Biology subjects

Horga, G.

Publications and source records attributed to Horga, G..

14 recordsLinked to original sources

bioRxiv2025

Pleasure in groove is associated with neuromelanin levels in the substantia nigra of younger healthy individuals: A neuromelanin-sensitive MRI study

The pleasurable urge to move in response to music is called groove. Prior research has suggested a potential link between groove and dopamine function. However, no studies to date have directly investigated the relationship between the two. Here, we aimed to assess individual dopamine function in the substantia nigra of healthy individuals using neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a non-invasive method associated with dopamine function, and to investigate the relationship between the individual dopamine proxy index and sensitivity to the groove experience. In this study, 15 younger (< 48 years) and 16 older ([greater double equals]48 years) healthy individuals participated. Participants listened to ten musical excerpts and rated the groove experience based on "pleasure" and "wanting to move." To assess whether the groove experience is related to NM levels, type of musical excerpts, and sex, we analyzed with linear mixed-effects regression models. The results showed that higher NM levels (p = 0.032) and male sex (p = 0.034) were associated with higher pleasure ratings in the younger group. For the "urge to move" ratings, type of musical excerpts was associated with ratings in both groups (ps < 0.001), where high-groove music (Janata et al., 2012) receiving higher ratings. Taken together, these results suggest that the "pleasure" aspect of the groove experience in younger individuals was related to dopamine levels in the substantia nigra, but may not be associated with the "urge to move." Thus, pleasure and the urge to move are likely to involve distinct dopaminergic pathways and mechanisms, warranting further investigation.

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bioRxiv2025

A corticostriatal learning mechanism linking excess striatal dopamine and auditory hallucinations

1Auditory hallucinations are linked to elevated striatal dopamine, but their underlying computational mechanisms have been obscured by regional heterogeneity in striatal dopamine signaling. To address this, we developed a normative circuit model in which corticostriatal plasticity in the ventral striatum is modulated by reward prediction errors to drive reinforcement learning while that in the sensory-dorsal striatum is modulated by sensory prediction errors derived from internal belief to drive self-supervised learning. We then validate the key predictions of this model using dopamine recordings across striatal regions in mice, as well as human behavior across various tasks including a new hybrid learning task. Finally, we find that changes in learning resulting from optogenetic stimulation of the sensory-dorsal striatum in mice and individual variability in hallucinations in humans are best explained by selectively enhancing dopamine levels in the model sensory-dorsal striatum. These findings identify plasticity mechanisms underlying biased learning of sensory expectations as a biologically plausible link between excess dopamine and hallucinations.

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bioRxiv2024

Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales

Intrinsic neural timescale (INT) is a resting-state fMRI (rs-fMRI) measure that reflects the time window of neural integration within a brain region. Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame censoring and global signal regression (GSR). We used a subset of the HCP Young Adult dataset with runs annotated for breathing patterns (Lynch et al., 2020) and at least one "clean" (reference) run that had minimal head motion and no respiration artifacts; other runs from the same participants (n = 46) were labeled as "non-clean." We found that non-clean runs exhibited brain-wide increases in INT compared to their respective clean runs and the magnitude of error in INT between non-clean and clean runs correlated with the amount of head motion. Importantly, effect sizes were comparable to INT effects reported in the clinical literature. GSR and high-motion frame censoring improved the similarity between INT maps from non-clean runs and their respective clean run. Using a pseudo-random frame-censoring approach, there was a relationship between the amount of censored frames and both the mean INT and mean error, suggesting that frame censoring itself biases INT estimation. A group-level correction procedure reduced this bias and improved similarity between non-clean runs and their respective clean run. Based on our findings, we offer recommendations for rs-fMRI INT studies, which include implementing GSR and high-motion frame censoring with Lomb-Scargle interpolation of censored data, and performing group-level correction of the bias introduced by frame censoring.

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bioRxiv2024

Functional Localization of the Human Auditory and Visual Thalamus Using a Thalamic Localizer Functional Magnetic Resonance Imaging Task

Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due in part to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmark their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

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bioRxiv2023

Covert attention for uncertainty reduction duringsequential inference

A major question in attention research is how the brain identifies task-relevant stimuli in the absence of exogenous instructions or cues. Recent studies propose that endogenous attention control expected information gains (EIG) or, equivalently, minimizes decision uncertainty, but the mechanisms of this process are not understood. We show that, in a task in which participants covertly attended to decision-relevant stimuli, their perceptual sensitivity (d) for discriminating the stimuli depended on the diagnosticity of the stimuli and the participants prior decision uncertainty, consistent with Bayesian EIG. The fronto-parietal network, in particular left areas V3A/B and IPS1/2, integrated uncertainty with diagnosticity in a manner correlating with behavioral effects on d, and uncertainty signals relied on interactions between this network and the medial prefrontal cortex (mPFC). The findings show that covert attention can be deployed based on EIG and reveal the neural mechanisms of this process.

