Auditory predictions shape the neural responses to stimulus repetition and sensory change

Perception is a highly active process relying on the continuous formulation of predictive inferences using short-term sensory memory templates, which are recursively adjusted based on new input. According to this idea, earlier studies have shown that novel stimuli preceded by a higher number of repetitions yield greater novelty responses, indexed by larger mismatch negativity (MMN). However, it is not clear whether this MMN memory trace effect is driven by more adapted responses to prior stimulation or rather by a heightened processing of the unexpected deviant, and only few studies have so far attempted to characterize the functional neuroanatomy of these effects. Here we implemented a modified version of the auditory frequency oddball paradigm that enables modeling the responses to both repeated standard and deviant stimuli. Fifteen subjects underwent functional magnetic resonance imaging (fMRI) while their attention was diverted from auditory stimulation. We found that deviants with longer stimulus history of standard repetitions yielded a more robust and widespread activation in the bilateral auditory cortex. Standard tones repetition yielded a pattern of response entangling both suppression and enhancement effects depending on the predictability of upcoming stimuli. We also observed that regularity encoding and deviance detection mapped onto spatially segregated cortical subfields. Our data provide a better understanding of the neural representations underlying auditory repetition and deviance detection effects, and further support that perception operates through the principles of Bayesian predictive coding

Involvement of the human midbrain and thalamus in auditory deviance detection

International audiencePrompt detection of unexpected changes in the sensory environment is critical for survival. In the auditory domain, the occurrence of a rare stimulus triggers a cascade of neurophysiological events spanning over multiple timescales. Besides the role of the mismatch negativity (MMN), whose cortical generators are located in supratemporal areas, cumulative evidence suggests that violations of auditory regularities can be detected earlier and lower in the auditory hierarchy. Recent human scalp recordings have shown signatures of auditory mismatch responses at shorter latencies than those of the MMN. Moreover, animal single-unit recordings have demonstrated that rare stimulus changes cause a release from stimulus-specific adaptation in neurons of the primary auditory cortex, the medial geniculate body (MGB), and the inferior colliculus (IC). Although these data suggest that change detection is a pervasive property of the auditory system which may reside upstream cortical sites, direct evidence for the involvement of sub-cortical stages in the human auditory novelty system is lacking. Using event-related functional magnetic resonance imaging during a frequency oddball paradigm, we here report that auditory deviance detection occurs in the MGB and the IC of healthy human participants. By implementing a random condition controlling for neural refractoriness effects, we show that auditory change detection in these subcortical stations involves the encoding of statistical regularities from the acoustic input. These results provide the first direct evidence of the existence of multiple mismatch detectors nested at different levels along the human ascending auditory pathway

Structural networks for brain age prediction

Biological networks have gained considerable attention within the Deep Learning community because of the promising framework of Graph Neural Networks (GNN), neural models that operate in complex networks. In the context of neuroimaging, GNNs have successfully been employed for functional MRI processing but their application to ROI-level structural MRI (sMRI) remains mostly unexplored. In this work we analyze the implementation of these geometric models with sMRI by building graphs of ROIs (ROI graphs) using tools from Graph Signal Processing literature and evaluate their performance in a downstream supervised task, age prediction. We first make a qualitative and quantitative comparison of the resulting networks obtained with common graph topology learning strategies. In a second stage, we train GNN-based models for brain age prediction. Since the order of every ROI graph is exactly the same and each vertex is an entity by itself (a ROI), we evaluate whether including ROI information during message-passing or global pooling operations is beneficial and compare the performance of GNNs against a Fully-Connected Neural Network baseline. The results show that ROI-level information is needed during the global pooling operation in order to achieve competitive results. However, no relevant improvement has been detected when it is incorporated during the message passing. These models achieve a MAE of 4.27 in hold-out test data, which is a performance very similar to the baseline, suggesting that the inductive bias included with the obtained graph connectivity is relevant and useful to reduce the dimensionality of the problem.This work has been supported by the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033 and the FI-AGAUR grant funded by Direcció General de Recerca (DGR) of Departament de Recerca i Universitats (REU) of the Generalitat de Catalunya.Peer ReviewedPostprint (published version

Neural Mechanism of a Sex-Specific Risk Variant for Posttraumatic Stress Disorder in the Type I Receptor of the Pituitary Adenylate Cyclase Activating Polypeptide

