Sorting nexin 5 mediates virus-induced autophagy and immunity.

Autophagy, a process of degradation that occurs via the lysosomal pathway, has an essential role in multiple aspects of immunity, including immune system development, regulation of innate and adaptive immune and inflammatory responses, selective degradation of intracellular microorganisms, and host protection against infectious diseases1,2. Autophagy is known to be induced by stimuli such as nutrient deprivation and suppression of mTOR, but little is known about how autophagosomal biogenesis is initiated in mammalian cells in response to viral infection. Here, using genome-wide short interfering RNA screens, we find that the endosomal protein sorting nexin 5 (SNX5)3,4 is essential for virus-induced, but not for basal, stress- or endosome-induced, autophagy. We show that SNX5 deletion increases cellular susceptibility to viral infection in vitro, and that Snx5 knockout in mice enhances lethality after infection with several human viruses. Mechanistically, SNX5 interacts with beclin 1 and ATG14-containing class III phosphatidylinositol-3-kinase (PI3KC3) complex 1 (PI3KC3-C1), increases the lipid kinase activity of purified PI3KC3-C1, and is required for endosomal generation of phosphatidylinositol-3-phosphate (PtdIns(3)P) and recruitment of the PtdIns(3)P-binding protein WIPI2 to virion-containing endosomes. These findings identify a context- and organelle-specific mechanism-SNX5-dependent PI3KC3-C1 activation at endosomes-for initiation of autophagy during viral infection.

Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

Information flow in brain networks is reflected in local field potentials that have both periodic and aperiodic components. The 1/fχ aperiodic component of the power spectra tracks arousal and correlates with other physiological and pathophysiological states. Here we explored the aperiodic activity in the human thalamus and basal ganglia in relation to simultaneously recorded cortical activity. We elaborated on the parameterization of the aperiodic component implemented by specparam (formerly known as FOOOF) to avoid parameter unidentifiability and to obtain independent and more easily interpretable parameters. This allowed us to seamlessly fit spectra with and without an aperiodic knee, a parameter that captures a change in the slope of the aperiodic component. We found that the cortical aperiodic exponent χ, which reflects the decay of the aperiodic component with frequency, is correlated with Parkinson's disease symptom severity. Interestingly, no aperiodic knee was detected from the thalamus, the pallidum, or the subthalamic nucleus, which exhibited an aperiodic exponent significantly lower than in cortex. These differences were replicated in epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences. SIGNIFICANCE STATEMENT: The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

Intracranial Electroencephalography and Deep Neural Networks Reveal Shared Substrates for Representations of Face Identity and Expressions.

According to a classical view of face perception (Bruce and Young, 1986; Haxby et al., 2000), face identity and facial expression recognition are performed by separate neural substrates (ventral and lateral temporal face-selective regions, respectively). However, recent studies challenge this view, showing that expression valence can also be decoded from ventral regions (Skerry and Saxe, 2014; Li et al., 2019), and identity from lateral regions (Anzellotti and Caramazza, 2017). These findings could be reconciled with the classical view if regions specialized for one task (either identity or expression) contain a small amount of information for the other task (that enables above-chance decoding). In this case, we would expect representations in lateral regions to be more similar to representations in deep convolutional neural networks (DCNNs) trained to recognize facial expression than to representations in DCNNs trained to recognize face identity (the converse should hold for ventral regions). We tested this hypothesis by analyzing neural responses to faces varying in identity and expression. Representational dissimilarity matrices (RDMs) computed from human intracranial recordings (n = 11 adults; 7 females) were compared with RDMs from DCNNs trained to label either identity or expression. We found that RDMs from DCNNs trained to recognize identity correlated with intracranial recordings more strongly in all regions tested-even in regions classically hypothesized to be specialized for expression. These results deviate from the classical view, suggesting that face-selective ventral and lateral regions contribute to the representation of both identity and expression.SIGNIFICANCE STATEMENT Previous work proposed that separate brain regions are specialized for the recognition of face identity and facial expression. However, identity and expression recognition mechanisms might share common brain regions instead. We tested these alternatives using deep neural networks and intracranial recordings from face-selective brain regions. Deep neural networks trained to recognize identity and networks trained to recognize expression learned representations that correlate with neural recordings. Identity-trained representations correlated with intracranial recordings more strongly in all regions tested, including regions hypothesized to be expression specialized in the classical hypothesis. These findings support the view that identity and expression recognition rely on common brain regions. This discovery may require reevaluation of the roles that the ventral and lateral neural pathways play in processing socially relevant stimuli.

