Linking Cognitive Integrity to Working Memory Dynamics in the Aging Human Brain.

Aging is accompanied by a decline of working memory, an important cognitive capacity that involves stimulus-selective neural activity that persists after stimulus presentation. Here, we unraveled working memory dynamics in older human adults (male and female) including those diagnosed with mild cognitive impairment (MCI) using a combination of behavioral modeling, neuropsychological assessment, and MEG recordings of brain activity. Younger adults (male and female) were studied with behavioral modeling only. Participants performed a visuospatial delayed match-to-sample task under systematic manipulation of the delay and distance between sample and test stimuli. Their behavior (match/nonmatch decisions) was fit with a computational model permitting the dissociation of noise in the internal operations underlying the working memory performance from a strategic decision threshold. Task accuracy decreased with delay duration and sample/test proximity. When sample/test distances were small, older adults committed more false alarms than younger adults. The computational model explained the participants' behavior well. The model parameters reflecting internal noise (not decision threshold) correlated with the precision of stimulus-selective cortical activity measured with MEG during the delay interval. The model uncovered an increase specifically in working memory noise in older compared with younger participants. Furthermore, in the MCI group, but not in the older healthy controls, internal noise correlated with the participants' clinically assessed cognitive integrity. Our results are consistent with the idea that the stability of working memory contents deteriorates in aging, in a manner that is specifically linked to the overall cognitive integrity of individuals diagnosed with MCI.

Temporal Expectation Hastens Decision Onset But Does Not Affect Evidence Quality.

The ability to predict the timing of forthcoming events, known as temporal expectation, has a strong impact on human information processing. Although there is growing consensus that temporal expectations enhance the speed and accuracy of perceptual decisions, it remains unclear whether they affect the decision process itself, or non-decisional (sensory/motor) processes. Here, healthy human participants (N = 21; 18 female) used predictive auditory cues to anticipate the timing of low-contrast visual stimuli they were required to detect. Modeling of the behavioral data using a prominent sequential sampling model indicated that temporal expectations speeded up non-decisional processes but had no effect on decision formation. Electrophysiological recordings confirmed and extended this result: temporal expectations hastened the onset of a neural signature of decision formation but had no effect on its build-up rate. Anticipatory α band power was modulated by temporal expectation and co-varied with intrinsic trial-by-trial variability in behavioral and neural signatures of the onset latency of the decision process. These findings highlight how temporal predictions optimize our interaction with unfolding sensory events.SIGNIFICANCE STATEMENT Temporal expectation enhances performance, but the locus of this effect remains debated. Here, we contrasted the two dominant accounts: enhancement through (1) expedited decision onset, or (2) an increase in the quality of sensory evidence. We manipulated expectations about the onset of a dim visual target using a temporal cueing paradigm, and probed the locus of the expectation effect with two complementary approaches: drift diffusion modeling (DDM) of behavior, and estimation of the onset and progression of the decision process from a supramodal accumulation-to-bound signal in simultaneously measured EEG signals. Behavioral modeling and neural data provided strong, converging evidence for an account in which temporal expectations enhance perception by speeding up decision onset, without affecting evidence quality.

Peripheral Tolerance Checkpoints Imposed by Ubiquitous Antigen Expression Limit Antigen-Specific B Cell Responses under Strongly Immunogenic Conditions.

A series of layered peripheral checkpoints maintain self-reactive B cells in an unresponsive state. Autoantibody production occurs when these checkpoints are breached; however, when and how this occurs is largely unknown. In particular, how self-reactive B cells are restrained during bystander inflammation in otherwise healthy individuals is poorly understood. A weakness has been the unavailability of methods capable of dissecting physiologically relevant B cell responses without the use of an engineered BCR. Resolving this will provide insights that decipher how this process goes awry during autoimmunity or could be exploited for therapy. In this study, we use a strong adjuvant to provide bystander innate and adaptive signals that promote B cell responsiveness in conjunction with newly developed B cell detection tools to study in detail the ways that peripheral tolerance mechanisms limit the expansion and function of self-reactive B cells activated under these conditions. We show that although self-reactive B cells are recruited into the germinal center, their development does not proceed, possibly because of rapid counterselection. Consequently, differentiation of plasma cells is blunted, and Ab responses are transient and devoid of affinity maturation. We propose this approach, and these tools can be more widely applied to track Ag-specific B cell responses to more disease-relevant Ags, without the need for BCR transgenic mice, in settings where tolerance pathways are compromised or have been genetically manipulated to drive stronger insights into the biology underlying B cell-mediated autoimmunity.

