Update README.md

Author: AishwaryaHB

README.md

@@ -10,7 +10,7 @@
   Yet, we remain short of a framework that definitively explains the structure-function relationships of this fundamental neuroanatomical motif.
   To better understand how physical substrates of cortical circuitry facilitate their neuronal dynamics, we employ a computational approach using recurrent neural networks and representational analyses.
   We examine the differences manifested by the inclusion and exclusion of biologically-motivated inter-areal laminar connections on the computational roles of different neuronal populations in the microcircuit of hierarchically-related areas, throughout learning.
-  Our findings show that the presence of feedback connections correlates with the functional modularization of cortical populations in different layers, and provides the microcircuit with a natural inductive bias to differentiate expected and unexpected inputs at initialization.
+  Our findings show that the presence of feedback connections correlates with the functional modularization of cortical populations in different layers, and provides the microcircuit with a natural inductive bias to differentiate expected and unexpected inputs at initialization, which we justify mathematically.
   Furthermore, when testing the effects of training the microcircuit and its variants with a predictive-coding inspired strategy, we find that doing so helps better encode noisy stimuli in areas of the cortex that receive feedback,
   all of which combine to suggest evidence for a predictive-coding mechanism serving as an intrinsic operative logic in the cortex.
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