Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

Lei Qiao, Lijie Zhang, Antao Chen and Tobias Egner
Journal of Neuroscience 8 November 2017, 37 (45) 11037-11050

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion.


Transcranial Direct Current Stimulation Facilitates Associative Learning and Alters Functional Connectivity in the Primate Brain

Matthew R. Krause, Theodoros P. Zanos, Bennett A. Csorba, Praveen K. Pilly, Praveen K. Pilly, Jaehoon Choe, Matthew E. Phillips, Abhishek Datta, Christopher C. Pack
Current Biology, Volume 27, Issue 20, p3086–3096.e3, 23 October 2017

There has been growing interest in transcranial direct current stimulation (tDCS), a non-invasive technique purported to modulate neural activity via weak, externally applied electric fields. Although some promising preliminary data have been reported for applications ranging from stroke rehabilitation to cognitive enhancement, little is known about how tDCS affects the human brain, and some studies have concluded that it may have no effect at all. Here, we describe a macaque model of tDCS that allows us to simultaneously examine the effects of tDCS on brain activity and behavior. We find that applying tDCS to right prefrontal cortex improves monkeys’ performance on an associative learning task. While firing rates do not change within the targeted area, tDCS does induce large low-frequency oscillations in the underlying tissue. These oscillations alter functional connectivity, both locally and between distant brain areas, and these long-range changes correlate with tDCS’s effects on behavior. Together, these results are consistent with the idea that tDCS leads to widespread changes in brain activity and suggest that it may be a valuable method for cheaply and non-invasively altering functional connectivity in humans.


Dorsal Raphe Serotonergic Neurons Control Intertemporal Choice under Trade-off

Sangyu Xu, Gishnu Das, Emily Hueske, Susumu Tonegawa
Current Biology, Volume 27, Issue 20, p3111–3119.e3, 23 October 2017

Appropriate choice about delayed reward is fundamental to the survival of animals. Although animals tend to prefer immediate reward, delaying gratification is often advantageous. The dorsal raphe (DR) serotonergic neurons have long been implicated in the processing of delayed reward, but it has been unclear whether or when their activity causally directs choice. Here, we transiently augmented or reduced the activity of DR serotonergic neurons, while mice decided between differently delayed rewards as they performed a novel odor-guided intertemporal choice task. We found that these manipulations, precisely targeted at the decision point, were sufficient to bidirectionally influence impulsive choice. The manipulation specifically affected choices with more difficult trade-off. Similar effects were observed when we manipulated the serotonergic projections to the nucleus accumbens (NAc). We propose that DR serotonergic neurons preempt reward delays at the decision point and play a critical role in suppressing impulsive choice by regulating decision trade-off.


The Neural Basis of Aversive Pavlovian Guidance during Planning

Níall Lally, Quentin J.M. Huys, Neir Eshel, Paul Faulkner, Peter Dayan and Jonathan P. Roiser
Journal of Neuroscience 18 October 2017, 37 (42) 10215-10229

Important real-world decisions are often arduous as they frequently involve sequences of choices, with initial selections affecting future options. Evaluating every possible combination of choices is computationally intractable, particularly for longer multistep decisions. Therefore, humans frequently use heuristics to reduce the complexity of decisions. We recently used a goal-directed planning task to demonstrate the profound behavioral influence and ubiquity of one such shortcut, namely aversive pruning, a reflexive Pavlovian process that involves neglecting parts of the decision space residing beyond salient negative outcomes. However, how the brain implements this important decision heuristic and what underlies individual differences have hitherto remained unanswered. Therefore, we administered an adapted version of the same planning task to healthy male and female volunteers undergoing functional magnetic resonance imaging (fMRI) to determine the neural basis of aversive pruning. Through both computational and standard categorical fMRI analyses, we show that when planning was influenced by aversive pruning, the subgenual cingulate cortex was robustly recruited. This neural signature was distinct from those associated with general planning and valuation, two fundamental cognitive components elicited by our task but which are complementary to aversive pruning. Furthermore, we found that individual variation in levels of aversive pruning was associated with the responses of insula and dorsolateral prefrontal cortices to the receipt of large monetary losses, and also with subclinical levels of anxiety. In summary, our data reveal the neural signatures of an important reflexive Pavlovian process that shapes goal-directed evaluations and thereby determines the outcome of high-level sequential cognitive processes.


Posterior Cingulate Neurons Dynamically Signal Decisions to Disengage during Foraging

David L. Barack, Steve W.C. Chang, Michael L. Platt
Neuron, Volume 96, Issue 2, p339–347.e5, 11 October 2017

Foraging for resources is a fundamental behavior balancing systematic search and strategic disengagement. The foraging behavior of primates is especially complex and requires long-term memory, value comparison, strategic planning, and decision-making. Here we provide evidence from two different foraging tasks that neurons in primate posterior cingulate cortex (PCC) signal decision salience during foraging to motivate disengagement from the current strategy. In our foraging tasks, salience refers to the difference between decision thresholds and the net harvested reward. Salience signals were stronger in poor foraging contexts than rich ones, suggesting low harvest rates recruit mechanisms in PCC that regulate strategic disengagement and exploration during foraging.


Modulating musical reward sensitivity up and down with transcranial magnetic stimulation

Ernest Mas-Herrero, Alain Dagher & Robert J. Zatorre
Nature Human Behaviour 2, 27–32 (2017)

Humans have the unique capacity to experience pleasure from aesthetic stimuli, such as art and music. Recent neuroimaging findings with music have led to a model in which mesolimbic striatal circuits interact with cortical systems to generate expectancies leading to pleasure1,2. However, neuroimaging approaches are correlational. Here, we provide causal evidence for the model by combining transcranial magnetic stimulation over the left dorsolateral prefrontal cortex to directly modulate fronto-striatal function3 bidirectionally together with measures of pleasure and motivation during music listening. Our results show that perceived pleasure, psychophysiological measures of emotional arousal, and the monetary value assigned to music, are all significantly increased by exciting fronto-striatal pathways, whereas inhibition of this system leads to decreases in all of these variables compared with sham stimulation. These findings support the hypothesis that fronto-striatal function causally mediates both the affective responses and motivational aspects of music-induced reward, and provide insights into how aesthetic responses emerge in the human brain.


Continuous track paths reveal additive evidence integration in multistep decision making

Cristian Buc Calderon, Myrtille Dewulf, Wim Gevers, and Tom Verguts
PNAS, vol. 114 no. 40 10618–10623

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.