Biology subjects

Shanahan, M.

Publications and source records attributed to Shanahan, M..

4 recordsLinked to original sources

bioRxiv2025

Patterns of brain-wide associations reflect socioeconomics

Previous brain-wide association studies (BWAS) cross-sectionally linked a specific behavioral trait, most commonly IQ or psychopathology, to variation in brain function or structure. Here, we expanded the focus of BWAS from effect sizes to interpretability and generalizability by mapping 649 variables to brain function and structure. We compared the resultant BWAS maps to other types of brain data to annotate the BWAS patterns. Socioeconomic status (SES) -- not IQ or psychopathology -- showed the strongest associations with both resting-state functional connectivity (RSFC) and cortical thickness in the Adolescent Brain Cognitive Development (ABCD) Study. A principal exposome brain pattern, anchored to sensory and motor cortex, captured 34% of the variance across all BWAS maps. This exposome pattern was strongly correlated with the SES and IQ BWAS maps and non-BWAS maps of sleep (EEG), norepinephrine (PET), and stimulants (drug trial), but not cognitive activation maps (task fMRI). Adjusting for SES, reduced brain-IQ associations by 40%. Brain with IQ associations did not generalize, as they could no longer be detected in subsamples drawn from only higher SES backgrounds, while brain with SES associations remained strong in higher-IQ-only subsamples. These findings reveal SES as the principal axis of population-level brain variation, possibly stemming from the sleep deprivation and heightened stress associated with lower SES, since socioeconomics can only indirectly affect the brain.

neuroscience↗

bioRxiv2020

A predictive processing model of episodic memory and time perception

Human perception and experience of time is strongly influenced by ongoing stimulation, memory of past experiences, and required task context. When paying attention to time, time experience seems to expand; when distracted, it seems to contract. When considering time based on memory, the experience may be different than in the moment, exemplified by sayings like "time flies when youre having fun". Experience of time also depends on the content of perceptual experience - rapidly changing or complex perceptual scenes seem longer in duration than less dynamic ones. The complexity of interactions between attention, memory, and perceptual stimulation is a likely reason that an overarching theory of time perception has been difficult to achieve. Here, we introduce a model of perceptual processing and episodic memory that makes use of hierarchical predictive coding, short-term plasticity, spatio-temporal attention, and episodic memory formation and recall, and apply this model to the problem of human time perception. In an experiment with ~ 13, 000 human participants we investigated the effects of memory, cognitive load, and stimulus content on duration reports of dynamic natural scenes up to ~ 1 minute long. Using our model to generate duration estimates, we compared human and model performance. Model-based estimates replicated key qualitative biases, including differences by cognitive load (attention), scene type (stimulation), and whether the judgement was made based on current or remembered experience (memory). Our work provides a comprehensive model of human time perception and a foundation for exploring the computational basis of episodic memory within a hierarchical predictive coding framework. Author summaryExperience of the duration of present or past events is a central aspect of human experience, the underlying mechanisms of which are not yet fully understood. In this work, we combine insights from machine learning and neuroscience to propose a combination of mathematical models that replicate human perceptual processing, long-term memory, attention, and duration perception. Our computational implementation of this framework can process information from video clips of ordinary life scenes, record and recall important events, and report the duration of these clips. To assess the validity of our proposal, we conducted an experiment with ~ 13, 000 human participants. Each was shown a video between 1-64 seconds long and reported how long they believed it was. Reports of duration by our computational model qualitatively matched these human reports, made about the exact same videos. This was true regardless of the video content, whether time was actively judged or based on memory of the video, or whether the participants focused on a single task or were distracted - all factors known to influence human time perception. Our work provides the first model of human duration perception to incorporate these diverse and complex factors and provides a basis to probe the deep links between memory and time in human experience.

neuroscience↗

bioRxiv2017

Assessing Selectivity in the Basal Ganglia: The "Gearbox" Hypothesis

A plethora of evidence and theoretical work indicates that the basal ganglia (BG) might be the locus where conflicts between prospective motor programs, or actions, are being resolved. Similarly to the majority of brain regions, oscillations in this subcortical group are ubiquitous, largely driven by the cortex and associated with a number of motor symptoms in neurodegenerative diseases. However, the literature so far contains no systematic attempt to address the impact of cortical oscillations on the ability of the BG to select. In this study, we employed a state of the art spiking neural model of the BG circuitry and investigated the effectiveness of the BG as an action selection device. We found that cortical frequency, phase, dopamine and the examined time scale, all have a very important impact on the models ability to select. Our simulations resulted n a canonical profile of selectivity, termed selectivity portraits, which suggests that the cortex is the structure that determines whether selection will be performed in the BG and what strategy will be utilized. Some frequency ranges promote the exploitation of highly salient actions, others promote the exploration of alternative options, while the remaining frequencies simply halt the selection process. Based on this behaviour, we propose that the BG circuitry can be viewed as the \"gearbox\" of action selection. Coalitions of rhythmic cortical areas are able to switch between a repertoire of available BG modes which, in turn, change the course of information flow within the Cortico BG thalamo cortical loop. Dopamine, akin to \"control pedals\", either stops or initiates a decision, while cortical frequencies, as a \"gear lever\", determine whether a decision can be triggered and what type of decision this will be. Finally, we identified a selection cycle with a period of around 200ms, which was used to assess the biological plausibility of the popular cognitive architectures.

neuroscience↗

bioRxiv2017

A functioning model of human time perception

Despite being a fundamental dimension of experience, how the human brain generates the perception of time remains unknown. Here, we provide a novel explanation for how human time perception might be accomplished, based on non-temporal perceptual clas-sification processes. To demonstrate this proposal, we built an artificial neural system centred on a feed-forward image classification network, functionally similar to human visual processing. In this system, input videos of natural scenes drive changes in network activation, and accumulation of salient changes in activation are used to estimate duration. Estimates produced by this system match human reports made about the same videos, replicating key qualitative biases, including differentiating between scenes of walking around a busy city or sitting in a cafe or office. Our approach provides a working model of duration perception from stimulus to estimation and presents a new direction for examining the foundations of this central aspect of human experience.

neuroscience↗