@article {153341, title = {Discriminating neural ensemble patterns through dendritic computations in randomly connected feedforward networks.}, journal = {Elife}, volume = {13}, year = {2025}, month = {2025 Jan 24}, abstract = {

Co-active or temporally ordered neural ensembles are a signature of salient sensory, motor, and cognitive events. Local convergence of such patterned activity as synaptic clusters on dendrites could help single neurons harness the potential of dendritic nonlinearities to decode neural activity patterns. We combined theory and simulations to assess the likelihood of whether projections from neural ensembles could converge onto synaptic clusters even in networks with random connectivity. Using rat hippocampal and cortical network statistics, we show that clustered convergence of axons from three to four different co-active ensembles is likely even in randomly connected networks, leading to representation of arbitrary input combinations in at least 10 target neurons in a 100,000 population. In the presence of larger ensembles, spatiotemporally ordered convergence of three to five axons from temporally ordered ensembles is also likely. These active clusters result in higher neuronal activation in the presence of strong dendritic nonlinearities and low background activity. We mathematically and computationally demonstrate a tight interplay between network connectivity, spatiotemporal scales of subcellular electrical and chemical mechanisms, dendritic nonlinearities, and uncorrelated background activity. We suggest that dendritic clustered and sequence computation is pervasive, but its expression as somatic selectivity requires confluence of physiology, background activity, and connectomics.

}, keywords = {Animals, Axons, Computer Simulation, Dendrites, Hippocampus, Models, Neurological, Nerve Net, Neurons, Rats, Synapses}, issn = {2050-084X}, doi = {10.7554/eLife.100664}, author = {Bhanu Priya Somashekar and Upinder Singh Bhalla} } @article {161981, title = {Timing of Delamination of Inner Ear Neurons Specifies Their Topography and Target Innervation.}, journal = {J Comp Neurol}, volume = {533}, year = {2025}, month = {2025 Nov}, pages = {e70103}, abstract = {

The neurons of the inner ear delaminate from a sensorineurogenic epithelium in the ventral part of the otocyst. Delaminated neuroblasts then condense to form the acoustico-vestibular ganglion (AVG). As they differentiate, the neurons connect mechanosensory hair cells (HCs) of the inner ear with their targets in the hindbrain in a precise topographical manner. However, it is unclear how or when positional identities of neurons are specified within the AVG, such that topographical information from HCs is maintained into the auditory centers of the brain. Here, we find that the time of delamination from the otocyst correlates with neuroblast position in the ganglion. Using markers for neuronal differentiation, we find that the ganglion differentiates from a dorsal to ventral wave. Neurons that differentiate first innervate the vestibular apparatus, including the lagena and the proximal regions of the BP. Using sequential somatic cell labeling, we find that the central projection also follows a similar dependency on delamination order. Our studies show that the time of delamination of otic neuroblasts presages their target innervation choice and fiber positions within the developing eighth cranial nerve. We suggest that temporal information specifies the spatial identities during early inner ear neuron development.

}, keywords = {Animals, Cell Differentiation, Chick Embryo, Ear, Inner, Neurogenesis, Neurons, Time Factors}, issn = {1096-9861}, doi = {10.1002/cne.70103}, author = {Saini, Surjit Singh and Ladher, Raj K} } @article {139055, title = {Predictive neural computations in the cerebellum contribute to motor planning and faster behavioral responses in larval zebrafish.}, journal = {Sci Adv}, volume = {10}, year = {2024}, month = {2024 Jan 05}, pages = {eadi6470}, abstract = {

The ability to predict the future based on past experience lies at the core of the brain{\textquoteright}s ability to adapt behavior. However, the neural mechanisms that participate in generating and updating predictions are not clearly understood. Further, the evolutionary antecedents and the prevalence of predictive processing among vertebrates are even less explored. Here, we show evidence of predictive processing via the involvement of cerebellar circuits in larval zebrafish. We presented stereotyped optic flow stimuli to larval zebrafish to evoke swims and discovered that lesioning the cerebellum abolished prediction-dependent modulation of swim latency. When expectations of optic flow direction did not match with reality, error signals arrive at Purkinje cells via the olivary climbing fibers, whereas granule cells and Purkinje cells encode signals of expectation. Strong neural representations of expectation correlate with faster swim responses and vice versa. In sum, our results show evidence for predictive processing in nonmammalian vertebrates with the involvement of cerebellum, an evolutionarily conserved brain structure.

