bestmannlab

Computing value from quality and quantity in human decision making

de Berker Ao, Kurth_nelson Z, Rutledge RB, Bestmann S, Dolan R

J Neurosci

How organisms learn the value of single stimuli through experience is well described. In many decisions, however, value estimates are computed 'on the fly', by combining multiple stimulus attributes. The neural basis of this computation is poorly understood. Here we explore a common scenario in which decision-makers must combine information about quality and quantity to determine the best option. Using fMRI, we examined the neural representation of quality, quantity, and their integration into an integrated subjective value signal in humans of both genders. We found that activity within Inferior Frontal Gyrus (IFG) correlated with offer quality, whilst activity in the Intra Parietal Sulcus (IPS) specifically correlated with offer quantity. Several brain regions, including the Anterior Cingulate Cortex (ACC), were sensitive to an interaction of quality and quantity. However, the ACC was uniquely activated by quality, quantity, and their interaction, suggesting this region provides a substrate for flexible computation of value from both quality and quantity. Furthermore, ACC signals across subjects correlated with the strength of quality and quantity signals in IFG and IPS respectively. ACC tracking of subjective value also correlated with choice predictability. Finally, activity in the ACC was elevated for choice trials, suggesting that ACC provides a nexus for the computation of subjective value in multi-attribute decision making.SIGNIFICANCE STATEMENTWould you prefer 3 apples or 2 oranges? Many choices we make each day require us to weigh up the quality and quantity of different outcomes. Using fMRI, we show that option quality is selectively represented in the Inferior Frontal Gyrus (IFG), whilst option quantity correlates with areas of the Intra Parietal Sulcus (IPS) which have previously been associated with numerical processing. We show that information about the two is integrated into a value signal in the Anterior Cingulate Cortex (ACC), and the fidelity of this integration predicts choice predictability. Our results demonstrate how on-the-fly value estimates are computed from multiple attributes in human value-based decision making.
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Forget-me-some: General versus special purpose models in a hierarchical probabilistic task

Broker F, Marshall L, Bestmann S, Dayan P

PLoS One

Humans build models of their environments and act according to what they have learnt. In simple experimental environments, such model-based behaviour is often well accounted for as if subjects are ideal Bayesian observers. However, more complex probabilistic tasks require more sophisticated forms of inference that are sufficiently computationally and statistically taxing as to demand approximation. Here, we study properties of two approximation schemes in the context of a serial reaction time task in which stimuli were generated from a hierarchical Markov chain. One, pre-existing, scheme was a generically powerful variational method for hierarchical inference which has recently become popular as an account of psychological and neural data across a wide swathe of probabilistic tasks. A second, novel, scheme was more specifically tailored to the task at hand. We show that the latter model fit significantly better than the former. This suggests that our subjects were sensitive to many of the particular constraints of a complex behavioural task. Further, the tailored model provided a different perspective on the effects of cholinergic manipulations in the task. Neither model fit the behaviour on more complex contingencies that competently. These results illustrate the benefits and challenges that come with the general and special purpose modelling approaches and raise important questions of how they can advance our current understanding of learning mechanisms in the brain
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Motor training modulates intracortical inhibitory dynamics in motor cortex during movement preparation

Hadwen-Dupont J, Bestmann S, Stagg CJ

Brain Stimulation

Background: The primary motor cortex (M1) has a vital role to play in the learning of novel motor skills. However, the physiological changes underpinning this learning, particularly in terms of dynamic changes during movement preparation, are incompletely understood. In particular, a substantial decrease in resting gamma-amino butyric acid (GABA) activity, i.e. a release of resting inhibition, is seen within M1 as a subject prepares to move. Although there is evidence that a decrease in resting inhibition occurs within M1 during motor learning it is not known whether the pre-movement “release” of GABAergic inhibition is modulated during skill acquisition. Objective: Here, we investigated changes in pre-movement GABAergic inhibitory “release” during training on a motor skill task. Methods: We studied GABAA activity using paired-pulse TMS (Short-Interval Intracortical Inhibition (SICI)) during training on a ballistic thumb abduction task, both at rest and at two time-points during movement preparation. Results: Improvement in task performance was related to a later, steeper, release of inhibition during the movement preparation phase. Specifically, subjects who showed greater improvement in the task in the early stages of training showed a reduced level of GABAergic release immediately prior to movement compared with those who improved less. Later in training, subjects who performed better showed a reduction in GABAergic release early in movement preparation. Conclusions: These findings suggest that motor training is associated with maintained inhibition in motor cortex during movement preparation.
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Lamina-specific cortical dynamics in human visual and sensorimotor cortices

James J Bonaiuto , Sofie S Meyer, Simon Little, Holly Rossiter, Martina F Callaghan, Frederic Dick, Gareth R Barnes, Sven Bestmann

Elife https://doi.org/10.7554/eLife.33977.001

Distinct anatomical and spectral channels are thought to play specialized roles in the communication within cortical networks. While activity in the alpha and beta frequency range (7 – 40 Hz) is thought to predominantly originate from infragranular cortical layers conveying feedback-related information, activity in the gamma range (>40 Hz) dominates in supragranular layers communicating feedforward signals. We leveraged high precision MEG to test this proposal, directly and non-invasively, in human participants performing visually cued actions. We found that visual alpha mapped onto deep cortical laminae, whereas visual gamma predominantly occurred more superficially. This lamina-specificity was echoed in movement-related sensorimotor beta and gamma activity. These lamina-specific pre- and post- movement changes in sensorimotor beta and gamma activity suggest a more complex functional role than the proposed feedback and feedforward communication in sensory cortex. Distinct frequency channels thus operate in a lamina-specific manner across cortex, but may fulfill distinct functional roles in sensory and motor processes
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Pharmacological Dopamine Manipulation Does Not Alter Reward-Based Improvements in Memory Retention during a Visuomotor Adaptation Task

Graziella Quattrocchi,Jessica Monaco,Andy Ho,Friederike Irmen,Wolfgang Strube, Diane Ruge, Sven Bestmann, Joseph M. Galea

eNeuro

Motor adaptation tasks investigate our ability to adjust motor behaviors to an ever-changing and unpredictable world. Previous work has shown that punishment-based feedback delivered during a visuomotor adaptation task enhances error-reduction, whereas reward increases memory retention. While the neural underpinnings of the influence of punishment on the adaptation phase remain unclear, reward has been hypothesized to increase retention through dopaminergic mechanisms. We directly tested this hypothesis through pharmacological manipulation of the dopaminergic system. A total of 96 young healthy human participants were tested in a placebo-controlled double-blind between-subjects design in which they adapted to a 40° visuomotor rotation under reward or punishment conditions. We confirmed previous evidence that reward enhances retention, but the dopamine (DA) precursor levodopa (LD) or the DA antagonist haloperidol failed to influence performance. We reason that such a negative result could be due to experimental limitations or it may suggest that the effect of reward on motor memory retention is not driven by dopaminergic processes. This provides further insight regarding the role of motivational feedback in optimizing motor learning, and the basis for further decomposing the effect of reward on the subprocesses known to underlie motor adaptation paradigms
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Preparation of movement

Haith A, Bestmann S

Cognitive Neurosciences, 6th edition, Eds David Poeppel, George Mangun, Michael Gazzaniga

It is widely believed that voluntary movements must be prepared before they are executed, but there is so far little consensus on exactly what mechanisms and computations must occur prior to a movement. Here, we argue that movement preparation is most usefully thought of as a process of setting an appropriate state for the motor system that poises it to generate a particular desired movement. This process, which can occur in as little as 50 ms, does not directly trigger movement initiation, nor is it required to initiate a movement. Instead, initiation of movement is determined by a distinct process, independent of the state of movement preparation. We suggest that, during the course of determining a task goal, or making a decision, the prepared state is continually updated as the desired movement changes in light of new evidence and beliefs. This ensures that the motor system is able to generate an appropriate movement as rapidly possible when necessary.
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Cognitive neuroscience using wearable magnetometer arrays: non-invasive assessment of language function

