Expectation modulates neural representations of valence throughout the human brain

Human response times are governed by dual anticipatory processes with distinct neural signatures

Human behavior is strongly influenced by anticipation, but the underlying neural mechanisms are poorly understood. We obtained intracranial electrocephalography (iEEG) measurements in neurosurgical patients as they performed a simple sensory-motor task with variable (short or long) foreperiod delays that affected anticipation of the cue to respond. Participants showed two forms of anticipatory response biases, distinguished by more premature false alarms (FAs) or faster response times (RTs) on long-delay trials. These biases had distinct neural signatures in prestimulus neural activity modulations that were distributed and intermixed across the brain: the FA bias was most evident in preparatory motor activity immediately prior to response-cue presentation, whereas the RT bias was most evident in visuospatial activity at the beginning of the foreperiod. These results suggest that human anticipatory behavior emerges from a combination of motor-preparatory and attention-like modulations of neural activity, implemented by anatomically widespread and intermixed, but functionally identifiable, brain networks.

Therapeutic Efficacy of Reward Circuit‐Targeted Transcranial Magnetic Stimulation (TMS) on Suicidal Ideation in Depressed Patients: A Sham‐Controlled Trial of Two TMS Protocols

Background: Suicide is one of the leading causes of premature death, and dysfunctional reward processing may serve as a potential mechanism. However, effective treatment targeting reward circuits is rarely reported.

Objective: The present study investigated the therapeutic efficacy of two individualized protocols, repetitive transcranial magnetic stimulation (rTMS) and intermittent theta burst stimulation (iTBS), targeting the left dorsolateral prefrontal cortex (lDLPFC)–nucleus accumbens (NAcc) circuit on suicidal ideation among patients with major depressive disorder (MDD).

Methods: Here, 40 healthy controls (HCs) and 70 MDD patients (MDDs) were recruited for this double‐blinded, sham‐controlled clinical trial. The reward learning process during the Iowa gambling task (IGT) was initially measured at the baseline. Further, 62 MDDs were assigned to receive 15 daily sessions of individualized rTMS (n = 25), iTBS (n = 15), or sham treatment (n = 22) to the site of strongest lDLPFC–NAcc connectivity.

Results: We found MDDs demonstrated abnormalities in both IGT performance and reward‐associated event‐related potential (ERP) components compared to HCs. MDDs in the rTMS and iTBS groups showed significant improvements in suicidal ideation and anhedonia symptoms compared to the sham group. The rTMS group also exhibited a more negative‐going N170 and feedback‐related negativity (FRN) after treatment, and the increase in N170 absolute amplitude posttreatment showed a trend of correlation with improved Temporal Experience Pleasure Scales (TEPSs) and TEPS‐anticipatory (TEPS‐ant) scores.

Conclusion: The current study indicates that reward circuit‐based rTMS and iTBS showed comparable antisuicidal effects in depressive patients, suggesting that the lDLPFC–NAcc pathway may serve as a potential treatment target.

Trial Registration: ClinicalTrials.gov identifier: NCT03991572

Beta and theta oscillations track effort and previous reward in the human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we report an exploratory investigation into this with chronic intracranial recordings from the prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson's disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12 to 20 Hz) oscillations tracking effort on a single-trial basis and PFC theta (4 to 7 Hz) signaling previous trial reward, with no effects of net subjective value. Stimulation of PFC increased overall acceptance of offers and sensitivity to reward while decreasing the impact of effort on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, supports a causal role of PFC for such choices, and seeds hypotheses for future studies.

Dichotomous frequency-dependent phase synchrony in the sensorimotor network characterizes simplistic movement

