Biology subjects

Jones, H. M.

Publications and source records attributed to Jones, H. M..

10 recordsLinked to original sources

bioRxiv2025

Decoding Distraction From the Human Brain: A Unique Neural Signature Beyond Failures of Selective Attention and Control

Attentional lapses are a ubiquitous feature of cognition, yet their underlying causes remain poorly understood. Theories of sustained attention often point to failures of cognitive control in maintaining the task-set, while data-driven approaches suggest that lapses may instead reflect a breakdown in the selection of task-relevant information. This study aimed to characterize the neural mechanisms of sustained attention lapses and to test whether EEG-based signatures of lapse-prone states are distinct from signatures of failures of selective attention and task-set maintenance. Twenty adults completed a sustained attention go/no-go task while focusing on either numbers or letters, with EEG recorded simultaneously. Poor sustained attention was examined at two complementary levels: trial-level lapses, defined as no-go errors, and attentional states, derived from reaction-time variability and categorized as "in-the-zone" versus "out-of-the-zone". Across both levels, suboptimal sustained attention was associated with attenuated event-related potentials, most notably a reduced parietal P3 amplitude and weaker whole-scalp inter-electrode correlation. To isolate a unique EEG marker of lapse-prone state, a machine-learning classifier decoded attentional state from EEG activity. Cross-validated accuracy reached [~]80% and remained robust after controlling for reaction time. Finally, representational similarity analysis confirmed that this neural signature was dissociable from stimulus-side selection and task-set maintenance.

neuroscience↗

bioRxiv2025

Population-Level Activity Dissociates Preparatory Overt from Covert Attention

The neural signatures of preparing overt eye movements and directing covert spatial attention overlap as they recruit the same brain areas. Yet, these neural signatures are dissociable at the single-cell level: Specific cells within visuo-oculomotor areas are exclusively involved in motor preparation or covert attention. Nevertheless, it has been proposed that many cells in visuo-oculomotor areas are involved in both motor preparation and covert attention, and consequently their neural signatures should functionally overlap to a large degree. Here, we directly tested this proposal: we combined human (both sexes) EEG with sensitive decoding techniques to investigate whether the neural signatures of preparatory overt and covert attention are dissociable across large-scale neuronal populations. We found that neural decoding reliably discerned whether overt or covert attention was shifted well before saccade initiation. Further, inverted encoding modeling revealed earlier and sharper spatially-tuned activity in preparatory overt than in covert attention. We then asked whether preparatory overt attention achieved sharper spatially-tuned activity by using more-of-the-same covert attention, or by recruiting additional spatially selective neural processing. Cross-decoding results demonstrated that preparatory overt attention recruited at least one additional, frontal process. This additional spatially selective process emerged early and likely reflects motor preparation or predictive remapping. To summarize, we found that the neural signatures of overt and covert attention overlap, yet diverge rapidly, in part because overt attention employs an additional spatially selective neural process. Extending beyond a dissociation on the single-cell level, our findings demonstrate that population-level neural activity dissociates preparatory overt from covert attention. Significance statementThe world provides much more visual input than the brain can process simultaneously. Spatial visual attention allows for the selective processing of only the most important parts of this input. Spatial attention shifts either overtly (with an eye movement) or covertly (without an accompanying eye movement). The neural signatures underlying these types of spatial attention have long thought to overlap to a large degree. This strong overlap was thought to only break down at the level of single neurons. In our EEG study, we instead demonstrate that large populations of neurons dissociate overt from covert attention. Our results show that the neural signatures of overt and covert attention differ on a much broader scale than previously thought.

neuroscience↗

bioRxiv2025

A Bivalent Molecular Glue Linking Lysine Acetyltransferases to Oncogene-induced Cell Death

Developing cancer therapies that induce robust death of the malignant cell is critical to prevent relapse. Highly effective strategies, such as immunotherapy, exemplify this observation. Here we provide the structural and molecular underpinnings for an approach that leverages chemical induced proximity to produce specific cell killing of diffuse large B cell lymphoma, the most common non-Hodgkins lymphoma. We develop KAT-TCIPs (lysine acetyltransferase transcriptional/epigenetic chemical inducers of proximity) that redirect p300 and CBP to activate programmed cell death genes normally repressed by the oncogenic driver, BCL6. Acute treatment rapidly reprograms the epigenome to initiate apoptosis and repress c-MYC. The crystal structure of the chemically induced p300-BCL6 complex reveals how chance interactions between the two proteins can be systematically exploited to produce the exquisite potency and selectivity of KAT-TCIPs. Thus, the malignant function of an oncogenic driver can be co-opted to activate robust cell death, with implications for precision epigenetic therapies.

cancer biology↗

bioRxiv2024

Development of potent and selective CK1α Molecular Glue Degraders

Molecular glue degraders (MGDs) are small molecules that facilitate proximity between a target protein and an E3 ubiquitin ligase thereby inducing target protein degradation. Glutarimide-containing compounds are MGDs that bind to cereblon (CRBN) and recruit neosubstrates. Through explorative synthesis of a glutarimide-based library, we discovered a series of molecules that induce casein kinase 1 alpha (CK1) degradation. By scaffold hopping and rational modification of the chemical scaffold, we identified an imidazo[1,2-a]pyrimidine compound that induces potent and selective CK1 degradation. A structure-activity relationship study of the lead compound, QXG-6442, identified the structural features that contribute to degradation potency and selectivity compared to other frequently observed neosubstrates. The glutarimide library screening and structure activity relationship medicinal chemistry approach we employed is generally useful for developing new molecular glue degraders towards new targets of interest.