Tierney T, Holmes N, Meyer S, Boto E, Roberts G, Leggett J, Buck S, Duque-Muñoz L, Litvak V, Bestmann S, Baldeweg T, Bowtell, Brookes MJ, Barnes GR

NeuroImage

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Quantifying the performance of MEG source reconstruction using resting state data

Little S, Bonaiuto JJ, Meyer S, Lopez J, Bestmann S, Barnes G

NeuroImage

In magnetoencephalography (MEG) research there are a variety of inversion methods to transform sensor data into estimates of brain activity. Each new inversion scheme is generally justified against a specific simulated or task scenario. The choice of this scenario will however have a large impact on how well the scheme performs. We describe a method with minimal selection bias to quantify algorithm performance using human resting state data. These recordings provide a generic, heterogeneous, and plentiful functional substrate against which to test different MEG recording and reconstruction approaches. We used a Hidden Markov model to spatio-temporally partition data into self-similar dynamic states. To test the anatomical precision that could be achieved, we then inverted these data onto libraries of systematically distorted subject-specific cortical meshes and compared the quality of the fit using cross validation and a Free energy metric. This revealed which inversion scheme was able to identify the least distorted (most accurate) anatomical models, and allowed us to quantify an upper bound on the mean anatomical distortion accordingly. We used two resting state datasets, one recorded with head-casts and one without. In the head-cast data, the Empirical Bayesian Beamformer (EBB) algorithm showed the best mean anatomical discrimination (3.7 mm) compared with Minimum Norm/LORETA (6.0 mm) and Multiple Sparse Priors (9.4 mm). This pattern was replicated in the second (conventional dataset) although with a marginally poorer (non-significant) prediction of the missing (cross-validated) data. Our findings suggest that the abundant resting state data now commonly available could be used to refine and validate MEG source reconstruction methods and/or recording paradigms.
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Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions

Spieser L, Kohl C, Forster B, Bestmann S, Yarrow K

eNeuro

Evolutionary pressures suggest that choices should be optimized to maximize rewards, by appropriately trading speed for accuracy. This speed-accuracy tradeoff (SAT) is commonly explained by variation in just the baseline-to-boundary distance, i.e., the excursion, of accumulation-to-bound models of perceptual decision-making. However, neural evidence is not consistent with this explanation. A compelling account of speeded choice should explain both overt behavior and the full range of associated brain signatures. Here, we reconcile seemingly contradictory behavioral and neural findings. In two variants of the same experiment, we triangulated upon the neural underpinnings of the SAT in the human brain using both EEG and transcranial magnetic stimulation (TMS). We found that distinct neural signals, namely the event-related potential (ERP) centroparietal positivity (CPP) and a smoothed motor-evoked potential (MEP) signal, which have both previously been shown to relate to decision-related accumulation, revealed qualitatively similar average neurodynamic profiles with only subtle differences between SAT conditions. These signals were then modelled from behavior by either incorporating traditional boundary variation or utilizing a forced excursion. These model variants are mathematically equivalent, in terms of their behavioral predictions, hence providing identical fits to correct and erroneous reaction time distributions. However, the forced-excursion version instantiates SAT via a more global change in parameters and implied neural activity, a process conceptually akin to, but mathematically distinct from, urgency. This variant better captured both ERP and MEP neural profiles, suggesting that the SAT may be implemented via neural gain modulation, and reconciling standard modelling approaches with human neural data
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Age-dependent Pavlovian biases influence motor decision-making

Chen X, Rutledge R, Brown H, Dolan R, Bestmann S, Galea J

PLoS Comp Biol

Motor decision-making is an essential component of everyday life which requires weighing potential rewards and punishments against the probability of successfully executing an action. To achieve this, humans rely on two key mechanisms; a flexible, instrumental, value-dependent process and a hardwired, Pavlovian, value-independent process. In economic decision-making, age-related decline in risk taking is explained by reduced Pavlovian biases that promote action toward reward. Although healthy ageing has also been associated with decreased risk-taking in motor decision-making, it is currently unknown whether this is a result of changes in Pavlovian biases, instrumental processes or a combination of both. Using a newly established approach-avoidance computational model together with a novel app-based motor decision-making task, we measured sensitivity to reward and punishment when participants (n=26,532) made a ‘go/no-go’ motor gamble based on their perceived ability to execute a complex action. We show that motor decision-making can be better explained by a model with both instrumental and Pavlovian parameters, and reveal age-related changes across punishment- and reward-based instrumental and Pavlovian processes. However, the most striking effect of ageing was a decrease in Pavlovian attraction towards rewards, which was associated with a reduction in optimality of choice behaviour. In a subset of participants who also played an independent economic decision-making task (n=17,220), we found similar decision-making tendencies across motor and economic domains. Pavlovian biases, therefore, play an important role in not only explaining motor decision-making behaviour but also the changes which occur through normal ageing. This provides a deeper understanding of the mechanisms which shape motor decision-making across the lifespan.
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Moving magnetoencephalography towards real-world applications with a wearable system

Boto, Holmes, Leggett, Roberts, Shah, Meyer, Duque Muñoz, Mullinger, Tierney, Bestmann, Barnes, Bowtell, Brookes

Nature

Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders
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Incomplete evidence that increasing current intensity of tDCS boosts outcomes

Esmaeilpour Z, Marangolo P, Hampstead BM, Bestmann S, Galletta E, Knotkova H, Bikson M

Brain Stimulation

BACKGROUND: Transcranial direct current stimulation (tDCS) is investigated to modulate neuronal function by applying a fixed low-intensity direct current to scalp. OBJECTIVES: We critically discuss evidence for a monotonic response in effect size with increasing current intensity, with a specific focus on a question if increasing applied current enhance the efficacy of tDCS. METHODS: We analyzed tDCS intensity does-response from different perspectives including biophysical modeling, animal modeling, human neurophysiology, neuroimaging and behavioral/clinical measures. Further, we discuss approaches to design dose-response trials. RESULTS: Physical models predict electric field in the brain increases with applied tDCS intensity. Data from animal studies are lacking since a range of relevant low-intensities is rarely tested. Results from imaging studies are ambiguous while human neurophysiology, including using transcranial magnetic stimulation (TMS) as a probe, suggests a complex state-dependent non-monotonic dose response. The diffusivity of brain current flow produced by conventional tDCS montages complicates this analysis, with relatively few studies on focal High Definition (HD)-tDCS. In behavioral and clinical trials, only a limited range of intensities (1-2 mA), and typically just one intensity, are conventionally tested; moreover, outcomes are subject brain-state dependent. Measurements and models of current flow show that for the same applied current, substantial differences in brain current occur across individuals. Trials are thus subject to inter-individual differences that complicate consideration of population-level dose response. CONCLUSION: The presence or absence of simple dose response does not impact how efficacious a given tDCS dose is for a given indication. Understanding dose-response in human applications of tDCS is needed for protocol optimization including individualized dose to reduce outcome variability, which requires intelligent design of dose-response studies
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Transcranial electrical stimulation

Bestmann S, Walsh V

Current Biology (in press)

Transcranial electrical stimulation (tES) is a neuromodulatory technique in which low voltage constant or alternating currents are applied to the human brain via scalp electrodes. The basic idea of tES is that the application of weak currents can interact with neural processing, modify plasticity and entrain brain networks, and that this in turn can modify behaviour. The technique is now widely employed in basic and translational research, and increasingly is also used privately in sport, the military and recreation. The proposed capacity to augment recovery of brain function, by promoting learning and facilitating plasticity, has motivated a burgeoning number of clinical trials in a wide range of disorders of the nervous system. The mechanisms through which tES exerts its behavioural effects in the human brain, however, remain poorly understood. Recent debate has also focussed on the reliability and reproducibility of tES, including debate about its overall utility. This primer highlights important concepts, but also misconceptions surrounding the technique, and outlines possible avenues through which to advance the current state of the art.
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tDCS changes in motor excitability are specific to orientation of current flow

