Rita Almeida

Structural Maturation and Brain Activity Predict Future Working Memory Capacity during Childhood Development

Human working memory capacity develops during childhood and is a strong predictor of future academic performance, in particular, achievements in mathematics and reading. Predicting working memory development is important for the early identification of children at risk for poor cognitive and academic development. Here we show that structural and functional magnetic resonance imaging data explain variance in childrens working memory capacity 2 years later, which was unique variance in addition to that predicted using cognitive tests. While current working memory capacity correlated with frontoparietal cortical activity, the future capacity could be inferred from structure and activity in basal ganglia and thalamus. This gives a novel insight into the neural mechanisms of childhood development and supports the idea that neuroimaging can have a unique role in predicting childrens cognitive development.

Modeling the Link between Functional Imaging and Neuronal Activity: Synaptic Metabolic Demand and Spike Rates

Functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) measurements reflect changes in the hemodynamics which are thought to be related to local synaptic input to neuron populations. The local neuronal spiking activity, which is believed to form the basis of neuronal coding and communication, is not directly reflected in fMRI/PET measurements. We used a mean-field neuronal model of recurrently coupled excitatory and inhibitory neuronal populations to characterize the relationship between the synaptic activity (reflected in the PET and fMRI measurements) and the neuronal spike rates, averaged over brain areas. We analyzed this relation for a number of cases. For a single brain area and in the absence of external input to its inhibitory neurons, the relation between average spike rates and synaptic activity is linear. However, departures from linearity are found when: (i) the local synaptic strengths vary, (ii) the external inputs vary, in the presence of external input to the inhibitory population, or (iii) the synchronization between oscillations of the average spike rates of two areas changes. We further show that an increase in the imaging signal can reflect a decrease in average spiking activity, in the presence of external input to the inhibitory population. Synaptic activity can also be associated with silent neuronal populations, when input to the excitatory population does not reach the activation threshold or for certain synchronizations between oscillations of two areas. In conclusion, caution should be used when interpreting neuroimaging results in terms of mean spike rates.

Serotonin Regulates Performance Nonmonotonically in a Spatial Working Memory Network

The prefrontal cortex (PFC) contains a dense network of serotonergic [serotonin, 5-hydroxytryptamine (5-HT)] axons, and endogenous 5-HT markedly modulates PFC neuronal function via several postsynaptic receptors. The therapeutic action of atypical antipsychotic drugs, acting mainly via 5-HT receptors, also suggests a role for serotonergic neurotransmission in cognitive functions. However, psychopharmacological studies have failed to find a consistent relationship between serotonergic transmission and cognitive functions of the PFC, including spatial working memory (SWM). Here, we built a computational network model to investigate 5-HT modulation of SWM in the PFC. We found that 5-HT modulates networks SWM performance nonmonotonically via 5-HT1A and 5-HT2A receptors, following an inverted U-shape. This relationship may contribute to blur the effects of serotonergic agents in previous SWM group-based behavioral studies. Our simulations also showed that errors occurring at low and high 5-HT concentrations are due to different network dynamics instabilities, suggesting that these 2 conditions can be distinguished experimentally based on their distinct dependency on experimental variables. We inferred specific predictions regarding the expected behavioral effects of serotonergic agents in 2 classic working-memory tasks. Our results underscore the relevance of identifying different error types in SWM tasks in order to reveal the association between neuromodulatory systems and SWM.

Diurnal and seasonal variation of the brain serotonin system in healthy male subjects

The mammalian circadian clock underlies both diurnal and seasonal changes in physiology, and its function is thought to be disturbed in both seasonal and non-seasonal depression. In humans, molecular imaging studies have reported seasonal changes in the serotonin system. Despite the role of the circadian clock in generating seasonal physiological changes, however, diurnal variation of serotonin receptors and transporters has never been directly studied in humans. We used positron emission tomography to examine diurnal and seasonal changes in the serotonin 5-HT1A receptor and serotonin transporter in two large cohorts of healthy male subjects, employing a cross-sectional design. In 56 subjects measured with [(11)C]WAY-100635, we observed diurnal increases in the availability of 5-HT1A receptors in the cortex. In 40 subjects measured with [(11)C]MADAM, a decrease in 5-HTT was observed in the midbrain across the day. We also found seasonal changes in the 5-HT1A receptor in serotonin projection regions, with higher availability on days with a longer duration of daylight. Our observation that serotonin receptor and transporter levels may change across the day in humans is corroborated by experimental research in rodents. These findings have important implications for understanding the relationship between the circadian and serotonin systems in both the healthy brain and in affective disorders, as well as for the design of future molecular imaging studies.

A biologically plausible model of time-scale invariant interval timing

The temporal durations between events often exert a strong influence over behavior. The details of this influence have been extensively characterized in behavioral experiments in different animal species. A remarkable feature of the data collected in these experiments is that they are often time-scale invariant. This means that response measurements obtained under intervals of different durations coincide when plotted as functions of relative time. Here we describe a biologically plausible model of an interval timing device and show that it is consistent with time-scale invariant behavior over a substantial range of interval durations. The model consists of a set of bistable units that switch from one state to the other at random times. We first use an abstract formulation of the model to derive exact expressions for some key quantities and to demonstrate time-scale invariance for any range of interval durations. We then show how the model could be implemented in the nervous system through a generic and biologically plausible mechanism. In particular, we show that any system that can display noise-driven transitions from one stable state to another can be used to implement the timing device. Our work demonstrates that a biologically plausible model can qualitatively account for a large body of data and thus provides a link between the biology and behavior of interval timing.

