bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.09.29.560190

Attention-dependent coupling with forebrain and brainstem neuromodulatory nuclei changes across the lifespan

Abstract

Attentional states continuously reflect the predictability and uncertainty in ones environment having important consequences for learning and memory. Beyond well known cortical contributions, rapid shifts in attention are hypothesized to also originate from deep nuclei, such as the basal forebrain (BF) and locus coeruleus (LC) neuromodulatory systems. These systems are also the first to change with aging. Here we characterized the interplay between these systems and their regulation of afferent targets - the hippocampus (HPC) and posterior cingulate cortex (PCC) - across the lifespan. To examine the role of attentional salience on task-dependent functional connectivity, we used a target-distractor go/no go task presented during functional MRI. In younger adults, BF coupling with the HPC, and LC coupling with the PCC, increased with behavioral relevance (targets vs distractors). Although the strength and presence of significant regional coupling changed in middle age, the most striking change in network connectivity was in old age, such that in older adults BF and LC coupling with their cortical afferents was largely absent and replaced by stronger interconnectivity between LC-BF nuclei. Overall rapid changes in attention related to behavioral relevance revealed distinct roles of subcortical neuromodulatory systems. The pronounced changes in functional network architecture across the lifespan suggest a decrease in these distinct roles, with deafferentation of cholinergic and noradrenergic systems associated with a shift towards mutual support during attention guided to external stimuli. Significance statementChanges in attentional control across the lifespan may originate from cortical control networks or subcortical neuromodulatory systems, which are the first sites of age-related neuropathology. In young adults, we demonstrated functional coupling of the basal forebrain with the hippocampus, and locus coeruleus with the posterior cingulate cortex varies with task relevance. This coupling changed in middle age and most strikingly in older adults. In old age, task-dependent coupling between the locus coeruleus and basal forebrain was the predominant connection remaining within the observed network. Older adults exhibit reduced subcortical-cortical connectivity, consistent with a relative neuromodulatory deafferentation, replaced by subcortical-subcortical deep nuclear connectivity. This alteration in noradrenergic and cholinergic signaling has important implications for attention and memory formation and neurocognitive aging.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Cicero, N. G., Riley, E., Swallow, K., De Rosa, E., Anderson, A. K.. 2023-09-30. Attention-dependent coupling with forebrain and brainstem neuromodulatory nuclei changes across the lifespan. https://doi.org/10.1101/2023.09.29.560190

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