Biology subjects

Parsa, M.

Publications and source records attributed to Parsa, M..

4 recordsLinked to original sources

bioRxiv2025

Cholinergic dynamics in the septo-hippocampal system provide phasic multiplexed signals for spatial novelty and correlate with behavioral states

In the hippocampal formation, cholinergic modulation from the medial septum/diagonal band of Broca (MSDB) is known to correlate with the speed of an animals movements at sub-second timescales and also supports spatial memory formation. Yet, the extent to which sub-second cholinergic dynamics, if at all, align with transient behavioral and cognitive states supporting the encoding of novel spatial information remains unknown. In this study, we used fiber photometry to record the temporal dynamics in the population activity of septo-hippocampal cholinergic neurons at sub-second resolution during a hippocampus-dependent object location memory task using ChAT-Cre mice. Using a general linear model, we quantified the extent to which cholinergic dynamics were explained by changes in movement speed, behavioral states such as locomotion, grooming, and rearing, and hippocampus-dependent cognitive states such as recognizing a novel location of a familiar object. The data show that cholinergic dynamics contain a multiplexed code of fast and slow signals i) coding for the logarithm of movement speed at sub-second timescales, ii) providing a phasic spatial novelty signal during the brief periods of exploring a novel object location, and iii) coding for environmental novelty at a seconds-long timescale. Furthermore, behavioral event-related phasic cholinergic activity around the onset and offset of the behavior demonstrates that fast cholinergic transients help facilitate a switch in cognitive and behavioral state before and during the onset of behavior. These findings enhance understanding of the mechanisms by which cholinergic modulation contributes to the coding of movement speed and encoding of novel spatial information.

animal behavior and cognition↗

bioRxiv2022

Biological connectomes as a representation for the architecture of artificial neural networks

AO_SCPLOWBSTRACTC_SCPLOWGrand efforts in neuroscience are working toward mapping the connectomes of many new species, including the near completion of the Drosophila melanogaster. It is important to ask whether these models could benefit artificial intelligence. In this work we ask two fundamental questions: (1) where and when biological connectomes can provide use in machine learning, (2) which design principles are necessary for extracting a good representation of the connectome. Toward this end, we translate the motor circuit of the C. Elegans nematode into artificial neu-ral networks at varying levels of biophysical realism and evaluate the outcome of training these networks on motor and non-motor behavioral tasks. We demonstrate that biophysical realism need not be upheld to attain the advantages of using biological circuits. We also establish that, even if the exact wiring diagram is not retained, the architectural statistics provide a valuable prior. Finally, we show that while the C. Elegans locomotion circuit provides a powerful inductive bias on locomotion problems, its structure may hinder performance on tasks unrelated to locomotion such as visual classification problems.

neuroscience↗

bioRxiv2022

IRIS: Integrated Retinal Functionality in Image Sensors

Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in the past decade, has not been implemented in image sensor technology. We present a technology-circuit co-design solution that implements two motion computations occurring at the output of the retina that could have wide applications for vision based decision making in dynamic environments. Our simulations on Globalfoundries 22nm technology node show that, by taking advantage of the recent advances in semiconductor chip stacking technology, the proposed retina-inspired circuits can be fabricated on image sensing platforms in existing semiconductor foundries. Integrated Retinal Functionality in Image Sensors (IRIS) technology could drive advances in machine vision applications that demand robust, high-speed, energy-efficient and low-bandwidth real-time decision making.

bioengineering↗

bioRxiv2021

Overexpression of Zinc finger (GpZF) promotes drought tolerance in grass pea (Lathyrus sativus)

The genes encoding Cys2/His2-type zinc finger proteins constitute a large family in higher plants consisting of a family of plant transcription factors. GpZF encodes a Cys2/His2-type zinc finger protein. The purposes of this study are to elucidate further the functions of a novel zinc finger transcription factor in the grass pea (GpZF) gene involved in the drought stress response in the grass pea (Lathyrus sativus) and to investigate its biochemical and physiological parameters under stress conditions. GpZF was expressed in grass pea. Relative gene expression analysis showed the GpZF gene in independent transgenic lines was more under drought mild and severe treatments (50% and 25% field capacity-FC). Furthermore, overexpression of this gene in grass pea results in more relative water content, free proline, and soluble sugars than the wild-type (WT) plants under 50% and 25% FC stresses. Moreover, in 25% FC, the independent transgenic lines revealed an increase in survival rates and dry weight than the WT plants. GpZF thus implies the positive role in drought stress tolerance in Lathyrus sativus. In conclusion, the transgenic grass pea plants generated in this study could be used to farm arid areas. HighlightGpZF is a positive regulator in drought stress tolerance in grass pea.

molecular biology↗