Biology subjects

Jensen, C. M.

Publications and source records attributed to Jensen, C. M..

5 recordsLinked to original sources

bioRxiv2025

Structured experience shapes strategy learning and neural dynamics in the medial entorhinal cortex

Animals can solve new, complex tasks by reusing and adapting what theyve learned before. This kind of flexibility depends not just on having prior experience, but on how that experience was structured in the first place. The design of early training curriculum is especially important: poorly structured experiences can hinder abstraction and limit generalization, while carefully structured training promotes more flexible and adaptive behavior. Yet, the neural mechanisms supporting this process remain unclear. To investigate how early training shapes learning we first trained recurrent neural networks (RNNs) on variants of an odor-timing task previously used to study complex timing behavior in mice. We then tested the RNN predictions on how previous experience affects generalization using behavioral and electrophysiological recordings in mice trained on the same task using staged training sequences. RNNs and mice trained without well-structured early experience developed rigid strategies and made repeated errors. In contrast, those given more balanced early training were better able to generalize and showed similar neural activity patterns that reflected the tasks underlying temporal structure. Using dynamical systems approaches, we reveal a mechanism for this effect: networks trained with appropriately structured curricula developed distinct dynamical motifs that support the correct abstractions when complexity was increased. Networks that lacked early training or received remedial curricula developed single fixed-point solutions that failed to generalize beyond the training stimuli. Together, these findings demonstrate that it is not just the presence of prior experience, but its structure, that governs how flexible and generalizable knowledge emerges in both biological systems and computational models.

neuroscience↗

bioRxiv2024

Oddball evoked deviant responses reflect complex context dependent expectations in mouse V1

Evoked responses in the mouse primary visual cortex can be modulated by the temporal context in which visual inputs are presented. Oddball stimuli embedded in a sequence of regularly repeated visual elements have been shown to drive relatively large deviant responses, a finding that is generally consistent with the theory that cortical circuits implement a form of predictive coding. These results can be confounded by short-term adaptation effects, however, that make interpretation difficult. Here we use various forms of the oddball paradigm to disentangle temporal and ordinal components of the deviant response, showing that it is a complex phenomenon affected by temporal structure, ordinal expectation, and event frequency. Specifically, we use visually evoked potentials to show that deviant responses occur over a large range of time, lead to long-term plasticity in some cases, cannot be explained by a simple adaptation model, scale with predictability, and are modulated by violations of both first and second-order sequential expectations. Significance StatementVisual experience and temporal context can modulate evoked responses in mouse V1. There remains disagreement about whether this reflects predictive coding in visual circuits and if visual mismatched negativity, which has important cross-over implications for human clinical work, constitutes evidence supporting this theory or simple neural adaptation. This work strongly supports the former interpretation by demonstrating complex experience-dependent deviant responses that cannot be easily explained by a simple adaptation model. We use statistically rigorous analysis of the local field potential to show that oddball evoked deviance signals reflect relative timing, event frequency, 1st and 2nd order sequence expectations and scale as a function of event probability.

neuroscience↗

bioRxiv2022

Sex and estrous cycle affect experience-dependent plasticity in mouse primary visual cortex

Sex hormones can affect cellular physiology and modulate synaptic plasticity, but it is not always clear whether or how sex-dependent differences identified in vitro express themselves as functional dimorphisms in the brain. Historically, most experimental neuroscience has been conducted using only male animals and the literature is largely mute about whether including female mice in will introduce variability due to inherent sex differences or endogenous estrous cycles. Though this is beginning to change following an NIH directive that sex should be included as a factor in vertebrate research, the lack of information raises practical issues around how to design experimental controls and apply existing knowledge to more heterogeneous populations. Various lines of research suggest that visual processing can be affected by sex and estrous cycle stage. For these reasons, we performed a series of in vivo electrophysiological experiments to characterize baseline visual function and experience-dependent plasticity in the primary visual cortex (V1) of male and female mice. We find that sex and estrous stage have no statistically significant effect on baseline acuity measurements, but that both sex and estrous stage have can modulate two mechanistically distinct forms of experience dependent cortical plasticity. We also demonstrate that resulting variability can be largely controlled with appropriate normalizations. These findings suggest that V1 plasticity can be used for mechanistic studies focusing on how sex hormones effect experience dependent plasticity in the mammalian cortex.

neuroscience↗

bioRxiv2022

M2 Receptors are required for spatiotemporal sequence learning in mouse primary visual cortex

Acetylcholine is a neurotransmitter that plays a variety of roles in the central nervous system. It was previously shown that blocking muscarinic receptors with a non-selective antagonist prevents a form of experience-dependent plasticity termed "spatiotemporal sequence learning" in the mouse primary visual cortex (V1). Muscarinic signaling is a complex process involving the combined activities of five different G-protein coupled receptors, M1-M5, all of which are expressed in the murine brain but differ from each other functionally and in anatomical localization. Here we present electrophysiological evidence that M2, but not M1, receptors are required for spatiotemporal sequence learning in mouse V1. We show in male mice that M2 is highly expressed in the neuropil in V1, especially in thalamorecipient layer 4, and co-localizes with the soma in a subset of somatostatin expressing neurons in deep layers. We also show that expression of M2 receptors is higher in the monocular region of V1 than it is in the binocular region, but that the amount of experience-dependent sequence potentiation is similar in both regions, and that blocking muscarinic signaling after visual stimulation does not prevent plasticity. This work establishes a new functional role for M2-type receptors in processing temporal information and demonstrates that monocular circuits are modified by experience in a manner similar to binocular circuits. Significance StatementMuscarinic acetylcholine receptors are required for multiple forms of plasticity in the brain and support perceptual functions, but the precise role of the five subtypes (M1-M5) are unclear. Here we show that the M2 receptor is specifically required to encode experience-dependent representations of spatiotemporal relationships in both monocular and binocular regions of mouse V1. Muscarinic receptors are metabotropic in nature and have complex downstream signaling effects that can be difficult to isolate experimentally. In addition to identifying a novel functional role for M2 receptors, this work also suggests that V1 circuits can be used as an in-vivo model to understand the relationship between cholinergic signaling and coding of complex temporal relationships in cortical circuits.

neuroscience↗

bioRxiv2022

Expectation violations produce error signals in mouse V1

Repeated exposure to visual sequences changes the form of evoked activity in the primary visual cortex (V1). Predictive coding theory provides a potential explanation for this, namely that plasticity shapes cortical circuits to encode spatiotemporal predictions and that subsequent responses are modulated by the degree to which actual inputs match these expectations. Here we use a recently developed statistical modeling technique called Model-Based Targeted Dimensionality Reduction (MbTDR) to study visually-evoked dynamics in mouse V1 in context of a previously described experimental paradigm called "sequence learning". We report that evoked spiking activity changed significantly with training, in a manner generally consistent with the predictive coding framework. Neural responses to expected stimuli were suppressed in a late window (100-150ms) after stimulus onset following training, while responses to novel stimuli were not. Omitting predictable stimuli led to increased firing at the expected time of stimulus onset, but only in trained mice. Substituting a novel stimulus for a familiar one led to changes in firing that persisted for at least 300ms. In addition, we show that spiking data can be used to accurately decode time within the sequence. Our findings are consistent with the idea that plasticity in early visual circuits is involved in coding spatiotemporal information.

neuroscience↗