Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval.

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval.

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

On the Operational Utility of Measures of Multichannel EEGs.

Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition and in the eyes-open condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel-Ziv measures of the first principal component, and with three measures of integrated information, including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes-closed condition. When the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in line with the other measures, integrated synergy was greater in the eyes-open condition. Eyes-open versus eyes-closed separation was quantified by calculating the between-condition effect size. The Lempel-Ziv complexity of the first principal component showed greater separation than the measures of integrated information.

Alternative Devices for Heart Rate Variability Measures: A Comparative Test-Retest Reliability Study.

Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

Information dynamics with confidence: Using reservoir computing to construct confidence intervals for information-dynamic measures.

Information dynamics provides a broad set of measures for characterizing how a dynamical system stores, processes, and transmits information. While estimators for these measures are commonly used in applications, the statistical properties of these estimators for finite time series are not well understood. In particular, the precision of a given estimate is generally unknown. We develop confidence intervals for generic information-dynamic parameters using a bootstrap procedure. The bootstrap procedure uses an echo state network, a particular instance of a reservoir computer, as a simulator to generate bootstrap samples from a given time series. We perform a Monte Carlo analysis to investigate the performance of the bootstrap confidence intervals in terms of their coverage and expected lengths with two model systems and compare their performance to a simulator based on the random analog predictor. We find that our bootstrap procedure generates confidence intervals with nominal, or near nominal, coverage of the information-dynamic measures, with smaller expected length than the random analog predictor-based confidence intervals. Finally, we demonstrate the applicability of the confidence intervals for characterizing the information dynamics of a time series of sunspot counts.

Disrupted Gamma Synchrony after Mild Traumatic Brain Injury and Its Correlation with White Matter Abnormality.

Mild traumatic brain injury (mTBI) has been firmly associated with disrupted white matter integrity due to induced white matter damage and degeneration. However, comparatively less is known about the changes of the intrinsic functional connectivity mediated via neural synchronization in the brain after mTBI. Moreover, despite the presumed link between structural and functional connectivity, no existing studies in mTBI have demonstrated clear association between the structural abnormality of white matter axons and the disruption of neural synchronization. To investigate these questions, we recorded resting state EEG and diffusion tensor imaging (DTI) from a cohort of military service members. A newly developed synchronization measure, the weighted phase lag index was applied on the EEG data for estimating neural synchronization. Fractional anisotropy was computed from the DTI data for estimating white matter integrity. Fifteen service members with a history of mTBI within the past 3 years were compared to 22 demographically similar controls who reported no history of head injury. We observed that synchronization at low-gamma frequency band (25-40 Hz) across scalp regions was significantly decreased in mTBI cases compared with controls. The synchronization in theta (4-7 Hz), alpha (8-13 Hz), and beta (15-23 Hz) frequency bands were not significantly different between the two groups. In addition, we found that across mTBI cases, the disrupted synchronization at low-gamma frequency was significantly correlated with the white matter integrity of the inferior cerebellar peduncle, which was also significantly reduced in the mTBI group. These findings demonstrate an initial correlation between the impairment of white matter integrity and alterations in EEG synchronization in the brain after mTBI. The results also suggest that disruption of intrinsic neural synchronization at low-gamma frequency may be a characteristic functional pathology following mTBI and may prove useful for developing better methods of diagnosis and treatment.

Specific transfer entropy and other state-dependent transfer entropies for continuous-state input-output systems.

Since its original formulation in 2000, transfer entropy has become an invaluable tool in the toolbox of nonlinear dynamicists working with empirical data. Transfer entropy and its generalizations provide a precise definition of uncertainty and information transfer that are central to the coupled systems studied in nonlinear science. However, a canonical definition of state-dependent transfer entropy has yet to be introduced. We introduce a candidate measure, the specific transfer entropy, and compare its properties to both total and local transfer entropy. Specific transfer entropy makes possible both state- and time-resolved analysis of the predictive impact of a candidate input system on a candidate output system. We also present principled methods for estimating total, local, and specific transfer entropies from empirical data. We demonstrate the utility of specific transfer entropy and our proposed estimation procedures with two model systems, and find that specific transfer entropy provides more, and more easily interpretable, information about an input-output system compared to currently existing methods.