Rawiji V, Ciocca M, Zacharia A, Soares D, Truong D, Bikson M, Rothwell J, Bestmann S

Brain Stimulation

Background: Measurements and models of current flow in the brain during transcranial Direct Current Stimulation (tDCS) indicate stimulation of regions in-between electrodes. Moreover, the folded cortex results in local fluctuations in current flow intensity and direction, and animal studies suggest current flow direction relative to cortical columns determines response to tDCS. Methods: Here we test this idea by using Transcranial Magnetic Stimulation Motor Evoked Potentials (TMS-MEP) to measure changes in corticospinal excitability following tDCS applied with electrodes aligned orthogonal (across) or parallel to M1 in the central sulcus. Results: Current flow models predicted that the orthogonal electrode montage produces consistently oriented current across the hand region of M1 that flows along cortical columns, while the parallel electrode montage produces non-uniform current directions across the M1 cortical surface. We find that orthogonal, but not parallel, orientated tDCS modulates TMS-MEPs. We also show modulation is sensitive to the orientation of the TMS coil (PA or AP), which is thought to select different afferent pathways to M1. Conclusions: Our results are consistent with tDCS producing directionally specific neuromodulation in brain regions in-between electrodes, but shows nuanced changes in excitability that are presumably current direction relative to column and axon pathway specific. We suggest that the direction of current flow through cortical target regions should be considered for targeting and dose-control of tDCS.
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Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithm

Bonaiuto J, Rossiter HE, Meyer SS, Adams N, Little S, Callaghan MF, Dick F, Bestmann S, Barnes GR

Neuroimage

Magnetoencephalography (MEG) is a direct measure of neuronal current flow; its anatomical resolution is therefore not constrained by physiology but rather by data quality and the models used to explain these data. Recent simulation work has shown that it is possible to distinguish between signals arising in the deep and superficial cortical laminae given accurate knowledge of these surfaces with respect to the MEG sensors. This previous work has focused around a single inversion scheme (multiple sparse priors) and a single global parametric fit metric (free energy). In this paper we use several different source inversion algorithms and both local and global, as well as parametric and non-parametric fit metrics in order to demonstrate the robustness of the discrimination between layers. We find that only algorithms with some sparsity constraint can successfully be used to make laminar discrimination. Importantly, local t-statistics, global cross-validation and free energy all provide robust and mutually corroborating metrics of fit. We show that discrimination accuracy is affected by patch size estimates, cortical surface features, and lead field strength, which suggests several possible future improvements to this technique. This study demonstrates the possibility of determining the laminar origin of MEG sensor activity, and thus directly testing theories of human cognition that involve laminar- and frequency- specific mechanisms. This possibility can now be achieved using recent developments in high precision MEG, most notably the use of subject-specific head-casts, which allow for significant increases in data quality and therefore anatomically precise MEG recordings.
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tDCS changes in motor excitability are specific to orientation of current flow

Vishal Rawji, Matteo Ciocca, Andre Zacharia, David Soares, Dennis Truong, Marom Bikson, John Rothwell, Sven Bestmann

BioRxiv

Measurements and models of current flow in the brain during transcranial Direct Current Stimulation (tDCS) indicate stimulation of regions in-between electrodes. Moreover, the cephalic cortex result in local fluctuations in current flow intensity and direction, and animal studies suggest current flow direction relative to cortical columns determines response to tDCS. Here we test this idea by measuring changes in cortico-spinal excitability by Transcranial Magnetic Stimulation Motor Evoked Potentials (TMS-MEP), following tDCS applied with electrodes aligned orthogonal (across) or parallel to M1 in the central sulcus. Current flow models predicted that the orthogonal electrode montage produces consistently oriented current across the hand region of M1 that flows along cortical columns, while the parallel electrode montage produces none-uniform current directions across the M1 cortical surface. We find that orthogonal, but not parallel, orientated tDCS modulates TMS-MEPs. We also show modulation is sensitive to the orientation of the TMS coil (PA or AP), which is through to select different afferent pathways to M1. Our results are consistent with tDCS producing directionally specific neuromodulation in brain regions in-between electrodes, but shows nuanced changes in excitability that are presumably current direction relative to column and axon pathway specific. We suggest that the direction of current flow through cortical target regions should be considered for targeting and dose-control of tDCS.
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Are current flow models for transcranial electrical stimulation fit for purpose?

Bestmann S, Ward NS

Brain Stimulation

Transcranial electrical stimulation (tES) enjoys a burgeoning reputation in basic and clinical research, and home-use. Even though Rush and Driscoll highlighted more than 40 years ago that “the amount of current entering the brain is of great consequence”, to this day tES studies generally do not control how much current is actually delivered to the brain. Instead, tES applications control the output of a stimulator, and so for most applications we do not control that comparable doses of current are delivered to the brain of different individuals. Yet we do know that the idiosyncratic properties of the head strongly influence how much of a fixed output current (e.g. 1mA) will reach the brain, and so we are in the extraordinary position of knowing that the effective dose of tES is highly variable across individuals, yet doing very little about it.
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Reward and punishment enhance motor adaptation in stroke

Quattrocchi G, Greenwood R, Rothwell JC, Galea JM, Bestmann S

J Neurology Neurosurgery & Psychiatry

The effects of motor learning, such as motor adaptation, in stroke rehabilitation are often transient, thus mandating approaches that enhance the amount of learning and retention. Previously, we showed in young individuals that reward and punishment feedback have dissociable effects on motor adaptation, with punishment improving adaptation and reward enhancing retention. If these findings were able to generalise to patients with stroke, they would provide a way to optimise motor learning in these patients. Therefore, we tested this in 45 patients with chronic stroke allocated in three groups. Patients performed reaching movements with their paretic arm with a robotic manipulandum. After training (day 1), day 2 involved adapting to a novel force field. During this adaptation phase, patients received performance-based feedback according to the group they were allocated: reward, punishment or no feedback (neutral). On day 3, patients readapted to the force field but all groups now received neutral feedback. All patients adapted, with reward and punishment groups displaying greater adaptation and readaptation than the neutral group, irrespective of demographic, cognitive or functional differences. Remarkably, the reward and punishment groups adapted to similar degree as ealthy controls. Finally, the reward group showed greater retention. This study provides, for the first time, evidence that reward and punishment an enhance motor adaptation in patients with stroke. Further research on reinforcement based motor learning regimes is warranted to translate these promising results into clinical practice and improve motor rehabilitation outcomes in patients with stroke.
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Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models

Bonaiuto J, de Berker A, Bestmann S

eLife

Animals and humans have a tendency to repeat recent choices, a phenomenon known as choice hysteresis. The mechanism for this choice bias remains unclear. Using an established, biophysically informed model of a competitive attractor network for decision making, we found that decaying tail activity from the previous trial caused choice hysteresis, especially during difficult trials, and accurately predicted human perceptual choices. In the model, choice variability could be directionally altered through amplification or dampening of post-trial activity decay through simulated depolarizing or hyperpolarizing network stimulation. An analogous intervention using transcranial direct current stimulation (tDCS) over left dorsolateral prefrontal cortex (dlPFC) yielded a close match between model predictions and experimental results: net soma depolarizing currents increased choice hysteresis, while hyperpolarizing currents suppressed it. Residual activity in competitive attractor networks within dlPFC may thus give rise to biases in perceptual choices, which can be directionally controlled through non-invasive brain stimulation.
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Flexible head-casts for high spatial precision MEG

Meyer SS, Bonaiuto J, Lim M, Rossiter H, Waters S, Bradbury D, Bestmann S, Brookes M, Callaghan MF, Weiskopf N, Barnes GR

