Humans strategically shift decision bias by flexibly adjusting sensory evidence accumulation

A diffusion decision model analysis of the cognitive effects of neurofeedback for ADHD

OBJECTIVE

To examine cognitive effects of neurofeedback (NF) for attention-deficit hyperactivity disorder (ADHD) as a secondary outcome of a randomized clinical trial.

METHOD

In a double-blind randomized clinical trial (NCT02251743), 133 7-10-year olds with ADHD received either 38 sessions of NF (n = 78) or control treatment (n = 55) and performed an integrated visual and auditory continuous performance test at baseline, mid- and end-treatment. We used the diffusion decision model to decompose integrated visual and auditory continuous performance test performance at each assessment into cognitive components: efficiency of integrating stimulus information (v), context sensitivity (cv), response cautiousness (a), response bias (z/a), and nondecision time for perceptual encoding and response execution (Ter). Based on prior findings, we tested whether the components known to be deficient improved with NF and explored whether other cognitive components improved using linear mixed modeling.

RESULTS

Before NF, children with ADHD showed main deficits in integrating stimulus information (v), which led to less accurate and slower responses than healthy controls (p = .008). The NF group showed significantly more improvement in integrating auditory stimulus information (v) than control treatment (significant group-by-time-by-modality effect: p = .044).

CONCLUSIONS

NF seems to improve v, deficient in ADHD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal

Perceptual decision-making is highly dependent on the momentary arousal state of the brain, which fluctuates over time on a scale of hours, minutes, and even seconds. The textbook relationship between momentary arousal and task performance is captured by an inverted U-shape, as put forward in the Yerkes-Dodson law. This law suggests optimal performance at moderate levels of arousal and impaired performance at low or high arousal levels. However, despite its popularity, the evidence for this relationship in humans is mixed at best. Here, we use pupil-indexed arousal and performance data from various perceptual decision-making tasks to provide converging evidence for the inverted U-shaped relationship between spontaneous arousal fluctuations and performance across different decision types (discrimination, detection) and sensory modalities (visual, auditory). To further understand this relationship, we built a neurobiologically plausible mechanistic model and show that it is possible to reproduce our findings by incorporating two types of interneurons that are both modulated by an arousal signal. The model architecture produces two dynamical regimes under the influence of arousal: one regime in which performance increases with arousal and another regime in which performance decreases with arousal, together forming an inverted U-shaped arousal-performance relationship. We conclude that the inverted U-shaped arousal-performance relationship is a general and robust property of sensory processing. It might be brought about by the influence of arousal on two types of interneurons that together act as a disinhibitory pathway for the neural populations that encode the available sensory evidence used for the decision.

Short-Term Effect of Auditory Stimulation on Neural Activities: A Scoping Review of Longitudinal Electroencephalography and Magnetoencephalography Studies

Explored through EEG/MEG, auditory stimuli function as a suitable research probe to reveal various neural activities, including event-related potentials, brain oscillations and functional connectivity. Accumulating evidence in this field stems from studies investigating neuroplasticity induced by long-term auditory training, specifically cross-sectional studies comparing musicians and non-musicians as well as longitudinal studies with musicians. In contrast, studies that address the neural effects of short-term interventions whose duration lasts from minutes to hours are only beginning to be featured. Over the past decade, an increasing body of evidence has shown that short-term auditory interventions evoke rapid changes in neural activities, and oscillatory fluctuations can be observed even in the prestimulus period. In this scoping review, we divided the extracted neurophysiological studies into three groups to discuss neural activities with short-term auditory interventions: the pre-stimulus period, during stimulation, and a comparison of before and after stimulation. We show that oscillatory activities vary depending on the context of the stimuli and are greatly affected by the interplay of bottom-up and top-down modulational mechanisms, including attention. We conclude that the observed rapid changes in neural activitiesin the auditory cortex and the higher-order cognitive part of the brain are causally attributed to short-term auditory interventions.

Knowledge of Threat Biases Perceptual Decision Making in Anxiety: Evidence From Signal Detection Theory and Drift Diffusion Modeling

Background

Threat biases are considered key factors in the development and maintenance of anxiety. However, these biases are poorly operationalized and remain unquantified. Furthermore, it is unclear whether and how prior knowledge of threat and its uncertainty induce these biases and how they manifest in anxiety.

Method

Participants (n = 55) used prestimulus cues to decide whether the subsequently presented stimuli were threatening or neutral. The cues either provided no information about the probability (high uncertainty) or indicated high probability (low uncertainty) of encountering threatening or neutral targets. We used signal detection theory and hierarchical drift diffusion modeling to quantify bias.

Results

High-uncertainty threat cues improved discrimination of subsequent threatening and neutral stimuli more than neutral cues. However, anxiety was associated with worse discrimination of threatening versus neutral stimuli following high-uncertainty threat cues. Using hierarchical drift diffusion modeling, we found that threat cues biased decision making not only by shifting the starting point of evidence accumulation toward the threat decision but also by increasing the efficiency with which sensory evidence was accumulated for both threat-related and neutral decisions. However, higher anxiety was associated with a greater shift of starting point toward the threat decision but not with the efficiency of evidence accumulation.

Conclusions

Using computational modeling, these results highlight the biases by which knowledge regarding uncertain threat improves perceptual decision making but impairs it in case of anxiety.

