Biology subjects

Kochalka, J.

Publications and source records attributed to Kochalka, J..

3 recordsLinked to original sources

bioRxiv2026

Ultrasensitive voltage imaging reveals distinct electrical microdomains in neurons

For the brain to compute, electrical signals must propagate over the membranes of individual neurons, connecting synaptic inputs to synaptic outputs1. Complex neuronal morphologies coupled with the spatial organization of synaptic inputs and outputs enable diverse voltage transformations that underlie cell-type specific computations2,3. However, measuring these transformations in vivo has remained challenging, leaving a crucial gap in our mechanistic understanding of single neuron computation. Here, we develop ASAP7y, a genetically encoded voltage indicator with unprecedented subthreshold sensitivity and expanded excitation compatibility in both mice and flies. We leveraged ASAP7y combined with two-photon random-access microscopy to record sensory stimulus-evoked voltage dynamics with millisecond, subcellular, and subthreshold resolution along the neurites of individual neurons in Drosophila. We found remarkable heterogeneity in voltage propagation across cell-types, delineating a fundamental axis of electrical diversity. Leveraging a nanoscale EM reconstruction of the visual system4, we modeled the electrotonic properties of single neurons spanning 717 cell types, revealing how morphology shapes voltage transformations. Finally, we demonstrate that confined voltage propagation creates substrates for local computation, producing subcellular domains with distinct feature selectivity across multiple cell types. These results provide mechanistic insight into how critical single neuron computations arise and reveal parallel processing in single neurons.

neuroscience↗

bioRxiv2026

Intrinsic space-time couplings governing multi-scale cortical dynamics

The neocortex covers a vast expanse of the mammalian brain and represents the principal target of clinical neuromodulation; however, the global principles of neocortical operation have been challenging to identify. In this regard, a limitation has been tracking activity with cortex-wide spatial coverage while maintaining access to the millisecond temporal resolution of neuronal firing-- a crucial combination not achievable with existing recording technologies. Here we introduce and apply conformal immersion microscopy, enabling activity tracking across the entire dorsal cortex with millisecond temporal resolution and 100 {micro}m spatial resolution (thus spanning five orders of magnitude in time and four in space), at sufficient sensitivity to resolve single-trial activity beyond 100 Hz. Drawing on physics-based frameworks, we apply multiscale analysis to identify a fundamental frequency-dependent coherence length that partitions the neocortex into discrete dynamical elements with well-defined propagation speeds, boundaries, and scale-invariant dynamics. These dynamical elements were found to be conserved from sub-threshold to suprathreshold (neuronal firing) regimes of neural activity, and were robust to diverse pharmacological, optogenetic, and genetic interventions. However, it was possible to identify and establish conditions allowing elemental boundaries to be selectively overridden, and to allow perturbation of specific elements even while conserving global dynamical architecture. Together, these findings enable measurement of intrinsic spatiotemporal parameters governing the dynamical organization of neocortex, which may provide a foundation for mechanistically-informed basic and translational understanding.

neuroscience↗

bioRxiv2026

Causal and directional elements of global brain dynamics

Mammalian cognition appears to involve coordinated neural activity within and across brain-spanning networks. However, the governing principles of large-scale integration remain largely unknown. Here we developed an approach to record spontaneous cortex-wide neural activity (including with novel genetically encoded activity sensors), over very long timescales, and applied unbiased computation to capture conserved spatiotemporal regularities in these data. Initial screening extracted a set of directional elements: consistent spatiotemporal patterns of cortical activity that generalized across excitatory and inhibitory neuronal cell types as revealed by genetic targeting of activity sensors. In particular, novel genetically encoded voltage-sensing strategies revealed that the directional elements were not only highly conserved, but also were represented across the full neural activity frequency spectrum including the fastest timescales (gamma rhythms) enabled by voltage-sensing. Exploiting the spatiotemporal structure revealed by these directional elements, we tested for causal rules governing cortical network activation, using patterned optogenetic stimulation combined with activity imaging. We found that the directional propagation structure of these elements encoded a causal control hierarchy, as source regions (but not sink regions) sufficed to drive full element recruitment--a principle that held across all tested directional elements. Employing a panel of psychotropic drugs, we showed that directional element structure and excitability were robust to manipulations of neural and behavioral state, even as spontaneous network dynamics were reshaped in compound-specific ways. Finally, we developed and applied an all-optical sensing/control approach targeting the directional elements in a behavioral visual detection paradigm, revealing contributions of these conserved large-scale dynamics to elevated sensorimotor behavioral performance.

neuroscience↗