Signal processing methods for reducing artifacts in microelectrode brain recordings caused by functional electrical stimulation

OBJECTIVE

Functional electrical stimulation (FES) is a promising technology for restoring movement to paralyzed limbs. Intracortical brain-computer interfaces (iBCIs) have enabled intuitive control over virtual and robotic movements, and more recently over upper extremity FES neuroprostheses. However, electrical stimulation of muscles creates artifacts in intracortical microelectrode recordings that could degrade iBCI performance. Here, we investigate methods for reducing the cortically recorded artifacts that result from peripheral electrical stimulation.

APPROACH

One participant in the BrainGate2 pilot clinical trial had two intracortical microelectrode arrays placed in the motor cortex, and thirty-six stimulating intramuscular electrodes placed in the muscles of the contralateral limb. We characterized intracortically recorded electrical artifacts during both intramuscular and surface stimulation. We compared the performance of three artifact reduction methods: blanking, common average reference (CAR) and linear regression reference (LRR), which creates channel-specific reference signals, composed of weighted sums of other channels.

MAIN RESULTS

Electrical artifacts resulting from surface stimulation were 175  ×  larger than baseline neural recordings (which were 110 µV peak-to-peak), while intramuscular stimulation artifacts were only 4  ×  larger. The artifact waveforms were highly consistent across electrodes within each array. Application of LRR reduced artifact magnitudes to less than 10 µV and largely preserved the original neural feature values used for decoding. Unmitigated stimulation artifacts decreased iBCI decoding performance, but performance was almost completely recovered using LRR, which outperformed CAR and blanking and extracted useful neural information during stimulation artifact periods.

SIGNIFICANCE

The LRR method was effective at reducing electrical artifacts resulting from both intramuscular and surface FES, and almost completely restored iBCI decoding performance (>90% recovery for surface stimulation and full recovery for intramuscular stimulation). The results demonstrate that FES-induced artifacts can be easily mitigated in FES  +  iBCI systems by using LRR for artifact reduction, and suggest that the LRR method may also be useful in other noise reduction applications.

A-63 The Fatigue Severity Scale and Depression in an Aging Population

Objective

The Fatigue Severity Scale (FSS) is often used in clinical populations in which fatigue is a common symptom (e.g., multiple sclerosis). Despite the prevalence of fatigue in depression, relatively few investigations have examined the relationship between the FSS and mood symptoms, particularly in aging populations with concerns of memory loss. Thus, the primary aim of the present investigation was to elucidate the relationship between fatigue symptoms and depression among older adults evaluated in a cognitive disorders clinic.

Method

Data were collected as part of a neuropsychological battery administered to patients presenting to clinic due to complaints of memory impairment. Scores on the FSS and the Geriatric Depression Scale (GDS) were collected from 430 patients (48.10% women). Mean age was 74.97 years (SD = 5.81) and 147 subjects were diagnosed with depression, based on a score of 10 or above on the GDS.

Results

We observed a small, but significant inverse relationship between age and scores on the FSS [r = -.103, p = .033], such that older adults endorsed less severe fatigue. A moderate, positive relationship between FSS and GDS was observed [r = .416, p = .000]. Comparing FSS endorsement between depressed and non-depressed individuals finds individuals with depression endorsed significantly greater levels of fatigue than non-depressed individuals, even after accounting for the effects of age [F(1, 427) = 85.79. p < .001; Cohen's d = 0.96].

Conclusion

Present findings suggest that older adults do not necessarily endorse higher rates of fatigue on the FSS. However, the presence of depression in older adults has large effects on fatigue severity.

A-61 The Cattell-Horn-Carroll Model Does Not Outperform a Traditional Neuropsychological Model When Using a Digital Test Battery

Objective

Following recent (meta-)analyses showing that the Cattell-Horn-Carroll (CHC) model outperforms traditional neuropsychological models of cognition, we investigated the relative performance of the traditional neuropsychological model (TNM) of cognitive functioning and the CHC model using the digital Philips IntelliSpace Cognition (ISC) test battery.

