Alzheimer’s disease showed even greater tangle and thread burdens. Regional tau burden resembled that observed in tau imaging of a separate cohort at earlier clinical stages. Finally, our results suggest tau imaging measures total tau burden in Alzheimer’s disease, composed predominantly of tangle and thread pathology.

Interest in understanding the roles of white matter (WM) inflammation and damage in the pathophysiology of Alzheimer disease (AD) has been growing significantly in recent years. However, in vivo magnetic resonance imaging (MRI) techniques for imaging inflammation are still lacking. An advanced diffusion-based MRI method, neuro-inflammation imaging (NII), has been developed to clinically image and quantify WM inflammation and damage in AD. Here, we employed NII measures in conjunction with cerebrospinal fluid (CSF) biomarker classification (for β-amyloid (Aβ) and neurodegeneration) to evaluate 200 participants in an ongoing study of memory and aging. Elevated NII-derived cellular diffusivity was observed in both preclinical and early symptomatic phases of AD, while disruption of WM integrity, as detected by decreased fractional anisotropy (FA) and increased radial diffusivity (RD), was only observed in the symptomatic phase of AD. This may suggest that WM inflammation occurs earlier than WM damage following abnormal Aβ accumulation in AD. The negative correlation between NII-derived cellular diffusivity and CSF Aβ42 level (a marker of amyloidosis) may indicate that WM inflammation is associated with increasing Aβ burden. NII-derived FA also negatively correlated with CSF t-tau level (a marker of neurodegeneration), suggesting that disruption of WM integrity is associated with increasing neurodegeneration. Our findings demonstrated the capability of NII to simultaneously image and quantify WM cellularity changes and damage in preclinical and early symptomatic AD. NII may serve as a clinically feasible imaging tool to study the individual and composite roles of WM inflammation and damage in AD., Highlights • New diffusion MRI technique, NII, was developed to simultaneously image and quantify coexisting white matter pathologies in AD. • Using MRI NII, white matter cellularity and damage were examined in the preclinical and early symptomatic stages of AD. • MRI NII biomarkers segregate preclinical and early symptomatic AD and correlate with CSF biomarkers of Aβ42 and t-tau.

The ability to use information about the uncertainty of future outcomes is critical for adaptive behavior in an uncertain world. We show that the basal forebrain (BF) contains at least two distinct neural-coding strategies to support this capacity. The dorsal-lateral BF, including the ventral pallidum (VP), contains reward-sensitive neurons, some of which are selectively suppressed by uncertain-reward predictions (U(−)). In contrast, the medial BF (mBF) contains reward-sensitive neurons, some of which are selectively enhanced (U(+)) by uncertain-reward predictions. In a two-alternative choice-task, U(−) neurons were selectively suppressed while monkeys chose uncertain options over certain options. During the same choice-epoch, U(+) neurons signaled the subjective reward value of the choice options. Additionally, after the choice was reported, U(+) neurons signaled reward uncertainty until the choice outcome. We suggest that uncertainty-related suppression of VP may participate in the mediation of uncertainty-seeking actions, whereas uncertainty-related enhancement of the mBF may direct cognitive resources to monitor and learn from uncertain-outcomes. SIGNIFICANCE STATEMENT To survive in an uncertain world, we must approach uncertainty and learn from it. Here we provide evidence for two mostly distinct mechanisms for processing uncertainty about rewards within different subregions of the primate basal forebrain (BF). We found that uncertainty suppressed the representation of certain (or safe) reward values by some neurons in the dorsal-lateral BF, in regions occupied by the ventral pallidum. This uncertainty-related suppression was evident as monkeys made risky choices. We also found that uncertainty-enhanced the activity of many medial BF neurons, most prominently after the monkeys' choices were completed (as they awaited uncertain outcomes). Based on these findings, we propose that different subregions of the BF could support action and learning under uncertainty in distinct but complimentary manners.

