Biology subjects

Gold, J. I.

Publications and source records attributed to Gold, J. I..

At least 19 recordsLinked to original sources

bioRxiv2026

An Information Compass for Probabilistic Reasoning in the Brain

Probabilistic reasoning in the brain has been studied primarily using simple two-choice tasks that are experimentally and theoretically tractable but have unclear relevance to more complex problems. Here we generalize principles from these studies using information geometry, which treats probability distributions (``beliefs'') as points on statistical manifolds whose geometry captures relationships between those beliefs. We introduce an ``information compass,'' a context-dependent, one-dimensional axis along which an arbitrarily complex belief is reinforced or repudiated. Projecting high-dimensional belief updates onto this axis casts even complex decisions into familiar forms of deliberation and commitment used for simpler decisions. Our framework provides a unified account of how biological and artificial systems can use geometric forms of probabilistic reasoning to make decisions across a range of tasks and domains.

neuroscience↗

bioRxiv2026

Different Sources of Expectations Differentially Modulate Communication Between Auditory and Prefrontal Cortices During Auditory Decision-Making

Perceptual decisions can be influenced by expectations that arise from different sources. However, relatively little is known about how and where in the brain these different sources affect decision formation, particularly in the auditory system. To begin to address this question, we recorded local field potentials (LFPs) simultaneously from the auditory cortex (AC) and ventrolateral prefrontal cortex (vlPFC) while monkeys performed an auditory frequency-discrimination task. We manipulated their expectations by presenting either informative cues (LEDs that predicted the target frequency) or uninformative cues (tone sequences that did not predict the target frequency) prior to target onset. Both cues had similar effects on the monkeys accuracy and response times but induced distinct neurophysiological signatures. Coherence, a measure of undirected coupling, between AC and vlPFC increased from cue to target presentation on informative trials but decreased from cue to target presentation on uninformative trials. Phase-slope index (PSI), a measure of directed coupling, between AC and vlPFC was strongest when the target tone contradicted expectations, particularly for ambiguous stimulus conditions when expectations were most valuable. These expectation-dependent changes in the magnitude of functional connectivity also included changes in its spatial organization. Together, these findings provide new insights into how different expectations can dynamically reconfigure functional connectivity between cortical brain areas to support different task demands and behavioral outcomes.

neuroscience↗

bioRxiv2026

Limitations of pupil diameter as a proxy for modes of locus coeruleus activity

The locus coeruleus-norepinephrine (LC-NE) system plays multiple roles in higher brain function that are thought to depend on its mode of activation, which reflects relationships between baseline and evoked activation levels. These relationships are evident in both single-unit LC activity and proposed physiological proxies of LC-NE activity, such as pupil size. Here we used measurements in awake monkeys to show that the baseline-evoked relationships evident within these two different measures are unreliably coupled between them: baseline-evoked relationships of the pupil are not predictive of those in the LC, and vice versa. These results imply that pupil modulations, which can reflect LC-NE activity, should be used with caution to make inferences about "phasic" (moderate baseline, high evoked) and "tonic" (high baseline, low evoked) LC-NE activity modes that are thought to support different forms of information processing in the brain.

neuroscience↗

bioRxiv2026

Reassessing Choice Probability: What 59 Macaque Studies Tell Us About Decision-Related Activity in Visual Cortex

Choice probability (CP) quantifies the trial-by-trial covariation between a sensory neurons response and perceptual reports. Despite extensive interest in CP as a window into how perception is linked to the activity of sensory neurons, the usefulness of CP remains debated. On one hand, reported CP magnitudes vary widely across seemingly equivalent studies, questioning its utility as a metric. On the other hand, the absence of clear patterns in CP variability has made it difficult to use it to adjudicate between competing models of visual perception. Here, we performed a meta-analysis of 150 CP estimates from 59 macaque neurophysiology studies to identify factors that systematically influence CP. We confirmed the positive relationship between CP and neuronal sensitivity both across and within individual studies. When controlled for sensitivity, we found remarkable consistency in CP across varying tasks and brain regions with two notable exceptions. First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception. Second, CPs were smaller in area V1, supporting prior suggestions about V1s special role in visual processing. We further found a significant effect of stimulus duration on CP, providing evidence against strictly feedforward models and favoring models with substantial feedback and recurrent processing. Finally, we offer recommendations for future studies to enhance the cross-study comparability and theoretical utility of choice signals as the field transitions to large-scale population recordings. More broadly, our findings demonstrate the benefits of meta-studies that expose patterns across many different tasks and animals - yielding insights that complement large-scale population recordings.

neuroscience↗

bioRxiv2026

Suboptimal human inference reflects an efficient and flexible information bottleneck