Noradrenergic and Cholinergic Modulation of Belief Updating.

To make optimal predictions in a dynamic environment, the impact of new observations on existing beliefs-that is, the learning rate-should be guided by ongoing estimates of change and uncertainty. Theoretical work has proposed specific computational roles for various neuromodulatory systems in the control of learning rate, but empirical evidence is still sparse. The aim of the current research was to examine the role of the noradrenergic and cholinergic systems in learning rate regulation. First, we replicated our recent findings that the centroparietal P3 component of the EEG-an index of phasic catecholamine release in the cortex-predicts trial-to-trial variability in learning rate and mediates the effects of surprise and belief uncertainty on learning rate (Study 1, n = 17). Second, we found that pharmacological suppression of either norepinephrine or acetylcholine activity produced baseline-dependent effects on learning rate following nonobvious changes in an outcome-generating process (Study 1). Third, we identified two genes, coding for α2A receptor sensitivity (ADRA2A) and norepinephrine reuptake (NET), as promising targets for future research on the genetic basis of individual differences in learning rate (Study 2, n = 137). Our findings suggest a role for the noradrenergic and cholinergic systems in belief updating and underline the importance of studying interactions between different neuromodulatory systems.

Catecholaminergic Neuromodulation Shapes Intrinsic MRI Functional Connectivity in the Human Brain.

UNLABELLED: The brain commonly exhibits spontaneous (i.e., in the absence of a task) fluctuations in neural activity that are correlated across brain regions. It has been established that the spatial structure, or topography, of these intrinsic correlations is in part determined by the fixed anatomical connectivity between regions. However, it remains unclear which factors dynamically sculpt this topography as a function of brain state. Potential candidate factors are subcortical catecholaminergic neuromodulatory systems, such as the locus ceruleus-norepinephrine system, which send diffuse projections to most parts of the forebrain. Here, we systematically characterized the effects of endogenous central neuromodulation on correlated fluctuations during rest in the human brain. Using a double-blind placebo-controlled crossover design, we pharmacologically increased synaptic catecholamine levels by administering atomoxetine, an NE transporter blocker, and examined the effects on the strength and spatial structure of resting-state MRI functional connectivity. First, atomoxetine reduced the strength of inter-regional correlations across three levels of spatial organization, indicating that catecholamines reduce the strength of functional interactions during rest. Second, this modulatory effect on intrinsic correlations exhibited a substantial degree of spatial specificity: the decrease in functional connectivity showed an anterior-posterior gradient in the cortex, depended on the strength of baseline functional connectivity, and was strongest for connections between regions belonging to distinct resting-state networks. Thus, catecholamines reduce intrinsic correlations in a spatially heterogeneous fashion. We conclude that neuromodulation is an important factor shaping the topography of intrinsic functional connectivity. SIGNIFICANCE STATEMENT: The human brain shows spontaneous activity that is strongly correlated across brain regions. The factors that dynamically sculpt these inter-regional correlation patterns are poorly understood. Here, we test the hypothesis that they are shaped by the catecholaminergic neuromodulators norepinephrine and dopamine. We pharmacologically increased synaptic catecholamine levels and measured the resulting changes in intrinsic fMRI functional connectivity. At odds with common understanding of catecholamine function, we found (1) overall reduced inter-regional correlations across several levels of spatial organization; and (2) a remarkable spatial specificity of this modulatory effect. Our results identify norepinephrine and dopamine as important factors shaping intrinsic functional connectivity and advance our understanding of catecholamine function in the central nervous system.