Adaptive decision-making depends on pupil-linked arousal in rats performing tactile discrimination tasks

Perceptual decision-making is a dynamic cognitive process and is shaped by many factors, including behavioral state, reward contingency, and sensory environment. To understand the extent to which adaptive behavior in decision-making is dependent on pupil-linked arousal, we trained head-fixed rats to perform perceptual decision-making tasks and systematically manipulated the probability of Go and No-go stimuli while simultaneously measuring their pupil size in the tasks. Our data demonstrated that the animals adaptively modified their behavior in response to the changes in the sensory environment. The response probability to both Go and No-go stimuli decreased as the probability of the Go stimulus being presented decreased. Analyses within the signal detection theory framework showed that while the animals' perceptual sensitivity was invariant, their decision criterion increased as the probability of the Go stimulus decreased. Simulation results indicated that the adaptive increase in the decision criterion will increase possible water rewards during the task. Moreover, the adaptive decision-making is dependent on pupil-linked arousal as the increase in the decision criterion was the largest during low pupil-linked arousal periods. Taken together, our results demonstrated that the rats were able to adjust their decision-making to maximize rewards in the tasks, and that adaptive behavior in perceptual decision-making is dependent on pupil-linked arousal.NEW & NOTEWORTHY Perceptual decision-making is a dynamic cognitive process and is shaped by many factors. However, the extent to which changes in sensory environment result in adaptive decision-making remains poorly understood. Our data provided new experimental evidence demonstrating that the rats were able to adaptively modify their decision criterion to maximize water reward in response to changes in the statistics of the sensory environment. Furthermore, the adaptive decision-making is dependent on pupil-linked arousal.

Predictions and rewards affect decision-making but not subjective experience

To survive, organisms constantly make decisions to avoid danger and maximize rewards in information-rich environments. As a result, decisions about sensory input are not only driven by sensory information but also by other factors, such as the expected rewards of a decision (known as the payoff matrix) or by information about temporal regularities in the environment (known as cognitive priors or predictions). However, it is unknown to what extent these different types of information affect subjective experience or whether they merely result in nonperceptual response criterion shifts. To investigate this question, we used three carefully matched manipulations that typically result in behavioral shifts in decision criteria: a visual illusion (Müller-Lyer condition), a punishment scheme (payoff condition), and a change in the ratio of relevant stimuli (base rate condition). To gauge shifts in subjective experience, we introduce a task in which participants not only make decisions about what they have just seen but are also asked to reproduce their experience of a target stimulus. Using Bayesian ordinal modeling, we show that each of these three manipulations affects the decision criterion as intended but that the visual illusion uniquely affects sensory experience as measured by reproduction. In a series of follow-up experiments, we use computational modeling to show that although the visual illusion results in a distinct drift-diffusion (DDM) parameter profile relative to nonsensory manipulations, reliance on DDM parameter estimates alone is not sufficient to ascertain whether a given manipulation is perceptual or nonperceptual.

Brain signatures indexing variation in internal processing during perceptual decision-making

Brain activity is highly variable during a task. Discovering, characterizing, and linking variability in brain activity to internal processes has primarily relied on experimental manipulations. However, changes in internal processing could arise from many factors independent of experimental conditions. Here we utilize a data-driven clustering method based on modularity-maximation to identify consistent spatial-temporal EEG activity patterns across individual trials. Subjects (N = 25) performed a motion discrimination task with six interleaved levels of coherence. Clustering identified two discrete subtypes of trials with different patterns of activity. Surprisingly, Subtype 1 occurred more frequently in trials with lower motion coherence but was associated with faster response times. Computational modeling suggests that Subtype 1 was characterized by a lower threshold for reaching a decision. These results highlight across-trial variability in decision processes traditionally hidden to experimenters and provide a method for identifying endogenous brain state variability relevant to cognition and behavior.

Frontal-occipital phase synchronization predicts occipital alpha power in perceptual decision-making

Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4-30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09862-7.

Neurodynamics of awareness detection in Tibetan immigrants: evidence from EEG analysis

The psychological effects of long-term exposure to high-altitude environments have attracted great attention. These effects are usually attributed to the diminished cognitive resources due to high-altitude exposure. This study employed electroencephalography (EEG) to investigate the effects of exposure duration on awareness detection tasks. Neither reaction time nor accuracy showed the direct effects of the exposure duration, so did the model indexes obtained from drift diffusion model analysis. However, event-related potentials (ERP) analysis revealed that exposure duration was associated with changes in the visual awareness negativity (VAN) and the late positivity (LP) components, which in turn affected reaction time. Specifically, longer exposure durations were associated with lower VAN and higher LP, resulting in shorter reaction times and greater drift rate. In contrast to previous studies, the reverse relationship between VAN and LP may reflect a compensatory response to the reduced cognitive resources caused by high-altitude exposure. Additionally, increased LP and shorter reaction times with exposure duration may reflect a resistance to the high-altitude environment. We also conducted time-frequency analysis and found that theta power did not vary with exposure duration, suggesting that the reduction in cognitive resources remains stable in these individuals over time. Overall, our study provides new insights into the dynamic effects of high-altitude environments on awareness detection in the presence of reduced cognitive resources.

Accounting for endogenous effects in decision-making with a non-linear diffusion decision model

The Drift-Diffusion Model (DDM) is widely accepted for two-alternative forced-choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter-trial dynamics at the single-trial level and endogenous influences. We propose a novel model, the non-linear Drift-Diffusion Model (nl-DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non-linear model performs better than the drift-diffusion model for an equivalent complexity. To give better intuition on the meaning of nl-DDM parameters, we compare the DDM and the nl-DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl-DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across-trial variability for perceptual decisions and accounts for peri-stimulus influences.

Cognitive markers for efficacy of neurofeedback for attention-deficit hyperactivity disorder - personalized medicine using computational psychiatry in a randomized clinical trial

BACKGROUND

Exploring whether cognitive components (identified by baseline cognitive testing and computational modeling) moderate clinical outcome of neurofeedback (NF) for attention-deficit hyperactivity disorder (ADHD).

METHOD

142 children (aged 7-10) with ADHD were randomly assigned to either NF (n = 84) or control treatment (n = 58) in a double-blind clinical trial (NCT02251743). The NF group received live, self-controlled downtraining of electroencephalographic theta/beta ratio power. The control group received identical-appearing reinforcement from prerecorded electroencephalograms from other children. 133 (78 NF, 55 control) children had cognitive processing measured at baseline with the Integrated Visual and Auditory Continuous Performance Test (IVA2-CPT) and were included in this analysis. A diffusion decision model applied to the IVA2-CPT data quantified two latent cognitive components deficient in ADHD: drift rate and drift bias, indexing efficiency and context sensitivity of cognitive processes involving information integration. We explored whether these cognitive components moderated the improvement in parent- and teacher-rated inattention symptoms from baseline to treatment end (primary clinical outcome).

