Switch-Independent Task Representations in Frontal and Parietal Cortex

Lasse S. Loose, David Wisniewski, Marco Rusconi, Thomas Goschke and John-Dylan Haynes
Journal of Neuroscience 16 August 2017, 37 (33) 8033-8042; DOI: https://doi.org/10.1523/JNEUROSCI.3656-16.2017

Alternating between two tasks is effortful and impairs performance. Previous fMRI studies have found increased activity in frontoparietal cortex when task switching is required. One possibility is that the additional control demands for switch trials are met by strengthening task representations in the human brain. Alternatively, on switch trials, the residual representation of the previous task might impede the buildup of a neural task representation. This would predict weaker task representations on switch trials, thus also explaining the performance costs. To test this, male and female participants were cued to perform one of two similar tasks, with the task being repeated or switched between successive trials. Multivoxel pattern analysis was used to test which regions encode the tasks and whether this encoding differs between switch and repeat trials. As expected, we found information about task representations in frontal and parietal cortex, but there was no difference in the decoding accuracy of task-related information between switch and repeat trials. Using cross-classification, we found that the frontoparietal cortex encodes tasks using a generalizable spatial pattern in switch and repeat trials. Therefore, task representations in frontal and parietal cortex are largely switch independent. We found no evidence that neural information about task representations in these regions can explain behavioral costs usually associated with task switching.


When Brain Beats Behavior: Neuroforecasting Crowdfunding Outcomes

Alexander Genevsky, Carolyn Yoon and Brian Knutson
The Journal of Neuroscience, 6 September 2017, 37(36):8625-8634

Although traditional economic and psychological theories imply that individual choice best scales to aggregate choice, primary components of choice reflected in neural activity may support even more generalizable forecasts. Crowdfunding represents a significant and growing platform for funding new and unique projects, causes, and products. To test whether neural activity could forecast market-level crowdfunding outcomes weeks later, 30 human subjects (14 female) decided whether to fund proposed projects described on an Internet crowdfunding website while undergoing scanning with functional magnetic resonance imaging. Although activity in both the nucleus accumbens (NAcc) and medial prefrontal cortex predicted individual choices to fund on a trial-to-trial basis in the neuroimaging sample, only NAcc activity generalized to forecast market funding outcomes weeks later on the Internet. Behavioral measures from the neuroimaging sample, however, did not forecast market funding outcomes. This pattern of associations was replicated in a second study. These findings demonstrate that a subset of the neural predictors of individual choice can generalize to forecast market-level crowdfunding outcomes—even better than choice itself.


Ventromedial Prefrontal Cortex Encodes a Latent Estimate of Cumulative Reward

Keno Juechems, Jan Balaguer, Maria Ruz, Christopher Summerfield
Neuron, Volume 93, Issue 3, p705–714.e4, 8 February 2017

Humans and other animals accumulate resources, or wealth, by making successive risky decisions. If and how risk attitudes vary with wealth remains an open question. Here humans accumulated reward by accepting or rejecting successive monetary gambles within arbitrarily defined temporal contexts. Risk preferences changed substantially toward risk aversion as reward accumulated within a context, and blood oxygen level dependent (BOLD) signals in the ventromedial prefrontal cortex (PFC) tracked the latent growth of cumulative economic outcomes. Risky behavior was captured by a computational model in which reward prompts an adaptive update to the function that links utilities to choices. These findings can be understood if humans have evolved economic decision policies that fail to maximize overall expected value but reduce variance in cumulative outcomes, thereby ensuring that resources remain above a critical survival threshold.


Suppression of Ventral Hippocampal Output Impairs Integrated Orbitofrontal Encoding of Task Structure

Andrew M. Wikenheiser, Yasmin Marrero-Garcia, Geoffrey Schoenbaum
Neuron, Volume 95, Issue 5, p1197–1207.e3, 30 August 2017

The hippocampus and orbitofrontal cortex (OFC) both make important contributions to decision making and other cognitive processes. However, despite anatomical links between the two, few studies have tested the importance of hippocampal–OFC interactions. Here, we recorded OFC neurons in rats performing a decision making task while suppressing activity in a key hippocampal output region, the ventral subiculum. OFC neurons encoded information about expected outcomes and rats’ responses. With hippocampal output suppressed, rats were slower to adapt to changes in reward contingency, and OFC encoding of response information was strongly attenuated. In addition, ventral subiculum inactivation prevented OFC neurons from integrating information about features of outcomes to form holistic representations of the outcomes available in specific trial blocks. These data suggest that the hippocampus contributes to OFC encoding of both concrete, low-level features of expected outcomes, and abstract, inferred properties of the structure of the world, such as task state.


Specialized Representations of Value in the Orbital and Ventrolateral Prefrontal Cortex: Desirability versus Availability of Outcomes

Peter H. Rudebeck, Richard C. Saunders, Dawn A. Lundgren, Elisabeth A. Murray
Neuron, Volume 95, Issue 5, p1208–1220.e5, 30 August 2017

Advantageous foraging choices benefit from an estimation of two aspects of a resource’s value: its current desirability and availability. Both orbitofrontal and ventrolateral prefrontal areas contribute to updating these valuations, but their precise roles remain unclear. To explore their specializations, we trained macaque monkeys on two tasks: one required updating representations of a predicted outcome’s desirability, as adjusted by selective satiation, and the other required updating representations of an outcome’s availability, as indexed by its probability. We evaluated performance on both tasks in three groups of monkeys: unoperated controls and those with selective, fiber-sparing lesions of either the OFC or VLPFC. Representations that depend on the VLPFC but not the OFC play a necessary role in choices based on outcome availability; in contrast, representations that depend on the OFC but not the VLPFC play a necessary role in choices based on outcome desirability.


Learning Predictive Statistics: Strategies and Brain Mechanisms

Rui Wang, Yuan Shen, Peter Tino, Andrew E. Welchman and Zoe Kourtzi
Journal of Neuroscience 30 August 2017, 37 (35) 8412-8427; DOI: https://doi.org/10.1523/JNEUROSCI.0144-17.2017

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory–motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions.


Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility

Alberto Del Arco, Junchol Park, Jesse Wood, Yunbok Kim and Bita Moghaddam
Journal of Neuroscience 30 August 2017, 37 (35) 8363-8373; DOI: https://doi.org/10.1523/JNEUROSCI.0450-17.2017

The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action–outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action–outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action.


Basolateral Amygdala to Orbitofrontal Cortex Projections Enable Cue-Triggered Reward Expectations

Nina T. Lichtenberg, Zachary T. Pennington, Sandra M. Holley, Venuz Y. Greenfield, Carlos Cepeda, Michael S. Levine and Kate M. Wassum
Journal of Neuroscience 30 August 2017, 37 (35) 8374-8384; DOI: https://doi.org/10.1523/JNEUROSCI.0486-17.2017

To make an appropriate decision, one must anticipate potential future rewarding events, even when they are not readily observable. These expectations are generated by using observable information (e.g., stimuli or available actions) to retrieve often quite detailed memories of available rewards. The basolateral amygdala (BLA) and orbitofrontal cortex (OFC) are two reciprocally connected key nodes in the circuitry supporting such outcome-guided behaviors. But there is much unknown about the contribution of this circuit to decision making, and almost nothing known about the whether any contribution is via direct, monosynaptic projections, or the direction of information transfer. Therefore, here we used designer receptor-mediated inactivation of OFC→BLA or BLA→OFC projections to evaluate their respective contributions to outcome-guided behaviors in rats. Inactivation of BLA terminals in the OFC, but not OFC terminals in the BLA, disrupted the selective motivating influence of cue-triggered reward representations over reward-seeking decisions as assayed by Pavlovian-to-instrumental transfer. BLA→OFC projections were also required when a cued reward representation was used to modify Pavlovian conditional goal-approach responses according to the reward's current value. These projections were not necessary when actions were guided by reward expectations generated based on learned action-reward contingencies, or when rewards themselves, rather than stored memories, directed action. These data demonstrate that BLA→OFC projections enable the cue-triggered reward expectations that can motivate the execution of specific action plans and allow adaptive conditional responding.


