Recurrent interactions in local cortical circuits.

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations1-4. Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average5,6. Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes5-7, and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually8. Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity7 and photoablating9,10 neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.

Using Robson's Ten-Group Classification System for comparing caesarean section rates in Europe: an analysis of routine data from the Euro-Peristat study.

OBJECTIVE: Robson's Ten Group Classification System (TGCS) creates clinically relevant sub-groups for monitoring caesarean birth rates. This study assesses whether this classification can be derived from routine data in Europe and uses it to analyse national caesarean rates. DESIGN: Observational study using routine data. SETTING: Twenty-seven EU member states plus Iceland, Norway, Switzerland and the UK. POPULATION: All births at ≥22 weeks of gestational age in 2015. METHODS: National statistical offices and medical birth registers derived numbers of caesarean births in TGCS groups. MAIN OUTCOME MEASURES: Overall caesarean rate, prevalence and caesarean rates in each of the TGCS groups. RESULTS: Of 31 countries, 18 were able to provide data on the TGCS groups, with UK data available only from Northern Ireland. Caesarean birth rates ranged from 16.1 to 56.9%. Countries providing TGCS data had lower caesarean rates than countries without data (25.8% versus 32.9%, P = 0.04). Countries with higher caesarean rates tended to have higher rates in all TGCS groups. Substantial heterogeneity was observed, however, especially for groups 5 (previous caesarean section), 6, 7 (nulliparous/multiparous breech) and 10 (singleton cephalic preterm). The differences in percentages of abnormal lies, group 9, illustrate potential misclassification arising from unstandardised definitions. CONCLUSIONS: Although further validation of data quality is needed, using TGCS in Europe provides valuable comparator and baseline data for benchmarking and surveillance. Higher caesarean rates in countries unable to construct the TGCS suggest that effective routine information systems may be an indicator of a country's investment in implementing evidence-based caesarean policies. TWEETABLE ABSTRACT: Many European countries can provide Robson's Ten-Group Classification to improve caesarean rate comparisons.

Efficient neural decoding of self-location with a deep recurrent network.

Place cells in the mammalian hippocampus signal self-location with sparse spatially stable firing fields. Based on observation of place cell activity it is possible to accurately decode an animal's location. The precision of this decoding sets a lower bound for the amount of information that the hippocampal population conveys about the location of the animal. In this work we use a novel recurrent neural network (RNN) decoder to infer the location of freely moving rats from single unit hippocampal recordings. RNNs are biologically plausible models of neural circuits that learn to incorporate relevant temporal context without the need to make complicated assumptions about the use of prior information to predict the current state. When decoding animal position from spike counts in 1D and 2D-environments, we show that the RNN consistently outperforms a standard Bayesian approach with either flat priors or with memory. In addition, we also conducted a set of sensitivity analysis on the RNN decoder to determine which neurons and sections of firing fields were the most influential. We found that the application of RNNs to neural data allowed flexible integration of temporal context, yielding improved accuracy relative to the more commonly used Bayesian approaches and opens new avenues for exploration of the neural code.

Hippocampal CA1 activity correlated with the distance to the goal and navigation performance.

Coding the distance to a future goal is an important function of a neural system supporting navigation. While some evidence indicates the hippocampus increases activity with proximity to the goal, others have found activity to decrease with proximity. To explore goal distance coding in the hippocampus we recorded from CA1 hippocampal place cells in rats as they navigated to learned goals in an event arena with a win-stay lose-shift rule. CA1 activity was positively correlated with the distance - decreasing with proximity to the goal. The stronger the correlation between distance to the goal and CA1 activity, the more successful navigation was in a given task session. Acceleration, but not speed, was also correlated with the distance to the goal. However, the relationship between CA1 activity and navigation performance was independent of variation in acceleration and variation in speed. These results help clarify the situations in which CA1 activity encodes navigationally relevant information and the extent to which it relates to behavior.

Wide differences in mode of delivery within Europe: risk-stratified analyses of aggregated routine data from the Euro-Peristat study.