J Neurosci Methods

BACKGROUND: In combination with magnetoencephalographic (MEG) data, accurate knowledge of the brain's structure and location provide a principled way of reconstructing neural activity with high temporal resolution. However, measuring the brain's location is compromised by head movement during scanning, and by fiducial-based co-registration with magnetic resonance imaging (MRI) data. The uncertainty from these two factors introduces errors into the forward model and limit the spatial resolution of the data. NEW METHOD: We present a method for stabilizing and reliably repositioning the head during scanning, and for co-registering MRI and MEG data with low error. RESULTS: Using this new flexible and comfortable subject-specific head-cast prototype, we find within-session movements of <0.25mm and between-session repositioning errors around 1mm. COMPARISON WITH EXISTING METHOD(S): This method is an improvement over existing methods for stabilizing the head or correcting for location shifts on- or off-line, which still introduce approximately 5mm of uncertainty at best (Adjamian et al., 2004; Stolk et al., 2013; Whalen et al., 2008). Further, the head-cast design presented here is more comfortable, safer, and easier to use than the earlier 3D printed prototype, and give slightly lower co-registration errors (Troebinger et al., 2014b). CONCLUSIONS: We provide an empirical example of how these head-casts impact on source level reproducibility. Employment of the individual flexible head-casts for MEG recordings provide a reliable method of safely stabilizing the head during MEG recordings, and for co-registering MRI anatomical images to MEG functional data.
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Pharmacological fingerprints of contextual uncertainty

Marshall M, Mathys C, Ruge D, de Berker A, Dayan P, Stephan KE, Bestmann S

PLOS Biology http://dx.doi.org/10.1371/journal.pbio.1002575

Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.
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Neural Signatures of Value Comparison in Human Cingulate Cortex during Decisions Requiring an Effort-Reward Trade-off

Klein-Flugge M, Kennerley SW, Friston K, Bestmann S

Journal of Neuroscience

Integrating costs and benefits is crucial for optimal decision-making. Although much is known about decisions that involve outcomerelated costs (e.g., delay, risk), many of our choices are attached to actions and require an evaluation of the associated motor costs. Yet how the brain incorporates motor costs into choices remains largely unclear. We used human fMRI during choices involving monetary reward and physical effort to identify brain regions that serve as a choice comparator for effort-reward trade-offs. By independently varying both options’ effort and reward levels, we were able to identify the neural signature of a comparator mechanism. A network involving supplementary motor area and the caudal portion of dorsal anterior cingulate cortex encoded the difference in reward (positively) and effort levels (negatively) between chosen and unchosen choice options. We next modeled effort-discounted subjective values using a novel behavioral model. This revealed that the same network of regions involving dorsal anterior cingulate cortex and supplementary motor area encoded the difference between the chosen and unchosen options’ subjective values, and that activity was best described using a concave model of effort-discounting. In addition, this signal reflected how precisely value determined participants’ choices. By contrast, separate signals in supplementary motor area and ventromedial prefrontal cortex correlated with participants’ tendency to avoid effort and seek reward, respectively. This suggests that the critical neural signature of decision-making for choices involving motor costs is found inhumancingulate cortex and not ventromedial prefrontal cortex as typically reported for outcome-based choice. Furthermore, distinct frontal circuits seem to drive behavior toward reward maximization and effort minimization
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Cerebellar tDCS Dissociates the Timing of Perceptual Decisions from Perceptual Change in Speech

Lametti D, Oostwoud Wijdenes L, Bonaiuto J, Bestmann S, Rothwell JC

Journal of Neurophysiology

Neuroimaging studies suggest that the cerebellum might play a role in both speech perception and speech perceptual learning. However, it remains unclear what this role is: does the cerebellum help shape the perceptual decision? Or does it contribute to the timing of perceptual decisions? To test this, we used transcranial direct current stimulation (tDCS) in combination with a speech perception task. Participants experienced a series of speech perceptual tests designed to measure and then manipulate (via training) their perception of a phonetic contrast. One group received cerebellar tDCS during speech perceptual learning and a different group received sham tDCS during the same task. Both groups showed similar learning-related changes in speech perception that transferred to a different phonetic contrast. For both trained and untrained speech perceptual decisions, cerebellar tDCS significantly increased the time it took participants to indicate their decisions with a keyboard press. By analysing perceptual responses made by both hands, we present evidence that cerebellar tDCS disrupted the timing of perceptual decisions, while leaving the eventual decision unaltered. In support of this conclusion, we use the drift diffusion model to decompose the data into processes that determine the outcome of perceptual decision-making and those that do not. The modelling suggests that cerebellar tDCS disrupted processes unrelated to decision-making. Taken together, the empirical data and modelling demonstrate that right cerebellar tDCS dissociates the timing of perceptual decisions from perceptual change. The results provide initial evidence in healthy humans that the cerebellum critically contributes to speech timing in the perceptual domain.
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Are Movement Preparation and Movement Initiation Truly Independent?

Weinberg I

Journal of Neuroscience

Review of Haith et al Journal of Neuroscience 2016
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Acute stress selectively impairs learning to act

de Berker AO, Tirole M, Rutledge R, Cross G, Dolan R, Bestmann S

Nature Scientific Reports

Stress interferes with instrumental learning. However, choice is also influenced by non-instrumental factors, most strikingly by biases arising from Pavlovian associations that facilitate action in pursuit of rewards and inaction in the face of punishment. Whether stress impacts on instrumental learning via these Pavlovian associations is unknown. Here, in a task where valence (reward or punishment) and action (go or no-go) were orthogonalised, we asked whether the impact of stress on learning was action or valence specific. We exposed 60 human participants either to stress (socially-evaluated cold pressor test) or a control condition (room temperature water). We contrasted two hypotheses: that stress would lead to a non-selective increase in the expression of Pavlovian biases; or that stress, as an aversive state, might specifically impact action production due to the Pavlovian linkage between inaction and aversive states. We found support for the second of these hypotheses. Stress specifically impaired learning to produce an action, irrespective of the valence of the outcome, an effect consistent with a Pavlovian linkage between punishment and inaction. This deficit in action-learning was also reflected in pupillary responses; stressed individuals showed attenuated pupillary responses to action, hinting at a noradrenergic contribution to impaired action-learning under stress.
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Selective alteration of human value decisions with medial frontal tDCS is predicted by changes in attractor dynamics

Hammerer D, Bonaiuto J, Klein-Flugge M, Bikson M, Bestmann S

Nature Scientific Reports

During value-based decision making, ventromedial prefrontal cortex (vmPFC) is thought to support choices by tracking the expected gain from different outcomes via a competition based process. Using a computational neurostimulation approach we asked how perturbing this region might alter this competition and resulting value-decisions. We simulated a perturbation of neural dynamics in a biophysically informed model of decision-making through in silico depolarization at the level of neuronal ensembles. Simulated depolarization increased baseline firing rates of pyramidal neurons, which altered their susceptibility to background noise, and thereby increased choice stochasticity. These behavioural predictions were compared to choice behaviour in healthy participants performing similar value decisions during transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique. We placed the depolarizing electrode over medial frontal PFC. In line with model predictions, this intervention resulted in more random choices. By contrast, no such effect was observed when placing the depolarizing electrode over lateral PFC. Using a causal manipulation of ventromedial and lateral prefrontal function, these results provide support for competition-based choice dynamics in human vmPFC, and introduce computational neurostimulation as a mechanistic assay for neurostimulation studies of cognition.
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The Evidence Information Service as a new platform for supporting evidence-based policy: A consultation of UK parliamentarians

Lawrence N, Chambers J, Morrison S, Bestmann S, O'Grady G, Chambers CD, kythreotis AP