Midbrain Dopamine Neurons Signal Belief in Choice Accuracy during a Perceptual Decision

Lak A, Nomoto K, Keramati M, Sakagami M, Kepecs A.
Curr Biol. 2017 Mar 20;27(6):821-832.

Central to the organization of behavior is the ability to predict the values of outcomes to guide choices. The accuracy of such predictions is honed by a teaching signal that indicates how incorrect a prediction was ("reward prediction error," RPE). In several reinforcement learning contexts, such as Pavlovian conditioning and decisions guided by reward history, this RPE signal is provided by midbrain dopamine neurons. In many situations, however, the stimuli predictive of outcomes are perceptually ambiguous. Perceptual uncertainty is known to influence choices, but it has been unclear whether or how dopamine neurons factor it into their teaching signal. To cope with uncertainty, we extended a reinforcement learning model with a belief state about the perceptually ambiguous stimulus; this model generates an estimate of the probability of choice correctness, termed decision confidence. We show that dopamine responses in monkeys performing a perceptually ambiguous decision task comply with the model's predictions. Consequently, dopamine responses did not simply reflect a stimulus' average expected reward value but were predictive of the trial-to-trial fluctuations in perceptual accuracy. These confidence-dependent dopamine responses emerged prior to monkeys' choice initiation, raising the possibility that dopamine impacts impending decisions, in addition to encoding a post-decision teaching signal. Finally, by manipulating reward size, we found that dopamine neurons reflect both the upcoming reward size and the confidence in achieving it. Together, our results show that dopamine responses convey teaching signals that are also appropriate for perceptual decisions.


Neural Basis for Economic Saving Strategies in Human Amygdala-Prefrontal Reward Circuits

Zangemeister L, Grabenhorst F, Schultz W.
Curr Biol. 2016 Nov 21;26(22):3004-3013.

Economic saving is an elaborate behavior in which the goal of a reward in the future directs planning and decision-making in the present. Here, we measured neural activity while subjects formed simple economic saving strategies to accumulate rewards and then executed their strategies through choice sequences of self-defined lengths. Before the initiation of a choice sequence, prospective activations in the amygdala predicted subjects' internal saving plans and their value up to two minutes before a saving goal was achieved. The valuation component of this planning activity persisted during execution of the saving strategy and predicted subjects' economic behavior across different tasks and testing days. Functionally coupled amygdala and prefrontal cortex activities encoded distinct planning components that signaled the transition from saving strategy formation to execution and reflected individual differences in saving behavior. Our findings identify candidate neural mechanisms for economic saving in amygdala and prefrontal cortex and suggest a novel planning function for the human amygdala in directing strategic behavior toward self-determined future rewards.


Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments

Leong YC, Radulescu A, Daniel R, DeWoskin V, Niv Y.
Neuron. 2017 Jan 18;93(2):451-463.

Little is known about the relationship between attention and learning during decision making. Using eye tracking and multivariate pattern analysis of fMRI data, we measured participants' dimensional attention as they performed a trial-and-error learning task in which only one of three stimulus dimensions was relevant for reward at any given time. Analysis of participants' choices revealed that attention biased both value computation during choice and value update during learning. Value signals in the ventromedial prefrontal cortex and prediction errors in the striatum were similarly biased by attention. In turn, participants' focus of attention was dynamically modulated by ongoing learning. Attentional switches across dimensions correlated with activity in a frontoparietal attention network, which showed enhanced connectivity with the ventromedial prefrontal cortex between switches. Our results suggest a bidirectional interaction between attention and learning: attention constrains learning to relevant dimensions of the environment, while we learn what to attend to via trial and error.


Ravens parallel great apes in flexible planning for tool-use and bartering

Can Kabadayi, Mathias Osvath
Science  14 Jul 2017: Vol. 357, Issue 6347, pp. 202-204
DOI: 10.1126/science.aam8138

The ability to flexibly plan for events outside of the current sensory scope is at the core of being human and is crucial to our everyday lives and society. Studies on apes have shaped a belief that this ability evolved within the hominid lineage. Corvids, however, have shown evidence of planning their food hoarding, although this has been suggested to reflect a specific caching adaptation rather than domain-general planning. Here, we show that ravens plan for events unrelated to caching—tool-use and bartering—with delays of up to 17 hours, exert self-control, and consider temporal distance to future events. Their performance parallels that seen in apes and suggests that planning evolved independently in corvids, which opens new avenues for the study of cognitive evolution.


Two areas for familiar face recognition in the primate brain

Sofia M. Landi, Winrich A. Freiwald
Science  11 Aug 2017: Vol. 357, Issue 6351, pp. 591-595

Familiarity alters face recognition: Familiar faces are recognized more accurately than unfamiliar ones and under difficult viewing conditions when unfamiliar face recognition fails. The neural basis for this fundamental difference remains unknown. Using whole-brain functional magnetic resonance imaging, we found that personally familiar faces engage the macaque face-processing network more than unfamiliar faces. Familiar faces also recruited two hitherto unknown face areas at anatomically conserved locations within the perirhinal cortex and the temporal pole. These two areas, but not the core face-processing network, responded to familiar faces emerging from a blur with a characteristic nonlinear surge, akin to the abruptness of familiar face recognition. In contrast, responses to unfamiliar faces and objects remained linear. Thus, two temporal lobe areas extend the core face-processing network into a familiar face-recognition system.


Pavlovian conditioning–induced hallucinations result from overweighting of perceptual priors

A. R. Powers, C. Mathys, P. R. Corlett
Science  11 Aug 2017: Vol. 357, Issue 6351, pp. 596-600

Some people hear voices that others do not, but only some of those people seek treatment. Using a Pavlovian learning task, we induced conditioned hallucinations in four groups of people who differed orthogonally in their voice-hearing and treatment-seeking statuses. People who hear voices were significantly more susceptible to the effect. Using functional neuroimaging and computational modeling of perception, we identified processes that differentiated voice-hearers from non–voice-hearers and treatment-seekers from non–treatment-seekers and characterized a brain circuit that mediated the conditioned hallucinations. These data demonstrate the profound and sometimes pathological impact of top-down cognitive processes on perception and may represent an objective means to discern people with a need for treatment from those without.


Hierarchically Organized Medial Frontal Cortex-Basal Ganglia Loops Selectively Control Task- and Response-Selection

Franziska M. Korb, Jiefeng Jiang, Joseph A. King and Tobias Egner
Journal of Neuroscience 16 August 2017, 37 (33) 7893-7905; DOI: https://doi.org/10.1523/JNEUROSCI.3289-16.2017

Adaptive behavior requires context-sensitive configuration of task-sets that specify time-varying stimulus–response mappings. Intriguingly, response time costs associated with changing task-sets and motor responses are known to be strongly interactive: switch costs at the task level are small in the presence of a response-switch but large when accompanied by a response-repetition, and vice versa for response-switch costs. The reasons behind this well known interdependence between task- and response-level control processes are currently not well understood. Here, we formalized and tested a model assuming a hierarchical organization of superordinate task-set and subordinate response-set selection processes to account for this effect. The model was found to successfully explain the full range of behavioral task- and response-switch costs across first and second order trial transitions. Using functional magnetic resonance imaging (fMRI) in healthy humans, we then characterized the neural circuitry mediating these effects. We found that presupplementary motor area (preSMA) activity tracked task-set control costs, SMA activity tracked response-set control costs, and basal ganglia (BG) activity mirrored the interaction between task- and response-set regulation processes that characterized participants' response times. A subsequent fMRI-guided transcranial magnetic stimulation experiment confirmed dissociable roles of the preSMA and SMA in determining response costs. Together, these data provide evidence for a hierarchical organization of posterior medial frontal cortex and its interaction with the BG, where a superordinate preSMA-BG loop establishes task-set selection, which imposes a (unidirectional) constraint on a subordinate SMA-BG loop that determines response-selection, resulting in the characteristic interdependence in task- and response-switch costs in behavior.