Shiftless inhibits flavivirus replication in vitro and is neuroprotective in a mouse model of Zika virus pathogenesis.

Flaviviruses such as Zika virus and West Nile virus have the potential to cause severe neuropathology if they invade the central nervous system. The type I interferon response is well characterized as contributing to control of flavivirus-induced neuropathogenesis. However, the interferon-stimulated gene (ISG) effectors that confer these neuroprotective effects are less well studied. Here, we used an ISG expression screen to identify Shiftless (SHFL, C19orf66) as a potent inhibitor of diverse positive-stranded RNA viruses, including multiple members of the Flaviviridae (Zika, West Nile, dengue, yellow fever, and hepatitis C viruses). In cultured cells, SHFL functions as a viral RNA-binding protein that inhibits viral replication at a step after primary translation of the incoming genome. The murine ortholog, Shfl, is expressed constitutively in multiple tissues, including the central nervous system. In a mouse model of Zika virus infection, Shfl-/- knockout mice exhibit reduced survival, exacerbated neuropathological outcomes, and increased viral replication in the brain and spinal cord. These studies demonstrate that Shfl is an important antiviral effector that contributes to host protection from Zika virus infection and virus-induced neuropathological disease.

Lateralized and Region-Specific Thalamic Processing of Lexical Status during Reading Aloud.

To explore whether the thalamus participates in lexical status (word vs nonword) processing during spoken word production, we recorded local field potentials from the ventral lateral thalamus in 11 essential tremor patients (three females) undergoing thalamic deep-brain stimulation lead implantation during a visually cued word and nonword reading-aloud task. We observed task-related beta (12-30 Hz) activity decreases that were preferentially time locked to stimulus presentation, and broadband gamma (70-150 Hz) activity increases, which are thought to index increased multiunit spiking activity, occurring shortly before and predominantly time locked to speech onset. We further found that thalamic beta activity decreases bilaterally were greater when nonwords were read, demonstrating bilateral sensitivity to lexical status that likely reflects the tracking of task effort; in contrast, greater nonword-related increases in broadband gamma activity were observed only on the left, demonstrating lateralization of thalamic broadband gamma selectivity for lexical status. In addition, this lateralized lexicality effect on broadband gamma activity was strongest in more anterior thalamic locations, regions which are more likely to receive basal ganglia than cerebellar afferents and have extensive connections with prefrontal cortex including Brodmann's areas 44 and 45, regions consistently associated with grapheme-to-phoneme conversions. These results demonstrate active thalamic participation in reading aloud and provide direct evidence from intracranial thalamic recordings for the lateralization and topography of subcortical lexical status processing.SIGNIFICANCE STATEMENT Despite the corticocentric focus of most experimental work and accompanying models, there is increasing recognition of the role of subcortical structures in speech and language. Using local field potential recordings in neurosurgical patients, we demonstrated that the thalamus participates in lexical status (word vs nonword) processing during spoken word production, in a lateralized and region-specific manner. These results provide direct evidence from intracranial thalamic recordings for the lateralization and topography of subcortical lexical status processing.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Developmental changes in functional connectivity between the prefrontal cortex and amygdala following fear extinction.