RESULTS

Baseline cognitive components reflecting information integration (drift rate, drift bias) moderated the improvement in inattention due to NF vs. control treatment (p = 0.006). Specifically, those with either the most or least severe deficits in these components showed more improvement in parent- and teacher-rated inattention when assigned to NF (Cohen's d = 0.59) than when assigned to control (Cohen's d = -0.21).

CONCLUSIONS

Pre-treatment cognitive testing with computational modeling identified children who benefitted more from neurofeedback than control treatment for ADHD.

Wider and Stronger Inhibitory Ring of the Attentional Focus in Schizophrenia

Anomalies of attentional selection have been repeatedly described in individuals with schizophrenia spectrum disorders. However, a precise analysis of their ability to inhibit irrelevant visual information during attentional selection is not documented. Recent behavioral as well as neurophysiological and computational evidence showed that attentional search among different competing stimuli elicits an area of suppression in the immediate surrounding of the attentional focus. In the present study, the strength and spatial extension of this surround suppression were tested in individuals with schizophrenia and neurotypical controls. Participants were asked to report the orientation of a visual "pop-out" target, which appeared in different positions within a peripheral array of non-target stimuli. In half of the trials, after the target appeared, a probe circle circumscribed a non-target stimulus at various target-to-probe distances; in this case, participants were asked to report the probe orientation instead. Results suggest that, as compared to neurotypical controls, individuals with schizophrenia showed stronger and spatially more extended filtering of visual information in the areas surrounding their attentional focus. This increased filtering of visual information outside the focus of attention might potentially hamper their ability to integrate different elements into coherent percepts and influence higher order behavioral, affective, and cognitive domains.

Spontaneous Alpha-Band Oscillations Bias Subjective Contrast Perception

Perceptual decisions depend both on the features of the incoming stimulus and on the ongoing brain activity at the moment the stimulus is received. Specifically, trial-to-trial fluctuations in cortical excitability have been linked to fluctuations in the amplitude of prestimulus α oscillations (∼8-13 Hz), which are in turn are associated with fluctuations in subjects' tendency to report the detection of a stimulus. It is currently unknown whether α oscillations bias postperceptual decision-making, or even bias subjective perception itself. To answer this question, we used a contrast discrimination task in which both male and female human subjects reported which of two gratings (one in each hemifield) was perceived as having a stronger contrast. Our EEG analysis showed that subjective contrast was reduced for the stimulus in the hemifield represented in the hemisphere with relatively stronger prestimulus α amplitude, reflecting reduced cortical excitability. Furthermore, the strength of this spontaneous hemispheric lateralization was strongly correlated with the magnitude of individual subjects' biases, suggesting that the spontaneous patterns of α lateralization play a role in explaining the intersubject variability in contrast perception. These results indicate that spontaneous fluctuations in cortical excitability, indicated by patterns of prestimulus α amplitude, affect perceptual decisions by altering the phenomenological perception of the visual world.SIGNIFICANCE STATEMENT Our moment-to-moment perception of the world is shaped by the features of the environment surrounding us, as much as by the constantly evolving states that characterize our brain activity. Previous research showed how the ongoing electrical activity of the brain can influence whether a stimulus has accessed conscious perception. However, evidence is currently missing on whether these electrical brain states can be associated to the subjective experience of a sensory input. Here we show that local changes in patterns of electrical brain activity preceding visual stimulation can bias our phenomenological perception. Importantly, we show that the strength of these variations can help explain the great interindividual variability in how we perceive the visual environment surrounding us.

Effects of Rhythmic Transcranial Magnetic Stimulation in the Alpha-Band on Visual Perception Depend on Deviation From Alpha-Peak Frequency: Faster Relative Transcranial Magnetic Stimulation Alpha-Pace Improves Performance

Alpha-band oscillatory activity over occipito-parietal areas is involved in shaping perceptual and cognitive processes, with a growing body of electroencephalographic (EEG) evidence indicating that pre-stimulus alpha-band amplitude relates to the subjective perceptual experience, but not to objective measures of visual task performance (discrimination accuracy). The primary aim of the present transcranial magnetic stimulation (TMS) study was to investigate whether causality can be established for this relationship, using rhythmic (alpha-band) TMS entrainment protocols. It was anticipated that pre-stimulus 10 Hz-TMS would induce changes in subjective awareness ratings but not accuracy, in the visual hemifield contralateral to TMS. To test this, we administered 10 Hz-TMS over the right intraparietal sulcus prior to visual stimulus presentation in 17 participants, while measuring their objective performance and subjective awareness in a visual discrimination task. Arrhythmic and 10 Hz sham-TMS served as control conditions (within-participant design). Resting EEG was used to record individual alpha frequency (IAF). A study conducted in parallel to ours with a similar design but reported after we completed data collection informed further, secondary analyses for a causal relationship between pre-stimulus alpha-frequency and discrimination accuracy. This was explored through a regression analysis between rhythmic-TMS alpha-pace relative to IAF and performance measures. Our results revealed that contrary to our primary expectation, pre-stimulus 10 Hz-TMS did not affect subjective measures of performance, nor accuracy, relative to control-TMS. This null result is in accord with a recent finding showing that for influencing subjective measures of performance, alpha-TMS needs to be applied post-stimulus. In addition, our secondary analysis showed that IAF was positively correlated with task accuracy across participants, and that 10 Hz-TMS effects on accuracy—but not awareness ratings—depended on IAF: The slower (or faster) the IAF, relative to the fixed 10 Hz TMS frequency, the stronger the TMS-induced performance improvement (or worsening), indicating that 10 Hz-TMS produced a gain (or a loss) in individual performance, directly depending on TMS-pace relative to IAF. In support of recent reports, this is evidence for alpha-frequency playing a causal role in perceptual sensitivity likely through regulating the speed of sensory sampling.

