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.

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.

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.

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.

Lateralized Effect of Thalamic Deep Brain Stimulation Location on Verbal Abstraction.

BACKGROUND: Regionalized thalamic activity has been implicated in language function, and yet the effect of thalamic deep brain stimulation (DBS) on language-related clinical outcomes is underexplored. OBJECTIVE: The objective of this study was to determine if the location of stimulation within the thalamus correlates with changes in language-related neuropsychological outcomes following DBS for essential tremor. METHODS: Thirty patients with essential tremor underwent comprehensive neuropsychological evaluations before and after DBS surgery targeting the ventral intermediate nucleus of the thalamus. Changes in neuropsychological functions were evaluated. The relationships between language-related outcomes and stimulation location were assessed using both categorical and linear methods. Any significant results were further validated using linear discriminant analysis. RESULTS: Most neuropsychological functions remained unchanged at the group level. However, outcome on a measure of verbal abstraction was significantly dependent on stimulation location along the anterior-posterior axis within the left ventral lateral thalamus, with anterior stimulation associated with reduced verbal abstraction performance. This result was supported by linear discriminant analysis, which showed that stimulation locations with improved and reduced verbal abstraction function were best separated by a vector nearly parallel to the anterior-posterior axis. No stimulation location dependence was found for verbal abstraction outcome in the right thalamus or for outcomes of other language functions in either hemisphere. CONCLUSION: We demonstrate an effect of thalamic DBS on verbal abstraction as a function of left thalamic topography. This finding provides clinical evidence for the lateralization and regionalization of thalamic language function that may be relevant for understanding nonmotor effects of stimulation. © 2021 International Parkinson and Movement Disorder Society.

Association of Preoperative Visual Hallucinations With Cognitive Decline After Deep Brain Stimulation for Parkinson's Disease.

OBJECTIVE: Deep brain stimulation (DBS) is effective for the motor symptoms of Parkinson's disease (PD). Although most patients benefit with minimal cognitive side effects, cognitive decline is a risk, and there is little available evidence to guide preoperative risk assessment. Visual illusions or visual hallucinations (VHs) and impulse-control behaviors (ICBs) are relatively common complications of PD and its treatment and may be a marker of more advanced disease, but their relationship with postoperative cognition has not been established. The authors aimed to determine whether any preoperative history of VHs or ICBs is associated with cognitive change after DBS. METHODS: Retrospective chart review identified 54 patients with PD who received DBS of the subthalamic nucleus or globus pallidus internus and who completed both pre- and postoperative neuropsychological testing. Linear regression models were used to assess whether any preoperative history of VHs or ICBs was associated with changes in attention, executive function, language, memory, or visuospatial cognitive domains while controlling for surgical target and duration between evaluations. RESULTS: The investigators found that a history of VHs was associated with declines in attention (b=-4.04, p=0.041) and executive function (b=-4.24, p=0.021). A history of ICBs was not associated with any significant changes. CONCLUSIONS: These results suggest that a history of VHs may increase risk of cognitive decline after DBS; thus, specific preoperative counseling and targeted remediation strategies for these patients may be indicated. In contrast, a history of ICBs does not appear to be associated with increased cognitive risk.

Subthalamic Nucleus Activity Influences Sensory and Motor Cortex during Force Transduction.

The subthalamic nucleus (STN) is proposed to participate in pausing, or alternately, in dynamic scaling of behavioral responses, roles that have conflicting implications for understanding STN function in the context of deep brain stimulation (DBS) therapy. To examine the nature of event-related STN activity and subthalamic-cortical dynamics, we performed primary motor and somatosensory electrocorticography while subjects (n = 10) performed a grip force task during DBS implantation surgery. Phase-locking analyses demonstrated periods of STN-cortical coherence that bracketed force transduction, in both beta and gamma ranges. Event-related causality measures demonstrated that both STN beta and gamma activity predicted motor cortical beta and gamma activity not only during force generation but also prior to movement onset. These findings are consistent with the idea that the STN participates in motor planning, in addition to the modulation of ongoing movement. We also demonstrated bidirectional information flow between the STN and somatosensory cortex in both beta and gamma range frequencies, suggesting robust STN participation in somatosensory integration. In fact, interactions in beta activity between the STN and somatosensory cortex, and not between STN and motor cortex, predicted PD symptom severity. Thus, the STN contributes to multiple aspects of sensorimotor behavior dynamically across time.

Subthalamic Nucleus and Sensorimotor Cortex Activity During Speech Production.