Human inference is often suboptimal in ways that vary across individuals and tasks. We propose that at least some of this variability reflects information-processing limits. To test this idea, we developed a task-general application of the information-bottleneck framework to quantify how much information individuals use (information capacity) and how effectively they use it (information efficiency). We applied this framework to human choice behavior on two distinct inference tasks and found that individual differences in performance were driven largely by variation in information capacity, while information efficiency remained consistently high. This pattern of variable capacity and high efficiency also applied to a subset of participants who appeared inefficient overall, but were efficient when evaluated relative to a simplified (heuristic) encoding of the observations. Regardless of whether participants based their strategies on full or simplified encodings, they tended to adjust their performance to different task demands by changing their information capacity while maintaining efficiency. We interpret these findings in terms of new analytical results linking optimal inference under information-capacity constraints to evidence-based choice noise, suggesting that a key driver of human behavioral variability is rational adaptation to flexible information-processing limits.

neuroscience↗

bioRxiv2026

Human decision-makers terminate evidence accumulation using flexible decision rules

Decisions based on evidence accumulated over time require rules governing when to end the accumulation process and commit to a choice. These rules control inherent trade-offs between decision speed and accuracy, which require careful balance to maximize quantities that depend on both like reward rate. We previously showed that, to maximize reward rate, normative decision rules adapt to changing task conditions (Barendregt et al., 2022). Here we used a novel task to examine whether and how people use adaptive rules for individual decisions under a variety of conditions, including changes in decision outcomes across trials and changes in evidence quality both across and within trials. We found that the participants tended to use rules that adjusted, at least partially, to predictable changes in task conditions to improve reward rate, consistent with a rationally bounded implementation of normative principles. These findings help inform our understanding of the extent and limits of flexible decision formation in the brain.

neuroscience↗

bioRxiv2026

Sensory adaptation supports flexible evidence accumulation during perceptual decision making

Effective decision making in dynamic environments requires flexible evidence accumulation. Although models often express this flexibility as a property of the accumulator, its implementation in the brain may involve adaptive mechanisms operating at other stages of the decision process. We examined two such mechanisms: 1) stimulus-specific sensory adaptation at the level of evidence encoding; and 2) arousal-related neuromodulation, which could, in principle, affect both evidence encoding and accumulation. We measured single-unit activity in the middle temporal area (MT) and pupil-linked arousal while monkeys performed a modified random-dot motion direction-discrimination task in which an adapting stimulus with varied temporal stability preceded a behaviorally relevant test stimulus. The monkeys decisions reflected adaptive evidence accumulation that depended on temporal-context stability and corresponded to context-dependent changes in both stimulus-specific sensory adaptation in MT and task-evoked pupil responses. However, adaptation and pupil adjustments were not related to each other. Together, these findings suggest that multiple mechanisms contribute to flexible, context-dependent evidence accumulation, including changes in sensory adaptation that shape evidence encoding and changes in arousal that may shape the accumulation process itself.

neuroscience↗

bioRxiv2025

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys

The subthalamic nucleus (STN) is a part of the indirect and hyperdirect pathways in the basal ganglia (BG) and has been implicated in movement control, impulsivity, and decision-making. We recently demonstrated that, for perceptual decisions, the STN includes at least three subpopulations of neurons with different decision-related activity patterns (Branam et al., 2024). Here we show that, for decisions that require both perceptual and reward-based processing, many STN neurons are sensitive to both sensory evidence and reward expectations. Within a drift-diffusion framework, three STN subpopulations show different relationships to model components reflecting formation of the decision variable, dynamics of the decision bound, and non-decision-related processes. Many STN neurons also represent quantities related to decision evaluation, including choice accuracy and reward expectation. These results help to further delineate the multiple roles that STN plays in forming and evaluating complex decisions that combine multiple sources of information.

neuroscience↗

bioRxiv2024

Diversity of ancestral brainstem noradrenergic neurons across species and multiple biological factors

The brainstem cell group, locus coeruleus (LC), is present across vertebrates and influences cardiorespiratory, metabolic, immune, and cognitive functions by activating in two putatively distinct firing patterns. Yet, the degree to which the LC firing rates and patterns are homogenous across species has never been assessed due to inherently limited sample sizes. To remedy this, we pooled cross-species data from 20 laboratories to show that firing rates differ across species and are modulated by sex, age, and type of in vitro or in vivo preparation. Contrary to the prevailing dual-mode firing pattern schema, we observed patterns spread across a low-dimensional manifold, with subregions enriched for specific biological factors and neurodegenerative disease models. Our findings show considerable diversity in an ancestral vertebrate neuromodulatory system.

