Biology subjects

Solomon, S. G.

Publications and source records attributed to Solomon, S. G..

5 recordsLinked to original sources

bioRxiv2024

Loom response in mouse superior colliculus depends on sensorimotor context

Visual motion is produced both by an organisms movement through the world, and by objects moving in the world such as potential predators. Choosing appropriate behaviour therefore requires organisms to distinguish these sources of visual motion. Here we asked how mice integrate self-movement with looming visual motion by combining virtual reality and neural recordings from superior colliculus (SC), a brain area important in visually-guided approach and avoidance behaviours. We first measured locomotion behaviour and neural activity while animals approached an object in virtual reality, and while the same object loomed at them. In both cases, vision dominated activity in superficial layers (SCs), while locomotion had more influence on activity in intermediate layers (SCim). In addition, animals instinctively slowed their locomotion when nearing the object, or when the object neared them. To directly test animals ability to distinguish self-from object motion we replayed the visual images generated during object approach. Locomotion behaviour often changed during replay, showing animals are able to establish if visual motion is matched to their self-movement. Further, decoders trained on locomotion behaviour, or on population activity in SC, particularly in SCim, were able to reliably discriminate epochs of replay and object approach. We conclude that both mouse behaviour and SC activity encode whether looming visual motion arises from self-or object movement, with implications for understanding sensorimotor coordination in dynamic environments. HighlightsO_LIWe recorded from superficial (SCs) and intermediate (SCim) superior colliculus in VR C_LIO_LIVision dominated SCs, while SCim was modulated by both vision and locomotion C_LIO_LIMice altered behaviour when visual experience did not match that expected from their locomotion C_LIO_LIPopulation activity differed between matched and unmatched visual experiences, particularly in SCim C_LI

neuroscience↗

bioRxiv2021

Altered low frequency brain rhythms precede changes in gamma power during tauopathy

Alzheimers disease and other dementias are associated with disruptions of electrophysiological brain activity, including low frequency and gamma rhythms. Many of these dementias are also associated with the malfunction of the membrane associated protein tau. Tauopathy disrupts neuronal function and the stability of synapses and is a key driver of neurodegeneration. Here we ask how brain rhythms are affected by tauopathy, at different stages of its progression. We performed local field potential recordings from visual cortex of rTg4510 and control animals at early stages of neurodegeneration (5 months) and at a more advanced stage where pathology is evident (8 months). We measured brain activity in the presence or absence of external visual stimulation, and while monitoring pupil diameter and locomotion to establish animal behavioural states. At 5 months, before substantial pathology, we found an increase in low frequency rhythms during resting state in tauopathic animals. This was because tauopathic animals entered intermittent periods of increased neural synchronisation, where activity across a wide band of low frequencies was strongly correlated. At 8 months, when the degeneration was more advanced, the increased synchronisation and low frequency power was accompanied by a reduction in power in the gamma range, with diverse effects across different components of the gamma rhythm. Our results indicate that slower rhythms are impaired earlier than gamma rhythms in tauopathy, suggesting that electrophysiological measurements can indicate both the presence and progression of tauopathic degeneration.

neuroscience↗

bioRxiv2021

Brief stimuli cast a long-term trace in visual cortex

Visual processing is strongly influenced by the recent stimulus history - a phenomenon termed adaptation. Prominent theories cast adaptation as a consequence of optimized encoding of visual information, by exploiting the temporal statistics of the world. However, this would require the visual system to track the history of individual briefly experienced events, within a stream of visual input, to build up statistical representations over longer timescales. Here, using an openly available dataset from the Allen Brain Observatory, we show that neurons in the early visual cortex of the mouse indeed maintain long-term traces of individual past stimuli that persist despite the presentation of several intervening stimuli, leading to long-term and stimulus-specific adaptation over dozens of seconds. Long-term adaptation was selectively expressed in cortical, but not in thalamic neurons, which only showed short-term adaptation. Early visual cortex thus maintains concurrent stimulusspecific memory traces of past input, enabling the visual system to build up a statistical representation of the world to optimize the encoding of new information in a changing environment. Significance StatementIn the natural world, previous sensory input is predictive of current input over multi-second timescales. The visual system could exploit these predictabilities by adapting current visual processing to the long-term history of visual input. However, it is unclear whether the visual system can track the history of individual briefly experienced images, within a stream of input, to build up statistical representations over such long timescales. Here, we show that neurons in early visual cortex of the mouse brain exhibit remarkably long-term adaptation to brief stimuli, persisting over dozens of seconds, and despite the presentation of several intervening stimuli. The visual cortex thus maintains long-term traces of individual briefly experienced past images, enabling the formation of statistical representations over extended timescales.

neuroscience↗

bioRxiv2020

Plasticity in visual cortex is disrupted in a mouse model of tauopathy and neurodegeneration

Neurodegeneration is a hallmark of many dementias and is thought to underlie a progressive impairment of neural plasticity. How neurodegeneration affects plasticity in neural circuits is not known. We therefore characterised the impact of tau-driven neurodegeneration on plasticity in the visual system, where normal function is well understood. We studied a very simple form of visual plasticity that allowed us to track both long timescales (across days) and shorter timescales (over minutes). We recorded the local field potential in the primary visual cortex of rTg4510 transgenic mice, a mouse model of tauopathy, while animals were repeatedly exposed to the same stimulus over the course of 9 days. We studied animals at early stages of neurodegeneration (5 months old) and at a more advanced stage where pathology is evident (8 months). We found that both short- and long-term visual plasticity were already disrupted at early stages of neurodegeneration, and were further reduced in older animals, such that it was abolished in mice expressing the mutant tau. Additionally, we found that visually evoked behaviours were disrupted in both younger and older mice expressing the mutant tau. Our results show that visual cortical plasticity and visually evoked behaviours are disrupted in the rTg4510 model of tauopathy, even at early stages of neurodegeneration. This simple measure of neural plasticity may help understand how neurodegeneration disrupts neural circuits, and offers a translatable platform for detection and tracking of the disease. HighlightsO_LIVisual plasticity is disrupted at early stages of neurodegeneration in rTg4510 mice C_LIO_LIVisual plasticity is reduced in older animals, particularly during neurodegeneration C_LIO_LIInstinctive visual behaviours are reduced in neurodegeneration C_LIO_LIShort-term visual plasticity is reduced in neurodegeneration C_LI

neuroscience↗

bioRxiv2020

BonVision - an open-source software to create and control visual environments

Real-time rendering of closed-loop visual environments is necessary for next-generation understanding of brain function and behaviour, but is prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks and communication with behavioural and physiological measurement and manipulation devices.

neuroscience↗