Crowdsourcing Samples in Cognitive Science

Neil Stewart, Jesse Chandler, and Gabriele Paolacci
Trends in Cognitive Sciences, Available online 10 August 2017

Crowdsourcing data collection from research participants recruited from online labor markets is now common in cognitive science. We review who is in the crowd and who can be reached by the average laboratory. We discuss reproducibility and review some recent methodological innovations for online experiments. We consider the design of research studies and arising ethical issues. We review how to code experiments for the web, what is known about video and audio presentation, and the measurement of reaction times. We close with comments about the high levels of experience of many participants and an emerging tragedy of the commons.


Conversion of object identity to object-general semantic value in the primate temporal cortex

Keita Tamura , Masaki Takeda, Rieko Setsuie, Tadashi Tsubota, Toshiyuki Hirabayashi, Kentaro Miyamoto, Yasushi Miyashita
Science  18 Aug 2017: Vol. 357, Issue 6352, pp. 687-692

At the final stage of the ventral visual stream, perirhinal neurons encode the identity of memorized objects through learning. However, it remains elusive whether and how object percepts alone, or concomitantly a nonphysical attribute of the objects (“learned”), are decoded from perirhinal activities. By combining monkey psychophysics with optogenetic and electrical stimulations, we found a focal spot of memory neurons where both stimulations led monkeys to preferentially judge presented objects as “already seen.” In an adjacent fringe area, where neurons did not exhibit selective responses to the learned objects, electrical stimulation induced the opposite behavioral bias toward “never seen before,” whereas optogenetic stimulation still induced bias toward “already seen.” These results suggest that mnemonic judgment of objects emerges via the decoding of their nonphysical attributes encoded by perirhinal neurons.


Piercing of Consciousness as a Threshold-Crossing Operation

Yul H.R. Kang, Frederike H. Petzschner, Daniel M. Wolpert, Michael N. Shadlen
Current Biology, Volume 27, Issue 15, p2285–2295.e6, 7 August 2017

Many decisions arise through an accumulation of evidence to a terminating threshold. The process, termed bounded evidence accumulation (or drift diffusion), provides a unified account of decision speed and accuracy, and it is supported by neurophysiology in human and animal models. In many situations, a decision maker may not communicate a decision immediately and yet feel that at some point she had made up her mind. We hypothesized that this occurs when an accumulation of evidence reaches a termination threshold, registered, subjectively, as an “aha” moment. We asked human participants to make perceptual decisions about the net direction of dynamic random dot motion. The difficulty and viewing duration were controlled by the experimenter. After indicating their choice, participants adjusted the setting of a clock to the moment they felt they had reached a decision. The subjective decision times (tSDs) were faster on trials with stronger (easier) motion, and they were well fit by a bounded drift-diffusion model. The fits to the tSDs alone furnished parameters that fully predicted the choices (accuracy) of four of the five participants. The quality of the prediction provides compelling evidence that these subjective reports correspond to the terminating process of a decision rather than a post hoc inference or arbitrary report. Thus, conscious awareness of having reached a decision appears to arise when the brain’s representation of accumulated evidence reaches a threshold or bound. We propose that such a mechanism might play a more widespread role in the “piercing of consciousness” by non-conscious thought processes.


Selective overweighting of larger magnitudes during noisy numerical comparison

Bernhard Spitzer, Leonhard Waschke & Christopher Summerfield
Nature Human Behaviour 1, Article number: 0145 (2017)

Humans are often required to compare average magnitudes in numerical data; for example, when comparing product prices on two rival consumer websites. However, the neural and computational mechanisms by which numbers are weighted, integrated and compared during categorical decisions are largely unknown1,2,3,4,5. Here, we show a systematic deviation from ‘optimality’ in both visual and auditory tasks requiring averaging of symbolic numbers. Participants comparing numbers drawn from two categories selectively overweighted larger numbers when making a decision, and larger numbers evoked disproportionately stronger decision-related neural signals over the parietal cortex. A representational similarity analysis6 showed that neural (dis)similarity in patterns of electroencephalogram activity reflected numerical distance, but that encoding of number in neural data was systematically distorted in a way predicted by the behavioural weighting profiles, with greater neural distance between adjacent larger numbers. Finally, using a simple computational model, we show that although it is suboptimal for a lossless observer, this selective overweighting policy paradoxically maximizes expected accuracy by making decisions more robust to noise arising during approximate numerical integration2. In other words, although selective overweighting discards decision information, it can be beneficial for limited-capacity agents engaging in rapid numerical averaging.


Functional dissection of signal and noise in MT and LIP during decision-making

Jacob L Yates, Il Memming Park, Leor N Katz, Jonathan W Pillow & Alexander C Huk
Nature Neuroscience (2017) doi:10.1038/nn.4611

During perceptual decision-making, responses in the middle temporal (MT) and lateral intraparietal (LIP) areas appear to map onto theoretically defined quantities, with MT representing instantaneous motion evidence and LIP reflecting the accumulated evidence. However, several aspects of the transformation between the two areas have not been empirically tested. We therefore performed multistage systems identification analyses of the simultaneous activity of MT and LIP during individual decisions. We found that monkeys based their choices on evidence presented in early epochs of the motion stimulus and that substantial early weighting of motion was present in MT responses. LIP responses recapitulated MT early weighting and contained a choice-dependent buildup that was distinguishable from motion integration. Furthermore, trial-by-trial variability in LIP did not depend on MT activity. These results identify important deviations from idealizations of MT and LIP and motivate inquiry into sensorimotor computations that may intervene between MT and LIP.


Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment

Anthony Burgos-Robles, Eyal Y Kimchi, Ehsan M Izadmehr, Mary Jane Porzenheim, William A Ramos-Guasp, Edward H Nieh, Ada C Felix-Ortiz, Praneeth Namburi, Christopher A Leppla, Kara N Presbrey, Kavitha K Anandalingam, Pablo A Pagan-Rivera, Melodi Anahtar, Anna Beyeler & Kay M Tye
Nature Neuroscience 20, 824–835 (2017)

Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral nucleus of the amygdala (BLA) and prelimbic (PL) medial prefrontal cortex have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task wherein competing shock- and sucrose-predictive cues were simultaneously presented. The correlated firing primarily displayed a BLAright arrowPL directionality during the shock-associated cue. Furthermore, BLA neurons optogenetically identified as projecting to PL more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally photostimulation of the BLAright arrowPL projection increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. Therefore, the BLAright arrowPL circuit is critical in governing the selection of behavioral responses in the face of competing signals.


