Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.02.25.964965

Top-down Control of Inhibition Reshapes Neural Dynamics Giving Rise to a Diversity of Computations

Chen, Z.·Padmanabhan, K.
View original source ↗Export metadata ↓

Abstract

Growing evidence shows that top-down projections from excitatory neurons in higher brain areas selectively synapse onto local inhibitory interneurons in sensory systems. While this connectivity is conserved across sensory modalities, the role of this feedback in shaping the dynamics of local circuits, and the resultant computational benefits it provides remains poorly understood. Using rate models of neuronal firing in a network consisting of excitatory, inhibitory and top-down populations, we found that changes in the weight of feedback to inhibitory neurons generated diverse network dynamics and complex transitions between these dynamics. Additionally, modulation of the weight of top-down feedback supported a number of computations, including both pattern separation and oscillatory synchrony. A bifurcation analysis of the network identified a new mechanism by which gamma oscillations could be generated in a model of neural circuits, which we termed Top-down control of Inhibitory Neuron Gamma (TING). We identified the unique roles that top-down feedback of inhibition plays in shaping network dynamics and computation, and the ways in which these dynamics can be deployed to process sensory inputs. Significance StatementThe functional role of feedback projections, connecting excitatory neurons in higher brain areas to inhibitory neurons in primary sensory regions, remains a fundamental open question in neuroscience. Growing evidence suggests that this architecture is recapitulated across a diverse array of sensory systems, ranging from vision to olfaction. Using a rate model of top-down feedback onto inhibition, we found that changes in the weight of feedback support both pattern separation and oscillatory synchrony, including a mechanism by which top-down inputs could entrain gamma oscillations within local networks. These dual functions were accomplished via a codimension-2 bifurcation in the dynamical system. Our results highlight a key role for this top-down feedback, gating inhibition to facilitate often diametrically different local computations.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chen, Z., Padmanabhan, K.. 2020-02-26. Top-down Control of Inhibition Reshapes Neural Dynamics Giving Rise to a Diversity of Computations. https://doi.org/10.1101/2020.02.25.964965

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Novel Tau Interaction Partners as Potential Biomarkers and Therapeutic Targets in Neurodegenerative Diseases

Alzheimers disease is a progressive neurodegenerative disorder leading to cognitive decline and ultimately death. One of the main hallmarks of this disease is the accumulation of pathological tau protein into neurofibrillary tangles. To better understand these pathological mechanisms, it is essential to characterize the tau protein interactome in health and disease. In this study, we performed a yeast two-hybrid screening using a human brain cDNA library, from which we identified 15 novel tau-interacting proteins that bind to full-length human tau, or its fragments: the N-terminus, microtubule-binding domain, or C-terminus. We subsequently validated these novel interactions using in vitro co-immunoprecipitation and colocalization assays with both physiological and pathological tau isoforms. Furthermore, their interactions with the human tau protein were analyzed using surface plasmon resonance. Finally, an in silico interactome analysis of these newly discovered tau-binding partners revealed several additional interactors that can link them to downstream processes critical to neurodegenerative pathways Our findings offer fresh insights into tau biology and highlight novel targets for therapeutic intervention and biomarker development.

neuroscience↗
bioRxiv2026

Early visual cortex is not functionally necessary for temporal attention: A TMS study

Temporal attention enhances the selective processing of information at a specific point in time and improves perception. Previous neuroimaging studies investigating its neural mechanisms have either conflated temporal attention with temporal expectation or provided correlational evidence. Thus, whether early visual cortex is functionally necessary for temporal attention remains unknown. Here, we combined psychophysics with transcranial magnetic stimulation (TMS) to examine whether V1/V2 are functionally necessary and play a causal role in temporal attention. Observers performed an orientation-discrimination task in which two consecutive stimuli, T1 and T2, were presented in the periphery, preceded by a precue providing either valid or neutral temporal information. Double-pulse TMS was delivered under four conditions: at T1 (T1-TMS), at T2 (T2-TMS), at both T1 and T2 (both-TMS), or not at all (none-TMS), to assess its effects on temporal attention and the efficacy of the stimulation was verified by pupil size analysis. Behavioral results revealed robust temporal attention benefits on d', reaction time, and the Balanced Integration Score (BIS) across all four TMS conditions, indicating that the benefits of temporal attention were unaffected by occipital TMS. Furthermore, pupil dilation was largest in the both-TMS condition, followed by the T1-TMS and T2-TMS conditions, and smallest in the none-TMS condition, providing physiological verification of the stimulation protocol. Together, these findings reveal the first causal evidence that the early visual cortex is not functionally necessary for endogenous temporal attention.

neuroscience↗
bioRxiv2026

Disentanglement of persistent and dynamic neural substrates of working memory

Competing theories of working memory have alternatively emphasized the importance of persistent and dynamic substrates of this cognitive function. Here, we directly tested these theories by computationally isolating the contributions of persistent and dynamic activity to working memory. We analyzed neuronal population activity recordings in macaques doing match/non-match working memory tasks. We first extracted signatures of persistent and dynamic activity through cue-specific temporal means, temporal principal components, and correlations of activity patterns across task epochs. We then generated synthetic data constrained by these signatures, and decoded cue stimuli from these data, separately from persistent and non-persistent neurons. We found that high decoding performance arose from a nuanced interplay of persistent and dynamic activity. Specifically, we could decode stimuli at empirical or above-chance levels across all tasks only from persistent neurons, but only after constraining correlations of activity patterns across epochs. In this way, we showed distinct roles for persistent and dynamic neuronal activity that help to unify two competing theories of working memory. More broadly, we also advanced computational controlled experiments as a principled framework for adjudicating between competing models of neuronal population activity.

neuroscience↗