Are you confident enough to act? Individual differences in action control are associated with post-decisional metacognitive bias

The art of making good choices and being consistent in executing them is essential for having a successful and fulfilling life. Individual differences in action control are believed to have a crucial impact on how we make choices and whether we put them in action. Action-oriented people are more decisive, flexible and likely to implement their intentions in the face of adversity. In contrast, state-oriented people often struggle to commit to their choices and end up second-guessing themselves. Here, we employ a model-based computational approach to study the underlying cognitive differences between action and state-oriented people in simple binary-choice decision tasks. In Experiment 1 we show that there is little-to-no evidence that the two groups differ in terms of decision-related parameters and strong evidence for differences in metacognitive bias. Action-oriented people exhibit greater confidence in the correctness of their choices as well as slightly elevated judgement sensitivity, although no differences in performance are present. In Experiment 2 we replicate this effect and show that the confidence gap generalizes to value-based decisions, widens as a function of difficulty and is independent of deliberation interval. Furthermore, allowing more time for confidence deliberation indicated that state-oriented people focus more strongly on external features of choice. We propose that a positive confidence bias, coupled with appropriate metacognitive sensitivity, might be crucial for the successful realization of intentions in many real-life situations. More generally, our study provides an example of how modelling latent cognitive processes can bring meaningful insight into the study of individual differences.

Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/ EEG

Removing power line noise and other frequency‐specific artifacts from electrophysiological data without affecting neural signals remains a challenging task. Recently, an approach was introduced that combines spectral and spatial filtering to effectively remove line noise: Zapline. This algorithm, however, requires manual selection of the noise frequency and the number of spatial components to remove during spatial filtering. Moreover, it assumes that noise frequency and spatial topography are stable over time, which is often not warranted. To overcome these issues, we introduce Zapline‐plus, which allows adaptive and automatic removal of frequency‐specific noise artifacts from M/electroencephalography (EEG) and LFP data. To achieve this, our extension first segments the data into periods (chunks) in which the noise is spatially stable. Then, for each chunk, it searches for peaks in the power spectrum, and finally applies Zapline. The exact noise frequency around the found target frequency is also determined separately for every chunk to allow fluctuations of the peak noise frequency over time. The number of to‐be‐removed components by Zapline is automatically determined using an outlier detection algorithm. Finally, the frequency spectrum after cleaning is analyzed for suboptimal cleaning, and parameters are adapted accordingly if necessary before re‐running the process. The software creates a detailed plot for monitoring the cleaning. We highlight the efficacy of the different features of our algorithm by applying it to four openly available data sets, two EEG sets containing both stationary and mobile task conditions, and two magnetoencephalography sets containing strong line noise.

Characterizing Underlying Cognitive Components of ADHD Presentations and Co-morbid Diagnoses: A Diffusion Decision Model Analysis

OBJECTIVE

To Explore whether subtypes and comorbidities of attention-deficit hyperactivity disorder (ADHD) induce distinct biases in cognitive components involved in information processing.

METHOD

Performance on the Integrated Visual and Auditory Continuous Performance Test (IVA-CPT) was compared between 150 children (aged 7 to 10) with ADHD, grouped by DSM-5 presentation (ADHD-C, ADHD-I) or co-morbid diagnoses (anxiety, oppositional defiant disorder [ODD], both, neither), and 60 children without ADHD. Diffusion decision modeling decomposed performance into cognitive components.

RESULTS

Children with ADHD had poorer information integration than controls. Children with ADHD-C were more sensitive to changes in presentation modality (auditory/visual) than those with ADHD-I and controls. Above and beyond these results, children with ADHD+anxiety+ODD had larger increases in response biases when targets became frequent than children with ADHD-only or with ADHD and one comorbidity.

CONCLUSION

ADHD presentations and comorbidities have distinct cognitive characteristics quantifiable using DDM and IVA-CPT. We discuss implications for tailored cognitive-behavioral therapy.

Noradrenergic modulation of rhythmic neural activity shapes selective attention

During moments involving selective attention, the thalamus orchestrates the preferential processing of prioritized information by coordinating rhythmic neural activity within a distributed frontoparietal network. The timed release of neuromodulators from subcortical structures dynamically sculpts neural synchronization in thalamocortical networks to meet current attentional demands. In particular, noradrenaline modulates the balance of cortical excitation and inhibition, as reflected by thalamocortical alpha synchronization (~8-12 Hz). These neuromodulatory adjustments facilitate the selective processing of prioritized information. Thus, by disrupting effective rhythmic coordination in attention networks, age-related locus coeruleus (LC) degeneration can impair higher levels of neural processing. In sum, findings across different levels of analysis and modalities shed light on how the noradrenergic modulation of neural synchronization helps to shape selective attention.

The time-course of distractor-based activation modulates effects of speed-accuracy tradeoffs in conflict tasks

The cognitive processes underlying the ability of human performers to trade speed for accuracy is often conceptualized within evidence accumulation models, but it is not yet clear whether and how these models can account for decision-making in the presence of various sources of conflicting information. In the present study, we provide evidence that speed-accuracy tradeoffs (SATs) can have opposing effects on performance across two different conflict tasks. Specifically, in a single preregistered experiment, the mean reaction time (RT) congruency effect in the Simon task increased, whereas the mean RT congruency effect in the Eriksen task decreased, when the focus was put on response speed versus accuracy. Critically, distributional RT analyses revealed distinct delta plot patterns across tasks, thus indicating that the unfolding of distractor-based response activation in time is sufficient to explain the opposing pattern of congruency effects. In addition, a recent evidence accumulation model with the notion of time-varying conflicting information was successfully fitted to the experimental data. These fits revealed task-specific time-courses of distractor-based activation and suggested that time pressure substantially decreases decision boundaries in addition to reducing the duration of non-decision processes and the rate of evidence accumulation. Overall, the present results suggest that time pressure can have multiple effects in decision-making under conflict, but that strategic adjustments of decision boundaries in conjunction with different time-courses of distractor-based activation can produce counteracting effects on task performance with different types of distracting sources of information.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