Identifying Electrophysiological Prodromes of Post-traumatic Stress Disorder: Results from a Pilot Study.

The objective of this research project is the identification of a physiological prodrome of post-traumatic stress disorder (PTSD) that has a reliability that could justify preemptive treatment in the sub-syndromal state. Because abnormalities in event-related potentials (ERPs) have been observed in fully expressed PTSD, the possible utility of abnormal ERPs in predicting delayed-onset PTSD was investigated. ERPs were recorded from military service members recently returned from Iraq or Afghanistan who did not meet PTSD diagnostic criteria at the time of ERP acquisition. Participants (n = 65) were followed for up to 1 year, and 7.7% of the cohorts (n = 5) were PTSD-positive at follow-up. The initial analysis of the receiver operating characteristic (ROC) curve constructed using ERP metrics was encouraging. The average amplitude to target stimuli gave an area under the ROC curve of greater than 0.8. Classification based on the Youden index, which is determined from the ROC, gave positive results. Using average target amplitude at electrode Cz yielded Sensitivity = 0.80 and Specificity = 0.87. A more systematic statistical analysis of the ERP data indicated that the ROC results may simply represent a fortuitous consequence of small sample size. Predicted error rates based on the distribution of target ERP amplitudes approached those of random classification. A leave-one-out cross validation using a Gaussian likelihood classifier with Bayesian priors gave lower values of sensitivity and specificity. In contrast with the ROC results, the leave-one-out classification at Cz gave Sensitivity = 0.65 and Specificity = 0.60. A bootstrap calculation, again using the Gaussian likelihood classifier at Cz, gave Sensitivity = 0.59 and Specificity = 0.68. Two provisional conclusions can be offered. First, the results can only be considered preliminary due to the small sample size, and a much larger study will be required to assess definitively the utility of ERP prodromes of PTSD. Second, it may be necessary to combine ERPs with other biomarkers in a multivariate metric to produce a prodrome that can justify preemptive treatment.

Predictors of Neurocognitive Syndromes in Combat Veterans.

Traumatic brain injury, depression and posttraumatic stress disorder (PTSD) are neurocognitive syndromes often associated with impairment of physical and mental health, as well as functional status. These syndromes are also frequent in military service members (SMs) after combat, although their presentation is often delayed until months after their return. The objective of this prospective cohort study was the identification of independent predictors of neurocognitive syndromes upon return from deployment could facilitate early intervention to prevent disability. We completed a comprehensive baseline assessment, followed by serial evaluations at three, six, and 12 months, to assess for new-onset PTSD, depression, or postconcussive syndrome (PCS) in order to identify baseline factors most strongly associated with subsequent neurocognitive syndromes. On serial follow-up, seven participants developed at least one neurocognitive syndrome: five with PTSD, one with depression and PTSD, and one with PCS. On univariate analysis, 60 items were associated with syndrome development at p < 0.15. Decision trees and ensemble tree multivariate models yielded four common independent predictors of PTSD: right superior longitudinal fasciculus tract volume on MRI; resting state connectivity between the right amygdala and left superior temporal gyrus (BA41/42) on functional MRI; and single nucleotide polymorphisms in the genes coding for myelin basic protein as well as brain-derived neurotrophic factor. Our findings require follow-up studies with greater sample size and suggest that neuroimaging and molecular biomarkers may help distinguish those at high risk for post-deployment neurocognitive syndromes.

Traumatic brain injury detection using electrophysiological methods.

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

Procedures for the Comparative Testing of Noninvasive Neuroassessment Devices.

