Biology subjects

Donner, T. H.

Publications and source records attributed to Donner, T. H..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

An information-theoretic quantification of the content of communication between brain regions

Quantifying the amount, content and direction of communication between brain regions is key to understanding brain function. Traditional methods to analyze brain activity based on the Wiener-Granger causality principle quantify the overall information propagated by neural activity between simultaneously recorded brain regions, but do not reveal the information flow about specific features of interest (such as sensory stimuli). Here, we develop a new information theoretic measure termed Feature-specific Information Transfer (FIT), quantifying how much information about a specific feature flows between two regions. FIT merges the Wiener-Granger causality principle with information-content specificity. We first derive FIT and prove analytically its key properties. We then illustrate and test them with simulations of neural activity, demonstrating that FIT identifies, within the total information flowing between regions, the information that is transmitted about specific features. We then analyze three neural datasets obtained with different recording methods, magneto- and electro-encephalography, and spiking activity, to demonstrate the ability of FIT to uncover the content and direction of information flow between brain regions beyond what can be discerned with traditional anaytical methods. FIT can improve our understanding of how brain regions communicate by uncovering previously hidden feature-specific information flow.

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bioRxiv2022

Adaptive biasing of action-selective cortical build-upactivity by choice history

Decisions under uncertainty are often biased by the history of preceding sensory input, behavioral choices, or received outcomes. Behavioral studies of perceptual decisions suggest that such history-dependent biases affect the accumulation of evidence and can be adapted to the correlation structure of the sensory environment. Here, we systematically varied this correlation structure while human participants performed a canonical perceptual choice task. We tracked the trial-by-trial variations of history biases via behavioral modeling and of a neural signature of decision formation via magnetoencephalography (MEG). The history bias was flexibly adapted to the environment and exerted a selective effect on the build-up (not baseline level) of action-selective motor cortical activity during decision formation. This effect added to the impact of the current stimulus. We conclude that the build-up of action plans in human motor cortical circuits is shaped by dynamic prior expectations that result from an adaptive interaction with the environment.

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bioRxiv2022

Auditory accessory stimulus boosts pupil-linked arousal and reduces choice bias

AO_SCPLOWBSTRACTC_SCPLOWRecent work indicates that pupil-linked phasic arousal signals reduce the impact of prior expectations and biases on decision formation. It has remained unclear whether phasic arousal (i) causes the bias reduction, if (ii) choosing against ones bias causes phasic arousal, or if (iii) a third variable is driving both. Here, using an auditory accessory stimulus, we found evidence for the first scenario: on accessory stimulus vs normal trials, pupil-linked phasic arousal was robustly elevated and choice bias was reduced. With computational modeling of behavior, we established that the bias reduction was not due to a change in response caution (i.e., speed-accuracy tradeoff), but due to a change in a bias in the accumulation of evidence leading up to a choice. Thus, pupil-linked phasic arousal shapes choice behavior.

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bioRxiv2022

Large-Scale Circuit Configuration for Flexible Sensory-Motor Decisions

Humans and non-human primates can flexibly switch between different arbitrary mappings from sensation to action to solve a cognitive task. It has remained unknown how the brain implements such flexible sensory-motor mapping rules. Here, we uncovered a dynamic reconfiguration of task-specific correlated variability between sensory and motor brain regions. Human participants switched between two rules for reporting visual orientation judgments during fMRI recordings. Rule switches were either signaled explicitly or inferred by the participants from ambiguous cues. We used behavioral modeling to reconstruct the time course of their belief about the active rule. In both contexts, the patterns of correlations between ongoing fluctuations in stimulus- and action-selective activity across visual and action-related brain regions tracked participants belief about the active rule. The rule-specific correlation patterns broke down around the time of behavioral errors. We conclude that internal beliefs about task state are instantiated in brain-wide, selective patterns of correlated variability.

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bioRxiv2021

Parietal and Motor Cortical Dynamics Differentially Shape the Computation of Choice History Bias

AO_SCPLOWBSTRACTC_SCPLOWHumans and other animals tend to repeat or alternate their previous choices, even when judging sensory stimuli presented in a random sequence. It is unclear if and how sensory, associative, and motor cortical circuits produce these idiosyncratic behavioral biases. Here, we combined behavioral modeling of a visual perceptual decision with magnetoencephalographic (MEG) analyses of neural dynamics, across multiple regions of the human cerebral cortex. We identified distinct history-dependent neural signals in motor and posterior parietal cortex. Gamma-band activity in parietal cortex tracked previous choices in a sustained fashion, and biased evidence accumulation toward choice repetition; sustained beta-band activity in motor cortex inversely reflected the previous motor action, and biased the accumulation starting point toward alternation. The parietal, not motor, signal mediated the impact of previous on current choice and reflected individual differences in choice repetition. In sum, parietal cortical signals seem to play a key role in shaping choice sequences.