neuroscience↗

bioRxiv2024

Normative evidence weighting and accumulation in correlated environments

The brain forms certain deliberative decisions following normative principles related to how sensory observations are weighed and accumulated over time. Previously we showed that these principles can account for how people adapt their decisions to the temporal dynamics of the observations (Glaze et al., 2015). Here we show that this adaptability extends to accounting for correlations in the observations, which can have a dramatic impact on the weight of evidence provided by those observations. We tested online human participants on a novel visual-discrimination task with pairwise-correlated observations. With minimal training, the participants adapted to uncued, trial-by-trial changes in the correlations and produced decisions based on an approximately normative weighing and accumulation of evidence. The results highlight the robustness of our brains ability to process sensory observations with respect to not just their physical features but also the weight of evidence they provide for a given decision.

neuroscience↗

bioRxiv2024

The subthalamic nucleus contributes causally to perceptual decision-making in monkeys

The subthalamic nucleus (STN) plays critical roles in the motor and cognitive function of the basal ganglia (BG), but the exact nature of these roles is not fully understood, especially in the context of decision-making based on uncertain evidence. Guided by theoretical predictions of specific STN contributions, we used single-unit recording and electrical microstimulation in the STN of healthy monkeys to assess its causal, computational roles in visual-saccadic decisions based on noisy evidence. The recordings identified subpopulations of STN neurons with distinct task-related activity patterns that related to different theoretically predicted functions. Microstimulation caused changes in behavioral choices and response times that reflected multiple contributions to an "accumulate-to-bound"-like decision process, including modulation of decision bounds and evidence accumulation, and to non-perceptual processes. These results provide new insights into the multiple ways that the STN can support higher brain function.

neuroscience↗

bioRxiv2023

How Occam's razor guides human decision-making

Occam's razor is the principle that, all else being equal, simpler explanations should be preferred over more complex ones. This principle is thought to guide human decision-making, but the nature of this guidance is not known. Here we used preregistered behavioral experiments to show that people tend to prefer the simpler of two alternative explanations for uncertain data. These preferences align quantitatively with predictions of formal theories of model selection that penalize excessive flexibility. These penalties emerge when considering not just the best explanation but the integral over all possible, relevant explanations. We further show that these simplicity preferences persist in humans, but not in certain artificial neural networks, even when they are maladaptive. Our results imply that principled notions of statistical model selection, including integrating over possible, latent causes to avoid overfitting to noisy data, may play a central role in human decision-making.

neuroscience↗

bioRxiv2022

Neural Representations of Post-Decision Choice Confidence and Reward Expectation in the Caudate Nucleus and Frontal Eye Field

Performance monitoring that supports ongoing behavioral adjustments is often examined in the context of either choice confidence for perceptual decisions (i.e., "did I get it right?") or reward expectation for reward-based decisions (i.e., "what reward will I receive?"). However, our understanding of how the brain encodes these distinct evaluative signals remains limited because they are easily conflated, particularly in commonly used two-alternative tasks with symmetric rewards for correct choices. Previously we reported behavioral and neural results related to decision formation by monkeys performing a visual motion discrimination task with asymmetric rewards (Doi et al., 2020; Fan et al., 2020). Here we leveraged this task design to partially decouple trial-by-trial estimates of choice confidence and reward expectation and examine their impacts on behavior and their representations in the caudate nucleus (part of the striatum in the basal ganglia) and the frontal eye field (FEF, in prefrontal cortex). We found that these evaluative signals had infrequent, but consistent, effects on the behavior of well-trained monkeys. We also identified distinguishable representations of the two types of signals in FEF and caudate neurons, including different distribution patterns, time courses, and relationships to behavior in the two brain areas. These results suggest that the cortico-striatal decision network may use diverse evaluative signals for performance monitoring and add to our understanding of the different roles of the FEF and caudate nucleus in decision-related computations.

neuroscience↗

bioRxiv2022

Anticipatory influences on simple sensory-motor behaviors are encoded by rapidly fluctuating neural dynamics across the human brain

Human behavior can be highly sensitive to anticipation, but the mechanisms underlying this sensitivity 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. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=190 HEIGHT=200 SRC="FIGDIR/small/496029v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1ca47corg.highwire.dtl.DTLVardef@72d43borg.highwire.dtl.DTLVardef@cb875dorg.highwire.dtl.DTLVardef@23f348_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Normative Decision Rules in Changing Environments