Neurofeedback Modulation of the Sound-induced Flash Illusion Using Parietal Cortex Alpha Oscillations Reveals Dependency on Prior Multisensory Congruency

Spontaneous neural oscillations are key predictors of perceptual decisions to bind multisensory signals into a unified percept. Research links decreased alpha power in the posterior cortices to attention and audiovisual binding in the sound-induced flash illusion (SIFI) paradigm. This suggests that controlling alpha oscillations would be a way of controlling audiovisual binding. In the present feasibility study we used MEG-neurofeedback to train one group of subjects to increase left/right and another to increase right/left alpha power ratios in the parietal cortex. We tested for changes in audiovisual binding in a SIFI paradigm where flashes appeared in both hemifields. Results showed that the neurofeedback induced a significant asymmetry in alpha power for the left/right group, not seen for the right/left group. Corresponding asymmetry changes in audiovisual binding in illusion trials (with 2, 3, and 4 beeps paired with 1 flash) were not apparent. Exploratory analyses showed that neurofeedback training effects were present for illusion trials with the lowest numeric disparity (i.e., 2 beeps and 1 flash trials) only if the previous trial had high congruency (2 beeps and 2 flashes). Our data suggest that the relation between parietal alpha power (an index of attention) and its effect on audiovisual binding is dependent on the learned causal structure in the previous stimulus. The present results suggests that low alpha power biases observers towards audiovisual binding when they have learned that audiovisual signals originate from a common origin, consistent with a Bayesian causal inference account of multisensory perception.

Alpha Oscillations Shape Sensory Representation and Perceptual Sensitivity

Alpha activity (8-14 Hz) is the dominant rhythm in the awake brain and is thought to play an important role in setting the internal state of the brain. Previous work has associated states of decreased alpha power with enhanced neural excitability. However, evidence is mixed on whether and how such excitability enhancement modulates sensory signals of interest versus noise differently, and what, if any, are the consequences for subsequent perception. Here, human subjects (male and female) performed a visual detection task in which we manipulated their decision criteria in a blockwise manner. Although our manipulation led to substantial criterion shifts, these shifts were not reflected in prestimulus alpha band changes. Rather, lower prestimulus alpha power in occipital-parietal areas improved perceptual sensitivity and enhanced information content decodable from neural activity patterns. Additionally, oscillatory alpha phase immediately before stimulus presentation modulated accuracy. Together, our results suggest that alpha band dynamics modulate sensory signals of interest more strongly than noise.SIGNIFICANCE STATEMENT The internal state of our brain fluctuates, giving rise to variability in perception and action. Neural oscillations, most prominently in the alpha band, have been suggested to play a role in setting this internal state. Here, we show that ongoing alpha band activity in occipital-parietal regions predicts the quality of visual information decodable in neural activity patterns and subsequently the human observer's sensitivity in a visual detection task. Our results provide comprehensive evidence that visual representation is modulated by ongoing alpha band activity and advance our understanding on how, when faced with unchanging external stimuli, internal neural fluctuations influence perception and behavior.

Causal role for the primate superior colliculus in the computation of evidence for perceptual decisions

Trained monkeys performed a two-choice perceptual decision-making task in which they reported the perceived orientation of a dynamic Glass pattern, before and after unilateral, reversible, inactivation of a brainstem area-the superior colliculus (SC)-involved in preparing eye movements. We found that unilateral SC inactivation produced significant decision biases and changes in reaction times consistent with a causal role for the primate SC in perceptual decision-making. Fitting signal detection theory and sequential sampling models to the data showed that SC inactivation produced a decrease in the relative evidence for contralateral decisions, as if adding a constant offset to a time-varying evidence signal for the ipsilateral choice. The results provide causal evidence for an embodied cognition model of perceptual decision-making and provide compelling evidence that the SC of primates (a brainstem structure) plays a causal role in how evidence is computed for decisions-a process usually attributed to the forebrain.

A neural-based account of sequential bias during perceptual judgment

Sequential effects are prominent and pervasive phenomena that exist in most perceptual judgments. Of importance, these effects reflect dynamic aspects in our judgment bias induced by the recent context. When making successive judgments in response to a sequence of stimuli, two opposing consequences have frequently been observed: assimilation effects - current stimuli judged as being closer to preceding stimuli than they actually are, and contrast effects - current stimuli judged as being further from preceding stimuli than they actually are. Although several cognitive accounts have been previously proposed, there is still a lack of consensus on the underlying mechanism, particularly regarding the insights of the temporal dynamics. Building upon accumulating human M/EEG findings, I propose a framework to explain how sequential bias is generated, unfolded over time, and eventually incorporated into the formation of current biased judgment. By bringing sequential effects closer to a biologically plausible framework, this synthetic view could account for how the opposing consequences of sequential effects differentially evolve, distinguish the effects from other perceptual phenomena with similar behavioral outcomes (such as aftereffects and priming), and illuminate how perceptual judgment is adaptively adjusted under the impact of temporal context.

Neural attentional-filter mechanisms of listening success in middle-aged and older individuals

Successful listening crucially depends on intact attentional filters that separate relevant from irrelevant information. Research into their neurobiological implementation has focused on two potential auditory filter strategies: the lateralization of alpha power and selective neural speech tracking. However, the functional interplay of the two neural filter strategies and their potency to index listening success in an ageing population remains unclear. Using electroencephalography and a dual-talker task in a representative sample of listeners (N = 155; age=39-80 years), we here demonstrate an often-missed link from single-trial behavioural outcomes back to trial-by-trial changes in neural attentional filtering. First, we observe preserved attentional-cue-driven modulation of both neural filters across chronological age and hearing levels. Second, neural filter states vary independently of one another, demonstrating complementary neurobiological solutions of spatial selective attention. Stronger neural speech tracking but not alpha lateralization boosts trial-to-trial behavioural performance. Our results highlight the translational potential of neural speech tracking as an individualized neural marker of adaptive listening behaviour.