Manipulating fear associations via optogenetic modulation of amygdala inputs to prefrontal cortex

Oded Klavir, Matthias Prigge, Ayelet Sarel, Rony Paz & Ofer Yizhar
Nature Neuroscience 20, 836–844 (2017)

Fear-related disorders are thought to reflect strong and persistent fear memories. The basolateral amygdala (BLA) and the medial prefrontal cortex (mPFC) form strong reciprocal synaptic connections that play a key role in acquisition and extinction of fear memories. While synaptic contacts of BLA cells onto mPFC neurons are likely to play a crucial role in this process, the BLA connects with several additional nuclei within the fear circuit that could relay fear-associated information to the mPFC, and the contribution of direct monosynaptic BLA–mPFC inputs is not yet clear. Here we establish an optogenetic stimulation protocol that induces synaptic depression in BLA–mPFC synapses. In behaving mice, optogenetic high-frequency stimulation of BLA inputs to mPFC interfered with retention of cued associations, attenuated previously acquired cue-associated responses in mPFC neurons and facilitated extinction. Our findings demonstrate the contribution of BLA inputs to mPFC in forming and maintaining cued fear associations.


The neural correlates of dreaming

Francesca Siclari, Benjamin Baird, Lampros Perogamvros, Giulio Bernardi, Joshua J LaRocque, Brady Riedner, Melanie Boly, Bradley R Postle & Giulio Tononi
Nature Neuroscience 20, 872–878 (2017)

Consciousness never fades during waking. However, when awakened from sleep, we sometimes recall dreams and sometimes recall no experiences. Traditionally, dreaming has been identified with rapid eye-movement (REM) sleep, characterized by wake-like, globally 'activated', high-frequency electroencephalographic activity. However, dreaming also occurs in non-REM (NREM) sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density electroencephalography, we contrasted the presence and absence of dreaming in NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with local decreases in low-frequency activity in posterior cortical regions. High-frequency activity in these regions correlated with specific dream contents. Monitoring this posterior 'hot zone' in real time predicted whether an individual reported dreaming or the absence of dream experiences during NREM sleep, suggesting that it may constitute a core correlate of conscious experiences in sleep.


Dynamic hidden states underlying working-memory-guided behavior

Michael J Wolff, Janina Jochim, Elkan G Akyürek & Mark G Stokes
Nature Neuroscience 20, 864–871 (2017)

Recent theoretical models propose that working memory is mediated by rapid transitions in 'activity-silent' neural states (for example, short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-guided behavior and dissolve them equally fast to allow forgetting. We developed a perturbation approach to measure mnemonic hidden states in an electroencephalogram. By 'pinging' the brain during maintenance, we show that memory-item-specific information is decodable from the impulse response, even in the absence of attention and lingering delay activity. Moreover, hidden memories are remarkably flexible: an instruction cue that directs people to forget one item is sufficient to wipe the corresponding trace from the hidden state. In contrast, temporarily unattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-directed forgetting. Finally, the strength of hidden-state coding predicts the accuracy of working-memory-guided behavior, including memory precision.


Moral transgressions corrupt neural representations of value

Molly J Crockett, Jenifer Z Siegel, Zeb Kurth-Nelson, Peter Dayan & Raymond J Dolan
Nature Neuroscience 20, 879–885 (2017)

Moral systems universally prohibit harming others for personal gain. However, we know little about how such principles guide moral behavior. Using a task that assesses the financial cost participants ascribe to harming others versus themselves, we probed the relationship between moral behavior and neural representations of profit and pain. Most participants displayed moral preferences, placing a higher cost on harming others than themselves. Moral preferences correlated with neural responses to profit, where participants with stronger moral preferences had lower dorsal striatal responses to profit gained from harming others. Lateral prefrontal cortex encoded profit gained from harming others, but not self, and tracked the blameworthiness of harmful choices. Moral decisions also modulated functional connectivity between lateral prefrontal cortex and the profit-sensitive region of dorsal striatum. The findings suggest moral behavior in our task is linked to a neural devaluation of reward realized by a prefrontal modulation of striatal value representations.


Posterior Parietal Cortex Guides Visual Decisions in Rats

Angela M. Licata, Matthew T. Kaufman, David Raposo, Michael B. Ryan, John P. Sheppard and Anne K. Churchland
Journal of Neuroscience 13 April 2017, 37 (19) 4954-4966

Neurons in putative decision-making structures can reflect both sensory and decision signals, making their causal role in decisions unclear. Here, we tested whether rat posterior parietal cortex (PPC) is causal for processing visual sensory signals or instead for accumulating evidence for decision alternatives. We disrupted PPC activity optogenetically during decision making and compared effects on decisions guided by auditory versus visual evidence. Deficits were largely restricted to visual decisions. To further test for visual dominance in PPC, we evaluated electrophysiological responses after individual sensory events and observed much larger response modulation after visual stimuli than auditory stimuli. Finally, we measured trial-to-trial spike count variability during stimulus presentation and decision formation. Variability decreased sharply, suggesting that the network is stabilized by inputs, unlike what would be expected if sensory signals were locally accumulated. Our findings suggest that PPC plays a causal role in processing visual signals that are accumulated elsewhere.


Dissociation of Choice Formation and Choice-Correlated Activity in Macaque Visual Cortex

Robbe L.T. Goris, Corey M. Ziemba, Gabriel M. Stine, Eero P. Simoncelli and J. Anthony Movshon
Journal of Neuroscience 21 April 2017, 37 (20) 5195-5203;
DOI: https://doi.org/10.1523/JNEUROSCI.3331-16.2017

Responses of individual task-relevant sensory neurons can predict monkeys' trial-by-trial choices in perceptual decision-making tasks. Choice-correlated activity has been interpreted as evidence that the responses of these neurons are causally linked to perceptual judgments. To further test this hypothesis, we studied responses of orientation-selective neurons in V1 and V2 while two macaque monkeys performed a fine orientation discrimination task. Although both animals exhibited a high level of neuronal and behavioral sensitivity, only one exhibited choice-correlated activity. Surprisingly, this correlation was negative: when a neuron fired more vigorously, the animal was less likely to choose the orientation preferred by that neuron. Moreover, choice-correlated activity emerged late in the trial, earlier in V2 than in V1, and was correlated with anticipatory signals. Together, these results suggest that choice-correlated activity in task-relevant sensory neurons can reflect postdecision modulatory signals.


Effort-Based Reinforcement Processing and Functional Connectivity Underlying Amotivation in Medicated Patients with Depression and Schizophrenia

Ho Il Park, Boung Chul Lee, Jae-Jin Kim, Joong Il Kim and Min-Seung Koo
Journal of Neuroscience 10 March 2017, 2524-16; DOI: https://doi.org/10.1523/JNEUROSCI.2524-16.2017

Amotivation is a common phenotype of major depressive disorder and schizophrenia which are clinically distinct disorders. Effective treatment targets and strategies can be discovered by examining the dopaminergic reward network function underlying amotivation between these disorders. We conducted a functional MRI study in healthy human participants and medicated patients with depression and schizophrenia using an effort-based reinforcement task. We examined regional activations related to reward type (positive and negative reinforcement), effort level, and their composite value as well as resting-state functional connectivities within the meso-striatal-prefrontal pathway. We found that integrated reward and effort values of low effort-positive reinforcement and high effort-negative reinforcement were behaviorally anticipated and represented in the putamen and medial orbitofrontal cortex activities. Patients with schizophrenia and depression did not show anticipation-related and work-related reaction time reductions, respectively. Greater amotivation severity correlated with smaller work-related putamen activity changes according to reward type in schizophrenia and effort level in depression. Patients with schizophrenia showed feedback-related putamen hyperactivity of low effort compared to healthy controls and depressed patients. The strength of medial orbitofrontal-striatal functional connectivity predicted work-related reaction time reduction of high effort negative reinforcement in healthy controls and amotivation severity in both patients with schizophrenia and depression. Patients with depression showed deficient medial orbitofrontal-striatal functional connectivity compared to healthy controls and patients with schizophrenia. These results indicate that amotivations in depression and schizophrenia involve different pathophysiology in the prefrontal-striatal circuitry.