Method

The ISC battery consists of 11 conventional cognitive tests, which were administered to 221 healthy participants. We used confirmatory factor analysis (CFA) to map outcome measures to cognitive domains. Both models contained processing speed, working memory, memory, and visuospatial ability. TNM included executive functioning consisting of TMT B, Stroop interference, and Phonetic and Semantic Fluency. In the CHC model, these outcome measures were distributed over processing speed and a word fluency domain. The models’ fit was compared through Vuong test for non-nested models.

Results

Both models were a good fit (TNM: χ2(64) = 91.95, p = .013, CFI = .971, RMSEA = .044; CHC: χ2(64) = 83.66, p = .050, CFI = .979, RMSEA = .037). The Vuong test showed that the models could be significantly distinguished based on the observed data, ω2 = 0.21, p < .001. However, the non-nested likelihood ratio test did not offer evidence that either model was a better fit, z = -0.61, p = .727. The 95% confidence interval of the AIC difference contained zero [-18.60, 35.20].

Conclusions

Recent findings showing that the CHC model outperforms the TNM are not corroborated by our findings. Instead, both models captured the data equally well, suggesting that the two theoretical frameworks are not necessarily mutually exclusive.

B-59 Prevalence of Pseudobulbar Affect Symptoms in Professional Fighters

Objective

Pseudobulbar Affect (PBA) is defined as dysregulation of emotional expression and is characterized by sudden, uncontrollable, laughing and/or crying that is discordant with the present mood or social context. This study sought to establish the prevalence of PBA symptoms in individuals with a high incidence of sports-related head injuries and explore the relationship between two rating scales designed to measure PBA symptoms.

Methods

Sixty-three professional fighters (age: M = 44.7, SD = 10.0; 98% male) underwent neurological and neuropsychological assessment including completion of the Pathological Laughing and Crying Scale (PLCS) and the Center for Neurologic Study – Lability Scale (CNS-LS). Diagnostic criteria for PBA were reviewed during the neurological exam to establish the prevalence of the clinical syndrome. Prevalence statistics for item endorsement on the rating scales and diagnostic status were calculated. To investigate the rate of agreement between rating scales, concordance correlation coefficient (CCC) and root mean square difference (RMSD) were calculated.

Results

Eleven percent of participants met clinical criteria for PBA diagnosis, 25% of participants endorsed clinically significant PBA symptoms on the CNS-LS (M = 10.9, SD = 4.9), and 8% endorsed significant symptoms on the PLCS (M = 3.1, SD = 6.5). The rating scales were significantly positively correlated (r = .58; p < .01), though overall agreement was low (CCC = 0.55; RMSD = 5.4).

Conclusions

This study demonstrates that the prevalence of PBA symptoms in a sample of professional fighters is not uncommon. Although both the CNS-LS and PCLS are designed to measure PBA symptoms, they appear to be measuring unique aspects of PBA that may provide complimentary, rather than redundant information.

A-48 The Role of Processing Speed in Verbal and Nonverbal Learning within a Clinical Sample of Older Adults

Objective

Prior research revealed that processing speed predicts nonverbal learning in healthy older adults (Tam & Schmitter-Edgecombe, 2013). This study aims to examine the role of processing speed in both verbal and nonverbal learning in a clinical sample. We expect that processing speed will lend the most variance to the initial learning trials.

Method

Records from 718 patients were reviewed (mean age = 74). Hierarchical regression analyses were conducted using Brief Visuospatial Memory Test –Revised (BVMT-R) and Hopkins Verbal Learning Test –Revised (HVLT-R) learning trials as outcome variables. Demographics were entered in a first step followed by BVMT-R copy or Wechsler Adult Intelligence Scale (WAIS-IV) Digit Span –longest digit span forward raw score, to account for visuoconstruction or simple auditory attention for nonverbal and verbal learning outcomes respectively. A processing speed composite of sample-standardized raw scores was entered in a final step.

Results

Processing speed accounted for 5.4% of the variance in BVMT-R trial 1, 7.5% of the variance in trial 2, and 8.5% of the variance in trial 3, all p < .001. Processing speed accounted for 6.6% of the variance in HVLT-R trial 1, 11.1% of the variance in trial 2, and 11.5% of the variance in trial 3, all p < .001.