Regional tau deposition measured by [18F]THK5317 positron emission tomography is associated to cognition via glucose metabolism in Alzheimer’s disease

BackgroundThe recent development of tau-specific positron emission tomography (PET) tracers has allowed in vivo quantification of regional tau deposition and offers the opportunity to monitor the progression of tau pathology along with cognitive impairment. In this study, we investigated the relationships of cerebral tau deposition ([18F]THK5317-PET) and metabolism ([18F]FDG-PET) with concomitant cognitive function in patients with probable Alzheimer’s disease (AD).MethodsNine patients diagnosed with AD dementia and 11 with prodromal AD (mild cognitive impairment, amyloid-positive on [11C]PiB-PET) were included in this study. All patients underwent PET scans using each tracer, as well as episodic memory and global cognition assessment. Linear models were used to investigate the association of regional [18F]THK5317 retention and [18F]FDG uptake with cognition. The possible mediating effect of local metabolism on the relationship between tau deposition and cognitive performance was investigated using mediation analyses.ResultsSignificant negative associations were found between [18F]THK5317 regional retention, mainly in temporal regions, and both episodic memory and global cognition. Significant positive associations were found between [18F]FDG regional uptake and cognition. The association of [18F]FDG with global cognition was regionally more extensive than that of [18F]THK5317, while the opposite was observed with episodic memory, suggesting that [18F]THK5317 retention might be more sensitive than [18F]FDG regional uptake to early cognitive impairment. Finally, [18F]FDG uptake had a mediating effect on the relationship between [18F]THK5317 retention in temporal regions and global cognition.ConclusionsThese findings suggest a mediating role for local glucose metabolism in the observed association between in vivo tau deposition and concomitant cognitive impairment in AD.

Neural circuit basis of visuo-spatial working memory precision: a computational and behavioral study

The amount of information that can be retained in working memory (WM) is limited. Limitations of WM capacity have been the subject of intense research, especially in trying to specify algorithmic models for WM. Comparatively, neural circuit perspectives have barely been used to test WM limitations in behavioral experiments. Here we used a neuronal microcircuit model for visuo-spatial WM (vsWM) to investigate memory of several items. The model assumes that there is a topographic organization of the circuit responsible for spatial memory retention. This assumption leads to specific predictions, which we tested in behavioral experiments. According to the model, nearby locations should be recalled with a bias, as if the two memory traces showed attraction or repulsion during the delay period depending on distance. Another prediction is that the previously reported loss of memory precision for an increasing number of memory items (memory load) should vanish when the distances between items are controlled for. Both predictions were confirmed experimentally. Taken together, our findings provide support for a topographic neural circuit organization of vsWM, they suggest that interference between similar memories underlies some WM limitations, and they put forward a circuit-based explanation that reconciles previous conflicting results on the dependence of WM precision with load.

Serotonergic modulation of spatial working memory: predictions from a computational network model

Serotonin (5-HT) receptors of types 1A and 2A are strongly expressed in prefrontal cortex (PFC) neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM). However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5-HT and SWM (Cano-Colino et al., 2013). This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5-HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5-HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation by 5-HT receptors.

Trade-off between capacity and precision in visuospatial working memory

Limitations in the performance of working memory (WM) tasks have been characterized in terms of the number of items retained (capacity) and in terms of the precision with which the information is retained. The neural mechanisms behind these limitations are still unclear. Here we used a biological constrained computational model to study the capacity and precision of visuospatial WM. The model consists of two connected networks of spiking neurons. One network is responsible for storage of information. The other provides a nonselective excitatory input to the storage network. Simulations showed that this excitation boost could temporarily increase storage capacity but also predicted that this would be associated with a decrease in precision of the memory. This prediction was subsequently tested in a behavioral (38 participants) and fMRI (22 participants) experiment. The behavioral results confirmed the trade-off effect, and the fMRI results suggest that a frontal region might be engaged in the trial-by-trial control of WM performance. The average effects were small, but individuals differed in the amount of trade-off, and these differences correlated with the frontal activation. These results support a two-module model of WM where performance is determined both by storage capacity and by top–down influence, which can vary on a trial-by-trial basis, affecting both the capacity and precision of WM.

Behavior and neuroimaging at baseline predict individual response to combined mathematical and working memory training in children

Mathematical performance is highly correlated with several general cognitive abilities, including working memory (WM) capacity. Here we investigated the effect of numerical training using a number-line (NLT), WM training (WMT), or the combination of the two on a composite score of mathematical ability. The aim was to investigate if the combination contributed to the outcome, and determine if baseline performance or neuroimaging predict the magnitude of improvement. We randomly assigned 308, 6-year-old children to WMT, NLT, WMT + NLT or a control intervention. Overall, there was a significant effect of NLT but not WMT. The WMT + NLT was the only group that improved significantly more than the controls, although the interaction NLTxWM was non-significant. Higher WM and maths performance predicted larger benefits for WMT and NLT, respectively. Neuroimaging at baseline also contributed significant information about training gain. Different individuals showed as much as a three-fold difference in their responses to the same intervention. These results show that the impact of an intervention is highly dependent on individual characteristics of the child. If differences in responses could be used to optimize the intervention for each child, future interventions could be substantially more effective.