The basal forebrain (BF) is a principal source of modulation of the neocortex, and is thought to regulate cognitive functions such as attention, motivation, and learning by broadcasting information about the behavioral salience of events. An event can be salient because it is novel, surprising, or associated with reward prediction errors. But to date, the type of salience-related information the BF broadcasts is unclear. Here, we report that many BF neurons display phasic excitatory bursting that rapidly conveys the magnitude, probability, and timing of primary reinforcements. The same BF neurons also discriminate fully expected novel visual objects from familiar objects and respond to object-sequence violations, regardless of their relevance for subsequent behaviors, suggesting that they are not dedicated to signaling information about primary reinforcements. A different group of BF neurons displayed ramping activations that predicted the time of novel and surprising events. Their ramping was highly sensitive to the subjects’ confidence in event timing. Hence, BF neurons signal statistics about time and salience. Their activity may organize cortical computations to facilitate accurate behavioral responses to a diverse set of expected and ongoing events.

When axonal fibres approach or leave the cortex, their trajectories tend to closely follow the cortical convolutions. To quantify this tendency, we propose a three-dimensional coordinate system based on the gyral geometry. For every voxel in the brain, we define a “radial” axis orthogonal to nearby surfaces, a “sulcal” axis along the sulcal depth gradient that preferentially points from deep white matter to the gyral crown, and a “gyral” axis aligned with the long axis of the gyrus.\ud \ud When compared with high-resolution, in-vivo diffusion MRI data from the Human Connectome Project, we find that in superficial white matter the apparent diffusion coefficient (at b = 1000) along the sulcal axis is on average 16% larger than along the gyral axis and twice as large as along the radial axis. This is reflected in the vast majority of observed fibre orientations lying close to the tangential plane (median angular offset

Summary The basal forebrain (BF) is a principal source of modulation of the neocortex [ 1 , 2 , 3 , 4 , 5 , 6 ] and is thought to regulate cognitive functions such as attention, motivation, and learning by broadcasting information about salience [ 2 , 3 , 5 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. However, events can be salient for multiple reasons—such as novelty, surprise, or reward prediction errors [ 20 , 21 , 22 , 23 , 24 ]—and to date, precisely which salience-related information the BF broadcasts is unclear. Here, we report that the primate BF contains at least two types of neurons that often process salient events in distinct manners: one with phasic burst responses to cues predicting salient events and one with ramping activity anticipating such events. Bursting neurons respond to cues that convey predictions about the magnitude, probability, and timing of primary reinforcements. They also burst to the reinforcement itself, particularly when it is unexpected. However, they do not have a selective response to reinforcement omission (the unexpected absence of an event). Thus, bursting neurons do not convey value-prediction errors but do signal surprise associated with external events. Indeed, they are not limited to processing primary reinforcement: they discriminate fully expected novel visual objects from familiar objects and respond to object-sequence violations. In contrast, ramping neurons predict the timing of many salient, novel, and surprising events. Their ramping activity is highly sensitive to the subjects’ confidence in event timing and on average encodes the subjects’ surprise after unexpected events occur. These data suggest that the primate BF contains mechanisms to anticipate the timing of a diverse set of important external events (via ramping activity) and to rapidly deploy cognitive resources when these events occur (via short latency bursting).

Systematic mapping of long-distance pathways in the human brain (the “macro-connectome”) represents a grand challenge for the coming century. Diffusion imaging and resting-state functional MRI represent the two main modalities for examining the macro-connectome in vivo. However, the fidelity with which these two complementary techniques reflect true connectional anatomy is yet to be thoroughly assessed. We review a set of neuroanatomical observations in the macaque monkey that frame our understanding of brain connectivity for primates, including humans. We then describe approaches used by the Human Connectome Project (HCP) to improve data acquisition, analysis, and visualization for diffusion and functional imaging. We also analyze methodological biases and limitations in diffusion imaging and tractography, and discuss options for reducing their impact.