The Brain’s Reward System in Health and Disease

Lewis, Robert W.; Florio, Ermanno; Punzo, Daniela; Borrelli, Emiliana

doi:10.1007/978-3-030-81147-1_4

Cited by 55 publications

(29 citation statements)

References 137 publications

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“…Moreover, considering the important part in goal‐directed and habitual learning with the caudate, a hypothesis may be confirmed that compulsive symptoms are associated with an imbalance between the two systems (Peng et al, 2022). And it collaborated with the NAcc on the reward system and were linked with motivation processing (Lewis et al, 2021). So our neuroimaging findings could supplement previous investigations that putamen dysfunction may become an etiological marker for OCD (Yu et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Abnormal voxel‐mirrored homotopic connectivity in first‐episode, drug‐naïve patients with obsessive–compulsive disorder

Xu,

Zhang

2023

Eur J of Neuroscience

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Prior studies suggest that obsessive–compulsive disorder (OCD) can cause both anatomical and functional variations in the brain, but to date, altered functional synchronization between two functional hemispheres remains unclear in OCD patients. Voxel‐mirrored homotopic connectivity (VMHC) is defined as the temporal correlation of spontaneous low‐frequency blood oxygenation level‐dependent signal fluctuations across mirror regions of hemisphere revealing the homotopic connectivity between each voxel in one hemisphere and its mirrored counterpart in the contralateral hemisphere. To investigate the alterations of brain regional function and VMHC in patients with OCD, the current study enrolled 103 OCD patients and 118 healthy controls, undergoing resting‐state functional magnetic resonance imaging. Compared to healthy controls (HCs), patients had decreased VMHC in bilateral cerebellum, lingual and fusiform gyrus; bilateral paracentral lobule, pre and postcentral gyrus; and bilateral superior and middle temporal gyrus, putamen and bilateral precuneus without global signal regression. And we found mostly similar results after regressing global signals; apart from the regions mentioned above, decreased in bilateral cuneus and calcarine was also showed. Furthermore, the mean VMHC values of the left cerebellum were negatively correlated with the obsession scores (ρ = −.204, π = .039). The decreased values in right fusiform and putamen were negatively correlated with duration of disease (ρ = −.205, π = .038; ρ = −.196, π = .047). We confirmed a significant VMHC reduction in OCD patients in broad areas. Our findings suggest that the patients tend to disconnect information exchange across hemispheres.

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Section: Discussionmentioning

confidence: 99%

Abnormal voxel‐mirrored homotopic connectivity in first‐episode, drug‐naïve patients with obsessive–compulsive disorder

Xu,

Zhang

2023

Eur J of Neuroscience

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“…Having validated the SPECTRE method directly with simultaneous fMRI/EEG, iEEG, and an attention paradigm, we investigated the ability of SPECTRE to faithfully reconstruct the well known neural ‘reward circuit’ that is one of the most important in understanding human cognition, emotion, and behavior ( 20 – 22 ) and is of great clinical significance in the understanding of addiction ( 23 , 24 ), mood disorders ( 25 , 26 ), and a variety of other conditions ( 27 ).…”

Section: Investigation Of the ‘Reward Circuit’mentioning

confidence: 99%

Imaging of brain electric field networks

Frank,

Galinsky,

Krigolson

et al. 2024

Preprint

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We present a method for direct imaging of the electric field networks in the hu- man brain from electroencephalography (EEG) data with much higher tem- poral and spatial resolution than functional MRI (fMRI), without the con- comitant distortions. The method is validated using simultaneous EEG/fMRI data in healthy subjects, intracranial EEG data in epilepsy patients, and in a direct comparison with standard EEG analysis in a well-established atten- tion paradigm. The method is then demonstrated on a very large cohort of subjects performing a standard gambling task designed to activate the brain’s ’reward circuit’. The technique uses the output from standard EEG systems and thus has potential for immediate benefit to a broad range of important basic scientific and clinical questions concerning brain electrical activity, but also provides an inexpensive and portable alternative to function MRI (fMRI).

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“…[15][16][17] Reward processing is performed primarily by the mesolimbic system, with the ventral tegmental area thought to play a major role in directing reward-related responses and communicating reward-related information directly and indirectly to other limbic regions such as the prefrontal cortex, amygdala, cingulate, and insula. [18][19][20] Moreover, reward processing signals have been shown to be linked to risk-taking. 21,22 Reward prediction error signals (RPE) are signals associated with the difference between expected and received reward coded by dopaminergic neurons, and these signals have been suggested to modulate future risk-taking.…”

Section: Introductionmentioning

confidence: 99%

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Hughes,

Qian,

Zargari

et al. 2024

Preprint

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Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking.Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient.Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex (p=0.0022), high-gamma in the anterior cingulate (p=0.0004), and high-gamma in the insula (p=0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power (p=2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex (p=2.0E-4), broad frequencies in amygdala (p=2.0E-4), and theta to low-gamma in insula (p=4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal (p=0.0048) and with patient impulsivity (p=0.00478).Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.

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The Brain’s Reward System in Health and Disease

Cited by 55 publications

References 137 publications

Abnormal voxel‐mirrored homotopic connectivity in first‐episode, drug‐naïve patients with obsessive–compulsive disorder

Abnormal voxel‐mirrored homotopic connectivity in first‐episode, drug‐naïve patients with obsessive–compulsive disorder

Imaging of brain electric field networks

Reward Circuit Local Field Potential Modulations Precede Risk Taking

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