A sequential process for comparison testing of noninvasive neuroassessment devices is presented. Comparison testing of devices in a clinical population should be preceded by computational research and reliability testing with healthy populations, as opposed to proceeding immediately to testing with clinical participants. A five-step process is outlined as follows: 1. Complete a preliminary literature review identifying candidate measures. 2. Conduct systematic simulation studies to determine the computational properties and data requirements of candidate measures. 3. Establish the test-retest reliability of each measure in a healthy comparison population and the clinical population of interest. 4. Investigate the clinical validity of reliable measures in appropriately defined clinical populations. 5. Complete device usability assessment (weight, simplicity of use, cost effectiveness, ruggedness) only for devices and measures that are promising after steps 1 through 4 are completed. Usability may be considered throughout the device evaluation process but such considerations are subordinate to the higher priorities addressed in steps 1 through 4.

Statistical Issues in TBI Clinical Studies.

The identification and longitudinal assessment of traumatic brain injury presents several challenges. Because these injuries can have subtle effects, efforts to find quantitative physiological measures that can be used to characterize traumatic brain injury are receiving increased attention. The results of this research must be considered with care. Six reasons for cautious assessment are outlined in this paper. None of the issues raised here are new. They are standard elements in the technical literature that describes the mathematical analysis of clinical data. The purpose of this paper is to draw attention to these issues because they need to be considered when clinicians evaluate the usefulness of this research. In some instances these points are demonstrated by simulation studies of diagnostic processes. We take as an additional objective the explicit presentation of the mathematical methods used to reach these conclusions. This material is in the appendices. The following points are made: (1) A statistically significant separation of a clinical population from a control population does not ensure a successful diagnostic procedure. (2) Adding more variables to a diagnostic discrimination can, in some instances, actually reduce classification accuracy. (3) A high sensitivity and specificity in a TBI versus control population classification does not ensure diagnostic successes when the method is applied in a more general neuropsychiatric population. (4) Evaluation of treatment effectiveness must recognize that high variability is a pronounced characteristic of an injured central nervous system and that results can be confounded by either disease progression or spontaneous recovery. A large pre-treatment versus post-treatment effect size does not, of itself, establish a successful treatment. (5) A procedure for discriminating between treatment responders and non-responders requires, minimally, a two phase investigation. This procedure must include a mechanism to discriminate between treatment responders, placebo responders, and spontaneous recovery. (6) A search for prodromes of neuropsychiatric disorders following traumatic brain injury can be implemented with these procedures.

Advancing Translational Research through Facility Design in Non-AMC Hospitals.

OBJECTIVE: This article aims to explore the future of translational research and its physical design implications for community hospitals and hospitals not attached to large centralized research platforms. BACKGROUND: With a shift in medical services delivery focus to community wellness, continuum of care, and comparative effectiveness research, healthcare research will witness increasing pressure to include community-based practitioners. METHODS: The roundtable discussion group, comprising 14 invited experts from 10 institutions representing the fields of biomedical research, research administration, facility planning and design, facility management, finance, and environmental design research, examined the issue in a structured manner. The discussion was conducted at the Washington Hospital Center, MedStar Health, Washington, D.C. CONCLUSIONS: Institutions outside the AMCs will be increasingly targeted for future research. Three factors are crucial for successful research in non-AMC hospitals: operational culture, financial culture, and information culture. An operating culture geared towards creation, preservation, and protection of spaces needed for research; creative management of spaces for financial accountability; and a flexible information infrastructure at the system level that enables complete link of key programmatic areas to academic IT research infrastructure are critical to success of research endeavors. KEYWORDS: Hospital, interdisciplinary, leadership, planning, work environment.

Patient Characterization Protocols for Psychophysiological Studies of Traumatic Brain Injury and Post-TBI Psychiatric Disorders.

