A computational model of fMRI activity in the intraparietal sulcus that supports visual working memory

Abstract

A computational model was developed to explain a pattern of results of fMRI activation in the intraparietal sulcus (IPS) supporting visual working memory for multiobject scenes. The model is based on the hypothesis that dendrites of excitatory neurons are major computational elements in the cortical circuit. Dendrites enable formation of a competitive queue that exhibits a gradient of activity values for nodes encoding different objects, and this pattern is stored in working memory. In the model, brain imaging data are interpreted as a consequence of blood flow arising from dendritic processing. Computer simulations showed that the model successfully simulates data showing the involvement of inferior IPS in object individuation and spatial grouping through representation of objects' locations in space, along with the involvement of superior IPS in object identification through representation of a set of objects' features. The model exhibits a capacity limit due to the limited dynamic range for nodes and the operation of lateral inhibition among them. The capacity limit is fixed in the inferior IPS regardless of the objects' complexity, due to the normalization of lateral inhibition, and variable in the superior IPS, due to the different encoding demands for simple and complex shapes. Systematic variation in the strength of self-excitation enables an understanding of the individual differences in working memory capacity. The model offers several testable predictions regarding the neural basis of visual working memory.

Resonant Dynamics of Grounded Cognition: Explanation of Behavioral and Neuroimaging Data Using the ART Neural Network

“…One hypothesis is that the fMRI represents total synaptic activity because transmitter synthesis and release are energy-demanding processes (Horwitz et al, 1999 ; Arbib et al, 2000 ). Another possibility is that dendrites are responsible for generating the fMRI signal (Lauritzen, 2005 ; Domijan, 2011 ). Under these interpretations, the fMRI signal reflects processing pathways rather than neural outputs.…”

A Neurocomputational account of the role of contour facilitation in brightness perception

“…It consists of the excitatory and inhibitory node in a specific synaptic arrangement. The excitatory node is assumed to be a multi-compartment unit with dendrites as independent computational subunits (Häusser and Mel, 2003 ; Spruston and Kath, 2004 ; London and Häusser, 2005 ; Spruston, 2008 ; Domijan, 2011 ). The excitatory node receives feedforward input and recurrent excitation from other excitatory nodes encoding the same stimulus property (e.g., contour orientation) at different network locations.…”

Systems-level decoding reveals the cognitive and behavioral profile of the human intraparietal sulcus

“…Activations within IPS were also found during memory routines. These include encoding and maintaining of visual information in visual short-term memory tasks (Xu and Chun, 2006 ; Harrison et al, 2010 ; Offen et al, 2010 ; Domijan, 2011 ; Xu and Jeong, 2015 ; Markett et al, 2018 ; Sheremata et al, 2018 ; Duma et al, 2019 ; Praß and de Haan, 2019 ; Lefco et al, 2020 ) as well as familiarity based memory retrieval (Frithsen and Miller, 2014 ; Hutchinson et al, 2014 ; Rosen et al, 2015 , 2018 ; Chen et al, 2017 ). Further, the IPS engages in visuomotor coordination such as grasping, action observation and control of hand and eye movements (Corbetta et al, 1998 ; Shikata et al, 2001 ; Grefkes and Fink, 2005 ; Villarreal et al, 2008 ; Cavina-Pratesi et al, 2018 ).…”