Can Oscillatory Alpha-Gamma Phase-Amplitude Coupling be Used to Understand and Enhance TMS Effects?

Recent applications of simultaneous scalp electroencephalography (EEG) and transcranial magnetic stimulation (TMS) suggest that adapting stimulation to underlying brain states may enhance neuroplastic effects of TMS. It is often assumed that longer-lasting effects of TMS on brain function may be mediated by phasic interactions between TMS pulses and endogenous cortical oscillatory dynamics. The mechanisms by which TMS exerts its neuromodulatory effects, however, remain unknown.

Sensory Tricks Are Associated with Higher Sleep-Related Quality of Life in Cervical Dystonia.

Background: Sensory tricks are compensatory gestures that cervical dystonia (CD) patients use to reduce abnormal neck posture and movements. Although sensory tricks are common in CD, little is known about whether trick efficacy changes over time or has effect on quality of life.

Methods: We analyzed clinical data and video recordings from 188 patients with isolated CD.

Impairments in remote memory caused by the lack of Type 2 IP receptors.

The second messenger inositol 1,4,5-trisphosphate (IP ) is paramount for signal transduction in biological cells, mediating Ca release from the endoplasmic reticulum. Of the three isoforms of IP receptors identified in the nervous system, Type 2 (IP R2) is the main isoform expressed by astrocytes. The complete lack of IP R2 in transgenic mice was shown to significantly disrupt Ca signaling in astrocytes, while leaving neuronal intracellular pathways virtually unperturbed.

Working Memory: Flexible but Finite.

There are inherent trade-offs between the flexibility and the capacity of working memory, or the ability to temporarily hold information "in mind." In a recent issue of Neuron, Bouchacourt and Buschman (2019) present a new model of working memory that demonstrates how coordinated activity between specialized sensory networks and flexible higher-order networks may support these competing constraints.

Spontaneity and diversity of movement to music are not uniquely human.

Spontaneous movement to music occurs in every human culture and is a foundation of dance [1]. This response to music is absent in most species (including monkeys), yet it occurs in parrots, perhaps because they (like humans, and unlike monkeys) are vocal learners whose brains contain strong auditory-motor connections, conferring sophisticated audiomotor processing abilities [2,3]. Previous research has shown that parrots can bob their heads or lift their feet in synchrony with a musical beat [2,3], but humans move to music using a wide variety of movements and body parts.

Striatal functional connectivity in chronic ketamine users: a pilot study.

: The striatum supports motivated behavior and impulse control. Altered striatal activation and connectivity has been observed in link with impulse control dysfunction in individuals with drug addiction.: We examined how resting state functional connectivity (rsFC) of the striatum is altered as a result of chronic ketamine misuse.

Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation.

A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking.

Mismatch negativity reveals plasticity in cortical dynamics after 1-hour of auditory training exercises.

Background: Impaired sensory processing contributes to deficits in cognitive and psychosocial functioning in individuals with schizophrenia (SZ). Mismatch Negativity (MMN), an event-related potential (ERP) index of sensory discrimination associated with cognitive and psychosocial functioning, is a candidate biomarker of auditory discrimination and thus possibly of changes following auditory-based Targeted Cognitive Training (TCT). Here we evaluated the acute effect of TCT on cortical processes supporting auditory discrimination.

Computer Vision Technology in the Differential Diagnosis of Cushing's Syndrome.

Objective: Cushing's syndrome is a rare disease characterized by clinical features that show morphological similarity with the metabolic syndrome. Distinguishing these diseases in clinical practice is challenging. We have previously shown that computer vision technology can be a potentially useful diagnostic tool in Cushing's syndrome.

Attenuated mismatch negativity in patients with first-episode antipsychotic-naive schizophrenia using a source-resolved method.

Background: Mismatch negativity (MMN) is a measure of pre-attentive auditory information processing related to change detection. Traditional scalp-level EEG methods consistently find attenuated MMN in patients with chronic but not first-episode schizophrenia. In the current paper, we use a source-resolved method to assess MMN and hypothesize that more subtle changes can be identified with this analysis method.

Eye fixation-related fronto-parietal neural network correlates of memory retrieval.

Eye movements are considered to be informative with regard to the underlying cognitive processes of human beings. Previous studies have reported that eye movements are associated with which scientific concepts are retrieved correctly. Moreover, other studies have also suggested that eye movements involve the cooperative activity of the human brain's fronto-parietal circuits.

Dissecting the Neural Focus of Attention Reveals Distinct Processes for Spatial Attention and Object-Based Storage in Visual Working Memory.

Complex cognition relies on both on-line representations in working memory (WM), said to reside in the focus of attention, and passive off-line representations of related information. Here, we dissected the focus of attention by showing that distinct neural signals index the on-line storage of objects and sustained spatial attention. We recorded electroencephalogram (EEG) activity during two tasks that employed identical stimulus displays but varied the relative demands for object storage and spatial attention.

