A group model for stable multi-subject ICA on fMRI datasets

Spatial Independent Component Analysis (ICA) is an increasingly used data-driven method to analyze functional Magnetic Resonance Imaging (fMRI) data. To date, it has been used to extract sets of mutually correlated brain regions without prior information on the time course of these regions. Some of these sets of regions, interpreted as functional networks, have recently been used to provide markers of brain diseases and open the road to paradigm-free population comparisons. Such group studies raise the question of modeling subject variability within ICA: how can the patterns representative of a group be modeled and estimated via ICA for reliable inter-group comparisons? In this paper, we propose a hierarchical model for patterns in multi-subject fMRI datasets, akin to mixed-effect group models used in linear-model-based analysis. We introduce an estimation procedure, CanICA (Canonical ICA), based on i) probabilistic dimension reduction of the individual data, ii) canonical correlation analysis to identify a data subspace common to the group iii) ICA-based pattern extraction. In addition, we introduce a procedure based on cross-validation to quantify the stability of ICA patterns at the level of the group. We compare our method with state-of-the-art multi-subject fMRI ICA methods and show that the features extracted using our procedure are more reproducible at the group level on two datasets of 12 healthy controls: a resting-state and a functional localizer study

Synchronisation in the prefrontal-striatal circuit tracks behavioural choice in a go no-go task in rats

Rodent striatum is involved in sensory-motor transformations and reward-related learning. Lesion studies suggest dorsolateral striatum, dorsomedial striatum, and nucleus accumbens underlie stimulus-response transformations, goal-directed behaviour and reward expectation respectively. In addition, prefrontal inputs likely control these functions. Here we set out to study how reward-driven behaviour is mediated by the coordinated activity of these structures in the intact brain. We implemented a discrimination task requiring rats to either respond or suppress responding on a lever after the presentation of auditory cues in order to obtain rewards. Single unit activity in the striatal subregions and prelimbic cortex was recorded using tetrode arrays. Striatal units showed strong onset responses to auditory cues paired with an opportunity to obtain reward. Cue onset responses in both striatum and cortex were significantly modulated by previous errors suggesting a role of these structures in maintaining appropriate motivation or action selection during ongoing behaviour. Furthermore, failure to respond to the reward-paired tones was associated with higher pre-trial coherence among striatal subregions and between cortex and striatum suggesting a task-negative corticostriatal network whose activity may be suppressed to enable processing of reward-predictive cues. Our findings highlight that coordinated activity in a distributed network including both prelimbic cortex and multiple striatal regions underlies reward-related decisions

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis

Covert Waking Brain Activity Reveals Instantaneous Sleep Depth

The neural correlates of the wake-sleep continuum remain incompletely understood, limiting the development of adaptive drug delivery systems for promoting sleep maintenance. The most useful measure for resolving early positions along this continuum is the alpha oscillation, an 8–13 Hz electroencephalographic rhythm prominent over posterior scalp locations. The brain activation signature of wakefulness, alpha expression discloses immediate levels of alertness and dissipates in concert with fading awareness as sleep begins. This brain activity pattern, however, is largely ignored once sleep begins. Here we show that the intensity of spectral power in the alpha band actually continues to disclose instantaneous responsiveness to noise—a measure of sleep depth—throughout a night of sleep. By systematically challenging sleep with realistic and varied acoustic disruption, we found that sleepers exhibited markedly greater sensitivity to sounds during moments of elevated alpha expression. This result demonstrates that alpha power is not a binary marker of the transition between sleep and wakefulness, but carries rich information about immediate sleep stability. Further, it shows that an empirical and ecologically relevant form of sleep depth is revealed in real-time by EEG spectral content in the alpha band, a measure that affords prediction on the order of minutes. This signal, which transcends the boundaries of classical sleep stages, could potentially be used for real-time feedback to novel, adaptive drug delivery systems for inducing sleep

Identification of Early Intermediates of Caspase Activation Using Selective Inhibitors and Activity-Based Probes

Caspases are cysteine proteases that are key effectors in apoptotic cell death. Currently, there is a lack of tools that can be used to monitor the regulation of specific caspases in the context of distinct apoptotic programs. We describe the development of highly selective inhibitors and active site probes and their applications to directly monitor executioner (caspase-3 and -7) and initiator (caspase-8 and -9) caspase activity. Specifically, these reagents were used to dissect the kinetics of caspase activation upon stimulation of apoptosis in cell-free extracts and intact cells. These studies identified a full-length caspase-7 intermediate that becomes catalytically activated early in the pathway and whose further processing is mediated by mature executioner caspases rather than initiator caspases. This form also shows distinct inhibitor sensitivity compared to processed caspase-7. Our data suggest that caspase-7 activation proceeds through a previously uncharacterized intermediate that is formed without cleavage of the intact zymogen

Alternative splicing converts STIM2 from an activator to an inhibitor of store-operated calcium channels

Store-operated calcium entry (SOCE) regulates a wide variety of essential cellular functions. SOCE is mediated by STIM1 and STIM2, which sense depletion of ER Ca2+ stores and activate Orai channels in the plasma membrane. Although the amplitude and dynamics of SOCE are considered important determinants of Ca2+-dependent responses, the underlying modulatory mechanisms are unclear. In this paper, we identify STIM2??, a highly conserved alternatively spliced isoform of STIM2, which, in contrast to all known STIM isoforms, is a potent inhibitor of SOCE. Although STIM2?? does not by itself strongly bind Orai1, it is recruited to Orai1 channels by forming heterodimers with other STIM isoforms. Analysis of STIM2?? mutants and Orai1-STIM2?? chimeras suggested that it actively inhibits SOCE through a sequence-specific allosteric interaction with Orai1. Our results reveal a previously unrecognized functional flexibility in the STIM protein family by which alternative splicing creates negative and positive regulators of SOCE to shape the amplitude and dynamics of Ca2+ signals.open

Probabilistic Computation in Human Perception under Variability in Encoding Precision

A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain’s remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making