Conclusions

Processing speed significantly predicted all verbal and nonverbal learning trials. Contrary to our hypotheses, processing speed actually had a greater contribution during subsequent learning trials. These findings have implications for evaluating memory performance in patients with syndromes where processing speed is typically affected (e.g., cerebrovascular disease, Parkinson’s disease).

B-23 Non-Motor Symptom Profile in Parkinson’s Disease Patients and its impact on Quality of Life

Objective

Non-motor Symptoms (NMS) in Parkinson’s Disease (PD) are known to be diverse and may include cognitive, psychiatric and sleep disturbance, fatigue, and autonomic disorders (e.g., cardiovascular dysregulation, orthostatic hypotension, thermo-dysregulation, sexual dysfunction, urinary and bowel dyscontrol). The aim of this study was to define the NMS profile in a large sample of PD patients with and without Deep Brain Stimulation (DBS) and its impact on quality of life (QOL).

Method

Cross-sectional, survey-based research design was used. 1,164 individuals with PD participated in this survey: 275 participants who underwent DBS and 889 without DBS. Participants completed the Non-Motor Symptom Scale (NMSS) and answered questions assessing the impact of NMS on everyday life. Participants were divided into younger (ages 50-69) and older (ages 70+) age cohorts and disease duration cohorts with early stage ( < 6 years) and advanced stage (6-10 years; 11+ years) groups.

Results

24 out of 31 NMS categories were experienced by more than 50% of the participants. Urination difficulty, fatigue, sleep, constipation, and cognitive difficulties were symptoms most frequently reported to adversely impact day-to-day living, and cognitive difficulties followed by sleep disturbance had the strongest impact to quality of life.

Conclusions

NMS burden drives quality of life for many individuals and has remained a relatively new frontier for exploration, at least in depth and scope as it relates to assessment and treatment of NMS. Management of NMS remains an unmet need for individuals with PD. Implications for neuropsychologists are discussed.

A-62 The Philips IntelliSpace Cognition Platform: Ability to Classify a Mixed Clinical Sample

Objective

We developed a cloud-based platform, Philips Intellispace Cognition (ISC), containing tablet-based versions of conventional cognitive tests. We investigated the battery’s sensitivity for subtle cognitive impairment in a mixed clinical sample.

Method

The sample consisted of 221 healthy participants and 98 traumatic brain injury (TBI) and stroke patients who all scored above the MMSE-2 cutoff of 24, but reported subjective cognitive complaints. All completed the following ISC tests: Phonetic Fluency; Semantic Fluency; Trail-Making; Stroop; O-Cancellation; Star-Cancellation; Digit Span; Rey Auditory Verbal Learning; Rey-Osterrieth Complex Figure. We used ROC analyses to investigate our ability to distinguish the patient and healthy samples. Specifically, we assessed the area under the curve (AUC), where a value of .50 indicates random classification and 1 indicates perfect distinguishability. To this end, we compared sensitivity of cognitive domain scores distilled from the ISC tests (using confirmatory factor analysis) with the sensitivity of MMSE-2 scores. The cognitive domains were executive functioning, processing speed, working memory, memory, and visuospatial ability.

Results

The AUC of the MMSE-2 was .46, as expected given the fact that all patients scored above the cut-off. The AUCs of the model domain scores ranged from .56 to .73. The differences between these AUCs and the MMSE AUC were all significant (ps ≤ .004), except for visuospatial ability (p = .070).

Conclusions

The ISC test battery was able to pick up on cognitive impairment in a mixed clinical sample consisting of patients that all scored normally on the MMSE-2. These findings show the usefulness of the digital platform in clinical practice.

Tests of General Relativity with GW170817

The recent discovery by Advanced LIGO and Advanced Virgo of a gravitational wave signal from a binary neutron star inspiral has enabled tests of general relativity (GR) with this new type of source. This source, for the first time, permits tests of strong-field dynamics of compact binaries in the presence of matter. In this Letter, we place constraints on the dipole radiation and possible deviations from GR in the post-Newtonian coefficients that govern the inspiral regime. Bounds on modified dispersion of gravitational waves are obtained; in combination with information from the observed electromagnetic counterpart we can also constrain effects due to large extra dimensions. Finally, the polarization content of the gravitational wave signal is studied. The results of all tests performed here show good agreement with GR.