}, keywords = {Animals, Cerebellum, Larva, Neurons, Purkinje Cells, Zebrafish}, issn = {2375-2548}, doi = {10.1126/sciadv.adi6470}, author = {Narayanan, Sriram and Varma, Aalok and Thirumalai, Vatsala} } @article {118433, title = {Face neurons and super-normal stimuli:A window into visual processing.}, journal = {J Biosci}, volume = {47}, year = {2022}, month = {2022}, keywords = {Neurons, Pattern Recognition, Visual, Photic Stimulation, Visual Perception}, issn = {0973-7138}, author = {Bhalla, U S} } @article {1037, title = {An Interglomerular Circuit Gates Glomerular Output and Implements Gain Control in the Mouse Olfactory Bulb.}, journal = {Neuron}, volume = {87}, year = {2015}, month = {2015 Jul 1}, pages = {193-207}, abstract = {

Odors elicit distributed activation of glomeruli in the olfactory bulb (OB). Crosstalk between co-active glomeruli has been proposed to perform a variety of computations, facilitating efficient extraction of sensory information by the cortex. Dopaminergic/GABAergic cells in the OB, which can be identified by their expression of the dopamine transporter (DAT), provide the earliest opportunity for such crosstalk. Here we show in mice that DAT+ cells carry concentration-dependent odor signals and broadcast focal glomerular inputs throughout the OB to cause suppression of mitral/tufted (M/T) cell firing, an effect that is mediated by the external tufted (ET) cells coupled to DAT+ cells via chemical and electrical synapses. We find that DAT+ cells implement gain control and decorrelate odor representations in the M/T cell population. Our results further indicate that ET cells are gatekeepers of glomerular output and prime determinants of M/T responsiveness.

}, keywords = {Animals, Dopamine Plasma Membrane Transport Proteins, Dopaminergic Neurons, GABAergic Neurons, Mice, Neurons, Odors, Olfactory Bulb, Synaptic Transmission}, issn = {1097-4199}, doi = {10.1016/j.neuron.2015.06.019}, author = {Banerjee, Arkarup and Marbach, Fred and Anselmi, Francesca and Koh, Matthew S and Davis, Martin B and Garcia da Silva, Pedro and Delevich, Kristen and Oyibo, Hassana K and Gupta, Priyanka and Li, Bo and Albeanu, Dinu F} } @article {907, title = {Neuronal encoding of the switch from specific to generalized fear.}, journal = {Nat Neurosci}, volume = {18}, year = {2015}, month = {2015 Jan}, pages = {112-20}, abstract = {

Fear memories are crucial for survival. However, excessive generalization of such memories, characterized by a failure to discriminate dangerous from safe stimuli, is common in anxiety disorders. Neuronal encoding of the transition from cue-specific to generalized fear is poorly understood. We identified distinct neuronal populations in the lateral amygdala (LA) of rats that signaled generalized versus cue-specific associations and determined how their distributions switched during fear generalization. Notably, the same LA neurons that were cue specific before the behavioral shift to generalized fear lost their specificity afterwards, thereby tilting the balance of activity toward a greater proportion of generalizing neurons. Neuronal activity in the LA, but not the auditory cortex, was necessary for fear generalization. Furthermore, targeted activation of cAMP-PKA signaling in the LA increased neuronal excitability of LA neurons and led to generalized fear. These results provide a cellular basis in the amygdala for the alteration of emotional states from normal to pathological fear.

