Publications by authors named "Justin Blanco"

Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data.

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Objective: Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity.

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  • The study investigated cognitive stress responses using a low-cost wireless EEG headset during a Stroop-type test with 18 participants.
  • EEG signals from 13 scalp locations were recorded and analyzed in different frequency bands (theta, alpha, beta) after stimulus presentation, utilizing algorithms to extract key features for classification.
  • The analysis achieved around 80% accuracy in classifying stress states using various machine learning techniques, indicating that specific electrode-feature combinations effectively distinguished stress responses among subjects.
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A novel ERP approach was proposed to index variations in mental workload, particularly in attentional reserve, which is complementary to EEG spectral content thought to reflect mental effort. To our knowledge, no study has assessed mental effort and attentional reserve simultaneously in EEG gel-based and, importantly, dry systems, which are particularly well suited for real-world settings. Therefore, by systematically considering ERP, EEG spectral, and importantly the combination of both, this study examined if a small set of dry EEG electrodes could detect changes in both spectral and ERP metrics to assess the mental workload under various challenges with a similar fidelity to their gel-based counterparts in a laboratory setting.

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  • Current epilepsy mapping often uses sparse electrode arrays, but new research highlights the importance of high-resolution electrodes to study seizure dynamics more effectively.
  • Researchers used flexible electrode arrays with 500 μm spacing on cats to examine how epileptiform activity propagates in real-time before and during seizures.
  • Findings suggest that high-resolution recordings reveal distinct seizure patterns that standard methods miss, providing valuable insights into seizure networks.
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Many wireless devices in common use today are worn either on or in close proximity to the body. Among them are a growing number of wrist-mounted devices designed for applications such as activity or vital-signs monitoring, typically using Bluetooth technology to communicate with external devices. Here, we use a tissue-mimicking phantom material in conjunction with anechoic chamber and network analyzer testing to investigate how antenna propagation patterns in one such device are influenced by the electrical properties of the human wrist.

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  • High-frequency oscillations (HFOs), categorized as ripples (100-250 Hz) or fast ripples (250-500 Hz), serve as potential biomarkers for identifying seizure-prone brain areas in patients with epilepsy.
  • Researchers analyzed HFO data from five epilepsy patients using an automated algorithm, focusing on changes in HFO characteristics across different seizure-related time periods (interictal, preictal, ictal, and postictal).
  • The study found significant, patient-specific fluctuations in HFO morphology and rates, indicating the potential for these temporal changes to inform customized seizure prediction methods and enhance understanding of seizure mechanisms.
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  • More than one third of the 60 million people with epilepsy have medication-resistant seizures, leading to limited surgical options with a success rate of only 35%.
  • Current epilepsy treatments face a technological barrier as existing devices cannot effectively map the brain's epileptic networks due to size limitations of electrodes.
  • A new collaborative team has developed advanced implantable brain devices made from flexible silicon nanoribbons, allowing for precise recording from small brain areas with closely spaced microelectrodes.
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Advances in neural electrode technology are enabling brain recordings with increasingly fine spatial and temporal resolution. We explore spatio-temporal (ST) patterns of local field potential spikes using a new high-density active electrode array with 500 μm resolution. We record subdural micro-electrocorticographic (μECoG) signals in vivo from a feline model of acute neocortical epileptiform spikes and seizures induced with local administration of the GABA antagonist, picrotoxin.

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Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires. We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures.

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  • Transient high-frequency oscillations (100-500 Hz) in the local field potential indicate increased ripple (100-250 Hz) and fast ripple (250-500 Hz) activity in the seizure-onset zone of mesial temporal lobe epilepsy, but less is known about these patterns in neocortical epilepsy and normal brains.
  • A comprehensive analysis using over 12 terabytes of continuous intracranial recordings from 9 neocortical epilepsy patients and 2 controls revealed that ripple oscillations are more prevalent in seizure-onset zones compared to fast ripples.
  • While controls and non-seizure-onset zones show similar rates of high-frequency oscillations, micro-electrode recordings yielded higher frequencies than surface electrodes, suggesting that
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Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. We present innovations in both hardware and software that allow sampling and interpretation of data from brain networks from hundreds or thousands of sensors at submillimeter resolution. These innovations consist of novel flexible, active electrode arrays and unsupervised algorithms for detecting and classifying neurophysiologic biomarkers, specifically high frequency oscillations.

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High-frequency oscillations (HFOs) have been observed in animal and human intracranial recordings during both normal and aberrant brain states. It has been proposed that the relationship between subclasses of these oscillations can be used to identify epileptic brain. Studies of HFOs in epilepsy have been hampered by selection bias arising primarily out of the need to reduce the volume of data so that clinicians can manually review it.

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Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface.

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In all current implantable medical devices such as pacemakers, deep brain stimulators, and epilepsy treatment devices, each electrode is independently connected to separate control systems. The ability of these devices to sample and stimulate tissues is hindered by this configuration and by the rigid, planar nature of the electronics and the electrode-tissue interfaces. Here, we report the development of a class of mechanically flexible silicon electronics for multiplexed measurement of signals in an intimate, conformal integrated mode on the dynamic, three-dimensional surfaces of soft tissues in the human body.

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The brain's sensitivity to unexpected outcomes plays a fundamental role in an organism's ability to adapt and learn new behaviors. Emerging research suggests that midbrain dopaminergic neurons encode these unexpected outcomes. We used microelectrode recordings during deep brain stimulation surgery to study neuronal activity in the human substantia nigra (SN) while patients with Parkinson's disease engaged in a probabilistic learning task motivated by virtual financial rewards.

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