The representation of priors and decisions in the human parietal cortex

Animals actively sample their environment through orienting actions such as saccadic eye movements. Saccadic targets are selected based both on sensory evidence immediately preceding the saccade, and a “salience map” or prior built-up over multiple saccades. In the primate cortex, the selection of each individual saccade depends on competition between target-selective cells that ramp up their firing rate to saccade release. However, it is less clear how a cross-saccade prior might be implemented, either in neural firing or through an activity-silent mechanism such as modification of synaptic weights on sensory inputs. Here, we present evidence from magnetoencephalography for 2 distinct processes underlying the selection of the current saccade, and the representation of the prior, in human parietal cortex. While the classic ramping decision process for each saccade was reflected in neural firing rates (measured in the event-related field), a prior built-up over multiple saccades was implemented via modulation of the gain on sensory inputs from the preferred target, as evidenced by rapid frequency tagging. A cascade of computations over time (initial representation of the prior, followed by evidence accumulation and then an integration of prior and evidence) provides a mechanism by which a salience map may be built up across saccades in parietal cortex. It also provides insight into the apparent contradiction that inactivation of parietal cortex has been shown not to affect performance on single-trials, despite the presence of clear evidence accumulation signals in this region

Two Anatomically and Computationally Distinct Learning Signals Predict Changes to Stimulus-Outcome Associations in Hippocampus

Complex cognitive processes require sophisticated local processing but also interactions between distant brain regions. It is therefore critical to be able to study distant interactions between local computations and the neural representations they act on. Here we report two anatomically and computationally distinct learning signals in lateral orbitofrontal cortex (lOFC) and the dopaminergic ventral midbrain (VM) that predict trial-by-trial changes to a basic internal model in hippocampus. To measure local computations during learning and their interaction with neural representations, we coupled computational fMRI with trial-by-trial fMRI suppression. We find that suppression in a medial temporal lobe network changes trial-by-trial in proportion to stimulus-outcome associations. During interleaved choice trials, we identify learning signals that relate to outcome type in lOFC and to reward value in VM. These intervening choice feedback signals predicted the subsequent change to hippocampal suppression, suggesting a convergence of signals that update the flexible representation of stimulus-outcome associations

Defensive freezing and its relation to approach–avoidance decision-making under threat

Abstract Successful responding to acutely threatening situations requires adequate approach–avoidance decisions. However, it is unclear how threat-induced states—like freezing-related bradycardia—impact the weighing of the potential outcomes of such value-based decisions. Insight into the underlying computations is essential, not only to improve our models of decision-making but also to improve interventions for maladaptive decisions, for instance in anxiety patients and first-responders who frequently have to make decisions under acute threat. Forty-two participants made passive and active approach–avoidance decisions under threat-of-shock when confronted with mixed outcome-prospects (i.e., varying money and shock amounts). Choice behavior was best predicted by a model including individual action-tendencies and bradycardia, beyond the subjective value of the outcome. Moreover, threat-related bradycardia (high-vs-low threat) interacted with subjective value, depending on the action-context (passive-vs-active). Specifically, in action-contexts incongruent with participants’ intrinsic action-tendencies, stronger bradycardia related to diminished effects of subjective value on choice across participants. These findings illustrate the relevance of testing approach–avoidance decisions in relatively ecologically valid conditions of acute and primarily reinforced threat. These mechanistic insights into approach–avoidance conflict-resolution may inspire biofeedback-related techniques to optimize decision-making under threat. Critically, the findings demonstrate the relevance of incorporating internal psychophysiological states and external action-contexts into models of approach–avoidance decision-making

Causal manipulation of functional connectivity in a specific neural pathway during behaviour and at rest

Correlations in brain activity between two areas (functional connectivity) have been shown to relate to their underlying structural connections. We examine the possibility that functional connectivity also reflects short-term changes in synaptic efficacy. We demonstrate that paired transcranial magnetic stimulation (TMS) near ventral premotor cortex (PMv) and primary motor cortex (M1) with a short 8-ms inter-pulse interval evoking synchronous pre- and post-synaptic activity and which strengthens interregional connectivity between the two areas in a pattern consistent with Hebbian plasticity, leads to increased functional connectivity between PMv and M1 as measured with functional magnetic resonance imaging (fMRI). Moreover, we show that strengthening connectivity between these nodes has effects on a wider network of areas, such as decreasing coupling in a parallel motor programming stream. A control experiment revealed that identical TMS pulses at identical frequencies caused no change in fMRI-measured functional connectivity when the inter-pulse-interval was too long for Hebbian-like plasticity

Demographic details of the training group and control participants considered as a single group, and divided into two groups according to training task gain (HG: high gain; LG: low gain; BDI: Beck Depression Inventory II; NART: National Adult Reading Test).

<p>Demographic details of the training group and control participants considered as a single group, and divided into two groups according to training task gain (HG: high gain; LG: low gain; BDI: Beck Depression Inventory II; NART: National Adult Reading Test).</p

Statistical comparison of pre-training assessment scores (HG: high gain; LG: low gain).

<p>Statistical comparison of pre-training assessment scores (HG: high gain; LG: low gain).</p

Mean gain scores (±S.E.) on the BOMAT.

<p>**p<0.001; *p = 0.05; n.s. = not significant.</p

Mean gain scores (±S.E.) on the EM composite scores.

<p>**p<0.001; *p<0.05; n.s. = not significant.</p

Mean gain scores (±S.E.) on the training task (A) and change in performance across 20 days of training for the LG and HG groups (B).

<p>The mean scores at the first (AS1) and second (AS2) assessments are also shown. ** p<0.001.</p

The pre- (1) and post-training (2) assessment scores for the training task, BOMAT, and recognition memory tests (average d′, recollection and familiarity scores, as well as individual scores for the object and scene tasks) (HG: high gain; LG: low gain).

<p>The pre- (1) and post-training (2) assessment scores for the training task, BOMAT, and recognition memory tests (average d′, recollection and familiarity scores, as well as individual scores for the object and scene tasks) (HG: high gain; LG: low gain).</p