Biology subjects

Hernaus, D.

Publications and source records attributed to Hernaus, D..

7 recordsLinked to original sources

bioRxiv2023

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional nearinfrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural selfregulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

neuroscience↗

bioRxiv2022

Age-dependent changes in the dynamic functional organization of the brain at rest - a cross - cultural replication approach

Age-associated changes in brain function play an important role in the development of neurodegenerative diseases. Although previous work has examined age-related changes in static functional connectivity (FC), accumulating evidence suggests that advancing age is especially associated with alterations in the dynamic interactions and transitions between different brain states, which hitherto has received less attention. Moreover, conclusions of previous studies in this domain are limited by suboptimal replicability of resting state fMRI and culturally homogenous cohorts. Here, we investigate the robustness of age-associated changes in dynamic functional connectivity (dFC) by capitalizing on the availability of fMRI cohorts from two cultures (Western European and Chinese). In both cohorts we consistently identify two distinct connectivity states: a more frequent segregated within-network connectivity state (state I) and a less frequent integrated between-network connectivity state (state II). In both cohorts, older (55-80 years) compared to younger participants (20-35 years) exhibited lower occurrence of and spent less time in state I. Moreover, older participants tended to exhibit more transitions between networks and greater variance in global efficiency. Overall, our cross-cultural replication of age-associated changes in key dFC metrics implies that advancing age is robustly associated with a reorganization of dynamic brain activation that favors the use of less functionally-specific networks. HighlightsAging is associated with a reorganization of dynamic functional brain connectivity. Age-dependent dynamic functional connectivity changes are relatively stable across cultures. Dynamic properties are promising neural indexes for brain aging in older healthy populations.

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bioRxiv2021

Asymmetric effects of acute stress on cost and benefit learning

Stressful events trigger a complex physiological reaction - the fight-or-flight response - that can hamper flexible decision-making. Inspired by key neural and peripheral characteristics of the fight-or-flight response, here we ask whether acute stress changes how humans learn about costs and benefits. Participants were randomly exposed to an acute stress or no-stress control condition after which they completed a cost-benefit reinforcement learning task. Acute stress improved learning to maximize benefits (monetary rewards) relative to minimising energy expenditure (grip force). Using computational modelling, we demonstrate that costs and benefits can exert asymmetric effects on decisions when prediction errors that convey information about the reward value and cost of actions receive inappropriate importance; a process associated with distinct alterations in pupil size fluctuations. These results provide new insights into learning strategies under acute stress - which, depending on the context, may be maladaptive or beneficial - and candidate neuromodulatory mechanisms that could underlie such behaviour.

neuroscience↗

bioRxiv2018

Impaired expected value computations in schizophrenia are associated with a reduced ability to integrate reward probability and magnitude of recent outcomes.

ABSTRACTO_ST_ABSBackgroundC_ST_ABSMotivational deficits in people with schizophrenia (PSZ) are associated with an inability to integrate the magnitude and probability of previous outcomes. The mechanisms that underlie probability-magnitude integration deficits, however, are poorly understood. We hypothesized that increased reliance on \"value-less\" stimulus-response associations, in lieu of expected value (EV)-based learning, could drive probability-magnitude integration deficits in PSZ with motivational deficits.\n\nMethodsHealthy volunteers (n= 38) and PSZ (n=49) completed a reinforcement learning paradigm consisting of four stimulus pairs. Reward magnitude (3/2/1/0 points) and probability (90%/80%/20%/10%) together determined each stimulus EV. Following a learning phase, new and familiar stimulus pairings were presented. Participants were asked to select stimuli with the highest reward value.\n\nResultsPSZ with high motivational deficits made increasingly less optimal choices as the difference in reward value (probability*magnitude) between two competing stimuli increased. Using a previously-validated computational hybrid model, PSZ relied less on EV (\"Q-learning\") and more on stimulus-response learning (\"actor-critic\"), which correlated with SANS motivational deficit severity. PSZ specifically failed to represent reward magnitude, consistent with model demonstrations showing that response tendencies in the actor-critic were preferentially driven by reward probability.\n\nConclusionsProbability-magnitude deficits in PSZ with motivational deficits arise from underutilization of EV in favor of reliance on value-less stimulus-response associations. Consistent with previous work and confirmed by our computational hybrid framework, probability-magnitude integration deficits were driven specifically by a failure to represent reward magnitude. This work reconfirms the importance of decreased Q-learning/increased actor-critic-type learning as an explanatory framework for a range of EV deficits in PSZ.