It is hypothesized that disparate brain regions interact via synchronous activity to control behavior. The nature of these interconnected ensembles remains an area of active investigation, and particularly the role of high frequency synchronous activity in simplistic behavior is not well known. Using intracranial electroencephalography, we explored the spectral dynamics and network connectivity of sensorimotor cortical activity during a simple motor task in seven epilepsy patients. Confirming prior work, we see a "spectral tilt" (increased high-frequency (HF, 70-100 Hz) and decreased low-frequency (LF, 3-33 Hz) broadband oscillatory activity) in motor regions during movement compared to rest, as well as an increase in LF synchrony between these regions using time-resolved phase-locking. We then explored this phenomenon in high frequency and found a robust but opposite effect, where time-resolved HF broadband phase-locking significantly decreased during movement. This "connectivity tilt" (increased LF synchrony and decreased HF synchrony) displayed a graded anatomical dependency, with the most robust pattern occurring in primary sensorimotor cortical interactions and less robust pattern occurring in associative cortical interactions. Connectivity in theta (3-7 Hz) and high beta (23-27 Hz) range had the most prominent low frequency contribution during movement, with theta synchrony building gradually while high beta having the most prominent effect immediately following the cue. There was a relatively sharp, opposite transition point in both the spectral and connectivity tilt at approximately 35 Hz. These findings support the hypothesis that task-relevant high-frequency spectral activity is stochastic and that the decrease in high-frequency synchrony may facilitate enhanced low frequency phase coupling and interregional communication. Thus, the "connectivity tilt" may characterize behaviorally meaningful cortical interactions.

Beta and theta oscillations track effort and previous reward in human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we investigate this with chronic intracranial recordings from prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson's disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12-20 Hz) oscillations tracking subjective effort on a single trial basis and PFC theta (4-7 Hz) signaling previous trial reward. Stimulation of PFC increased overall acceptance of offers in addition to increasing the impact of reward on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, as well as supporting a causal role of PFC for such choices.

High-Definition Transcranial Direct Current Stimulation Improves Decision-Making Ability: A Study Based on EEG

High-definition transcranial direct current stimulation (HD-tDCS) has been shown to modulate decision-making; however, the neurophysiological mechanisms underlying this effect remain unclear. To further explore the neurophysiological processes of decision-making modulated by HD-tDCS, health participants underwent ten anodal (n = 16)/sham (n = 17) HD-tDCS sessions targeting the left DLPFC. Iowa gambling task was performed simultaneously with electroencephalography (EEG) before and after HD-tDCS. Iowa gambling task performance, the P300 amplitude, and the power of theta oscillation as an index of decision-making were compared. Behavioral changes were found that showed anodal HD-tDCS could improve the decision-making function, in which participants could make more advantageous choices. The electrophysiological results showed that the P300 amplitude significantly increased in CZ, CPZ electrode placement site and theta oscillation power significantly activated in FCZ, CZ electrode placement site after anodal HD-tDCS. Significant positive correlations were observed between the changes in the percent use of negative feedback and the changes in theta oscillation power before and after anodal HD-tDCS. This study showed that HD-tDCS is a promising technology in improving decision-making and theta oscillation induced by may be a predictor of improved decision-making.

Anatomical dissociation of intracerebral signals for reward and punishment prediction errors in humans

Whether maximizing rewards and minimizing punishments rely on distinct brain systems remains debated, given inconsistent results coming from human neuroimaging and animal electrophysiology studies. Bridging the gap across techniques, we recorded intracerebral activity from twenty participants while they performed an instrumental learning task. We found that both reward and punishment prediction errors (PE), estimated from computational modeling of choice behavior, correlate positively with broadband gamma activity (BGA) in several brain regions. In all cases, BGA scaled positively with the outcome (reward or punishment versus nothing) and negatively with the expectation (predictability of reward or punishment). However, reward PE were better signaled in some regions (such as the ventromedial prefrontal and lateral orbitofrontal cortex), and punishment PE in other regions (such as the anterior insula and dorsolateral prefrontal cortex). These regions might therefore belong to brain systems that differentially contribute to the repetition of rewarded choices and the avoidance of punished choices.

Whether maximizing rewards and minimizing punishments rely on distinct brain learning systems remains debated. Here, using intracerebral recordings in humans, the authors provide evidence for brain regions differentially engaged in signaling reward and punishment prediction errors that prescribe repetition versus avoidance of past choices.