AbstractBackgroundPosttraumatic stress disorder (PTSD) is a frequent anxiety disorder with higher prevalence rates in female patients than in male patients (2.5:1). Association with a single nucleotide polymorphism (rs2267735) in the gene ADCYAP1R1 encoding the type I receptor (PAC1-R) of the pituitary adenylate cyclase activating polypeptide has been reported with PTSD in female patients. We sought to identify the neural correlates of the described PAC1-R effects on associative learning.MethodsIn a reverse genetic approach, we examined two independent healthy samples (N1 = 112, N2 = 73) using functional magnetic resonance imaging during cued and contextual fear conditioning. Skin conductance responses and verbal self-reports of arousal, valence, and contingency were recorded.ResultsWe found that PAC1-R modulates the blood oxygenation level–dependent response of the hippocampus. Specifically, we observed decreased hippocampal activity during contextual, but not during cued, fear conditioning in female participants carrying the PAC1-R risk allele. We observed no significant differences in conditionability for skin conductance responses, verbal reports, or activation in other brain regions between the genotype groups in female participants.ConclusionsOur results suggest that impaired contextual conditioning in the hippocampal formation may mediate the association between PAC1-R and PTSD symptoms. Our findings potentially identify a missing link between the involvement of PAC1-R in PTSD and the well-established structural and functional hippocampal deficits in these patients

Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-b, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging related to markers of AD and neurodegeneration.The project leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004 and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). Additional support has been received from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2017-SGR-892 and the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033. FB is supported by the NIHR biomedical research center at UCLH. MSC receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 948677), the Instituto de Salud Carlos III (PI19/00155), and from a fellowship from ”la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648 (LCF/BQ/PR21/11840004).Report de recerca signat per 27 autors/es: Irene Cumplido-Mayoral 1,2; Marina García-Prat 1; Grégory Operto 1,3,4; Carles Falcon 1,3,5; Mahnaz Shekari 1,2,3; Raffaele Cacciaglia 1,3,4; Marta Milà-Alomà 1,2,3,4; Luigi Lorenzini 6; Silvia Ingala 6; Alle Meije Wink 6; Henk JMM Mutsaerts 6; Carolina Minguillón 1,3,4; Karine Fauria 1,4; José Luis Molinuevo 1; Sven Haller 7; Gael Chetelat 8,10; Adam Waldman 9; Adam Schwarz 10; Frederik Barkhof 6,11; Ivonne Suridjan 12, 11; Gwendlyn Kollmorgen 13; Anna Bayfield 13; Henrik Zetterberg 14,15,16,17,18; Kaj Blennow 14,15 12; Marc Suárez-Calvet 1,3,4,19; Verónica Vilaplana 20; Juan Domingo Gispert 1,3,5; ALFA study; EPAD study; ADNI study; OASIS study // 1) Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; 2) Universitat Pompeu Fabra, Barcelona, Spain; 3) IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; 4) CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain; 5) Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; 6) Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; 7) CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland; 8) Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France; 9) Centre for Dementia Prevention, Edinburgh Imaging, and UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK; 10) Takeda Pharmaceutical Company Ltd, Cambridge, MA, USA; 11) Institutes of Neurology and Healthcare Engineering, University College London, London, UK; 12) Roche Diagnostics International Ltd, Rotkreuz, Switzerland; 13) Roche Diagnostics GmbH, Penzberg, Germany; 14) Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden; 15) Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; 16) Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom; 17) UK Dementia Research Institute at UCL, London, United Kingdom; 18) Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China; 19) Servei de Neurologia, Hospital del Mar, Barcelona, Spain; 20) Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain.Preprin

Effects of APOE-ε4 allele load on brain morphology in a cohort of middle-aged healthy individuals with enriched genetic risk for Alzheimer's disease

INTRODUCTION: Apolipoprotein E (APOE)-ε4 is the major genetic risk factor for Alzheimer's disease. However, the dose-dependent impact of this allele on brain morphology of healthy individuals remains unclear. METHODS: We analyzed gray matter volumes (GMvs) in a sample of 533 healthy middle-aged individuals with a substantial representation of ε4-carriers (207 heterozygotes and 65 homozygotes). RESULTS: We found APOE-ε4 additive GMv reductions in the right hippocampus, caudate, precentral gyrus, and cerebellar crus. In these regions, the APOE genotype interacted with age, with homozygotes displaying lower GMv after the fifth decade of life. APOE-ε4 was also associated to greater GMv in the right thalamus, left occipital gyrus, and right frontal cortex. DISCUSSION: Our data indicate that APOE-ε4 exerts additive effects on GMv in regions relevant for Alzheimer's disease pathophysiology already in healthy individuals. These findings elucidate the mechanisms underlying the increased Alzheimer's disease risk in ε4-carriers, suggesting a dose-dependent disease vulnerability on the brain structure level

Interactive effect of age and APOE-ε4 allele load on white matter myelin content in cognitively normal middle-aged subjects