The sensorimotor cortex is somatotopically organized to represent the vocal tract articulators such as lips, tongue, larynx, and jaw. How speech and articulatory features are encoded at the subcortical level, however, remains largely unknown. We analyzed LFP recordings from the subthalamic nucleus (STN) and simultaneous electrocorticography recordings from the sensorimotor cortex of 11 human subjects (1 female) with Parkinson's disease during implantation of deep-brain stimulation (DBS) electrodes while they read aloud three-phoneme words. The initial phonemes involved either articulation primarily with the tongue (coronal consonants) or the lips (labial consonants). We observed significant increases in high-gamma (60-150 Hz) power in both the STN and the sensorimotor cortex that began before speech onset and persisted for the duration of speech articulation. As expected from previous reports, in the sensorimotor cortex, the primary articulators involved in the production of the initial consonants were topographically represented by high-gamma activity. We found that STN high-gamma activity also demonstrated specificity for the primary articulator, although no clear topography was observed. In general, subthalamic high-gamma activity varied along the ventral-dorsal trajectory of the electrodes, with greater high-gamma power recorded in the dorsal locations of the STN. Interestingly, the majority of significant articulator-discriminative activity in the STN occurred before that in sensorimotor cortex. These results demonstrate that articulator-specific speech information is contained within high-gamma activity of the STN, but with different spatial and temporal organization compared with similar information encoded in the sensorimotor cortex.SIGNIFICANCE STATEMENT Clinical and electrophysiological evidence suggest that the subthalamic nucleus (STN) is involved in speech; however, this important basal ganglia node is ignored in current models of speech production. We previously showed that STN neurons differentially encode early and late aspects of speech production, but no previous studies have examined subthalamic functional organization for speech articulators. Using simultaneous LFP recordings from the sensorimotor cortex and the STN in patients with Parkinson's disease undergoing deep-brain stimulation surgery, we discovered that STN high-gamma activity tracks speech production at the level of vocal tract articulators before the onset of vocalization and often before related cortical encoding.

GABA bouton subpopulations in the human dentate gyrus are differentially altered in mesial temporal lobe epilepsy.

Medically intractable temporal lobe epilepsy is a devastating disease, for which surgical removal of the seizure onset zone is the only known cure. Multiple studies have found evidence of abnormal dentate gyrus network circuitry in human mesial temporal lobe epilepsy (MTLE). Principal neurons within the dentate gyrus gate entorhinal input into the hippocampus, providing a critical step in information processing. Crucial to that role are GABA-expressing neurons, particularly parvalbumin (PV)-expressing basket cells (PVBCs) and chandelier cells (PVChCs), which provide strong, temporally coordinated inhibitory signals. Alterations in PVBC and PVChC boutons have been described in epilepsy, but the value of these studies has been limited due to methodological hurdles associated with studying human tissue. We developed a multilabel immunofluorescence confocal microscopy and a custom segmentation algorithm to quantitatively assess PVBC and PVChC bouton densities and to infer relative synaptic protein content in the human dentate gyrus. Using en bloc specimens from MTLE subjects with and without hippocampal sclerosis, paired with nonepileptic controls, we demonstrate the utility of this approach for detecting cell-type specific synaptic alterations. Specifically, we found increased density of PVBC boutons, while PVChC boutons decreased significantly in the dentate granule cell layer of subjects with hippocampal sclerosis compared with matched controls. In contrast, bouton densities for either PV-positive cell type did not differ between epileptic subjects without sclerosis and matched controls. These results may explain conflicting findings from previous studies that have reported both preserved and decreased PV bouton densities and establish a new standard for quantitative assessment of interneuron boutons in epilepsy.NEW & NOTEWORTHY A state-of-the-art, multilabel immunofluorescence confocal microscopy and custom segmentation algorithm technique, developed previously for studying synapses in the human prefrontal cortex, was modified to study the hippocampal dentate gyrus in specimens surgically removed from patients with temporal lobe epilepsy. The authors discovered that chandelier and basket cell boutons in the human dentate gyrus are differentially altered in mesial temporal lobe epilepsy.

Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe epilepsy.

The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) remains poorly understood. The use of ex vivo hippocampal samples excised from patients with mTLE affords mesoscale diffusion magnetic resonance imaging (MRI) to identify individual cell layers, such as the pyramidal (PCL) and granule cell layers (GCL), which are thought to be impacted by seizure activity. Diffusion tensor imaging (DTI) of control (n = 3) and mTLE (n = 7) hippocampi on an 11.7 T MRI scanner allowed us to reveal intra-hippocampal connectivity and evaluate how epilepsy affected mean (MD), axial (AD), and radial diffusivity (RD), as well as fractional anisotropy (FA). Regional measurements indicated a volume loss in the PCL of the cornu ammonis (CA) 1 subfield in mTLE patients compared to controls, which provided anatomical context. Diffusion measurements, as well as streamline density, were generally higher in mTLE patients compared to controls, potentially reflecting differences due to tissue fixation. mTLE measurements were more variable than controls. This variability was associated with disease severity, as indicated by a strong correlation (r = 0.87) between FA in the stratum radiatum and the frequency of seizures in patients. MD and RD of the PCL in subfields CA3 and CA4 also correlated strongly with disease severity. No correlation of MR measures with disease duration was evident. These results reveal the potential of mesoscale diffusion MRI to examine layer-specific diffusion changes and connectivity to determine how these relate to clinical measures. Improving the visualization of intra-hippocampal connectivity will advance the development of novel hypotheses about seizure networks.

Mesoscale diffusion magnetic resonance imaging of the ex vivo human hippocampus.