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bioRxiv2023

A Distinct Neural Code Supports Prospection of Future Probabilities During Instrumental Information-Seeking

To make adaptive decisions, we must actively demand information, but relatively little is known about the mechanisms of active information gathering. An open question is how the brain estimates expected information gains (EIG) when comparing the current decision uncertainty with the uncertainty that is expected after gathering information. We examined this question using fMRI in a task in which people placed bids to obtain information in conditions that varied independently by prior decision uncertainty, information diagnosticity, and the penalty for an erroneous choice. Consistent with value of information theory, bids were sensitive to EIG and its components of prior certainty and expected posterior certainty. Expected posterior certainty was decoded above chance from multivoxel activation patterns in the posterior parietal and extrastriate cortices. This representation was independent of instrumental rewards and overlapped with distinct representations of EIG and prior certainty. Thus, posterior parietal and extrastriate cortices are candidates for mediating the prospection of posterior probabilities as a key step to estimate EIG during active information gathering.

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bioRxiv2023

Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease

Alzheimers disease (AD) is a devastating neurodegenerative disease that affects millions of older adults in the US and worldwide. Resting-state functional magnetic resonance imaging (rs-fMRI) has become a widely used neuroimaging tool to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of intrinsic neural signals using rs-fMRI, is thought to quantify the duration that neural information is stored in a local cortical circuit. The heterogeneity of the timescales is considered to be a basis of the functional hierarchy in the brain. In addition, INT captures an aspect of circuit dynamics relevant to excitation/inhibition (E/I) balance, which is thought to be broadly relevant for cognitive functions. Here we examined its relevance to AD. We used rs-fMRI data of 904 individuals from the Alzheimers Disease Neuroimaging Initiative (ADNI) database. The subjects were divided into 4 groups based on their baseline and end-visit clinical status, which were cognitively normal (CN), stable MCI, Converter, and AD groups. Linear mixed effect model and pairwise comparison were implemented to investigate the large-scale hierarchical organization and local differences. We observed high similarities between AD and Converter groups. Specifically, among the eight identified ROIs with distinct INT alterations in AD, three ROIs (inferior temporal, caudate, pallidum areas) exhibit stable and significant alteration in AD converter. In addition, distinct INT related pathological changes in stable MCI and AD/Converter were found. For AD and Converter groups, neural information is stored for a longer time in lower hierarchical order areas, while higher levels of hierarchy seem to be preferentially impaired in stable MCI leading to a less pronounced hierarchical gradient effect. These results inform that the INT holds great potential as an additional measure for AD prediction, a stable biomarker for clinical diagnosis and an important therapeutic target in AD.

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bioRxiv2022

Normative values of neuromelanin-sensitive MRI signal in older adults obtained using a standard protocol for acquisition and analysis

BackgroundThe integrity and function of catecholamine neurotransmitter systems can be assessed using MRI sequences often referred to as neuromelanin-sensitive MRI (NM-MRI). The relevance of this method to neurodegenerative and psychiatric disorders is becoming increasingly evident, and it has potential as a clinical biomarker. To support such future applications, we report here the normative range of NM-MRI signal and volume metrics in cognitively normal older adults. Methods3 Tesla NM-MRI images and demographic and cognitive data were available from 152 cognitively normal older adults aged 53-86 years old at baseline; a subsample of 68 participants also had follow-up NM-MRI data collected around one-year later. NM-MRI images were processed to yield summary measures of volume and signal (contrast-to-noise ratio, CNR) for the substantia nigra (SN) and locus coeruleus (LC) using a recently developed software employing a fully automated algorithm. The extent of annual change in these metrics was quantified and tested for significance using 1-sample t-tests. ResultsBaseline SN signal (CNR) was 10.02% (left SN) and 10.28% (right) and baseline LC signal was 24.71% (left) and 20.42% (right). The only NM-MRI metric to show a significant annual change was a decrease in left SN volume. ConclusionWe report normative values for NM-MRI signal and volume in the SN and LC of cognitively normal older adults and normative values for their change over time. These values may help future efforts to use NM-MRI as a clinical biomarker for adults in this age range by facilitating identification of patients with extreme NM-MRI values.