The amygdala and prefrontal cortex (PFC) undergo dramatic changes in structure, function, and regional connectivity in early life, ultimately stabilizing in early adulthood. Pathways between these two structures underlie many forms of emotional learning, including the extinction of conditioned fear. Here we sought to characterize changes in extinction-related medial PFC (mPFC) â†’ amygdala functional connectivity across development that might explain adolescent impairments in extinction. The retrograde tracer Fluorogold was infused into the amygdala of postnatal day (P)22-23 (juvenile), P31-32 (adolescent), or ≥ P69 (adult) rats, which were then exposed to fear conditioning and extinction training. Brains were collected following extinction or context exposure and processed for expression of pMAPK (as a marker of learning-dependent plasticity) in prelimbic (PL) and infralimbic (IL) amygdala-projecting neurons. Consistent with previous findings, amygdala-projecting mPFC neurons were located primarily in layers (L)II/III and V of the mPFC. We noted that mPFC LII/III projected predominantly to the ipsilateral basolateral amygdala, whereas LV projected bilaterally and targeted multiple amygdalar nuclei. Extinction was not associated with changes in extinction-related plasticity in the PL-amygdala pathways in any age group. No changes were seen in LII/III of the IL, but extinction-related plasticity in LV amygdala-projecting IL neurons decreased linearly across development. These findings suggest that extinction-related functional connectivity between the IL and the amygdala undergoes fundamental changes across development that may contribute to alterations in fear suppression across development.

Amygdala DCX and blood Cdk14 are implicated as cross-species indicators of individual differences in fear, extinction, and resilience to trauma exposure.

Doublecortin (DCX) has long been implicated in, and employed as a marker for, neurogenesis, yet little is known about its function in non-neurogenic brain regions, including the amygdala. This study sought first to explore, in rodents, whether fear learning and extinction modulate amygdala DCX expression and, second, to assess the utility of peripheral DCX correlates as predictive biomarkers of trauma response in rodents and humans. Pavlovian conditioning was found to alter DCX protein levels in mice 24 h later, resulting in higher DCX expression associated with enhanced learning in paradigms examining both the acquisition and extinction of fear (p < 0.001). This, in turn, is associated with differences in freezing on subsequent fear expression tests, and the same relationship between DCX and fear extinction was replicated in rats (p < 0.001), with higher amygdala DCX levels associated with more rapid extinction of fear. RNAseq of amygdala and blood from mice identified 388 amygdala genes that correlated with DCX (q < 0.001) and which gene ontology analyses revealed were significantly over-represented for neurodevelopmental processes. In blood, DCX-correlated genes included the Wnt signaling molecule Cdk14 which was found to predict freezing during both fear acquisition (p < 0.05) and brief extinction protocols (p < 0.001). High Cdk14 measured in blood immediately after testing was also associated with less freezing during fear expression testing (p < 0.01). Finally, in humans, Cdk14 expression in blood taken shortly after trauma was found to predict resilience in males for up to a year post-trauma (p < 0.0001). These data implicate amygdala DCX in fear learning and suggest that Cdk14 may serve as a predictive biomarker of trauma response.

Deep net detection and onset prediction of electrographic seizure patterns in responsive neurostimulation.

OBJECTIVE: Managing the progress of drug-resistant epilepsy patients implanted with the Responsive Neurostimulation (RNS) System requires the manual evaluation of hundreds of hours of intracranial recordings. The generation of these large amounts of data and the scarcity of experts' time for evaluation necessitate the development of automatic tools to detect intracranial electroencephalographic (iEEG) seizure patterns (iESPs) with expert-level accuracy. We developed an intelligent system for identifying the presence and onset time of iESPs in iEEG recordings from the RNS device. METHODS: An iEEG dataset from 24 patients (36 293 recordings) recorded by the RNS System was used for training and evaluating a neural network model (iESPnet). The model was trained to identify the probability of seizure onset at each sample point of the iEEG. The reliability of the net was assessed and compared to baseline methods, including detections made by the device. iESPnet performance was measured using balanced accuracy and the F1 score for iESP detection. The prediction time was assessed via both the error and the mean absolute error. The model was evaluated following a hold-one-out strategy, and then validated in a separate cohort of 26 patients from a different medical center. RESULTS: iESPnet detected the presence of an iESP with a mean accuracy value of 90% and an onset time prediction error of approximately 3.4 s. There was no relationship between electrode location and prediction outcome. Model outputs were well calibrated and unbiased by the RNS detections. Validation on a separate cohort further supported iESPnet applicability in real clinical scenarios. Importantly, RNS device detections were found to be less accurate and delayed in nonresponders; therefore, tools to improve the accuracy of seizure detection are critical for increasing therapeutic efficacy. SIGNIFICANCE: iESPnet is a reliable and accurate tool with the potential to alleviate the time-consuming manual inspection of iESPs and facilitate the evaluation of therapeutic response in RNS-implanted patients.