The apolipoprotein E gene (APOE) ε4 allele has a strong and manifold impact on cognition and neuroimaging phenotypes in cognitively normal subjects, including alterations in the white matter (WM) microstructure. Such alterations have often been regarded as a reflection of potential thinning of the myelin sheath along axons, rather than pure axonal degeneration. Considering the main role of APOE in brain lipid transport, characterizing the impact of APOE on the myelin coating is therefore of crucial interest, especially in healthy APOE-ε4 homozygous individuals, who are exposed to a twelve-fold higher risk of developing Alzheimer's disease (AD), compared to the rest of the population. We examined T1w/T2w ratio maps in 515 cognitively healthy middle-aged participants from the ALFA study (ALzheimer and FAmilies) cohort, a single-site population-based study enriched for AD risk (68 APOE-ε4 homozygotes, 197 heterozygotes, and 250 non-carriers). Using tract-based spatial statistics, we assessed the impact of age and APOE genotype on this ratio taken as an indirect descriptor of myelin content. Healthy APOE-ε4 carriers display decreased T1w/T2w ratios in extensive regions in a dose-dependent manner. These differences were found to interact with age, suggesting faster changes in individuals with more ε4 alleles. These results obtained with T1w/T2w ratios, confirm the increased vulnerability of WM tracts in APOE-ε4 healthy carriers. Early alterations of myelin content could be the result of the impaired function of the ε4 isoform of the APOE protein in cholesterol transport. These findings help to clarify the possible interactions between the APOE-dependent non-pathological burden and age-related changes potentially at the source of the AD pathological cascade

Genotypic effects of APOE-epsilon 4 on resting-state connectivity in cognitively intact individuals support functional brain compensation

The investigation of resting-state functional connectivity (rsFC) in asymptomatic individuals at genetic risk for Alzheimer's disease (AD) enables discovering the earliest brain alterations in preclinical stages of the disease. The APOE-ε4 variant is the major genetic risk factor for AD, and previous studies have reported rsFC abnormalities in carriers of the ε4 allele. Yet, no study has assessed APOE-ε4 gene-dose effects on rsFC measures, and only a few studies included measures of cognitive performance to aid a clinical interpretation. We assessed the impact of APOE-ε4 on rsFC in a sample of 429 cognitively unimpaired individuals hosting a high number of ε4 homozygotes (n = 58), which enabled testing different models of genetic penetrance. We used independent component analysis and found a reduced rsFC as a function of the APOE-ε4 allelic load in the temporal default-mode and the medial temporal networks, while recessive effects were found in the extrastriate and limbic networks. Some of these results were replicated in a subsample with negative amyloid markers. Interaction with cognitive data suggests that such a network reorganization may support cognitive performance in the ε4-homozygotes. Our data indicate that APOE-ε4 shapes the functional architecture of the resting brain and favor the idea of a network-based functional compensation

Characteristic brain volumetric changes in the AD preclinical signature

Peer ReviewedPostprint (published version

Brain alterations in the early Alzheimer's continuum with amyloid-β, tau, glial and neurodegeneration CSF markers

Higher grey matter volumes/cortical thickness and fluorodeoxyglucose uptake have been consistently found in cognitively unimpaired individuals with abnormal Alzheimer's disease biomarkers compared with those with normal biomarkers. It has been hypothesized that such transient increases may be associated with neuroinflammatory mechanisms triggered in response to early Alzheimer's pathology. Here, we evaluated, in the earliest stages of the Alzheimer's continuum, associations between grey matter volume and fluorodeoxyglucose uptake with CSF biomarkers of several pathophysiological mechanisms known to be altered in preclinical Alzheimer's disease stages. We included 319 cognitively unimpaired participants from the ALFA+ cohort with available structural MRI, fluorodeoxyglucose PET and CSF biomarkers of amyloid-β and tau pathology (phosphorylated tau and total tau), synaptic dysfunction (neurogranin), neuronal and axonal injury (neurofilament light), glial activation (soluble triggering receptor on myeloid cells 2, YKL40, GFAP, interleukin-6 and S100b) and α-synuclein using the Roche NeuroToolKit. We first used the amyloid-β/tau framework to investigate differences in the neuroimaging biomarkers between preclinical Alzheimer's disease stages. Then, we looked for associations between the neuroimaging markers and all the CSF markers. Given the non-negative nature of the concentrations of CSF biomarkers and their high collinearity, we clustered them using non-negative matrix factorization approach (components) and sought associations with the imaging markers. By groups, higher grey matter volumes were found in the amyloid-β-positive tau-negative participants with respect to the reference amyloid-β-negative tau-negative group. Both amyloid-β and tau-positive participants showed higher fluorodeoxyglucose uptake than tau-negative individuals. Using the obtained components, we observed that tau pathology accompanied by YKL-40 (astrocytic marker) was associated with higher grey matter volumes and fluorodeoxyglucose uptake in extensive brain areas. Higher grey matter volumes in key Alzheimer-related regions were also found in association with two other components characterized by a higher expression of amyloid-β in combination with different glial markers: one with higher GFAP and S100b levels (astrocytic markers) and the other one with interleukin-6 (pro-inflammatory). Notably, these components' expression had different behaviours across amyloid-β/tau stages. Taken together, our results show that CSF amyloid-β and phosphorylated tau, in combination with different aspects of glial response, have distinctive associations with higher grey matter volumes and increased glucose metabolism in key Alzheimer-related regions. These mechanisms combine to produce transient higher grey matter volumes and fluorodeoxyglucose uptake at the earliest stages of the Alzheimer's continuum, which may revert later on the course of the disease when neurodegeneration drives structural and metabolic cerebral changes