Biology subjects

McGregor, J. N.

Publications and source records attributed to McGregor, J. N..

3 recordsLinked to original sources

bioRxiv2026

Amyloidosis and tauopathy progressively disrupt near-critical dynamics in selectively vulnerable circuits

Mechanistically distinct neurodegenerative diseases result in similar cognitive deficits, and pathology is often concentrated in a set of circuits known to be selectively vulnerable. Selective vulnerability is an intrinsic property of a circuit: in APP/PS1 mice, where plaques are global, functional disruptions are confined to circuits within the default mode network. What characterizes the dynamics of vulnerable circuits from those of spared circuits is unknown. We asked whether the distinguishing property is the proximity of population dynamics to criticality, a homeostatic set-point of network activity that determines computational capacity. We recorded single units simultaneously in three selectively vulnerable regions (retrosplenial cortex, anterior cingulate cortex, and CA1 hippocampus) and in primary visual cortex of freely behaving young and old APP/PS1 and wild-type mice. Firing rate and spike-time variability differed by genotype inconsistently across regions and ages. In contrast, three measures from criticality theory each revealed deficits that emerged only with age and only in the vulnerable regions. No measure detected a progressive change in V1. Avalanche scaling is not fixed in neural activity, but varies along a scaling line as the network state changes. As a result, the lines generated by each genotype revealed a constitutive effect of the transgene in young animals, which inverted with age in amyloid-bearing animals, but only in vulnerable circuits. If the destabilization of near-critical dynamics directly reflects a circuit's functional capacity, the same signature should identify a mechanistically distinct degenerative disease. In a model of tauopathy (P301S/E4), CA1 dynamics were displaced from the control scaling line with the same age-dependent reversal observed in APP/PS1. Our results suggest a network-level principle of neurodegenerative diseases: molecularly unrelated pathologies converge on the loss of near-critical dynamics in selectively vulnerable circuits.

neuroscience↗

bioRxiv2026

Environmental complexity reveals memory-guided search as the locus of learning in prey capture

Ethological behavior requires the integration of perception, memory, and decision-making, yet standard laboratory tasks are often too simplified to recruit these processes jointly. Here, mice that were expert hunters in a bare arena were challenged to capture live insect prey among objects that occlude vision and afford opportunities to hide. This revealed an axis of learning absent in an empty arena: mice improved not by refining pursuit but by reorganizing how they searched for concealed prey. An agent-based model showed that short-term memory and learning of object-specific values are sufficient to account for the behavior demonstrated by mice. A compact ethogram of object-directed actions revealed that animals selectively acquired the interactions most likely to expose prey. These results show that environmental complexity recruits memory- and value-guided search strategies. Reproducible with inexpensive materials, the paradigm and its open-source analyses offer a sensitive read-out of cognitive processes largely unobservable in conventional assays.

neuroscience↗

bioRxiv2023

Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not the activity of individual neurons.

The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the networks nearness to criticality, an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animals genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.

neuroscience↗