Policy & Evidence

The value of evidence-based policy is well established, yet major hurdles remain in connecting policymakers with the wider research community. Here we assess whether a UK Evidence Information Service (EIS) could facilitate interaction between parliamentarians and research professionals. Fifty-six UK parliamentarians were interviewed to gauge the challenges of working with evidence and the potential utility of an EIS. Grounded theory analysis identified several barriers to evidence-based policy making, however 85% of parliamentarians supported the EIS, preferring a rapid, impartial, concise, and optionally confidential service. We conclude that an EIS integrated with existing parliamentary systems could enhance dialogue between policymakers and researchers.
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Computations of uncertainty mediate acute stress responses in humans

de Berker Ao, Rutledge R, Mathys C, Marshall LM, Cross G, Dolan R, Bestmann S

Nature Communications

The effects of stress are frequently studied, yet its proximal causes remain unclear. Here we demonstrate that subjective estimates of uncertainty predict the dynamics of subjective and physiological stress responses. Subjects learned a probabilistic mapping between visual stimuli and electric shocks. Salivary cortisol confirmed that our stressor elicited changes in endocrine activity. Using a hierarchical Bayesian learning model, we quantified the relationship between the different forms of subjective task uncertainty and acute stress responses. Subjective stress, pupil diameter and skin conductance all tracked the evolution of irreducible uncertainty. We observed a coupling between emotional and somatic state, with subjective and physiological tuning to uncertainty tightly correlated. Furthermore, the uncertainty tuning of subjective and physiological stress predicted individual task performance, consistent with an adaptive role for stress in learning under uncertain threat. Our finding that stress responses are tuned to environmental uncertainty provides new insight into their generation and likely adaptive function.
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Computational Neurostimulation

Bestmann S

Prog Brain Research

Computational Neurostimulation, the latest volume in the Progress in Brain Research series provides an introduction to a nascent field with contributions from leading researchers. In addition, it addresses a very timely and relevant issue which has long been known to require more treatment.
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Causal evidence that intrinsic beta frequency is relevant for enhanced signal propagation in the motor system as shown through rhythmic TMS

Romei V, Bauer M, Brooks J, Economides M, Penny W, Thut G, Driver J, Bestmann S

Neuroimage

Correlative evidence provides support for the idea that brain oscillations underpin neural computations. Recent work using rhythmic stimulation techniques in humans provide causal evidence but the interactions of these external signals with intrinsic rhythmicity remain unclear. Here, we show that sensorimotor cortex follows externally applied rhythmic TMS (rTMS) stimulation in the beta-band but that the elicited responses are strongest at the intrinsic individual beta-peak-frequency. While these entrainment effects are of short duration, even subthreshold rTMS pulses propagate through the network and elicit significant cortico-spinal coupling, particularly when stimulated at the individual beta-frequency. Our results show that externally enforced rhythmicity interacts with intrinsic brain rhythms such that the individual peak frequency determines the effect of rTMS. The observed downstream spinal effect at the resonance frequency provides evidence for the causal role of brain rhythms for signal propagation.
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The role of Dopamine in temporal uncertainty

Tomassini A, Galea J, Ruge D, Penny W, Bestmann S

Journal of Cognitive Neuroscience

The temporal preparation of motor responses to external events (temporal preparation) relies on internal representations of the accumulated elapsed time (temporal representations) before an event occurs, and on estimates about its most likely time of occurrence (temporal expectations). The precision (inverse of uncertainty) of temporal preparation, however, is limited by two sources of uncertainty. One is intrinsic to the nervous system and scales with the length of elapsed time such that temporal representations are least precise for longest time durations. The other is external and arises from temporal variability of events in the outside world. The precision of temporal expectations thus decreases if events become more variable in time. It has long been recognized that the processing of time durations within the range of hundreds of milliseconds (interval timing) strongly depends on dopaminergic (DA) transmission. The role of DA for the precision of temporal preparation in humans, however, remains unclear. This study therefore directly assesses the role of DA in the precision of temporal preparation of motor responses in healthy humans. In a placebo-controlled double blind design using a selective D2- receptor antagonist (Sulpiride) and D1/D2 receptor antagonist (Haloperidol), participants performed a variable foreperiod reaching task, under different conditions of internal and external temporal uncertainty. DA blockade produced a striking impairment in the ability of extracting temporal expectations across trials, and on the precision of temporal representations within a trial. Large Weber fractions for interval timing, estimated by fitting subjective hazard functions, confirmed that this effect was driven by an increased uncertainty in the way subjects were experiencing time. This provides novel evidence that DA regulates the precision with which we process time when preparing for an action.
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Computational Neurostimulation for Parkinson’s disease

Little S, Bestmann S

Progress Brain Res

Deep brain stimulation (DBS) has had remarkable success thus far in treating a range of neurological and psychiatric conditions. However, efficacy remains suboptimal and patients can often develop side effects. The underlying causes of both the beneficial and detrimental effects of DBS remain incompletely understood which is delaying improvements to current DBS therapies and limiting developments of future treatments. Advancing this mechanistic understanding will require the design of appropriate models that can formalise the interaction between DBS and the cortico-basal-ganglia network. Recent advances in biophysical modelling have provided important insights into the impact of stimulation at local (neuronal membranes, electrical fields), intermediate (neuronal networks) and higher (phase, synchronisation) levels of description. Whilst biophysical models can be excellent at explaining the causes of neurophysiological data (e.g. spikes, local field potentials) they are often not equipped to make accurate predictions about the resultant consequences on behaviour. We argue that further advance will rest on models that focus on the specific computations that are performed in cortico-basal-ganglia networks. These models address how DBS alters information processing, and crucially, what it is that the circuits targeted by DBS actually encode. For the emergent field of computational modelling as applied to Parkinson’s disease we propose that models at mesoscopic levels of description are likely to be most valuable, with a particular focus on the role of oscillations and their relationship to behaviour. It is therefore hoped that computational neurostimulation will usher in a new era of rapid, rationally derived DBS advancements for neurological and psychiatric disorders.
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Understanding the nonlinear physiological and behavioral effects of tDCS through computational neurostimulation

Bonaiuto J, Bestmann S

Progress in Brain Research (in press)

Despite the success of non-invasive brain stimulation (NIBS), the mechanism of action through which different stimulation techniques interact with information processing in targeted neural circuits often remains unknown. Applying neurostimulation in silico to computational models with biophysical plausibility provides one route to interrogate the possible mechanisms through which stimulation interacts with neural circuits, and generate predictions about the resultant behavior. Here we address the recent observation that the physiological and behavioral effects of transcranial direct current stimulation (tDCS) might be non-linear with regards to stimulation intensity or duration. We use in silico neurostimulation of an established, biophysically informed neural network attractor model that generates simple behavioural choices, and thus allows for assessing the impact of stimulation on both neural dynamics and behavior. We demonstrate that nonlinear effects of stimulation intensity on the accuracy and decision time of the model can arise from a limit on the integration rate of the network, nonlinear effects of stimulation on neural firing rates before the onset of the stimulus, and the inhibitory effect of hyperpolarizing stimulation on pyramidal neurons. We thus present a detailed modeling treatment of non-linear tDCS effects during a behavioral task, and provide detailed hypotheses about the neural causes that lead to observed nonlinear behavioral effects during stimulation. This framework can provide a blueprint for future work on the neural and behavioral consequences of NIBS in health and disease.
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Transcranial magnetic stimulation: Decomposing the processes underlying action preparation

Bestmann S, Duque J

The Neuroscientist

Preparing actions requires the operation of several cognitive control processes that influence the state of the motor system to ensure that the appropriate behavior is ultimately selected and executed. For example, some form of competition resolution ensures that the right action is chosen among alternatives, often in the presence of conflict; at the same time, impulse control ought to be deployed to prevent premature responses. Here we review how state-changes in the human motor system during action preparation can be studied through motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation over the contralateral primary motor cortex (M1). We discuss how the physiological fingerprints afforded by MEPs have helped to decompose some of the dynamic and effector specific influences on the motor system during action preparation. We focus on competition resolution, conflict and impulse control, as well as on the influence of higher cognitive decision–related variables. The selected examples demonstrate the usefulness of MEPs as physiological readouts for decomposing the influence of distinct, but often overlapping, control processes on the human motor system during action preparation.
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On the use of meta-analysis in neuromodulatory non-invasive brain stimulation

Nitsche M, Bikson M, Bestmann S

Brain Stimulation

In humans, non-invasive brain stimulation (NIBS) can modulate cortical excitability and activity. The buoyant use of this technique in basic and applied research requires further characterization of the basic mechanisms to divorce promising applications from those producing more heterogeneous outcomes. Here we outline some criteria and pitfalls for using published results to gain estimates about the effects of NIBS techniques through meta-analysis and related tools [...].
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Dissociable Effects of Physical Effort & Temporal Delay on reward devaluation

Klein-Flugge M, Kennerley SW, Saraiva AC, Penny WD, Bestmann S

PLoS Computational Biology; DOI: 10.1371/journal.pcbi.1004116

There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity.
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Dorsolateral-Ventromedial Prefrontal Cortex Interactions during Value-Guided Choice: A Function of Context or Difficulty?