}, keywords = {Animals, Auditory Cortex, Conditioning, Operant, Cyclic AMP-Dependent Protein Kinases, Discrimination (Psychology), Fear, GABA Agonists, Generalization (Psychology), Male, Mental Recall, Neuronal Plasticity, Neurons, Rats, Rats, Sprague-Dawley, Signal Transduction}, issn = {1546-1726}, doi = {10.1038/nn.3888}, author = {Ghosh, Supriya and Chattarji, Sumantra} } @article {857, title = {Olfactory bulb coding of odors, mixtures and sniffs is a linear sum of odor time profiles.}, journal = {Nat Neurosci}, volume = {18}, year = {2015}, month = {2015 Feb}, pages = {272-81}, abstract = {

The olfactory system receives intermittent and fluctuating inputs arising from dispersion of odor plumes and active sampling by the animal. Previous work has suggested that the olfactory transduction machinery and excitatory-inhibitory olfactory bulb circuitry generate nonlinear population trajectories of neuronal activity that differ across odorants. Here we show that individual mitral/tufted (M/T) cells sum inputs linearly across odors and time. By decoupling odor sampling from respiration in anesthetized rats, we show that M/T cell responses to arbitrary odor waveforms and mixtures are well described by odor-specific impulse responses convolved with the odorant{\textquoteright}s temporal profile. The same impulse responses convolved with the respiratory airflow predict the classical respiration-locked firing of olfactory bulb neurons and several other reported response properties of M/T cells. These results show that the olfactory bulb linearly processes fluctuating odor inputs, thereby simplifying downstream decoding of stimulus identity and temporal dynamics.

}, keywords = {Animals, Female, Models, Neurological, Neurons, Odors, Olfactory Bulb, Olfactory Perception, Olfactory Receptor Neurons, Rats, Rats, Wistar, Respiration, Time Factors}, issn = {1546-1726}, doi = {10.1038/nn.3913}, author = {Gupta, Priyanka and Albeanu, Dinu F and Bhalla, Upinder S} } @article {1011, title = {Sloppiness in spontaneously active neuronal networks.}, journal = {J Neurosci}, volume = {35}, year = {2015}, month = {2015 Jun 3}, pages = {8480-92}, abstract = {

Various plasticity mechanisms, including experience-dependent, spontaneous, as well as homeostatic ones, continuously remodel neural circuits. Yet, despite fluctuations in the properties of single neurons and synapses, the behavior and function of neuronal assemblies are generally found to be very stable over time. This raises the important question of how plasticity is coordinated across the network. To address this, we investigated the stability of network activity in cultured rat hippocampal neurons recorded with high-density multielectrode arrays over several days. We used parametric models to characterize multineuron activity patterns and analyzed their sensitivity to changes. We found that the models exhibited sloppiness, a property where the model behavior is insensitive to changes in many parameter combinations, but very sensitive to a few. The activity of neurons with sloppy parameters showed faster and larger fluctuations than the activity of a small subset of neurons associated with sensitive parameters. Furthermore, parameter sensitivity was highly correlated with firing rates. Finally, we tested our observations from cell cultures on an in vivo recording from monkey visual cortex and we confirm that spontaneous cortical activity also shows hallmarks of sloppy behavior and firing rate dependence. Our findings suggest that a small subnetwork of highly active and stable neurons supports group stability, and that this endows neuronal networks with the flexibility to continuously remodel without compromising stability and function.

}, keywords = {Action Potentials, Animals, Brain, Cells, Cultured, Electric Stimulation, Embryo, Mammalian, Entropy, Models, Neurological, Nerve Net, Neural Pathways, Neurons, Rats, Synapses, Visual Cortex}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.4421-14.2015}, author = {Panas, Dagmara and Amin, Hayder and Maccione, Alessandro and Muthmann, Oliver and van Rossum, Mark and Berdondini, Luca and Hennig, Matthias H} }