By following explicit instructions, humans instantaneously get the hang of tasks they have never performed before. We used a specially calibrated multivariate analysis technique to uncover the elusive representational states during the first few implementations of arbitrary rules such as 'for coffee, press red button' following their first-time instruction. Distributed activity patterns within the ventrolateral prefrontal cortex (VLPFC) indicated the presence of neural representations specific of individual stimulus-response (S-R) rule identities, preferentially for conditions requiring the memorization of instructed S-R rules for correct performance. Identity-specific representations were detectable starting from the first implementation trial and continued to be present across early implementation trials. The increasingly fluent application of novel rule representations was channelled through increasing cooperation between VLPFC and anterior striatum. These findings inform representational theories on how the prefrontal cortex supports behavioral flexibility specifically by enabling the ad-hoc coding of newly instructed individual rule identities during their first-time implementation.

Neural representation of newly instructed rule identities during early implementation trials.

Alpha-beta decoupling relevant to inhibition deficits leads to suicide attempt in major depressive disorder.

By following explicit instructions humans can instantaneously get the hang of tasks they have never performed before. Here, we used a specially calibrated multivariate analysis technique to uncover the elusive representational states following newly instructed arbitrary behavioural rules such as ‘for coffee, press red button’, while transitioning from ‘knowing what to do’ to ‘actually doing it’. Subtle variation in distributed neural activity patterns reflected rule-specific representations within the ventrolateral prefrontal cortex (VLPFC), confined to instructed stimulus-response learning in contrast to incidental learning involving the same stimuli and responses. VLPFC representations were established right after first-time instruction and remained stable across early implementation trials. More and more fluent application of novel rule representations was channelled through increasing cooperation between VLPFC and anterior striatum. These findings inform representational theories on how the prefrontal cortex supports behavioural flexibility by enabling ad-hoc coding of novel task rules without recourse to familiar sub-routines

https://biorxiv.org/content/biorxiv/early/2019/04/05/598276.full-text.pdf

Initial neural representation of individual rules after first-time instruction

Many accounts of instruction-based learning assume that initial declarative representations are transformed into executable procedural ones, so as to enable instruction implementation. We tested the hypothesis that declarative-procedural transformation should be bound to a specific response modality and not transferable across different modalities. In Experiment 1, novel stimulus-response instructions had to be implemented either verbally or manually either once or three times. Modality-specific procedural encoding was probed via a subsequent implicit priming test. This involved the same stimuli but required a response that could be either compatible or incompatible with the originally instructed response using either the same or a different response modality. We found that procedural encoding was modality-specific as indicated by a stronger repetition-dependent increase of the compatibility effect when response modality was unchanged. Explicit test performance, serving as a marker of declarative encoding, was independent of modality transition and it was uncorrelated with implicit test performance. Unexpectedly, the implicit priming test also revealed a small yet significant transfer to the response modality that was previously not overtly implemented, likely reflecting covert response "simulation". To examine if covertly simulated responding occurs even when instruction implementation is omitted altogether, we conducted Experiment 2. Subjects merely viewed novel stimulus-response instructions prior to testing. Again, we found evidence for procedural encoding of the non-implemented instructions. Moreover, a direct comparison of both experiments revealed higher test scores (both implicit and explicit) for previously non-implemented instructions than for previously implemented instructions. This calls for theoretical reconciliation with diverging previous study results. 

Characterising the declarative-procedural transformation in instruction-based learning

Abstract We used fMRI to investigate the neural changes and representational dynamics associated with different learning modes during initial learning and subsequent implementation of previously acquired stimulus-response (S-R) associations. We compared instruction-based learning (INS) and trial-and-error learning (TE) via a third observation-based learning (OBS) condition. This was yoked to the TE condition and shared features with both, the INS and TE conditions. During learning, neural changes were observed in the Frontoparietal and Default Mode Networks across learning modes, consistent with a general decrease in cognitive control demand as learning progresses. INS and TE exhibited condition-specific signal changes, which we interpreted in the context of covert motor preparation during INS, and intentional action and increased cognitive control demand during early TE trials, respectively. Multivariate pattern analysis revealed individual rule information in bilateral prefrontal, premotor, and parietal cortices across learning modes. Most regions revealed consistent representations of individual S-R rules between the learning stage and subsequent implementation stage, regardless of the learning mode. This suggests that initially formed S-R rule representations guide task performance during S-R rule implementation, irrespective of how they are acquired. Finally, within the primary motor and sensory cortices, individual S-R rules were decodable during the learning stage not only when motor responses were overtly executed, as in TE, but also in the absence of overt motor execution, as in INS. This finding substantiates previous claims of covert motor preparatory mechanisms during INS. 

Initial Learning in the Brain: From Rules to Action

Recent work has highlighted that multi-voxel pattern analysis (MVPA) can be severely biased when BOLD response estimation involves systematic imbalance in model regressor correlations. This problem occurs in situations where trial types of interest are temporally dependent and the associated BOLD activity overlaps. For example, in learning paradigms early and late learning stage trials are inherently ordered. It has been shown empirically that MVPAs assessing consecutive learning stages can be substantially biased especially when stages are closely spaced. Here, we propose a simple technique that ensures zero bias in item-specific multi-voxel activation patterns for consecutive learning stages with stage being defined by the incremental number of individual item occurrences. For the simpler problem, when MVPA is computed irrespective of learning stage over all item occurrences within a trial sequence, our results confirm that a sufficiently large, randomly selected subset of all possible trial sequence permutations ensures convergence to zero bias - but only when different trial sequences are generated for different subjects. However, this does not help to solve the harder problem to obtain bias-free results for learning-related activation patterns regarding consecutive learning stages. Randomization over all item occurrences fails to ensure zero bias when the full trial sequence is retrospectively divided into item occurrences confined to early and late learning stages. To ensure bias-free MVPA of consecutive learning stages, trial-sequence randomization needs to be done separately for each consecutive learning stage.

/pdf/unbiased-analysis-of-item-specific-multi-voxel-activation-1cqyhe5j2d.pdf

Unbiased Analysis of Item-Specific Multi-Voxel Activation Patterns Across Learning.

Forward planning is often essential to achieve goals over extended time periods. However, forward planning is typically computationally costly for the brain and should only be employed when necessary. The explicit calculation of how necessary forward planning will be, is in itself computationally costly. We therefore assumed that the brain generates a mapping from a particular situation to a proxy of planning value to make fast decisions about whether to use forward planning, or not. Moreover, since the state space of real world decision problems can be large, we hypothesized that such a mapping will rely on mechanisms that generalize sets of situations based on shared demand for planning. We tested this hypothesis in an fMRI study using a novel complex sequential task. Our results indicate that participants abstracted from the set of task features to more generalized control contexts that govern the balancing between forward planning and a simple response strategy. Strikingly, we found that correlations of conflict with response time and with activity in the dorsal anterior cingulate cortex were dependent on context. This context-dependency might reflect that the cognitive control system draws on category-based cognition, harnessing regularities in control demand across task space to generate control contexts that help reduce the complexity of control allocation decisions.

/pdf/forward-planning-driven-by-context-dependent-conflict-2qt13akvxg.pdf

Forward planning driven by context-dependent conflict processing in anterior cingulate cortex

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Unbiased Analysis of Item-Specific Multi-Voxel Activation Patterns Across Learning.

Forward planning driven by context-dependent conflict processing in anterior cingulate cortex