Nonlinear dynamics underlying sensory processing dysfunction in schizophrenia.

Natural systems, including the brain, often seem chaotic, since they are typically driven by complex nonlinear dynamical processes. Disruption in the fluid coordination of multiple brain regions contributes to impairments in information processing and the constellation of symptoms observed in neuropsychiatric disorders. Schizophrenia (SZ), one of the most debilitating mental illnesses, is thought to arise, in part, from such a network dysfunction, leading to impaired auditory information processing as well as cognitive and psychosocial deficits.

Preventing a Thought from Coming to Mind Elicits Increased Right Frontal Beta Just as Stopping Action Does.

In the stop-signal task, an electrophysiological signature of action-stopping is increased early right frontal beta band power for successful vs. failed stop trials. Here we tested whether the requirement to stop an unwanted thought from coming to mind also elicits this signature.

A process account of the uncontrolled manifold structure of joint space variance in pointing movements.

In many situations, the human movement system has more degrees of freedom than needed to achieve a given movement task. Martin et al. (Neural Comput 21(5):1371-1414, 2009) accounted for signatures of such redundancy like self-motion and motor equivalence in a process model in which a neural oscillator generated timed end-effector virtual trajectories that a neural dynamics transformed into joint virtual trajectories while decoupling task-relevant and task-irrelevant combinations of joint angles.

Delay differential analysis for dynamical sleep spindle detection.

Background: Sleep spindles are involved in memory consolidation and other cognitive functions. Numerous automated methods for detection of spindles have been proposed; most of these rely on spectral analysis in some form. However, none of these approaches are ideal, and novel approaches to the problem could provide additional insights.

A visual working memory dataset collection with bootstrap Independent Component Analysis for comparison of electroencephalographic preprocessing pipelines.

Here we present an electroencephalographic (EEG) collection of 71-channel datasets recorded from 14 subjects (7 males, 7 females, aged 20-40 years) while performing a visual working memory task with a T set of 150 Independent Component Analysis (ICA) decompositions by Extended Infomax using RELICA, each on a bootstrap resampling of the data. These data are linked to the paper "Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition" [1]. Independent components (ICs) are clustered within subject and thereby associated with a quality index (QIc) measure of their stability to data resampling.

Global Convergence of the (1 + 1) Evolution Strategy to a Critical Point.

We establish global convergence of the (1 + 1) evolution strategy, that is, convergence to a critical point independent of the initial state. More precisely, we show the existence of a critical limit point, using a suitable extension of the notion of a critical point to measurable functions. At its core, the analysis is based on a novel progress guarantee for elitist, rank-based evolutionary algorithms.

Corrigendum: Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.

[This corrects the article DOI: 10.3389/fnins.2018.

Brain Zaps: An Underappreciated Symptom of Antidepressant Discontinuation.

Objective: To describe the characteristics of the electrical phenomena of antidepressant discontinuation syndrome known as brain zaps and their effect on quality of life.

Methods: We examined 595 unsolicited posts made by individuals frequenting a popular lay mental health website. The site was accessed between December 13, 2014, and December 12, 2016, and its content was saved in a text document.

Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.

Neuromorphic engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems. The brain has evolved over billions of years to solve difficult engineering problems by using efficient, parallel, low-power computation. The goal of NE is to design systems capable of brain-like computation.

Briefly Flashed Scenes Can Be Stored in Long-Term Memory.

The capacity of human memory is impressive. Previous reports have shown that when asked to memorize images, participants can recognize several thousands of visual objects in great details even with a single viewing of a few seconds per image. In this experiment, we tested recognition performance for natural scenes that participants saw for 20 ms only once (untrained group) or 22 times over many days (trained group) in an unrelated task.

Unraveling the spatiotemporal brain dynamics during a simulated reach-to-eat task.

The reach-to-eat task involves a sequence of action components including looking, reaching, grasping, and feeding. While cortical representations of individual action components have been mapped in human functional magnetic resonance imaging (fMRI) studies, little is known about the continuous spatiotemporal dynamics among these representations during the reach-to-eat task. In a periodic event-related fMRI experiment, subjects were scanned while they reached toward a food image, grasped the virtual food, and brought it to their mouth within each 16-s cycle.

Deep Supervised Learning Using Local Errors.

Error backpropagation is a highly effective mechanism for learning high-quality hierarchical features in deep networks. Updating the features or weights in one layer, however, requires waiting for the propagation of error signals from higher layers. Learning using delayed and non-local errors makes it hard to reconcile backpropagation with the learning mechanisms observed in biological neural networks as it requires the neurons to maintain a memory of the input long enough until the higher-layer errors arrive.