Towards network-guided neuromodulation for epilepsy.

Epilepsy is well-recognized as a disorder of brain networks. There is a growing body of research to identify critical nodes within dynamic epileptic networks with the aim to target therapies that halt the onset and propagation of seizures. In parallel, intracranial neuromodulation, including deep brain stimulation and responsive neurostimulation, are well-established and expanding as therapies to reduce seizures in adults with focal-onset epilepsy; and there is emerging evidence for their efficacy in children and generalized-onset seizure disorders. The convergence of these advancing fields is driving an era of 'network-guided neuromodulation' for epilepsy. In this review, we distil the current literature on network mechanisms underlying neurostimulation for epilepsy. We discuss the modulation of key 'propagation points' in the epileptogenic network, focusing primarily on thalamic nuclei targeted in current clinical practice. These include (i) the anterior nucleus of thalamus, now a clinically approved and targeted site for open loop stimulation, and increasingly targeted for responsive neurostimulation; and (ii) the centromedian nucleus of the thalamus, a target for both deep brain stimulation and responsive neurostimulation in generalized-onset epilepsies. We discuss briefly the networks associated with other emerging neuromodulation targets, such as the pulvinar of the thalamus, piriform cortex, septal area, subthalamic nucleus, cerebellum and others. We report synergistic findings garnered from multiple modalities of investigation that have revealed structural and functional networks associated with these propagation points - including scalp and invasive EEG, and diffusion and functional MRI. We also report on intracranial recordings from implanted devices which provide us data on the dynamic networks we are aiming to modulate. Finally, we review the continuing evolution of network-guided neuromodulation for epilepsy to accelerate progress towards two translational goals: (i) to use pre-surgical network analyses to determine patient candidacy for neurostimulation for epilepsy by providing network biomarkers that predict efficacy; and (ii) to deliver precise, personalized and effective antiepileptic stimulation to prevent and arrest seizure propagation through mapping and modulation of each patients' individual epileptogenic networks.

Deep brain stimulation for parkinson's disease induces spontaneous cortical hypersynchrony in extended motor and cognitive networks.

The mechanism of action of deep brain stimulation (DBS) to the basal ganglia for Parkinson's disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBS's effects on long range corticocortical synchronization. Here, we use machine learning combined with graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and to healthy controls. We found that turning DBS on increased high beta and gamma band synchrony (26 to 50 Hz) in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. The synchrony in this network was greater in DBS on relative to both DBS off and controls, with no significant difference between DBS off and controls. Turning DBS on also increased network efficiency and strength and subnetwork modularity relative to both DBS off and controls in the beta and gamma band. Thus, unlike DBS's subcortical normalization of pathological basal ganglia activity, it introduces greater synchrony relative to healthy controls in cortical circuitry that includes both motor and non-motor systems. This increased high beta/gamma synchronization may reflect compensatory mechanisms related to DBS's clinical benefits, as well as undesirable non-motor side effects.

Articulatory Gain Predicts Motor Cortex and Subthalamic Nucleus Activity During Speech.

Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson's disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.

A new paradigm for investigating real-world social behavior and its neural underpinnings.