OBJECTIVE: To use data from routine sources to compare rates of obstetric intervention in Europe both overall and for subgroups at higher risk of intervention. DESIGN: Retrospective analysis of aggregated routine data. SETTING: Thirty-one European countries or regions contributing data on mode of delivery to the Euro-Peristat project. POPULATION: Births in participating countries in 2010. METHODS: Countries provided aggregated data about overall rates of obstetric intervention and about caesarean section rates for specified subgroups. MAIN OUTCOME MEASURES: Mode of delivery. RESULTS: Rates of caesarean section ranged from 14.8% to 52.2% of all births and rates of instrumental vaginal delivery ranged from 0.5% to 16.4%. Overall, there was no association between rates of instrumental vaginal delivery and rates of caesarean section, but similarities were observed between some countries that are geographically close and may share common traditions of practice. Associations were observed between caesarean section rates for women with breech and vertex births and with singleton and multiple births but patterns of association for women who had and had not had previous caesarean sections were more complex. CONCLUSIONS: The persisting wide variations in caesarean section and instrumental vaginal delivery rates point to a lack of consensus about practice and raise questions for further investigation. Further research is needed to explore the impact of differences in clinical guidelines, healthcare systems and their financing and parents' and professionals' attitudes to care at delivery.

Cognitive-behavioural therapy in medication-treated adults with attention-deficit/hyperactivity disorder and co-morbid psychopathology: a randomized controlled trial using multi-level analysis.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by high rates of co-morbid psychopathology. Randomized controlled trials of multimodal interventions, combining pharmacological and psychological treatments, have shown a robust treatment effect for ADHD symptoms but outcomes for co-morbid symptoms have been mixed. This may be accounted for by the type of intervention selected and/or by methodological problems including lack of follow-up and low power. The current study addressed these limitations in a parallel-group randomized controlled trial conducted in Iceland. METHOD: A total of 95 adult ADHD patients who were already being treated with medication (MED) were randomly assigned to receive treatment as usual (TAU/MED) or 15 sessions of cognitive-behavioural therapy (CBT/MED) using the R&R2ADHD intervention which employs both group and individual modalities. Primary measures of ADHD symptoms and severity of illness, and secondary measures of anxiety, depression and quality of life were given at baseline, end of treatment and 3-month follow-up. Primary outcomes were rated by clinicians blind to treatment condition assignment. RESULTS: CBT/MED showed overall (combined outcome at end of treatment and 3-month follow-up) significantly greater reduction in primary outcomes for clinician-rated and self-rated ADHD symptoms. Treatment effect of primary outcomes was maintained at follow-up, which suggests robust and lasting findings. In contrast to the primary outcomes, the secondary outcomes showed significant improvement over time. CONCLUSIONS: The study provides evidence for the effectiveness of R&R2ADHD and demonstrates that there are differential effects over time for ADHD symptoms versus co-morbid problems, the latter taking longer to show positive effects.

Episodic memory development: Bridging animal and human research.

Human episodic memory is not functionally evident until about 2 years of age and continues to develop into the school years. Behavioral studies have elucidated this developmental timeline and its constituent processes. In tandem, lesion and neurophysiological studies in non-human primates and rodents have identified key neural substrates and circuit mechanisms that may underlie episodic memory development. Despite this progress, collaborative efforts between psychologists and neuroscientists remain limited, hindering progress. Here, we seek to bridge human and non-human episodic memory development research by offering a comparative review of studies using humans, non-human primates, and rodents. We highlight critical theoretical and methodological issues that limit cross-fertilization and propose a common research framework, adaptable to different species, that may facilitate cross-species research endeavors.

Rethinking the hippocampal cognitive map as a meta-learning computational module.

A hallmark of biological intelligence is the ability to adaptively draw on past experience to guide behaviour under novel situations. Yet, the neurobiological principles that underlie this form of meta-learning remain relatively unexplored. In this Opinion, we review the existing literature on hippocampal spatial representations and reinforcement learning theory and describe a novel theoretical framework that aims to account for biological meta-learning. We conjecture that so-called hippocampal cognitive maps of familiar environments are part of a larger meta-representation (meta-map) that encodes information states and sources, which support exploration and provides a foundation for learning. We also introduce concrete hypotheses on how these generic states can be encoded using a principle of superposition.

Cracking the neuronal code of episodic memory.

Hierarchical organization of memory is observed in the brains of rats.

Theta-band phase locking during encoding leads to coordinated entorhinal-hippocampal replay.

