Miller Lab alumnus David Freedman and colleagues present a model that shows how categorical neural activity can develop through learning. As a result of top-down influences from decision neurons, categorical representations develop in neurons that show choice-correlated activity fluctuations. They test the model via recordings from parietal cortex.
-
Braunlich et al compared stimulus identity vs categorization tasks using fMRI in humans. They applied a Constrained Principal Components Analysis. They found evidence for two distinct frontoparietal networks. One that rapidly analyzes the stimuli and a second one that more slowly categorizes them.
-
Task Dependence of Visual and Category Representations in Prefrontal and Inferior Temporal Cortices
Jillian L. McKee, Maximilian Riesenhuber, Earl K. Miller, and David J. FreedmanVisual categorization is an essential perceptual and cognitive process for assigning behavioral significance to incoming stimuli. Categorization depends on sensory processing of stimulus features as well as flexible cognitive processing for classifying stimuli according to the current behavioral context. Neurophysiological studies suggest that the prefrontal cortex (PFC) and the inferior temporal cortex (ITC) are involved in visual shape categorization. However, their precise roles in the perceptual and cognitive aspects of the categorization process are unclear, as the two areas have not been directly compared during changing task contexts. To address this, we examined the impact of task relevance on categorization-related activity in PFC and ITC by recording from both areas as monkeys alternated between a shape categorization and passive viewing tasks. As monkeys viewed the same stimuli in both tasks, the impact of task relevance on encoding in each area could be compared. While both areas showed task-dependent modulations of neuronal activity, the patterns of results differed markedly. PFC, but not ITC, neurons showed a modest increase in firing rates when stimuli were task relevant. PFC also showed significantly stronger category selectivity during the task compared with passive viewing, while task-dependent modulations of category selectivity in ITC were weak and occurred with a long latency. Finally, both areas showed an enhancement of stimulus selectivity during the task compared with passive viewing. Together, this suggests that the ITC and PFC show differing degrees of task-dependent flexibility and are preferentially involved in the perceptual and cognitive aspects of the categorization process, respectively.
-
We (Antoulatos and Miller) show increased beta-band synchrony between (but not within) the prefrontal cortex and striatum during category learning. By the time the categories were fully learned, the beta synchrony became category-specific. That is, different patterns of prefrontal cortex-striatum recording sites showed increased beta synchrony for one category or the other. Thus, category learning may depend on formation of oscillatory synchrony-aided functional circuits between the prefrontal cortex and striatum. Further, causality analysis suggested that the striatum exerted a greater influence on the prefrontal cortex than the other way around. This supports models positing that the basal ganglia “train” the prefrontal cortex (Pasupathy and Miller, 2005; Seger and Miller, 2010).
Antzoulatos, E.G. and Miller, E.K. (2014) “Increases in functional connectivity between the prefrontal cortex and striatum during category learning.” Neuron, 83:216-225 DOI: http://dx.doi.org/10.1016/j.neuron.2014.05.005 View PDF
For further reading:
Pasupathy, A. and Miller, E.K. (2005) Different time courses for learning-related activity in the prefrontal cortex and striatum. Nature, 433:873-876. View PDF »
Antzoulatos,E.G. and Miller, E.K. (2011) Differences between neural activity in prefrontal cortex and striatum during learning of novel, abstract categories. Neuron. 71(2): 243-249. View PDF »
Seger, C.A. and Miller, E.K. (2010) Category learning in the brain. Annual Review of Neuroscience, Vol. 33: 203-219. View PDF »
-
Roy et al show that the activity of neurons in the prefrontal cortex (pFC) are linked to categorical decisions. Monkeys were trained to categorize a set of computer-generated images as “cats” vs “dogs”. Then, they were shown ambiguous images were centered on a category boundary, that is, they were a mix of 50% of cats and dogs and therefore had no category information. The monkeys guessed at their category membership. Activity to the same ambiguous image differed significantly, depending on the monkey’s decision about the image’s category. Thus, pFC activity reflects categorical decisions.
-
Van der Linden et al used computer generated images to study categorization in the human brain. They found that the frontal cortex showed sensitivity to the features diagnostic for the categories, which is consistent with results from animal studies at the neuron level.
-
Jack Gallant and crew used FMRI to examine scene processing in the human brain. They found that scenes activated many regions of anterior visual cortex and that the scene categories capture the co-occurrence of the objects that compose the scenes.
-
Max Riesenhuber and colleagues used EEG to examine the time course of shape and category signals in the human brain. Neural adaptation for category changes was seen in frontal cortex and then subsequently in temporal cortex. This supports the hypothesis that shape categories are formed by shape signals from temporal cortex that converge and form explicit category representations in frontal cortex. A late category signal in temporal cortex is consistent with category signals feeding back from frontal to temporal cortex.
-
A Neuron Preview for Miller Lab graduate student Simon Kornblith’s paper on a network for scene processing:
Scene Areas in Humans and Macaques by Epstein and JulianHere’s the original post on Simon’s paper and a link to it:
A Network For Scene Processing -
Pannunzi et al propose a model of visual category learning in which bottom-up sensory inputs to the inferior temporal cortex are sculpted by top-down inputs from the prefrontal cortex (PFC). The PFC improves signal to noise by enhancing the category-relevant features of the stimuli.
Miller Lab work cited:
Freedman, D.J., Riesenhuber, M., Poggio, T., and Miller, E.K. (2001) Categorical representation of visual stimuli in the primate prefrontal cortex. Science, 291:312-316. View PDF »Freedman, D.J., Riesenhuber, M., Poggio, T., and Miller, E.K (2003) A comparison of primate prefrontal and inferior temporal cortices during visual categorization. Journal of Neuroscience, 23(12):5235-5246. View PDF »
Meyers, E.M., Freedman, D.J., Kreiman, G., Miller, E.K., and Poggio, T. (2008) Dynamic population coding of category information in the inferior temporal cortex and prefrontal cortex. Journal of Neurophysiology. 100:1407-1419. View PDF »
Muhammad, R., Wallis, J.D., and Miller, E.K. (2006) A comparison of abstract rules in the prefrontal cortex, premotor cortex, the inferior temporal cortex and the striatum. Journal of Cognitive Neuroscience, 18: 974-989. View PDF »
Seger, C.A. and Miller, E.K. (2010) Category learning in the brain. Annual Review of Neuroscience, Vol. 33: 203-219. View PDF »