Eye tracking and other behavioral measurements collected from patient-participants in their hospital rooms afford a unique opportunity to study natural behavior for basic and clinical translational research. We describe an immersive social and behavioral paradigm implemented in patients undergoing evaluation for surgical treatment of epilepsy, with electrodes implanted in the brain to determine the source of their seizures. Our studies entail collecting eye tracking with other behavioral and psychophysiological measurements from patient-participants during unscripted behavior, including social interactions with clinical staff, friends, and family in the hospital room. This approach affords a unique opportunity to study the neurobiology of natural social behavior, though it requires carefully addressing distinct logistical, technical, and ethical challenges. Collecting neurophysiological data synchronized to behavioral and psychophysiological measures helps us to study the relationship between behavior and physiology. Combining across these rich data sources while participants eat, read, converse with friends and family, etc., enables clinical-translational research aimed at understanding the participants' disorders and clinician-patient interactions, as well as basic research into natural, real-world behavior. We discuss data acquisition, quality control, annotation, and analysis pipelines that are required for our studies. We also discuss the clinical, logistical, and ethical and privacy considerations critical to working in the hospital setting.

Multiple adjoining word- and face-selective regions in ventral temporal cortex exhibit distinct dynamics.

The map of category-selectivity in human ventral temporal cortex (VTC) provides organizational constraints to models of object recognition. One important principle is lateral-medial response biases to stimuli that are typically viewed in the center or periphery of the visual field. However, little is known about the relative temporal dynamics and location of regions that respond preferentially to stimulus classes that are centrally viewed, like the face- and word-processing networks. Here, word- and face-selective regions within VTC were mapped using intracranial recordings from 36 patients. Partially overlapping, but also anatomically dissociable patches of face- and word-selectivity were found in VTC. In addition to canonical word-selective regions along the left posterior occipitotemporal sulcus, selectivity was also located medial and anterior to face-selective regions on the fusiform gyrus at the group level and within individual male and female subjects. These regions were replicated using 7 Tesla fMRI in healthy subjects. Left hemisphere word-selective regions preceded right hemisphere responses by 125 ms, potentially reflecting the left hemisphere bias for language; with no hemispheric difference in face-selective response latency. Word-selective regions along the posterior fusiform responded first, then spread medially and laterally, then anteriorally. Face-selective responses were first seen in posterior fusiform regions bilaterally, then proceeded anteriorally from there. For both words and faces, the relative delay between regions was longer than would be predicted by purely feedforward models of visual processing. The distinct time-courses of responses across these regions, and between hemispheres, suggest a complex and dynamic functional circuit supports face and word perception.SIGNIFICANCE STATEMENT:Representations of visual objects in the human brain have been shown to be organized by several principles, including whether those objects tend to be viewed centrally or peripherally in the visual field. However, it remains unclear how regions that process objects that are viewed centrally, like words and faces, are organized relative to one another. Here, invasive and non-invasive neuroimaging suggests there is a mosaic of regions in ventral temporal cortex that respond selectively to either words or faces. These regions display differences in the strength and timing of their responses, both within and between brain hemispheres, suggesting they play different roles in perception. These results illuminate extended, bilateral, and dynamic brain pathways that support face perception and reading.

Differentiation of speech-induced artifacts from physiological high gamma activity in intracranial recordings.

There is great interest in identifying the neurophysiological underpinnings of speech production. Deep brain stimulation (DBS) surgery is unique in that it allows intracranial recordings from both cortical and subcortical regions in patients who are awake and speaking. The quality of these recordings, however, may be affected to various degrees by mechanical forces resulting from speech itself. Here we describe the presence of speech-induced artifacts in local-field potential (LFP) recordings obtained from mapping electrodes, DBS leads, and cortical electrodes. In addition to expected physiological increases in high gamma (60-200 Hz) activity during speech production, time-frequency analysis in many channels revealed a narrowband gamma component that exhibited a pattern similar to that observed in the speech audio spectrogram. This component was present to different degrees in multiple types of neural recordings. We show that this component tracks the fundamental frequency of the participant's voice, correlates with the power spectrum of speech and has coherence with the produced speech audio. A vibration sensor attached to the stereotactic frame recorded speech-induced vibrations with the same pattern observed in the LFPs. No corresponding component was identified in any neural channel during the listening epoch of a syllable repetition task. These observations demonstrate how speech-induced vibrations can create artifacts in the primary frequency band of interest. Identifying and accounting for these artifacts is crucial for establishing the validity and reproducibility of speech-related data obtained from intracranial recordings during DBS surgery.

Responsive neurostimulation of the thalamus improves seizure control in idiopathic generalised epilepsy: initial case series.