Saraiva AS, Marshall L

journal of neuroscience (in press)

Adaptation to complex, dynamic environments 33 requires flexible, context-dependent valuation and choice. How does the brain manipulate value computations to maximise reward according to environmental context? Contemporary research into value-based decision-making has centred on regions of the prefrontal cortex, thought to constitute part of a frontostriatal decision network. One area of intense focus in human neuroscience is the ventromedial prefrontal cortex (vmPFC). fMRI studies have repeatedly demonstrated that human vmPFC activity correlates with the subjective reward value of a chosen option (Walton et al., 2015). Moreover, human lesion evidence suggests that the region plays a crucial role in value maximisation during choice (Camille et al., 2011). While single-unit vmPFC studies are scarce, macaque vmPFC neurons have recently been shown to signal the value of a chosen offer during a two-option gambling task (Strait et al., 2014)...
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Binding space and time through action

Binetti N, Hagura N, Fedipe C, Tomassini A, Walsh V, Bestmann S

Proceedings of the Royal Society B (in press)

Space and time are intimately coupled dimensions in the human brain. Several lines of evidence suggest that space and time are processed by a shared analogue magnitude system. It has been proposed that actions are instrumental in establishing this shared magnitude system. Here we provide evidence in support of this hypothesis, by showing that the interaction between space and time is enhanced when magnitude information is acquired through action. Participants observed increases or decreases in the height of a visual bar (spatial magnitude) while judging whether a simultaneously presented sequence of acoustic tones had accelerated or decelerated (temporal magnitude). In one condition (Action), participants directly controlled the changes in bar height with a hand grip device whereas in the other (No Action), changes in bar height were externally controlled but matched the spatial/temporal profile of the Action condition. The sign of changes in bar height biased the perceived rate of the tone sequences, where increases in bar height produced apparent increases in tone rate. This effect was amplified when the visual bar was actively controlled in the Action condition, and the strength of the interaction was scaled by the magnitude of the action. Subsequent experiments ruled out that this was simply explained by attentional factors, and additionally showed that a monotonic mapping is also required between grip force and bar height in order to bias the perception of the tones. These data provide support for an instrumental role of action in interfacing spatial and temporal quantities in the brain.
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The role of dopamine in motor flexibility

Bestmann S, Ruge D, Rothwell J, Galea JM.

Journal of Cognitive Neuroscience 2015 27:365-76

Humans carry out many daily tasks in a seemingly automatic fashion. However, when unexpected changes in the environment occur, we have the capacity to inhibit prepotent behavior and replace it with an alternative one. Such behavioral flexibility is a hallmark of executive functions. The neurotransmitter dopamine is known to be crucial for fast, efficient, and accurate cognitive flexibility. Despite the perceived similarities between cognitive and motor flexibility, less is known regarding the role of dopamine within the motor domain. Therefore, the aim of this study was to determine the role of dopamine in motor flexibility. In a double-blind, five-session, within-subject pharmacological experiment, human participants performed an RT task within a probabilistic context that was either predictable or unpredictable. The probabilistic nature of the predictable context resulted in prediction errors. This required participants to replace the prepotent or prepared action with an unprepared action (motor flexibility). The task was overlearned, and changes in context were explicitly instructed, thus controlling for contributions from other dopamine-related processes such as probabilistic or reversal learning and interactions with other types of uncertainty. We found that dopamine receptor blockade by high-dose haloperidol (D1/D2 dopamine receptors) impaired participants' ability to react to unexpected events occurring in a predictable context, which elicit large prediction errors and necessitate motor flexibility. This effect was not observed with selective D2 receptor blockade (sulpiride), with a general increase in tonic dopamine levels (levodopa), or during an unpredictable context, which evoked minimal prediction error. We propose that dopamine is vital in responding to low-level prediction errors about stimulus outcome that requires motor flexibility.
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The uses and interpretations of the motor-evoked potential for understanding behaviour

Bestmann S, Krakauer J

Experimental Brain Research

The motor-evoked potential (MEP) elicited in peripheral muscles by transcranial magnetic stimulation (TMS) over human motor cortex is one of the hallmark measures for non-invasive quantification of cortical and spinal excitability in cognitive and clinical neuroscience. In the present article, we distinguish three main uses for MEPs in studies of behaviour: for understanding execution and performance of actions, as markers of physiological change in the motor system, and as read-out of upstream processes influencing the motor system. Common to all three approaches is the assumption that different experimental manipulations act on the balance of excitatory and inhibitory pre-synaptic (inter)neurons at the stimulation site; this in turn contributes to levels of (post-synaptic) excitability of cortico-spinal output projections, which ultimately determines the size of MEPs recorded from peripheral muscles. We discuss the types of inference one can draw from human MEP measures given that the detailed physiological underpinnings of MEPs elicited by TMS are complex and remain incompletely understood. Awareness of the different mechanistic assumptions underlying different uses of MEPs can help inform both study design and interpretation of results obtained from human MEP studies of behaviour.
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Understanding the behavioural consequences of non-invasive brain stimulation

Bestmann S, de Berker AO, Bonaiuto J

Trends in Cognitive Sciences 2015 19:13-20.

Transcranial electrical stimulation (tES) influences neural activity in a way that can elicit behavioural change, but may also improve high-level cognition or ameliorate symptoms in neuropsychiatric disorders. However, the current fervour for tES contrasts with the paucity of mechanistically detailed models of how stimulation causes behavioural change. Here we challenge the plausibility of several common assumptions and interpretations of tES, and discuss how to bridge the ravines separating our understanding of the behavioural and neural consequences of tES. We argue that rational application of tES should occur in tandem with computational neurostimulation and appropriate physiological and behavioural assays. This will help to appreciate the limitations of tES and generate testable predictions of how tES expresses its effects on behaviour.
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A novel coil array for combined TMS/fMRI experiments at 3 T

Navarro de Lara, Windischberger, Kuehne, Sieg, Josephs, Bestmann, Weiskopf, Strasser, Moser, Laistler

Magnetic Resonance in Medicine

Purpose: To overcome current limitations in combined transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) studies by employing a dedicated coil array design for 3 Tesla. Methods: The state-of-the-art setup for concurrent TMS/fMRI is to use a large birdcage head coil, with the TMS between the subject’s head and the MR coil. This setup has drawbacks in sensitivity, positioning and available imaging techniques. Here, an ultra-slim 7-channel receive-only coil array for 3T, which can be placed between the subject’s head and the TMS, is presented. Interactions between the devices are investigated and the performance of the new setup is evaluated in comparison to the state-of-the-art. Results: MR sensitivity obtained at the depth of the TMS stimulation is increased by a factor of five. Parallel imaging with an acceleration factor of 2 is feasible with low g-factors. Possible interactions between TMS and the novel hardware were investigated and were found negligible. Conclusion: The novel coil array is safe, strongly improves the sensitivity of fMRI measurements in concurrent TMS/fMRI experiments, enables parallel imaging, and allows for flexible positioning of the TMS on the head, while, due to its ultra-slim design, ensuring efficient TMS stimulation.
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A Setup for Administering TMS to Medial and Lateral Cortical Areas During Whole-Brain fMRI Recording

de Weijer AD, Sommer IE, Bakker EJ, Bloemendaal M, Bakker CJ, Klomp DW, Bestmann S, Neggers SF.