Alpha oscillations and event-related potentials reflect distinct dynamics of attribute construction and evidence accumulation in dietary decision making

How does regulatory focus alter attribute value construction (AVC) and evidence accumulation (EA)? We recorded electroencephalogram during food choices while participants responded naturally or regulated their choices by attending to health attributes or decreasing attention to taste attributes. Using a drift diffusion model, we predicted the time course of neural signals associated with AVC and EA. Results suggested that event-related potentials (ERPs) correlated with the time course of model-predicted taste-attribute signals, with no modulation by regulation. By contrast, suppression of frontal and occipital alpha power correlated with the time course of EA, tracked tastiness according to its goal relevance, and predicted individual variation in successful down-regulation of tastiness. Additionally, an earlier rise in frontal and occipital theta power represented food tastiness more strongly during regulation and predicted a weaker influence of food tastiness on behaviour. Our findings illuminate how regulation modifies the representation of attributes during the process of EA.

Subliminal perception is continuous with conscious vision and can be predicted from prestimulus electroencephalographic activity

Individuals are able to discriminate visual stimuli they report not consciously seeing. This phenomenon is known as "subliminal perception." Such capacity is often assumed to be relatively automatic in nature and rely on stimulus-driven activity in low-level cortical areas. Instead, here we asked to what extent neural activity before stimulus presentation influences subliminal perception. We asked participants to discriminate the location of a briefly presented low-contrast visual stimulus and then rate how well they saw the stimulus. Consistent with previous studies, participants correctly discriminated with slightly above chance-level accuracy the location of a stimulus they reported not seeing. Signal detection analyses indicated that while subjects categorized their percepts as "unconscious," their capacity to discriminate these stimuli lay on the same continuum as conscious vision. We show that the accuracy of discriminating the location of a subliminal stimulus could be predicted with relatively high accuracy (AUC = 0.70) based on lateralized electroencephalographic (EEG) activity before the stimulus, the hemifield where the stimulus was presented, and the accuracy of previous trial's discrimination response. Altogether, our results suggest that rather than being a separate unconscious capacity, subliminal perception is based on similar processes as conscious vision.

Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans

A successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, called urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. Forty females and 34 males took part (mean age, 23.4 years). We find that an evoked potential time locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathologic decision-making such as in impulse control and addictive disorders.SIGNIFICANCE STATEMENT Perceptual decisions are often described by a class of models that assumes that sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.

Dynamic relationships between spontaneous and evoked electrophysiological activity

Spontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

Low pre-stimulus EEG alpha power amplifies visual awareness but not visual sensitivity

Pre-stimulus oscillatory neural activity has been linked to the level of awareness of sensory stimuli. More specifically, the power of low-frequency oscillations (primarily in the alpha-band, i.e., 8-14 Hz) prior to stimulus onset is inversely related to measures of subjective performance in visual tasks, such as confidence and visual awareness. Intriguingly, the same EEG signature does not seem to influence objective measures of task performance (i.e., accuracy). We here examined whether this dissociation holds when stringent accuracy measures are used. Previous EEG-studies have employed 2-alternative forced choice (2-AFC) discrimination tasks to link pre-stimulus oscillatory activity to correct/incorrect responses as an index of accuracy/objective performance at the single-trial level. However, 2-AFC tasks do not provide a good estimate of single-trial accuracy, as many of the responses classified as correct will be contaminated by guesses (with the chance correct response rate being 50%). Here instead, we employed a 19-AFC letter identification task to measure accuracy and the subjectively reported level of perceptual awareness on each trial. As the correct guess rate is negligible (~5%), this task provides a purer measure of accuracy. Our results replicate the inverse relationship between pre-stimulus alpha/beta-band power and perceptual awareness ratings in the absence of a link to discrimination accuracy. Pre-stimulus oscillatory phase did not predict either subjective awareness or accuracy. Our results hence confirm a dissociation of the pre-stimulus EEG power-task performance link for subjective versus objective measures of performance, and further substantiate pre-stimulus alpha power as a neural predictor of visual awareness.

Behavior needs neural variability

Human and non-human animal behavior is highly malleable and adapts successfully to internal and external demands. Such behavioral success stands in striking contrast to the apparent instability in neural activity (i.e., variability) from which it arises. Here, we summon the considerable evidence across scales, species, and imaging modalities that neural variability represents a key, undervalued dimension for understanding brain-behavior relationships at inter- and intra-individual levels. We believe that only by incorporating a specific focus on variability will the neural foundation of behavior be comprehensively understood.

Decision-Making in the Human-Machine Interface

If our choices make us who we are, then what does that mean when these choices are made in the human-machine interface? Developing a clear understanding of how human decision making is influenced by automated systems in the environment is critical because, as human-machine interfaces and assistive robotics become even more ubiquitous in everyday life, many daily decisions will be an emergent result of the interactions between the human and the machine – not stemming solely from the human. For example, choices can be influenced by the relative locations and motor costs of the response options, as well as by the timing of the response prompts. In drift diffusion model simulations of response-prompt timing manipulations, we find that it is only relatively equibiased choices that will be successfully influenced by this kind of perturbation. However, with drift diffusion model simulations of motor cost manipulations, we find that even relatively biased choices can still show some influence of the perturbation. We report the results of a two-alternative forced-choice experiment with a computer mouse modified to have a subtle velocity bias in a pre-determined direction for each trial, inducing an increased motor cost to move the cursor away from the pre-designated target direction. With queries that have each been normed in advance to be equibiased in people’s preferences, the participant will often begin their mouse movement before their cognitive choice has been finalized, and the directional bias in the mouse velocity exerts a small but significant influence on their final choice. With queries that are not equibiased, a similar influence is observed. By exploring the synergies that are developed between humans and machines and tracking their temporal dynamics, this work aims to provide insight into our evolving decisions.