Models based on normative principles have played a major role in our understanding of how the brain forms decisions. However, these models have typically been derived for simple, stable environments, and their relevance to decisions under more naturalistic, dynamic conditions is unclear. We previously derived a normative decision model in which evidence accumulation is adapted to environmental dynamics (Glaze et al., 2015), but the evolution of commitment rules (e.g., thresholds on the accumulated evidence) under such dynamic conditions is not fully understood. Here we derive a normative model for decisions based on changing evidence or reward. In these cases, performance (reward rate) is maximized using adaptive decision thresholds that best account for diverse environmental changes, in contrast to predictions of many previous decision models. These adaptive thresholds exhibit several distinct temporal motifs that depend on the specific, predicted and experienced changes in task conditions. These adaptive decision strategies perform robustly even when implemented imperfectly (noisily) and can account for observed response times on a task with time-varying evidence better than commonly used constant-threshold or urgency-gating models. These results further link normative and neural decision-making while expanding our view of both as dynamic, adaptive processes that update and use expectations to govern both deliberation and commitment.

neuroscience↗

bioRxiv2021

Rule-based and stimulus-based cues bias auditory decisions via different computational and physiological mechanisms

Expectations, such as those arising from either learned rules or recent stimulus regularities, can bias subsequent auditory perception in diverse ways. However, it is not well understood if and how these diverse effects depend on the source of the expectations. Further, it is unknown whether different sources of bias use the same or different computational and physiological mechanisms. We examined how rule-based and stimulus-based expectations influenced behavior and pupil- linked arousal, a marker of certain forms of expectation-based processing, of human subjects performing an auditory frequency-discrimination task. Rule-based cues consistently biased choices and response times (RTs) toward the more-probable stimulus. In contrast, stimulus-based cues had a complex combination of effects, including choice and RT biases toward and away from the frequency of recently presented stimuli. These different behavioral patterns also had: 1) distinct computational signatures, including different modulations of key components of a novel form of a drift-diffusion decision model and 2) distinct physiological signatures, including substantial bias- dependent modulations of pupil size in response to rule-based but not stimulus-based cues. These results imply that different sources of expectations can modulate auditory processing via distinct mechanisms: one that uses arousal-linked, rule-based information and another that uses arousal- independent, stimulus-based information to bias the speed and accuracy of auditory perceptual decisions. Author summaryPrior information about upcoming stimuli can bias our perception of those stimuli. Whether different sources of prior information bias perception in similar or distinct ways is not well understood. We compared the influence of two kinds of prior information on tone-frequency discrimination: rule-based cues, in the form of explicit information about the most-likely identity of the upcoming tone; and stimulus-based cues, in the form of sequences of tones presented before the to-be-discriminated tone. Although both types of prior information biased auditory decision- making, they demonstrated distinct behavioral, computational, and physiological signatures. Our results suggest that the brain processes prior information in a form-specific manner rather than utilizing a general-purpose prior. Such form-specific processing has implications for understanding decision biases real-world contexts, in which prior information comes from many different sources and modalities.

neuroscience↗

bioRxiv2021

Strategy-dependent effects of working-memory limitations on human perceptual decision-making

Deliberative decisions based on an accumulation of evidence over time depend on working memory, and working memory has limitations, but how these limitations affect deliberative decision-making is not understood. We used human psychophysics to assess the impact of working-memory limitations on the fidelity of a continuous decision variable. Participants decided the average location of multiple visual targets. This computed, continuous decision variable degraded with time and capacity in a manner that depended critically on the strategy used to form the decision variable. This dependence reflected whether the decision variable was computed either: 1) immediately upon observing the evidence, and thus stored as a single value in memory; or 2) at the time of the report, and thus stored as multiple values in memory. These results provide important constraints on how the brain computes and maintains temporally dynamic decision variables.

neuroscience↗

bioRxiv2020

Normative decision asymmetries with symmetric priors but asymmetric evidence

Solutions to challenging inference problems are often subject to a fundamental trade-off between bias (being systematically wrong) that is minimized with complex inference strategies and variance (being oversensitive to uncertain observations) that is minimized with simple inference strategies. However, this trade-off is based on the assumption that the strategies being considered are optimal for their given complexity and thus has unclear relevance to the frequently suboptimal inference strategies used by humans. We examined inference problems involving rare, asymmetrically available evidence, which a large population of human subjects solved using a diverse set of strategies that were suboptimal relative to the Bayesian ideal observer. These suboptimal strategies reflected an inversion of the classic bias-variance trade-off: subjects who used more complex, but imperfect, Bayesian-like strategies tended to have lower variance but high bias because of incorrect tuning to latent task features, whereas subjects who used simpler heuristic strategies tended to have higher variance because they operated more directly on the observed samples but displayed weaker, near-normative bias. Our results yield new insights into the principles that govern individual differences in behavior that depends on rare-event inference, and, more generally, about the information-processing trade-offs that are sensitive to not just the complexity, but also the optimality of the inference process.

neuroscience↗