J Clin Neurophysiol 2015 31:474-87

Stimulating brain areas with transcranial magnetic stimulation (TMS) while concurrently and noninvasively recording brain activity changes through functional MRI enables a new range of investigations about causal interregional interactions in the human brain. However, standard head-coil arrangements for current methods for concurrent TMS-functional MRI somewhat restrict the cortical brain regions that can be targeted with TMS because space in typical MR head coils is limited. Another limitation for concurrent TMS-functional MRI approaches concerns the estimation of the precise stimulation site, which can limit the interpretation of the activity changes induced by TMS and increase the variability of the stimulation effects. Here, we present a novel approach using flexible MR receiver coils, allowing for stimulation of a large part of the cortex including more lateral areas. Furthermore, we present a fast and economical method to determine the precise location of the stimulation coil during scanning. This point-based registration method can accurately compute, during scanning, where TMS pulses are delivered. We validated this approach by stimulating medial (M1) and more lateral (dorsal part of the supramarginal gyrus) brain areas concurrently with functional MRI. Activation close to but not directly at the stimulated location and in distal areas connected to the targeted site was observed. This study provides a proof of concept that TMS of medial and lateral brain areas is feasible without significantly compromising brain coverage and that one can precisely determine the exact coil location inside the bore to verify targeting of brain areas.
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Discrimination of cortical laminae using MEG.

Troebinger L, Lopez JD, Lutti A, Bestmann S, Barnes G

Neuroimage doi: 10.1016/j.neuroimage.2014.07.015.

Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2mm translation and 2° rotation at SNR>11dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2013) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm and show that it is possible to discriminate between these cortical layer models in real data.
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Journal Club: Possible role of the basal ganglia in poor reward sensitivity and apathy after stroke.

Quattrocchi G, Bestmann S

Neurology 82:e171-3

Comment on "Poor reward sensitivity and apathy after stroke: implication of basal ganglia. [Neurology. 2013]"
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High precision anatomy for MEG

Troebinger L, Lopez JD, Lutti A, Bradbury D, Bestmann S, Barnes G

Neuroimage 2014 86:583-591

Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1mm. Estimates of relative co-registration error were <1.5mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG
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Emotional valence and contextual affordances flexibly shape approach-avoidance movements

Saraiva AC, Schuur F, Bestmann S

Frontiers Psychol. 2013 4:933

Behavior is influenced by the emotional content-or valence-of stimuli in our environment. Positive stimuli facilitate approach, whereas negative stimuli facilitate defensive actions such as avoidance (flight) and attack (fight). Facilitation of approach or avoidance movements may also be influenced by whether it is the self that moves relative to a stimulus (self-reference) or the stimulus that moves relative to the self (object-reference), adding flexibility and context-dependence to behavior. Alternatively, facilitation of approach avoidance movements may happen in a pre-defined and muscle-specific way, whereby arm flexion is faster to approach positive (e.g., flexing the arm brings a stimulus closer) and arm extension faster to avoid negative stimuli (e.g., extending the arm moves the stimulus away). While this allows for relatively fast responses, it may compromise the flexibility offered by contextual influences. Here we asked under which conditions approach-avoidance actions are influenced by contextual factors (i.e., reference-frame). We manipulated the reference-frame in which actions occurred by asking participants to move a symbolic manikin (representing the self) toward or away from a positive or negative stimulus, and move a stimulus toward or away from the manikin. We also controlled for the type of movements used to approach or avoid in each reference. We show that the reference-frame influences approach-avoidance actions to emotional stimuli, but additionally we find muscle-specificity for negative stimuli in self-reference contexts. We speculate this muscle-specificity may be a fast and adaptive response to threatening stimuli. Our results confirm that approach-avoidance behavior is flexible and reference-frame dependent, but can be muscle-specific depending on the context and valence of the stimulus. Reference-frame and stimulus-evaluation are key factors in guiding approach-avoidance behavior toward emotional stimuli in our environment.
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Predicting the behavioral impact of transcranial direct current stimulation: issues and limitations

de Berker AO, Bikson M, Bestmann S

Frontiers Human Neuroscience 2013 7:613

The transcranial application of weak currents to the human brain has enjoyed a decade of widespread use, providing a simple and powerful tool for non-invasively altering human brain function. However, our understanding of current delivery and its impact upon neural circuitry leaves much to be desired. We argue that the credibility of conclusions drawn with transcranial direct current stimulation (tDCS) is contingent upon realistic explanations of how tDCS works, and that our present understanding of tDCS limits the technique's use to localize function in the human brain. We outline two central issues where progress is required: the localization of currents, and predicting their functional consequence. We encourage experimenters to eschew simplistic explanations of mechanisms of transcranial current stimulation. We suggest the use of individualized current modeling, together with computational neurostimulation to inform mechanistic frameworks in which to interpret the physiological impact of tDCS. We hope that through mechanistically richer descriptions of current flow and action, insight into the biological processes by which transcranial currents influence behavior can be gained, leading to more effective stimulation protocols and empowering conclusions drawn with tDCS
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Neuroscience: transcranial devices are not playthings

Bikson M, Bestmann S, Edwards D

Nature 2013 501:167

Controlled investigation of transcranial direct-current stimulation (tDCS) for treating neuropsychiatric disorders or for neurorehabilitation should not be confused with improvised devices or practices that apply electricity to the brain without reference to established protocols (see Nature 498, 271–272; 2013). Unorthodox technologies and applications must not be allowed to distort the long-term validation of tDCS. Experimentation outside established and tested norms may put subjects at risk. In tDCS, the delivered dose of electrical brain stimulation (defined by the waveform and intensity applied) and the electrode size, number and position are all crucial. Safe and effective dose ranges have been established in clinical trials. Patients receiving tDCS do so in a controlled environment, under guidance from institutional ethics review boards and with strict criteria for patient inclusion. Meddling with the tDCS dose is potentially as dangerous as tampering with a drug's chemical composition. Painstaking efforts by researchers to understand the risks and benefits of tDCS should never be interpreted as encouraging such practices
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Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future

Bestmann, S., Feredoes, E.

Ann N Y Acad Sci. 2013 Aug;1296:11-30

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition.
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Failure of explicit movement control in patients with functional motor symptoms

Pareés, I., Kassavetis, P., Saifee, T. A., Sadnicka, A., Davare, M., Bhatia, K. P., Rothwell, J. C., Bestmann, S., Edwards, M. J.

Mov. Disord., 2013 Apr;28(4):517-23

Functional neurological symptoms are one of the most common conditions observed in neurological practice, but understanding of their underlying neurobiology is poor. Historic psychological models, based on the concept of conversion of emotional trauma into physical symptoms, have not been implemented neurobiologically, and are not generally supported by epidemiological studies. In contrast, there are robust clinical procedures that positively distinguish between organic and functional motor signs that rely primarily on distracting attention away from movement or accessing it covertly. We aimed to investigate the neurobiological principles underpinning these techniques and implications for understanding functional symptoms. We assessed 11 patients with functional motor symptoms and 11 healthy controls in three experimental set-ups, where voluntary movements were made either with full explicit control or could additionally be influenced automatically by factors of which participants were much less aware (one-back reaching, visuomotor transformation, and precued reaction time with variable predictive value of the precue). Patients specifically failed in those tasks where preplanning of movement could occur and under conditions of increasing certainty regarding the movement to be performed. However, they implicitly learned to adapt to a visuomotor transformation as well as healthy controls. We propose that when the movement to be performed can be preplanned or is highly predicted, patients with functional motor symptoms shift to an explicit attentive mode of processing that impairs kinematics of movement control, but movement becomes normal when such processes cannot be employed (e.g., during unexpected movement or implicit motor adaptation).
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Muscle and Timing-specific Functional Connectivity between the Dorsolateral Prefrontal Cortex and the Primary Motor Cortex

Hasan, A., Galea, J. M., Casula, E. P., Falkai, P., Bestmann, S., Rothwell, J. C.