OBJECTIVES: Up to 40% of patients with idiopathic generalised epilepsy (IGE) are drug resistant and potentially could benefit from intracranial neuromodulation of the seizure circuit. We present outcomes following 2 years of thalamic-responsive neurostimulation for IGE. METHODS: Four patients with pharmacoresistant epilepsy underwent RNS System implantation in the bilateral centromedian (CM) nucleus region. Electrophysiological data were extracted from the clinical patient data management system and analysed using a specialised platform (BRAINStim). Postoperative visualisation of electrode locations was performed using Lead-DBS. Seizure outcomes were reported using the Engel scale. RESULTS: Patients experienced a 75%-99% reduction in seizure frequency with decreased seizure duration and severity (Engel class IB, IC, IIA and IIIA), as well as significant improvements in quality of life. Outcomes were durable through at least 2 years of therapy. Detection accuracy for all patients overall decreased over successive programming epochs from a mean of 96.5% to 88.3%. Most electrodes used to deliver stimulation were located in the CM (7/10) followed by the posterior dorsal ventral lateral (2/2), posterior ventral posterior lateral (3/4) and posterior ventral ventral lateral (2/3). In all patients, stimulation varied from 0.2 to 2.0 mA and amplitude only increased over successive epochs. The raw percentage of intracranial electroencephalography recordings with stimulations delivered to electrographic seizures was 24.8%, 1.2%, 7.6% and 8.8%. CONCLUSION: Closed-loop stimulation of the CM region may provide significant improvement in seizure control and quality of life for patients with drug-resistant IGE. Optimal detection and stimulation locations and parameters remain an active area of investigation for accelerating and fine-tuning clinical responses.

Evaluation of approaches to estimate scapular kinematics during baseball pitching.

Biomechanical analyses of pitching possess limitations in accurately measuring dynamic scapular orientation and are thus unable to distinguish between glenohumeral and scapulothoracic contributions to global shoulder motion. In lieu of direct measurement, several methods to estimate scapular kinematics have been developed. This study evaluated the ability of the linear model and the double calibration acromion marker cluster (D-AMC) approaches to estimate scapular kinematics throughout a full-speed pitching motion. Each approach's estimates were compared against scapulothoracic range of motion limits established in a non-pitching biplane fluoroscopy study involving various functional arm movements that approximate physiological limits of scapular motion. Fourteen healthy collegiate pitchers participated. Motion capture measured upper extremity joint kinematics during full-speed fastball pitches. Linear model and D-AMC approaches estimated scapulothoracic kinematics during each pitch. Linear model estimates of scapulothoracic kinematics were largely within established physiological limits on each scapular axis of motion while D-AMC estimates exceeded fluoroscopy-established bounds for more subjects and by larger, less physiologically plausible amounts. These findings demonstrate that the linear model outperforms the D-AMC and suggest that it is a viable approach to estimate scapular kinematics during pitching. Finally, these results offer additional evidence to support the accepted pattern of scapular kinematics during pitching.

The colour and sensory characteristics of longissimus muscle from beef cattle that grazed grass or consumed concentrates prior to slaughter.

BACKGROUND: Grazed grass is an important component of the majority of beef production systems used in temperate climates. Compared to concentrate-fed beef, 'grass-fed' beef can command a premium in some markets based on perceived differences in appearance and sensory characteristics. The influence of grazed grass per se, as well as the duration of grazing, on selected sensory characteristics of beef within a heifer production system was examined. RESULTS: In general, fat from grass-fed cattle was more yellow than fat from similar cattle fed concentrates, whereas muscle from grass-fed cattle was darker than muscle from cattle fed concentrates. At the same carcass weight, muscle from grass-fed cattle had a lower fat concentration than cattle fed concentrates. In the most extreme situation examined, whereby early-maturing heifers were fed concentrates ad libitum from weaning or grazed grass/conserved grass throughout life, until slaughtered at a similar carcass weight (260 kg) and differed in age by 5 months, beef was rated similarly for tenderness and a range of flavours by a trained sensory panel. CONCLUSION: Within the range of beef heifer production systems examined, the sensory characteristics of grass-fed beef do not differ greatly from concentrate-fed beef. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Assessment of the relationship between Brachial Plexus Profile activity short form scores and modified Mallet scores.