Theta Synchrony Is Increased near Neural Populations That Are Active When Initiating Instructed Movement

Theta oscillations (3–8 Hz) in the human brain have been linked to perception, cognitive control, and spatial memory, but their relation to the motor system is less clear. We tested the hypothesis that theta oscillations coordinate distributed behaviorally relevant neural representations during movement using intracranial electroencephalography (iEEG) recordings from nine patients (n = 490 electrodes) as they performed a simple instructed movement task. Using high frequency activity (HFA; 70–200 Hz) as a marker of local spiking activity, we identified electrodes that were positioned near neural populations that showed increased activity during instruction and movement. We found that theta synchrony was widespread throughout the brain but was increased near regions that showed movement-related increases in neural activity. These results support the view that theta oscillations represent a general property of brain activity that may also play a specific role in coordinating widespread neural activity when initiating voluntary movement.

Neuronal phase consistency tracks dynamic changes in acoustic spectral regularity

The brain parses the auditory environment into distinct sounds by identifying those acoustic features in the environment that have common relationships (e.g., spectral regularities) with one another and then grouping together the neuronal representations of these features. Although there is a large literature that tests how the brain tracks spectral regularities that are predictable, it is not known how the auditory system tracks spectral regularities that are not predictable and that change dynamically over time. Furthermore, the contribution of brain regions downstream of the auditory cortex to the coding of spectral regularity is unknown. Here, we addressed these two issues by recording electrocorticographic activity, while human patients listened to tone-burst sequences with dynamically varying spectral regularities, and identified potential neuronal mechanisms of the analysis of spectral regularities throughout the brain. We found that the degree of oscillatory stimulus phase consistency (PC) in multiple neuronal-frequency bands tracked spectral regularity. In particular, PC in the delta-frequency band seemed to be the best indicator of spectral regularity. We also found that these regularity representations existed in multiple regions throughout cortex. This widespread reliable modulation in PC - both in neuronal-frequency space and in cortical space - suggests that phase-based modulations may be a general mechanism for tracking regularity in the auditory system specifically and other sensory systems more generally. Our findings also support a general role for the delta-frequency band in processing the regularity of auditory stimuli.

Cortical neurons multiplex reward-related signals along with sensory and motor information

Rewards are known to influence neural activity associated with both motor preparation and execution. This influence can be exerted directly upon the primary motor (M1) and somatosensory (S1) cortical areas via the projections from reward-sensitive dopaminergic neurons of the midbrain ventral tegmental areas. However, the neurophysiological manifestation of reward-related signals in M1 and S1 are not well understood. Particularly, it is unclear how the neurons in these cortical areas multiplex their traditional functions related to the control of spatial and temporal characteristics of movements with the representation of rewards. To clarify this issue, we trained rhesus monkeys to perform a center-out task in which arm movement direction, reward timing, and magnitude were manipulated independently. Activity of several hundred cortical neurons was simultaneously recorded using chronically implanted microelectrode arrays. Many neurons (9-27%) in both M1 and S1 exhibited activity related to reward anticipation. Additionally, neurons in these areas responded to a mismatch between the reward amount given to the monkeys and the amount they expected: A lower-than-expected reward caused a transient increase in firing rate in 60-80% of the total neuronal sample, whereas a larger-than-expected reward resulted in a decreased firing rate in 20-35% of the neurons. Moreover, responses of M1 and S1 neurons to reward omission depended on the direction of movements that led to those rewards. These observations suggest that sensorimotor cortical neurons corepresent rewards and movement-related activity, presumably to enable reward-based learning.

Neural and neurochemical basis of reinforcement-guided decision making

Decision making is an adaptive behavior that takes into account several internal and external input variables and leads to the choice of a course of action over other available and often competing alternatives. While it has been studied in diverse fields ranging from mathematics, economics, ecology, and ethology to psychology and neuroscience, recent cross talk among perspectives from different fields has yielded novel descriptions of decision processes. Reinforcement-guided decision making models are based on economic and reinforcement learning theories, and their focus is on the maximization of acquired benefit over a defined period of time. Studies based on reinforcement-guided decision making have implicated a large network of neural circuits across the brain. This network includes a wide range of cortical (e.g., orbitofrontal cortex and anterior cingulate cortex) and subcortical (e.g., nucleus accumbens and subthalamic nucleus) brain areas and uses several neurotransmitter systems (e.g., dopaminergic and serotonergic systems) to communicate and process decision-related information. This review discusses distinct as well as overlapping contributions of these networks and neurotransmitter systems to the processing of decision making. We end the review by touching on neural circuitry and neuromodulatory regulation of exploratory decision making.