Psychophysiological investigations of traumatic brain injury (TBI) are being conducted for several reasons, including the objective of learning more about the underlying physiological mechanisms of the pathological processes that can be initiated by a head injury. Additional goals include the development of objective physiologically based measures that can be used to monitor the response to treatment and to identify minimally symptomatic individuals who are at risk of delayed-onset neuropsychiatric disorders following injury. Research programs studying TBI search for relationships between psychophysiological measures, particularly ERP (event-related potential) component properties (e.g., timing, amplitude, scalp distribution), and a participant's clinical condition. Moreover, the complex relationships between brain injury and psychiatric disorders are receiving increased research attention, and ERP technologies are making contributions to this effort. This review has two objectives supporting such research efforts. The first is to review evidence indicating that TBI is a significant risk factor for post-injury neuropsychiatric disorders. The second objective is to introduce ERP researchers who are not familiar with neuropsychiatric assessment to the instruments that are available for characterizing TBI, post-concussion syndrome, and psychiatric disorders. Specific recommendations within this very large literature are made. We have proceeded on the assumption that, as is typically the case in an ERP laboratory, the investigators are not clinically qualified and that they will not have access to participant medical records.

Improved behavior, motor, and cognition assessments in neonatal piglets.

The alterations of animal behavior after traumatic brain injury (TBI) can be subtle, and their quantitative characterization can present significant methodological challenges. Meeting these challenges is a critical need, because quantitative measures are required in studies that compare the efficacy of different clinical interventions. We developed a battery of assessments to quantify behavioral, motor, and cognitive changes in neonatal piglets with good sensitivity and specificity to the detection of persistent deficits that correlate with axonal injury severity after a rapid non-impact head rotation with a diffuse pattern of axonal injury. The battery of measures developed included open field behaviors of sniffing and moving a toy, locomotion measures of Lempel-Ziv complexity and the probability of remaining in the current location, and a novel metric for evaluating motor performance. Our composite porcine disability score was able to detect brain injury with a sensitivity of 100% and specificity of 85.7% at day +4 post-injury for n=8 injured and n=7 sham piglets and significantly correlated with the percent axonal injury in these animals (day +4: ρ=0.76, p=0.0011). A significant improvement over our previous assessments, this new porcine disability score has potential use in a wide variety of porcine disease and injury models.

Behavioral deficits and axonal injury persistence after rotational head injury are direction dependent.

Pigs continue to grow in importance as a tool in neuroscience. However, behavioral tests that have been validated in the rodent model do not translate well to pigs because of their very different responses to behavioral stimuli. We refined metrics for assessing porcine open field behavior to detect a wide spectrum of clinically relevant behaviors in the piglet post-traumatic brain injury (TBI). Female neonatal piglets underwent a rapid non-impact head rotation in the sagittal plane (n=8 evaluable) or were instrumented shams (n=7 evaluable). Open field testing was conducted 1 day prior to injury (day -1) in order to establish an individual baseline for analysis, and at days +1 and +4 after injury. Animals were then killed on day +6 after injury for neuropathological assessment of axonal injury. Injured piglets were less interested in interacting with environmental stimuli and had a lower activity level than did shams. These data were compared with previously published data for axial rotational injuries in neonatal piglets. Acute behavioral outcomes post-TBI showed a dependence on the rotational plane of the brain injury, with animals with sagittal injuries demonstrating a greater level of inactivity and less random usage of the open field space than those with axial injuries. The persistence of axonal injury is also dependent on the rotational plane, with sagittal rotations causing more prolonged injuries than axial rotations. These results are consistent with animal studies, finite element models, and studies of concussions in football, which have all demonstrated differences in injury severity depending upon the direction of head impact rotation.

Is a diagnosis of "mild traumatic brain injury" a category mistake?