Parsing the neural signatures of reduced error detection in older age.

Recent work has demonstrated that explicit error detection relies on a neural evidence accumulation process that can be traced in the human electroencephalogram (EEG). Here, we sought to establish the impact of natural aging on this process by recording EEG from young (18-35 years) and older adults (65-88 years) during the performance of a Go/No-Go paradigm in which participants were required to overtly signal their errors. Despite performing the task with equivalent accuracy, older adults reported substantially fewer errors, and the timing of their reports were both slower and more variable. These behavioral differences were linked to three key neurophysiological changes reflecting distinct parameters of the error detection decision process: a reduction in medial frontal delta/theta (2-7 Hz) activity, indicating diminished top-down input to the decision process; a slower rate of evidence accumulation as indexed by the rate of rise of a centro-parietal signal, known as the error positivity; and a higher motor execution threshold as indexed by lateralized beta-band (16-30 Hz) activity. Our data provide novel insight into how the natural aging process affects the neural underpinnings of error detection.

Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.

Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.

The classic P300 encodes a build-to-threshold decision variable.

The P300 component of the human event-related potential has been the subject of intensive experimental investigation across a five-decade period, owing to its apparent relevance to a wide range of cognitive functions and its sensitivity to numerous brain disorders, yet its exact contribution to cognition remains unresolved. Here, we carry out key analyses of the P300 elicited by transient auditory and visual targets to examine its potential role as a 'decision variable' signal that accumulates evidence to a decision bound. Consistent with the latter, we find that the P300 reaches a stereotyped amplitude immediately prior to response execution and that its rate of rise scales with target detection difficulty and accounts for trial-to-trial variance in RT. Computational simulations of an accumulation-to-bound decision process faithfully captured P300 dynamics when its parameters were set by model fits to the RT distributions. Thus, where the dominant explanatory accounts have conceived of the P300 as a unitary neural event, our data reveal it to be a dynamically evolving neural signature of decision formation. These findings place the P300 at the heart of a mechanistically principled framework for understanding decision-making in both the typical and atypical human brain.

Pupil-linked arousal determines variability in perceptual decision making.

Decision making between several alternatives is thought to involve the gradual accumulation of evidence in favor of each available choice. This process is profoundly variable even for nominally identical stimuli, yet the neuro-cognitive substrates that determine the magnitude of this variability are poorly understood. Here, we demonstrate that arousal state is a powerful determinant of variability in perceptual decision making. We measured pupil size, a highly sensitive index of arousal, while human subjects performed a motion-discrimination task, and decomposed task behavior into latent decision making parameters using an established computational model of the decision process. In direct contrast to previous theoretical accounts specifying a role for arousal in several discrete aspects of decision making, we found that pupil diameter was uniquely related to a model parameter representing variability in the rate of decision evidence accumulation: Periods of increased pupil size, reflecting heightened arousal, were characterized by greater variability in accumulation rate. Pupil diameter also correlated trial-by-trial with specific patterns of behavior that collectively are diagnostic of changing accumulation rate variability, and explained substantial individual differences in this computational quantity. These findings provide a uniquely clear account of how arousal state impacts decision making, and may point to a relationship between pupil-linked neuromodulation and behavioral variability. They also pave the way for future studies aimed at augmenting the precision with which people make decisions.

Pupil diameter covaries with BOLD activity in human locus coeruleus.

The locus coeruleus-noradrenergic (LC-NA) neuromodulatory system has been implicated in a broad array of cognitive processes, yet scope for investigating this system's function in humans is currently limited by an absence of reliable non-invasive measures of LC activity. Although pupil diameter has been employed as a proxy measure of LC activity in numerous studies, empirical evidence for a relationship between the two is lacking. In the present study, we sought to rigorously probe the relationship between pupil diameter and BOLD activity localized to the human LC. Simultaneous pupillometry and fMRI revealed a relationship between continuous pupil diameter and BOLD activity in a dorsal pontine cluster overlapping with the LC, as localized via neuromelanin-sensitive structural imaging and an LC atlas. This relationship was present both at rest and during performance of a two-stimulus oddball task, with and without spatial smoothing of the fMRI data, and survived retrospective image correction for physiological noise. Furthermore, the spatial extent of this pupil/LC relationship guided a volume-of-interest analysis in which we provide the first demonstration in humans of a fundamental characteristic of animal LC activity: phasic modulation by oddball stimulus relevance. Taken together, these findings highlight the potential for utilizing pupil diameter to achieve a more comprehensive understanding of the role of the LC-NA system in human cognition.