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bioRxiv2021

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted-U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits.

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bioRxiv2020

Pupil dilation and P3 reflect subjective surprise about decision outcome

Central to human and animal cognition is the ability to learn from feedback in order to optimize future rewards. Such a learning signal might be encoded and broadcasted by the brains arousal systems, including the noradrenergic locus coeruleus. Pupil responses and the positive slow wave component of event-related potentials reflect rapid changes in the arousal level of the brain. Here we ask whether and how these variables may reflect surprise: the mismatch between ones expectation about being correct and the outcome of a decision, when expectations fluctuate due to internal factors (e.g., engagement). We show that during an elementary decision-task in the face of uncertainty both physiological markers of phasic arousal reflect surprise. We further show that pupil responses and slow wave ERP are unrelated to each other, and that prediction error computations depend on feedback awareness. These results further advance our understanding of the role of central arousal systems in decision-making under uncertainty.

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bioRxiv2020

Dissociation between catecholamines and acetylcholine in the human cerebral cortex

Influential accounts postulate distinct roles of the catecholamine and acetylcholine neuromodulatory systems in cognition and behavior. But previous work found similar effects of these modulators on the response properties of individual cortical neurons. Here, we report a double dissociation between catecholamine and acetylcholine effects at the level of cortex-wide network interactions in humans. A pharmacological boost of catecholamine levels increased cortex-wide interactions during a visual task, but not rest. Conversely, an acetylcholine-boost decreased correlations during rest, but not task. Cortical circuit modeling explained this dissociation by differential changes in two circuit properties: the local excitation-inhibition balance (more strongly altered by catecholamines) and intracortical transmission (more strongly reduced by acetylcholine). The inferred catecholaminergic mechanism also predicted increased behavioral exploration, which we confirmed in human behavior during both a perceptual and value-based choice task. In sum, we identified specific circuit mechanisms for shaping cortex-wide network interactions and behavior by key neuromodulatory systems.

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bioRxiv2020

Comparing fMRI responses measured at 3 versus 7 Tesla across human cortex, striatum, and brainstem

Significant progress has been made in ultra-high field functional magnetic resonance imaging (fMRI) at 7 Tesla (T). While fMRI at 7 T promises a general increase in sensitivity compared to lower field strengths, the benefits may be most pronounced for specific applications. The current study aimed to evaluate the relative benefit of 7 T over 3 T fMRI for the assessment of task-evoked fMRI responses in different brain regions. We compared the amplitude of task-evoked responses between 3 T and 7 T measured from the same human participants. Participants performed a challenging random dot motion discrimination task with delayed monetary feedback, which animal physiology has linked to several cortical and subcortical structures including extrastriate (dorsal) visual cortical areas, the striatum, and the brainstem including dopaminergic midbrain nuclei. We quantified the evoked fMRI responses in each of these brain regions during the decision interval and the post-feedback interval of the task, and compared them between brain regions and field strengths. The dependence of response amplitudes on field strength during the decision interval differed between cortical, striatal, and brainstem regions, with a generally bigger 7 T vs. 3 T benefit in subcortical (in particular brainstem) structures. We also found stronger differential responses during easy than hard decisions at 7 T for the dopaminergic nuclei, possibly reflecting reward expectation. Our results demonstrate the potential of 7 T fMRI for illuminating the contribution of small brainstem nuclei to the orchestration of cognitive computations in the human brain. HighlightsO_LIWe compared 7 T to 3 T fMRI during perceptual decision-making under uncertainty. C_LIO_LIDifferences between 7 T and 3 T evoked responses and tSNR varied across the brain. C_LIO_LIEvoked responses in dopaminergic brainstem nuclei were bigger at 7 T than 3 T. C_LIO_LIThe responses of dopaminergic nuclei are consistent with reward expectation. C_LIO_LIResults highlight the potential of 7 T fMRI for imaging small brainstem nuclei. C_LI

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bioRxiv2020

Choices Change the Temporal Weighting of Decision Evidence

Decisions do not occur in isolation, but are embedded in sequences of other decisions, often pertaining to the same source of evidence. Here, we characterized the impact of intermittent choices on the accumulation of a protracted stream of decision-relevant evidence towards a final decision. Human participants performed two versions, based on perceptual or numerical evidence, of a decision task that required two successive judgments at different times during the evidence stream: an intermittent response consisting of a binary choice, and a continuous estimation at the end of the evidence stream. In a control condition, subjects executed a choice-independent motor response instead of binary choice as the intermittent response. In both, perceptual and numerical tasks, the intermittent choice reduced the sensitivity of subsequent evidence, and flipped the relative temporal weighting of early and late evidence in the final estimation judgment. The individual extent of the choice-induced overall (non-selective) sensitivity reduction predicted the extent of the selective down-weighting of subsequent evidence inconsistent with the initial choice, a form of confirmation bias. In sum, active decisions about a protracted evidence stream profoundly alter the dynamics of evidence accumulation, consistent with an active, modulatory mechanism triggered by the choice.