Opposite Effects of Recent History on Perception and Decision

Fritsche M, Mostert P, de Lange FP.
Curr Biol. 2017 Feb 20;27(4):590-595. doi: 10.1016/j.cub.2017.01.006.

Recent studies claim that visual perception of stimulus features, such as orientation, numerosity, and faces, is systematically biased toward visual input from the immediate past [1-3]. However, the extent to which these positive biases truly reflect changes in perception rather than changes in post-perceptual processes is unclear [4, 5]. In the current study we sought to disentangle perceptual and decisional biases in visual perception. We found that post-perceptual decisions about orientation were indeed systematically biased toward previous stimuli and this positive bias did not strongly depend on the spatial location of previous stimuli (replicating previous work [1]). In contrast, observers' perception was repelled away from previous stimuli, particularly when previous stimuli were presented at the same spatial location. This repulsive effect resembles the well-known negative tilt-aftereffect in orientation perception [6]. Moreover, we found that the magnitude of the positive decisional bias increased when a longer interval was imposed between perception and decision, suggesting a shift of working memory representations toward the recent history as a source of the decisional bias. We conclude that positive aftereffects on perceptual choice are likely introduced at a post-perceptual stage. Conversely, perception is negatively biased away from recent visual input. We speculate that these opposite effects on perception and post-perceptual decision may derive from the distinct goals of perception and decision-making processes: whereas perception may be optimized for detecting changes in the environment, decision processes may integrate over longer time periods to form stable representations.


Perceptual Decision Making in Rodents, Monkeys, and Humans

Hanks TD, Summerfield C.
Neuron. 2017 Jan 4;93(1):15-31. doi: 10.1016/j.neuron.2016.12.003.

Perceptual decision making is the process by which animals detect, discriminate, and categorize information from the senses. Over the past two decades, understanding how perceptual decisions are made has become a central theme in the neurosciences. Exceptional progress has been made by recording from single neurons in the cortex of the macaque monkey and using computational models from mathematical psychology to relate these neural data to behavior. More recently, however, the range of available techniques and paradigms has dramatically broadened, and researchers have begun to harness new approaches to explore how rodents and humans make perceptual decisions. The results have illustrated some striking convergences with findings from the monkey, but also raised new questions and provided new theoretical insights. In this review, we summarize key findings, and highlight open challenges, for understanding perceptual decision making in rodents, monkeys, and humans.


Mnemonic Training Reshapes Brain Networks to Support Superior Memory

Dresler M, Shirer WR, Konrad BN, Müller NC, Wagner IC, Fernández G, Czisch M, Greicius MD
Neuron. 2017 Mar 8;93(5):1227-1235.e6. doi: 10.1016/j.neuron.2017.02.003.

Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network organization of 23 of the world's most successful memory athletes and matched controls with fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that, in a group of naive controls, functional connectivity changes induced by 6 weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain's functional network organization to enable superior memory performance.


Effects of Medial Orbitofrontal Cortex Lesions on Self-Control in Intertemporal Choice

Peters J, D'Esposito M
Curr Biol. 2016 Oct 10;26(19):2625-2628. doi: 10.1016/j.cub.2016.07.035.

Many decisions involve a trade-off between the temporal proximity of a reward and its magnitude. A range of clinical conditions are associated with poor self-control during such intertemporal choices, such that smaller rewards that are received sooner are preferred over larger rewards that are received later to a greater extent [1, 2]. According to a prominent neural model of self-control [3-6], subjective reward values are represented in the medial orbitofrontal cortex (mOFC) at the time of choice [7-9]. Successful self-control in this model is then thought to depend on a modulation of these mOFC value representations via the lateral prefrontal cortex (lPFC) [3, 6]. Here we directly tested three key predictions of this model in patients with lesions to the mOFC (n = 9) and matched controls (n = 19). First, we show that mOFC lesions disrupt choice-free valuation ratings. This finding provides causal evidence for a role of the mOFC in reward valuation and contrasts with the effects of lPFC disruption [6]. Second, we show that mOFC damage indeed decreases self-control during intertemporal choice, replicating previous findings [10]. Third, extending these previous observations, we show that the effect of mOFC damage on intertemporal choice depends on the actual self-control demands of the task. Our findings thus provide causal evidence for a role of mOFC in reward valuation and are compatible with the idea that mOFC damage affects self-control specifically under conditions that might normally require a modulation of mOFC value representations, e.g., by the lPFC.


Reversed Procrastination by Focal Disruption of Medial Frontal Cortex

Jha A, Diehl B, Scott C, McEvoy AW, Nachev P.
Curr Biol. 2016 Nov 7;26(21):2893-2898. doi: 10.1016/j.cub.2016.08.016.

An enduring puzzle in the neuroscience of voluntary action is the origin of the remarkably wide dispersion of the reaction time distribution, an interval far greater than is explained by synaptic or signal transductive noise [1, 2]. That we are able to change our planned actions-a key criterion of volition [3]-so close to the time of their onset implies decision-making must reach deep into the execution of action itself [4-6]. It has been influentially suggested the reaction time distribution therefore reflects deliberate neural procrastination [7], giving alternative response tendencies sufficient time for fair competition in pursuing a decision threshold that determines which one is behaviorally manifest: a race model, where action selection and execution are closely interrelated [8-11]. Although the medial frontal cortex exhibits a sensitivity to reaction time on functional imaging that is consistent with such a mechanism [12-14], direct evidence from disruptive studies has hitherto been lacking. If movement-generating and movement-delaying neural substrates are closely co-localized here, a large-scale lesion will inevitably mask any acceleration, for the movement itself could be disrupted. Circumventing this problem, here we observed focal intracranial electrical disruption of the medial frontal wall in the context of the pre-surgical evaluation of two patients with epilepsy temporarily reversing such hypothesized procrastination. Effector-specific behavioral acceleration, time-locked to the period of electrical disruption, occurred exclusively at a specific locus at the ventral border of the pre-supplementary motor area. A cardinal prediction of race models of voluntary action is thereby substantiated in the human brain.


Dynamical Representation of Dominance Relationships in the Human Rostromedial Prefrontal Cortex

Ligneul R, Obeso I, Ruff CC, Dreher JC
Curr Biol. 2016 Dec 5;26(23):3107-3115. doi: 10.1016/j.cub.2016.09.015.

Humans and other primates have evolved the ability to represent their status in the group's social hierarchy, which is essential for avoiding harm and accessing resources. Yet it remains unclear how the human brain learns dominance status and adjusts behavior accordingly during dynamic social interactions. Here we address this issue with a combination of fMRI and transcranial direct current stimulation (tDCS). In a first fMRI experiment, participants learned an implicit dominance hierarchy while playing a competitive game against three opponents of different skills. Neural activity in the rostromedial PFC (rmPFC) dynamically tracked and updated the dominance status of the opponents, whereas the ventromedial PFC and ventral striatum reacted specifically to competitive victories and defeats. In a second experiment, we applied anodal tDCS over the rmPFC to enhance neural excitability while subjects performed a similar competitive task. The stimulation enhanced the relative weight of victories over defeats in learning social dominance relationships and exacerbated the influence of one's own dominance over competitive strategies. Importantly, these tDCS effects were specific to trials in which subjects learned about dominance relationships, as they were not present for control choices associated with monetary incentives but no competitive feedback. Taken together, our findings elucidate the role of rmPFC computations in dominance learning and unravel a fundamental mechanism that governs the emergence and maintenance of social dominance relationships in humans.