Short bursts of transcutaneous auricular vagus nerve stimulation enhance evoked pupil dilation as a function of stimulation parameters.

Transcutaneous auricular vagus nerve stimulation (taVNS) is a neurostimulatory technique hypothesised to enhance central noradrenaline. Currently, there is scarce evidence in support of a noradrenergic mechanism of taVNS and limited knowledge on its stimulation parameters (i.e., intensity and pulse width). Therefore, the present study aimed to test whether taVNS enhances pupil dilation, a noradrenergic biomarker, as a function of stimulation parameters. Forty-nine participants received sham (i.e., left ear earlobe) and taVNS (i.e., left ear cymba concha) stimulation in two separate sessions, in a counterbalanced order. We administered short bursts (5s) of seven stimulation settings varying as a function of pulse width and intensity and measured pupil size in parallel. Each stimulation setting was administered sixteen times in separate blocks. We expected short bursts of stimulation to elicit phasic noradrenergic activity as indexed by event-related pupil dilation and event-related temporal derivative. We hypothesised higher stimulation settings, quantified as the total charge per pulse (pulse width x intensity), to drive greater event-related pupil dilation and temporal derivative in the taVNS compared to sham condition. Specifically, we expected stimulation settings in the taVNS condition to be associated with a linear increase in event-related pupil dilation and temporal derivative. We found stimulation settings to linearly increase both pupil measures. In line with our hypothesis, the observed dose-dependent effect was stronger in the taVNS condition. We also found taVNS to elicit more intense and unpleasant sensations than sham stimulation. These results support the hypothesis of a noradrenergic mechanism of taVNS. However, future studies should disentangle whether stimulation elicited sensations mediate the effect of taVNS on evoked pupil dilation.

Flexible sensory-motor mapping rules manifest in correlated variability of stimulus and action codes across the brain.

Humans and non-human primates can flexibly switch between different arbitrary mappings from sensation to action to solve a cognitive task. It has remained unknown how the brain implements such flexible sensory-motor mapping rules. Here, we uncovered a dynamic reconfiguration of task-specific correlated variability between sensory and motor brain regions. Human participants switched between two rules for reporting visual orientation judgments during fMRI recordings. Rule switches were either signaled explicitly or inferred by the participants from ambiguous cues. We used behavioral modeling to reconstruct the time course of their belief about the active rule. In both contexts, the patterns of correlations between ongoing fluctuations in stimulus- and action-selective activity across visual- and action-related brain regions tracked participants' belief about the active rule. The rule-specific correlation patterns broke down around the time of behavioral errors. We conclude that internal beliefs about task state are instantiated in brain-wide, selective patterns of correlated variability.

Methods to Identify Immune Cells in Tissues With a Focus on Skin as a Model.

The skin protects our body from external challenges, insults, and pathogens and consists of two layers, epidermis and dermis. The immune cells of the skin are an integral part of protecting the body and essential for mediating skin immune homeostasis. They are distributed in the epidermal and dermal layers of the skin. Under homeostatic conditions, the mouse and human skin epidermis harbors immune cells such as Langerhans cells and CD8+ T cells, whereas the dermis contains dendritic cells (DCs), mast cells, macrophages, T cells, and neutrophils. Skin immune homeostasis is maintained through communication between epidermal and dermal cells and soluble factors. This communication is important for proper recruitment of immune cells in the skin to mount immune responses during infection/injury or in response to external/internal insults that alter the local cellular milieu. Imbalance in this crosstalk that occurs in association with inflammatory skin disorders such as psoriasis and atopic dermatitis can lead to alterations in the number and type of immune cells contributing to pathological manifestation in these disorders. Profiling changes in the immune cell type, localization, and number can provide important information about disease mechanisms and help design interventional therapeutic strategies. Toward this end, skin cells can be detected and characterized using basic techniques like immunofluorescence, immunohistochemistry, and flow cytometry, and recently developed methods of multiplexing. This article provides an overview on the basic techniques that are widely accessible to researchers to characterize immune cells of the skin. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Understanding neural signals of post-decisional performance monitoring: An integrative review.