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bioRxiv2022

Suboptimal foraging decisions and involvement of the ventral tegmental area in human opioid addiction

Addiction is marked by a tendency to exploit sources of reward despite diminishing returns. This behavior is aptly captured by animal patch-foraging models that have recently been extended to humans. Dopamine and norepinephrine centrally mediate addictive behavior and activity in both catecholaminergic systems is proposed to reflect the computations necessary for optimal foraging. However, the specific neural bases of excessive foraging and their role in human addiction are largely unknown. To address this gap, we studied the behavior of people with and without opioid use disorder (OUD) on a patch-foraging task in which they made serial decisions to "harvest" a depleting resource ("patch") for reward or incur a varying cost to "travel" to a replenished patch. In a subset of participants, we used high-resolution neuromelanin-sensitive MRI to image neuromelanin concentration, a proxy for long-term catecholaminergic function, in distinct dopaminergic nuclei (ventral tegmental area, substantia nigra subregions) and the noradrenergic locus coeruleus. While all participants were sensitive to the long-run reward rates of different patch-foraging environments, OUD participants stayed in reward patches longer than optimal--markedly overharvesting a source of reward despite its declining value--and this correlated with more chronic drug use. Overharvesting was selectively associated with lower neuromelanin signal in the ventral tegmental area but not other dopaminergic nuclei, nor the locus coeruleus. Our findings suggest that foraging decisions relevant to addiction involve a ventral-tegmental-area circuit that may signal reward rates in dynamic environments and implicate this circuit in maladaptive reward pursuit in human addiction to opioids. Significance statementPatch-foraging provides a potentially important translational framework for understanding addictive behavior by revealing how maladaptive reward pursuit emerges in more ecologically valid decision contexts. Here, we show that the tendency to exploit sources of reward despite diminishing returns is associated with chronic drug use in people with opioid use disorder, a particularly devastating form of addiction. We further use neuromelanin-sensitive MRI, a neuroimaging measure of the long-term function of dopamine neurons, to reveal that variation in ventral tegmental area neuromelanin signal selectively underlies individual differences in this overharvesting bias. These findings establish a role for specific dopaminergic circuits in patch-foraging decisions and advance understanding of the neurobiology of human addiction to opioids that has so far eluded the field.

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bioRxiv2021

Insightful inference compensates for distorted perception

Introspective agents can recognize the extent to which their internal perceptual experiences deviate from the actual states of the external world. This ability, also known as insight, is critically required for reality testing and is impaired in psychosis, yet very little is known about its cognitive underpinnings. We developed a Bayesian modeling framework and a novel psychophysics paradigm to quantitatively characterize this type of insight while participants experienced a motion after-effect illusion. Participants could incorporate knowledge about the illusion into their decisions when judging the actual direction of a motion stimulus, compensating for the illusion (and often overcompensating). Furthermore, confidence, reaction-time, and pupil-dilation data all showed signatures consistent with inferential adjustments in the Bayesian insight model. Our results suggest that people can question the veracity of what they see by making insightful inferences that incorporate introspective knowledge about internal distortions.

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bioRxiv2021

A neural substrate for Bayesian integration in human parietal cortex

Making adaptive decisions often requires inferring unobservable states based on unreliable information. Bayesian logic prescribes that individuals form probabilistic beliefs about a state by integrating the likelihood of new evidence with their prior beliefs, but human neuroimaging studies on probability representations have not typically examined this integration process. We developed an inference fMRI task in which participants estimated the posterior probability of a hidden state while we parametrically modulated the prior probability of the state, the likelihood of the supporting evidence, and a monetary penalty for estimation inaccuracy. Consistent with a neural substrate for Bayesian integration, activation in left posterior parietal cortex tracked the estimated posterior probability of the solicited state and its components of prior probability and likelihood, all independently of expected value. This activation further reflected deviations in individual reports from objective probabilities. Thus, this region may provide a neural substrate for humans ability to approximate Bayesian inference.