Precisely timed interactions between hippocampal and cortical neurons during replay epochs are thought to support learning. Indeed, research has shown that replay is associated with heightened hippocampal-cortical synchrony. Yet many caveats remain in our understanding. Namely, it remains unclear how this offline synchrony comes about, whether it is specific to particular behavioral states, and how-if at all-it relates to learning. In this study, we sought to address these questions by analyzing coordination between CA1 cells and neurons of the deep layers of the medial entorhinal cortex (dMEC) while rats learned a novel spatial task. During movement, we found a subset of dMEC cells that were particularly locked to hippocampal LFP theta-band oscillations and that were preferentially coordinated with hippocampal replay during offline periods. Further, dMEC synchrony with CA1 replay peaked ∼10 ms after replay initiation in CA1, suggesting that the distributed replay reflects extra-hippocampal information propagation and is specific to "offline" periods. Finally, theta-modulated dMEC cells showed a striking experience-dependent increase in synchronization with hippocampal replay trajectories, mirroring the animals' acquisition of the novel task and coupling to the hippocampal local field. Together, these findings provide strong support for the hypothesis that synergistic hippocampal-cortical replay supports learning and highlights phase locking to hippocampal theta oscillations as a potential mechanism by which such cross-structural synchrony comes about.

Ripple band phase precession of place cell firing during replay.

Neuronal "replay," in which place cell firing during rest recapitulates recently experienced trajectories, is thought to mediate the transmission of information from hippocampus to neocortex, but the mechanism for this transmission is unknown. Here, we show that replay uses a phase code to represent spatial trajectories by the phase of firing relative to the 150- to 250-Hz "ripple" oscillations that accompany replay events. This phase code is analogous to the theta phase precession of place cell firing during navigation, in which place cells fire at progressively earlier phases of the 6- to 12-Hz theta oscillation as their place field is traversed, providing information about self-location that is additional to the rate code and a necessary precursor of replay. Thus, during replay, each ripple cycle contains a "forward sweep" of decoded locations along the recapitulated trajectory. Our results indicate a novel encoding of trajectory information during replay and implicates phase coding as a general mechanism by which the hippocampus transmits experienced and replayed sequential information to downstream targets.

Shining a light on hippocampal remapping.

In this issue of Neuron, McKenzie et al. (2021) test the degree to which pre-existing biases in hippocampal circuits constrict the encoding of new information via artificial induction of place cell remapping. Their results suggest that the hippocampal spatial map encodes new information via pre-existing latent place fields.

Temporally delayed linear modelling (TDLM) measures replay in both animals and humans.

There are rich structures in off-task neural activity which are hypothesized to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit - temporal delayed linear modelling (TDLM) - for analysing such activity. TDLM is a domain-general method for finding neural sequences that respect a pre-specified transition graph. It combines nonlinear classification and linear temporal modelling to test for statistical regularities in sequences of task-related reactivations. TDLM is developed on the non-invasive neuroimaging data and is designed to take care of confounds and maximize sequence detection ability. Notably, as a linear framework, TDLM can be easily extended, without loss of generality, to capture rodent replay in electrophysiology, including in continuous spaces, as well as addressing second-order inference questions, for example, its temporal and spatial varying pattern. We hope TDLM will advance a deeper understanding of neural computation and promote a richer convergence between animal and human neuroscience.

Electronically ascertained extended pedigrees in breast cancer genetic counseling.

A comprehensive pedigree, usually provided by the counselee and verified by medical records, is essential for risk assessment in cancer genetic counseling. Collecting the relevant information is time-consuming and sometimes impossible. We studied the use of electronically ascertained pedigrees (EGP). The study group comprised women (n = 1352) receiving HBOC genetic counseling between December 2006 and December 2016 at Landspitali in Iceland. EGP's were ascertained using information from the population-based Genealogy Database and Icelandic Cancer Registry. The likelihood of being positive for the Icelandic founder BRCA2 pathogenic variant NM_000059.3:c.767_771delCAAAT was calculated using the risk assessment program Boadicea. We used this unique data to estimate the optimal size of pedigrees, e.g., those that best balance the accuracy of risk assessment using Boadicea and cost of ascertainment. Sub-groups of randomly selected 104 positive and 105 negative women for the founder BRCA2 PV were formed and Receiver Operating Characteristics curves compared for efficiency of PV prediction with a Boadicea score. The optimal pedigree size included 3° relatives or up to five generations with an average no. of 53.8 individuals (range 9-220) (AUC 0.801). Adding 4° relatives did not improve the outcome. Pedigrees including 3° relatives are difficult and sometimes impossible to generate with conventional methods. Pedigrees ascertained with data from pre-existing genealogy databases and cancer registries can save effort and contain more information than traditional pedigrees. Genetic services should consider generating EGP's which requires access to an accurate genealogy database and cancer registry. Local data protection laws and regulations have to be addressed.

