Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias

<div><p>The activity of neural populations in the brains of humans and animals can exhibit vastly different spatial patterns when faced with different tasks or environmental stimuli. The degrees of similarity between these neural activity patterns in response to different events are used to characterize the representational structure of cognitive states in a neural population. The dominant methods of investigating this similarity structure first estimate neural activity patterns from noisy neural imaging data using linear regression, and then examine the similarity between the estimated patterns. Here, we show that this approach introduces spurious bias structure in the resulting similarity matrix, in particular when applied to fMRI data. This problem is especially severe when the signal-to-noise ratio is low and in cases where experimental conditions cannot be fully randomized in a task. We propose Bayesian Representational Similarity Analysis (BRSA), an alternative method for computing representational similarity, in which we treat the covariance structure of neural activity patterns as a hyper-parameter in a generative model of the neural data. By marginalizing over the unknown activity patterns, we can directly estimate this covariance structure from imaging data. This method offers significant reductions in bias and allows estimation of neural representational similarity with previously unattained levels of precision at low signal-to-noise ratio, without losing the possibility of deriving an interpretable distance measure from the estimated similarity. The method is closely related to Pattern Component Model (PCM), but instead of modeling the estimated neural patterns as in PCM, BRSA models the imaging data directly and is suited for analyzing data in which the order of task conditions is not fully counterbalanced. The probabilistic framework allows for jointly analyzing data from a group of participants. The method can also simultaneously estimate a signal-to-noise ratio map that shows where the learned representational structure is supported more strongly. Both this map and the learned covariance matrix can be used as a structured prior for maximum <i>a posteriori</i> estimation of neural activity patterns, which can be further used for fMRI decoding. Our method therefore paves the way towards a more unified and principled analysis of neural representations underlying fMRI signals. We make our tool freely available in Brain Imaging Analysis Kit (BrainIAK).</p></div

A Reflection Principle for the Control of Molecular Photodissociation in Solids: Model Simulation for F2 in Ar

Laser pulse induced photodissociation of molecules in rare gas solids is investigated by representative quantum wavepackets or classical trajectories which are directed towards, or away from cage exits, yielding dominant photodissociation into different neighbouring cages. The directionality is determined by a sequence of reflections inside the relief provided by the slopes of the potential energy surface of the excited system, which in turn depend on the initial preparation of the matrix isolated system, e.g. by laser pulses with different frequencies or by vibrational pre-excitation of the cage atoms. This reflection principle is demonstrated for a simple, two-dimensional model of F2 in Ar

Neural Signatures of Prediction Errors in a Decision-Making Task are Modulated by Action Execution Failures

Decisions must be implemented through actions, and actions are prone to error. As such, when an expected outcome is not obtained, an individual should be sensitive to not only whether the choice itself was suboptimal but also whether the action required to indicate that choice was executed successfully. The intelligent assignment of credit to action execution versus action selection has clear ecological utility for the learner. To explore this, we used a modified version of a classic reinforcement learning task in which feedback indicated whether negative prediction errors were, or were not, associated with execution errors. Using fMRI, we asked if prediction error computations in the human striatum, a key substrate in reinforcement learning and decision making, are modulated when a failure in action execution results in the negative outcome. Participants were more tolerant of non-rewarded outcomes when these resulted from execution errors versus when execution was successful, but reward was withheld. Consistent with this behavior, a model-driven analysis of neural activity revealed an attenuation of the signal associated with negative reward prediction errors in the striatum following execution failures. These results converge with other lines of evidence suggesting that prediction errors in the mesostriatal dopamine system integrate high-level information during the evaluation of instantaneous reward outcomes

Photodissociation Dynamics of Molecular Fluorine in an Argon Matrix Induced by Ultrashort Laser Pulses

The electronic excitation induced by ultrashort laser pulses and the subsequent photodissociation dynamics of molecular fluorine in an argon matrix are studied. The interactions of photofragments and host atoms are modeled using a Diatomics-In-Molecule Hamiltonian. Two types of methods are compared: Quantum-classical simulations where the nuclei are treated classically, with surface-hopping algorithms to describe either radiative or non-radiative transitions between different electronic states. Fully quantum-mechanical simulations, but for a model system of reduced dimensionality, in which the two most essential degrees of freedom are considered. Some of the main results are: The sequential energy transfer events from the photoexcited F2 into the lattice modes are such that the ``reduced dimensionality'' model is valid for the first 200 fs. This, in turn, allows us to use the quantum results to investigate the details of the excitation process with short laser pulses. Thus, it also serves as a reference for the quantum-classical ``surface hopping'' model of the excitation process. Moreover, it supports the validity of a laser pulse control strategy developed on the basis of the ``reduced dimensionality'' model. Both in the quantum and quantum-classical simulations, the separation of the F atoms following photodissociation does not exceed 20 bohr. The cage exit mechanisms appear qualitatively similar in the two sets of simulations but quantum effects are quantitatively important. Nonlinear effects are important in determining the photoexcitation yield. In summary, this paper demonstrates that quantum-classical simulations combined with reduced dimensionality quantum calculations can be a powerful approach to the analysis and control of the dynamics of complex systems

The taste of the pandemic—contemporary review on the current state of research on gustation in coronavirus disease 2019 (COVID‐19)

Subjectively perceived impairment of taste is a common and distinct symptom of coronavirus disease 2019 (COVID-19). Large meta-analyses identified this symptom in approximately 50% of cases. However, this high prevalence is not supported by blinded and validated psychophysical gustatory testing, which showed a much lower prevalence in up to 26% of patients. This discrepancy may be due to misinterpretation of impaired retronasal olfaction as gustatory dysfunction. In addition, we hypothesized that COVID-19–associated hyposmia is involved in the decrease of gustatory function, as found for hyposmia of different origin. This indirect mechanism would be based on the central-nervous mutual amplification between the chemical senses, which fails in COVID-19–associated olfactory loss. However, further research is necessary on how severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) may directly impair the gustatory pathway as well as its subjective perception

Esophageal muscle physiology and morphogenesis require assembly of a collagen XIX–rich basement membrane zone

Collagen XIX is an extremely rare extracellular matrix component that localizes to basement membrane zones and is transiently expressed by differentiating muscle cells. Characterization of mice harboring null and structural mutations of the collagen XIX (Col19a1) gene has revealed the critical contribution of this matrix protein to muscle physiology and differentiation. The phenotype includes smooth muscle motor dysfunction and hypertensive sphincter resulting from impaired swallowing-induced, nitric oxide–dependent relaxation of the sphincteric muscle. Muscle dysfunction was correlated with a disorganized matrix and a normal complement of enteric neurons and interstitial cells of Cajal. Mice without collagen XIX exhibit an additional defect, namely impaired smooth-to-skeletal muscle cell conversion in the abdominal segment of the esophagus. This developmental abnormality was accounted for by failed activation of myogenic regulatory factors that normally drive esophageal muscle transdifferentiation. Therefore, these findings identify collagen XIX as the first structural determinant of sphincteric muscle function, and as the first extrinsic factor of skeletal myogenesis in the murine esophagus

Tacrolimus-Induced Intestinal Angioedema: Diagnosis by Capsule Endoscopy

Small intestinal angioedema has been reported with angiotensin converting enzyme inhibitors therapy, but not in implanted patients treated with tacrolimus. We present a kidney transplanted patient, hospitalized with severe diarrhea, diagnosed with tacrolimus-induced intestinal angioedema with abdominal computerized tomography and capsule endoscopy. To the best of our knowledge this is the first described case of tacrolimus-induced small bowel angioedema diagnosed with capsule endoscopy