Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders.

In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesized dopaminergic signaling, but also characterized by suffering and the inability to change one's behavior despite negative consequences. In this review, we provide an overview of the RPE theory of phasic dopamine neuron activity and review the gains that have been made through the use of computational reinforcement learning theory as a framework for understanding changes in reward processing. The relative dearth of explicit accounts of punishment learning in computational reinforcement learning theory and its application in neuroscience is highlighted as a significant gap in current computational psychiatric research. Four disorders comprise the main focus of this review: two disorders of traditionally hypothesized hyperdopaminergic function, addiction and schizophrenia, followed by two disorders of traditionally hypothesized hypodopaminergic function, depression and post-traumatic stress disorder (PTSD). Insights gained from a reward processing based reinforcement learning framework about underlying dopaminergic mechanisms and the role of punishment learning (when available) are explored in each disorder. Concluding remarks focus on the future directions required to characterize neuropsychiatric disorders with a hypothesized cause of underlying dopaminergic transmission.

Theta-gamma coupling as a cortical biomarker of brain-computer interface-mediated motor recovery in chronic stroke.

Chronic stroke patients with upper-limb motor disabilities are now beginning to see treatment options that were not previously available. To date, the two options recently approved by the United States Food and Drug Administration include vagus nerve stimulation and brain-computer interface therapy. While the mechanisms for vagus nerve stimulation have been well defined, the mechanisms underlying brain-computer interface-driven motor rehabilitation are largely unknown. Given that cross-frequency coupling has been associated with a wide variety of higher-order functions involved in learning and memory, we hypothesized this rhythm-specific mechanism would correlate with the functional improvements effected by a brain-computer interface. This study investigated whether the motor improvements in chronic stroke patients induced with a brain-computer interface therapy are associated with alterations in phase-amplitude coupling, a type of cross-frequency coupling. Seventeen chronic hemiparetic stroke patients used a robotic hand orthosis controlled with contralesional motor cortical signals measured with EEG. Patients regularly performed a therapeutic brain-computer interface task for 12 weeks. Resting-state EEG recordings and motor function data were acquired before initiating brain-computer interface therapy and once every 4 weeks after the therapy. Changes in phase-amplitude coupling values were assessed and correlated with motor function improvements. To establish whether coupling between two different frequency bands was more functionally important than either of those rhythms alone, we calculated power spectra as well. We found that theta-gamma coupling was enhanced bilaterally at the motor areas and showed significant correlations across brain-computer interface therapy sessions. Importantly, an increase in theta-gamma coupling positively correlated with motor recovery over the course of rehabilitation. The sources of theta-gamma coupling increase following brain-computer interface therapy were mostly located in the hand regions of the primary motor cortex on the left and right cerebral hemispheres. Beta-gamma coupling decreased bilaterally at the frontal areas following the therapy, but these effects did not correlate with motor recovery. Alpha-gamma coupling was not altered by brain-computer interface therapy. Power spectra did not change significantly over the course of the brain-computer interface therapy. The significant functional improvement in chronic stroke patients induced by brain-computer interface therapy was strongly correlated with increased theta-gamma coupling in bihemispheric motor regions. These findings support the notion that specific cross-frequency coupling dynamics in the brain likely play a mechanistic role in mediating motor recovery in the chronic phase of stroke recovery.

Homotopic functional connectivity disruptions in glioma patients are associated with tumor malignancy and overall survival.

BACKGROUND: Gliomas exhibit widespread bilateral functional connectivity (FC) alterations that may be associated with tumor grade. Limited studies have examined the connection-level mechanisms responsible for these effects. Given the typically strong FC observed between mirroring/homotopic brain regions in healthy subjects, we hypothesized that homotopic connectivity (HC) is altered in low-grade and high-grade glioma patients and the extent of disruption is associated with tumor grade and predictive of overall survival (OS) in a cohort of de novo high-grade glioma (World Health Organization [WHO] grade 4) patients. METHODS: We used a mirrored FC-derived cortical parcellation to extract blood-oxygen-level-dependent (BOLD) signals and to quantify FC differences between homotopic pairs in normal-appearing brain in a retrospective cohort of glioma patients and healthy controls. RESULTS: Fifty-nine glioma patients (WHO grade 2, n = 9; grade 4 = 50; mean age, 57.5 years) and 30 healthy subjects (mean age, 65.9 years) were analyzed. High-grade glioma patients showed lower HC compared with low-grade glioma patients and healthy controls across several cortical locations and resting-state networks. Connectivity disruptions were also strongly correlated with hemodynamic lags between homotopic regions. Finally, in high-grade glioma patients with known survival times (n = 42), HC in somatomotor and dorsal attention networks were significantly correlated with OS. CONCLUSIONS: These findings demonstrate an association between tumor grade and HC alterations that may underlie global FC changes and provide prognostic information.

Functional connectivity within glioblastoma impacts overall survival.

BACKGROUND: Glioblastoma (GBM; World Health Organization grade IV) assumes a variable appearance on MRI owing to heterogeneous proliferation and infiltration of its cells. As a result, the neurovascular units responsible for functional connectivity (FC) may exist within gross tumor boundaries, albeit with altered magnitude. Therefore, we hypothesize that the strength of FC within GBMs is predictive of overall survival. METHODS: We used predefined FC regions of interest (ROIs) in de novo GBM patients to characterize the presence of within-tumor FC observable via resting-state functional MRI and its relationship to survival outcomes. RESULTS: Fifty-seven GBM patients (mean age, 57.8 ±â€…13.9 y) were analyzed. Functionally connected voxels, not identifiable on conventional structural images, can be routinely found within the tumor mass and was not significantly correlated to tumor size. In patients with known survival times (n = 31), higher intranetwork FC strength within GBM tumors was associated with better overall survival even after accounting for clinical and demographic covariates. CONCLUSIONS: These findings suggest the possibility that functionally intact regions may persist within GBMs and that the extent to which FC is maintained may carry prognostic value and inform treatment planning.

Chemical cross-linking of a variety of green fluorescent proteins as Förster resonance energy transfer donors for Yukon orange fluorescent protein: A project-based undergraduate laboratory experience.

Förster resonance energy transfer (FRET) is the basis for many techniques used in biomedical research. Due to its wide use in molecular sensing, FRET is commonly introduced in many biology, chemistry, and physics courses. While FRET is of great importance in the biophysical sciences, the complexity and difficulty of constructing FRET experiments has resulted in limited usage in undergraduate laboratory settings. Here, we present a practical undergraduate laboratory experiment for teaching FRET using a diverse set of green-emitting fluorescent proteins (FPs) as donors for a cross-linked Yukon orange FP. This laboratory experiment enables students to make the connection of basic lab procedures to real world applications and can be applied to molecular biology, biochemistry, physical chemistry, and biophysical laboratory courses. Published 2018. This article is a U.S. Government work and is in the public domain in the USA., 46(5):516-522, 2018.