BACKGROUND: Efforts to produce definitions and diagnostic standards for mild traumatic brain injury (TBI) have a long and complex history. The diagnosis of TBI must be considered in the larger context of neuropsychiatric diagnosis. A major reconceptualization of diagnosis is now underway in which the classical syndrome conceptualization is being discarded. We address the question, what are the implications of this revision of thinking in the specific context of TBI? METHODS: A recent literature on logical structures for neuropsychiatric disorders was reviewed. The symptom pattern of TBI was identified, and a literature survey determined the frequency of these symptom patterns in other disorders and in healthy control populations. RESULTS: The frequency of symptom endorsement in populations without a history of TBI can be equal to endorsement frequencies in populations with a history of mild TBI. In some studies, the frequency of symptom endorsement in healthy controls having no history of head injury actually exceeded the endorsement rates in a comparison group with a history mild TBI. CONCLUSION: The heterogeneity of this clinical population and their clinical presentations, the absence of a unitary etiology of postinjury deficits, and the complex idiosyncratic time course of the appearance of these deficits argue against the valid implementation of the classical model of diagnosis. In addition, the accepted criteria of diagnostic utility are not satisfied. TBI is not a disease; it is an event. More precisely, TBI is an event or a sequence of events that can, in some instances, lead to a diagnosable neurological or psychiatric disorder.

Communication patterns in a psychotherapy following traumatic brain injury: a quantitative case study based on symbolic dynamics.

BACKGROUND: The role of psychotherapy in the treatment of traumatic brain injury is receiving increased attention. The evaluation of psychotherapy with these patients has been conducted largely in the absence of quantitative data concerning the therapy itself. Quantitative methods for characterizing the sequence-sensitive structure of patient-therapist communication are now being developed with the objective of improving the effectiveness of psychotherapy following traumatic brain injury. METHODS: The content of three therapy session transcripts (sessions were separated by four months) obtained from a patient with a history of several motor vehicle accidents who was receiving dialectical behavior therapy was scored and analyzed using methods derived from the mathematical theory of symbolic dynamics. RESULTS: The analysis of symbol frequencies was largely uninformative. When repeated triples were examined a marked pattern of change in content was observed over the three sessions. The context free grammar complexity and the Lempel-Ziv complexity were calculated for each therapy session. For both measures, the rate of complexity generation, expressed as bits per minute, increased longitudinally during the course of therapy. The between-session increases in complexity generation rates are consistent with calculations of mutual information. Taken together these results indicate that there was a quantifiable increase in the variability of patient-therapist verbal behavior during the course of therapy. Comparison of complexity values against values obtained from equiprobable random surrogates established the presence of a nonrandom structure in patient-therapist dialog (P = .002). CONCLUSIONS: While recognizing that only limited conclusions can be based on a case history, it can be noted that these quantitative observations are consistent with qualitative clinical observations of increases in the flexibility of discourse during therapy. These procedures can be of particular value in the examination of therapies following traumatic brain injury because, in some presentations, these therapies are complicated by deficits that result in subtle distortions of language that produce significant post-injury social impairment. Independently of the mathematical analysis applied to the investigation of therapy-generated symbol sequences, our experience suggests that the procedures presented here are of value in training therapists.

Fully optimized discrimination of physiological responses to auditory stimuli.

The use of multivariate measurements to characterize brain activity (electrical, magnetic, optical) is widespread. The most common approaches to reduce the complexity of such observations include principal and independent component analyses (PCA and ICA), which are not well suited for discrimination tasks. We addressed two questions: first, how do the neurophysiological responses to elongated phonemes relate to tone and phoneme responses in normal children, and, second, how discriminable are these responses. We employed fully optimized linear discrimination analysis to maximally separate the multi-electrode responses to tones and phonemes, and classified the response to elongated phonemes. We find that discrimination between tones and phonemes is dependent upon responses from associative regions of the brain apparently distinct from the primary sensory cortices typically emphasized by PCA or ICA, and that the neuronal correlates corresponding to elongated phonemes are highly variable in normal children (about half respond with neural correlates of tones and half as phonemes). Our approach is made feasible by the increase in computational power of ordinary personal computers and has significant advantages for a wide range of neuronal imaging modalities.