Imbalanced Activity in the Orbitofrontal Cortex and Nucleus Accumbens Impairs Behavioral Inhibition

Meyer HC, Bucci DJ.
Curr Biol. 2016 Oct 24;26(20):2834-2839. doi: 10.1016/j.cub.2016.08.034.

Contemporary models of behavioral regulation maintain that balanced activity between cognitive control areas (prefrontal cortex, PFC) and subcortical reward-related regions (nucleus accumbens, NAC) mediates the selection of appropriate behavioral responses, whereas imbalanced activity (PFC < NAC) results in maladaptive behavior [1-6]. Imbalance can arise from reduced engagement of PFC (via fatigue or stress [7]) or from excessive activity in NAC [8]. Additionally, a concept far less researched is that an imbalance can result from simultaneously low PFC activity and high NAC activity. This occurs during adolescence, when the maturation of PFC lags behind that of NAC and NAC is more functionally active compared to adulthood or pre-adolescence [2, 5, 9, 10]. Accordingly, activity is disproportionately higher in NAC than in PFC, which may contribute to impulsivity and risk-taking exhibited by adolescents [5, 6, 10-12]. Despite having explanatory value, support for this notion has been solely correlational. Here, we causally tested this using chemogenetics to simultaneously decrease neural activity in the orbitofrontal cortex (OFC) and increase activity in NAC in adult rats, mimicking the imbalance during adolescence. We tested the effects on negative occasion setting, an important yet understudied form of inhibitory learning that may be particularly relevant during adolescence. Rats with combined manipulation of OFC and NAC were impaired in learning to use environmental cues to withhold a response, an effect that was greater than that of either manipulation alone. These findings provide direct evidence that simultaneous underactivity in OFC and overactivity in NAC can negatively impact behavioral control and provide insight into the neural systems that underlie inhibitory learning.


Dissociation of Choice Formation and Choice-Correlated Activity in Macaque Visual Cortex

Robbe L.T. Goris, Corey M. Ziemba, Gabriel M. Stine, Eero P. Simoncelli and J. Anthony Movshon
Journal of Neuroscience 21 April 2017, 37 (20) 5195-5203;
DOI: https://doi.org/10.1523/JNEUROSCI.3331-16.2017

Responses of individual task-relevant sensory neurons can predict monkeys' trial-by-trial choices in perceptual decision-making tasks. Choice-correlated activity has been interpreted as evidence that the responses of these neurons are causally linked to perceptual judgments. To further test this hypothesis, we studied responses of orientation-selective neurons in V1 and V2 while two macaque monkeys performed a fine orientation discrimination task. Although both animals exhibited a high level of neuronal and behavioral sensitivity, only one exhibited choice-correlated activity. Surprisingly, this correlation was negative: when a neuron fired more vigorously, the animal was less likely to choose the orientation preferred by that neuron. Moreover, choice-correlated activity emerged late in the trial, earlier in V2 than in V1, and was correlated with anticipatory signals. Together, these results suggest that choice-correlated activity in task-relevant sensory neurons can reflect postdecision modulatory signals.


Interaction of Instrumental and Goal-Directed Learning Modulates Prediction Error Representations in the Ventral Striatum

Guo R, Böhmer W, Hebart M, Chien S, Sommer T, Obermayer K, Gläscher J.
J Neurosci. 2016 Dec 14;36(50):12650-12660.

Goal-directed and instrumental learning are both important controllers of human behavior. Learning about which stimulus event occurs in the environment and the reward associated with them allows humans to seek out the most valuable stimulus and move through the environment in a goal-directed manner. Stimulus-response associations are characteristic of instrumental learning, whereas response-outcome associations are the hallmark of goal-directed learning. Here we provide behavioral, computational, and neuroimaging results from a novel task in which stimulus-response and response-outcome associations are learned simultaneously but dominate behavior at different stages of the experiment. We found that prediction error representations in the ventral striatum depend on which type of learning dominates. Furthermore, the amygdala tracks the time-dependent weighting of stimulus-response versus response-outcome learning. Our findings suggest that the goal-directed and instrumental controllers dynamically engage the ventral striatum in representing prediction errors whenever one of them is dominating choice behavior.


Decoding Spontaneous Emotional States in the Human Brain

Kragel PA, Knodt AR, Hariri AR, LaBar KS.
PLoS Biol. 2016 Sep 14;14(9):e2000106. doi: 10.1371/journal.pbio.2000106.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.


Approach-Induced Biases in Human Information

Hunt LT, Rutledge RB, Malalasekera WM, Kennerley SW, Dolan RJ
PLoS Biol. 2016 Nov 10;14(11):e2000638. doi: 10.1371/journal.pbio.2000638.

Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach"), the selection of which information to sample ("sampling the favorite"), and the interaction between information sampling and subsequent choices ("rejecting unsampled options"). The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.


A basal ganglia circuit for evaluating action outcomes

Stephenson-Jones M, Yu K, Ahrens S, Tucciarone JM, van Huijstee AN, Mejia LA, Penzo MA, Tai LH, Wilbrecht L, Li B.
Nature. 2016 Nov 10;539(7628):289-293. doi: 10.1038/nature19845. Epub 2016 Sep 21.

The basal ganglia, a group of subcortical nuclei, play a crucial role in decision-making by selecting actions and evaluating their outcomes. While much is known about the function of the basal ganglia circuitry in selection, how these nuclei contribute to outcome evaluation is less clear. Here we show that neurons in the habenula-projecting globus pallidus (GPh) in mice are essential for evaluating action outcomes and are regulated by a specific set of inputs from the basal ganglia. We find in a classical conditioning task that individual mouse GPh neurons bidirectionally encode whether an outcome is better or worse than expected. Mimicking these evaluation signals with optogenetic inhibition or excitation is sufficient to reinforce or discourage actions in a decision-making task. Moreover, cell-type-specific synaptic manipulations reveal that the inhibitory and excitatory inputs to the GPh are necessary for mice to appropriately evaluate positive and negative feedback, respectively. Finally, using rabies-virus-assisted monosynaptic tracing, we show that the GPh is embedded in a basal ganglia circuit wherein it receives inhibitory input from both striosomal and matrix compartments of the striatum, and excitatory input from the 'limbic' regions of the subthalamic nucleus. Our results provide evidence that information about the selection and evaluation of actions is channelled through distinct sets of basal ganglia circuits, with the GPh representing a key locus in which information of opposing valence is integrated to determine whether action outcomes are better or worse than expected.


Neural ensemble dynamics underlying a long-term associative memory

Grewe BF, Gründemann J, Kitch LJ, Lecoq JA, Parker JG, Marshall JD, Larkin MC, Jercog PE, Grenier F, Li JZ, Lüthi A, Schnitzer MJ
Nature. 2017 Mar 30;543(7647):670-675. doi: 10.1038/nature21682. Epub 2017 Mar 22.

The brain's ability to associate different stimuli is vital for long-term memory, but how neural ensembles encode associative memories is unknown. Here we studied how cell ensembles in the basal and lateral amygdala encode associations between conditioned and unconditioned stimuli (CS and US, respectively). Using a miniature fluorescence microscope, we tracked the Ca2+ dynamics of ensembles of amygdalar neurons during fear learning and extinction over 6 days in behaving mice. Fear conditioning induced both up- and down-regulation of individual cells' CS-evoked responses. This bi-directional plasticity mainly occurred after conditioning, and reshaped the neural ensemble representation of the CS to become more similar to the US representation. During extinction training with repetitive CS presentations, the CS representation became more distinctive without reverting to its original form. Throughout the experiments, the strength of the ensemble-encoded CS-US association predicted the level of behavioural conditioning in each mouse. These findings support a supervised learning model in which activation of the US representation guides the transformation of the CS representation.


