For us to answer the question: "What is right there in front of us."
We have to reference the EYES themselves and the part of the
brain that is located so as to function to make sense of the visual
data in such a position that it is this that is the cause of the visual
itself.So ,just as there are "CONCEPTS" in the PREFRONTAL,
there are also VISUAL DATA in the PREFRONTAL.
So concepts and vision go together.
https://www.sciencedirect.com/science/article/pii/S095943881730140X
We are rapidly approaching a comprehensive understanding of the neural mechanisms behind object recognition. How we use this knowledge of the visual world to plan and act is comparatively mysterious. To fill this gap, we must understand how visual representations are transformed within cognitive regions, and how these cognitive representations of visual information act back upon earlier sensory representations. Here, we summarize our current understanding of visual representation in inferotemporal cortex (IT) and prefrontal cortex (PFC), and the interactions between them. We emphasize the apparent consistency of visual representation in PFC across tasks, and suggest ways to leverage advances in our understanding of high-level vision to better understand cognitive processing.
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Figure 2. Topography and visual representation in PFC. (a) Boundaries of anatomically defined lateral prefrontal regions (derived from [80]), with approximate locations of FEF [30], VPA [28••], and face patches PA and PL [34] overlaid. (b) Performance of a classifier trained to classify the identity of the sample stimulus in a delayed match to sample task based on LPFC unit activity, during passive fixation before training (blue) and during task execution after training (red), adapted from [35••]. Shaded regions indicate 1 se in decoding accuracy if different neurons were used. Bars at bottom indicate time points when decoding accuracy significantly exceeded chance (P < 0.005, permutation test). (c) Selectivity of neurons to different stimuli in VPA, FEF, VPS, and IT, sorted by response magnitude and normalized by the response to the best stimulus, adapted from [28••]. Since FEF exhibited no significant stimulus selectivity, it is shown for comparison purposes only. Error bars are sem. (d) Spatial tuning of units in VPA, FEF, VPS, and IT with well-defined extrafoveal receptive field, adapted from [28••]. Activity is normalized by the response at the receptive field center and plotted as a function of distance from this center. Error bars are sem. (e1) Model of selection and integration by recurrent dynamics, adapted from [40]. Averaged responses of a recurrent neural network model to a brief (1 ms) color pulse when the task requires action selection based on integration of color (‘cued context,’ turquoise) or motion (‘uncued context,’ orange), projected into the two-dimensional subspace spanned by the direction of the pulse and the locally computed line attractor. In both the cued and uncued contexts, the initial pulse has a substantial projection onto the line attractor, but the dynamics following the pulse (dots: 3 ms intervals) ensure that color is integrated only when it is cued. (e2) A simulated neuron responding to a brief pulse of color and motion (black bar), following the dynamics in (e1). The fact that stimulus representation is context independent is indicated by the fact that the orange and blue curves overlap during the stimulus presentation period. Simulated firing rates reflect the sum of responses to two simultaneous pulses, one corresponding to a stimulus from the cued context, and one corresponding to a stimulus from the uncued context, each of which may be of the neuron's preferred color/motion direction or of the neuron's nonpreferred color/motion direction. Note that the neuron's transient response to a combination of a preferred and nonpreferred stimulus is largely independent of which is cued, but the decay following the pulse is context-dependent. The neuron's selectivity is such that the maximum contributions along the axes spanned by the pulse direction and line attractor are equal when both the cued and uncued stimulus are preferred; the preferred direction along the line attractor is congruent with the cell's stimulus preferences; and the response to a nonpreferred stimulus is 10 times smaller than that for a preferred stimulus. (b) is reprinted from Proc Natl Acad Sci U S A, vol. 109, E.M. Meyers, X.-L. Qi, and C. Constantinidis, Incorporation of new information into prefrontal cortical activity after learning working memory tasks, p. 4651–4656 (2014). (c) and (d) are reprinted from Neuron, vol. 88, N.P. Bichot, M.T. Heard, E.M. DeGennaro, and R. Desimone, A source for feature-based attention in the prefrontal cortex, p. 832–844, Copyright 2015, with permission from Elsevier. (e) is adapted by permission from Macmillan Publishers Ltd: Nature, vol. 503, V. Mante, D. Sussillo, K.V. Shenoy, and W.T. Newsome, Context-dependent computation by recurrent dynamics in prefrontal cortex, p. 78–84, Copyright 2013.
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