Effect of ultrasound on bubble-particle interaction in quartz-amine flotation system

In this study, the effect of ultrasound (US) on the quartz-amine flotation system was investigated in detail by considering various surface chemistry techniques. The effect of ultrasound on particle size, shape factor, and surface roughness were characterized by using Brunauer-Emmett-Teller (BET) surface area measurements and scanning electron microscopy (SEM) analyses. The contact angle and bubble-particle attachment time, as well as adsorption density measurements was carried out to evaluate the effect of ultrasound on quartz surface wetting ability. In addition, atomic force microscopy (AFM) analyses were conducted, and finally micro-flotation studies were performed. As a result, it was found that the micro-flotation recovery at 2 × 10^-5 M dodecyl amine hydrochloride (DAH) concentration increased from 45.45% to 63.64% with 30 W ultrasonic application at conditioning step. However, the micro-flotation recovery decreased to 37.50% when the ultrasonic power increased to 150 W. The results showed some effect of ultrasound on particle size, particle shape, and surface roughness in some extent. The increase in the contact angle and the decrease in the bubble-particle attachment time were observed. A slightly high adsorption density was measured. All these show a positive effect of ultrasound on quartz flotation with amine as a collector.

Constraining the p-Mode-g-Mode Tidal Instability with GW170817

We analyze the impact of a proposed tidal instability coupling p modes and g modes within neutron stars on GW170817. This nonresonant instability transfers energy from the orbit of the binary to internal modes of the stars, accelerating the gravitational-wave driven inspiral. We model the impact of this instability on the phasing of the gravitational wave signal using three parameters per star: an overall amplitude, a saturation frequency, and a spectral index. Incorporating these additional parameters, we compute the Bayes factor (lnB_{!pg}^{pg}) comparing our p-g model to a standard one. We find that the observed signal is consistent with waveform models that neglect p-g effects, with lnB_{!pg}^{pg}=0.03_{-0.58}^{+0.70} (maximum a posteriori and 90% credible region). By injecting simulated signals that do not include p-g effects and recovering them with the p-g model, we show that there is a ≃50% probability of obtaining similar lnB_{!pg}^{pg} even when p-g effects are absent. We find that the p-g amplitude for 1.4  M_{⊙} neutron stars is constrained to less than a few tenths of the theoretical maximum, with maxima a posteriori near one-tenth this maximum and p-g saturation frequency ∼70  Hz. This suggests that there are less than a few hundred excited modes, assuming they all saturate by wave breaking. For comparison, theoretical upper bounds suggest ≲10^{3} modes saturate by wave breaking. Thus, the measured constraints only rule out extreme values of the p-g parameters. They also imply that the instability dissipates ≲10^{51}  erg over the entire inspiral, i.e., less than a few percent of the energy radiated as gravitational waves.

Cross sectional imaging of truncal and quadriceps muscles relates to different functional outcomes in cancer

Introduction

Following the consensus definition of cancer cachexia, more studies are using CT scan analysis of truncal muscles as a marker of muscle wasting. However, how CT-derived body composition relates to function, strength and power in patients with cancer is largely unknown.

Aims

We aimed to describe the relationship between CT truncal (L3) skeletal muscle index (SMI) and MRI quadriceps cross sectional area with lower limb strength, power and measures of complex function.

Methods

Patients undergoing assessment for potentially curative surgery for oesophagogastric or pancreatic cancer were recruited from the regional upper gastrointestinal (UGI) or hepatopancreaticobiliary (HPB) multi-disciplinary team meetings. Maximum Isometric Knee Extensor Strength (IKES) and Maximum Leg Extensor Power (Nottingham Power Rig) (LEP) were used as measures of lower limb performance. Both Sit to Stand (STS) and Timed Up and Go (TUG) were used as measures of global complex muscle function. Muscle SMI was measured from routine CT scans at the level of the third lumbar vertebrae (L3) and MRI scan was used for the assessment of quadriceps muscles. Linear regression analysis was performed for CT SMI or MRI quadriceps as a predictor of each measure of performance.

