scholarly journals Zero-shot neural decoding of visual categories without prior exemplars

2019 ◽  
Author(s):  
Thomas P. O’Connell ◽  
Marvin M. Chun ◽  
Gabriel Kreiman
Keyword(s):  
Neural Network ◽  
Visual Cortex ◽  
Neural Activity ◽  
Deep Neural Network ◽  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Neural Decoding ◽  
Neural Responses ◽  
Prior Training ◽  
Single Category

AbstractDecoding information from neural responses in visual cortex demonstrates interpolation across repetitions or exemplars. Is it possible to decode novel categories from neural activity without any prior training on activity from those categories? We built zero-shot neural decoders by mapping responses from macaque inferior temporal cortex onto a deep neural network. The resulting models correctly interpreted responses to novel categories, even extrapolating from a single category.

scholarly journals Multiple states in ongoing neural activity in the rat visual cortex

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256791
Author(s):  
Daichi Konno ◽  
Shinji Nishimoto ◽  
Takafumi Suzuki ◽  
Yuji Ikegaya ◽  
Nobuyoshi Matsumoto
Keyword(s):  
Visual Cortex ◽  
Neural Activity ◽  
Activity Patterns ◽  
Electrode Array ◽  
Nonlinear Dimensionality Reduction ◽  
Neural Responses ◽  
Spontaneous Neural Activity ◽  
Custom Made ◽  
Visual Cortices ◽  
Freely Behaving

The brain continuously produces internal activity in the absence of afferently salient sensory input. Spontaneous neural activity is intrinsically defined by circuit structures and associated with the mode of information processing and behavioral responses. However, the spatiotemporal dynamics of spontaneous activity in the visual cortices of behaving animals remain almost elusive. Using a custom-made electrode array, we recorded 32-site electrocorticograms in the primary and secondary visual cortex of freely behaving rats and determined the propagation patterns of spontaneous neural activity. Nonlinear dimensionality reduction and unsupervised clustering revealed multiple discrete states of the activity patterns. The activity remained stable in one state and suddenly jumped to another state. The diversity and dynamics of the internally switching cortical states would imply flexibility of neural responses to various external inputs.

A Comparison of Abstract Rules in the Prefrontal Cortex, Premotor Cortex, Inferior Temporal Cortex, and Striatum

2006 ◽  
Vol 18 (6) ◽  
pp. 974-989 ◽  
Author(s):  
Rahmat Muhammad ◽  
Jonathan D. Wallis ◽  
Earl K. Miller
Keyword(s):  
Prefrontal Cortex ◽  
Neural Activity ◽  
Premotor Cortex ◽  
Temporal Cortex ◽  
Dorsal Striatum ◽  
Behavioral Responses ◽  
Inferior Temporal Cortex ◽  
Perceptual Information ◽  
Lateral Prefrontal Cortex

The ability to use abstract rules or principles allows behavior to generalize from specific circumstances. We have previously shown that such rules are encoded in the lateral prefrontal cortex (PFC) and premotor cortex (PMC). Here, we extend these investigations to two other areas directly connected with the PFC and the PMC, the inferior temporal cortex (ITC) and the dorsal striatum (STR). Monkeys were trained to use two abstract rules: “same” or “different”. They had to either hold or release a lever, depending on whether two successively presented pictures were the same or different, and depending on which rule was in effect. The rules and the behavioral responses were reflected most strongly and, on average, tended to be earlier in the PMC followed by the PFC and then the STR; few neurons in the ITC reflected the rules or the actions. By contrast, perceptual information (the identity of the pictures used as sample and test stimuli) was encoded more strongly and earlier in the ITC, followed by the PFC; they had weak, if any, effects on neural activity in the PMC and STR. These findings are discussed in the context of the anatomy and posited functions of these areas.

scholarly journals Attractor dynamics in networks with learning rules inferred from in vivo data

2017 ◽  
Author(s):  
Ulises Pereira ◽  
Nicolas Brunel
Keyword(s):  
Neural Network ◽  
Hebbian Learning ◽  
Temporal Cortex ◽  
Memory Storage ◽  
Inferior Temporal Cortex ◽  
Association Cortex ◽  
Visual Responses ◽  
Neural Network Models ◽  
Firing Rates ◽  
Learning Rules

AbstractThe attractor neural network scenario is a popular scenario for memory storage in association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both learning rules and distribution of stored patterns are inferred from distributions of visual responses for novel and familiar images in inferior temporal cortex (ITC). Unlike classical attractor neural network models, our model exhibits graded activity in retrieval states, with distributions of firing rates that are close to lognormal. Inferred learning rules are close to maximizing the number of stored patterns within a family of unsupervised Hebbian learning rules, suggesting learning rules in ITC are optimized to store a large number of attractor states. Finally, we show that there exists two types of retrieval states: one in which firing rates are constant in time, another in which firing rates fluctuate chaotically.

scholarly journals Reduced visual and frontal cortex activation during visual working memory in grapheme-colour synaesthetes relative to young and older adults

2018 ◽  
Author(s):  
Gaby Pfeifer ◽  
Jamie Ward ◽  
Natasha Sigala
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Visual Cortex ◽  
Visual Working Memory ◽  
Temporal Cortex ◽  
Region Of Interest ◽  
Inferior Temporal Cortex ◽  
Long Term Memory ◽  
Sensory Recruitment ◽  
Recruitment Model

AbstractThe sensory recruitment model envisages visual working memory (VWM) as an emergent property that is encoded and maintained in sensory (visual) regions. The model implies that enhanced sensory-perceptual functions, as in synaesthesia, entail a dedicated VWM-system, showing reduced visual cortex activity as a result of neural specificity. By contrast, sensory-perceptual decline, as in old age, is expected to show enhanced visual cortex activity as a result of neural broadening. To test this model, young grapheme-colour synaesthetes, older adults and young controls engaged in a delayed pair-associative retrieval and a delayed matching-to-sample task, consisting of achromatic fractal stimuli that do not induce synaesthesia. While a previous analysis of this dataset (Pfeifer et al., 2016) has focused on cued retrieval and recognition of pair-associates (i.e. long-term memory), the current study focuses on visual working memory and considers, for the first time, the crucial delay period in which no visual stimuli are present, but working memory processes are engaged. Participants were trained to criterion and demonstrated comparable behavioural performance on VWM tasks. Whole-brain and region-of-interest-analyses revealed significantly lower activity in synaesthetes’ middle frontal gyrus and visual regions (cuneus, inferior temporal cortex) respectively, suggesting greater neural efficiency relative to young and older adults in both tasks. The results support the sensory recruitment model and can explain age and individual WM-differences based on neural specificity in visual cortex.

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