MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures.

Microelectrode array (MEA) recordings are commonly used to compare firing and burst rates in neuronal cultures. MEA recordings can also reveal microscale functional connectivity, topology, and network dynamics-patterns seen in brain networks across spatial scales. Network topology is frequently characterized in neuroimaging with graph theoretical metrics. However, few computational tools exist for analyzing microscale functional brain networks from MEA recordings. Here, we present a MATLAB MEA network analysis pipeline (MEA-NAP) for raw voltage time-series acquired from single- or multi-well MEAs. Applications to 3D human cerebral organoids or 2D human-derived or murine cultures reveal differences in network development, including topology, node cartography, and dimensionality. MEA-NAP incorporates multi-unit template-based spike detection, probabilistic thresholding for determining significant functional connections, and normalization techniques for comparing networks. MEA-NAP can identify network-level effects of pharmacologic perturbation and/or disease-causing mutations and, thus, can provide a translational platform for revealing mechanistic insights and screening new therapeutic approaches.

Mouse frontal cortex mediates additive multisensory decisions.

The brain can combine auditory and visual information to localize objects. However, the cortical substrates underlying audiovisual integration remain uncertain. Here, we show that mouse frontal cortex combines auditory and visual evidence; that this combination is additive, mirroring behavior; and that it evolves with learning. We trained mice in an audiovisual localization task. Inactivating frontal cortex impaired responses to either sensory modality, while inactivating visual or parietal cortex affected only visual stimuli. Recordings from >14,000 neurons indicated that after task learning, activity in the anterior part of frontal area MOs (secondary motor cortex) additively encodes visual and auditory signals, consistent with the mice's behavioral strategy. An accumulator model applied to these sensory representations reproduced the observed choices and reaction times. These results suggest that frontal cortex adapts through learning to combine evidence across sensory cortices, providing a signal that is transformed into a binary decision by a downstream accumulator.

Behavioral origin of sound-evoked activity in mouse visual cortex.

Sensory cortices can be affected by stimuli of multiple modalities and are thus increasingly thought to be multisensory. For instance, primary visual cortex (V1) is influenced not only by images but also by sounds. Here we show that the activity evoked by sounds in V1, measured with Neuropixels probes, is stereotyped across neurons and even across mice. It is independent of projections from auditory cortex and resembles activity evoked in the hippocampal formation, which receives little direct auditory input. Its low-dimensional nature starkly contrasts the high-dimensional code that V1 uses to represent images. Furthermore, this sound-evoked activity can be precisely predicted by small body movements that are elicited by each sound and are stereotyped across trials and mice. Thus, neural activity that is apparently multisensory may simply arise from low-dimensional signals associated with internal state and behavior.

Characterization of exploratory patterns and hippocampal-prefrontal network oscillations during the emergence of free exploration.

During free exploration, the emergence of patterned and sequential behavioral responses to an unknown environment reflects exploration traits and adaptation. However, the behavioral dynamics and neural substrates underlying the exploratory behavior remain poorly understood. We developed computational tools to quantify the exploratory behavior and performed in vivo electrophysiological recordings in a large arena in which mice made sequential excursions into unknown territory. Occupancy entropy was calculated to characterize the cumulative and moment-to-moment behavioral dynamics in explored and unexplored territories. Local field potential analysis revealed that the theta activity in the dorsal hippocampus (dHPC) was highly correlated with the occupancy entropy. Individual dHPC and prefrontal cortex (PFC) oscillatory activities could classify various aspects of free exploration. Initiation of exploration was accompanied by a coordinated decrease and increase in theta activity in PFC and dHPC, respectively. Our results indicate that dHPC and PFC work synergistically in shaping free exploration by modulating exploratory traits during emergence and visits to an unknown environment.

Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output.

Neural organoids have the potential to improve our understanding of human brain development and neurological disorders. However, it remains to be seen whether these tissues can model circuit formation with functional neuronal output. Here we have adapted air-liquid interface culture to cerebral organoids, leading to improved neuronal survival and axon outgrowth. The resulting thick axon tracts display various morphologies, including long-range projection within and away from the organoid, growth-cone turning, and decussation. Single-cell RNA sequencing reveals various cortical neuronal identities, and retrograde tracing demonstrates tract morphologies that match proper molecular identities. These cultures exhibit active neuronal networks, and subcortical projecting tracts can innervate mouse spinal cord explants and evoke contractions of adjacent muscle in a manner dependent on intact organoid-derived innervating tracts. Overall, these results reveal a remarkable self-organization of corticofugal and callosal tracts with a functional output, providing new opportunities to examine relevant aspects of human CNS development and disease.