Results

Forty-four patients underwent assessment. Height and weight were significantly related to function in terms of quadriceps power, while only weight was associated with strength (P < 0.001). CT SMI was not related to measures of quadriceps strength or power but had significant association with more complex functional measures (P = 0.006, R² = 0.234 and 0.0019, R² = 0.175 for STS and TUG respectively). In comparison, both gross and fat-subtracted measures of quadriceps muscle mass from MRI were significantly correlated with quadriceps strength and power (P < 0.001), but did not show any significant association with complex functional measures.

Conclusion

CT SMI and MRI quadriceps have been shown to reflect different aspects of functional ability with CT SMI being a marker of global muscle function and MRI quadriceps being specific to quadriceps power and strength. This should therefore be considered when choosing outcome measures for trials or definitions of muscle mass and function.

Search for Subsolar-Mass Ultracompact Binaries in Advanced LIGO's First Observing Run

We present the first Advanced LIGO and Advanced Virgo search for ultracompact binary systems with component masses between 0.2  M_{⊙}-1.0  M_{⊙} using data taken between September 12, 2015 and January 19, 2016. We find no viable gravitational wave candidates. Our null result constrains the coalescence rate of monochromatic (delta function) distributions of nonspinning (0.2  M_{⊙}, 0.2  M_{⊙}) ultracompact binaries to be less than 1.0×10^{6}  Gpc^{-3}  yr^{-1} and the coalescence rate of a similar distribution of (1.0  M_{⊙}, 1.0  M_{⊙}) ultracompact binaries to be less than 1.9×10^{4}  Gpc^{-3}  yr^{-1} (at 90% confidence). Neither black holes nor neutron stars are expected to form below ∼1  M_{⊙} through conventional stellar evolution, though it has been proposed that similarly low mass black holes could be formed primordially through density fluctuations in the early Universe and contribute to the dark matter density. The interpretation of our constraints in the primordial black hole dark matter paradigm is highly model dependent; however, under a particular primordial black hole binary formation scenario we constrain monochromatic primordial black hole populations of 0.2  M_{⊙} to be less than 33% of the total dark matter density and monochromatic populations of 1.0  M_{⊙} to be less than 5% of the dark matter density. The latter strengthens the presently placed bounds from microlensing surveys of massive compact halo objects (MACHOs) provided by the MACHO and EROS Collaborations.

Closed-loop cortical control of virtual reach and posture using Cartesian and joint velocity commands

OBJECTIVE

Brain-computer interfaces (BCIs) are a promising technology for the restoration of function to people with paralysis, especially for controlling coordinated reaching. Typical BCI studies decode Cartesian endpoint velocities as commands, but human arm movements might be better controlled in a joint-based coordinate frame, which may match underlying movement encoding in the motor cortex. A better understanding of BCI controlled reaching by people with paralysis may lead to performance improvements in brain-controlled assistive devices.

APPROACH

Two intracortical BCI participants in the BrainGate2 pilot clinical trial performed a visual 3D endpoint virtual reality reaching task using two decoders: Cartesian and joint velocity. Task performance metrics (i.e. success rate and path efficiency) and single feature and population tuning were compared across the two decoder conditions. The participants also demonstrated the first BCI control of a fourth dimension of reaching, the arm's swivel angle, in a 4D posture matching task.

MAIN RESULTS

Both users achieved significantly higher success rates using Cartesian velocity control, and joint controlled trajectories were more variable and significantly more curved. Neural tuning analyses showed that most single feature activity was best described by a Cartesian kinematic encoding model, and population analyses revealed only slight differences in aggregate activity between the decoder conditions. Simulations of a BCI user reproduced trajectory features seen during closed-loop joint control when assuming only Cartesian-tuned features passed through a joint decoder. With minimal training, both participants controlled the virtual arm's swivel angle to complete a 4D posture matching task, and achieved significantly higher success using a Cartesian  +  swivel velocity decoder compared to a joint velocity decoder.

SIGNIFICANCE

These results suggest that Cartesian velocity command interfaces may provide better BCI control of arm movements than other kinematic variables, even in 4D posture tasks with swivel angle targets.