Biology subjects

Martinez-Trujillo, J.

Publications and source records attributed to Martinez-Trujillo, J..

7 recordsLinked to original sources

bioRxiv2026

An age-preserving neuronal iSpheroid platform for modeling human aging and Alzheimer disease

Aging is the strongest risk factor for Alzheimer disease (AD), yet existing human neuronal models either erase age-associated features during reprogramming or fail to recapitulate three-dimensional organization of human neuronal tissue. Here, we establish directly induced neuronal spheroids (iSpheroids), a scalable three-dimensional platform generated by direct conversion of primary fibroblasts without pluripotency. iSpheroids generate long-lived, electrophysiologically active neurons from young, unimpaired aged, and sporadic AD donors while preserving donor-specific epigenetic age. Single-nucleus RNA sequencing revealed approximately 96% of cells acquired a neuronal identity and were distributed across multiple neuronal states, including a diversity of neurons. The platform supports incorporation of astrocytes and microglia and generation from non-human primate fibroblasts. AD iSpheroids spontaneously recapitulated neuronal degeneration, amyloid-beta; accumulation, progressive Tau pathology, and metabolic dysfunction. Integrated proteomic, metabolomic, and lipidomic profiling distinguished physiological aging from AD and revealed disease-associated metabolic remodeling. Oxaliplatin shifted AD iSpheroids toward oxidative metabolism, whereas a multi-compound screen identified trametinib as a modulator of inflammatory and age-associated programs.

neuroscience↗

bioRxiv2025

Visual exploration drives Hippocampal SWR rates during 3D spatial navigation in the freely moving marmoset

Spatial navigation requires the brain to continuously sample the external world while evaluating internal representations of space. In rodents, this process unfolds through alternating periods of locomotion and pauses. During pauses, hippocampal sharp-wave ripples (SWRs) rates increase, likely reflecting the broadcast of spatial memories that guide navigation. Whether similar dynamics govern navigation in primates remains unknown. Here, we recorded hippocampal activity in freely moving marmosets navigating a 3D maze. Like rodents, marmosets alternated between locomotion and pauses. However, pauses were long and showed an increase in SWR rates relative to locomotion. SWRs were most prominent when animals maintained stable head orientations toward rewarded locations and were reduced during rapid exploratory head movements. SWR rates further increased when spatial memories were used to guide navigation. Our findings reveal a phylogenetically conserved motif linking behavioral states during spatial navigation to hippocampal SWR dynamics across mammals and show how primate visual specializations have adapted this motif to support vision-guided navigation. Significance StatementOur results reveal a phylogenetically conserved hippocampal navigation motif that has persisted despite major evolutionary changes in mammalian sensory ecology. Across species, navigation alternates between external exploration and internal evaluation, with SWRs marking periods of memory-guided computation. However, primate evolution reshaped the behavioral expression of this motif by coupling it to active visual sampling, gaze control, and foveal inspection of landmarks. Thus, evolution appears to have preserved a core hippocampal algorithm for navigation while adapting its sensory inputs and behavioral context to the demands of diurnal, vision-guided life.

animal behavior and cognition↗

bioRxiv2025

Spatially and non-spatially tuned hippocampal neurons are linear perceptual and nonlinear memory encoders

The hippocampus has long been regarded as a neural map of physical space, with its neurons categorized as spatially or non-spatially tuned according to their response selectivity. However, growing evidence suggests that this dichotomy oversimplifies the complex roles hippocampal neurons play in integrating spatial and non-spatial information. Through computational modeling and in-vivo electrophysiology in macaques, we show that neurons classified as spatially tuned primarily encode linear combinations of immediate behaviorally relevant factors, while those labeled as non-spatially tuned rely on nonlinear mechanisms to integrate temporally distant experiences. Furthermore, our findings reveal a temporal gradient in the primate CA3 region, where spatial selectivity diminishes as neurons encode increasingly distant past events. Finally, using artificial neural networks, we demonstrate that nonlinear recurrent connections are crucial for capturing the response dynamics of non-spatially tuned neurons, particularly those encoding memory-related information. These findings challenge the traditional dichotomy of spatial versus non-spatial representations and instead suggest a continuum of linear and nonlinear computations that underpin hippocampal function. This framework provides new insights into how the hippocampus bridges perception and memory, informing on its role in episodic memory, spatial navigation, and associative learning.