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bioRxiv2020

Dynamic expressions of confidence within an evidence accumulation framework

Human observers can reliably report their confidence in the choices they make. An influential framework conceptualizes decision confidence as the probability of a decision being correct, given the choice made and the evidence on which it was based. This framework accounts for three diagnostic signatures of human confidence reports, including an opposite dependence of confidence on evidence strength for correct and error trials. However, the framework does not account for the temporal evolution of these signatures, because it only describes the transformation of a static representation of evidence into choice and the associated confidence. Here, we combine this framework with another influential framework: dynamic accumulation of evidence over time, and build on the notion that confidence reflects the probability of being correct, given the choice and accumulated evidence up until that point. Critically, we show that such a dynamic model predicts that the diagnostic signatures of confidence depend on time; most critically, it predicts a stronger opposite dependence of confidence on evidence strength and choice correctness as a function of time. We tested, and confirmed, these predictions in human behaviour during random dot motion discrimination, in which confidence judgments were queried at different points in time. We conclude that human confidence reports reflect the dynamics of the probability of being correct given the accumulated evidence and choice.

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bioRxiv2020

Normative Circuit Dynamics Across Human Cortex During Evidence Accumulation in Changing Environments

Many decisions under uncertainty entail the temporal accumulation of evidence that informs about the state of the environment. When environments are subject to hidden changes in their state, maximizing accuracy and reward requires non-linear accumulation of the evidence. How this adaptive, non-linear computation is realized in the brain is unknown. We analyzed human behavior and cortical population activity (measured with magnetoencephalography) recorded during visual evidence accumulation in a changing environment. Behavior and decision-related activity in cortical regions involved in action planning exhibited hallmarks of adaptive evidence accumulation, which could also be implemented by a recurrent cortical microcircuit. Decision dynamics in action-encoding parietal and frontal regions were mirrored in a frequency-specific modulation of the state of visual cortex that depended on pupil-linked arousal and the expected probability of change. These findings link normative decision computations to recurrent cortical circuit dynamics and highlight the adaptive nature of decision-related feedback to sensory cortex.

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bioRxiv2019

The relationship between neural variability and neural oscillations

Neural activity fluctuates over time, creating considerable variability across trials. This trial-by-trial neural variability is dramatically reduced ("quenched") after the presentation of sensory stimuli. Likewise, the power of neural oscillations, primarily in the alpha-beta band, is also reduced. Despite their similarity, these phenomena have been discussed independently. We hypothesized that the two phenomena are tightly coupled. To test this, we examined magnetoencephalography (MEG) recordings of healthy subjects viewing repeated presentations of a visual stimulus. The timing, amplitude, and spatial topography of variability-quenching and power suppression were remarkably similar. Neural variability quenching was eliminated by excluding the alpha-beta band from the recordings, but not by excluding other frequency-bands. Moreover, individual magnitudes of alpha-beta band power explained 86% of between-subject differences in variability quenching. In contrast, inter-trial-phase-coherence (ITPC) was not correlated with variability quenching. These results reveal that neural variability quenching reflects stimulus-induced changes in the power of alpha-beta band oscillations.

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bioRxiv2018

Post-decisional sense of confidence shapes speed-accuracy tradeoff for subsequent choices

When external feedback about decision outcomes is lacking, agents need to adapt their decision policies based on an internal estimate of the correctness of their choices (i.e., decision confidence). We hypothesized that agents use confidence to continuously update the tradeoff between the speed and accuracy of their decisions: When confidence is low in one decision, the agent needs more evidence before committing to a choice in the next decision, leading to slower but more accurate decisions. We tested this hypothesis by fitting a bounded accumulation decision model to behavioral data from three different perceptual choice tasks. Decision bounds indeed depended on the reported confidence on the previous trial, independent of objective accuracy. This increase in decision bound was predicted by a centro-parietal EEG component sensitive to confidence. We conclude that the brain uses internally computed confidence signals for the ongoing adjustment of decision policies.