Defending subjective inflation: an inference to the best explanation

In a recent opinion piece, Abid (2019) criticizes the hypothesis that subjective inflation may partly account for apparent phenomenological richness across the visual field and outside the focus of attention. In response, we address three main issues. First, we maintain that inflation should be interpreted as an intraperceptual-and not post-perceptual-phenomenon. Second, we describe how inflation may differ from filling-in. Finally, we contend that, in general, there is sufficient evidence to tip the scales toward intraperceptual interpretations of visibility and confidence judgments.

Illusions of control without delusions of grandeur

We frequently experience feelings of agency over events we do not objectively influence - so-called 'illusions of control'. These illusions have prompted widespread claims that we can be insensitive to objective relationships between actions and outcomes, and instead rely on grandiose beliefs about our abilities. However, these illusory biases could instead arise if we are highly sensitive to action-outcome correlations, but attribute agency when such correlations emerge simply by chance. We motion-tracked participants while they made agency judgements about a cursor that could be yoked to their actions or follow an independent trajectory. A combination of signal detection analysis, reverse correlation methods and computational modelling indeed demonstrated that 'illusions' of control could emerge solely from sensitivity to spurious action-outcome correlations. Counterintuitively, this suggests that illusions of control could arise because agents have excellent insight into the relationships between actions and outcomes in a world where causal relationships are not perfectly deterministic.

Boosts in brain signal variability track liberal shifts in decision bias

Adopting particular decision biases allows organisms to tailor their choices to environmental demands. For example, a liberal response strategy pays off when target detection is crucial, whereas a conservative strategy is optimal for avoiding false alarms. Using conventional time-frequency analysis of human electroencephalographic (EEG) activity, we previously showed that bias setting entails adjustment of evidence accumulation in sensory regions (Kloosterman et al., 2019), but the presumed prefrontal signature of a conservative-to-liberal bias shift has remained elusive. Here, we show that a liberal bias shift is reflected in a more unconstrained neural regime (boosted entropy) in frontal regions that is suited to the detection of unpredictable events. Overall EEG variation, spectral power and event-related potentials could not explain this relationship, highlighting that moment-to-moment neural variability uniquely tracks bias shifts. Neural variability modulation through prefrontal cortex appears instrumental for permitting an organism to adapt its biases to environmental demands.

Late Positivity Does Not Meet the Criteria to be Considered a Proper Neural Correlate of Perceptual Awareness

Contrastive analysis has been widely employed in the search for the electrophysiological neural correlates of consciousness. However, despite its clear logic, it has been argued that it may not succeed in isolating neural processes solely involved in the emergence of perceptual awareness. In fact, data from contrastive analysis would be contaminated by potential confounding factors reflecting distinct, though related, processes either preceding or following the conscious perception. At present, the ERP components representing the proper correlates of perceptual awareness still remain to be identified among those correlating with awareness (i.e., Visual Awareness Negativity, VAN and Late Positivity, LP). In order to dissociate visual awareness from post-perceptual confounds specifically related to decision making, we manipulated the response criterion, which affects how a percept is translated into a decision. In particular, while performing an orientation discrimination task, participants were asked to shift their response criterion across sessions. As a consequence, the resulting modulation should concern the ERP component(s) not exclusively reflecting mechanisms regulating the subjective conscious experience itself but rather the processes accompanying it. Electrophysiological results showed that N1 and P3 were sensitive to the response criterion adopted by participants. Additionally, the more the participants shifted their response criterion, the bigger the ERP modulation was; this was consequently indicative of the critical role of these components in the decision-making processes regardless of awareness level. When considering data independently from the response criterion, the aware vs. unaware contrast showed that both VAN and LP were significant. Crucially, the LP component was also modulated by the interaction of awareness and response criterion, while VAN results to be unaffected. In agreement with previous literature, these findings provide evidence supporting the hypothesis that VAN tracks the emergence of visual awareness by encoding the conscious percept, whereas LP reflects the contribution from post-perceptual processes related to response requirements. This excludes a direct functional role of this later component in giving rise to perceptual awareness.

Spontaneous Brain Oscillations and Perceptual Decision-Making

Making rapid decisions on the basis of sensory information is essential to everyday behaviors. Why, then, are perceptual decisions so variable despite unchanging inputs? Spontaneous neural oscillations have emerged as a key predictor of trial-to-trial perceptual variability. New work casting these effects in the framework of models of perceptual decision-making has driven novel insight into how the amplitude of spontaneous oscillations impact decision-making. This synthesis reveals that the amplitude of ongoing low-frequency oscillations (<30 Hz), particularly in the alpha-band (8-13 Hz), bias sensory responses and change conscious perception but not, surprisingly, the underlying sensitivity of perception. A key model-based insight is that various decision thresholds do not adapt to alpha-related changes in sensory activity, demonstrating a seeming suboptimality of decision mechanisms in tracking endogenous changes in sensory responses.

Perceptual bias is reduced with longer reaction times during visual discrimination

Fast and slow decisions exhibit distinct behavioral properties, such as the presence of decision bias in faster but not slower responses. This dichotomy is currently explained by assuming that distinct cognitive processes map to separate brain mechanisms. Here, we suggest an alternative single-process account based on the stochastic properties of decision processes. Our experimental results show perceptual biases in a variety of tasks (specifically: learned priors, tilt aftereffect, and tilt illusion) that are much reduced with increasing reaction time. To account for this, we consider a simple yet general explanation: prior and noisy decision-related evidence are integrated serially, with evidence and noise accumulating over time (as in the standard drift diffusion model). With time, owing to noise accumulation, the prior effect is predicted to diminish. This illustrates that a clear behavioral separation—presence vs. absence of bias—may reflect a simple stochastic mechanism.

Ron Dekel and Dov Sagi use a visual discrimination task to show that when making a choice, longer reaction times decrease human perceptual bias without affecting accuracy. This decrease in perceptual bias can be explained by the accumulation of evidence and noise over time.