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bioRxiv2020

Human dorsal anterior cingulate neurons signal conflict by amplifying task-relevant information

Hemodynamic activity in dorsal anterior cingulate cortex (dACC) correlates with conflict, suggesting it contributes to conflict processing. This correlation could be explained by multiple neural processes that can be disambiguated by population firing rates patterns. We used targeted dimensionality reduction to characterize activity of populations of single dACC neurons as humans performed a task that manipulates two forms of conflict. Although conflict enhanced firing rates, this enhancement did not come from a discrete population of domain-general conflict-encoding neurons, nor from a distinct conflict-encoding response axis. Nor was it the epiphenomenal consequence of simultaneous coactivation of action plans. Instead, conflict amplified the task-relevant information encoded across the neuronal population. Effects of conflict were weaker and more heterogeneous in the dorsolateral prefrontal cortex (dlPFC), suggesting that dACCs role in conflict processing may be somewhat specialized. Overall, these results support the theory that conflict biases competition between sensorimotor transformation processes occurring in dACC.

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bioRxiv2020

Distinct Hierarchical Alterations of Intrinsic Neural Timescales Account for Different Manifestations of Psychosis

Hierarchical perceptual-inference models of psychosis may provide a holistic framework for understanding psychosis in schizophrenia including heterogeneity in clinical presentations. Particularly, hypothesized alterations at distinct levels of the perceptual-inference hierarchy may explain why hallucinations and delusions tend to cluster together yet sometimes manifest in isolation. To test this, we used a recently developed resting-state fMRI measure of intrinsic neural timescale (INT), which reflects the time window of neural integration and captures hierarchical brain gradients. In analyses examining extended sensory hierarchies that we first validated, we found distinct hierarchical INT alterations for hallucinations versus delusions in the auditory and somatosensory systems, thus providing support for hierarchical perceptual-inference models of psychosis. Simulations using a large-scale biophysical model suggested local elevations of excitation-inhibition ratio at different hierarchical levels as a potential mechanism. More generally, our work highlights the robustness and utility of INT for studying hierarchical processes relevant to basic and clinical neuroscience.

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bioRxiv2019

Reproducibility Assessment of Neuromelanin-Sensitive Magnetic Resonance Imaging Protocols for Region-of-Interest and Voxelwise Analyses

Neuromelanin-sensitive MRI (NM-MRI) provides a noninvasive measure of the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). NM-MRI has been validated as a measure of both dopamine neuron loss, with applications in neurodegenerative disease, and dopamine function, with applications in psychiatric disease. Furthermore, a voxelwise-analysis approach has been validated to resolve substructures, such as the ventral tegmental area (VTA), within midbrain dopaminergic nuclei thought to have distinct anatomical targets and functional roles. NM-MRI is thus a promising tool that could have diverse research and clinical applications to noninvasively interrogate in vivo the dopamine system in neuropsychiatric illness. Although a test-retest reliability study by Langley et al. using the standard NM-MRI protocol recently reported high reliability, a systematic and comprehensive investigation of the performance of the method for various acquisition parameters and preprocessing methods has not been conducted. In particular, most previous studies used relatively thick MRI slices ([~]3 mm), compared to the typical in-plane resolution ([~]0.5 mm) and to the height of the SN ([~]15 mm), to overcome technical limitations such as specific absorption rate and signal-to-noise ratio, at the cost of partial-volume effects. Here, we evaluated the effect of various acquisition and preprocessing parameters on the strength and test-retest reliability of the NM-MRI signal to determine optimized protocols for both region-of-interest (including whole SN/VTA-complex and atlas-defined dopaminergic nuclei) and voxelwise measures. Namely, we determined a combination of parameters that optimizes the strength and reliability of the NM-MRI signal, including acquisition time, slice-thickness, spatial-normalization software, and degree of spatial smoothing. Using a newly developed, detailed acquisition protocol, across two scans separated by 13 days on average, we obtained intra-class correlation values indicating excellent reliability and high contrast-to-noise, which could be achieved with a different set of parameters depending on the measures of interest and experimental constraints such as acquisition time. Based on this, we provide detailed guidelines covering acquisition through analysis and recommendations for performing NM-MRI experiments with high quality and reproducibility. This work provides a foundation for the optimization and standardization of NM-MRI, a promising MRI approach with growing applications throughout clinical and basic neuroscience.\n\nHighlightsO_LIA detailed NM-MRI volume placement protocol is described.\nC_LIO_LIGuidelines covering acquisition through analysis for NM-MRI are given.\nC_LIO_LIA test-retest study in 10 healthy subjects shows high reproducibility for region-of-interest (ROI) and voxelwise analyses.\nC_LIO_LI[~]3 minutes of NM-MRI data is needed for high-quality ROI-analysis.\nC_LIO_LI[~]6 minutes of NM-MRI data is needed for high-quality voxelwise-analysis.\nC_LI

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