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bioRxiv2017

Impaired expected value computations coupled with overreliance on prediction error learning in schizophrenia

BackgroundWhile many have emphasized impaired reward prediction error (RPE) signaling in schizophrenia, multiple studies suggest that some decision-making deficits may arise from overreliance on RPE systems together with a compromised ability to represent expected value. Guided by computational frameworks, we formulated and tested two scenarios in which maladaptive representation of expected value should be most evident, thereby delineating conditions that may evoke decision-making impairments in schizophrenia.\n\nMethodsIn a modified reinforcement learning paradigm, 42 medicated people with schizophrenia (PSZ) and 36 healthy volunteers learned to select the most frequently rewarded option in a 75-25 pair: once when presented with more deterministic (90-10) and once when presented with more probabilistic (60-40) pairs. Novel and old combinations of choice options were presented in a subsequent transfer phase. Computational modeling was employed to elucidate contributions from RPE systems (\"actor-critic\") and expected value (\"Q-leaming\").\n\nResultsPSZ showed robust performance impairments with increasing value difference between two competing options, which strongly correlated with decreased contributions from expected value-based (\"Q-leaming\") learning. Moreover, a subtle yet consistent contextual choice bias for the \"probabilistic\" 75 option was present in PSZ, which could be accounted for by a context-dependent RPE in the \"actor-critic\".\n\nConclusionsWe provide evidence that decision-making impairments in schizophrenia increase monotonically with demands placed on expected value computations. A contextual choice bias is consistent with overreliance on RPE-based learning, which may signify a deficit secondary to the maladaptive representation of expected value. These results shed new light on conditions under which decisionmaking impairments may arise.

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bioRxiv2017

A proof-of-principle study of the effect of combined haloperidol and levodopa administration on working memory-related brain activation in humans

Background and PurposeCognitive deficits including impaired working memory are a hallmark feature of schizophrenia. Changes in prefrontal cortex function modulated by dopamine D1 receptors, play a potentially important role in the pathology underlying such deficits. However, pharmacological interventions that selectively engage the D1 receptor are severely restricted for research in humans. The present study is a proof-of-principle for enhancing cognitive performance and associated brain activation via indirect D1 stimulation. Here, we combine the non-selective dopamine agonist L-dopa with the D2-antagonist haloperidol, theoretically producing increased stimulation at the D1 receptor.\n\nExperimental ApproachFourteen healthy volunteers received placebo or combined carbidopa (125 mg, 100mg L-dopa) plus haloperidol (2 mg) orally on two separate occasions according to a within-subjects cross-over design. Drug-induced differences in brain activity were assessed during an N-back working memory task in a 3T magnetic resonance imaging environment.\n\nKey ResultsDrug treatment was associated with a reduction in activity in a large number of brain areas, most prominently occipital/temporal brain areas during 2-back performance, which may be due to the effects of haloperidol specifically. Drug treatment was also associated with greater functional connectivity within parts of the salience network during all N-back trials.\n\nConclusion and ImplicationsThis preliminary study provides initial evidence for combined L-dopa/haloperidol modulation in cognition-related brain areas and networks, which is relevant for the treatment of cognitive impairments in mental illness.

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bioRxiv2017

Catecholaminergic Manipulation Alters Dynamic Network Topology Across Behavioral States

The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both task-free and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared to placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands.

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