J Cogn Neurosci., 2013 Apr;25(4):558-70

The pFC has a crucial role in cognitive control, executive function, and sensory processing. Functional imaging, neurophysiological, and animal studies provide evidence for a functional connectivity between the dorsolateral pFC (DLPFC) and the primary motor cortex (M1) during free choice but not instructed choice selection tasks. In this study, twin coil, neuronavigated TMS was used to examine the precise timing of the functional interaction between human left DLPFC and ipsilateral M1 during the execution of a free/specified choice selection task involving the digits of the right hand. In a thumb muscle that was not involved in the task, a conditioning pulse to the left DLPFC enhanced the excitability of the ipsilateral M1 during free selection more than specified selection 100 msec after presentation of the cue; the opposite effect was seen at 75 msec. However, the difference between free and externally specified conditions disappeared when a task-specific muscle was investigated. In this case, the influence from DLPFC was dominated by task involvement rather than mode of selection, suggesting that other processes related to movement execution were also operating. Finally, we show that the effects were spatially specific because they were absent when an adjacent area of DLPFC was stimulated. These results reveal temporally and spatially selective interactions between BA 46 and M1 that are both task and muscle specific.
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Variability of human corticospinal excitability tracks the state of action preparation

Klein-Flügge, M. C., Nobbs, D., Pitcher, J. B., Bestmann, S.

J Neurosci. 2013 Mar 27;33(13):5564-72

Task-evoked trial-by-trial variability is a ubiquitous property of neural responses, yet its functional role remains largely unclear. Recent work in nonhuman primates shows that the temporal structure of neural variability in several brain regions is task-related. For example, trial-by-trial variability in premotor cortex tracks motor preparation with increasingly consistent firing rates and thus a decline in variability before movement onset. However, whether noninvasive measures of the variability of population activity available from humans can similarly track the preparation of actions remains unknown. We tested this by using single-pulse transcranial magnetic stimulation (TMS) over primary motor cortex (M1) to measure corticospinal excitability (CSE) at different times during action preparation. First, we established the basic properties of intrinsic CSE variability at rest. Then, during the task, responses (left or right button presses) were either directly instructed (forced choice) or resulted from a value decision (choice). Before movement onset, we observed a temporally specific task-related decline in CSE variability contralateral to the responding hand. This decline was stronger in fast-response compared with slow-response trials, consistent with data in nonhuman primates. For the nonresponding hand, CSE variability also decreased, but only in choice trials, and earlier compared with the responding hand, possibly reflecting choice-specific suppression of unselected actions. These findings suggest that human CSE variability measured by TMS over M1 tracks the state of motor preparation, and may reflect the optimization of preparatory population activity. This provides novel avenues in humans to assess the dynamics of action preparation but also more complex processes, such as choice-to-action transformations.
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Punishment-Induced Behavioral and Neurophysiological Variability Reveals Dopamine-Dependent Selection of Kinematic Movement Parameters

Galea, J. M., Ruge, D., Buijink, A., Bestmann, S., Rothwell, J. C.

J Neurosci. 2013 Feb 27;33(9):3981-8

Action selection describes the high-level process that selects between competing movements. In animals, behavioral variability is critical for the motor exploration required to select the action that optimizes reward and minimizes cost/punishment and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioral and neurophysiological variability on DA and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant's behavior but predetermined. Blocks highly biased toward punishment were associated with increased MA variability relative to blocks either with reward or without feedback. This increase in behavioral variability was positively correlated with neurophysiological variability, as measured by changes in corticospinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA antagonist, the variability associated with punishment diminished and the correlation between behavioral and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a predetermined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioral variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes.
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Left dorsal premotor cortex and supramarginal gyrus complement each other during rapid action reprogramming

Hartwigsen G, Bestmann S, Ward NS, Woerbel S, Mastroeni C, Granert O, Siebner HR.

Journal of Neuroscience 2012 32:16162-71

The ability to discard a prepared action plan in favor of an alternative action is critical when facing sudden environmental changes. We tested whether the functional contribution of left supramarginal gyrus (SMG) during action reprogramming depends on the functional integrity of left dorsal premotor cortex (PMd). Adopting a dual-site repetitive transcranial magnetic stimulation (rTMS) strategy, we first transiently disrupted PMd with "off-line" 1 Hz rTMS and then applied focal "on-line" rTMS to SMG while human subjects performed a spatially precued reaction time (RT) task. Effective on-line rTMS of SMG but not sham rTMS of SMG increased errors when subjects had to reprogram their action in response to an invalid precue regardless of the type of preceding off-line rTMS. This suggests that left SMG primarily contributes to the on-line updating of actions by suppressing invalidly prepared responses. On-line rTMS of SMG additionally increased RTs for correct responses in invalidly precued trials, but only after off-line rTMS of PMd. We infer that off-line rTMS caused an additional dysfunction of PMd, which increased the functional relevance of SMG for rapid activation of the correct response, and sensitized SMG to the disruptive effects of on-line rTMS. These results not only provide causal evidence that left PMd and SMG jointly contribute to action reprogramming, but also that the respective functional weight of these areas can be rapidly redistributed. This mechanism might constitute a generic feature of functional networks that allows for rapid functional compensation in response to focal dysfunctions
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Time-dependent changes in human corticospinal excitability reveal value-based competition for action during decision processing.

Klein-Flugge M, Bestmann S

Journal of Neuroscience 2012 32:8373-82

Our choices often require appropriate actions to obtain a preferred outcome, but the neural underpinnings that link decision making and action selection remain largely undetermined. Recent theories propose that action selection occurs simultaneously, i.e., parallel in time, with the decision process. Specifically, it is thought that action selection in motor regions originates from a competitive process that is gradually biased by evidence signals originating in other regions, such as those specialized in value computations. Biases reflecting the evaluation of choice options should thus emerge in the motor system before the decision process is complete. Using transcranial magnetic stimulation, we sought direct physiological evidence for this prediction by measuring changes in corticospinal excitability in human motor cortex during value-based decisions. We found that excitability for chosen versus unchosen actions distinguishes the forthcoming choice before completion of the decision process. Both excitability and reaction times varied as a function of the subjective value-difference between chosen and unchosen actions, consistent with this effect being value-driven. This relationship was not observed in the absence of a decision. Our data provide novel evidence in humans that internally generated value-based decisions influence the competition between action representations in motor cortex before the decision process is complete. This is incompatible with models of serial processing of stimulus, decision, and action
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Action reprogramming in Parkinson's disease: response to prediction error is modulated by levels of dopamine

Galea JM, Bestmann S, Beigi M, Jahanshahi M, Rothwell JC.

Journal of Neuroscience 32:542-50

Humans are able to use knowledge of previous events to estimate the probability of future actions. Consequently, an unexpected event will elicit a prediction error as the prepared action has to be replaced by an unprepared option in a process known as "action reprogramming" (AR). Here we show that people with Parkinson's disease (PD) have a dopamine-sensitive deficit in AR that is proportional to the size of the prediction error. Participants performed a probabilistic reaction time (RT) task in the context of either a predictable or unpredictable environment. For an overall predictable sequence, PD patients, on and off dopamine medication, and healthy controls showed similar improvements in RT. However, in the context of a generally predictable sequence, PD patients off medication were impaired in reacting to unexpected events that elicit large prediction errors and require AR. Critically, this deficit in AR was modulated by the prediction error associated with the upcoming event. The prolongation of RT was not observed during an overall unpredictable sequence, in which relatively unexpected events evoke little prediction error and the requirement for AR should be minimal, given the context. The data are compatible with recent theoretical accounts suggesting that levels of dopamine encode the reliability, i.e., precision, of sensory information. In this scheme, PD patients off medication have low dopamine levels and may therefore be less confident about incoming sensory information and more reliant on top-down predictions. Consequently, when these internal predictions are incorrect, PD patients take longer to respond appropriately to unexpected sensory information
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Dopamine, affordance and active inference

Friston KJ, Shiner T, FitzGerald T, Galea JM, Adams R, Brown H, Dolan RJ, Moran R, Stephan KE, Bestmann S.

PLoS Computational Biology 8:e1002327

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level
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