Nonpolitical Images Evoke Neural Predictors of Political Ideology

Woo-Young Ahn, Kenneth T. Kishida, Xiaosi Gu, Terry Lohrenz, Ann Harvey, John R. Alford, Kevin B. Smith, Gideon Yaffe, John R. Hibbing, Peter Dayan, P. Read Montague
Current Biology. Volume 24, Issue 22, p2693–2699, 17 November 2014

Political ideologies summarize dimensions of life that define how a person organizes their public and private behavior, including their attitudes associated with sex, family, education, and personal autonomy [ 1, 2 ]. Despite the abstract nature of such sensibilities, fundamental features of political ideology have been found to be deeply connected to basic biological mechanisms [ 3–7 ] that may serve to defend against environmental challenges like contamination and physical threat [ 8–12 ]. These results invite the provocative claim that neural responses to nonpolitical stimuli (like contaminated food or physical threats) should be highly predictive of abstract political opinions (like attitudes toward gun control and abortion) [ 13 ]. We applied a machine-learning method to fMRI data to test the hypotheses that brain responses to emotionally evocative images predict individual scores on a standard political ideology assay. Disgusting images, especially those related to animal-reminder disgust (e.g., mutilated body), generate neural responses that are highly predictive of political orientation even though these neural predictors do not agree with participants’ conscious rating of the stimuli. Images from other affective categories do not support such predictions. Remarkably, brain responses to a single disgusting stimulus were sufficient to make accurate predictions about an individual subject’s political ideology. These results provide strong support for the idea that fundamental neural processing differences that emerge under the challenge of emotionally evocative stimuli may serve to structure political beliefs in ways formerly unappreciated.


How prior preferences determine decision-making frames and biases in the human brain

Lopez-Persem A, Domenech P, Pessiglione M
Elife. 2016 Nov 19;5. pii: e20317. doi: 10.7554/eLife.20317.

Understanding how option values are compared when making a choice is a key objective for decision neuroscience. In natural situations, agents may have a priori on their preferences that create default policies and shape the neural comparison process. We asked participants to make choices between items belonging to different categories (e.g., jazz vs. rock music). Behavioral data confirmed that the items taken from the preferred category were chosen more often and more rapidly, which qualified them as default options. FMRI data showed that baseline activity in classical brain valuation regions, such as the ventromedial Prefrontal Cortex (vmPFC), reflected the strength of prior preferences. In addition, evoked activity in the same regions scaled with the default option value, irrespective of the eventual choice. We therefore suggest that in the brain valuation system, choices are framed as comparisons between default and alternative options, which might save some resource but induce a decision bias.


Dynamic neural architecture for social knowledge retrieval

Y Wang et al.
Proc Natl Acad Sci U S A 114 (16), E3305-E3314. 2017 Mar 13.

Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often guide our decisions as we navigate complex social interactions. Even abstract traits associated with an individual, such as their political affiliation, can cue a rich cascade of person-specific knowledge. Here, we asked whether the anterior temporal lobe (ATL) serves as a hub for a distributed neural circuit that represents person knowledge. Fifty participants across two studies learned biographical information about fictitious people in a 2-d training paradigm. On day 3, they retrieved this biographical information while undergoing an fMRI scan. A series of multivariate and connectivity analyses suggest that the ATL stores abstract person identity representations. Moreover, this region coordinates interactions with a distributed network to support the flexible retrieval of person attributes. Together, our results suggest that the ATL is a central hub for representing and retrieving person knowledge.


Neural processes mediating contextual influences on human choice behaviour

Francesco Rigoli, Karl J. Friston & Raymond J. Dolan
Nature Communications 7, Article number: 12416 (2016) doi:10.1038/ncomms12416

Contextual influences on choice are ubiquitous in ecological settings. Current evidence suggests that subjective values are normalized with respect to the distribution of potentially available rewards. However, how this context-sensitivity is realised in the brain remains unknown. To address this, here we examine functional magnetic resonance imaging (fMRI) data during performance of a gambling task where blocks comprise values drawn from one of two different, but partially overlapping, reward distributions or contexts. At the beginning of each block (when information about context is provided), hippocampus is activated and this response is enhanced when contextual influence on choice increases. In addition, response to value in ventral tegmental area/substantia nigra (VTA/SN) shows context-sensitivity, an effect enhanced with an increased contextual influence on choice. Finally, greater response in hippocampus at block start is associated with enhanced context sensitivity in VTA/SN. These findings suggest that context-sensitive choice is driven by a brain circuit involving hippocampus and dopaminergic midbrain.


Confidence Is the Bridge between Multi-stage Decisions

van den Berg R, Zylberberg A, Kiani R, Shadlen MN, Wolpert DM
Curr Biol. 2016 Dec 5;26(23):3157-3168. doi: 10.1016/j.cub.2016.10.021.

Demanding tasks often require a series of decisions to reach a goal. Recent progress in perceptual decision-making has served to unite decision accuracy, speed, and confidence in a common framework of bounded evidence accumulation, furnishing a platform for the study of such multi-stage decisions. In many instances, the strategy applied to each decision, such as the speed-accuracy trade-off, ought to depend on the accuracy of the previous decisions. However, as the accuracy of each decision is often unknown to the decision maker, we hypothesized that subjects may carry forward a level of confidence in previous decisions to affect subsequent decisions. Subjects made two perceptual decisions sequentially and were rewarded only if they made both correctly. The speed and accuracy of individual decisions were explained by noisy evidence accumulation to a terminating bound. We found that subjects adjusted their speed-accuracy setting by elevating the termination bound on the second decision in proportion to their confidence in the first. The findings reveal a novel role for confidence and a degree of flexibility, hitherto unknown, in the brain's ability to rapidly and precisely modify the mechanisms that control the termination of a decision.


Observational learning computations in neurons of the human anterior cingulate cortex

Michael R. Hill, Erie D. Boorman & Itzhak Fried
Nature Communications 7, Article number: 12722 (2016) doi:10.1038/ncomms12722

When learning from direct experience, neurons in the primate brain have been shown to encode a teaching signal used by algorithms in artificial intelligence: the reward prediction error (PE)—the difference between how rewarding an event is, and how rewarding it was expected to be. However, in humans and other species learning often takes place by observing other individuals. Here, we show that, when humans observe other players in a card game, neurons in their rostral anterior cingulate cortex (rACC) encode both the expected value of an observed choice, and the PE after the outcome was revealed. Notably, during the same task neurons recorded in the amygdala (AMY) and the rostromedial prefrontal cortex (rmPFC) do not exhibit this type of encoding. Our results suggest that humans learn by observing others, at least in part through the encoding of observational PEs in single neurons in the rACC.


Neurons in the primate dorsal striatum signal the uncertainty of object–reward associations

J. Kael White & Ilya E. Monosov
Nature Communications 7, Article number: 12735 (2016) doi:10.1038/ncomms12735

To learn, obtain reward and survive, humans and other animals must monitor, approach and act on objects that are associated with variable or unknown rewards. However, the neuronal mechanisms that mediate behaviours aimed at uncertain objects are poorly understood. Here we demonstrate that a set of neurons in an internal-capsule bordering regions of the primate dorsal striatum, within the putamen and caudate nucleus, signal the uncertainty of object–reward associations. Their uncertainty responses depend on the presence of objects associated with reward uncertainty and evolve rapidly as monkeys learn novel object–reward associations. Therefore, beyond its established role in mediating actions aimed at known or certain rewards, the dorsal striatum also participates in behaviours aimed at reward-uncertain objects.


Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents

Christian Büchel, Jan Peters[…]the IMAGEN consortium
Nature Communications 8, Article number: 14140 (2017) doi:10.1038/ncomms14140

Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use.


Striatal prediction errors support dynamic control of declarative memory decisions

Jason M. Scimeca, Perri L. Katzman & David Badre
Nature Communications 7, Article number: 13061 (2016) doi:10.1038/ncomms13061

Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants’ recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals’ final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals.


Computations Underlying Social Hierarchy Learning: Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information

Kumaran D, Banino A, Blundell C, Hassabis D, Dayan P.
Neuron. 2016 Dec 7;92(5):1135-1147. doi: 10.1016/j.neuron.2016.10.052.

Knowledge about social hierarchies organizes human behavior, yet we understand little about the underlying computations. Here we show that a Bayesian inference scheme, which tracks the power of individuals, better captures behavioral and neural data compared with a reinforcement learning model inspired by rating systems used in games such as chess. We provide evidence that the medial prefrontal cortex (MPFC) selectively mediates the updating of knowledge about one's own hierarchy, as opposed to that of another individual, a process that underpinned successful performance and involved functional interactions with the amygdala and hippocampus. In contrast, we observed domain-general coding of rank in the amygdala and hippocampus, even when the task did not require it. Our findings reveal the computations underlying a core aspect of social cognition and provide new evidence that self-relevant information may indeed be afforded a unique representational status in the brain.


Lateral orbitofrontal cortex anticipates choices and integrates prior with current information

Ramon Nogueira, Juan M. Abolafia, Jan Drugowitsch, Emili Balaguer-Ballester, Maria V. Sanchez-Vives & Rubén Moreno-Bote
Nature Communications 8, Article number: 14823 (2017) doi:10.1038/ncomms14823

Adaptive behavior requires integrating prior with current information to anticipate upcoming events. Brain structures related to this computation should bring relevant signals from the recent past into the present. Here we report that rats can integrate the most recent prior information with sensory information, thereby improving behavior on a perceptual decision-making task with outcome-dependent past trial history. We find that anticipatory signals in the orbitofrontal cortex about upcoming choice increase over time and are even present before stimulus onset. These neuronal signals also represent the stimulus and relevant second-order combinations of past state variables. The encoding of choice, stimulus and second-order past state variables resides, up to movement onset, in overlapping populations. The neuronal representation of choice before stimulus onset and its build-up once the stimulus is presented suggest that orbitofrontal cortex plays a role in transforming immediate prior and stimulus information into choices using a compact state-space representation.


Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality

Drugowitsch J, Wyart V, Devauchelle AD, Koechlin E
Neuron. 2016 Dec 21;92(6):1398-1411. doi: 10.1016/j.neuron.2016.11.005. Epub 2016 Dec 1.

Making decisions in uncertain environments often requires combining multiple pieces of ambiguous information from external cues. In such conditions, human choices resemble optimal Bayesian inference, but typically show a large suboptimal variability whose origin remains poorly understood. In particular, this choice suboptimality might arise from imperfections in mental inference rather than in peripheral stages, such as sensory processing and response selection. Here, we dissociate these three sources of suboptimality in human choices based on combining multiple ambiguous cues. Using a novel quantitative approach for identifying the origin and structure of choice variability, we show that imperfections in inference alone cause a dominant fraction of suboptimal choices. Furthermore, two-thirds of this suboptimality appear to derive from the limited precision of neural computations implementing inference rather than from systematic deviations from Bayes-optimal inference. These findings set an upper bound on the accuracy and ultimate predictability of human choices in uncertain environments.


Generalization of prior information for rapid Bayesian time estimation

Roach NW, McGraw PV, Whitaker DJ, Heron J
Proc Natl Acad Sci U S A. 2017 Jan 10;114(2):412-417. doi: 10.1073/pnas.1610706114. Epub 2016 Dec 22.

To enable effective interaction with the environment, the brain combines noisy sensory information with expectations based on prior experience. There is ample evidence showing that humans can learn statistical regularities in sensory input and exploit this knowledge to improve perceptual decisions and actions. However, fundamental questions remain regarding how priors are learned and how they generalize to different sensory and behavioral contexts. In principle, maintaining a large set of highly specific priors may be inefficient and restrict the speed at which expectations can be formed and updated in response to changes in the environment. However, priors formed by generalizing across varying contexts may not be accurate. Here, we exploit rapidly induced contextual biases in duration reproduction to reveal how these competing demands are resolved during the early stages of prior acquisition. We show that observers initially form a single prior by generalizing across duration distributions coupled with distinct sensory signals. In contrast, they form multiple priors if distributions are coupled with distinct motor outputs. Together, our findings suggest that rapid prior acquisition is facilitated by generalization across experiences of different sensory inputs but organized according to how that sensory information is acted on.


Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making

Baskin-Sommers A, Stuppy-Sullivan AM, Buckholtz JW
Proc Natl Acad Sci U S A. 2016 Dec 13;113(50):14438-14443. Epub 2016 Nov 28.

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost-benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior.


A neural model of valuation and information virality

Scholz C, Baek EC, O'Donnell MB, Kim HS, Cappella JN, Falk EB
Proc Natl Acad Sci U S A. 2017 Mar 14;114(11):2881-2886. doi: 10.1073/pnas.1615259114. Epub 2017 Feb 27.

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing-to express ourselves in positive ways and to strengthen our social bonds.


Explicit representation of confidence informs future value-based decisions

Tomas Folke, Catrine Jacobsen, Stephen M. Fleming & Benedetto De Martino
Nature Human Behaviour 1, Article number: 0002 (2016) doi:10.1038/s41562-016-0002

Humans can reflect on decisions and report variable levels of confidence. But why maintain an explicit representation of confidence for choices that have already been made and therefore cannot be undone? Here we show that an explicit representation of confidence is harnessed for subsequent changes of mind. Specifically, when confidence is low, participants are more likely to change their minds when the same choice is presented again, an effect that is most pronounced in participants with greater fidelity in their confidence reports. Furthermore, we show that choices reported with high confidence follow a more consistent pattern (fewer transitivity violations). Finally, by tracking participants’ eye movements, we demonstrate that lower-level gaze dynamics can track uncertainty but do not directly impact changes of mind. These results suggest that an explicit and accurate representation of confidence has a positive impact on the quality of future value-based decisions.


Perceptual learning alters post-sensory processing in human decision-making

Jessica A. Diaz, Filippo Queirazza & Marios G. Philiastides
Nature Human Behaviour 1, Article number: 0035 (2017) doi:10.1038/s41562-016-0035

An emerging view in perceptual learning is that improvements in perceptual sensitivity are not only due to enhancements in early sensory representations but also due to changes in post-sensory decision-processing. In humans, however, direct neurobiological evidence of the latter remains scarce. Here, we trained participants on a visual categorization task over three days and used multivariate pattern analysis of the electroencephalogram to identify two temporally specific components encoding sensory (‘Early’) and decision (‘Late’) evidence, respectively. Importantly, the single-trial amplitudes of the Late, but not the Early component, were amplified in the course of training, and these enhancements predicted the behavioural improvements on the task. Correspondingly, we modelled these improvements with a reinforcement learning mechanism, using a reward prediction error signal to strengthen the readout of sensory evidence used for the decision. We validated this mechanism through a robust association between the model’s decision variables and the amplitudes of our Late component that encode decision evidence.