Topic: principal component analysis

Early-career industrial chemists present research from pharmaceutical, biotechnology and agrochemical settings, connecting academic chemistry with the practical constraints of industrial discovery and development. The programme examines digital route design for KRAS inhibitors, principal-component analysis of pharmaceutical oils, antibody modification by sulfur(VI)-fluoride exchange, photochemical oligonucleotide synthesis, flow photoredox chemistry, molecular-glue synthesis and ERAP1 inhibitor discovery. A closing keynote considers digital strategy in industrial chemistry. Talks include discu

Since the advent of large-scale extracellular recordings in neuroscience and the widespread adoption of neural population frameworks, there is an increased need to achieve efficient decoding of task-relevant behavioral information from neural dynamics. The most prevalent methods to uncover task-related topologies in population dynamics, often approximated as neural manifolds, are linear dimensionality reduction methods such as principal component analysis (PCA). These techniques, however, find large-variance subspaces within which to embed neural manifolds and such embeddings do not necessaril

Recent work has shown that global signals related to arousal are embedded in the population activity of cortical neurons. In mice, slow fluctuations in neural activity are correlated with whisking and locomotion, while in monkeys a similar pattern has been identified (termed “slow drift”) that is: 1) present in visual/prefrontal cortices; 2) correlated with pupil size; and 3) associated with performance on cognitive tasks. These results demonstrate that changes in brain state are represented in the coordinated activity of cortical neurons. However, it is unknown if these fluctuations are also

The generating mechanism for the gyrification of the mammalian cerebral cortex remains a central open question in neuroscience. Although many models have been proposed over the years, very few were able to provide empirically testable predictions. In this paper, we assume a model in which the cortex folds for all species of mammals according to a simple mechanism of effective free energy minimization of a growing self-avoiding surface subjected to inhomogeneous bulk stresses to derive a new set of morphological variables to express cortical morphology. In terms of these new variables, we seek

While neural population recordings are increasingly high-dimensional, the bulk of recorded activities is usually structured along lower-dimensional manifolds. These manifolds often appear to be nonlinear, so that linear dimensionality reduction methods such as principal component analysis (PCA) yield embedding dimensionalities (ED) that are much higher than the intrinsic dimensionality (ID) of the manifold [Jazayeri, Ostojic, 2021]. Across datasets, the embedding often generates components that resemble higher-order functions of each other, or ‘higher-order components’ (HOCs), thus suggesting

Despite the large number of active neurons in the cortex, the activity of neuronal populations is expected to lie on a low-dimensional manifold for different brain regions [1]. Variants of principal component analysis (PCA) are commonly used to assess this manifold. However, these methods are limited by the assumption that the data follows a Gaussian distribution and neglect additional features such as the curvature of the manifold. Hence, their performance as generative models tends to be subpar. To construct a generative model that entirely learns the statistics of neural activity with no a

Accumulating evidence from electrocorticogram (ECoG) recordings and imaging challenge traditional views of brain oscillations as spatially stationary periodic sources. Understanding the spatio-temporal dynamics of cortical activity requires novel measurement and analysis methodologies. We recorded broadband local field potential (LFP) across the whole neocortex in freely behaving rats using high-density flexible surface arrays using active transistors. 3D tracking and spatio-spectral analysis of recordings over long sessions enabled automatic and accurate brain and behavioral states segmentati

Psychedelics (5-HT2AR agonists) show great promise in treating mental disorders but their effects on neuronal population activity are not clear. Latent dimensions identified by Principal Component Analysis (PCA) capture the dynamics of this interrelated neuronal population activity. We asked whether latent dimensions emerge or disappear as a result of psychedelic administration (acute), and across other naturally occurring brain state transitions (sleep, arousal). Contrastive PCA (cPCA) [Abid et al. (2018), Nature Comm.] was applied to spontaneous brain activity recordings in rodents before