neuroscience↗

bioRxiv2024

Task-specific topographical maps of neural activity in the primate lateral prefrontal cortex

Neurons in the primate lateral prefrontal cortex (LPFC) flexibly adapt their activity to support a wide range of cognitive tasks. Whether and how the topography of LPFC neural activity changes as a function of task is unclear. In the present study, we address this issue by characterizing the functional topography of LPFC neural activity in awake behaving macaques performing three distinct cognitive tasks. We recorded from chronically implanted multi-electrode arrays and show that the topography of LPFC activity is stable within a task, but adaptive across tasks. The topography of neural activity exhibits a spatial scale compatible with prior anatomical tracing work on a!erent LPFC inputs. Our findings show that LPFC maps of neural population activity are stable for a specific task, providing robust neural codes that support task specialization. Moreover, the variability in functional topographies across tasks indicates activity landscapes can adapt, providing flexibility to LPFC neural codes.

neuroscience↗

bioRxiv2021

Feature-based attention induces surround suppression during the perception of visual motion

Feature-based attention prioritizes the processing of the attended feature while strongly suppressing the processing of nearby ones. This creates a non-linearity or attentional suppressive surround predicted by the Selective Tuning model of visual attention. However, previously reported effects of feature-based attention on neuronal responses are linear, e.g., feature-similarity gain. Here, we investigated this apparent contradiction by neurophysiological and psychophysical approaches. Responses of motion direction-selective neurons in area MT/MST of monkeys were recorded during a motion task. When attention was allocated to a stimulus moving in the neurons preferred direction response tuning curves showed its minimum for directions 60-90 degrees away from the preferred direction, an attentional suppressive surround. This effect was modeled via the interaction of two Gaussian fields representing excitatory narrowly-tuned and inhibitory widely-tuned inputs into a neuron, with feature-based attention predominantly increasing the gain of inhibitory inputs. We further showed using a motion repulsion paradigm in humans that feature-based attention produces a similar non-linearity on motion discrimination performance. Our results link the gain modulation of neuronal inputs and tuning curves examined through the feature-similarity gain lens to the attentional impact on neural population responses predicted by the Selective Tuning model, providing a unified framework for the documented effects of feature-based attention on neuronal responses and behavior.

neuroscience↗

bioRxiv2019

Spontaneous Traveling Cortical Waves Gate Perception in Awake Behaving Primates

Perceptual sensitivity varies from moment to moment. One potential source of variability is spontaneous fluctuations in cortical activity that can travel as a wave. Spontaneous traveling waves have been reported during anesthesia, but questioned as to whether they are relevant to waking cortical function. Using newly developed analytic techniques, we find spontaneous waves of activity in extrastriate visual cortex of awake marmosets (Callithrix jacchus). In monkeys trained to detect faint visual targets, the timing and position of spontaneous traveling waves, prior to target onset, predict the magnitude of evoked activity and the likelihood of detection. In contrast, spatially disorganized fluctuations of neural activity are much less predictive. These results reveal an important role for spontaneous traveling waves in sensory processing through modulating neural and perceptual sensitivity.\n\nOne Sentence SummaryFluctuations in cortical activity often travel as waves, shape incoming sensory information, and affect conscious perception.

neuroscience↗

bioRxiv2019

Identifying the most influential features of neural population responses for information encoding and behavior

Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding the neural code. Statistical features such as tuning properties, individual and shared response variability, and global activity modulations could all affect the amount of information encoded and modulate behavioral performance. We show that two features in particular affect information: the modulation of population responses across conditions and the projection of the inverse population variability along the modulation axis. We demonstrate that fluctuations of these two quantities are correlated with fluctuations of behavioral performance in various tasks and brain regions. In contrast, fluctuations in mean correlations among neurons and global activity have negligible or inconsistent effects on the amount of information encoded and behavioral performance. Our results are consistent with predictions of a model that optimally decodes population responses, which suggests that in our behavioral tasks the readout of information is near-optimal.

neuroscience↗