Performance monitoring is a key cognitive function, allowing to detect mistakes and adapt future behavior. Post-decisional neural signals have been identified that are sensitive to decision accuracy, decision confidence and subsequent adaptation. Here, we review recent work that supports an understanding of late error/confidence signals in terms of the computational process of post-decisional evidence accumulation. We argue that the error positivity, a positive-going centro-parietal potential measured through scalp electrophysiology, reflects the post-decisional evidence accumulation process itself, which follows a boundary crossing event corresponding to initial decision commitment. This proposal provides a powerful explanation for both the morphological characteristics of the signal and its relation to various expressions of performance monitoring. Moreover, it suggests that the error positivity -a signal with thus far unique properties in cognitive neuroscience - can be leveraged to furnish key new insights into the inputs to, adaptation, and consequences of the post-decisional accumulation process.

Adaptive circuit dynamics across human cortex during evidence accumulation in changing environments.

Many decisions under uncertainty entail the temporal accumulation of evidence that informs about the state of the environment. When environments are subject to hidden changes in their state, maximizing accuracy and reward requires non-linear accumulation of evidence. How this adaptive, non-linear computation is realized in the brain is unknown. We analyzed human behavior and cortical population activity (measured with magnetoencephalography) recorded during visual evidence accumulation in a changing environment. Behavior and decision-related activity in cortical regions involved in action planning exhibited hallmarks of adaptive evidence accumulation, which could also be implemented by a recurrent cortical microcircuit. Decision dynamics in action-encoding parietal and frontal regions were mirrored in a frequency-specific modulation of the state of the visual cortex that depended on pupil-linked arousal and the expected probability of change. These findings link normative decision computations to recurrent cortical circuit dynamics and highlight the adaptive nature of decision-related feedback to the sensory cortex.

Tasmanian devil CD28 and CTLA4 capture CD80 and CD86 from adjacent cells.

Immune checkpoint immunotherapy is a pillar of human oncology treatment with potential for non-human species. The first checkpoint immunotherapy approved for human cancers targeted the CTLA4 protein. CTLA4 can inhibit T cell activation by capturing and internalizing CD80 and CD86 from antigen presenting cells, a process called trans-endocytosis. Similarly, CD28 can capture CD80 and CD86 via trogocytosis and retain the captured ligands on the surface of the CD28-expressing cells. The wild Tasmanian devil (Sarcophilus harrisii) population has declined by 77% due to transmissible cancers that evade immune defenses despite genetic mismatches between the host and tumors. We used a live cell-based assay to demonstrate that devil CTLA4 and CD28 can capture CD80 and CD86. Mutation of evolutionarily conserved motifs in CTLA4 altered functional interactions with CD80 and CD86 in accordance with patterns observed in other species. These results suggest that checkpoint immunotherapies can be translated to evolutionarily divergent species.

Large-scale dynamics of perceptual decision information across human cortex.

Perceptual decisions entail the accumulation of sensory evidence for a particular choice towards an action plan. An influential framework holds that sensory cortical areas encode the instantaneous sensory evidence and downstream, action-related regions accumulate this evidence. The large-scale distribution of this computation across the cerebral cortex has remained largely elusive. Here, we develop a regionally-specific magnetoencephalography decoding approach to exhaustively map the dynamics of stimulus- and choice-specific signals across the human cortical surface during a visual decision. Comparison with the evidence accumulation dynamics inferred from behavior disentangles stimulus-dependent and endogenous components of choice-predictive activity across the visual cortical hierarchy. We find such an endogenous component in early visual cortex (including V1), which is expressed in a low (<20 Hz) frequency band and tracks, with delay, the build-up of choice-predictive activity in (pre-) motor regions. Our results are consistent with choice- and frequency-specific cortical feedback signaling during decision formation.