The Role of Hippocampal Replay in Memory and Planning.

The mammalian hippocampus is important for normal memory function, particularly memory for places and events. Place cells, neurons within the hippocampus that have spatial receptive fields, represent information about an animal's position. During periods of rest, but also during active task engagement, place cells spontaneously recapitulate past trajectories. Such 'replay' has been proposed as a mechanism necessary for a range of neurobiological functions, including systems memory consolidation, recall and spatial working memory, navigational planning, and reinforcement learning. Focusing mainly, but not exclusively, on work conducted in rodents, we describe the methodologies used to analyse replay and review evidence for its putative roles. We identify outstanding questions as well as apparent inconsistencies in existing data, making suggestions as to how these might be resolved. In particular, we find support for the involvement of replay in disparate processes, including the maintenance of hippocampal memories and decision making. We propose that the function of replay changes dynamically according to task demands placed on an organism and its current level of arousal.

Task Demands Predict a Dynamic Switch in the Content of Awake Hippocampal Replay.

Reactivation of hippocampal place cell sequences during behavioral immobility and rest has been linked with both memory consolidation and navigational planning. Yet it remains to be investigated whether these functions are temporally segregated, occurring during different behavioral states. During a self-paced spatial task, awake hippocampal replay occurring either immediately before movement toward a reward location or just after arrival at a reward location preferentially involved cells consistent with the current trajectory. In contrast, during periods of extended immobility, no such biases were evident. Notably, the occurrence of task-focused reactivations predicted the accuracy of subsequent spatial decisions. Additionally, during immobility, but not periods preceding or succeeding movement, grid cells in deep layers of the entorhinal cortex replayed coherently with the hippocampus. Thus, hippocampal reactivations dynamically and abruptly switch between operational modes in response to task demands, plausibly moving from a state favoring navigational planning to one geared toward memory consolidation.

Coordinated grid and place cell replay during rest.

Hippocampal replay has been hypothesized to underlie memory consolidation and navigational planning, yet the involvement of grid cells in replay is unknown. During replay we found grid cells to be spatially coherent with place cells, encoding locations 11 ms delayed relative to the hippocampus, with directionally modulated grid cells and forward replay exhibiting the greatest coherence with the CA1 area of the hippocampus. This suggests grid cells are engaged during the consolidation of spatial memories to the neocortex.

Unsupervised motion-compensation of multi-slice cardiac perfusion MRI.

This paper presents a novel method for registration of single and multi-slice cardiac perfusion MRI. Utilising off-line computer intensive analyses of variance and clustering in an annotated training set, the presented method is capable of providing registration without any manual interaction in less than a second per frame. Changes in image intensity during the bolus passage are modelled by a slice-coupled active appearance model, which is augmented with a cluster analysis of the training set. Landmark correspondences are optimised using the MDL framework due to Davies et al. Image search is verified and stabilised using perfusion specific prior models of pose and shape estimated from training data. Qualitative and quantitative validation of the method is carried out using 2000 clinical quality, short-axis, perfusion MR slice images, acquired from 10 freely breathing patients with acute myocardial infarction. Despite evident perfusion deficits and varying image quality in the limited training set, a leave-one-out cross-validation of the method showed a mean point to curve distance of 1.25+/-0.36 pixels for the left and right ventricle combined. We conclude that this learning-based method holds great promise for the automation of cardiac perfusion investigations, due to its accuracy, robustness and generalisation ability.

Spatial Cognition: Grid Cell Firing Depends on Self-Motion Cues.

A recent study has found that the periodic spatial activity of grid cells is completely degraded when animals are moved passively around an enclosure, strengthening the view that grid-firing is generated on the basis of self-motion information.