Convolutional neural networks (CNNs) provide a generalizable architecture for encoding models that predict neural activity evoked by natural sounds with much greater accuracy than other established models. However, the complexity of CNNs makes it difficult to discern the computational properties that support their improved predictive power. We used a combination of local linear approximation and dimensionality reduction to measure the tuning subspace captured by a CNN. Single-unit data was recorded using microelectrode arrays from primary auditory cortex (A1) of awake, passively listening ferr

Anxiety disorders are marked by intense and chronic worrying along other symptoms, including an attentional bias towards negative valence. Preclinical models have linked the activity of the anterior insular cortex (or insula) to both anxiety and negative valence[1]. We recently showed an increased dopamine release onto anterior insula neurons expressing type-1 dopamine receptors (D1R) during anxiogenic events and during aversive stimuli[2]. We also revealed that both systemic and intra-anterior insula D1R activation heighten anxiety-like behaviors[2]. However, the impact of D1R on anterior ins

Prevalent dynamical systems view posits that cortical preparatory activity seeds temporal evolution to generate movement, but it remains unclear the neural computation that preparatory activity develops to initialize movements in dynamic sensorimotor contingency, such as interception of motion targets. In the present study, we analyzed neural population dynamics recorded from motor cortex via Utah array while two macaques performed a delayed reach toward a target either static or moving circularly. Principal component analysis (PCA) showed that the directional tuning of preparatory latent fact

Our attention falters, which is commonly known as ‘attentional blink’ (AB), after spotting a target; as a result, the subsequent target often goes unnoticed. Attentional demand also affects the size of the pupillary aperture. In previous studies, differential pupillary dilation averaged across trials within a short critical epoch distinguished AB. In contrast, we examined the pupil dynamics on a trial-by-trial basis. Healthy young volunteers performed a task, wherein two visual targets embedded in a series of distractors were presented in a rapid succession. The participants were asked to iden

Resting-state functional connectivity (FC) has received considerable attention in the study of brain-behavior associations. However, the low generalizability of brain-behavior studies is a common challenge due to the limited sample-to-feature ratio. In this study, we aimed to improve the generalizability of brain-behavior associations in resting-state FC by focusing on diverse and stable edges, i.e., edges that show both high between-subject and low within-subject variability. We used resting-state data from 1003 participants with multiple fMRI sessions from the Human Connectome Project to gro

It has been hypothesized that feedback connections originating from motor areas exert top-down influences on the posterior parietal cortex during visuomotor behavior. However, a comprehensive understanding of the dynamic reciprocal flow of information within the fronto-parietal network is still lacking. This study aims to investigate whether fronto-parietal communication can be modulated by cognitive components of motor preparation such as anticipation of the appearance of a visual target. To this end, two rhesus macaques were trained in a visuomotor sequential reaching task. Critically, the s

The hippocampal representation of space can change on a time scale of minutes as a result of goal learning. However, the link between behaviour performance and the representation of other variables in the hippocampus is less clear, especially at longer time scales. To investigate this, we recorded the activity of hippocampal CA1 neurons of rats using in vivo electrophysiology, as they learned a space-context association task over the course of 5 days. To assess the representation of different task-related variables such as position, reward, movement direction or context in the population activ

Cortical local fields and oscillatory events are usually analyzed by estimating their spectral characteristics, but these approaches have limited ability to extract all the information carried by the signal. Applying dimensionality reduction methods such as principal component analysis can improve classification performance, help discover hidden patterns, and create new features. We aimed to assemble a multi-step analysis workflow that can transform oscillatory LFP activity into a statistical representation. After filtering and downsampling the LFP signal, waveform segments for the events of i

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by motor neuron death, leading to motor paralysis and cognitive and behavioural disorders. In clinical trials, ALS patients are stratified by disease stage, whereas in preclinical studies, animals are recruited based solely on age, neglecting individual disease progression. Additionally, both ALS onset and progression are influenced by sex, a factor often mirrored in animal models. This mismatch might contribute to the frequent failures of translating preclinical data to clinical success, suggesting the impo