Spatial Attentional Selection Modulates Early Visual Stimulus Processing Independently of Visual Alpha Modulations

The capacity-limited human brain is constantly confronted with a huge amount of sensory information. Selective attention is needed for biasing neural processing towards relevant information and consequently allows meaningful interaction with the environment. Activity in the alpha-band has been proposed to be related to top-down modulation of neural inhibition and could thus represent a viable candidate to control the priority of stimulus processing. It is, however, unknown whether modulations in the alpha-band directly relate to changes in the sensory gain control of the early visual cortex. Here, we used a spatial cueing paradigm while simultaneously measuring ongoing alpha-band oscillations and steady-state visual evoked potentials (SSVEPs) as a marker of continuous early sensory processing in the human visual cortex. Thereby, the effects of spatial attention for both of these signals and their potential interactions were assessed. As expected, spatial attention modulated both alpha-band and SSVEP responses. However, their modulations were independent of each other and the corresponding activity profiles differed across task demands. Thus, our results challenge the view that modulations of alpha-band activity represent a mechanism that directly alters or controls sensory gain. The potential role of alpha-band oscillations beyond sensory processing will be discussed in light of the present results.

Local cortical desynchronization and pupil-linked arousal differentially shape brain states for optimal sensory performance

Instantaneous brain states have consequences for our sensation, perception, and behaviour. Fluctuations in arousal and neural desynchronization likely pose perceptually relevant states. However, their relationship and their relative impact on perception is unclear. We here show that, at the single-trial level in humans, local desynchronization in sensory cortex (expressed as time-series entropy) versus pupil-linked arousal differentially impact perceptual processing. While we recorded electroencephalography (EEG) and pupillometry data, stimuli of a demanding auditory discrimination task were presented into states of high or low desynchronization of auditory cortex via a real-time closed-loop setup. Desynchronization and arousal distinctly influenced stimulus-evoked activity and shaped behaviour displaying an inverted u-shaped relationship: States of intermediate desynchronization elicited minimal response bias and fastest responses, while states of intermediate arousal gave rise to highest response sensitivity. Our results speak to a model in which independent states of local desynchronization and global arousal jointly optimise sensory processing and performance.

The role of premature evidence accumulation in making difficult perceptual decisions under temporal uncertainty

The computations and neural processes underpinning decision making have primarily been investigated using highly simplified tasks in which stimulus onsets cue observers to start accumulating choice-relevant information. Yet, in daily life we are rarely afforded the luxury of knowing precisely when choice-relevant information will appear. Here, we examined neural indices of decision formation while subjects discriminated subtle stimulus feature changes whose timing relative to stimulus onset ('foreperiod') was uncertain. Joint analysis of behavioural error patterns and neural decision signal dynamics indicated that subjects systematically began the accumulation process before any informative evidence was presented, and further, that accumulation onset timing varied systematically as a function of the foreperiod of the preceding trial. These results suggest that the brain can adjust to temporal uncertainty by strategically modulating accumulation onset timing according to statistical regularities in the temporal structure of the sensory environment with particular emphasis on recent experience.

Contribution of Sensory Encoding to Measured Bias

Signal detection theory (SDT) is a widely used theoretical framework that describes how variable sensory signals are integrated with a decision criterion to support perceptual decision-making. SDT provides two key measurements: sensitivity (d') and bias (c), which reflect the separability of decision variable distributions (signal and noise) and the position of the decision criterion relative to optimal, respectively. Although changes in the subject's decision criterion can be reflected in changes in bias, decision criterion placement is not the sole contributor to measured bias. Indeed, neuronal representations of bias have been observed in sensory areas, suggesting that some changes in bias are because of effects on sensory encoding. To directly test whether the sensory encoding process can influence bias, we optogenetically manipulated neuronal excitability in primary visual cortex (V1) in mice of both sexes during either an orientation discrimination or a contrast detection task. Increasing excitability in V1 significantly decreased behavioral bias, whereas decreasing excitability had the opposite effect. To determine whether this change in bias is consistent with effects on sensory encoding, we made extracellular recordings from V1 neurons in passively viewing mice. Indeed, we found that optogenetic manipulation of excitability shifted the neuronal bias in the same direction as the behavioral bias. Moreover, manipulating the quality of V1 encoding by changing stimulus contrast or interstimulus interval also resulted in consistent changes in both behavioral and neuronal bias. Thus, changes in sensory encoding are sufficient to drive changes in bias measured using SDT.SIGNIFICANCE STATEMENT Perceptual decision-making involves sensory integration followed by application of a cognitive criterion. Using signal detection theory, one can extract features of the underlying decision variables and rule: sensitivity (d') and bias (c). Because bias is measured as the difference between the optimal and actual criterion, it is sensitive to both the sensory encoding processes and the placement of the decision criterion. Here, we use behavioral and electrophysiological approaches to demonstrate that measures of bias depend on sensory processes. Optogenetic manipulations of V1 in mice bidirectionally affect both behavioral and neuronal measures of bias with little effect on sensitivity. Thus, changes in sensory encoding influence bias, and the absence of changes in sensitivity do not preclude changes in sensory encoding.

Humans strategically shift decision bias by flexibly adjusting sensory evidence accumulation

Decision bias is traditionally conceptualized as an internal reference against which sensory evidence is compared. Instead, we show that individuals implement decision bias by shifting the rate of sensory evidence accumulation toward a decision bound. Participants performed a target detection task while we recorded EEG. We experimentally manipulated participants' decision criterion for reporting targets using different stimulus-response reward contingencies, inducing either a liberal or a conservative bias. Drift diffusion modeling revealed that a liberal strategy biased sensory evidence accumulation toward target-present choices. Moreover, a liberal bias resulted in stronger midfrontal pre-stimulus 2-6 Hz (theta) power and suppression of pre-stimulus 8-12 Hz (alpha) power in posterior cortex. Alpha suppression in turn was linked to the output activity in visual cortex, as expressed through 59-100 Hz (gamma) power. These findings show that observers can intentionally control cortical excitability to strategically bias evidence accumulation toward the decision bound that maximizes reward.