Encoding of continuous perceptual choices in human early visual cortex

Introduction: Research on the neural mechanisms of perceptual decision-making has typically focused on simple categorical choices, say between two alternative motion directions. Studies on such discrete alternatives have often suggested that choices are encoded either in a motor-based or in an abstract, categorical format in regions beyond sensory cortex. Methods: In this study, we used motion stimuli that could vary anywhere between 0 degrees and 360 degrees to assess how the brain encodes choices for features that span the full sensory continuum. We employed a combination of neuroimaging and encoding models based on Gaussian process regression to assess how either stimuli or choices were encoded in brain responses. Results: We found that single-voxel tuning patterns could be used to reconstruct the trial-by-trial physical direction of motion as well as the participants' continuous choices. Importantly, these continuous choice signals were primarily observed in early visual areas. The tuning properties in this region generalized between choice encoding and stimulus encoding, even for reports that reflected pure guessing. Discussion: We found only little information related to the decision outcome in regions beyond visual cortex, such as parietal cortex, possibly because our task did not involve differential motor preparation. This could suggest that decisions for continuous stimuli take can place already in sensory brain regions, potentially using similar mechanisms to the sensory recruitment in visual working memory

Encoding of continuous perceptual choices in human early visual cortex

IntroductionResearch on the neural mechanisms of perceptual decision-making has typically focused on simple categorical choices, say between two alternative motion directions. Studies on such discrete alternatives have often suggested that choices are encoded either in a motor-based or in an abstract, categorical format in regions beyond sensory cortex.MethodsIn this study, we used motion stimuli that could vary anywhere between 0° and 360° to assess how the brain encodes choices for features that span the full sensory continuum. We employed a combination of neuroimaging and encoding models based on Gaussian process regression to assess how either stimuli or choices were encoded in brain responses.ResultsWe found that single-voxel tuning patterns could be used to reconstruct the trial-by-trial physical direction of motion as well as the participants’ continuous choices. Importantly, these continuous choice signals were primarily observed in early visual areas. The tuning properties in this region generalized between choice encoding and stimulus encoding, even for reports that reflected pure guessing.DiscussionWe found only little information related to the decision outcome in regions beyond visual cortex, such as parietal cortex, possibly because our task did not involve differential motor preparation. This could suggest that decisions for continuous stimuli take can place already in sensory brain regions, potentially using similar mechanisms to the sensory recruitment in visual working memory

Neurocan genome-wide psychiatric risk variant affects explicit memory performance and hippocampal function in healthy humans

Alterations of the brain extracellular matrix (ECM) can perturb the structure and function of brain networks like the hippocampus, a key region in human memory that is commonly affected in psychiatric disorders. Here, we investigated the potential effects of a genome‐wide psychiatric risk variant in the NCAN gene encoding the ECM proteoglycan neurocan (rs1064395) on memory performance, hippocampal function and cortical morphology in young, healthy volunteers. We assessed verbal memory performance in two cohorts (N = 572, 302) and found reduced recall performance in risk allele (A) carriers across both cohorts. In 117 participants, we performed functional magnetic resonance imaging using a novelty‐encoding task with visual scenes. Risk allele carriers showed higher false alarm rates during recognition, accompanied by inefficiently increased left hippocampal activation. To assess effects of rs1064395 on brain morphology, we performed voxel‐based morphometry in 420 participants from four independent cohorts and found lower grey matter density in the ventrolateral and rostral prefrontal cortex of risk allele carriers. In silico eQTL analysis revealed that rs1064395 SNP is linked not only to increased prefrontal expression of the NCAN gene itself, but also of the neighbouring HAPLN4 gene, suggesting a more complex effect of the SNP on ECM composition. Our results suggest that the NCAN rs1064395 A allele is associated with lower hippocampus‐dependent memory function, variation of prefrontal cortex structure and ECM composition. Considering the well‐documented hippocampal and prefrontal dysfunction in bipolar disorder and schizophrenia, our results may reflect an intermediate phenotype by which NCAN rs1064395 contributes to disease risk

A comprehensive score reflecting memory-related fMRI activations and deactivations as potential biomarker for neurocognitive aging

Older adults and particularly those at risk for developing dementia typically show a decline in episodic memory performance, which has been associated with altered memory network activity detectable via functional magnetic resonance imaging (fMRI). To quantify the degree of these alterations, a score has been developed as a putative imaging biomarker for successful aging in memory for older adults (Functional Activity Deviations during Encoding, FADE; Düzel et al., Hippocampus, 2011; 21: 803–814). Here, we introduce and validate a more comprehensive version of the FADE score, termed FADE-SAME (Similarity of Activations during Memory Encoding), which differs from the original FADE score by considering not only activations but also deactivations in fMRI contrasts of stimulus novelty and successful encoding, and by taking into account the variance of young adults' activations. We computed both scores for novelty and subsequent memory contrasts in a cohort of 217 healthy adults, including 106 young and 111 older participants, as well as a replication cohort of 117 young subjects. We further tested the stability and generalizability of both scores by controlling for different MR scanners and gender, as well as by using different data sets of young adults as reference samples. Both scores showed robust agegroup-related differences for the subsequent memory contrast, and the FADE-SAME score additionally exhibited age-group-related differences for the novelty contrast. Furthermore, both scores correlate with behavioral measures of cognitive aging, namely memory performance. Taken together, our results suggest that single-value scores of memory-related fMRI responses may constitute promising biomarkers for quantifying neurocognitive aging

A comprehensive score reflecting memory-related fMRI activations and deactivations as potential biomarker for neurocognitive aging

Older adults and particularly those at risk for developing dementia typically show a decline in episodic memory performance, which has been associated with altered memory network activity detectable via functional magnetic resonance imaging (fMRI). To quantify the degree of these alterations, a score has been developed as a putative imaging biomarker for successful aging in memory for older adults (Functional Activity Deviations during Encoding, FADE; Düzel et al., Hippocampus, 2011; 21: 803–814). Here, we introduce and validate a more comprehensive version of the FADE score, termed FADE-SAME (Similarity of Activations during Memory Encoding), which differs from the original FADE score by considering not only activations but also deactivations in fMRI contrasts of stimulus novelty and successful encoding, and by taking into account the variance of young adults' activations. We computed both scores for novelty and subsequent memory contrasts in a cohort of 217 healthy adults, including 106 young and 111 older participants, as well as a replication cohort of 117 young subjects. We further tested the stability and generalizability of both scores by controlling for different MR scanners and gender, as well as by using different data sets of young adults as reference samples. Both scores showed robust agegroup-related differences for the subsequent memory contrast, and the FADE-SAME score additionally exhibited age-group-related differences for the novelty contrast. Furthermore, both scores correlate with behavioral measures of cognitive aging, namely memory performance. Taken together, our results suggest that single-value scores of memory-related fMRI responses may constitute promising biomarkers for quantifying neurocognitive aging

Machine learning‐based classification of Alzheimer's disease and its at‐risk states using personality traits, anxiety, and depression

Background Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages. Methods In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aβ42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). Results Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets. Conclusion Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages