Biology subjects

Mosher, C. P.

Publications and source records attributed to Mosher, C. P..

6 recordsLinked to original sources

bioRxiv2023

Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

neuroscience↗

bioRxiv2021

Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation

While experience unfolds continuously, memories are organized as a set of discrete events that bind together the "where", "when", and "what" of episodic memory. This segmentation of continuous experience is thought to be facilitated by the detection of salient environmental or cognitive events. However, the underlying neural mechanisms and how such segmentation shapes episodic memory representations remain unclear. We recorded from single neurons in the human medial temporal lobe while subjects watched videos with different types of embedded boundaries and were subsequently evaluated for memories of the video contents. Here we show neurons that signal the presence of cognitive boundaries between subevents from the same episode and neurons that detect the abstract separation between different episodes. The firing rate and spike timing of these boundary-responsive neurons were predictive of later memory retrieval accuracy. At the population level, abrupt neural state changes following boundaries predicted enhanced memory strength but impaired order memory, capturing the behavioral tradeoff subjects exhibited when recalling episodic content versus temporal order. Successful retrieval was associated with reinstatement of the neural state present following boundaries, indicating that boundaries structure memory search. These findings reveal a neuronal substrate for detecting cognitive boundaries and show that cognitive boundary signals facilitate the mnemonic organization of continuous experience as a set of discrete episodic events.

neuroscience↗

bioRxiv2020

Inferring brain-wide interactions using data-constrained recurrent neural network models

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets.

neuroscience↗

bioRxiv2020

Temporally-specific sequences of neural activity across interconnected corticolimbic structures during reward anticipation

Functional neuroimaging studies indicate that interconnected parts of the subcallosal anterior cingulate cortex (ACC), striatum, and amygdala play a fundamental role in affect in health and disease. Yet, while the patterns of neural activity engaged in striatum and amygdala during affective processing are well established, especially during reward anticipation, little is known about subcallosal ACC. Here we recorded neural activity in non-human primate subcallosal ACC and compared this to interconnected parts of basolateral amygdala and rostromedial striatum while macaque monkeys performed reward-based tasks. Applying multiple analysis approaches, we found that neurons in subcallosal ACC and rostromedial striatum preferentially signal anticipated reward using short bursts of activity that form temporally specific patterns. By contrast, basolateral amygdala uses a mixture of both temporally specific and more sustained patterns of activity to signal anticipated reward. Thus, dynamic patterns of neural activity across populations of neurons are engaged in affect, especially in subcallosal ACC. HIGHLIGHTSO_LISustained changes in neural activity signal anticipated reward in basolateral amygdala C_LIO_LITemporally specific patterns signal anticipated reward in all areas recorded C_LIO_LINeurons exhibit more punctate encoding when tasks become more complex C_LIO_LITemporally specific patterns of neural activity signal different anticipated rewards in BLA C_LI

neuroscience↗

bioRxiv2020

Distinct roles of dorsal and ventral subthalamic neurons in action selection and cancellation

The subthalamic nucleus (STN) supports action selection by inhibiting all motor programs except the desired one. Recent evidence suggests that STN can also cancel an already selected action when goals change, a key aspect of cognitive control. However, there is little neurophysiological evidence for a dissociation between selecting and cancelling actions in the human STN. We recorded single neurons in the STN of humans performing a stop-signal task. Movement-related neurons suppressed their activity during successful stopping whereas stop-signal neurons activated at low-latencies regardless of behavioral outcome. In contrast, STN and motor-cortical beta-bursting occurred only later in the stopping process. Task-related neuronal properties varied by recording location from dorsolateral movement to ventromedial stop-signal tuning. Therefore, action selection and cancellation coexist in STN but are anatomically segregated. These results show that human ventromedial STN neurons carry fast stop-related signals suitable for implementing cognitive control.

neuroscience↗

bioRxiv2017

Amygdala Input Differentially Influences Prefrontal Local Field Potential And Single Neuron Encoding Of Reward-Based Decisions

Reward-guided behaviors require functional interaction between amygdala, orbital (OFC), and medial (MFC) divisions of prefrontal cortex, but the neural mechanisms underlying these interactions are unclear. Here, we used a decoding approach to analyze local field potentials (LFPs) recorded from OFC and MFC of monkeys engaged in a stimulus-choice task, before and after excitotoxic amygdala lesions. Whereas OFC LFP responses were strongly modulated by the amount of reward associated with each stimulus, MFC responses best represented which stimulus subjects decided to choose. This was counter to what we observed in the level of single neurons where their activity was closely associated with the value of the stimuli presented on each trial. After lesions of the amygdala, stimulus-reward value and choice encoding were reduced in OFC and MFC, respectively. However, while the lesion-induced decrease in OFC LFP encoding of stimulus-reward value mirrored changes in single neuron activity, reduced choice encoding in MFC LFPs was distinct from changes in single neuron activity. Thus, LFPs and single neurons represent different information required for decision-making in OFC and MFC. At the circuit-level, amygdala input to these two areas play a distinct role in stimulus-reward encoding in OFC and choice encoding in MFC.

neuroscience↗