INTRODUCTION: This study aims to assess the relationship between the modified Mallet classification and the Brachial Plexus Profile activity short form (BP-PRO activity SF). The therapist or surgeon classifies upper extremity movement for the modified Mallet classification, while the BP-PRO assesses parents' perceptions of difficulty performing activities. PURPOSE: To provide a deeper understanding of the relationship of functional and perceived outcome measurements. STUDY DESIGN: Prospective, correlational design. METHODS: Eighty children with brachial plexus birth injuries were evaluated using the modified Mallet classification, while parents simultaneously answered the BP-PRO activity SF questions. All patients had undergone one of three surgical interventions to improve shoulder function. The relationship between the two measures, patient injury levels, and surgical histories were assessed. RESULTS: The average modified Mallet scores and BP-PRO activity SF scores weakly correlated (r = 0.312, P = .005) and both measures differentiated between C5-6 and C5-7 injury levels (P = .03 and P = .02, respectively). Conversely, the modified Mallet scores could differentiate between the three surgical groups (F = 8.2, P < .001), while the BP-PRO activity SF could not (P = .54). CONCLUSION: The results suggest that these tools measure different aspects of patient outcomes. The Mallet classification may be more focused on shoulder motion than the BP-PRO activity SF. Additional questions that specifically require shoulder function could be incorporated into the BP-PRO activity SF to improve understanding of patient/parent perceptions of shoulder function for children with brachial plexus injuries. Clinicians should be aware of the strengths, weaknesses, and limitations of each outcome assessment tool for appropriate use and interpretation of results.

Heart failure with preserved ejection fraction diminishes peripheral hemodynamics and accelerates exercise-induced neuromuscular fatigue.

This study investigated the impact of HFpEF on neuromuscular fatigue and peripheral hemodynamics during small muscle mass exercise not limited by cardiac output. Eight HFpEF patients (NYHA II-III, ejection-fraction: 61 ± 2%) and eight healthy controls performed dynamic knee extension exercise (80% peak workload) to task failure and maximal intermittent quadriceps contractions (8 × 15 s). Controls repeated knee extension at the same absolute intensity as HFpEF. Leg blood flow (QL) was quantified using Doppler ultrasound. Pre/postexercise changes in quadriceps twitch torque (ΔQtw; peripheral fatigue), voluntary activation (ΔVA; central fatigue), and corticospinal excitability were quantified. At the same relative intensity, HFpEF (24 ± 5 W) and controls (42 ± 6 W) had a similar time-to-task failure (∼10 min), ΔQtw (∼50%), and ΔVA (∼6%). This resulted in a greater exercise-induced change in neuromuscular function per unit work in HFpEF, which was significantly correlated with a slower QL response time. Knee extension exercise at the same absolute intensity resulted in an ∼40% lower QL and greater ΔQtw and ΔVA in HFpEF than in controls. Corticospinal excitability remained unaltered during exercise in both groups. Finally, despite a similar ΔVA, ΔQtw was larger in HFpEF versus controls during isometric exercise. In conclusion, HFpEF patients are characterized by a similar development of central and peripheral fatigue as healthy controls when tested at the same relative intensity during exercise not limited by cardiac output. However, HFpEF patients have a greater susceptibility to neuromuscular fatigue during exercise at a given absolute intensity, and this impairs functional capacity. The patients' compromised QL response to exercise likely accounts, at least partly, for the patients' attenuated fatigue resistance.NEW & NOTEWORTHY The susceptibility to neuromuscular fatigue during exercise is substantially exaggerated in individuals with heart failure with a preserved ejection fraction. The faster rate of fatigue development is associated with the compromised peripheral hemodynamic response characterizing these patients during exercise. Given the role of neuromuscular fatigue as a factor limiting exercise, this impairment likely accounts for a significant portion of the exercise intolerance typical for this population.