Generation and Testing of Fluorescent Adaptable Simple Theranostic (FAST) Proteins.

This protocol provides a step-by-step method to create recombinant fluorescent fusion proteins that can be secreted from mammalian cell lines. This builds on many other recombinant protein and fluorescent protein techniques, but is among the first to harness fluorescent fusion proteins secreted directly into cell culture supernatant. This opens new possibilities that are not achievable with proteins produced in bacteria or yeast, such as direct use of the fluorescent protein-secreting cells in live co-culture assays. The Fluorescent Adaptable Simple Theranostic (FAST) protein system includes a histidine purification tag and a tobacco etch virus (TEV) cleavage site, allowing the purification tag and fluorescent protein to be removed for therapeutic use. This protocol is split into five parts: (A) In silico characterization of the gene-of-interest (GOI) and protein-of-interest (POI); (B) design of the expression vector; (C) assembly of the expression vector; (D) transfection of a eukaryotic cell line with the expression vector; (E) testing of the recombinant protein. This extensive protocol can be completed with only polymerase chain reaction (PCR) and cell culture training. Additionally, each part of the protocol can be used independently.

A novel system to map protein interactions reveals evolutionarily conserved immune evasion pathways on transmissible cancers.

Around 40% of humans and Tasmanian devils (Sarcophilus harrisii) develop cancer in their lifetime, compared to less than 10% for most species. In addition, devils are affected by two of the three known transmissible cancers in mammals. Immune checkpoint immunotherapy has transformed human medicine, but a lack of species-specific reagents has limited checkpoint immunology in most species. We developed a cut-and-paste reagent development system and used the fluorescent fusion protein system to show that immune checkpoint interactions are conserved across 160,000,000 years of evolution, CD200 is highly expressed on transmissible tumor cells, and coexpression of CD200R1 can block CD200 surface expression. The system's versatility across species was demonstrated by fusing a fluorescent reporter to a camelid-derived nanobody that binds human programmed death ligand 1. The evolutionarily conserved pathways suggest that naturally occurring cancers in devils and other species can be used to advance our understanding of cancer and immunological tolerance.

Coupling of respiration and attention via the locus coeruleus: Effects of meditation and pranayama.

The locus coeruleus (LC) has established functions in both attention and respiration. Good attentional performance requires optimal levels of tonic LC activity, and must be matched to task consistently. LC neurons are chemosensitive, causing respiratory phrenic nerve firing to increase frequency with higher CO2 levels, and as CO2 level varies with the phase of respiration, tonic LC activity should exhibit fluctuations at respiratory frequency. Top-down modulation of tonic LC activity from brain areas involved in attentional regulation, intended to optimize LC firing to suit task requirements, may have respiratory consequences as well, as increases in LC activity influence phrenic nerve firing. We hypothesize that, due to the physiological and functional overlaps of attentional and respiratory functions of the LC, this small neuromodulatory nucleus is ideally situated to act as a mechanism of synchronization between respiratory and attentional systems, giving rise to a low-amplitude oscillation that enables attentional flexibility, but may also contribute to unintended destabilization of attention. Meditative and pranayama practices result in attentional, emotional, and physiological enhancements that may be partially due to the LC's pivotal role as the nexus in this coupled system. We present original findings of synchronization between respiration and LC activity (via fMRI and pupil dilation) and provide evidence of a relationship between respiratory phase modulation and attentional performance. We also present a mathematical dynamical systems model of respiratory-LC-attentional coupling, review candidate neurophysiological mechanisms of changes in coupling dynamics, and discuss implications for attentional theory, meditation, and pranayama, and possible therapeutic applications.