Large-scale design and refinement of stable proteins using sequence-only models.

Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources.

Prediction of whole-cell transcriptional response with machine learning.

Motivation: Applications in synthetic and systems biology can benefit from measuring whole-cell response to biochemical perturbations. Execution of experiments to cover all possible combinations of perturbations is infeasible. In this paper, we present the host response model (HRM), a machine learning approach that maps response of single perturbations to transcriptional response of the combination of perturbations.

Improved datasets and evaluation methods for the automatic prediction of DNA-binding proteins.

Motivation: Accurate automatic annotation of protein function relies on both innovative models and robust datasets. Due to their importance in biological processes, the identification of DNA-binding proteins directly from protein sequence has been the focus of many studies. However, the datasets used to train and evaluate these methods have suffered from substantial flaws.

The Role of Configurational Entropy in Miniprotein Stability.

Predicting protein stability is a challenge due to the many competing thermodynamic effects. Through protein design, one begins with a target structure and searches for a sequence that will fold into it. Previous work by Rocklin et al.

What is changing when: Decoding visual information in movies from human intracranial recordings.

The majority of visual recognition studies have focused on the neural responses to repeated presentations of static stimuli with abrupt and well-defined onset and offset times. In contrast, natural vision involves unique renderings of visual inputs that are continuously changing without explicitly defined temporal transitions. Here we considered commercial movies as a coarse proxy to natural vision.

Sensitivity to timing and order in human visual cortex.

Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information must progress from stage to stage very quickly. This rapid progression of information suggests that fine temporal details of the neural response may be important to the brain's encoding of visual signals.

Localization of sleep spindles, k-complexes, and vertex waves with subdural electrodes in children.

Purpose: To describe for the first time in children the localization of sleep spindles, K-complexes, and vertex waves using subdural electrodes.

Methods: We enrolled children who underwent presurgical evaluation of refractory epilepsy with subdural grid electrodes. We analyzed electroencephalogram data from subdural electrodes and simultaneous recording with Cz scalp electrode.

Short temporal asynchrony disrupts visual object recognition.

Humans can recognize objects and scenes in a small fraction of a second. The cascade of signals underlying rapid recognition might be disrupted by temporally jittering different parts of complex objects. Here we investigated the time course over which shape information can be integrated to allow for recognition of complex objects.

Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes.

The cerebral cortex needs to maintain information for long time periods while at the same time being capable of learning and adapting to changes. The degree of stability of physiological signals in the human brain in response to external stimuli over temporal scales spanning hours to days remains unclear. Here, we quantitatively assessed the stability across sessions of visually selective intracranial field potentials (IFPs) elicited by brief flashes of visual stimuli presented to 27 subjects.

Quickest detection of drug-resistant seizures: an optimal control approach.

Epilepsy affects 50 million people worldwide, and seizures in 30% of the cases remain drug resistant. This has increased interest in responsive neurostimulation, which is most effective when administered during seizure onset. We propose a novel framework for seizure onset detection that involves (i) constructing statistics from multichannel intracranial EEG (iEEG) to distinguish nonictal versus ictal states; (ii) modeling the dynamics of these statistics in each state and the state transitions; you can remove this word if there is no room.

Temporal cortex neurons encode articulated actions as slow sequences of integrated poses.

Form and motion processing pathways of the primate visual system are known to be interconnected, but there has been surprisingly little investigation of how they interact at the cellular level. Here we explore this issue with a series of three electrophysiology experiments designed to reveal the sources of action selectivity in monkey temporal cortex neurons. Monkeys discriminated between actions performed by complex, richly textured, rendered bipedal figures and hands.

Toward unmasking the dynamics of visual perception.

Fisch et al. report in this issue of Neuron the results of an investigation of the neural correlates of conscious perception. They find an early, dramatic, and long-lasting gamma response in high-level visual areas, when (and only when) a rapidly presented image is perceived.

A method for the real-time rendering of formless dot field structure-from-motion stimuli.

The perception of visual motion relies on different computations and different neural substrates than the perception of static form. It is therefore useful to have psychophysical stimuli that carry mostly or entirely motion information, conveying little or nothing about form in any single frame. Structure-from-motion stimuli can sometimes achieve this dissociation, with some examples in studies of biological motion using point-light walkers.

Effects of long-term object familiarity on event-related potentials in the monkey.

Although some change in the neural representation of an object must occur as it becomes familiar, the nature of this change is not fully understood. In humans, it has been shown that the N170-an evoked visual potential-is enhanced for classes of objects for which people have visual expertise. In this study, we explored whether monkeys show a similar modulation in event-related potential (ERP) amplitude as a result of long-term familiarity by recording ERPs with chronically implanted electrodes over extended training periods spanning many sessions.

XOR style tasks for testing visual object processing in monkeys.

Using visually complex stimuli, three monkeys learned visual exclusive-or (XOR) tasks that required detecting two way visual feature conjunctions. Monkeys with passive exposure to the test images, or prior experience, were quicker to acquire an XOR style task. Training on each pairwise comparison of the stimuli to be used in an XOR task provided nearly complete transfer when stimuli became intermingled in the full XOR task.