biochemistry↗

bioRxiv2024

Discovery of electrophilic degraders that exploit SNAr chemistry

Targeted covalent inhibition (TCI) and targeted protein degradation (TPD) have proven effective in pharmacologically addressing formerly undruggable targets. Integration of both methodologies has resulted in the development of electrophilic degraders where recruitment of a suitable E3 ubiquitin ligase is achieved through formation of a covalent bond with a cysteine nucleophile. Expanding the scope of electrophilic degraders requires the development of electrophiles with tempered reactivity that enable selective ligase recruitment and reduce cross-reactivity with other cellular nucleophiles. In this study, we report the use of chemical moieties that enable nucleophilic aromatic substitution (SNAr) reactions in the rational design of electrophilic protein degraders. Appending an SNAr covalent warhead to several preexisting small molecule inhibitors transformed them into degraders, obviating the need for a defined E3 ligase recruiter. The SNAr covalent warhead is versatile; it can recruit various E3 ligases, including DDB1 and CUL4 associated factor 11 (DCAF11), DDB1 and CUL4 associated factor 16 (DCAF16), and possibly others. The incorporation of an SNAr covalent warhead into the BRD4 inhibitor led to the discovery of degraders with low picomolar degradation potency. Furthermore, we demonstrate the broad applicability of this approach through rational functional switching from kinase inhibitors into potent degraders.

biochemistry↗

bioRxiv2023

Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation

We describe the following shared data from N=103 healthy adults who completed a broad set cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90- minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. Subjects also completed resting state scans. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard.

neuroscience↗

bioRxiv2023

Edge-based general linear models capture high-frequency fluctuations in attention

Although we must prioritize the processing of task-relevant information to navigate life, our ability to do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individuals ability to sustain attention and vary with attentional state from one minute to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-by-moment network fluctuations. Recently, researchers have unfurled traditional FC matrices in edge cofluctuation time series which measure time point-by-time point cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture high-frequency fluctuations in networks related to attention. In two independent fMRI datasets in which participants performed a sustained attention task, we identified a reliable set of edges that rapidly deflects in response to rare task events. Another set of edges varies with continuous fluctuations in attention and overlaps with a previously defined set of edges associated with individual differences in sustained attention. Demonstrating that edge-based analyses are not simply redundant with traditional regions-of-interest based approaches, up to one-third of reliably deflected edges were not predicted from univariate activity patterns alone. These results reveal the large potential in combining traditional fMRI analyses with edge time series to identify rapid reconfigurations in networks across the brain.

neuroscience↗

bioRxiv2023

The response time paradox in functional magnetic resonance imaging analyses

The functional MRI (fMRI) signal is a proxy for an unobservable neuronal signal, and differences in fMRI signals on cognitive tasks are generally interpreted as reflecting differences in the intensity of local neuronal activity. However, changes in either intensity or duration of neuronal activity can yield identical differences in fMRI signals. When conditions differ in response times (RTs), it is thus impossible to determine whether condition differences in fMRI signals are due to differences in the intensity of neuronal activity or to potentially spurious differences in the duration of neuronal activity. The most common fMRI analysis approach ignores RTs, making it difficult to interpret condition differences that could be driven by RTs and/or intensity. Because differences in response time are one of the most important signals of interest for cognitive psychology, nearly every task of interest for fMRI exhibits RT differences across conditions of interest. This results in a paradox, wherein the signal of interest for the psychologist is a potential confound for the fMRI researcher. We review this longstanding problem, and demonstrate that the failure to address RTs in the fMRI time series model can also lead to spurious correlations at the group level related to RTs or other variables of interest, potentially impacting the interpretation of brain-behavior correlations. We propose a simple approach that remedies this problem by including RT in the fMRI time series model. This model separates condition differences from RT differences, retaining power for detection of unconfounded condition differences while also allowing the identification of RT-related activation. We conclude by highlighting the need for further theoretical development regarding the interpretation of fMRI signals and their relationship to response times.

neuroscience↗

bioRxiv2022

A Genome Scale Transcriptional Regulatory Model of the Human Placenta

Gene regulation is essential to placental function and fetal development. We report a genome-scale transcriptional regulatory network (TRN) of the human placenta built using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)-target gene interactions. In an independent dataset, the TRN model predicted target gene expression with an out of sample R2 value greater than 0.25 for 74% of target genes. We performed siRNA knockdowns of 4 TFs and achieved concordance between the predicted gene targets in our TRN and differences in expression of knockdowns with an accuracy of >0.7 for 3 of the 4 TFs. Our final model contained 113,158 interactions across 391 TFs and 7,712 target genes and is publicly available. We identified six TFs which were significantly enriched as regulators for genes previously associated with preterm birth.

systems biology↗

bioRxiv2020

Neural representation of abstract task structure during generalization

Cognitive models in psychology and neuroscience widely assume that the human brain maintains an abstract representation of tasks. This assumption is fundamental to theories explaining how we learn quickly, think creatively, and act flexibly. However, neural evidence for a verifiably generative abstract task representation has been lacking. Here, we report an experimental paradigm that requires forming such a representation to act adaptively in novel conditions without feedback. Using functional magnetic resonance imaging, we observed that abstract task structure was represented within left mid-lateral prefrontal cortex, bilateral precuneus and inferior parietal cortex. These results provide support for the neural instantiation of the long-supposed abstract task representation in a setting where we can verify its influence. Such a representation can afford massive expansions of behavioral flexibility without additional experience, a vital characteristic of human cognition.

neuroscience↗