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bioRxiv2018

Phasic arousal optimizes decision computations in mice and humans

Decisions are often made by accumulating ambiguous evidence over time. The brains arousal systems are activated during such decisions. In previous work in humans, we showed that evoked responses of arousal centers during decisions are reported by rapid dilations of the pupil, and predict a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al. 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes across species (humans / mice), sensory systems (visual / auditory), and domains of decision-making (perceptual / memory-based). In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high arousal. Similar bias suppression occurred when evidence was drawn from memory. All these behavioral effects were explained by reduced evidence accumulation biases. Our results pinpoint a general principle of the interplay between phasic arousal and decision-making.

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bioRxiv2018

Task-evoked pupil responses reflect internal belief states

Perceptual decisions about the state of the environment are often made in the face of uncertain evidence. Internal uncertainty signals are considered important regulators of learning and decision-making. A growing body of work has implicated the brains arousal systems in uncertainty signaling. Here, we found that two specific computational variables, postulated by recent theoretical work, evoke boosts of arousal at different times during a perceptual decision: decision confidence (the observers internally estimated probability that a choice was correct given the evidence) before feedback, and prediction errors (deviations from expected reward) after feedback. We monitored pupil diameter, a peripheral marker of central arousal state, while subjects performed a challenging perceptual choice task with a delayed monetary reward. We quantified evoked pupil responses during decision formation and after reward-linked feedback. During both intervals, decision difficulty and accuracy had interacting effects on pupil responses. Pupil responses negatively scaled with decision confidence prior to feedback and scaled with uncertainty-dependent prediction errors after feedback. This pattern of pupil responses during both intervals was in line with a model using the observers graded belief about choice accuracy to anticipate rewards and compute prediction errors. We conclude that pupil-linked arousal systems are modulated by internal belief states.

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bioRxiv2018

Amplification and Suppression of Distinct Brain-wide Activity Patterns by Catecholamines

The widely projecting catecholaminergic (norepinephrine and dopamine) neurotransmitter systems profoundly shape the state of neuronal networks in the forebrain. Current models posit that the effects of catecholaminergic modulation on network dynamics are homogenous across the brain. However, the brain is equipped with a variety of catecholamine receptors with distinct functional effects and heterogeneous density across brain regions. Consequently, catecholaminergic effects on brain-wide network dynamics might be more spatially specific than assumed. We tested this idea through the analysis of functional magnetic resonance imaging (fMRI) measurements performed in humans (19 females, 5 males) at rest under pharmacological (atomoxetine-induced) elevation of catecholamine levels. We used a linear decomposition technique to identify spatial patterns of correlated fMRI signal fluctuations that were either increased or decreased by atomoxetine. This yielded two distinct spatial patterns, each expressing reliable and specific drug effects. The spatial structure of both fluctuation patterns resembled the spatial distribution of the expression of catecholamine receptor genes: 1 norepinephrine receptors (for the fluctuation pattern: placebo > atomoxetine), D2-like dopamine receptors (pattern: atomoxetine > placebo), and {beta} norepinephrine receptors (for both patterns, with correlations of opposite sign). We conclude that catecholaminergic effects on the forebrain are spatially more structured than traditionally assumed and at least in part explained by the heterogeneous distribution of various catecholamine receptors. Our findings link catecholaminergic effects on large-scale brain networks to low-level characteristics of the underlying neurotransmitter systems. They also provide key constraints for the development of realistic models of neuromodulatory effects on large-scale brain network dynamics.\n\nSIGNIFICANCE STATEMENTThe catecholamines norepinephrine and dopamine are an important class of modulatory neurotransmitters. Because of the widespread and diffuse release of these neuromodulators, it has commonly been assumed that their effects on neural interactions are homogenous across the brain. Here, we present results from the human brain that challenge this view. We pharmacologically increased catecholamine levels and imaged the effects on the spontaneous covariations between brain-wide fMRI signals at rest. We identified two distinct spatial patterns of covariations: one that was amplified and another that was suppressed by catecholamines. Each pattern was associated with the heterogeneous spatial distribution of the expression of distinct catecholamine receptor genes. Our results provide novel insights into the catecholaminergic modulation of large-scale human brain dynamics.

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bioRxiv2018

Reading memory formation from the eyes

At any time, we are processing thousands of stimuli, but only few of them will be remembered hours or days later. Is there any way to predict which ones? Here, we show that the pupil response to ongoing stimuli, an indicator of physiological arousal, is a reliable predictor of long-term memory for these stimuli, over at least one day. Pupil dilation was tracked while participants performed visual and auditory encoding tasks. Memory was tested immediately after encoding and 24 hours later. Irrespective of the encoding modality, trial-by-trial variations in pupil dilation predicted which stimuli were recalled in the immediate and 24 hours-delayed tests. These results show that our eyes may provide a window into the formation of long-term memories. Furthermore, our findings underline the important role of central arousal systems in the rapid formation of memories in the brain, possibly by gating synaptic plasticity mechanisms.

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