Mesoscale diffusion magnetic resonance imaging (MRI) endeavors to bridge the gap between macroscopic white matter tractography and microscopic studies investigating the cytoarchitecture of human brain tissue. To ensure a robust measurement of diffusion at the mesoscale, acquisition parameters were arrayed to investigate their effects on scalar indices (mean, radial, axial diffusivity, and fractional anisotropy) and streamlines (i.e., graphical representation of axonal tracts) in hippocampal layers. A mesoscale resolution afforded segementation of the pyramidal cell layer (CA1-4), the dentate gyrus, as well as stratum moleculare, radiatum, and oriens. Using ex vivo samples, surgically excised from patients with intractable epilepsy (n = 3), we found that shorter diffusion times (23.7 ms) with a b-value of 4,000 s/mm2 were advantageous at the mesoscale, providing a compromise between mean diffusivity and fractional anisotropy measurements. Spatial resolution and sample orientation exerted a major effect on tractography, whereas the number of diffusion gradient encoding directions minimally affected scalar indices and streamline density. A sample temperature of 15°C provided a compromise between increasing signal-to-noise ratio and increasing the diffusion properties of the tissue. Optimization of the acquisition afforded a system's view of intra- and extra-hippocampal connections. Tractography reflected histological boundaries of hippocampal layers. Individual layer connectivity was visualized, as well as streamlines emanating from individual sub-fields. The perforant path, subiculum and angular bundle demonstrated extra-hippocampal connections. Histology of the samples confirmed individual cell layers corresponding to ROIs defined on MR images. We anticipate that this ex vivo mesoscale imaging will yield novel insights into human hippocampal connectivity.

Magnetic resonance imaging-guided phase 1 trial of putaminal AADC gene therapy for Parkinson's disease.

OBJECTIVE: To understand the safety, putaminal coverage, and enzyme expression of adeno-associated viral vector serotype-2 encoding the complementary DNA for the enzyme, aromatic L-amino acid decarboxylase (VY-AADC01), delivered using novel intraoperative monitoring to optimize delivery. METHODS: Fifteen subjects (three cohorts of 5) with moderately advanced Parkinson's disease and medically refractory motor fluctuations received VY-AADC01 bilaterally coadministered with gadoteridol to the putamen using intraoperative magnetic resonance imaging (MRI) guidance to visualize the anatomic spread of the infusate and calculate coverage. Cohort 1 received 8.3 × 1011 vg/ml and ≤450 µl per putamen (total dose, ≤7.5 × 1011 vg); cohort 2 received the same concentration (8.3 × 1011 vg/ml) and ≤900 µl per putamen (total dose, ≤1.5 × 1012 vg); and cohort 3 received 2.6 × 1012 vg/ml and ≤900 µl per putamen (total dose, ≤4.7 × 1012 vg). (18)F-fluoro-L-dihydroxyphenylalanine positron emission tomography (PET) at baseline and 6 months postprocedure assessed enzyme activity; standard assessments measured clinical outcomes. RESULTS: MRI-guided administration of ascending VY-AADC01 doses resulted in putaminal coverage of 21% (cohort 1), 34% (cohort 2), and 42% (cohort 3). Cohorts 1, 2, and 3 showed corresponding increases in enzyme activity assessed by PET of 13%, 56%, and 79%, and reductions in antiparkinsonian medication of -15%, -33%, and -42%, respectively, at 6 months. At 12 months, there were dose-related improvements in clinical outcomes, including increases in patient-reported ON-time without troublesome dyskinesia (1.6, 3.3, and 1.5 hours, respectively) and quality of life. INTERPRETATION: Novel intraoperative monitoring of administration facilitated targeted delivery of VY-AADC01 in this phase 1 study, which was well tolerated. Increases in enzyme expression and clinical improvements were dose dependent. ClinicalTrials.gov Identifier: NCT01973543 Ann Neurol 2019;85:704-714.

Data-driven evolution of neurosurgical gene therapy delivery in Parkinson's disease.

Loss of nigrostriatal dopaminergic projection neurons is a key pathology in Parkinson's disease, leading to abnormal function of basal ganglia motor circuits and the accompanying characteristic motor features. A number of intraparenchymally delivered gene therapies designed to modify underlying disease and/or improve clinical symptoms have shown promise in preclinical studies and subsequently were evaluated in clinical trials. Here we review the challenges with surgical delivery of gene therapy vectors that limited therapeutic outcomes in these trials, particularly the lack of real-time monitoring of vector administration. These challenges have recently been addressed during the evolution of novel techniques for vector delivery that include the use of intraoperative MRI. The preclinical development of these techniques are described in relation to recent clinical translation in an adeno-associated virus serotype 2-mediated human aromatic L-amino acid decarboxylase gene therapy development programme. This new paradigm allows visualisation of the accuracy and adequacy of viral vector delivery within target structures, enabling intertrial modifications in surgical approaches, cannula design, vector volumes and dosing. The rapid, data-driven evolution of these procedures is unique and has led to improved vector delivery.