arXiv subjects

Heather Woodhouse

Publications and source records attributed to Heather Woodhouse.

4 recordsLinked to original sources

arXiv2025

From Bedside to Desktop: A Data Protocol for Normative Intracranial EEG and Abnormality Mapping

Normative mapping is a framework used to map population-level features of health-related variables. It is widely used in neuroscience research, but the literature lacks established protocols in modalities that do not support healthy control measurements, such as intracranial EEG (icEEG). An icEEG normative map would allow researchers to learn about population-level brain activity and enable comparison of individual data against these norms to identify abnormalities. Currently, no standardised guide exists for transforming clinical data into a normative, regional icEEG map. Papers often cite different software and numerous articles to summarise the lengthy method, making it laborious for other researchers to understand or apply the process. Our protocol seeks to remedy this gap by providing a dataflow guide and key decision points that summarise existing methods. This protocol is used heavily in published works from our own lab (twelve peer-reviewed journal publications). Briefly, we take as input, icEEG recordings and neuroimaging data from people with epilepsy who are undergoing evaluation for resective surgery. As final outputs, we obtain a normative icEEG map, comprising signal properties localised to brain regions. Optionally, we can also process new subjects through the same pipeline and obtain their z-scores (or centiles) in each brain region, for abnormality detection and localisation. To date, a single, cohesive, dataflow pipeline for generating normative icEEG maps, along with abnormality mapping, has not been created. We envisage that this dataflow guide will not only increase understanding and application of normative mapping methods, but will also improve the consistency and quality of studies in the field.

q-bio.NC↗

arXiv2024

Comparing Methodological Variations in Seizure Onset Localisation Algorithms using intracranial EEG

During clinical treatment for epilepsy, the area of the brain thought to be responsible for pathological activity is identified. This identification is typically performed through visual assessment of EEG recordings; however, this is time consuming and prone to subjective inconsistency. Automated onset localisation algorithms provide objective identification of the onset location by highlighting changes in signal features associated with seizure onset. In this work we investigate how methodological differences in such algorithms can result in different onset locations being identified. We analysed ictal intracranial EEG (icEEG) recordings in 16 subjects (100 seizures) with drug-resistant epilepsy from the SWEZ-ETHZ public database. We identified a series of key methodological differences that must be considered when designing or selecting an onset localisation algorithm. These differences were demonstrated using three distinct algorithms that capture different, but complementary, seizure onset features: Imprint, Epileptogenicity Index, and Low Entropy Map. We assessed methodological differences (or Decision Points), and their impact on the identified onset locations. Our independent application of all three algorithms to the same ictal icEEG dataset revealed low agreement between them: 27-60% of onset channels showed minimal or no overlap. Therefore, we investigated the effect of three key differences: (i) how to define a baseline, (ii) whether low-frequency components are considered, and finally (iii) whether electrodecrement is considered. Changes at each Decision Point were found to substantially influence resultant onset channels (r>0.3). Our results demonstrate how seemingly small methodological changes can result in large differences in onset locations. We propose that key Decision Points must be considered when using or designing an onset localisation algorithm.

q-bio.NC↗

arXiv2024

Multi-centre normative brain mapping of intracranial EEG lifespan patterns in the human brain

Background: Understanding healthy human brain function is crucial to identify and map pathological tissue within it. Whilst previous studies have mapped intracranial EEG (icEEG) from non-epileptogenic brain regions, these maps do not consider the effects of age and sex. Further, most existing work on icEEG has often suffered from a small sample size due to the modality's invasive nature. Here, we substantially increase the subject sample size compared to existing literature, to create a multi-centre, normative map of brain activity which additionally considers the effects of age, sex and recording hospital. Methods: Using interictal icEEG recordings from n = 502 subjects originating from 15 centres, we constructed a normative map of non-pathological brain activity by regressing age and sex on relative band power in five frequency bands, whilst accounting for the hospital effect. Results: Recording hospital significantly impacted normative icEEG maps in all frequency bands, and age was a more influential predictor of band power than sex. The age effect varied by frequency band, but no spatial patterns were observed at the region-specific level. Certainty about regression coefficients was also frequency band specific and moderately impacted by sample size. Conclusion: The concept of a normative map is well-established in neuroscience research and particularly relevant to the icEEG modality, which does not allow healthy control baselines. Our key results regarding the hospital site and age effect guide future work utilising normative maps in icEEG.

q-bio.NC↗

arXiv2023

Incomplete resection of the icEEG seizure onset zone is not associated with post-surgical outcomes

Delineation of seizure onset regions from EEG is important for effective surgical workup. However, it is unknown if their complete resection is required for seizure freedom, or in other words, if post-surgical seizure recurrence is due to incomplete removal of the seizure onset regions. Retrospective analysis of icEEG recordings from 63 subjects (735 seizures) identified seizure onset regions through visual inspection and algorithmic delineation. We analysed resection of onset regions and correlated this with post-surgical seizure control. Most subjects had over half of onset regions resected (70.7% and 60.5% of subjects for visual and algorithmic methods, respectively). In investigating spatial extent of onset or resection, and presence of diffuse onsets, we found no substantial evidence of association with post-surgical seizure control (all AUC<0.7, p>0.05). Seizure onset regions tends to be at least partially resected, however a less complete resection is not associated with worse post-surgical outcome. We conclude that seizure recurrence after epilepsy surgery is not necessarily a result of failing to completely resect the seizure onset zone, as defined by icEEG. Other network mechanisms must be involved, which are not limited to seizure onset regions alone.

q-bio.NC↗